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10 Simple & 6 Exponential Moving Averages (w/ 18 day,week,month)* This is for the trader who wants tons of moving averages on their chart from one indicator * Using the options, you should be able ot turn off some of them if the screen is too noisy for you * You should also be able to change colors and thickness of the bars * The thicker bars are for longer term averages * This version is similar to my other script except it adds the 18 day, 18 week, and 18 Month SMa * I added them after watching ira Epstein's YouTube videos * Let me know if there are any bugs or things that need to be change
مؤشر Pine Script®
من ‎ryanman0‎
4
ICT Order Block Identifier [Eˣ]📦 Order Block Identifier - Free Indicator Overview The Order Block Identifier automatically detects and displays institutional order blocks on your charts - the exact zones where banks, hedge funds, and market makers place their orders. Based on ICT (Inner Circle Trader) concepts, this indicator helps you trade alongside smart money by identifying where institutions are likely to defend their positions and where price often finds support or resistance. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎯 What This Indicator Does Detects Order Blocks: • 🟢 Bullish Order Blocks (OB+) - Last bearish candle before strong bullish move • 🔴 Bearish Order Blocks (OB-) - Last bullish candle before strong bearish move • Automatically identifies institutional buying/selling zones • Tracks up to 30 order blocks simultaneously • Works on all timeframes and instruments Smart Features: • Auto-Timeframe Adjustment - Optimizes detection for 1min to Weekly charts • Active Block Highlighting - Shows which OB price is approaching (🎯) • Mitigation Tracking - Knows when blocks are "used" and no longer valid • ATR-Based Detection - Adapts to each instrument's volatility • Strength Filtering - Choose Low/Medium/High to control sensitivity Visual Display: • Clean boxes extending from order block to current price • Color-coded: Green (bullish), Red (bearish), Gray (mitigated) • OB+ / OB- labels for quick identification • Active blocks highlighted with 🎯 emoji • Distance indicator showing how far price is from nearest OB Statistics Panel: • Count of active bullish and bearish order blocks • Market bias based on OB balance • Distance to nearest order block • Real-time status updates ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📚 Understanding Order Blocks What Are Order Blocks? Order blocks are the "footprints" left behind by institutional traders (banks, hedge funds, market makers) when they enter large positions. Because institutions can't fill massive orders at once without moving the market, they: 1. Place orders gradually over time 2. Leave zones where their buy/sell orders are concentrated 3. Defend these zones when price returns 4. Create reliable support and resistance levels The ICT Concept: Developed by Michael Huddleston (Inner Circle Trader), order block theory states that: • The last opposite-colored candle before a strong move contains institutional orders • Price often returns to test these zones before continuing • These zones act as strong support (bullish OB) or resistance (bearish OB) • Smart money defends their positions at these levels Why Order Blocks Work: • Unfilled Orders: Institutions may still have pending orders in the block • Position Defense: They protect their entries by adding to positions • Stop Placement: Retail stops cluster near these zones (liquidity for institutions) • Market Structure: Price respects these levels due to order flow dynamics ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🟢 Bullish Order Blocks Explained How They Form: 1. Price is consolidating or declining 2. Institutions begin accumulating (buying) 3. A strong bullish move erupts 4. The last bearish candle before this move = Bullish Order Block 5. This candle represents where institutions were buying aggressively Why The Last Bearish Candle? • Institutions absorbed all selling pressure at this level • Their buy orders filled as price was declining • When price returns, they defend this zone with more buying • It becomes a demand zone / support level Trading Bullish Order Blocks: Setup: • Wait for price to retrace back to bullish OB (green box) • Look for rejection/reversal pattern (pin bar, engulfing, etc.) • Enter long when price bounces from the OB zone • Stop loss: Below the order block • Target: Recent high or opposite order block Best Scenarios: • OB aligns with other support (trendline, fibonacci, round number) • First touch of OB (unmitigated) has highest probability • Occurs during high-volume sessions (London/NY) • Trend is bullish on higher timeframe Example Trade: • Bullish OB forms at $50,000 (last red candle before rally) • Price rallies to $52,000 then retraces • Price drops back to $50,100 (touching OB) • Bullish pin bar forms on the OB • Enter long at $50,200, stop at $49,800 • Target: $52,000+ (previous high) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🔴 Bearish Order Blocks Explained How They Form: 1. Price is consolidating or rising 2. Institutions begin distributing (selling) 3. A strong bearish move erupts 4. The last bullish candle before this move = Bearish Order Block 5. This candle represents where institutions were selling aggressively Why The Last Bullish Candle? • Institutions absorbed all buying pressure at this level • Their sell orders filled as price was rising • When price returns, they defend this zone with more selling • It becomes a supply zone / resistance level Trading Bearish Order Blocks: Setup: • Wait for price to retrace back to bearish OB (red box) • Look for rejection/reversal pattern (shooting star, bearish engulfing) • Enter short when price rejects from the OB zone • Stop loss: Above the order block • Target: Recent low or opposite order block Best Scenarios: • OB aligns with other resistance (trendline, fibonacci, round number) • First touch of OB (unmitigated) has highest probability • Occurs during high-volume sessions (London/NY) • Trend is bearish on higher timeframe Example Trade: • Bearish OB forms at $48,000 (last green candle before drop) • Price drops to $46,000 then retraces • Price rallies back to $47,900 (touching OB) • Bearish engulfing forms at the OB • Enter short at $47,800, stop at $48,200 • Target: $46,000- (previous low) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 How To Use This Indicator Strategy 1: Order Block Retest (Classic) Best For: Swing trading, capturing reversals Timeframes: 15min, 1H, 4H, Daily Win Rate: 60-70% (first touch) Entry Rules: 1. Identify unmitigated order block (bright color, not gray) 2. Wait for price to return to the OB zone 3. Look for price action confirmation: • Bullish OB: Pin bar, bullish engulfing, hammer • Bearish OB: Shooting star, bearish engulfing, doji 4. Enter in the direction of the OB 5. Stop loss: Beyond the opposite side of OB (20-30 pips) 6. Target: 2-3R or opposite OB Example: • Bullish OB at $100-$102 • Price drops to $101.50 (enters OB) • Bullish pin bar forms with low at $100.80 • Enter long at $102 (OB high), stop at $99.50 • Risk: $2.50, Target: $107.50 (3R) Strategy 2: Break & Retest Best For: Trend trading, breakout confirmation Timeframes: 5min, 15min, 1H Win Rate: 65-75% Entry Rules: 1. Price breaks through an order block 2. Wait for pullback to the broken OB 3. The OB now acts as support (if broken up) or resistance (if broken down) 4. Enter when price respects the flipped OB 5. Stop: Inside the OB zone 6. Target: Next OB or structure level Why It Works: Broken OBs flip polarity - support becomes resistance and vice versa Strategy 3: Multi-Timeframe Confirmation Best For: High-probability setups Timeframes: Combine 1H + 4H or 15min + 1H Win Rate: 70-80% Entry Rules: 1. Identify order block on higher timeframe (4H or Daily) 2. Switch to lower timeframe (1H or 15min) 3. Wait for lower TF order block to form within higher TF OB 4. Trade the lower TF OB in direction of higher TF OB 5. Stop: Below lower TF OB 6. Target: Edge of higher TF OB or beyond Why It Works: Alignment across timeframes = institutional consensus Strategy 4: Order Block to Order Block Best For: Range trading, swing entries Timeframes: 1H, 4H Win Rate: 55-65% Entry Rules: 1. Identify both bullish OB below and bearish OB above 2. Price is ranging between these OBs 3. Enter long at bullish OB, target bearish OB 4. Enter short at bearish OB, target bullish OB 5. Stop: Beyond the trading OB 6. Exit at opposite OB Why It Works: Price moves from one institutional zone to another Strategy 5: Mitigation Fade Best For: Aggressive scalping Timeframes: 5min, 15min Win Rate: 50-60% (higher risk) Entry Rules: 1. Price approaches an order block 2. Instead of bouncing, price breaks through (mitigates it) 3. Enter immediately in direction of breakout 4. Stop: Back inside the mitigated OB 5. Quick target: 1-1.5R Why It Works: When OB fails, it often leads to strong continuation ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚙️ Settings Explained Core Settings Auto-Adjust for Timeframe (Default: ON) • Automatically optimizes detection for current chart timeframe • 1min: 3 bars lookback • 5min: 4 bars lookback • 15min: 5 bars lookback • 1H: 6 bars lookback • 4H: 8 bars lookback • Daily+: 10-12 bars lookback • Recommended: Keep ON for best results Manual Detection Length (Default: 5) • Only used when Auto-Adjust is OFF • Number of bars to look back for the "last opposite candle" • Lower (2-4): More sensitive, more blocks, more noise • Higher (6-10): Less sensitive, fewer blocks, higher quality • Recommended: Use Auto-Adjust instead Display Settings Show Bullish/Bearish Order Blocks • Toggle each type on/off independently • Customize colors for each OB type • Tip: Match colors to your chart theme Max Order Blocks to Display (Default: 10) • Limits how many OBs are shown at once • Lower (5-8): Cleaner chart, only recent blocks • Higher (15-30): More historical context • Recommended: 8-12 for most trading Show Order Block Labels (Default: ON) • Displays "OB+" and "OB-" text on blocks • Shows 🎯 on active (nearest) block • Turn OFF for minimal chart appearance • Recommended: Keep ON for clarity Extend Blocks (bars) (Default: 50) • How far to extend OB boxes to the right • Lower (20-30): Shorter boxes, less clutter • Higher (100+): Longer boxes, easier to see • Blocks auto-extend until mitigated or limit reached • Recommended: 40-60 bars Filters Block Strength Filter (Default: Medium) • Controls how strong a move must be to create an OB • Low: 0.5x ATR move required - Many blocks, more noise • Medium: 1x ATR move required - Balanced quality/quantity • High: 1.5x ATR move required - Only strongest institutional moves • Recommended for beginners: High • Recommended for experienced: Medium • Recommended for scalpers: Low Min Block Size % (Default: 0.1) • Minimum size of OB as percentage of price • Filters out tiny, insignificant blocks • Crypto: 0.1-0.3% • Forex: 0.05-0.15% • Stocks: 0.1-0.5% • Adjust based on instrument volatility Advanced Settings Show Mitigated Blocks (Default: OFF) • When ON: Shows gray boxes for "used" order blocks • When OFF: Blocks disappear after mitigation • Use ON: For learning and analysis • Use OFF: For clean, active trading Highlight Active Block (Default: ON) • Highlights the nearest order block to current price • Active block shown with 🎯 emoji and brighter color • Helps focus on most relevant trading opportunity • Recommended: Keep ON ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📱 Info Panel Guide Bullish OB Count • Number of active (unmitigated) bullish order blocks • Higher number = More support zones below price • Multiple bullish OBs = Strong demand structure Bearish OB Count • Number of active (unmitigated) bearish order blocks • Higher number = More resistance zones above price • Multiple bearish OBs = Strong supply structure Bias Indicator • ⬆ Bullish: More bullish OBs than bearish (demand > supply) • ⬇ Bearish: More bearish OBs than bullish (supply > demand) • ↔ Neutral: Equal OBs on both sides • Trade in direction of bias for higher probability Near Indicator • Shows which OB price is closest to • Displays distance as percentage • Example: "Bull OB 0.85%" = Bullish OB is 0.85% below current price • Watch for "Near" alerts to time entries ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📱 Alert Setup This indicator includes 4 alert types: 1. Price Entering Bullish OB • Fires when price touches a bullish order block • Action: Watch for bounce/reversal pattern • High-probability long setup developing 2. Price Entering Bearish OB • Fires when price touches a bearish order block • Action: Watch for rejection/reversal pattern • High-probability short setup developing 3. New Bullish OB Detected • Fires when a new bullish order block forms • Action: Mark the zone for future retest • New demand zone identified 4. New Bearish OB Detected • Fires when a new bearish order block forms • Action: Mark the zone for future retest • New supply zone identified To Set Up Alerts: 1. Click "Alert" button (clock icon) 2. Select "Order Block Identifier" 3. Choose your alert condition 4. Configure notification method 5. Click "Create" Pro Tip: Set "Price Entering" alerts to catch trading opportunities in real-time ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💎 Pro Tips & Best Practices ✅ DO: • First touch is best - Unmitigated OBs have highest win rate (60-70%) • Wait for confirmation - Don't buy/sell just because price touched OB • Use multiple timeframes - Higher TF OBs are stronger than lower TF • Combine with structure - OB + trendline/support = high probability • Trade with the bias - More bullish OBs = favor longs • Respect mitigation - Once OB is mitigated, it's less reliable • Use proper stop loss - Always place stops beyond the OB zone • Consider session timing - OBs work best during London/NY sessions ⚠️ DON'T: • Don't blindly buy/sell at OBs - Wait for confirmation • Don't ignore mitigation - Gray blocks are much weaker • Don't trade every OB - Quality over quantity • Don't fight strong trends - OBs can be run through in strong momentum • Don't use alone - Combine with price action, support/resistance • Don't expect 100% win rate - Even best OBs fail sometimes (30-40% of time) • Don't overtrade - Wait for A+ setups with confluence 🎯 Best Timeframes By Trading Style: • Scalpers: 1min, 5min (quick OB touches) • Day Traders: 5min, 15min, 1H (balanced view) • Swing Traders: 1H, 4H, Daily (major institutional zones) • Position Traders: 4H, Daily, Weekly (strongest OBs) 🔥 Best Instruments: • Excellent: Forex major pairs (EUR/USD, GBP/USD), BTC, ETH, ES, NQ • Good: Gold, Oil, Major indices, Large-cap stocks • Moderate: Altcoins, small-cap stocks (more noise) • Avoid: Very low liquidity instruments (OBs less reliable) ⏰ Best Times To Trade OBs: • London Session (03:00-12:00 EST): Highest OB respect rate • NY Session (08:00-17:00 EST): Strong OB reactions • London-NY Overlap (08:00-12:00 EST): Best probability • Asian Session: Lower probability, wait for London ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎓 Advanced Order Block Concepts Order Block Flips (Polarity Change) When price breaks through an OB and closes beyond it: • Bullish OB that's broken becomes bearish (support becomes resistance) • Bearish OB that's broken becomes bullish (resistance becomes support) • Trading: Watch for retest of broken OB from opposite side Order Block Refinement When multiple OBs form at similar level: • Later OB "refines" or "replaces" the earlier one • Use the most recent OB as the active zone • Older OBs become less relevant Order Block Clusters Multiple OBs stacked close together: • Creates a "super zone" of institutional interest • Higher probability of reversal • Wider zone for entries (more room for confirmation) Fair Value Gaps + Order Blocks When OB aligns with Fair Value Gap: • Extremely high probability setup • Price is drawn to fill the gap AND test the OB • Double confluence = institutional magnet Order Block Mitigation Types • Full Mitigation: Price fully enters and closes inside OB • Partial Mitigation: Price wicks into OB but closes outside • False Mitigation: Quick touch then immediate rejection • Partial/false mitigation = OB still somewhat valid ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📈 Common Order Block Patterns Pattern 1: The Perfect Retest • OB forms during strong move • Price continues 100-200+ pips • Price retraces back to OB • Clean bounce with confirmation candle • Highest probability pattern Pattern 2: The Double Tap • Price tests OB, bounces weakly • Price tests same OB again • Second test produces stronger reaction • Second touch often better entry Pattern 3: The Fake-Out • Price breaks through OB • Immediately reverses back • "Stop hunt" or liquidity grab • Enter after price reclaims OB Pattern 4: The Ladder • Multiple OBs stacked like stairs • Price steps from one OB to next • Each OB provides support/resistance • Trade OB-to-OB movements Pattern 5: The Failed OB • Price crashes through OB without pause • OB completely invalidated • Often signals strong momentum • Don't fight it, trade the breakout ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🚀 What Makes This Different? Unlike basic support/resistance indicators, Order Block Identifier: • ICT Methodology - Based on proven institutional concepts • Auto-Timeframe Optimization - Works perfectly on all timeframes • ATR-Based Detection - Adapts to each instrument's volatility • Mitigation Tracking - Knows when blocks are no longer valid • Active Block Highlighting - Shows most relevant opportunity • Smart Filtering - Only shows high-quality institutional zones • Visual Clarity - Clean, professional appearance • Real-Time Updates - Blocks update as price action develops Based On Professional Concepts: • ICT Smart Money Concepts (SMC) • Institutional order flow analysis • Market maker behavior patterns • Supply and demand zone theory ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📈 Upgrade Your Trading Arsenal This free indicator gives you institutional-level order block analysis. Want more? 🔥 Check out my premium scripts for: • Automated entries at order blocks with confirmation • Fair Value Gap detection combined with OBs • Multi-timeframe order block strategies • Breaker blocks and advanced ICT concepts • Complete smart money trading systems • And much more... 👉 Visit my profile to trade like institutions! ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📝 Important Notes • Order blocks are high-probability zones, not guarantees • Always use confirmation (price action patterns) • First touch of OB is most reliable (60-70% win rate) • Mitigated blocks are much weaker (30-40% win rate) • Works best during high-volume sessions • Combine with proper risk management (1-2% risk per trade) • Not all OBs are created equal - look for confluence • Practice on demo before trading live • Past performance doesn't guarantee future results Learning Curve: • Week 1-2: Learn to identify OBs and wait for retests • Week 3-4: Practice entry confirmation and risk management • Month 2-3: Combine with other analysis (MTF, structure, FVGs) • Month 3+: Develop personal OB trading system Disclaimer: For educational purposes only. Order block trading requires practice and proper risk management. Always do your own research. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🙏 Support This Work If this indicator helps you trade with institutions: • ⭐ Give it a thumbs up • 💬 Share your best order block trades in comments • 🔔 Follow for more free ICT/SMC tools • 🚀 Share with traders learning smart money concepts Questions about order blocks? Drop a comment and I'll explain! ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Developed with ❤️ for traders who want to see what institutions see ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Version History • v1.0 - Initial release with auto-timeframe detection and ATR-based strength filtering
مؤشر Pine Script®
من ‎Exponential-X‎
SMC + OB + FVG + Reversal + UT Bot + Hull Suite – by Fatich.id🎯 7 INTEGRATED SYSTEMS: ✓ Mxwll Suite (SMC + Auto Fibs + CHoCH/BOS) ✓ UT Bot (Trend Signals + Label Management) ✓ Hull Suite (Momentum Analysis) ✓ LuxAlgo FVG (Fair Value Gaps) ✓ LuxAlgo Order Blocks (Volume Pivots) ⭐ NEW ✓ Three Bar Reversal (Pattern Recognition) ✓ Reversal Signals (Momentum Count Style) ⚡ KEY FEATURES: • Smart Money Structure (CHoCH/BOS/I-CHoCH/I-BoS) • Auto Fibonacci (10 customizable levels) • Order Block Detection (Auto mitigation) • Fair Value Gap Tracking • Session Highlights (NY/London/Asia) • Volume Activity Dashboard • Multi-Timeframe Support • Clean Label Management 🎨 PERFECT FOR: • Smart Money Concept Traders • Order Flow & Liquidity Analysis • Support/Resistance Trading • Trend Following & Reversals • Multi-Timeframe Analysis 💡 RECOMMENDED SETTINGS: Clean Charts: OB Count 3, UT Signals 3, FVG 5 Detailed Analysis: OB Count 5-10, All Signals Scalping: Low sensitivity, Hull 20-30 Swing Trading: High sensitivity, Hull 55-100
مؤشر Pine Script®
من ‎fatich_id‎
Session Highlighter Pro [Eˣ]🌍 Session Highlighter Pro - Free Indicator Overview Session Highlighter Pro brings institutional-level session analysis to your charts. This indicator automatically highlights the Asian, London, and New York trading sessions, marks high-volatility "Kill Zones", identifies profitable session overlaps, and tracks key session levels - all essential for timing your trades and understanding when the smart money is active. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎯 What This Indicator Does Highlights Trading Sessions: • 🟡 Asian Session (19:00-04:00 EST) - Lower volatility, range-bound • 🔵 London Session (03:00-12:00 EST) - High volatility, trend moves • 🟢 New York Session (08:00-17:00 EST) - Highest volume, major moves • All times automatically adjust for EST/EDT (daylight saving) Marks Kill Zones: • 🔥 London Kill Zone (02:00-05:00 EST) - London market makers most active • 🔥 NY Kill Zone (08:30-11:00 EST) - NY institutional activity peaks • Highest probability setups occur during these windows • Peak liquidity and volatility periods Identifies Session Overlaps: • ⚡ London-NY Overlap (08:00-12:00 EST) - Maximum volume period • 💜 Asian-London Overlap (03:00-04:00 EST) - Early volatility spike • Most explosive moves happen during overlaps • Best time for breakout and momentum trading Tracks Session Levels: • Session High/Low lines (support and resistance) • Session Open lines (key reference levels) • Real-time range calculations • Customizable line styles and colors Smart Features: • Statistics panel showing current session and ranges • Fully customizable colors and display options • Works on all timeframes (best on 5min to 1H) • Built-in alerts for session starts and kill zones • Clean, professional visualization ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 Understanding Trading Sessions Why Sessions Matter Different trading sessions have dramatically different characteristics: • Volume: Sessions determine who's in the market (retail vs institutional) • Volatility: Major sessions bring major moves • Liquidity: Better fills and tighter spreads during active sessions • Trends: Real trends start during London/NY, not Asian • Reversals: Often happen at session opens/closes Professional traders time their entries based on sessions - now you can too. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🟡 Asian Session (19:00-04:00 EST) Characteristics: • Lowest volume of the three major sessions • Range-bound, choppy price action • Less institutional activity • Tokyo, Hong Kong, Singapore markets open • Good for range trading, poor for breakouts Best For: • Range trading strategies • Scalping in established ranges • Identifying support/resistance for London open • Pairs: AUD/JPY, NZD/JPY, AUD/USD Trading Tips: • Avoid breakout trades - often false breakouts • Trade between session high/low • Watch for range compression before London • Expect reversal at support/resistance What To Avoid: • Chasing breakouts (usually fail) • Large position sizes (low liquidity) • News trading (limited market participation) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🔵 London Session (03:00-12:00 EST) Characteristics: • High volatility and volume • Strongest trends develop here • Major institutional activity • European markets + early London traders • Real breakouts happen during this session Best For: • Trend trading strategies • Breakout trading (especially at open) • Major currency pairs (EUR/USD, GBP/USD, EUR/GBP) • Gold and oil trading Trading Tips: • Watch for breakout of Asian range at London open • First hour (03:00-04:00 EST) often sets daily tone • London Kill Zone (02:00-05:00) has highest win rate • Session high/low often hold as support/resistance Key Moments: • 03:00 EST: London open - major volatility spike • 02:00-05:00 EST: London Kill Zone - institutional orders • 08:00 EST: London-NY overlap begins - explosive moves ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🟢 New York Session (08:00-17:00 EST) Characteristics: • Highest volume globally (when overlapping with London) • US market open brings major moves • Economic news releases (08:30 EST typically) • Strong directional moves • US institutional money flows Best For: • Trend continuation trades • News trading (NFP, CPI, FOMC, etc.) • US indices (ES, NQ, YM) • Major pairs involving USD Trading Tips: • 08:30 EST = Most economic releases (high volatility) • NY Kill Zone (08:30-11:00) = Highest probability window • First 2 hours most volatile (08:00-10:00) • After 12:00 (London close) volume drops significantly Key Moments: • 08:00 EST: NY open + London overlap begins • 08:30 EST: Economic data releases • 08:30-11:00 EST: NY Kill Zone - institutional activity • 12:00 EST: London close - volume drops • 16:00 EST: Stock market close - volatility spike ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🔥 Kill Zones Explained What Are Kill Zones? Kill Zones are specific time windows within sessions where institutional traders (banks, hedge funds, market makers) are most active. These periods consistently show: • Highest win-rate setups • Largest moves relative to risk • Best liquidity for entries/exits • Most reliable technical patterns Popularized by ICT (Inner Circle Trader), these zones represent when smart money acts. London Kill Zone (02:00-05:00 EST) Why It Works: • London banks and institutions place orders • Pre-London positioning before official open • Often runs stops before reversing • Sets up the trend for London session How To Trade: 1. Watch for sweep of Asian highs/lows 2. Look for reversal back into range 3. Enter in direction of reversal 4. Target: Opposite side of range or session high/low Best Pairs: EUR/USD, GBP/USD, EUR/GBP, Gold NY Kill Zone (08:30-11:00 EST) Why It Works: • Overlaps with London session (maximum volume) • Economic data releases at 08:30 • US institutions enter positions • Highest liquidity period globally How To Trade: 1. Wait for news spike at 08:30 (if applicable) 2. Identify sweep and reversal patterns 3. Enter with momentum after confirmation 4. Target: Session high/low or previous day levels Best Instruments: Indices (ES, NQ), USD pairs, Gold ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚡ Session Overlaps London-NY Overlap (08:00-12:00 EST) The Golden Window: • Highest trading volume of entire 24-hour cycle • Both European and US traders active • Maximum liquidity = tightest spreads • Biggest moves of the day often occur here • Best time for all trading styles Trading Strategies: • Breakout trading (high follow-through probability) • Momentum trading (strong trends develop) • News trading (major releases during this time) • Scalping (high volatility + tight spreads) What To Watch: • Direction established in first hour often continues • 08:30 economic data can reverse or accelerate trends • After London close (12:00), expect consolidation Asian-London Overlap (03:00-04:00 EST) The Early Bird Window: • Short overlap period • Early volatility as Asian session ends • London traders positioning before official open • Often see reversal of Asian range Trading Strategies: • Fade Asian extremes (sell highs, buy lows) • Play breakout of Asian range • Quick scalps during volatility spike • Position for London session trend ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 How To Use This Indicator Strategy 1: Session Breakout Trading Best For: Trend trading, catching major moves Timeframes: 5min, 15min, 1H Setup: 1. Note Asian session high/low (yellow lines) 2. Wait for London open (03:00 EST) 3. If price breaks Asian high/low with strong candle, enter breakout 4. Stop loss: Opposite side of Asian range 5. Target: 1.5-2x Asian range or session high/low Why It Works: London volume breaks Asian consolidation Strategy 2: Kill Zone Reversals Best For: High win-rate setups Timeframes: 5min, 15min Setup: 1. Wait for Kill Zone to begin (red background) 2. Watch for stop hunt (sweep of recent high/low) 3. Look for rejection/reversal pattern 4. Enter when price reverses back into range 5. Stop: Beyond the swept level 6. Target: Opposite kill zone extreme Why It Works: Institutions sweep stops then reverse Strategy 3: Overlap Momentum Best For: Riding strong trends Timeframes: 15min, 1H Setup: 1. Wait for London-NY overlap (08:00 EST, orange background) 2. Identify trend direction in first 30 minutes 3. Enter pullbacks in trend direction 4. Stop: Below recent swing low/high 5. Target: Session high/low or previous day levels 6. Hold until overlap ends (12:00 EST) Why It Works: Maximum volume drives sustained moves Strategy 4: Asian Range Trading Best For: Low-risk scalping Timeframes: 5min, 15min Setup: 1. During Asian session (yellow background) 2. Let range establish (first 2-3 hours) 3. Buy at session low, sell at session high 4. Tight stops outside range 5. Exit before London open (03:00 EST) Why It Works: Asian session typically ranges Strategy 5: Session Level Trading Best For: Support/resistance trading Timeframes: All Setup: 1. Previous session highs/lows become S/R levels 2. Watch for price reaction at these levels 3. Enter bounces (support) or rejections (resistance) 4. Use session open lines as confirmation 5. Stop: Slightly beyond session level Why It Works: Traders watch session levels globally ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚙️ Settings Explained Sessions Show Asian/London/NY Session • Toggle each session on/off • Customize background colors for each • Adjust transparency to your preference • Tip: Disable sessions you don't trade Highlight Session Overlaps • Shows when sessions overlap (different color) • Critical for identifying high-volume periods • Recommended: Keep ON Overlap Color • Customize the overlap background color • Default: Orange (stands out from session colors) Levels Show Session High/Low Lines • Displays horizontal lines at session extremes • Acts as intraday support/resistance • Choose line style: Solid, Dashed, or Dotted • Recommended: Keep ON for level trading Show Session Open Lines • Displays line at session opening price • Key reference level for traders • Choose line style (default: Dashed) • Useful for mean reversion strategies Kill Zones Show Kill Zones • Master toggle for kill zone highlighting • Turn OFF if you don't use kill zone strategies London Kill Zone (02:00-05:00 EST) • Toggle London KZ on/off • Most important for forex traders NY Kill Zone (08:30-11:00 EST) • Toggle NY KZ on/off • Most important for indices/stock traders KZ Color • Customize kill zone background color • Default: Red (indicates high importance) Display Show Session Statistics • Toggle the info panel (top-left) • Displays current session and ranges • Keep ON for session awareness Show Session Labels • Toggle session name labels on chart • Shows session name + current range % • Turn OFF for cleaner appearance ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📱 Statistics Panel Guide Current Session • Shows which session is currently active • Color-coded for quick identification • Displays "KILL ZONE 🔥" when applicable • Shows "OVERLAP" during London-NY overlap Session Table Session Column: • Lists all three major sessions • Color-coded icons for quick reference Time Column: • Shows session hours in EST • All times automatically adjust for daylight saving Range Column: • Current session range as percentage • Updates in real-time during active session • Shows "-" when session hasn't started • Higher range = More volatility Using The Stats: • Compare daily ranges to historical average • Larger ranges = More opportunity • Small ranges in Kill Zones = Potential breakout coming • Track which sessions are most profitable for your style ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📱 Alert Setup This indicator includes 6 alert types: 1. Asian Session Open • Fires when Asian session starts (19:00 EST) • Useful for range traders 2. London Session Open • Fires when London session starts (03:00 EST) • Critical alert for breakout traders 3. NY Session Open • Fires when NY session starts (08:00 EST) • Important for US market traders 4. London Kill Zone Start • Fires at 02:00 EST • High-probability trading window begins 5. NY Kill Zone Start • Fires at 08:30 EST • Prime time for indices and USD pairs 6. London-NY Overlap Start • Fires at 08:00 EST • Maximum volume period begins To Set Up Alerts: 1. Click "Alert" button (clock icon) 2. Select "Session Highlighter Pro" 3. Choose your alert type 4. Configure notification method 5. Click "Create" Pro Tip: Set alerts for kill zones and overlaps - these are your highest probability trading windows ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💎 Pro Tips & Best Practices ✅ DO: • Trade during your session - Match your schedule to high-volume sessions • Focus on Kill Zones - Highest win-rate setups occur here • Use session levels as S/R - Previous session highs/lows are watched globally • Wait for overlaps - Best moves happen during London-NY overlap • Fade Asian extremes - Asian highs/lows often reversed by London • Watch the first hour - Sets tone for the entire session • Track session ranges - Know if volatility is high or low • Respect session transitions - Major reversals happen at opens/closes ⚠️ DON'T: • Don't fight the session - Don't expect trends during Asian session • Don't ignore overlaps - Missing London-NY overlap = Missing best moves • Don't trade all sessions - Focus on one or two that fit your schedule • Don't chase late session - After London close (12:00 EST), volume drops • Don't ignore time - Same setup has different probability in different sessions • Don't trade low-volume gaps - Between NY close and Asian open, stay flat 🎯 Session Selection By Trading Style: • Scalpers: London-NY overlap (08:00-12:00 EST) • Day Traders: London + NY sessions (03:00-17:00 EST) • Swing Traders: Focus on London/NY opens for entries • Range Traders: Asian session (19:00-04:00 EST) • Breakout Traders: London open + Kill Zones • News Traders: NY Kill Zone (08:30-11:00 EST) 🔥 Best Instruments By Session: • Asian: AUD/JPY, NZD/JPY, AUD/USD, Nikkei • London: EUR/USD, GBP/USD, EUR/GBP, Gold, FTSE, DAX • New York: All USD pairs, ES, NQ, YM, Gold, Oil • Overlap: Everything (maximum liquidity) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🚀 What Makes This Different? Unlike basic session indicators, Session Highlighter Pro includes: • Kill Zones - ICT-style high-probability windows marked • Session Overlaps - Automatically identifies peak volume periods • Real-Time Statistics - Track session ranges and volatility • Dynamic Levels - Session highs/lows update in real-time • Full Customization - Colors, styles, toggle everything • Clean Display - Professional look, not cluttered • Smart Alerts - Never miss a session or kill zone • EST Timezone - Standard format all pro traders use Based On Professional Concepts: • ICT Kill Zone methodology • Institutional order flow timing • Global market structure understanding • Session-based trading psychology ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📈 Common Session Patterns Pattern 1: Asian Range, London Breakout • Asian session creates tight range • London open breaks range with volume • Trade breakout in direction of London move Pattern 2: London Reversal At NY Open • London trends one direction all session • NY open (08:00) reverses the London trend • Often happens at London highs/lows Pattern 3: Kill Zone Sweep & Reverse • Kill zone begins • Price sweeps recent high/low (stop hunt) • Immediately reverses in opposite direction • Most reliable pattern in trading Pattern 4: Overlap Continuation • London establishes trend direction • NY open (08:00) confirms and accelerates • Trend continues through entire overlap Pattern 5: Late Session Consolidation • After London close (12:00 EST) • Volume drops, price ranges • Wait for next session instead of trading ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📈 Upgrade Your Trading Toolkit This free indicator gives you professional session analysis. Want more? 🔥 Check out my premium scripts for: • Automated entry signals timed to sessions • Advanced multi-timeframe session analysis • Kill zone-specific trading strategies • Backtested session-based systems • Complete trading solutions • And much more... 👉 Visit my profile for institutional-grade tools! ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📝 Important Notes • All times displayed in EST (Eastern Standard Time) • Automatically adjusts for daylight saving time • Works on all timeframes (best on 5min-1H) • Designed for Forex, Indices, and Commodities • Session times are approximate - liquidity varies • Use with proper risk management • Not all session patterns play out perfectly • Market conditions vary - adapt accordingly Timezone Note: This indicator uses EST/EDT. If you're in a different timezone, calculate the offset. For example, London traders should add 5 hours to all times displayed. Disclaimer: For educational purposes. Trading involves risk. Session-based trading requires practice and proper risk management. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🙏 Support This Work If this indicator helps you time your trades better: • ⭐ Give it a thumbs up • 💬 Share your best session-based trades in comments • 🔔 Follow for more free professional tools • 🚀 Share with traders who need better timing Questions about trading sessions? Drop a comment and I'll help! ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Developed with ❤️ for traders who understand that WHEN you trade matters as much as WHAT you trade ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Version History • v1.0 - Initial release with sessions, kill zones, overlaps, and real-time statistics
مؤشر Pine Script®
من ‎Exponential-X‎
Hellenic EMA Matrix - PremiumHellenic EMA Matrix - Alpha Omega Premium Complete User Guide Table of Contents Introduction Indicator Philosophy Mathematical Constants EMA Types Settings Trading Signals Visualization Usage Strategies FAQ Introduction Hellenic EMA Matrix is a premium indicator based on mathematical constants of nature: Phi (Phi - Golden Ratio), Pi (Pi), e (Euler's number). The indicator uses these universal constants to create dynamic EMAs that adapt to the natural rhythms of the market. Key Features: 6 EMA types based on mathematical constants Premium visualization with Neon Glow and Gradient Clouds Automatic Fast/Mid/Slow EMA sorting STRONG signals for powerful trends Pulsing Ribbon Bar for instant trend assessment Works on all timeframes (M1 - MN) Indicator Philosophy Why Mathematical Constants? Traditional EMAs use arbitrary periods (9, 21, 50, 200). Hellenic Matrix goes further, using universal mathematical constants found in nature: Phi (1.618) - Golden Ratio: galaxy spirals, seashells, human body proportions Pi (3.14159) - Pi: circles, waves, cycles e (2.71828) - Natural logarithm base: exponential growth, radioactive decay Markets are also a natural system composed of millions of participants. Using mathematical constants allows tuning into the natural rhythms of market cycles. Mathematical Constants Phi (Phi) - Golden Ratio Phi = 1.618033988749895 Properties: Phi² = Phi + 1 = 2.618 Phi³ = 4.236 Phi⁴ = 6.854 Application: Ideal for trending movements and Fibonacci corrections Pi (Pi) - Pi Number Pi = 3.141592653589793 Properties: 2Pi = 6.283 (full circle) 3Pi = 9.425 4Pi = 12.566 Application: Excellent for cyclical markets and wave structures e (Euler) - Euler's Number e = 2.718281828459045 Properties: e² = 7.389 e³ = 20.085 e⁴ = 54.598 Application: Suitable for exponential movements and volatile markets EMA Types 1. Phi (Phi) - Golden Ratio EMA Description: EMA based on the golden ratio Period Formula: Period = Phi^n × Base Multiplier Parameters: Phi Power Level (1-8): Power of Phi Phi¹ = 1.618 → ~16 period (with Base=10) Phi² = 2.618 → ~26 period Phi³ = 4.236 → ~42 period (recommended) Phi⁴ = 6.854 → ~69 period Recommendations: Phi² or Phi³ for day trading Phi⁴ or Phi⁵ for swing trading Works excellently as Fast EMA 2. Pi (Pi) - Circular EMA Description: EMA based on Pi for cyclical movements Period Formula: Period = Pi × Multiple × Base Multiplier Parameters: Pi Multiple (1-10): Pi multiplier 1Pi = 3.14 → ~31 period (with Base=10) 2Pi = 6.28 → ~63 period (recommended) 3Pi = 9.42 → ~94 period Recommendations: 2Pi ideal as Mid or Slow EMA Excellently identifies cycles and waves Use on volatile markets (crypto, forex) 3. e (Euler) - Natural EMA Description: EMA based on natural logarithm Period Formula: Period = e^n × Base Multiplier Parameters: e Power Level (1-6): Power of e e¹ = 2.718 → ~27 period (with Base=10) e² = 7.389 → ~74 period (recommended) e³ = 20.085 → ~201 period Recommendations: e² works excellently as Slow EMA Ideal for stocks and indices Filters noise well on lower timeframes 4. Delta (Delta) - Adaptive EMA Description: Adaptive EMA that changes period based on volatility Period Formula: Period = Base Period × (1 + (Volatility - 1) × Factor) Parameters: Delta Base Period (5-200): Base period (default 20) Delta Volatility Sensitivity (0.5-5.0): Volatility sensitivity (default 2.0) How it works: During low volatility → period decreases → EMA reacts faster During high volatility → period increases → EMA smooths noise Recommendations: Works excellently on news and sharp movements Use as Fast EMA for quick adaptation Sensitivity 2.0-3.0 for crypto, 1.0-2.0 for stocks 5. Sigma (Sigma) - Composite EMA Description: Composite EMA combining multiple active EMAs Composition Methods: Weighted Average (default): Sigma = (Phi + Pi + e + Delta) / 4 Simple average of all active EMAs Geometric Mean: Sigma = fourth_root(Phi × Pi × e × Delta) Geometric mean (more conservative) Harmonic Mean: Sigma = 4 / (1/Phi + 1/Pi + 1/e + 1/Delta) Harmonic mean (more weight to smaller values) Recommendations: Enable for additional confirmation Use as Mid EMA Weighted Average - most universal method 6. Lambda (Lambda) - Wave EMA Description: Wave EMA with sinusoidal period modulation Period Formula: Period = Base Period × (1 + Amplitude × sin(2Pi × bar / Frequency)) Parameters: Lambda Base Period (10-200): Base period Lambda Wave Amplitude (0.1-2.0): Wave amplitude Lambda Wave Frequency (10-200): Wave frequency in bars How it works: Period pulsates sinusoidally Creates wave effect following market cycles Recommendations: Experimental EMA for advanced users Works well on cyclical markets Frequency = 50 for day trading, 100+ for swing Settings Matrix Core Settings Base Multiplier (1-100) Multiplies all EMA periods Base = 1: Very fast EMAs (Phi³ = 4, 2Pi = 6, e² = 7) Base = 10: Standard (Phi³ = 42, 2Pi = 63, e² = 74) Base = 20: Slow EMAs (Phi³ = 85, 2Pi = 126, e² = 148) Recommendations by timeframe: M1-M5: Base = 5-10 M15-H1: Base = 10-15 (recommended) H4-D1: Base = 15-25 W1-MN: Base = 25-50 Matrix Source Data source selection for EMA calculation: close - closing price (standard) open - opening price high - high low - low hl2 - (high + low) / 2 hlc3 - (high + low + close) / 3 ohlc4 - (open + high + low + close) / 4 When to change: hlc3 or ohlc4 for smoother signals high for aggressive longs low for aggressive shorts Manual EMA Selection Critically important setting! Determines which EMAs are used for signal generation. Use Manual Fast/Slow/Mid Selection Enabled (default): You select EMAs manually Disabled: Automatic selection by periods Fast EMA Fast EMA - reacts first to price changes Recommendations: Phi Golden (recommended) - universal choice Delta Adaptive - for volatile markets Must be fastest (smallest period) Slow EMA Slow EMA - determines main trend Recommendations: Pi Circular (recommended) - excellent trend filter e Natural - for smoother trend Must be slowest (largest period) Mid EMA Mid EMA - additional signal filter Recommendations: e Natural (recommended) - excellent middle level Pi Circular - alternative None - for more frequent signals (only 2 EMAs) IMPORTANT: The indicator automatically sorts selected EMAs by their actual periods: Fast = EMA with smallest period Mid = EMA with middle period Slow = EMA with largest period Therefore, you can select any combination - the indicator will arrange them correctly! Premium Visualization Neon Glow Enable Neon Glow for EMAs - adds glowing effect around EMA lines Glow Strength: Light - subtle glow Medium (recommended) - optimal balance Strong - bright glow (may be too bright) Effect: 2 glow layers around each EMA for 3D effect Gradient Clouds Enable Gradient Clouds - fills space between EMAs with gradient Parameters: Cloud Transparency (85-98): Cloud transparency 95-97 (recommended) Higher = more transparent Dynamic Cloud Intensity - automatically changes transparency based on EMA distance Cloud Colors: Phi-Pi Cloud: Blue - when Pi above Phi (bullish) Gold - when Phi above Pi (bearish) Pi-e Cloud: Green - when e above Pi (bullish) Blue - when Pi above e (bearish) 2 layers for volumetric effect Pulsing Ribbon Bar Enable Pulsing Indicator Bar - pulsing strip at bottom/top of chart Parameters: Ribbon Position: Top / Bottom (recommended) Pulse Speed: Slow / Medium (recommended) / Fast Symbols and colors: Green filled square - STRONG BULLISH Pink filled square - STRONG BEARISH Blue hollow square - Bullish (regular) Red hollow square - Bearish (regular) Purple rectangle - Neutral Effect: Pulsation with sinusoid for living market feel Signal Bar Highlights Enable Signal Bar Highlights - highlights bars with signals Parameters: Highlight Transparency (88-96): Highlight transparency Highlight Style: Light Fill (recommended) - bar background fill Thin Line - bar outline only Highlights: Golden Cross - green Death Cross - pink STRONG BUY - green STRONG SELL - pink Show Greek Labels Shows Greek alphabet letters on last bar: Phi - Phi EMA (gold) Pi - Pi EMA (blue) e - Euler EMA (green) Delta - Delta EMA (purple) Sigma - Sigma EMA (pink) When to use: For education or presentations Show Old Background Old background style (not recommended): Green background - STRONG BULLISH Pink background - STRONG BEARISH Blue background - Bullish Red background - Bearish Not recommended - use new Gradient Clouds and Pulsing Bar Info Table Show Info Table - table with indicator information Parameters: Position: Top Left / Top Right (recommended) / Bottom Left / Bottom Right Size: Tiny / Small (recommended) / Normal / Large Table contents: EMA list - periods and current values of all active EMAs Effects - active visual effects TREND - current trend state: STRONG UP - strong bullish STRONG DOWN - strong bearish Bullish - regular bullish Bearish - regular bearish Neutral - neutral Momentum % - percentage deviation of price from Fast EMA Setup - current Fast/Slow/Mid configuration Trading Signals Show Golden/Death Cross Golden Cross - Fast EMA crosses Slow EMA from below (bullish signal) Death Cross - Fast EMA crosses Slow EMA from above (bearish signal) Symbols: Yellow dot "GC" below - Golden Cross Dark red dot "DC" above - Death Cross Show STRONG Signals STRONG BUY and STRONG SELL - the most powerful indicator signals Conditions for STRONG BULLISH: EMA Alignment: Fast > Mid > Slow (all EMAs aligned) Trend: Fast > Slow (clear uptrend) Distance: EMAs separated by minimum 0.15% Price Position: Price above Fast EMA Fast Slope: Fast EMA rising Slow Slope: Slow EMA rising Mid Trending: Mid EMA also rising (if enabled) Conditions for STRONG BEARISH: Same but in reverse Visual display: Green label "STRONG BUY" below bar Pink label "STRONG SELL" above bar Difference from Golden/Death Cross: Golden/Death Cross = crossing moment (1 bar) STRONG signal = sustained trend (lasts several bars) IMPORTANT: After fixes, STRONG signals now: Work on all timeframes (M1 to MN) Don't break on small retracements Work with any Fast/Mid/Slow combination Automatically adapt thanks to EMA sorting Show Stop Loss/Take Profit Automatic SL/TP level calculation on STRONG signal Parameters: Stop Loss (ATR) (0.5-5.0): ATR multiplier for stop loss 1.5 (recommended) - standard 1.0 - tight stop 2.0-3.0 - wide stop Take Profit R:R (1.0-5.0): Risk/reward ratio 2.0 (recommended) - standard (risk 1.5 ATR, profit 3.0 ATR) 1.5 - conservative 3.0-5.0 - aggressive Formulas: LONG: Stop Loss = Entry - (ATR × Stop Loss ATR) Take Profit = Entry + (ATR × Stop Loss ATR × Take Profit R:R) SHORT: Stop Loss = Entry + (ATR × Stop Loss ATR) Take Profit = Entry - (ATR × Stop Loss ATR × Take Profit R:R) Visualization: Red X - Stop Loss Green X - Take Profit Levels remain active while STRONG signal persists Trading Signals Signal Types 1. Golden Cross Description: Fast EMA crosses Slow EMA from below Signal: Beginning of bullish trend How to trade: ENTRY: On bar close with Golden Cross STOP: Below local low or below Slow EMA TARGET: Next resistance level or 2:1 R:R Strengths: Simple and clear Works well on trending markets Clear entry point Weaknesses: Lags (signal after movement starts) Many false signals in ranging markets May be late on fast moves Optimal timeframes: H1, H4, D1 2. Death Cross Description: Fast EMA crosses Slow EMA from above Signal: Beginning of bearish trend How to trade: ENTRY: On bar close with Death Cross STOP: Above local high or above Slow EMA TARGET: Next support level or 2:1 R:R Application: Mirror of Golden Cross 3. STRONG BUY Description: All EMAs aligned + trend + all EMAs rising Signal: Powerful bullish trend How to trade: ENTRY: On bar close with STRONG BUY or on pullback to Fast EMA STOP: Below Fast EMA or automatic SL (if enabled) TARGET: Automatic TP (if enabled) or by levels TRAILING: Follow Fast EMA Entry strategies: Aggressive: Enter immediately on signal Conservative: Wait for pullback to Fast EMA, then enter on bounce Pyramiding: Add positions on pullbacks to Mid EMA Position management: Hold while STRONG signal active Exit on STRONG SELL or Death Cross appearance Move stop behind Fast EMA Strengths: Most reliable indicator signal Doesn't break on pullbacks Catches large moves Works on all timeframes Weaknesses: Appears less frequently than other signals Requires confirmation (multiple conditions) Optimal timeframes: All (M5 - D1) 4. STRONG SELL Description: All EMAs aligned down + downtrend + all EMAs falling Signal: Powerful bearish trend How to trade: Mirror of STRONG BUY Visual Signals Pulsing Ribbon Bar Quick market assessment at a glance: Symbol Color State Filled square Green STRONG BULLISH Filled square Pink STRONG BEARISH Hollow square Blue Bullish Hollow square Red Bearish Rectangle Purple Neutral Pulsation: Sinusoidal, creates living effect Signal Bar Highlights Bars with signals are highlighted: Green highlight: STRONG BUY or Golden Cross Pink highlight: STRONG SELL or Death Cross Gradient Clouds Colored space between EMAs shows trend strength: Wide clouds - strong trend Narrow clouds - weak trend or consolidation Color change - trend change Info Table Quick reference in corner: TREND: Current state (STRONG UP, Bullish, Neutral, Bearish, STRONG DOWN) Momentum %: Movement strength Effects: Active visual effects Setup: Fast/Slow/Mid configuration Usage Strategies Strategy 1: "Golden Trailing" Idea: Follow STRONG signals using Fast EMA as trailing stop Settings: Fast: Phi Golden (Phi³) Mid: Pi Circular (2Pi) Slow: e Natural (e²) Base Multiplier: 10 Timeframe: H1, H4 Entry rules: Wait for STRONG BUY Enter on bar close or on pullback to Fast EMA Stop below Fast EMA Management: Hold position while STRONG signal active Move stop behind Fast EMA daily Exit on STRONG SELL or Death Cross Take Profit: Partially close at +2R Trail remainder until exit signal For whom: Swing traders, trend followers Pros: Catches large moves Simple rules Emotionally comfortable Cons: Requires patience Possible extended drawdowns on pullbacks Strategy 2: "Scalping Bounces" Idea: Scalp bounces from Fast EMA during STRONG trend Settings: Fast: Delta Adaptive (Base 15, Sensitivity 2.0) Mid: Phi Golden (Phi²) Slow: Pi Circular (2Pi) Base Multiplier: 5 Timeframe: M5, M15 Entry rules: STRONG signal must be active Wait for price pullback to Fast EMA Enter on bounce (candle closes above/below Fast EMA) Stop behind local extreme (15-20 pips) Take Profit: +1.5R or to Mid EMA Or to next level For whom: Active day traders Pros: Many signals Clear entry point Quick profits Cons: Requires constant monitoring Not all bounces work Requires discipline for frequent trading Strategy 3: "Triple Filter" Idea: Enter only when all 3 EMAs and price perfectly aligned Settings: Fast: Phi Golden (Phi³) Mid: e Natural (e²) Slow: Pi Circular (3Pi) Base Multiplier: 15 Timeframe: H4, D1 Entry rules (LONG): STRONG BUY active Price above all three EMAs Fast > Mid > Slow (all aligned) All EMAs rising (slope up) Gradient Clouds wide and bright Entry: On bar close meeting all conditions Or on next pullback to Fast EMA Stop: Below Mid EMA or -1.5 ATR Take Profit: First target: +3R Second target: next major level Trailing: Mid EMA For whom: Conservative swing traders, investors Pros: Very reliable signals Minimum false entries Large profit potential Cons: Rare signals (2-5 per month) Requires patience Strategy 4: "Adaptive Scalper" Idea: Use only Delta Adaptive EMA for quick volatility reaction Settings: Fast: Delta Adaptive (Base 10, Sensitivity 3.0) Mid: None Slow: Delta Adaptive (Base 30, Sensitivity 2.0) Base Multiplier: 3 Timeframe: M1, M5 Feature: Two different Delta EMAs with different settings Entry rules: Golden Cross between two Delta EMAs Both Delta EMAs must be rising/falling Enter on next bar Stop: 10-15 pips or below Slow Delta EMA Take Profit: +1R to +2R Or Death Cross For whom: Scalpers on cryptocurrencies and forex Pros: Instant volatility adaptation Many signals on volatile markets Quick results Cons: Much noise on calm markets Requires fast execution High commissions may eat profits Strategy 5: "Cyclical Trader" Idea: Use Pi and Lambda for trading cyclical markets Settings: Fast: Pi Circular (1Pi) Mid: Lambda Wave (Base 30, Amplitude 0.5, Frequency 50) Slow: Pi Circular (3Pi) Base Multiplier: 10 Timeframe: H1, H4 Entry rules: STRONG signal active Lambda Wave EMA synchronized with trend Enter on bounce from Lambda Wave For whom: Traders of cyclical assets (some altcoins, commodities) Pros: Catches cyclical movements Lambda Wave provides additional entry points Cons: More complex to configure Not for all markets Lambda Wave may give false signals Strategy 6: "Multi-Timeframe Confirmation" Idea: Use multiple timeframes for confirmation Scheme: Higher TF (D1): Determine trend direction (STRONG signal) Middle TF (H4): Wait for STRONG signal in same direction Lower TF (M15): Look for entry point (Golden Cross or bounce from Fast EMA) Settings for all TFs: Fast: Phi Golden (Phi³) Mid: e Natural (e²) Slow: Pi Circular (2Pi) Base Multiplier: 10 Rules: All 3 TFs must show one trend Entry on lower TF Stop by lower TF Target by higher TF For whom: Serious traders and investors Pros: Maximum reliability Large profit targets Minimum false signals Cons: Rare setups Requires analysis of multiple charts Experience needed Practical Tips DOs Use STRONG signals as primary - they're most reliable Let signals develop - don't exit on first pullback Use trailing stop - follow Fast EMA Combine with levels - S/R, Fibonacci, volumes Test on demo before real Adjust Base Multiplier for your timeframe Enable visual effects - they help see the picture Use Info Table - quick situation assessment Watch Pulsing Bar - instant state indicator Trust auto-sorting of Fast/Mid/Slow DON'Ts Don't trade against STRONG signal - trend is your friend Don't ignore Mid EMA - it adds reliability Don't use too small Base Multiplier on higher TFs Don't enter on Golden Cross in range - check for trend Don't change settings during open position Don't forget risk management - 1-2% per trade Don't trade all signals in row - choose best ones Don't use indicator in isolation - combine with Price Action Don't set too tight stops - let trade breathe Don't over-optimize - simplicity = reliability Optimal Settings by Asset US Stocks (SPY, AAPL, TSLA) Recommendation: Fast: Phi Golden (Phi³) Mid: e Natural (e²) Slow: Pi Circular (2Pi) Base: 10-15 Timeframe: H4, D1 Features: Use on daily for swing STRONG signals very reliable Works well on trending stocks Forex (EUR/USD, GBP/USD) Recommendation: Fast: Delta Adaptive (Base 15, Sens 2.0) Mid: Phi Golden (Phi²) Slow: Pi Circular (2Pi) Base: 8-12 Timeframe: M15, H1, H4 Features: Delta Adaptive works excellently on news Many signals on M15-H1 Consider spreads Cryptocurrencies (BTC, ETH, altcoins) Recommendation: Fast: Delta Adaptive (Base 10, Sens 3.0) Mid: Pi Circular (2Pi) Slow: e Natural (e²) Base: 5-10 Timeframe: M5, M15, H1 Features: High volatility - adaptation needed STRONG signals can last days Be careful with scalping on M1-M5 Commodities (Gold, Oil) Recommendation: Fast: Pi Circular (1Pi) Mid: Phi Golden (Phi³) Slow: Pi Circular (3Pi) Base: 12-18 Timeframe: H4, D1 Features: Pi works excellently on cyclical commodities Gold responds especially well to Phi Oil volatile - use wide stops Indices (S&P500, Nasdaq, DAX) Recommendation: Fast: Phi Golden (Phi³) Mid: e Natural (e²) Slow: Pi Circular (2Pi) Base: 15-20 Timeframe: H4, D1, W1 Features: Very trending instruments STRONG signals last weeks Good for position trading Alerts The indicator supports 6 alert types: 1. Golden Cross Message: "Hellenic Matrix: GOLDEN CROSS - Fast EMA crossed above Slow EMA - Bullish trend starting!" When: Fast EMA crosses Slow EMA from below 2. Death Cross Message: "Hellenic Matrix: DEATH CROSS - Fast EMA crossed below Slow EMA - Bearish trend starting!" When: Fast EMA crosses Slow EMA from above 3. STRONG BULLISH Message: "Hellenic Matrix: STRONG BULLISH SIGNAL - All EMAs aligned for powerful uptrend!" When: All conditions for STRONG BUY met (first bar) 4. STRONG BEARISH Message: "Hellenic Matrix: STRONG BEARISH SIGNAL - All EMAs aligned for powerful downtrend!" When: All conditions for STRONG SELL met (first bar) 5. Bullish Ribbon Message: "Hellenic Matrix: BULLISH RIBBON - EMAs aligned for uptrend" When: EMAs aligned bullish + price above Fast EMA (less strict condition) 6. Bearish Ribbon Message: "Hellenic Matrix: BEARISH RIBBON - EMAs aligned for downtrend" When: EMAs aligned bearish + price below Fast EMA (less strict condition) How to Set Up Alerts: Open indicator on chart Click on three dots next to indicator name Select "Create Alert" In "Condition" field select needed alert: Golden Cross Death Cross STRONG BULLISH STRONG BEARISH Bullish Ribbon Bearish Ribbon Configure notification method: Pop-up in browser Email SMS (in Premium accounts) Push notifications in mobile app Webhook (for automation) Select frequency: Once Per Bar Close (recommended) - once on bar close Once Per Bar - during bar formation Only Once - only first time Click "Create" Tip: Create separate alerts for different timeframes and instruments FAQ 1. Why don't STRONG signals appear? Possible reasons: Incorrect Fast/Mid/Slow order Solution: Indicator automatically sorts EMAs by periods, but ensure selected EMAs have different periods Base Multiplier too large Solution: Reduce Base to 5-10 on lower timeframes Market in range Solution: STRONG signals appear only in trends - this is normal Too strict EMA settings Solution: Try classic combination: Phi³ / Pi×2 / e² with Base=10 Mid EMA too close to Fast or Slow Solution: Select Mid EMA with period between Fast and Slow 2. How often should STRONG signals appear? Normal frequency: M1-M5: 5-15 signals per day (very active markets) M15-H1: 2-8 signals per day H4: 3-10 signals per week D1: 2-5 signals per month W1: 2-6 signals per year If too many signals - market very volatile or Base too small If too few signals - market in range or Base too large 4. What are the best settings for beginners? Universal "out of the box" settings: Matrix Core: Base Multiplier: 10 Source: close Phi Golden: Enabled, Power = 3 Pi Circular: Enabled, Multiple = 2 e Natural: Enabled, Power = 2 Delta Adaptive: Enabled, Base = 20, Sensitivity = 2.0 Manual Selection: Fast: Phi Golden Mid: e Natural Slow: Pi Circular Visualization: Gradient Clouds: ON Neon Glow: ON (Medium) Pulsing Bar: ON (Medium) Signal Highlights: ON (Light Fill) Table: ON (Top Right, Small) Signals: Golden/Death Cross: ON STRONG Signals: ON Stop Loss: OFF (while learning) Timeframe for learning: H1 or H4 5. Can I use only one EMA? No, minimum 2 EMAs (Fast and Slow) for signal generation. Mid EMA is optional: With Mid EMA = more reliable but rarer signals Without Mid EMA = more signals but less strict filtering Recommendation: Start with 3 EMAs (Fast/Mid/Slow), then experiment 6. Does the indicator work on cryptocurrencies? Yes, works excellently! Especially good on: Bitcoin (BTC) Ethereum (ETH) Major altcoins (SOL, BNB, XRP) Recommended settings for crypto: Fast: Delta Adaptive (Base 10-15, Sensitivity 2.5-3.0) Mid: Pi Circular (2Pi) Slow: e Natural (e²) Base: 5-10 Timeframe: M15, H1, H4 Crypto market features: High volatility → use Delta Adaptive 24/7 trading → set alerts Sharp movements → wide stops 7. Can I trade only with this indicator? Technically yes, but NOT recommended. Best approach - combine with: Price Action - support/resistance levels, candle patterns Volume - movement strength confirmation Fibonacci - retracement and extension levels RSI/MACD - divergences and overbought/oversold Fundamental analysis - news, company reports Hellenic Matrix: Excellently determines trend and its strength Provides clear entry/exit points Doesn't consider fundamentals Doesn't see major levels 8. Why do Gradient Clouds change color? Color depends on EMA order: Phi-Pi Cloud: Blue - Pi EMA above Phi EMA (bullish alignment) Gold - Phi EMA above Pi EMA (bearish alignment) Pi-e Cloud: Green - e EMA above Pi EMA (bullish alignment) Blue - Pi EMA above e EMA (bearish alignment) Color change = EMA order change = possible trend change 9. What is Momentum % in the table? Momentum % = percentage deviation of price from Fast EMA Formula: Momentum = ((Close - Fast EMA) / Fast EMA) × 100 Interpretation: +0.5% to +2% - normal bullish momentum +2% to +5% - strong bullish momentum +5% and above - overheating (correction possible) -0.5% to -2% - normal bearish momentum -2% to -5% - strong bearish momentum -5% and below - oversold (bounce possible) Usage: Monitor momentum during STRONG signals Large momentum = don't enter (wait for pullback) Small momentum = good entry point 10. How to configure for scalping? Settings for scalping (M1-M5): Base Multiplier: 3-5 Source: close or hlc3 (smoother) Fast: Delta Adaptive (Base 8-12, Sensitivity 3.0) Mid: None (for more signals) Slow: Phi Golden (Phi²) or Pi Circular (1Pi) Visualization: - Gradient Clouds: ON (helps see strength) - Neon Glow: OFF (doesn't clutter chart) - Pulsing Bar: ON (quick assessment) - Signal Highlights: ON Signals: - Golden/Death Cross: ON - STRONG Signals: ON - Stop Loss: ON (1.0-1.5 ATR, R:R 1.5-2.0) Scalping rules: Trade only STRONG signals Enter on bounce from Fast EMA Tight stops (10-20 pips) Quick take profit (+1R to +2R) Don't hold through news 11. How to configure for long-term investing? Settings for investing (D1-W1): Base Multiplier: 20-30 Source: close Fast: Phi Golden (Phi³ or Phi⁴) Mid: e Natural (e²) Slow: Pi Circular (3Pi or 4Pi) Visualization: - Gradient Clouds: ON - Neon Glow: ON (Medium) - Everything else - to taste Signals: - Golden/Death Cross: ON - STRONG Signals: ON - Stop Loss: OFF (use percentage stop) Investing rules: Enter only on STRONG signals Hold while STRONG active (weeks/months) Stop below Slow EMA or -10% Take profit: by company targets or +50-100% Ignore short-term pullbacks 12. What if indicator slows down chart? Indicator is optimized, but if it slows: Disable unnecessary visual effects: Neon Glow: OFF (saves 8 plots) Gradient Clouds: ON but low quality Lambda Wave EMA: OFF (if not using) Reduce number of active EMAs: Sigma Composite: OFF Lambda Wave: OFF Leave only Phi, Pi, e, Delta Simplify settings: Pulsing Bar: OFF Greek Labels: OFF Info Table: smaller size 13. Can I use on different timeframes simultaneously? Yes! Multi-timeframe analysis is very powerful: Classic scheme: Higher TF (D1, W1) - determine global trend Wait for STRONG signal This is our trading direction Middle TF (H4, H1) - look for confirmation STRONG signal in same direction Precise entry zone Lower TF (M15, M5) - entry point Golden Cross or bounce from Fast EMA Precise stop loss Example: W1: STRONG BUY active (global uptrend) H4: STRONG BUY appeared (confirmation) M15: Wait for Golden Cross or bounce from Fast EMA → ENTRY Advantages: Maximum reliability Clear timeframe hierarchy Large targets 14. How does indicator work on news? Delta Adaptive EMA adapts excellently to news: Before news: Low volatility → Delta EMA becomes fast → pulls to price During news: Sharp volatility spike → Delta EMA slows → filters noise After news: Volatility normalizes → Delta EMA returns to normal Recommendations: Don't trade at news release moment (spreads widen) Wait for STRONG signal after news (2-5 bars) Use Delta Adaptive as Fast EMA for quick reaction Widen stops by 50-100% during important news Advanced Techniques Technique 1: "Divergences with EMA" Idea: Look for discrepancies between price and Fast EMA Bullish divergence: Price makes lower low Fast EMA makes higher low = Possible reversal up Bearish divergence: Price makes higher high Fast EMA makes lower high = Possible reversal down How to trade: Find divergence Wait for STRONG signal in divergence direction Enter on confirmation Technique 2: "EMA Tunnel" Idea: Use space between Fast and Slow EMA as "tunnel" Rules: Wide tunnel - strong trend, hold position Narrow tunnel - weak trend or consolidation, caution Tunnel narrowing - trend weakening, prepare to exit Tunnel widening - trend strengthening, can add Visually: Gradient Clouds show this automatically! Trading: Enter on STRONG signal (tunnel starts widening) Hold while tunnel wide Exit when tunnel starts narrowing Technique 3: "Wave Analysis with Lambda" Idea: Lambda Wave EMA creates sinusoid matching market cycles Setup: Lambda Base Period: 30 Lambda Wave Amplitude: 0.5 Lambda Wave Frequency: 50 (adjusted to asset cycle) How to find correct Frequency: Look at historical cycles (distance between local highs) Average distance = your Frequency Example: if highs every 40-60 bars, set Frequency = 50 Trading: Enter when Lambda Wave at bottom of sinusoid (growth potential) Exit when Lambda Wave at top (fall potential) Combine with STRONG signals Technique 4: "Cluster Analysis" Idea: When all EMAs gather in narrow cluster = powerful breakout soon Cluster signs: All EMAs (Phi, Pi, e, Delta) within 0.5-1% of each other Gradient Clouds almost invisible Price jumping around all EMAs Trading: Identify cluster (all EMAs close) Determine breakout direction (where more volume, higher TFs direction) Wait for breakout and STRONG signal Enter on confirmation Target = cluster size × 3-5 This is very powerful technique for big moves! Technique 5: "Sigma as Dynamic Level" Idea: Sigma Composite EMA = average of all EMAs = magnetic level Usage: Enable Sigma Composite (Weighted Average) Sigma works as dynamic support/resistance Price often returns to Sigma before trend continuation Trading: In trend: Enter on bounces from Sigma In range: Fade moves from Sigma (trade return to Sigma) On breakout: Sigma becomes support/resistance Risk Management Basic Rules 1. Position Size Conservative: 1% of capital per trade Moderate: 2% of capital per trade (recommended) Aggressive: 3-5% (only for experienced) Calculation formula: Lot Size = (Capital × Risk%) / (Stop in pips × Pip value) 2. Risk/Reward Ratio Minimum: 1:1.5 Standard: 1:2 (recommended) Optimal: 1:3 Aggressive: 1:5+ 3. Maximum Drawdown Daily: -3% to -5% Weekly: -7% to -10% Monthly: -15% to -20% Upon reaching limit → STOP trading until end of period Position Management Strategies 1. Fixed Stop Method: Stop below/above Fast EMA or local extreme DON'T move stop against position Can move to breakeven For whom: Beginners, conservative traders 2. Trailing by Fast EMA Method: Each day (or bar) move stop to Fast EMA level Position closes when price breaks Fast EMA Advantages: Stay in trend as long as possible Automatically exit on reversal For whom: Trend followers, swing traders 3. Partial Exit Method: 50% of position close at +2R 50% hold with trailing by Mid EMA or Slow EMA Advantages: Lock profit Leave position for big move Psychologically comfortable For whom: Universal method (recommended) 4. Pyramiding Method: First entry on STRONG signal (50% of planned position) Add 25% on pullback to Fast EMA Add another 25% on pullback to Mid EMA Overall stop below Slow EMA Advantages: Average entry price Reduce risk Increase profit in strong trends Caution: Works only in trends In range leads to losses For whom: Experienced traders Trading Psychology Correct Mindset 1. Indicator is a tool, not holy grail Indicator shows probability, not guarantee There will be losing trades - this is normal Important is series statistics, not one trade 2. Trust the system If STRONG signal appeared - enter Don't search for "perfect" moment Follow trading plan 3. Patience STRONG signals don't appear every day Better miss signal than enter against trend Quality over quantity 4. Discipline Always set stop loss Don't move stop against position Don't increase risk after losses Beginner Mistakes 1. "I know better than indicator" Indicator says STRONG BUY, but you think "too high, will wait for pullback" Result: miss profitable move Solution: Trust signals or don't use indicator 2. "Will reverse now for sure" Trading against STRONG trend Result: stops, stops, stops Solution: Trend is your friend, trade with trend 3. "Will hold a bit more" Don't exit when STRONG signal disappears Greed eats profit Solution: If signal gone - exit! 4. "I'll recover" After losses double risk Result: huge losses Solution: Fixed % risk ALWAYS 5. "I don't like this signal" Skip signals because of "feeling" Result: inconsistency, no statistics Solution: Trade ALL signals or clearly define filters Trading Journal What to Record For each trade: 1. Entry/exit date and time 2. Instrument and timeframe 3. Signal type Golden Cross STRONG BUY STRONG SELL Death Cross 4. Indicator settings Fast/Mid/Slow EMA Base Multiplier Other parameters 5. Chart screenshot Entry moment Exit moment 6. Trade parameters Position size Stop loss Take Profit R:R 7. Result Profit/Loss in $ Profit/Loss in % Profit/Loss in R 8. Notes What was right What was wrong Emotions during trade Lessons Journal Analysis Analyze weekly: 1. Win Rate Win Rate = (Profitable trades / All trades) × 100% Good: 50-60% Excellent: 60-70% Exceptional: 70%+ 2. Average R Average R = Sum of all R / Number of trades Good: +0.5R Excellent: +1.0R Exceptional: +1.5R+ 3. Profit Factor Profit Factor = Total profit / Total losses Good: 1.5+ Excellent: 2.0+ Exceptional: 3.0+ 4. Maximum Drawdown Track consecutive losses If more than 5 in row - stop, check system 5. Best/Worst Trades What was common in best trades? (do more) What was common in worst trades? (avoid) Pre-Trade Checklist Technical Analysis STRONG signal active (BUY or SELL) All EMAs properly aligned (Fast > Mid > Slow or reverse) Price on correct side of Fast EMA Gradient Clouds confirm trend Pulsing Bar shows STRONG state Momentum % in normal range (not overheated) No close strong levels against direction Higher timeframe doesn't contradict Risk Management Position size calculated (1-2% risk) Stop loss set Take profit calculated (minimum 1:2) R:R satisfactory Daily/weekly risk limit not exceeded No other open correlated positions Fundamental Analysis No important news in coming hours Market session appropriate (liquidity) No contradicting fundamentals Understand why asset is moving Psychology Calm and thinking clearly No emotions from previous trades Ready to accept loss at stop Following trading plan Not revenging market for past losses If at least one point is NO - think twice before entering! Learning Roadmap Week 1: Familiarization Goals: Install and configure indicator Study all EMA types Understand visualization Tasks: Add indicator to chart Test all Fast/Mid/Slow settings Play with Base Multiplier on different timeframes Observe Gradient Clouds and Pulsing Bar Study Info Table Result: Comfort with indicator interface Week 2: Signals Goals: Learn to recognize all signal types Understand difference between Golden Cross and STRONG Tasks: Find 10 Golden Cross examples in history Find 10 STRONG BUY examples in history Compare their results (which worked better) Set up alerts Get 5 real alerts Result: Understanding signals Week 3: Demo Trading Goals: Start trading signals on demo account Gather statistics Tasks: Open demo account Trade ONLY STRONG signals Keep journal (minimum 20 trades) Don't change indicator settings Strictly follow stop losses Result: 20+ documented trades Week 4: Analysis Goals: Analyze demo trading results Optimize approach Tasks: Calculate win rate and average R Find patterns in profitable trades Find patterns in losing trades Adjust approach (not indicator!) Write trading plan Result: Trading plan on 1 page Month 2: Improvement Goals: Deepen understanding Add additional techniques Tasks: Study multi-timeframe analysis Test combinations with Price Action Try advanced techniques (divergences, tunnels) Continue demo trading (minimum 50 trades) Achieve stable profitability on demo Result: Win rate 55%+ and Profit Factor 1.5+ Month 3: Real Trading Goals: Transition to real account Maintain discipline Tasks: Open small real account Trade minimum lots Strictly follow trading plan DON'T increase risk Focus on process, not profit Result: Psychological comfort on real Month 4+: Scaling Goals: Increase account Become consistently profitable Tasks: With 60%+ win rate can increase risk to 2% Upon doubling account can add capital Continue keeping journal Periodically review and improve strategy Share experience with community Result: Stable profitability month after month Additional Resources Recommended Reading Technical Analysis: "Technical Analysis of Financial Markets" - John Murphy "Trading in the Zone" - Mark Douglas (psychology) "Market Wizards" - Jack Schwager (trader interviews) EMA and Moving Averages: "Moving Averages 101" - Steve Burns Articles on Investopedia about EMA Risk Management: "The Mathematics of Money Management" - Ralph Vince "Trade Your Way to Financial Freedom" - Van K. Tharp Trading Journals: Edgewonk (paid, very powerful) Tradervue (free version + premium) Excel/Google Sheets (free) Screeners: TradingView Stock Screener Finviz (stocks) CoinMarketCap (crypto) Conclusion Hellenic EMA Matrix is a powerful tool based on universal mathematical constants of nature. The indicator combines: Mathematical elegance - Phi, Pi, e instead of arbitrary numbers Premium visualization - Neon Glow, Gradient Clouds, Pulsing Bar Reliable signals - STRONG BUY/SELL work on all timeframes Flexibility - 6 EMA types, adaptation to any trading style Automation - auto-sorting EMAs, SL/TP calculation, alerts Key Success Principles: Simplicity - start with basic settings (Phi/Pi/e, Base=10) Discipline - follow STRONG signals strictly Patience - wait for quality setups Risk Management - 1-2% per trade, ALWAYS Journal - document every trade Learning - constantly improve skills Remember: Indicator shows probability, not guarantee Important is series statistics, not one trade Psychology more important than technique Quality more important than quantity Process more important than result Acknowledgments Thank you for using Hellenic EMA Matrix - Alpha Omega Premium! The indicator was created with love for mathematics, markets, and beautiful visualization. Wishing you profitable trading! Guide Version: 1.0 Date: 2025 Compatibility: Pine Script v6, TradingView "In the simplicity of mathematical constants lies the complexity of market movements"
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Markov Chain [3D] | FractalystWhat exactly is a Markov Chain? This indicator uses a Markov Chain model to analyze, quantify, and visualize the transitions between market regimes (Bull, Bear, Neutral) on your chart. It dynamically detects these regimes in real-time, calculates transition probabilities, and displays them as animated 3D spheres and arrows, giving traders intuitive insight into current and future market conditions. How does a Markov Chain work, and how should I read this spheres-and-arrows diagram? Think of three weather modes: Sunny, Rainy, Cloudy. Each sphere is one mode. The loop on a sphere means “stay the same next step” (e.g., Sunny again tomorrow). The arrows leaving a sphere show where things usually go next if they change (e.g., Sunny moving to Cloudy). Some paths matter more than others. A more prominent loop means the current mode tends to persist. A more prominent outgoing arrow means a change to that destination is the usual next step. Direction isn’t symmetric: moving Sunny→Cloudy can behave differently than Cloudy→Sunny. Now relabel the spheres to markets: Bull, Bear, Neutral. Spheres: market regimes (uptrend, downtrend, range). Self‑loop: tendency for the current regime to continue on the next bar. Arrows: the most common next regime if a switch happens. How to read: Start at the sphere that matches current bar state. If the loop stands out, expect continuation. If one outgoing path stands out, that switch is the typical next step. Opposite directions can differ (Bear→Neutral doesn’t have to match Neutral→Bear). What states and transitions are shown? The three market states visualized are: Bullish (Bull): Upward or strong-market regime. Bearish (Bear): Downward or weak-market regime. Neutral: Sideways or range-bound regime. Bidirectional animated arrows and probability labels show how likely the market is to move from one regime to another (e.g., Bull → Bear or Neutral → Bull). How does the regime detection system work? You can use either built-in price returns (based on adaptive Z-score normalization) or supply three custom indicators (such as volume, oscillators, etc.). Values are statistically normalized (Z-scored) over a configurable lookback period. The normalized outputs are classified into Bull, Bear, or Neutral zones. If using three indicators, their regime signals are averaged and smoothed for robustness. How are transition probabilities calculated? On every confirmed bar, the algorithm tracks the sequence of detected market states, then builds a rolling window of transitions. The code maintains a transition count matrix for all regime pairs (e.g., Bull → Bear). Transition probabilities are extracted for each possible state change using Laplace smoothing for numerical stability, and frequently updated in real-time. What is unique about the visualization? 3D animated spheres represent each regime and change visually when active. Animated, bidirectional arrows reveal transition probabilities and allow you to see both dominant and less likely regime flows. Particles (moving dots) animate along the arrows, enhancing the perception of regime flow direction and speed. All elements dynamically update with each new price bar, providing a live market map in an intuitive, engaging format. Can I use custom indicators for regime classification? Yes! Enable the "Custom Indicators" switch and select any three chart series as inputs. These will be normalized and combined (each with equal weight), broadening the regime classification beyond just price-based movement. What does the “Lookback Period” control? Lookback Period (default: 100) sets how much historical data builds the probability matrix. Shorter periods adapt faster to regime changes but may be noisier. Longer periods are more stable but slower to adapt. How is this different from a Hidden Markov Model (HMM)? It sets the window for both regime detection and probability calculations. Lower values make the system more reactive, but potentially noisier. Higher values smooth estimates and make the system more robust. How is this Markov Chain different from a Hidden Markov Model (HMM)? Markov Chain (as here): All market regimes (Bull, Bear, Neutral) are directly observable on the chart. The transition matrix is built from actual detected regimes, keeping the model simple and interpretable. Hidden Markov Model: The actual regimes are unobservable ("hidden") and must be inferred from market output or indicator "emissions" using statistical learning algorithms. HMMs are more complex, can capture more subtle structure, but are harder to visualize and require additional machine learning steps for training. A standard Markov Chain models transitions between observable states using a simple transition matrix, while a Hidden Markov Model assumes the true states are hidden (latent) and must be inferred from observable “emissions” like price or volume data. In practical terms, a Markov Chain is transparent and easier to implement and interpret; an HMM is more expressive but requires statistical inference to estimate hidden states from data. Markov Chain: states are observable; you directly count or estimate transition probabilities between visible states. This makes it simpler, faster, and easier to validate and tune. HMM: states are hidden; you only observe emissions generated by those latent states. Learning involves machine learning/statistical algorithms (commonly Baum–Welch/EM for training and Viterbi for decoding) to infer both the transition dynamics and the most likely hidden state sequence from data. How does the indicator avoid “repainting” or look-ahead bias? All regime changes and matrix updates happen only on confirmed (closed) bars, so no future data is leaked, ensuring reliable real-time operation. Are there practical tuning tips? Tune the Lookback Period for your asset/timeframe: shorter for fast markets, longer for stability. Use custom indicators if your asset has unique regime drivers. Watch for rapid changes in transition probabilities as early warning of a possible regime shift. Who is this indicator for? Quants and quantitative researchers exploring probabilistic market modeling, especially those interested in regime-switching dynamics and Markov models. Programmers and system developers who need a probabilistic regime filter for systematic and algorithmic backtesting: The Markov Chain indicator is ideally suited for programmatic integration via its bias output (1 = Bull, 0 = Neutral, -1 = Bear). Although the visualization is engaging, the core output is designed for automated, rules-based workflows—not for discretionary/manual trading decisions. Developers can connect the indicator’s output directly to their Pine Script logic (using input.source()), allowing rapid and robust backtesting of regime-based strategies. It acts as a plug-and-play regime filter: simply plug the bias output into your entry/exit logic, and you have a scientifically robust, probabilistically-derived signal for filtering, timing, position sizing, or risk regimes. The MC's output is intentionally "trinary" (1/0/-1), focusing on clear regime states for unambiguous decision-making in code. If you require nuanced, multi-probability or soft-label state vectors, consider expanding the indicator or stacking it with a probability-weighted logic layer in your scripting. Because it avoids subjectivity, this approach is optimal for systematic quants, algo developers building backtested, repeatable strategies based on probabilistic regime analysis. What's the mathematical foundation behind this? The mathematical foundation behind this Markov Chain indicator—and probabilistic regime detection in finance—draws from two principal models: the (standard) Markov Chain and the Hidden Markov Model (HMM). How to use this indicator programmatically? The Markov Chain indicator automatically exports a bias value (+1 for Bullish, -1 for Bearish, 0 for Neutral) as a plot visible in the Data Window. This allows you to integrate its regime signal into your own scripts and strategies for backtesting, automation, or live trading. Step-by-Step Integration with Pine Script (input.source) Add the Markov Chain indicator to your chart. This must be done first, since your custom script will "pull" the bias signal from the indicator's plot. In your strategy, create an input using input.source() Example: //@version=5 strategy("MC Bias Strategy Example") mcBias = input.source(close, "MC Bias Source") After saving, go to your script’s settings. For the “MC Bias Source” input, select the plot/output of the Markov Chain indicator (typically its bias plot). Use the bias in your trading logic Example (long only on Bull, flat otherwise): if mcBias == 1 strategy.entry("Long", strategy.long) else strategy.close("Long") For more advanced workflows, combine mcBias with additional filters or trailing stops. How does this work behind-the-scenes? TradingView’s input.source() lets you use any plot from another indicator as a real-time, “live” data feed in your own script (source). The selected bias signal is available to your Pine code as a variable, enabling logical decisions based on regime (trend-following, mean-reversion, etc.). This enables powerful strategy modularity : decouple regime detection from entry/exit logic, allowing fast experimentation without rewriting core signal code. Integrating 45+ Indicators with Your Markov Chain — How & Why The Enhanced Custom Indicators Export script exports a massive suite of over 45 technical indicators—ranging from classic momentum (RSI, MACD, Stochastic, etc.) to trend, volume, volatility, and oscillator tools—all pre-calculated, centered/scaled, and available as plots. // Enhanced Custom Indicators Export - 45 Technical Indicators // Comprehensive technical analysis suite for advanced market regime detection //@version=6 indicator('Enhanced Custom Indicators Export | Fractalyst', shorttitle='Enhanced CI Export', overlay=false, scale=scale.right, max_labels_count=500, max_lines_count=500) // |----- Input Parameters -----| // momentum_group = "Momentum Indicators" trend_group = "Trend Indicators" volume_group = "Volume Indicators" volatility_group = "Volatility Indicators" oscillator_group = "Oscillator Indicators" display_group = "Display Settings" // Common lengths length_14 = input.int(14, "Standard Length (14)", minval=1, maxval=100, group=momentum_group) length_20 = input.int(20, "Medium Length (20)", minval=1, maxval=200, group=trend_group) length_50 = input.int(50, "Long Length (50)", minval=1, maxval=200, group=trend_group) // Display options show_table = input.bool(true, "Show Values Table", group=display_group) table_size = input.string("Small", "Table Size", options= , group=display_group) // |----- MOMENTUM INDICATORS (15 indicators) -----| // // 1. RSI (Relative Strength Index) rsi_14 = ta.rsi(close, length_14) rsi_centered = rsi_14 - 50 // 2. Stochastic Oscillator stoch_k = ta.stoch(close, high, low, length_14) stoch_d = ta.sma(stoch_k, 3) stoch_centered = stoch_k - 50 // 3. Williams %R williams_r = ta.stoch(close, high, low, length_14) - 100 // 4. MACD (Moving Average Convergence Divergence) = ta.macd(close, 12, 26, 9) // 5. Momentum (Rate of Change) momentum = ta.mom(close, length_14) momentum_pct = (momentum / close ) * 100 // 6. Rate of Change (ROC) roc = ta.roc(close, length_14) // 7. Commodity Channel Index (CCI) cci = ta.cci(close, length_20) // 8. Money Flow Index (MFI) mfi = ta.mfi(close, length_14) mfi_centered = mfi - 50 // 9. Awesome Oscillator (AO) ao = ta.sma(hl2, 5) - ta.sma(hl2, 34) // 10. Accelerator Oscillator (AC) ac = ao - ta.sma(ao, 5) // 11. Chande Momentum Oscillator (CMO) cmo = ta.cmo(close, length_14) // 12. Detrended Price Oscillator (DPO) dpo = close - ta.sma(close, length_20) // 13. Price Oscillator (PPO) ppo = ta.sma(close, 12) - ta.sma(close, 26) ppo_pct = (ppo / ta.sma(close, 26)) * 100 // 14. TRIX trix_ema1 = ta.ema(close, length_14) trix_ema2 = ta.ema(trix_ema1, length_14) trix_ema3 = ta.ema(trix_ema2, length_14) trix = ta.roc(trix_ema3, 1) * 10000 // 15. Klinger Oscillator klinger = ta.ema(volume * (high + low + close) / 3, 34) - ta.ema(volume * (high + low + close) / 3, 55) // 16. Fisher Transform fisher_hl2 = 0.5 * (hl2 - ta.lowest(hl2, 10)) / (ta.highest(hl2, 10) - ta.lowest(hl2, 10)) - 0.25 fisher = 0.5 * math.log((1 + fisher_hl2) / (1 - fisher_hl2)) // 17. Stochastic RSI stoch_rsi = ta.stoch(rsi_14, rsi_14, rsi_14, length_14) stoch_rsi_centered = stoch_rsi - 50 // 18. Relative Vigor Index (RVI) rvi_num = ta.swma(close - open) rvi_den = ta.swma(high - low) rvi = rvi_den != 0 ? rvi_num / rvi_den : 0 // 19. Balance of Power (BOP) bop = (close - open) / (high - low) // |----- TREND INDICATORS (10 indicators) -----| // // 20. Simple Moving Average Momentum sma_20 = ta.sma(close, length_20) sma_momentum = ((close - sma_20) / sma_20) * 100 // 21. Exponential Moving Average Momentum ema_20 = ta.ema(close, length_20) ema_momentum = ((close - ema_20) / ema_20) * 100 // 22. Parabolic SAR sar = ta.sar(0.02, 0.02, 0.2) sar_trend = close > sar ? 1 : -1 // 23. Linear Regression Slope lr_slope = ta.linreg(close, length_20, 0) - ta.linreg(close, length_20, 1) // 24. Moving Average Convergence (MAC) mac = ta.sma(close, 10) - ta.sma(close, 30) // 25. Trend Intensity Index (TII) tii_sum = 0.0 for i = 1 to length_20 tii_sum += close > close ? 1 : 0 tii = (tii_sum / length_20) * 100 // 26. Ichimoku Cloud Components ichimoku_tenkan = (ta.highest(high, 9) + ta.lowest(low, 9)) / 2 ichimoku_kijun = (ta.highest(high, 26) + ta.lowest(low, 26)) / 2 ichimoku_signal = ichimoku_tenkan > ichimoku_kijun ? 1 : -1 // 27. MESA Adaptive Moving Average (MAMA) mama_alpha = 2.0 / (length_20 + 1) mama = ta.ema(close, length_20) mama_momentum = ((close - mama) / mama) * 100 // 28. Zero Lag Exponential Moving Average (ZLEMA) zlema_lag = math.round((length_20 - 1) / 2) zlema_data = close + (close - close ) zlema = ta.ema(zlema_data, length_20) zlema_momentum = ((close - zlema) / zlema) * 100 // |----- VOLUME INDICATORS (6 indicators) -----| // // 29. On-Balance Volume (OBV) obv = ta.obv // 30. Volume Rate of Change (VROC) vroc = ta.roc(volume, length_14) // 31. Price Volume Trend (PVT) pvt = ta.pvt // 32. Negative Volume Index (NVI) nvi = 0.0 nvi := volume < volume ? nvi + ((close - close ) / close ) * nvi : nvi // 33. Positive Volume Index (PVI) pvi = 0.0 pvi := volume > volume ? pvi + ((close - close ) / close ) * pvi : pvi // 34. Volume Oscillator vol_osc = ta.sma(volume, 5) - ta.sma(volume, 10) // 35. Ease of Movement (EOM) eom_distance = high - low eom_box_height = volume / 1000000 eom = eom_box_height != 0 ? eom_distance / eom_box_height : 0 eom_sma = ta.sma(eom, length_14) // 36. Force Index force_index = volume * (close - close ) force_index_sma = ta.sma(force_index, length_14) // |----- VOLATILITY INDICATORS (10 indicators) -----| // // 37. Average True Range (ATR) atr = ta.atr(length_14) atr_pct = (atr / close) * 100 // 38. Bollinger Bands Position bb_basis = ta.sma(close, length_20) bb_dev = 2.0 * ta.stdev(close, length_20) bb_upper = bb_basis + bb_dev bb_lower = bb_basis - bb_dev bb_position = bb_dev != 0 ? (close - bb_basis) / bb_dev : 0 bb_width = bb_dev != 0 ? (bb_upper - bb_lower) / bb_basis * 100 : 0 // 39. Keltner Channels Position kc_basis = ta.ema(close, length_20) kc_range = ta.ema(ta.tr, length_20) kc_upper = kc_basis + (2.0 * kc_range) kc_lower = kc_basis - (2.0 * kc_range) kc_position = kc_range != 0 ? (close - kc_basis) / kc_range : 0 // 40. Donchian Channels Position dc_upper = ta.highest(high, length_20) dc_lower = ta.lowest(low, length_20) dc_basis = (dc_upper + dc_lower) / 2 dc_position = (dc_upper - dc_lower) != 0 ? (close - dc_basis) / (dc_upper - dc_lower) : 0 // 41. Standard Deviation std_dev = ta.stdev(close, length_20) std_dev_pct = (std_dev / close) * 100 // 42. Relative Volatility Index (RVI) rvi_up = ta.stdev(close > close ? close : 0, length_14) rvi_down = ta.stdev(close < close ? close : 0, length_14) rvi_total = rvi_up + rvi_down rvi_volatility = rvi_total != 0 ? (rvi_up / rvi_total) * 100 : 50 // 43. Historical Volatility hv_returns = math.log(close / close ) hv = ta.stdev(hv_returns, length_20) * math.sqrt(252) * 100 // 44. Garman-Klass Volatility gk_vol = math.log(high/low) * math.log(high/low) - (2*math.log(2)-1) * math.log(close/open) * math.log(close/open) gk_volatility = math.sqrt(ta.sma(gk_vol, length_20)) * 100 // 45. Parkinson Volatility park_vol = math.log(high/low) * math.log(high/low) parkinson = math.sqrt(ta.sma(park_vol, length_20) / (4 * math.log(2))) * 100 // 46. Rogers-Satchell Volatility rs_vol = math.log(high/close) * math.log(high/open) + math.log(low/close) * math.log(low/open) rogers_satchell = math.sqrt(ta.sma(rs_vol, length_20)) * 100 // |----- OSCILLATOR INDICATORS (5 indicators) -----| // // 47. Elder Ray Index elder_bull = high - ta.ema(close, 13) elder_bear = low - ta.ema(close, 13) elder_power = elder_bull + elder_bear // 48. Schaff Trend Cycle (STC) stc_macd = ta.ema(close, 23) - ta.ema(close, 50) stc_k = ta.stoch(stc_macd, stc_macd, stc_macd, 10) stc_d = ta.ema(stc_k, 3) stc = ta.stoch(stc_d, stc_d, stc_d, 10) // 49. Coppock Curve coppock_roc1 = ta.roc(close, 14) coppock_roc2 = ta.roc(close, 11) coppock = ta.wma(coppock_roc1 + coppock_roc2, 10) // 50. Know Sure Thing (KST) kst_roc1 = ta.roc(close, 10) kst_roc2 = ta.roc(close, 15) kst_roc3 = ta.roc(close, 20) kst_roc4 = ta.roc(close, 30) kst = ta.sma(kst_roc1, 10) + 2*ta.sma(kst_roc2, 10) + 3*ta.sma(kst_roc3, 10) + 4*ta.sma(kst_roc4, 15) // 51. Percentage Price Oscillator (PPO) ppo_line = ((ta.ema(close, 12) - ta.ema(close, 26)) / ta.ema(close, 26)) * 100 ppo_signal = ta.ema(ppo_line, 9) ppo_histogram = ppo_line - ppo_signal // |----- PLOT MAIN INDICATORS -----| // // Plot key momentum indicators plot(rsi_centered, title="01_RSI_Centered", color=color.purple, linewidth=1) plot(stoch_centered, title="02_Stoch_Centered", color=color.blue, linewidth=1) plot(williams_r, title="03_Williams_R", color=color.red, linewidth=1) plot(macd_histogram, title="04_MACD_Histogram", color=color.orange, linewidth=1) plot(cci, title="05_CCI", color=color.green, linewidth=1) // Plot trend indicators plot(sma_momentum, title="06_SMA_Momentum", color=color.navy, linewidth=1) plot(ema_momentum, title="07_EMA_Momentum", color=color.maroon, linewidth=1) plot(sar_trend, title="08_SAR_Trend", color=color.teal, linewidth=1) plot(lr_slope, title="09_LR_Slope", color=color.lime, linewidth=1) plot(mac, title="10_MAC", color=color.fuchsia, linewidth=1) // Plot volatility indicators plot(atr_pct, title="11_ATR_Pct", color=color.yellow, linewidth=1) plot(bb_position, title="12_BB_Position", color=color.aqua, linewidth=1) plot(kc_position, title="13_KC_Position", color=color.olive, linewidth=1) plot(std_dev_pct, title="14_StdDev_Pct", color=color.silver, linewidth=1) plot(bb_width, title="15_BB_Width", color=color.gray, linewidth=1) // Plot volume indicators plot(vroc, title="16_VROC", color=color.blue, linewidth=1) plot(eom_sma, title="17_EOM", color=color.red, linewidth=1) plot(vol_osc, title="18_Vol_Osc", color=color.green, linewidth=1) plot(force_index_sma, title="19_Force_Index", color=color.orange, linewidth=1) plot(obv, title="20_OBV", color=color.purple, linewidth=1) // Plot additional oscillators plot(ao, title="21_Awesome_Osc", color=color.navy, linewidth=1) plot(cmo, title="22_CMO", color=color.maroon, linewidth=1) plot(dpo, title="23_DPO", color=color.teal, linewidth=1) plot(trix, title="24_TRIX", color=color.lime, linewidth=1) plot(fisher, title="25_Fisher", color=color.fuchsia, linewidth=1) // Plot more momentum indicators plot(mfi_centered, title="26_MFI_Centered", color=color.yellow, linewidth=1) plot(ac, title="27_AC", color=color.aqua, linewidth=1) plot(ppo_pct, title="28_PPO_Pct", color=color.olive, linewidth=1) plot(stoch_rsi_centered, title="29_StochRSI_Centered", color=color.silver, linewidth=1) plot(klinger, title="30_Klinger", color=color.gray, linewidth=1) // Plot trend continuation plot(tii, title="31_TII", color=color.blue, linewidth=1) plot(ichimoku_signal, title="32_Ichimoku_Signal", color=color.red, linewidth=1) plot(mama_momentum, title="33_MAMA_Momentum", color=color.green, linewidth=1) plot(zlema_momentum, title="34_ZLEMA_Momentum", color=color.orange, linewidth=1) plot(bop, title="35_BOP", color=color.purple, linewidth=1) // Plot volume continuation plot(nvi, title="36_NVI", color=color.navy, linewidth=1) plot(pvi, title="37_PVI", color=color.maroon, linewidth=1) plot(momentum_pct, title="38_Momentum_Pct", color=color.teal, linewidth=1) plot(roc, title="39_ROC", color=color.lime, linewidth=1) plot(rvi, title="40_RVI", color=color.fuchsia, linewidth=1) // Plot volatility continuation plot(dc_position, title="41_DC_Position", color=color.yellow, linewidth=1) plot(rvi_volatility, title="42_RVI_Volatility", color=color.aqua, linewidth=1) plot(hv, title="43_Historical_Vol", color=color.olive, linewidth=1) plot(gk_volatility, title="44_GK_Volatility", color=color.silver, linewidth=1) plot(parkinson, title="45_Parkinson_Vol", color=color.gray, linewidth=1) // Plot final oscillators plot(rogers_satchell, title="46_RS_Volatility", color=color.blue, linewidth=1) plot(elder_power, title="47_Elder_Power", color=color.red, linewidth=1) plot(stc, title="48_STC", color=color.green, linewidth=1) plot(coppock, title="49_Coppock", color=color.orange, linewidth=1) plot(kst, title="50_KST", color=color.purple, linewidth=1) // Plot final indicators plot(ppo_histogram, title="51_PPO_Histogram", color=color.navy, linewidth=1) plot(pvt, title="52_PVT", color=color.maroon, linewidth=1) // |----- Reference Lines -----| // hline(0, "Zero Line", color=color.gray, linestyle=hline.style_dashed, linewidth=1) hline(50, "Midline", color=color.gray, linestyle=hline.style_dotted, linewidth=1) hline(-50, "Lower Midline", color=color.gray, linestyle=hline.style_dotted, linewidth=1) hline(25, "Upper Threshold", color=color.gray, linestyle=hline.style_dotted, linewidth=1) hline(-25, "Lower Threshold", color=color.gray, linestyle=hline.style_dotted, linewidth=1) // |----- Enhanced Information Table -----| // if show_table and barstate.islast table_position = position.top_right table_text_size = table_size == "Tiny" ? size.tiny : table_size == "Small" ? size.small : size.normal var table info_table = table.new(table_position, 3, 18, bgcolor=color.new(color.white, 85), border_width=1, border_color=color.gray) // Headers table.cell(info_table, 0, 0, 'Category', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70)) table.cell(info_table, 1, 0, 'Indicator', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70)) table.cell(info_table, 2, 0, 'Value', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70)) // Key Momentum Indicators table.cell(info_table, 0, 1, 'MOMENTUM', text_color=color.purple, text_size=table_text_size, bgcolor=color.new(color.purple, 90)) table.cell(info_table, 1, 1, 'RSI Centered', text_color=color.purple, text_size=table_text_size) table.cell(info_table, 2, 1, str.tostring(rsi_centered, '0.00'), text_color=color.purple, text_size=table_text_size) table.cell(info_table, 0, 2, '', text_color=color.blue, text_size=table_text_size) table.cell(info_table, 1, 2, 'Stoch Centered', text_color=color.blue, text_size=table_text_size) table.cell(info_table, 2, 2, str.tostring(stoch_centered, '0.00'), text_color=color.blue, text_size=table_text_size) table.cell(info_table, 0, 3, '', text_color=color.red, text_size=table_text_size) table.cell(info_table, 1, 3, 'Williams %R', text_color=color.red, text_size=table_text_size) table.cell(info_table, 2, 3, str.tostring(williams_r, '0.00'), text_color=color.red, text_size=table_text_size) table.cell(info_table, 0, 4, '', text_color=color.orange, text_size=table_text_size) table.cell(info_table, 1, 4, 'MACD Histogram', text_color=color.orange, text_size=table_text_size) table.cell(info_table, 2, 4, str.tostring(macd_histogram, '0.000'), text_color=color.orange, text_size=table_text_size) table.cell(info_table, 0, 5, '', text_color=color.green, text_size=table_text_size) table.cell(info_table, 1, 5, 'CCI', text_color=color.green, text_size=table_text_size) table.cell(info_table, 2, 5, str.tostring(cci, '0.00'), text_color=color.green, text_size=table_text_size) // Key Trend Indicators table.cell(info_table, 0, 6, 'TREND', text_color=color.navy, text_size=table_text_size, bgcolor=color.new(color.navy, 90)) table.cell(info_table, 1, 6, 'SMA Momentum %', text_color=color.navy, text_size=table_text_size) table.cell(info_table, 2, 6, str.tostring(sma_momentum, '0.00'), text_color=color.navy, text_size=table_text_size) table.cell(info_table, 0, 7, '', text_color=color.maroon, text_size=table_text_size) table.cell(info_table, 1, 7, 'EMA Momentum %', text_color=color.maroon, text_size=table_text_size) table.cell(info_table, 2, 7, str.tostring(ema_momentum, '0.00'), text_color=color.maroon, text_size=table_text_size) table.cell(info_table, 0, 8, '', text_color=color.teal, text_size=table_text_size) table.cell(info_table, 1, 8, 'SAR Trend', text_color=color.teal, text_size=table_text_size) table.cell(info_table, 2, 8, str.tostring(sar_trend, '0'), text_color=color.teal, text_size=table_text_size) table.cell(info_table, 0, 9, '', text_color=color.lime, text_size=table_text_size) table.cell(info_table, 1, 9, 'Linear Regression', text_color=color.lime, text_size=table_text_size) table.cell(info_table, 2, 9, str.tostring(lr_slope, '0.000'), text_color=color.lime, text_size=table_text_size) // Key Volatility Indicators table.cell(info_table, 0, 10, 'VOLATILITY', text_color=color.yellow, text_size=table_text_size, bgcolor=color.new(color.yellow, 90)) table.cell(info_table, 1, 10, 'ATR %', text_color=color.yellow, text_size=table_text_size) table.cell(info_table, 2, 10, str.tostring(atr_pct, '0.00'), text_color=color.yellow, text_size=table_text_size) table.cell(info_table, 0, 11, '', text_color=color.aqua, text_size=table_text_size) table.cell(info_table, 1, 11, 'BB Position', text_color=color.aqua, text_size=table_text_size) table.cell(info_table, 2, 11, str.tostring(bb_position, '0.00'), text_color=color.aqua, text_size=table_text_size) table.cell(info_table, 0, 12, '', text_color=color.olive, text_size=table_text_size) table.cell(info_table, 1, 12, 'KC Position', text_color=color.olive, text_size=table_text_size) table.cell(info_table, 2, 12, str.tostring(kc_position, '0.00'), text_color=color.olive, text_size=table_text_size) // Key Volume Indicators table.cell(info_table, 0, 13, 'VOLUME', text_color=color.blue, text_size=table_text_size, bgcolor=color.new(color.blue, 90)) table.cell(info_table, 1, 13, 'Volume ROC', text_color=color.blue, text_size=table_text_size) table.cell(info_table, 2, 13, str.tostring(vroc, '0.00'), text_color=color.blue, text_size=table_text_size) table.cell(info_table, 0, 14, '', text_color=color.red, text_size=table_text_size) table.cell(info_table, 1, 14, 'EOM', text_color=color.red, text_size=table_text_size) table.cell(info_table, 2, 14, str.tostring(eom_sma, '0.000'), text_color=color.red, text_size=table_text_size) // Key Oscillators table.cell(info_table, 0, 15, 'OSCILLATORS', text_color=color.purple, text_size=table_text_size, bgcolor=color.new(color.purple, 90)) table.cell(info_table, 1, 15, 'Awesome Osc', text_color=color.blue, text_size=table_text_size) table.cell(info_table, 2, 15, str.tostring(ao, '0.000'), text_color=color.blue, text_size=table_text_size) table.cell(info_table, 0, 16, '', text_color=color.red, text_size=table_text_size) table.cell(info_table, 1, 16, 'Fisher Transform', text_color=color.red, text_size=table_text_size) table.cell(info_table, 2, 16, str.tostring(fisher, '0.000'), text_color=color.red, text_size=table_text_size) // Summary Statistics table.cell(info_table, 0, 17, 'SUMMARY', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.gray, 70)) table.cell(info_table, 1, 17, 'Total Indicators: 52', text_color=color.black, text_size=table_text_size) regime_color = rsi_centered > 10 ? color.green : rsi_centered < -10 ? color.red : color.gray regime_text = rsi_centered > 10 ? "BULLISH" : rsi_centered < -10 ? "BEARISH" : "NEUTRAL" table.cell(info_table, 2, 17, regime_text, text_color=regime_color, text_size=table_text_size) This makes it the perfect “indicator backbone” for quantitative and systematic traders who want to prototype, combine, and test new regime detection models—especially in combination with the Markov Chain indicator. How to use this script with the Markov Chain for research and backtesting: Add the Enhanced Indicator Export to your chart. Every calculated indicator is available as an individual data stream. Connect the indicator(s) you want as custom input(s) to the Markov Chain’s “Custom Indicators” option. In the Markov Chain indicator’s settings, turn ON the custom indicator mode. For each of the three custom indicator inputs, select the exported plot from the Enhanced Export script—the menu lists all 45+ signals by name. This creates a powerful, modular regime-detection engine where you can mix-and-match momentum, trend, volume, or custom combinations for advanced filtering. Backtest regime logic directly. Once you’ve connected your chosen indicators, the Markov Chain script performs regime detection (Bull/Neutral/Bear) based on your selected features—not just price returns. The regime detection is robust, automatically normalized (using Z-score), and outputs bias (1, -1, 0) for plug-and-play integration. Export the regime bias for programmatic use. As described above, use input.source() in your Pine Script strategy or system and link the bias output. You can now filter signals, control trade direction/size, or design pairs-trading that respect true, indicator-driven market regimes. With this framework, you’re not limited to static or simplistic regime filters. You can rigorously define, test, and refine what “market regime” means for your strategies—using the technical features that matter most to you. Optimize your signal generation by backtesting across a universe of meaningful indicator blends. Enhance risk management with objective, real-time regime boundaries. Accelerate your research: iterate quickly, swap indicator components, and see results with minimal code changes. Automate multi-asset or pairs-trading by integrating regime context directly into strategy logic. Add both scripts to your chart, connect your preferred features, and start investigating your best regime-based trades—entirely within the TradingView ecosystem. References & Further Reading Ang, A., & Bekaert, G. (2002). “Regime Switches in Interest Rates.” Journal of Business & Economic Statistics, 20(2), 163–182. Hamilton, J. D. (1989). “A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle.” Econometrica, 57(2), 357–384. Markov, A. A. (1906). "Extension of the Limit Theorems of Probability Theory to a Sum of Variables Connected in a Chain." The Notes of the Imperial Academy of Sciences of St. Petersburg. Guidolin, M., & Timmermann, A. (2007). “Asset Allocation under Multivariate Regime Switching.” Journal of Economic Dynamics and Control, 31(11), 3503–3544. Murphy, J. J. (1999). Technical Analysis of the Financial Markets. New York Institute of Finance. Brock, W., Lakonishok, J., & LeBaron, B. (1992). “Simple Technical Trading Rules and the Stochastic Properties of Stock Returns.” Journal of Finance, 47(5), 1731–1764. Zucchini, W., MacDonald, I. L., & Langrock, R. (2017). Hidden Markov Models for Time Series: An Introduction Using R (2nd ed.). Chapman and Hall/CRC. On Quantitative Finance and Markov Models: Lo, A. W., & Hasanhodzic, J. (2009). The Heretics of Finance: Conversations with Leading Practitioners of Technical Analysis. Bloomberg Press. Patterson, S. (2016). The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution. Penguin Press. TradingView Pine Script Documentation: www.tradingview.com TradingView Blog: “Use an Input From Another Indicator With Your Strategy” www.tradingview.com GeeksforGeeks: “What is the Difference Between Markov Chains and Hidden Markov Models?” www.geeksforgeeks.org What makes this indicator original and unique? - On‑chart, real‑time Markov. The chain is drawn directly on your chart. You see the current regime, its tendency to stay (self‑loop), and the usual next step (arrows) as bars confirm. - Source‑agnostic by design. The engine runs on any series you select via input.source() — price, your own oscillator, a composite score, anything you compute in the script. - Automatic normalization + regime mapping. Different inputs live on different scales. The script standardizes your chosen source and maps it into clear regimes (e.g., Bull / Bear / Neutral) without you micromanaging thresholds each time. - Rolling, bar‑by‑bar learning. Transition tendencies are computed from a rolling window of confirmed bars. What you see is exactly what the market did in that window. - Fast experimentation. Switch the source, adjust the window, and the Markov view updates instantly. It’s a rapid way to test ideas and feel regime persistence/switch behavior. Integrate your own signals (using input.source()) - In settings, choose the Source . This is powered by input.source() . - Feed it price, an indicator you compute inside the script, or a custom composite series. - The script will automatically normalize that series and process it through the Markov engine, mapping it to regimes and updating the on‑chart spheres/arrows in real time. Credits: Deep gratitude to @RicardoSantos for both the foundational Markov chain processing engine and inspiring open-source contributions, which made advanced probabilistic market modeling accessible to the TradingView community. Special thanks to @Alien_Algorithms for the innovative and visually stunning 3D sphere logic that powers the indicator’s animated, regime-based visualization. Disclaimer This tool summarizes recent behavior. It is not financial advice and not a guarantee of future results.
مؤشر Pine Script®
من ‎Fractalyst‎
8
VMDM - Volume, Momentum & Divergence Master [BullByte]VMDM - Volume, Momentum and Divergence Master Educational Multi-Layer Market Structure Analysis System Multi-factor divergence engine that scores RSI momentum, volume pressure, and institutional footprints into one non-repainting confluence rating (0-100). WHAT THIS INDICATOR IS VMDM is an educational indicator designed to teach traders how to recognize high-probability reversal and continuation patterns by analyzing four independent market dimensions simultaneously. Instead of relying on a single indicator that may produce frequent false signals, VMDM creates a confluence-based scoring system that weights multiple confirmation factors, helping you understand which setups have stronger technical backing and which are lower quality. This is NOT a trading system or signal generator. It is a learning tool that visualizes complex market structure concepts in an accessible format for both coders and non-coders. THE PROBLEM IT SOLVES Most traders face these common challenges: Challenge 1 - Indicator Overload: Running RSI, volume analysis, and divergence detection separately creates chart clutter and conflicting signals. You waste time cross-referencing multiple windows trying to determine if all factors align. Challenge 2 - False Divergences: Standard divergence indicators trigger on every minor pivot, creating noise. Many divergences fail because they lack supporting evidence from volume or market structure. Challenge 3 - Missed Context: A bullish RSI divergence means nothing if it occurs during weak volume or in the middle of strong distribution. Context determines quality. Challenge 4 - Repainting Confusion: Many divergence scripts repaint, showing perfect historical signals that never actually triggered in real-time, leading to false confidence. Challenge 5 - Institutional Pattern Recognition: Absorption zones, stop hunts, and exhaustion patterns are taught in trading education but difficult to identify systematically without manual analysis. VMDM addresses all five challenges by combining complementary analytical layers into one transparent, non-repainting, confluence-weighted system with visual clarity. WHY THIS SPECIFIC COMBINATION - MASHUP JUSTIFICATION This indicator is NOT a random mashup of popular indicators. Each of the four layers serves a specific analytical purpose and together they create a complete market structure assessment framework. THE FOUR ANALYTICAL LAYERS LAYER 1 - RSI MOMENTUM DIVERGENCE (Trend Exhaustion Detection) Purpose: Identifies when price momentum is weakening before price itself reverses. Why RSI: The Relative Strength Index measures momentum on a bounded 0-100 scale, making divergence detection mathematically consistent across all assets and timeframes. Unlike raw price oscillators, RSI normalizes momentum regardless of volatility regime. How It Contributes: Divergence between price pivots and RSI pivots reveals early momentum exhaustion. A lower price low with a higher RSI low (bullish regular divergence) signals sellers are losing strength even as price makes new lows. This is the PRIMARY signal generator in VMDM. Limitation If Used Alone: RSI divergence by itself produces many false signals because momentum can remain weak during continued trends. It needs confirmation from volume and structural evidence. LAYER 2 - VOLUME PRESSURE ANALYSIS (Buying vs Selling Intensity) Purpose: Quantifies whether the current bar's volume reflects buying pressure or selling pressure based on where price closed within the bar's range. Methodology: Instead of just measuring volume size, VMDM calculates WHERE in the bar range the close occurred. A close near the high on high volume indicates strong buying absorption. A close near the low indicates selling pressure. The calculation accounts for wick size (wicks reduce pressure quality) and uses percentile ranking over a lookback period to normalize pressure strength on a 0-100 scale. Formula Concept: Buy Pressure = Volume × (Close - Low) / (High - Low) × Wick Quality Factor Sell Pressure = Volume × (High - Close) / (High - Low) × Wick Quality Factor Net Pressure = Buy Pressure - Sell Pressure Pressure Strength = Percentile Rank of Net Pressure over lookback period Why Percentile Ranking: Absolute volume varies by asset and session. Percentile ranking makes 85th percentile pressure on low-volume crypto comparable to 85th percentile pressure on high-volume forex. How It Contributes: When a bullish divergence occurs at a pivot low AND pressure strength is above 60 (strong buying), this adds 25 confluence points. It confirms that the divergence is occurring during actual accumulation, not just weak selling. Limitation If Used Alone: Pressure analysis shows current bar intensity but cannot identify trend exhaustion or reversal timing. High buying pressure can exist during a strong uptrend with no reversal imminent. LAYER 3 - BEHAVIORAL FOOTPRINT PATTERNS (Volume Anomaly Detection) CRITICAL DISCLAIMER: The terms "institutional footprint," "absorption," "stop hunt," and "exhaustion" used in this indicator are EDUCATIONAL LABELS for specific price and volume behavioral patterns. These patterns are detected through technical analysis of publicly available price, volume, and bar structure data. This indicator does NOT have access to actual institutional order flow, market maker data, broker stop-loss locations, or any non-public data source. These pattern names are used because they are common terminology in trading education to describe these technical behaviors. The analysis is interpretive and based on observable price action, not privileged information. Purpose: Detect volume anomalies and price patterns that historically correlate with potential reversal zones or trend continuation failure. Pattern Type 1 - Absorption (Labeled as "ACCUMULATION" or "DISTRIBUTION") Detection Criteria: Volume is more than 2x the moving average AND bar range is less than 50 percent of the average bar range. Interpretation: High volume compressed into a tight range suggests large participants are absorbing supply (accumulation) or distribution (distribution) without allowing price to move significantly. This often precedes directional moves once absorption completes. Visual: Colored box zone highlighting the absorption area. Pattern Type 2 - Stop Hunt (Labeled as "BULL HUNT" or "BEAR HUNT") Detection Criteria: Price penetrates a recent 10-bar high or low by a small margin (0.2 percent), then closes back inside the range on above-average volume (1.5x+). Interpretation: Price briefly spikes beyond recent structure (likely triggering stop losses placed just beyond obvious levels) then reverses. This is a classic false breakout pattern often seen before reversals. Visual: Label at the wick extreme showing hunt direction. Pattern Type 3 - Exhaustion (Labeled as "SELL EXHAUST" or "BUY EXHAUST") Detection Criteria: Lower wick is more than 2.5x the body size with volume above 1.8x average and RSI below 35 (sell exhaustion), OR upper wick more than 2.5x body size with volume above 1.8x average and RSI above 65 (buy exhaustion). Interpretation: Large wicks with high volume and extreme RSI suggest aggressive buying or selling was met with equally aggressive rejection. This exhaustion often marks short-term extremes. Visual: Label showing exhaustion type. How These Contribute: When a divergence forms at a pivot AND one of these behavioral patterns is active, the confluence score increases by 20 points. This confirms the divergence is occurring during structural anomaly activity, not just normal price flow. Limitation If Used Alone: These patterns can occur mid-trend and do not indicate direction without momentum context. Absorption in a strong uptrend may just be continuation accumulation. LAYER 4 - CONFLUENCE SCORING MATRIX (Quality Weighting System) Purpose: Translate all detected conditions into a single 0-100 quality score so you can objectively compare setups. Scoring Breakdown: Divergence Present: +30 points (primary signal) Pressure Confirmation: +25 points (volume supports direction) Behavioral Footprint Active: +20 points (structural anomaly present) RSI Extreme: +15 points (RSI below 30 or above 70 at pivot) Volume Spike: +10 points (current volume above 1.5x average) Maximum Possible Score: 100 points Why These Weights: The weights reflect reliability hierarchy based on backtesting observation. Divergence is the core signal (30 points), but without volume confirmation (25 points) many fail. Behavioral patterns add meaningful context (20 points). RSI extremes and volume spikes are secondary confirmations (15 and 10 points). Quality Tiers: 90-100: TEXTBOOK (all factors aligned) 75-89: HIGH QUALITY (strong confluence) 60-74: VALID (meets minimum threshold) Below 60: DEVELOPING (not displayed unless threshold lowered) How It Contributes: The confluence score allows you to filter noise. You can set your minimum quality threshold in settings. Higher thresholds (75+) show fewer but higher-quality patterns. Lower thresholds (50-60) show more patterns but include lower-confidence setups. This teaches you to distinguish strong setups from weak ones. Limitation: Confluence scoring is historical observation-based, not predictive guarantee. A 95-point setup can still fail. The score represents technical alignment, not future certainty. WHY THIS COMBINATION WORKS TOGETHER Each layer addresses a limitation in the others: RSI Divergence identifies WHEN momentum is exhausting (timing) Volume Pressure confirms WHETHER the exhaustion is accompanied by opposite-side accumulation (confirmation) Behavioral Footprint shows IF structural anomalies support the reversal hypothesis (context) Confluence Scoring weights ALL factors into an objective quality metric (filtering) Using only RSI divergence gives you timing without confirmation. Using only volume pressure gives you intensity without directional context. Using only pattern detection gives you anomalies without trend exhaustion context. Using all four together creates a complete analytical framework where each layer compensates for the others' weaknesses. This is not a mashup for the sake of combining indicators. It is a structured analytical system where each component has a defined role in a multi-dimensional market assessment process. HOW TO READ THE INDICATOR - VISUAL ELEMENTS GUIDE VMDM displays up to five visual layer types. You can enable or disable each layer independently in settings under "Visual Layers." VISUAL LAYER 1 - MARKET STRUCTURE (Pivot Points and Lines) What You See: Small labels at swing highs and lows marked "PH" (Pivot High) and "PL" (Pivot Low) with horizontal dashed lines extending right from each pivot. What It Means: These are CONFIRMED pivots, not real-time. A pivot low appears AFTER the required right-side confirmation bars pass (default 3 bars). This creates a delay but prevents repainting. The pivot only appears once it is mathematically confirmed. The horizontal lines represent support (from pivot lows) and resistance (from pivot highs) levels where price previously found significant rejection. Color Coding: Green label and line: Pivot Low (potential support) Red label and line: Pivot High (potential resistance) How To Use: These pivots are the foundation for divergence detection. Divergence is only calculated between confirmed pivots, ensuring all signals are non-repainting. The lines help you see historical structure levels. VISUAL LAYER 2 - PRESSURE ZONES (Background Color) What You See: Subtle background color shading on bars - light green or light red tint. What It Means: This visualizes volume pressure strength in real-time. Color Coding: Light Green Background: Pressure Strength above 70 (strong buying pressure - price closing near highs on volume) Light Red Background: Pressure Strength below 30 (strong selling pressure - price closing near lows on volume) No Color: Neutral pressure (pressure between 30-70) How To Use: When a bullish divergence pattern appears during green pressure zones, it suggests the divergence is forming during accumulation. When a bearish divergence appears during red zones, distribution is occurring. Pressure zones help you filter divergences - those forming in supportive pressure environments have higher probability. VISUAL LAYER 3 - DIVERGENCE LINES (Dotted Connectors) What You See: Dotted lines connecting two pivot points (either two pivot lows or two pivot highs). What It Means: A divergence has been detected between those two pivots. The line connects the price pivots where RSI showed opposite behavior. Color Coding: Bright Green Line: Bullish divergence (regular or hidden) Bright Red Line: Bearish divergence (regular or hidden) How To Use: The divergence line appears ONLY after the second pivot is confirmed (delayed by right-side confirmation bars). This is intentional to prevent repainting. When you see the line appear, it means: For Bullish Regular Divergence: Price made a lower low (second pivot lower than first) RSI made a higher low (RSI at second pivot higher than first) Interpretation: Downtrend losing momentum For Bullish Hidden Divergence: Price made a higher low (second pivot higher than first) RSI made a lower low (RSI at second pivot lower than first) Interpretation: Uptrend continuation likely (pullback within uptrend) For Bearish Regular Divergence: Price made a higher high (second pivot higher than first) RSI made a lower high (RSI at second pivot lower than first) Interpretation: Uptrend losing momentum For Bearish Hidden Divergence: Price made a lower high (second pivot lower than first) RSI made a higher high (RSI at second pivot higher than first) Interpretation: Downtrend continuation likely (bounce within downtrend) If "Show Consolidated Analysis Label" is disabled, a small label will appear on the divergence line showing the divergence type abbreviation. VISUAL LAYER 4 - BEHAVIORAL FOOTPRINT MARKERS What You See: Boxes, labels, and markers at specific bars showing pattern detection. ABSORPTION ZONES (Boxes): Colored rectangular boxes spanning one or more bars. Purple Box: Accumulation absorption zone (high volume, tight range, bullish close) Red Box: Distribution absorption zone (high volume, tight range, bearish close) If absorption continues for multiple consecutive bars, the box extends and a counter appears in the label showing how many bars the absorption lasted. What It Means: Large volume is being absorbed without significant price movement. This often precedes directional breakouts once the absorption phase completes. STOP HUNT MARKERS (Labels): Small labels below or above wicks labeled "BULL HUNT" or "BEAR HUNT" (may show bar count if consecutive). What It Means: BULL HUNT : Price spiked below recent lows then reversed back up on volume - likely triggered sell stops before reversing BEAR HUNT : Price spiked above recent highs then reversed back down on volume - likely triggered buy stops before reversing EXHAUSTION MARKERS (Labels): Labels showing "SELL EXHAUST" or "BUY EXHAUST." What It Means: SELL EXHAUST : Large lower wick with high volume and low RSI - aggressive selling met with strong rejection BUY EXHAUST : Large upper wick with high volume and high RSI - aggressive buying met with strong rejection How To Use: These markers help you identify WHERE structural anomalies occurred. When a divergence signal appears AT THE SAME TIME as one of these patterns, the confluence score increases. You are looking for alignment - divergence + behavioral pattern + pressure confirmation = high-quality setup. VISUAL LAYER 5 - CONSOLIDATED ANALYSIS LABEL (Main Pattern Signal) What You See: A large label appearing at pivot points (or in real-time mode, at current bar) containing full pattern analysis. Label Appearance: Depending on your "Use Compact Label Format" setting: COMPACT MODE (Single Line): Example: "BULLISH REGULAR | Q:HIGH QUALITY C:82" Breakdown: BULLISH REGULAR: Divergence type detected Q:HIGH QUALITY: Pattern quality tier C:82: Confluence score (82 out of 100) FULL MODE (Multi-Line Detailed): Example: PATTERN DETECTED ------------------- BULLISH REGULAR Quality: HIGH QUALITY Price: Lower Low Momentum: Higher Low Signal: Weakening Downtrend CONFLUENCE: 82/100 ------------------- Divergence: 30 Pressure: 25 Institutional: 20 RSI Extreme: 0 Volume: 10 Breakdown: Top section: Pattern type and quality Middle section: Divergence explanation (what price did vs what RSI did) Bottom section: Confluence score with itemized breakdown showing which factors contributed Label Position: In Confirmed modes: Label appears AT the pivot point (delayed by confirmation bars) In Real-time mode: Label appears at current bar as conditions develop Label Color: Gold: Textbook quality (90+ confluence) Green: High quality (75-89 confluence) Blue: Valid quality (60-74 confluence) How To Use: This is your primary decision-making label. When it appears: Check the divergence type (regular divergences are reversal signals, hidden divergences are continuation signals) Review the quality tier (textbook and high quality have better historical win rates) Examine the confluence breakdown to see which factors are present and which are missing Look at the chart context (trend, support/resistance, timeframe) Use this information to assess whether the setup aligns with your strategy The label does NOT tell you to buy or sell. It tells you a technical pattern has formed and provides the quality assessment. Your trading decision must incorporate risk management, market context, and your strategy rules. UNDERSTANDING THE THREE DETECTION MODES VMDM offers three signal detection modes in settings to accommodate different trading styles and learning objectives. MODE 1: "Confluence Only (Real-Time)" How It Works: Displays signals AS THEY DEVELOP on the current bar without waiting for pivot confirmation. The system calculates confluence score from pressure, volume, RSI extremes, and behavioral patterns. Divergence signals are NOT required in this mode. Delay: ZERO - signals appear immediately. Use Case: Real-time scanning for high-confluence zones without divergence requirement. Useful for intraday traders who want immediate alerts when multiple factors align. Tradeoff: More frequent signals but includes setups without confirmed divergence. Higher false signal rate. Signals can change as the bar develops (not repainting in historical bars, but current bar updates). Visual Behavior: Labels appear at the current bar. No divergence lines unless divergence happens to be present. MODE 2: "Divergence + Confluence (Confirmed)" - DEFAULT RECOMMENDED How It Works: Full system engagement. Signals appear ONLY when: A pivot is confirmed (requires right-side confirmation bars to pass) Divergence is detected between current pivot and previous pivot Total confluence score meets or exceeds your minimum threshold Delay: Equal to your "Pivot Right Bars" setting (default 3 bars). This means signals appear 3 bars AFTER the actual pivot formed. Use Case: Highest-quality, non-repainting signals for swing traders and learners who want to study confirmed pattern completion. Tradeoff: Delayed signals. You will not receive the signal until confirmation occurs. In fast-moving markets, price may have already moved significantly by the time the signal appears. Visual Behavior: Labels appear at the historical pivot location (in the past). Divergence lines connect the two pivots. This is the most educational mode because it shows completed, confirmed patterns. Non-Repainting Guarantee: Yes. Once a signal appears, it never disappears or changes. MODE 3: "Divergence + Confluence (Relaxed)" How It Works: Same as Confirmed mode but with adaptive thresholds. If confluence is very high (10 points above threshold), the signal may appear even if some factors are weak. If divergence is present but confluence is slightly below threshold (within 10 points), it may still appear. Delay: Same as Confirmed mode (right-side confirmation bars). Use Case: Slightly more signals than Confirmed mode for traders willing to accept near-threshold setups. Tradeoff: More signals but lower average quality than Confirmed mode. Visual Behavior: Same as Confirmed mode. DASHBOARD GUIDE - READING THE METRICS The dashboard appears in the corner of your chart (position selectable in settings) and provides real-time market state analysis. You can choose between four dashboard detail levels in settings: Off, Compact, Optimized (default), Full. DASHBOARD ROW EXPLANATIONS ROW 1 - Header Information Left: Current symbol and timeframe Center: "VMDM " Right: Version number ROW 2 - Mode and Delay Shows which detection mode you are using and the signal delay. Example: "CONFIRMED | Delay: 3 bars" This reminds you that signals in confirmed mode appear 3 bars after the pivot forms. ROW 3 - Market Regime Format: "TREND UP HV" or "RANGING NV" First Part - Trend State: TREND UP: 20 EMA above 50 EMA with strong separation TREND DOWN: 20 EMA below 50 EMA with strong separation RANGING: EMAs close together, low trend strength TRANSITION: Between trending and ranging states Second Part - Volatility State: HV: High Volatility (current ATR more than 1.3x the 50-bar average ATR) NV: Normal Volatility (current ATR between 0.7x and 1.3x average) LV: Low Volatility (current ATR less than 0.7x average) Third Column: Volatility ratio (example: "1.45x" means current ATR is 1.45 times normal) How To Use: Regime context helps you interpret signals. Reversal divergences are more reliable in ranging or transitional regimes. Continuation divergences (hidden) are more reliable in trending regimes. High volatility means wider stops may be needed. ROW 4 - Pressure Shows current volume pressure state. Format: "BUYING | ██████████░░░░░░░░░" States: BUYING : Pressure strength above 60 (closes near highs) SELLING : Pressure strength below 40 (closes near lows) NEUTRAL : Pressure strength between 40-60 Bar Visualization: Each block represents 10 percentile points. A full bar (10 filled blocks) = 100th percentile pressure. Color: Green for buying, red for selling, gray for neutral. How To Use: When pressure aligns with divergence direction (bullish divergence during buying pressure), confluence is stronger. ROW 5 - Volume and RSI Format: "1.8x | RSI 68 | OB" First Value: Current volume ratio (1.8x = volume is 1.8 times the moving average) Second Value: Current RSI reading Third Value: RSI state OB: Overbought (RSI above 70) OS: Oversold (RSI below 30) Blank: Neutral RSI How To Use: Volume spikes (above 1.5x) during divergence formation add confluence. RSI extremes at pivots add confluence. ROW 6 - Behavioral Footprint Format: "BULL HUNT | 2 bars" Shows the most recent behavioral pattern detected and how long ago. States: ACCUMULATION / DISTRIBUTION: Absorption detected BULL HUNT / BEAR HUNT: Stop hunt detected SELL EXHAUST / BUY EXHAUST: Exhaustion detected SCANNING: No recent pattern NOW: Pattern is active on current bar How To Use: When footprint activity is recent (within 50 bars) or active now, it adds context to divergence signals forming in that area. ROW 7 - Current Pattern Shows the divergence type currently detected (if any). Examples: "BULLISH REGULAR", "BEARISH HIDDEN", "Scanning..." Quality: Shows pattern quality (TEXTBOOK, HIGH QUALITY, VALID) How To Use: This tells you what type of signal is active. Regular divergences are reversal setups. Hidden divergences are continuation setups. ROW 8 - Session Summary Format: "14 events | A3 H8 E3" First Value: Total institutional events this session Breakdown: A: Absorption events H: Stop hunt events E: Exhaustion events How To Use: High event counts suggest an active, volatile session with frequent structural anomalies. Low counts suggest quiet, orderly price action. ROW 9 - Confluence Score (Optimized/Full mode only) Format: "78/100 | ████████░░" Shows current real-time confluence score even if no pattern is confirmed yet. How To Use: Watch this in real-time to see how close you are to pattern formation. When it exceeds your threshold and divergence forms, a signal will appear (after confirmation delay). ROW 10 - Patterns Studied (Optimized/Full mode only) Format: "47 patterns | 12 bars ago" First Value: Total confirmed patterns detected since chart loaded Second Value: How many bars since the last confirmed pattern appeared How To Use: Helps you understand pattern frequency on your selected symbol and timeframe. If many bars have passed since last pattern, market may be trending without reversal opportunities. ROW 11 - Bull/Bear Ratio (Optimized/Full mode only) Format: "28:19 | BULL" Shows count of bullish vs bearish patterns detected. Balance: BULL: More bullish patterns detected (suggests market has had more bullish reversals/continuations) BEAR: More bearish patterns detected BAL: Equal counts How To Use: Extreme imbalances can indicate directional bias in the studied period. A heavily bullish ratio in a downtrend might suggest frequent failed rallies (bearish continuation). Context matters. ROW 12 - Volume Ratio Detail (Optimized/Full mode only) Shows current volume vs average volume in absolute terms. Example: "1.4x | 45230 / 32300" How To Use: Confirms whether current activity is above or below normal. ROW 13 - Last Institutional Event (Full mode only) Shows the most recent institutional pattern type and how many bars ago it occurred. Example: "DISTRIBUTION | 23 bars" How To Use: Tracks recency of last anomaly for context. SETTINGS GUIDE - EVERY PARAMETER EXPLAINED PERFORMANCE SECTION Enable All Visuals (Master Toggle) Default: ON What It Does: Master kill switch for ALL visual elements (labels, lines, boxes, background colors, dashboard). When OFF, only plot outputs remain (invisible unless you open data window). When To Change: Turn OFF on mobile devices, 1-second charts, or slow computers to improve performance. You can still receive alerts even with visuals disabled. Impact: Dramatic performance improvement when OFF, but you lose all visual feedback. Maximum Object History Default: 50 | Range: 10-100 What It Does: Limits how many of each object type (labels, lines, boxes) are kept in memory. Older objects beyond this limit are deleted. When To Change: Lower to 20-30 on fast timeframes (1-minute charts) to prevent slowdown. Increase to 100 on daily charts if you want more historical pattern visibility. Impact: Lower values = better performance but less historical visibility. Higher values = more history visible but potential slowdown on fast timeframes. Alert Cooldown (Bars) Default: 5 | Range: 1-50 What It Does: Minimum number of bars that must pass before another alert of the same type can fire. Prevents alert spam when multiple patterns form in quick succession. When To Change: Increase to 20+ on 1-minute charts to reduce noise. Decrease to 1-2 on daily charts if you want every pattern alerted. Impact: Higher cooldown = fewer alerts. Lower cooldown = more alerts. USER EXPERIENCE SECTION Show Enhanced Tooltips Default: ON What It Does: Enables detailed hover-over tooltips on labels and visual elements. When To Change: Turn OFF if you encounter Pine Script compilation errors related to tooltip arguments (rare, platform-specific issue). Impact: Minimal. Just adds helpful hover text. MARKET STRUCTURE DETECTION SECTION Pivot Left Bars Default: 3 | Range: 2-10 What It Does: Number of bars to the LEFT of the center bar that must be higher (for pivot low) or lower (for pivot high) than the center bar for a pivot to be valid. Example: With value 3, a pivot low requires the center bar's low to be lower than the 3 bars to its left. When To Change: Increase to 5-7 on noisy timeframes (1-minute charts) to filter insignificant pivots Decrease to 2 on slow timeframes (daily charts) to catch more pivots Impact: Higher values = fewer, more significant pivots = fewer signals. Lower values = more frequent pivots = more signals but more noise. Pivot Right Bars Default: 3 | Range: 2-10 What It Does: Number of bars to the RIGHT of the center bar that must pass for confirmation. This creates the non-repainting delay. Example: With value 3, a pivot is confirmed 3 bars AFTER it forms. When To Change: Increase to 5-7 for slower, more confirmed signals (better for swing trading) Decrease to 2 for faster signals (better for intraday, but still non-repainting) Impact: Higher values = longer delay but more reliable confirmation. Lower values = faster signals but less confirmation. This setting directly controls your signal delay in Confirmed and Relaxed modes. Minimum Confluence Score Default: 60 | Range: 40-95 What It Does: The threshold score required for a pattern to be displayed. Patterns with confluence scores below this threshold are not shown. When To Change: Increase to 75+ if you only want high-quality textbook setups (fewer signals) Decrease to 50-55 if you want to see more developing patterns (more signals, lower average quality) Impact: This is your primary signal filter. Higher threshold = fewer, higher-quality signals. Lower threshold = more signals but includes weaker setups. Recommended starting point is 60-65. TECHNICAL PERIODS SECTION RSI Period Default: 14 | Range: 5-50 What It Does: Lookback period for RSI calculation. When To Change: Decrease to 9-10 for faster, more sensitive RSI that detects shorter-term momentum changes Increase to 21-28 for slower, smoother RSI that filters noise Impact: Lower values make RSI more volatile (more frequent extremes and divergences). Higher values make RSI smoother (fewer but more significant divergences). 14 is industry standard. Volume Moving Average Period Default: 20 | Range: 10-200 What It Does: Lookback period for calculating average volume. Current volume is compared to this average to determine volume ratio. When To Change: Decrease to 10-14 for shorter-term volume comparison (more sensitive to recent volume changes) Increase to 50-100 for longer-term volume comparison (smoother, less sensitive) Impact: Lower values make volume ratio more volatile. Higher values make it more stable. 20 is standard. ATR Period Default: 14 | Range: 5-100 What It Does: Lookback period for Average True Range calculation used for volatility measurement and label positioning. When To Change: Rarely needs adjustment. Use 7-10 for faster volatility response, 21-28 for slower. Impact: Affects volatility ratio calculation and visual label spacing. Minimal impact on signals. Pressure Percentile Lookback Default: 50 | Range: 10-300 What It Does: Lookback period for calculating volume pressure percentile ranking. Your current pressure is ranked against the pressure of the last X bars. When To Change: Decrease to 20-30 for shorter-term pressure context (more responsive to recent changes) Increase to 100-200 for longer-term pressure context (smoother rankings) Impact: Lower values make pressure strength more sensitive to recent bars. Higher values provide more stable, long-term pressure assessment. Capped at 300 for performance reasons. SIGNAL DETECTION SECTION Signal Detection Mode Default: "Divergence + Confluence (Confirmed)" Options: Confluence Only (Real-time) Divergence + Confluence (Confirmed) Divergence + Confluence (Relaxed) What It Does: Selects which detection logic mode to use (see "Understanding The Three Detection Modes" section above). When To Change: Use Confirmed for learning and non-repainting signals. Use Real-time for live scanning without divergence requirement. Use Relaxed for slightly more signals than Confirmed. Impact: Fundamentally changes when and how signals appear. VISUAL LAYERS SECTION All toggles default to ON. Each controls visibility of one visual layer: Show Market Structure: Pivot markers and support/resistance lines Show Pressure Zones: Background color shading Show Divergence Lines: Dotted lines connecting pivots Show Institutional Footprint Markers: Absorption boxes, hunt labels, exhaustion labels Show Consolidated Analysis Label: Main pattern detection label Use Compact Label Format Default: OFF What It Does: Switches consolidated label between single-line compact format and multi-line detailed format. When To Change: Turn ON if you find full labels too large or distracting. Impact: Visual clarity vs. information density tradeoff. DASHBOARD SECTION Dashboard Mode Default: "Optimized" Options: Off, Compact, Optimized, Full What It Does: Controls how much information the dashboard displays. Off: No dashboard Compact: 8 rows (essential metrics only) Optimized: 12 rows (recommended balance) Full: 13 rows (every available metric) Dashboard Position Default: "Top Right" Options: Top Right, Top Left, Bottom Right, Bottom Left What It Does: Screen corner where dashboard appears. HOW TO USE VMDM - PRACTICAL WORKFLOW STEP 1 - INITIAL SETUP Add VMDM to your chart Select your detection mode (Confirmed recommended for learning) Set your minimum confluence score (start with 60-65) Adjust pivot parameters if needed (default 3/3 is good for most timeframes) Enable the visual layers you want to see STEP 2 - CHART ANALYSIS Let the indicator load and analyze historical data Review the patterns that appear historically Examine the confluence scores - notice which patterns had higher scores Observe which patterns occurred during supportive pressure zones Notice the divergence line connections - understand what price vs RSI did STEP 3 - PATTERN RECOGNITION LEARNING When a consolidated analysis label appears: Read the divergence type (regular or hidden, bullish or bearish) Check the quality tier (textbook, high quality, or valid) Review the confluence breakdown - which factors contributed Look at the chart context - where is price relative to structure, trend, etc. Observe the behavioral footprint markers nearby - do they support the pattern STEP 4 - REAL-TIME MONITORING Watch the dashboard for real-time regime and pressure state Monitor the current confluence score in the dashboard When it approaches your threshold, be alert for potential pattern formation When a new pattern appears (after confirmation delay), evaluate it using the workflow above Use your trading strategy rules to decide if the setup aligns with your criteria STEP 5 - POST-PATTERN OBSERVATION After a pattern appears: Mark the level on your chart Observe what price does after the pattern completes Did price respect the reversal/continuation signal What was the confluence score of patterns that worked vs. those that failed Learn which quality tiers and confluence levels produce better results on your specific symbol and timeframe RECOMMENDED TIMEFRAMES AND ASSET CLASSES VMDM is timeframe-agnostic and works on any asset with volume data. However, optimal performance varies: BEST TIMEFRAMES 15-Minute to 1-Hour: Ideal balance of signal frequency and reliability. Pivot confirmation delay is acceptable. Sufficient volume data for pressure analysis. 4-Hour to Daily: Excellent for swing trading. Very high-quality signals. Lower frequency but higher significance. Recommended for learning because patterns are clearer. 1-Minute to 5-Minute: Works but requires adjustment. Increase pivot bars to 5-7 for filtering. Decrease max object history to 30 for performance. Expect more noise. Weekly/Monthly: Works but very infrequent signals. Increase confluence threshold to 70+ to ensure only major patterns appear. BEST ASSET CLASSES Forex Majors: Excellent volume data and clear trends. Pressure analysis works well. Crypto (Major Pairs): Good volume data. High volatility makes divergences more pronounced. Works very well. Stock Indices (SPY, QQQ, etc.): Excellent. Clean price action and reliable volume. Individual Stocks: Works well on high-volume stocks. Low-volume stocks may produce unreliable pressure readings. Commodities (Gold, Oil, etc.): Works well. Clear trends and reactions. WHAT THIS INDICATOR CANNOT DO - LIMITATIONS LIMITATION 1 - It Does Not Predict The Future VMDM identifies when technical conditions align historically associated with potential reversals or continuations. It does not predict what will happen next. A textbook 95-confluence pattern can still fail if fundamental events, news, or larger timeframe structure override the setup. LIMITATION 2 - Confirmation Delay Means You Miss Early Entry In Confirmed and Relaxed modes, the non-repainting design means you receive signals AFTER the pivot is confirmed. Price may have already moved significantly by the time you receive the signal. This is the tradeoff for non-repainting reliability. You can use Real-time mode for faster signals but sacrifice divergence confirmation. LIMITATION 3 - It Does Not Tell You Position Sizing or Risk Management VMDM provides technical pattern analysis. It does not calculate stop loss levels, take profit targets, or position sizing. You must apply your own risk management rules. Never risk more than you can afford to lose based on a technical signal. LIMITATION 4 - Volume Pressure Analysis Requires Reliable Volume Data On assets with thin volume or unreliable volume reporting, pressure analysis may be inaccurate. Stick to major liquid assets with consistent volume data. LIMITATION 5 - It Cannot Detect Fundamental Events VMDM is purely technical. It cannot predict earnings reports, central bank decisions, geopolitical events, or other fundamental catalysts that can override technical patterns. LIMITATION 6 - Divergence Requires Two Pivots The indicator cannot detect divergence until at least two pivots of the same type have formed. In strong trends without pullbacks, you may go long periods without signals. LIMITATION 7 - Institutional Pattern Names Are Interpretive The behavioral footprint patterns are named using common trading education terminology, but they are detected through technical analysis, not actual institutional data access. The patterns are interpretations based on price and volume behavior. CONCEPT FOUNDATION - WHY THIS APPROACH WORKS MARKET PRINCIPLE 1 - Momentum Divergence Precedes Price Reversal Price is the final output of market forces, but momentum (the rate of change in those forces) shifts first. When price makes a new low but the momentum behind that move is weaker (higher RSI low), it signals that sellers are losing strength even though they temporarily pushed price lower. This precedes reversal. This is a fundamental principle in technical analysis taught by Charles Dow, widely observed in market behavior. MARKET PRINCIPLE 2 - Volume Reveals Conviction Price can move on low volume (low conviction) or high volume (high conviction). When price makes a new low on declining volume while RSI shows improving momentum, it suggests the new low is not confirmed by participant conviction. Adding volume pressure analysis to momentum divergence adds a confirmation layer that filters false divergences. MARKET PRINCIPLE 3 - Anomalies Mark Structural Extremes When volume spikes significantly but range contracts (absorption), or when price spikes beyond structure then reverses (stop hunt), or when aggressive moves are met with large-wick rejection (exhaustion), these anomalies often mark short-term extremes. Combining these structural observations with momentum analysis creates context. MARKET PRINCIPLE 4 - Confluence Improves Probability No single technical factor is reliable in isolation. RSI divergence alone fails frequently. Volume analysis alone cannot time entries. Combining multiple independent factors into a weighted system increases the probability that observed patterns have structural significance rather than random noise. THE EDUCATIONAL VALUE By visualizing all four layers simultaneously and breaking down the confluence scoring transparently, VMDM teaches you to think in terms of multi-dimensional analysis rather than single-indicator reliance. Over time, you will learn to recognize these patterns manually and understand which combinations produce better results on your traded assets. INSTITUTIONAL TERMINOLOGY - IMPORTANT CLARIFICATION This indicator uses the following terms that are common in trading education: Institutional Footprint Absorption (Accumulation / Distribution) Stop Hunt Exhaustion CRITICAL DISCLAIMER: These terms are EDUCATIONAL LABELS for specific price action and volume behavior patterns detected through technical analysis of publicly available chart data (open, high, low, close, volume). This indicator does NOT have access to: Actual institutional order flow or order book data Market maker positions or intentions Broker stop-loss databases Non-public trading data Proprietary institutional information The patterns labeled as "institutional footprint" are interpretations based on observable price and volume behavior that educational trading literature often associates with potential large-participant activity. The detection is algorithmic pattern recognition, not privileged data access. When this indicator identifies "absorption," it means it detected high volume within a small range - a condition that MAY indicate large orders being filled but is not confirmation of actual institutional participation. When it identifies a "stop hunt," it means price briefly penetrated a structural level then reversed - a pattern that MAY have triggered stop losses but is not confirmation that stops were specifically targeted. When it identifies "exhaustion," it means high volume with large rejection wicks - a pattern that MAY indicate aggressive participation meeting strong opposition but is not confirmation of institutional involvement. These are technical analysis interpretations, not factual statements about market participant identity or intent. DISCLAIMER AND RISK WARNING EDUCATIONAL PURPOSE ONLY This indicator is designed as an educational tool to help traders learn to recognize technical patterns, understand multi-factor analysis, and practice systematic market observation. It is NOT a trading system, signal service, or financial advice. NO PERFORMANCE GUARANTEE Past pattern behavior does not guarantee future results. A pattern that historically preceded price movement in one direction may fail in the future due to changing market conditions, fundamental events, or random variance. Confluence scores reflect historical technical alignment, not future certainty. TRADING INVOLVES SUBSTANTIAL RISK Trading financial instruments involves substantial risk of loss. You can lose more than your initial investment. Never trade with money you cannot afford to lose. Always use proper risk management including stop losses, position sizing, and portfolio diversification. NO PREDICTIVE CLAIMS This indicator does NOT predict future price movement. It identifies when technical conditions align in patterns that historically have been associated with potential reversals or continuations. Market behavior is probabilistic, not deterministic. BACKTESTING LIMITATIONS If you backtest trading strategies using this indicator, ensure you account for: Realistic commission costs Realistic slippage (difference between signal price and actual fill price) Sufficient sample size (minimum 100 trades for statistical relevance) Reasonable position sizing (risking no more than 1-2 percent of account per trade) The confirmation delay inherent in the indicator (you cannot enter at the exact pivot in Confirmed mode) Backtests that do not account for these factors will produce unrealistic results. AUTHOR LIABILITY The author (BullByte) is not responsible for any trading losses incurred using this indicator. By using this indicator, you acknowledge that all trading decisions are your sole responsibility and that you understand the risks involved. NOT FINANCIAL ADVICE Nothing in this indicator, its code, its description, or its visual outputs constitutes financial, investment, or trading advice. Consult a licensed financial advisor before making investment decisions. FREQUENTLY ASKED QUESTIONS Q: Why do signals appear in the past, not at the current bar A: In Confirmed and Relaxed modes, signals appear at confirmed pivots, which requires waiting for right-side confirmation bars (default 3). This creates a delay but prevents repainting. Use Real-time mode if you want current-bar signals without pivot confirmation. Q: Can I use this for automated trading A: You can create alert-based automation, but understand that Confirmed mode signals appear AFTER the pivot with delay, so your entry will not be at the pivot price. Real-time mode signals can change as the current bar develops. Automation requires careful consideration of these factors. Q: How do I know which confluence score to use A: Start with 60. Observe which patterns work on your symbol/timeframe. If too many false signals, increase to 70-75. If too few signals, decrease to 55. Quality vs. quantity tradeoff. Q: Do regular divergences mean I should enter a reversal trade immediately A: No. Regular divergences indicate momentum exhaustion, which is a WARNING sign that trend may reverse, not a confirmation that it will. Use confluence score, market context, support/resistance, and your strategy rules to make entry decisions. Many divergences fail. Q: What's the difference between regular and hidden divergence A: Regular divergence = price and momentum move in opposite directions at extremes = potential reversal signal. Hidden divergence = price and momentum move in opposite directions during pullbacks = potential continuation signal. Hidden divergence suggests the pullback is just a correction within the larger trend. Q: Why does the pressure zone color sometimes conflict with the divergence direction A: Pressure is real-time current bar analysis. Divergence is confirmed pivot analysis from the past. They measure different things at different times. A bullish divergence confirmed 3 bars ago might appear during current selling pressure. This is normal. Q: Can I use this on stocks without volume data A: No. Volume is required for pressure analysis and behavioral pattern detection. Use only on assets with reliable volume reporting. Q: How often should I expect signals A: Depends on timeframe and settings. Daily charts might produce 5-10 signals per month. 1-hour charts might produce 20-30. 15-minute charts might produce 50-100. Adjust confluence threshold to control frequency. Q: Can I modify the code A: Yes, this is open source. You can modify for personal use. If you publish a modified version, please credit the original and ensure your publication meets TradingView guidelines. Q: What if I disagree with a pattern's confluence score A: The scoring weights are based on general observations and may not suit your specific strategy or asset. You can modify the code to adjust weights if you have data-driven reasons to do so. Final Notes VMDM - Volume, Momentum and Divergence Master is an educational multi-layer market analysis system designed to teach systematic pattern recognition through transparent, confluence-weighted signal detection. By combining RSI momentum divergence, volume pressure quantification, behavioral footprint pattern recognition, and quality scoring into a unified framework, it provides a comprehensive learning environment for understanding market structure. Use this tool to develop your analytical skills, understand how multiple technical factors interact, and learn to distinguish high-quality setups from noise. Remember that technical analysis is probabilistic, not predictive. No indicator replaces proper education, risk management, and trading discipline. Trade responsibly. Learn continuously. Risk only what you can afford to lose. -BullByte
مؤشر Pine Script®
من ‎BullByte‎
10
YM Ultimate SNIPER# YM Ultimate SNIPER - Documentation & Trading Guide ## 🎯 Unified GRA + DeepFlow | YM-Optimized for Low Volatility **TARGET: 3-7 High-Confluence Trades per Day** > **Philosophy:** *YM's lower volatility is not a weakness—it's our edge. Predictability + precision = consistent profits.* --- ## ⚡ QUICK REFERENCE CARD ``` ┌─────────────────────────────────────────────────────────────────────────────┐ │ YM ULTIMATE SNIPER - QUICK REFERENCE │ ├─────────────────────────────────────────────────────────────────────────────┤ │ │ │ 💰 YM BASICS: │ │ ═════════════ │ │ • 1 tick = 1 point = $5/contract │ │ • Typical daily range: 150-400 points │ │ • 30-40% less volatile than NQ │ │ • More institutional, less retail noise │ │ │ ├─────────────────────────────────────────────────────────────────────────────┤ │ │ │ 🎯 TIER THRESHOLDS (YM-OPTIMIZED): │ │ ══════════════════════════════════ │ │ S-TIER: 50+ pts = $250+/contract → HOLD (Institutional sweep) │ │ A-TIER: 25-49 pts = $125-245/contract → SWING (Strong momentum) │ │ B-TIER: 12-24 pts = $60-120/contract → SCALP (Quick grab) │ │ │ ├─────────────────────────────────────────────────────────────────────────────┤ │ │ │ ⏰ SESSION WINDOWS: │ │ ═══════════════════ │ │ LDN → 3:00-5:00 AM ET (European flow) │ │ NY → 9:30-11:30 AM ET (US opening drive) │ │ PWR → 3:00-4:00 PM ET (End-of-day rebalancing) │ │ │ │ Expected Trades: 1-2 LDN | 2-3 NY | 1-2 PWR = 4-7 total │ │ │ ├─────────────────────────────────────────────────────────────────────────────┤ │ │ │ 📊 CONFLUENCE SCORING (MAX 10 POINTS): │ │ ═══════════════════════════════════════ │ │ Tier Signal: S=3, A=2, B=1 points │ │ In Active Zone: +2 points │ │ POC Aligned: +1 point (POC at body extreme) │ │ Imbalance Support:+1 point (supporting IMB nearby) │ │ Strong Volume: +1 point (2x+ average) │ │ Strong Delta: +1 point (70%+ dominance) │ │ CVD Momentum: +1 point (CVD trending with signal) │ │ │ │ MINIMUM SCORE: 5/10 to show signal (adjustable) │ │ IDEAL SCORE: 7+/10 for highest probability │ │ │ ├─────────────────────────────────────────────────────────────────────────────┤ │ │ │ 🚨 SIGNAL TYPES: │ │ ═════════════════ │ │ S🎯 / A🎯 / B🎯 → GRA Tier Signals (Full confluence) │ │ Z🎯 → Zone Entry (At DFZ zone + delta + volume) │ │ SP → Single Print (Institutional impulse) │ │ │ ├─────────────────────────────────────────────────────────────────────────────┤ │ │ │ ✓ ENTRY CHECKLIST: │ │ ═══════════════════ │ │ □ Signal appears (check Score ≥5) │ │ □ Session active (LDN!/NY!/PWR!) │ │ □ Table: Vol GREEN, Delta colored, Body GREEN │ │ □ CVD arrow (▲/▼) matches direction │ │ □ Note stop/target lines on chart │ │ □ Check Zone status (bonus if IN ZONE) │ │ □ Execute at signal candle close │ │ │ ├─────────────────────────────────────────────────────────────────────────────┤ │ │ │ 🎯 POSITION SIZING BY TIER: │ │ ═══════════════════════════ │ │ S-TIER (50+ pts): Full size, hold 2-5 min, target 2.5:1 R:R │ │ A-TIER (25-49): 75% size, hold 1-3 min, target 2.0:1 R:R │ │ B-TIER (12-24): 50% size, hold 30-90 sec, target 1.5:1 R:R │ │ │ ├─────────────────────────────────────────────────────────────────────────────┤ │ │ │ ⛔ DO NOT TRADE WHEN: │ │ ════════════════════ │ │ ✗ Session shows "---" │ │ ✗ Score < 5/10 │ │ ✗ Vol shows RED (<1.8x) │ │ ✗ Delta < 62% │ │ ✗ Multiple conflicting signals │ │ ✗ Just before major news (FOMC, NFP, etc.) │ │ │ └─────────────────────────────────────────────────────────────────────────────┘ ``` --- ## 📋 WHY YM? LEVERAGING LOW VOLATILITY ### The YM Advantage Most traders avoid YM because "it doesn't move enough." This is precisely why it's perfect for precision scalping: | Factor | NQ | YM | Advantage | |--------|----|----|-----------| | **Daily Range** | 300-600 pts | 150-400 pts | More predictable moves | | **Tick Value** | $5/tick (4 ticks/pt) | $5/tick (1 tick/pt) | Simpler math | | **Retail Noise** | High | Low | Cleaner signals | | **Whipsaws** | Frequent | Rare | Fewer fakeouts | | **Trend Persistence** | Short | Long | Easier holds | | **Fill Quality** | Variable | Consistent | Better execution | ### Why 3-7 Trades is the Sweet Spot ``` YM SESSION BREAKDOWN: ════════════════════ LONDON (3-5 AM ET): 1-2 trades ├── Why: European institutions positioning for US open ├── Character: Slow build-up, clean trends └── Best signals: Zone entries + A/B tier NY OPEN (9:30-11:30 AM ET): 2-3 trades ├── Why: Highest volume, most institutional activity ├── Character: Initial balance formation, breakouts └── Best signals: S/A tier, zone confluence POWER HOUR (3-4 PM ET): 1-2 trades ├── Why: End-of-day rebalancing, MOC orders ├── Character: Mean reversion or trend acceleration └── Best signals: Zone entries, B tier quick scalps TOTAL: 4-7 high-quality setups per day ``` --- ## 🔧 YM-SPECIFIC OPTIMIZATIONS This unified indicator has been specifically tuned for YM's characteristics: ### Tier Thresholds | Tier | NQ (Original) | YM (Optimized) | Rationale | |------|---------------|----------------|-----------| | S-Tier | 100 pts | **50 pts** | YM's daily range is ~50% of NQ | | A-Tier | 50 pts | **25 pts** | Proportional scaling | | B-Tier | 20 pts | **12 pts** | Still 5%+ of typical daily range | ### Filter Adjustments | Filter | NQ Value | YM Value | Why | |--------|----------|----------|-----| | Volume Ratio | 1.5x | **1.8x** | Higher bar = less retail noise | | Delta Threshold | 60% | **62%** | Tighter for cleaner signals | | Body Ratio | 70% | **72%** | More conviction required | | Range Multiplier | 1.3x | **1.4x** | Bigger move = real signal | | Gap ATR% | 30% | **25%** | Smaller gaps still significant | | Zone Age | 50 bars | **75 bars** | Zones last longer in slow market | ### Why These Changes Work 1. **Higher Volume Bar**: YM has more institutional flow. Requiring 1.8x volume ensures we're catching real moves, not retail chop. 2. **Tighter Delta**: With less noise, we can demand clearer buyer/seller dominance before entering. 3. **Longer Zone Life**: YM trends persist longer. A zone that would be stale in NQ is still viable in YM. 4. **Smaller Gap Threshold**: YM gaps are naturally smaller. 25% of ATR in YM is significant institutional activity. --- ## 📊 CONFLUENCE SCORING SYSTEM The unified indicator uses a 10-point confluence scoring system to filter for only the highest-probability setups: ### Score Breakdown ``` CONFLUENCE SCORE CALCULATION: ═════════════════════════════ BASE POINTS (Tier): ├── S-Tier signal: +3 points ├── A-Tier signal: +2 points └── B-Tier signal: +1 point BONUS POINTS: ├── Inside Active Zone (DFZ): +2 points │ └── Price within bull/bear zone = institutional level │ ├── POC Alignment: +1 point │ └── POC at body extreme = strong conviction │ ├── Imbalance Support: +1 point │ └── Supporting imbalance within 1 ATR │ ├── Strong Volume (2x+): +1 point │ └── Exceptional institutional participation │ ├── Strong Delta (70%+): +1 point │ └── Clear one-sided aggression │ └── CVD Momentum: +1 point └── CVD trending with signal direction MAXIMUM POSSIBLE: 10 points ``` ### Score Interpretation | Score | Quality | Action | Expected Win Rate | |-------|---------|--------|-------------------| | 8-10 | 🥇 Elite | Full size, hold for target | 75-80% | | 6-7 | 🥈 Strong | Standard size, manage actively | 65-70% | | 5 | 🥉 Valid | Reduced size, quick scalp | 55-60% | | <5 | ⚫ Filtered | No signal shown | N/A | ### Adjusting Minimum Score - **Conservative (Score ≥6)**: Fewer trades, higher win rate - **Standard (Score ≥5)**: Balanced approach, 3-7 trades/day - **Aggressive (Score ≥4)**: More trades, requires active management --- ## 📐 SIGNAL TYPES EXPLAINED ### 1. GRA Tier Signals (S🎯, A🎯, B🎯) These are the primary signals from the merged GRA system: ``` TIER SIGNAL REQUIREMENTS: ═══════════════════════════ ALL must be TRUE: ├── ✓ Point movement meets tier threshold ├── ✓ Volume ≥ 1.8x average ├── ✓ Delta ≥ 62% (buy or sell dominance) ├── ✓ Body ≥ 72% of candle range ├── ✓ Range ≥ 1.4x average ├── ✓ Small opposite wick (<50% of body) ├── ✓ CVD confirms direction (if enabled) ├── ✓ Active session (LDN/NY/PWR) └── ✓ Confluence Score ≥ minimum (default 5) ``` ### 2. Zone Entry Signals (Z🎯) When price enters a DeepFlow zone with confirmation: ``` ZONE ENTRY REQUIREMENTS: ═══════════════════════════ ALL must be TRUE: ├── ✓ Price inside fresh/tested zone (not broken) ├── ✓ Delta ≥ 62% in zone direction ├── ✓ Volume ≥ 1.5x average └── ✓ Active session NOTE: Z🎯 only appears when NOT already showing tier signal (prevents duplicate signals on same candle) ``` ### 3. Single Print Markers (SP) Mark institutional impulse candles for future S/R: ``` SINGLE PRINT REQUIREMENTS: ═══════════════════════════ ALL must be TRUE: ├── ✓ Range ≥ 1.6x average ├── ✓ Body ≥ 72% of range ├── ✓ Volume ≥ 1.8x average ├── ✓ Delta ≥ 62% confirms direction └── ✓ Active session USE: Horizontal lines at high/low act as future S/R ``` --- ## 🎯 TRADING STRATEGIES ### Strategy 1: Zone + Tier Confluence (Highest Probability) ``` THE ULTIMATE YM SETUP: ═══════════════════════ Setup: 1. Active DeepFlow zone exists (green box below for long) 2. Price pulls back INTO the zone 3. Tier signal fires INSIDE the zone (S🎯/A🎯) 4. Score shows 7+/10 Entry: Signal candle close Stop: Below zone bottom (for longs) Target: Based on tier (1.5-2.5:1 R:R) Why It Works: • Zone = institutional limit orders • Tier signal = momentum confirmation • Double confirmation = high probability Expected Win Rate: 70-75% ``` ### Strategy 2: Pure Tier Signal with POC Stop ``` SNIPER TIER TRADE: ══════════════════ Setup: 1. Tier signal appears (preferably A or S) 2. Score ≥ 5/10 3. Note POC level on signal candle 4. Red/green stop/target lines appear Entry: Signal candle close Stop: Beyond POC (shown on chart) Target: Auto-calculated based on tier Key: POC placement matters • POC near candle bottom (longs) = STRONG • POC in middle = weaker signal • POC at extreme = possible exhaustion Expected Win Rate: 60-65% ``` ### Strategy 3: Zone Bounce (Continuation) ``` ZONE BOUNCE TRADE: ══════════════════ Setup: 1. Fresh zone created during session 2. Price leaves zone, moves in zone direction 3. Price returns to test zone (within 15 bars) 4. Z🎯 signal appears or rejection candle forms Entry: At CE line (middle of zone) Stop: Beyond zone edge Target: Previous swing high/low Why It Works: • Zones represent unfilled orders • First retest often finds support/resistance • Lower volatility = cleaner bounces Expected Win Rate: 55-60% ``` ### Strategy 4: Single Print Scalp ``` SINGLE PRINT SCALP: ═══════════════════ Setup: 1. Single Print (SP) marker appears 2. Note the gold/purple lines at high/low 3. Wait for price to return to SP level 4. Look for rejection or tier signal at level Entry: At SP line with confirmation Stop: Beyond the SP line Target: Quick 1:1 or to next structure Why It Works: • SP = price moved too fast, orders unfilled • Price often returns to "fill" these levels • YM's slower pace makes retests likely Expected Win Rate: 55-60% ``` --- ## 📊 TABLE LEGEND | Field | Reading | Color Meaning | |-------|---------|---------------| | **Pts** | Current candle points | Gold/Green/Yellow = Tiered | | **Tier** | S/A/B/X | Tier color or white | | **Vol** | Volume ratio | 🟢 ≥1.8x, 🔴 <1.8x | | **Delta** | Buy/Sell % | 🟢 Buy dom, 🔴 Sell dom | | **Body** | Body % of range | 🟢 ≥72%, 🔴 <72% | | **CVD** | Trend direction | ▲ Bullish, ▼ Bearish | | **Sess** | Active session | 🟡 LDN!/NY!/PWR!, ⚫ --- | | **POC** | Point of Control | 🟡 Gold price level | | **Zone** | Zone position | 🟢 BUY⬚, 🔴 SELL⬚, ⚫ --- | | **Zones** | Active zone count | #B/#S format | | **Score** | Confluence score | 🟢 7+, 🟡 5-6, ⚫ <5 | | **IMB** | Recent imbalances | Count in last 10 bars | | **R:R** | Risk/Reward | 🟢 On signal, ⚫ No signal | --- ## ⏰ SESSION-SPECIFIC PLAYBOOKS ### London Session (3:00-5:00 AM ET) ``` CHARACTER: Slow, methodical, trend-building VOLUME: Medium (50-70% of NY) BEST SETUPS: Zone entries, A/B tier with zones PLAYBOOK: • Enter on zone retests • Expect 15-25 pt moves • Don't fight early direction • Watch for pre-NY positioning TYPICAL TRADES: 1-2 ``` ### NY Open (9:30-11:30 AM ET) ``` CHARACTER: Fast, volatile, high-conviction VOLUME: Highest of day BEST SETUPS: S/A tier, zone confluence PLAYBOOK: • First 15 min: Observe Initial Balance • 9:45-10:15: Best setups form • S-tier signals = ride the wave • Be aggressive on high scores TYPICAL TRADES: 2-3 ``` ### Power Hour (3:00-4:00 PM ET) ``` CHARACTER: Rebalancing, MOC orders VOLUME: Medium-high (70-80% of NY) BEST SETUPS: B tier scalps, zone entries PLAYBOOK: • Watch for mean reversion setups • Quick scalps around POC levels • Don't hold through close • Take profits at 1:1 R:R TYPICAL TRADES: 1-2 ``` --- ## 🔧 RECOMMENDED SETTINGS ### Conservative (Fewer, Better Trades) | Setting | Value | Notes | |---------|-------|-------| | Min Confluence Score | 6 | Only strong setups | | Min Volume Ratio | 2.0 | Higher bar | | Delta Threshold | 65% | Stricter dominance | | Max Zones | 8 | Less clutter | ### Standard (Balanced) | Setting | Value | Notes | |---------|-------|-------| | Min Confluence Score | 5 | Default | | Min Volume Ratio | 1.8 | Default | | Delta Threshold | 62% | Default | | Max Zones | 12 | Default | ### Aggressive (More Opportunities) | Setting | Value | Notes | |---------|-------|-------| | Min Confluence Score | 4 | More signals | | Min Volume Ratio | 1.5 | Lower bar | | Delta Threshold | 60% | Looser | | Max Zones | 15 | More context | --- ## 🚨 ALERT SETUP Configure these alerts in TradingView: | Alert | Priority | Action | |-------|----------|--------| | 🎯 YM S-TIER LONG/SHORT | 🔴 CRITICAL | Drop everything, check immediately | | 🎯 YM A-TIER LONG/SHORT | 🟠 HIGH | Evaluate within 15 seconds | | 🎯 YM B-TIER LONG/SHORT | 🟡 MEDIUM | Check if available | | 🎯 YM ZONE BUY/SELL | 🟢 STANDARD | Good context entry | | 📦 NEW ZONE | 🔵 INFO | Mark on mental map | | ⭐ SINGLE PRINT | 🔵 INFO | Note for future S/R | | SESSION OPEN | ⚪ INFO | Prepare to trade | ### Alert Message Format ``` 🎯 YM A-LONG | YM1! @ 42,150 | 68%B | Score: 7/10 | IN ZONE | POC: 42,125 | Stop: 42,098 | SWING ``` --- ## ⚠️ COMMON MISTAKES TO AVOID | Mistake | Why It's Bad | Solution | |---------|-------------|----------| | Trading outside sessions | Low volume = noise | Wait for LDN/NY/PWR | | Ignoring score | Low scores = low probability | Require ≥5/10 | | Fighting the zone | Zones are institutional | Trade WITH zones | | Oversizing B-tier | Quick scalps, not holds | 50% size max | | Holding through news | Volatility spike | Exit before FOMC, NFP | | Chasing after signal | Entry on close only | Miss it = wait for next | | Ignoring POC position | Middle POC = indecision | Strong = extreme POC | --- ## 📈 DAILY TRADE JOURNAL TEMPLATE ``` DATE: ___________ SESSION: □ LDN □ NY □ PWR TRADE 1: ├── Time: _______ ├── Signal: S🎯 / A🎯 / B🎯 / Z🎯 ├── Score: ___/10 ├── Entry: _______ ├── Stop: _______ ├── Target: _______ ├── In Zone: □ Yes □ No ├── Result: +/- ___ pts ($_____) └── Notes: _______________________ TRADE 2: DAILY SUMMARY: ├── Total Trades: ___ ├── Win Rate: ___% ├── Net P/L: $_____ ├── Best Setup: _______ └── Improvement: _______________________ ``` --- ## 🏆 GOLDEN RULES FOR YM > **"YM rewards patience. Wait for the confluence—it's worth it."** > **"Low volatility means you can size up. One good trade beats five forced trades."** > **"Score 7+ is your edge. Anything less is gambling."** > **"The zone + tier combo is your bread and butter. Master it."** > **"Leave every trade with money. YM gives you time to manage."** --- ## 📊 VISUAL GUIDE ``` PERFECT YM SNIPER SETUP: ═══════════════════════════════════════════════════════════════════ │ Current Price │ ┌─────────────────────────┴────────────────────────────┐ │ BEARISH ZONE (Red) │ │- - - - - - - CE Line (Entry for shorts) - - - - - - │ │ │ └──────────────────────────────────────────────────────┘ │ ══════════════════╪══════════════════ SP High (Purple) │ ┌─────────────────────┤ │█████████████████████│ ← A🎯 LONG Signal │█████████████████████│ Score: 8/10 │ ●──────────────────│ ← POC (Gold) near bottom = STRONG │█████████████████████│ │█████████████████████│ └─────────────────────┤ │ ══════════════════╪══════════════════ SP Low (Purple) │ ┌─────────────────────────┴────────────────────────────┐ │ BULLISH ZONE (Green) │ │- - - - - - - CE Line (Entry for longs) - - - - - - -│ │██████████████████████████████████████████████████████│ └──────────────────────────────────────────────────────┘ │ Stop Loss CONFLUENCE CHECK: ✓ A-Tier signal (+2) ✓ At edge of bullish zone (+2) ✓ POC at bottom of candle (+1) ✓ Strong volume 2.3x (+1) ✓ Delta 72% buyers (+1) ✓ CVD bullish (+1) TOTAL: 8/10 = ELITE SETUP ACTION: Full size LONG at signal candle close STOP: Below zone bottom TARGET: 2:1 R:R (auto-calculated) ``` --- ## 🔧 TROUBLESHOOTING | Issue | Cause | Fix | |-------|-------|-----| | No signals appearing | Score too high | Lower min score to 4-5 | | Too many signals | Score too low | Raise min score to 6+ | | Zones cluttering chart | Max zones high | Reduce to 8-10 | | POC not showing | Tiered filter on | Check "POC Only Tiered" | | Session not highlighting | Wrong timezone | Verify timezone setting | | Alerts not firing | Not configured | Set up in TradingView alerts | --- ## 📝 PINE SCRIPT V6 TECHNICAL NOTES This indicator uses advanced features: - **User Defined Types (UDT)**: Clean state management for zones/imbalances - **`request.security_lower_tf()`**: Intrabar volume analysis - **Dynamic Array Management**: Efficient memory for drawings - **Confluence Scoring Engine**: Multi-factor signal qualification - **Auto Stop/Target**: Dynamic risk management calculation **Minimum TradingView Plan:** Pro (for intrabar data access) --- *© Alexandro Disla - YM Ultimate SNIPER* *Pine Script v6 | TradingView* *Unified GRA v5 + DeepFlow Zones | YM-Optimized*
مؤشر Pine Script®
من ‎alexandrodisla‎
Dimensional Resonance ProtocolDimensional Resonance Protocol 🌀 CORE INNOVATION: PHASE SPACE RECONSTRUCTION & EMERGENCE DETECTION The Dimensional Resonance Protocol represents a paradigm shift from traditional technical analysis to complexity science. Rather than measuring price levels or indicator crossovers, DRP reconstructs the hidden attractor governing market dynamics using Takens' embedding theorem, then detects emergence —the rare moments when multiple dimensions of market behavior spontaneously synchronize into coherent, predictable states. The Complexity Hypothesis: Markets are not simple oscillators or random walks—they are complex adaptive systems existing in high-dimensional phase space. Traditional indicators see only shadows (one-dimensional projections) of this higher-dimensional reality. DRP reconstructs the full phase space using time-delay embedding, revealing the true structure of market dynamics. Takens' Embedding Theorem (1981): A profound mathematical result from dynamical systems theory: Given a time series from a complex system, we can reconstruct its full phase space by creating delayed copies of the observation. Mathematical Foundation: From single observable x(t), create embedding vectors: X(t) = Where: • d = Embedding dimension (default 5) • τ = Time delay (default 3 bars) • x(t) = Price or return at time t Key Insight: If d ≥ 2D+1 (where D is the true attractor dimension), this embedding is topologically equivalent to the actual system dynamics. We've reconstructed the hidden attractor from a single price series. Why This Matters: Markets appear random in one dimension (price chart). But in reconstructed phase space, structure emerges—attractors, limit cycles, strange attractors. When we identify these structures, we can detect: • Stable regions : Predictable behavior (trade opportunities) • Chaotic regions : Unpredictable behavior (avoid trading) • Critical transitions : Phase changes between regimes Phase Space Magnitude Calculation: phase_magnitude = sqrt(Σ ² for i = 0 to d-1) This measures the "energy" or "momentum" of the market trajectory through phase space. High magnitude = strong directional move. Low magnitude = consolidation. 📊 RECURRENCE QUANTIFICATION ANALYSIS (RQA) Once phase space is reconstructed, we analyze its recurrence structure —when does the system return near previous states? Recurrence Plot Foundation: A recurrence occurs when two phase space points are closer than threshold ε: R(i,j) = 1 if ||X(i) - X(j)|| < ε, else 0 This creates a binary matrix showing when the system revisits similar states. Key RQA Metrics: 1. Recurrence Rate (RR): RR = (Number of recurrent points) / (Total possible pairs) • RR near 0: System never repeats (highly stochastic) • RR = 0.1-0.3: Moderate recurrence (tradeable patterns) • RR > 0.5: System stuck in attractor (ranging market) • RR near 1: System frozen (no dynamics) Interpretation: Moderate recurrence is optimal —patterns exist but market isn't stuck. 2. Determinism (DET): Measures what fraction of recurrences form diagonal structures in the recurrence plot. Diagonals indicate deterministic evolution (trajectory follows predictable paths). DET = (Recurrence points on diagonals) / (Total recurrence points) • DET < 0.3: Random dynamics • DET = 0.3-0.7: Moderate determinism (patterns with noise) • DET > 0.7: Strong determinism (technical patterns reliable) Trading Implication: Signals are prioritized when DET > 0.3 (deterministic state) and RR is moderate (not stuck). Threshold Selection (ε): Default ε = 0.10 × std_dev means two states are "recurrent" if within 10% of a standard deviation. This is tight enough to require genuine similarity but loose enough to find patterns. 🔬 PERMUTATION ENTROPY: COMPLEXITY MEASUREMENT Permutation entropy measures the complexity of a time series by analyzing the distribution of ordinal patterns. Algorithm (Bandt & Pompe, 2002): 1. Take overlapping windows of length n (default n=4) 2. For each window, record the rank order pattern Example: → pattern (ranks from lowest to highest) 3. Count frequency of each possible pattern 4. Calculate Shannon entropy of pattern distribution Mathematical Formula: H_perm = -Σ p(π) · ln(p(π)) Where π ranges over all n! possible permutations, p(π) is the probability of pattern π. Normalized to : H_norm = H_perm / ln(n!) Interpretation: • H < 0.3 : Very ordered, crystalline structure (strong trending) • H = 0.3-0.5 : Ordered regime (tradeable with patterns) • H = 0.5-0.7 : Moderate complexity (mixed conditions) • H = 0.7-0.85 : Complex dynamics (challenging to trade) • H > 0.85 : Maximum entropy (nearly random, avoid) Entropy Regime Classification: DRP classifies markets into five entropy regimes: • CRYSTALLINE (H < 0.3): Maximum order, persistent trends • ORDERED (H < 0.5): Clear patterns, momentum strategies work • MODERATE (H < 0.7): Mixed dynamics, adaptive required • COMPLEX (H < 0.85): High entropy, mean reversion better • CHAOTIC (H ≥ 0.85): Near-random, minimize trading Why Permutation Entropy? Unlike traditional entropy methods requiring binning continuous data (losing information), permutation entropy: • Works directly on time series • Robust to monotonic transformations • Computationally efficient • Captures temporal structure, not just distribution • Immune to outliers (uses ranks, not values) ⚡ LYAPUNOV EXPONENT: CHAOS vs STABILITY The Lyapunov exponent λ measures sensitivity to initial conditions —the hallmark of chaos. Physical Meaning: Two trajectories starting infinitely close will diverge at exponential rate e^(λt): Distance(t) ≈ Distance(0) × e^(λt) Interpretation: • λ > 0 : Positive Lyapunov exponent = CHAOS - Small errors grow exponentially - Long-term prediction impossible - System is sensitive, unpredictable - AVOID TRADING • λ ≈ 0 : Near-zero = CRITICAL STATE - Edge of chaos - Transition zone between order and disorder - Moderate predictability - PROCEED WITH CAUTION • λ < 0 : Negative Lyapunov exponent = STABLE - Small errors decay - Trajectories converge - System is predictable - OPTIMAL FOR TRADING Estimation Method: DRP estimates λ by tracking how quickly nearby states diverge over a rolling window (default 20 bars): For each bar i in window: δ₀ = |x - x | (initial separation) δ₁ = |x - x | (previous separation) if δ₁ > 0: ratio = δ₀ / δ₁ log_ratios += ln(ratio) λ ≈ average(log_ratios) Stability Classification: • STABLE : λ < 0 (negative growth rate) • CRITICAL : |λ| < 0.1 (near neutral) • CHAOTIC : λ > 0.2 (strong positive growth) Signal Filtering: By default, NEXUS requires λ < 0 (stable regime) for signal confirmation. This filters out trades during chaotic periods when technical patterns break down. 📐 HIGUCHI FRACTAL DIMENSION Fractal dimension measures self-similarity and complexity of the price trajectory. Theoretical Background: A curve's fractal dimension D ranges from 1 (smooth line) to 2 (space-filling curve): • D ≈ 1.0 : Smooth, persistent trending • D ≈ 1.5 : Random walk (Brownian motion) • D ≈ 2.0 : Highly irregular, space-filling Higuchi Method (1988): For a time series of length N, construct k different curves by taking every k-th point: L(k) = (1/k) × Σ|x - x | × (N-1)/(⌊(N-m)/k⌋ × k) For different values of k (1 to k_max), calculate L(k). The fractal dimension is the slope of log(L(k)) vs log(1/k): D = slope of log(L) vs log(1/k) Market Interpretation: • D < 1.35 : Strong trending, persistent (Hurst > 0.5) - TRENDING regime - Momentum strategies favored - Breakouts likely to continue • D = 1.35-1.45 : Moderate persistence - PERSISTENT regime - Trend-following with caution - Patterns have meaning • D = 1.45-1.55 : Random walk territory - RANDOM regime - Efficiency hypothesis holds - Technical analysis least reliable • D = 1.55-1.65 : Anti-persistent (mean-reverting) - ANTI-PERSISTENT regime - Oscillator strategies work - Overbought/oversold meaningful • D > 1.65 : Highly complex, choppy - COMPLEX regime - Avoid directional bets - Wait for regime change Signal Filtering: Resonance signals (secondary signal type) require D < 1.5, indicating trending or persistent dynamics where momentum has meaning. 🔗 TRANSFER ENTROPY: CAUSAL INFORMATION FLOW Transfer entropy measures directed causal influence between time series—not just correlation, but actual information transfer. Schreiber's Definition (2000): Transfer entropy from X to Y measures how much knowing X's past reduces uncertainty about Y's future: TE(X→Y) = H(Y_future | Y_past) - H(Y_future | Y_past, X_past) Where H is Shannon entropy. Key Properties: 1. Directional : TE(X→Y) ≠ TE(Y→X) in general 2. Non-linear : Detects complex causal relationships 3. Model-free : No assumptions about functional form 4. Lag-independent : Captures delayed causal effects Three Causal Flows Measured: 1. Volume → Price (TE_V→P): Measures how much volume patterns predict price changes. • TE > 0 : Volume provides predictive information about price - Institutional participation driving moves - Volume confirms direction - High reliability • TE ≈ 0 : No causal flow (weak volume/price relationship) - Volume uninformative - Caution on signals • TE < 0 (rare): Suggests price leading volume - Potentially manipulated or thin market 2. Volatility → Momentum (TE_σ→M): Does volatility expansion predict momentum changes? • Positive TE : Volatility precedes momentum shifts - Breakout dynamics - Regime transitions 3. Structure → Price (TE_S→P): Do support/resistance patterns causally influence price? • Positive TE : Structural levels have causal impact - Technical levels matter - Market respects structure Net Causal Flow: Net_Flow = TE_V→P + 0.5·TE_σ→M + TE_S→P • Net > +0.1 : Bullish causal structure • Net < -0.1 : Bearish causal structure • |Net| < 0.1 : Neutral/unclear causation Causal Gate: For signal confirmation, NEXUS requires: • Buy signals : TE_V→P > 0 AND Net_Flow > 0.05 • Sell signals : TE_V→P > 0 AND Net_Flow < -0.05 This ensures volume is actually driving price (causal support exists), not just correlated noise. Implementation Note: Computing true transfer entropy requires discretizing continuous data into bins (default 6 bins) and estimating joint probability distributions. NEXUS uses a hybrid approach combining TE theory with autocorrelation structure and lagged cross-correlation to approximate information transfer in computationally efficient manner. 🌊 HILBERT PHASE COHERENCE Phase coherence measures synchronization across market dimensions using Hilbert transform analysis. Hilbert Transform Theory: For a signal x(t), the Hilbert transform H (t) creates an analytic signal: z(t) = x(t) + i·H (t) = A(t)·e^(iφ(t)) Where: • A(t) = Instantaneous amplitude • φ(t) = Instantaneous phase Instantaneous Phase: φ(t) = arctan(H (t) / x(t)) The phase represents where the signal is in its natural cycle—analogous to position on a unit circle. Four Dimensions Analyzed: 1. Momentum Phase : Phase of price rate-of-change 2. Volume Phase : Phase of volume intensity 3. Volatility Phase : Phase of ATR cycles 4. Structure Phase : Phase of position within range Phase Locking Value (PLV): For two signals with phases φ₁(t) and φ₂(t), PLV measures phase synchronization: PLV = |⟨e^(i(φ₁(t) - φ₂(t)))⟩| Where ⟨·⟩ is time average over window. Interpretation: • PLV = 0 : Completely random phase relationship (no synchronization) • PLV = 0.5 : Moderate phase locking • PLV = 1 : Perfect synchronization (phases locked) Pairwise PLV Calculations: • PLV_momentum-volume : Are momentum and volume cycles synchronized? • PLV_momentum-structure : Are momentum cycles aligned with structure? • PLV_volume-structure : Are volume and structural patterns in phase? Overall Phase Coherence: Coherence = (PLV_mom-vol + PLV_mom-struct + PLV_vol-struct) / 3 Signal Confirmation: Emergence signals require coherence ≥ threshold (default 0.70): • Below 0.70: Dimensions not synchronized, no coherent market state • Above 0.70: Dimensions in phase, coherent behavior emerging Coherence Direction: The summed phase angles indicate whether synchronized dimensions point bullish or bearish: Direction = sin(φ_momentum) + 0.5·sin(φ_volume) + 0.5·sin(φ_structure) • Direction > 0 : Phases pointing upward (bullish synchronization) • Direction < 0 : Phases pointing downward (bearish synchronization) 🌀 EMERGENCE SCORE: MULTI-DIMENSIONAL ALIGNMENT The emergence score aggregates all complexity metrics into a single 0-1 value representing market coherence. Eight Components with Weights: 1. Phase Coherence (20%): Direct contribution: coherence × 0.20 Measures dimensional synchronization. 2. Entropy Regime (15%): Contribution: (0.6 - H_perm) / 0.6 × 0.15 if H < 0.6, else 0 Rewards low entropy (ordered, predictable states). 3. Lyapunov Stability (12%): • λ < 0 (stable): +0.12 • |λ| < 0.1 (critical): +0.08 • λ > 0.2 (chaotic): +0.0 Requires stable, predictable dynamics. 4. Fractal Dimension Trending (12%): Contribution: (1.45 - D) / 0.45 × 0.12 if D < 1.45, else 0 Rewards trending fractal structure (D < 1.45). 5. Dimensional Resonance (12%): Contribution: |dimensional_resonance| × 0.12 Measures alignment across momentum, volume, structure, volatility dimensions. 6. Causal Flow Strength (9%): Contribution: |net_causal_flow| × 0.09 Rewards strong causal relationships. 7. Phase Space Embedding (10%): Contribution: min(|phase_magnitude_norm|, 3.0) / 3.0 × 0.10 if |magnitude| > 1.0 Rewards strong trajectory in reconstructed phase space. 8. Recurrence Quality (10%): Contribution: determinism × 0.10 if DET > 0.3 AND 0.1 < RR < 0.8 Rewards deterministic patterns with moderate recurrence. Total Emergence Score: E = Σ(components) ∈ Capped at 1.0 maximum. Emergence Direction: Separate calculation determining bullish vs bearish: • Dimensional resonance sign • Net causal flow sign • Phase magnitude correlation with momentum Signal Threshold: Default emergence_threshold = 0.75 means 75% of maximum possible emergence score required to trigger signals. Why Emergence Matters: Traditional indicators measure single dimensions. Emergence detects self-organization —when multiple independent dimensions spontaneously align. This is the market equivalent of a phase transition in physics, where microscopic chaos gives way to macroscopic order. These are the highest-probability trade opportunities because the entire system is resonating in the same direction. 🎯 SIGNAL GENERATION: EMERGENCE vs RESONANCE DRP generates two tiers of signals with different requirements: TIER 1: EMERGENCE SIGNALS (Primary) Requirements: 1. Emergence score ≥ threshold (default 0.75) 2. Phase coherence ≥ threshold (default 0.70) 3. Emergence direction > 0.2 (bullish) or < -0.2 (bearish) 4. Causal gate passed (if enabled): TE_V→P > 0 and net_flow confirms direction 5. Stability zone (if enabled): λ < 0 or |λ| < 0.1 6. Price confirmation: Close > open (bulls) or close < open (bears) 7. Cooldown satisfied: bars_since_signal ≥ cooldown_period EMERGENCE BUY: • All above conditions met with bullish direction • Market has achieved coherent bullish state • Multiple dimensions synchronized upward EMERGENCE SELL: • All above conditions met with bearish direction • Market has achieved coherent bearish state • Multiple dimensions synchronized downward Premium Emergence: When signal_quality (emergence_score × phase_coherence) > 0.7: • Displayed as ★ star symbol • Highest conviction trades • Maximum dimensional alignment Standard Emergence: When signal_quality 0.5-0.7: • Displayed as ◆ diamond symbol • Strong signals but not perfect alignment TIER 2: RESONANCE SIGNALS (Secondary) Requirements: 1. Dimensional resonance > +0.6 (bullish) or < -0.6 (bearish) 2. Fractal dimension < 1.5 (trending/persistent regime) 3. Price confirmation matches direction 4. NOT in chaotic regime (λ < 0.2) 5. Cooldown satisfied 6. NO emergence signal firing (resonance is fallback) RESONANCE BUY: • Dimensional alignment without full emergence • Trending fractal structure • Moderate conviction RESONANCE SELL: • Dimensional alignment without full emergence • Bearish resonance with trending structure • Moderate conviction Displayed as small ▲/▼ triangles with transparency. Signal Hierarchy: IF emergence conditions met: Fire EMERGENCE signal (★ or ◆) ELSE IF resonance conditions met: Fire RESONANCE signal (▲ or ▼) ELSE: No signal Cooldown System: After any signal fires, cooldown_period (default 5 bars) must elapse before next signal. This prevents signal clustering during persistent conditions. Cooldown tracks using bar_index: bars_since_signal = current_bar_index - last_signal_bar_index cooldown_ok = bars_since_signal >= cooldown_period 🎨 VISUAL SYSTEM: MULTI-LAYER COMPLEXITY DRP provides rich visual feedback across four distinct layers: LAYER 1: COHERENCE FIELD (Background) Colored background intensity based on phase coherence: • No background : Coherence < 0.5 (incoherent state) • Faint glow : Coherence 0.5-0.7 (building coherence) • Stronger glow : Coherence > 0.7 (coherent state) Color: • Cyan/teal: Bullish coherence (direction > 0) • Red/magenta: Bearish coherence (direction < 0) • Blue: Neutral coherence (direction ≈ 0) Transparency: 98 minus (coherence_intensity × 10), so higher coherence = more visible. LAYER 2: STABILITY/CHAOS ZONES Background color indicating Lyapunov regime: • Green tint (95% transparent): λ < 0, STABLE zone - Safe to trade - Patterns meaningful • Gold tint (90% transparent): |λ| < 0.1, CRITICAL zone - Edge of chaos - Moderate risk • Red tint (85% transparent): λ > 0.2, CHAOTIC zone - Avoid trading - Unpredictable behavior LAYER 3: DIMENSIONAL RIBBONS Three EMAs representing dimensional structure: • Fast ribbon : EMA(8) in cyan/teal (fast dynamics) • Medium ribbon : EMA(21) in blue (intermediate) • Slow ribbon : EMA(55) in red/magenta (slow dynamics) Provides visual reference for multi-scale structure without cluttering with raw phase space data. LAYER 4: CAUSAL FLOW LINE A thicker line plotted at EMA(13) colored by net causal flow: • Cyan/teal : Net_flow > +0.1 (bullish causation) • Red/magenta : Net_flow < -0.1 (bearish causation) • Gray : |Net_flow| < 0.1 (neutral causation) Shows real-time direction of information flow. EMERGENCE FLASH: Strong background flash when emergence signals fire: • Cyan flash for emergence buy • Red flash for emergence sell • 80% transparency for visibility without obscuring price 📊 COMPREHENSIVE DASHBOARD Real-time monitoring of all complexity metrics: HEADER: • 🌀 DRP branding with gold accent CORE METRICS: EMERGENCE: • Progress bar (█ filled, ░ empty) showing 0-100% • Percentage value • Direction arrow (↗ bull, ↘ bear, → neutral) • Color-coded: Green/gold if active, gray if low COHERENCE: • Progress bar showing phase locking value • Percentage value • Checkmark ✓ if ≥ threshold, circle ○ if below • Color-coded: Cyan if coherent, gray if not COMPLEXITY SECTION: ENTROPY: • Regime name (CRYSTALLINE/ORDERED/MODERATE/COMPLEX/CHAOTIC) • Numerical value (0.00-1.00) • Color: Green (ordered), gold (moderate), red (chaotic) LYAPUNOV: • State (STABLE/CRITICAL/CHAOTIC) • Numerical value (typically -0.5 to +0.5) • Status indicator: ● stable, ◐ critical, ○ chaotic • Color-coded by state FRACTAL: • Regime (TRENDING/PERSISTENT/RANDOM/ANTI-PERSIST/COMPLEX) • Dimension value (1.0-2.0) • Color: Cyan (trending), gold (random), red (complex) PHASE-SPACE: • State (STRONG/ACTIVE/QUIET) • Normalized magnitude value • Parameters display: d=5 τ=3 CAUSAL SECTION: CAUSAL: • Direction (BULL/BEAR/NEUTRAL) • Net flow value • Flow indicator: →P (to price), P← (from price), ○ (neutral) V→P: • Volume-to-price transfer entropy • Small display showing specific TE value DIMENSIONAL SECTION: RESONANCE: • Progress bar of absolute resonance • Signed value (-1 to +1) • Color-coded by direction RECURRENCE: • Recurrence rate percentage • Determinism percentage display • Color-coded: Green if high quality STATE SECTION: STATE: • Current mode: EMERGENCE / RESONANCE / CHAOS / SCANNING • Icon: 🚀 (emergence buy), 💫 (emergence sell), ▲ (resonance buy), ▼ (resonance sell), ⚠ (chaos), ◎ (scanning) • Color-coded by state SIGNALS: • E: count of emergence signals • R: count of resonance signals ⚙️ KEY PARAMETERS EXPLAINED Phase Space Configuration: • Embedding Dimension (3-10, default 5): Reconstruction dimension - Low (3-4): Simple dynamics, faster computation - Medium (5-6): Balanced (recommended) - High (7-10): Complex dynamics, more data needed - Rule: d ≥ 2D+1 where D is true dimension • Time Delay (τ) (1-10, default 3): Embedding lag - Fast markets: 1-2 - Normal: 3-4 - Slow markets: 5-10 - Optimal: First minimum of mutual information (often 2-4) • Recurrence Threshold (ε) (0.01-0.5, default 0.10): Phase space proximity - Tight (0.01-0.05): Very similar states only - Medium (0.08-0.15): Balanced - Loose (0.20-0.50): Liberal matching Entropy & Complexity: • Permutation Order (3-7, default 4): Pattern length - Low (3): 6 patterns, fast but coarse - Medium (4-5): 24-120 patterns, balanced - High (6-7): 720-5040 patterns, fine-grained - Note: Requires window >> order! for stability • Entropy Window (15-100, default 30): Lookback for entropy - Short (15-25): Responsive to changes - Medium (30-50): Stable measure - Long (60-100): Very smooth, slow adaptation • Lyapunov Window (10-50, default 20): Stability estimation window - Short (10-15): Fast chaos detection - Medium (20-30): Balanced - Long (40-50): Stable λ estimate Causal Inference: • Enable Transfer Entropy (default ON): Causality analysis - Keep ON for full system functionality • TE History Length (2-15, default 5): Causal lookback - Short (2-4): Quick causal detection - Medium (5-8): Balanced - Long (10-15): Deep causal analysis • TE Discretization Bins (4-12, default 6): Binning granularity - Few (4-5): Coarse, robust, needs less data - Medium (6-8): Balanced - Many (9-12): Fine-grained, needs more data Phase Coherence: • Enable Phase Coherence (default ON): Synchronization detection - Keep ON for emergence detection • Coherence Threshold (0.3-0.95, default 0.70): PLV requirement - Loose (0.3-0.5): More signals, lower quality - Balanced (0.6-0.75): Recommended - Strict (0.8-0.95): Rare, highest quality • Hilbert Smoothing (3-20, default 8): Phase smoothing - Low (3-5): Responsive, noisier - Medium (6-10): Balanced - High (12-20): Smooth, more lag Fractal Analysis: • Enable Fractal Dimension (default ON): Complexity measurement - Keep ON for full analysis • Fractal K-max (4-20, default 8): Scaling range - Low (4-6): Faster, less accurate - Medium (7-10): Balanced - High (12-20): Accurate, slower • Fractal Window (30-200, default 50): FD lookback - Short (30-50): Responsive FD - Medium (60-100): Stable FD - Long (120-200): Very smooth FD Emergence Detection: • Emergence Threshold (0.5-0.95, default 0.75): Minimum coherence - Sensitive (0.5-0.65): More signals - Balanced (0.7-0.8): Recommended - Strict (0.85-0.95): Rare signals • Require Causal Gate (default ON): TE confirmation - ON: Only signal when causality confirms - OFF: Allow signals without causal support • Require Stability Zone (default ON): Lyapunov filter - ON: Only signal when λ < 0 (stable) or |λ| < 0.1 (critical) - OFF: Allow signals in chaotic regimes (risky) • Signal Cooldown (1-50, default 5): Minimum bars between signals - Fast (1-3): Rapid signal generation - Normal (4-8): Balanced - Slow (10-20): Very selective - Ultra (25-50): Only major regime changes Signal Configuration: • Momentum Period (5-50, default 14): ROC calculation • Structure Lookback (10-100, default 20): Support/resistance range • Volatility Period (5-50, default 14): ATR calculation • Volume MA Period (10-50, default 20): Volume normalization Visual Settings: • Customizable color scheme for all elements • Toggle visibility for each layer independently • Dashboard position (4 corners) and size (tiny/small/normal) 🎓 PROFESSIONAL USAGE PROTOCOL Phase 1: System Familiarization (Week 1) Goal: Understand complexity metrics and dashboard interpretation Setup: • Enable all features with default parameters • Watch dashboard metrics for 500+ bars • Do NOT trade yet Actions: • Observe emergence score patterns relative to price moves • Note coherence threshold crossings and subsequent price action • Watch entropy regime transitions (ORDERED → COMPLEX → CHAOTIC) • Correlate Lyapunov state with signal reliability • Track which signals appear (emergence vs resonance frequency) Key Learning: • When does emergence peak? (usually before major moves) • What entropy regime produces best signals? (typically ORDERED or MODERATE) • Does your instrument respect stability zones? (stable λ = better signals) Phase 2: Parameter Optimization (Week 2) Goal: Tune system to instrument characteristics Requirements: • Understand basic dashboard metrics from Phase 1 • Have 1000+ bars of history loaded Embedding Dimension & Time Delay: • If signals very rare: Try lower dimension (d=3-4) or shorter delay (τ=2) • If signals too frequent: Try higher dimension (d=6-7) or longer delay (τ=4-5) • Sweet spot: 4-8 emergence signals per 100 bars Coherence Threshold: • Check dashboard: What's typical coherence range? • If coherence rarely exceeds 0.70: Lower threshold to 0.60-0.65 • If coherence often >0.80: Can raise threshold to 0.75-0.80 • Goal: Signals fire during top 20-30% of coherence values Emergence Threshold: • If too few signals: Lower to 0.65-0.70 • If too many signals: Raise to 0.80-0.85 • Balance with coherence threshold—both must be met Phase 3: Signal Quality Assessment (Weeks 3-4) Goal: Verify signals have edge via paper trading Requirements: • Parameters optimized per Phase 2 • 50+ signals generated • Detailed notes on each signal Paper Trading Protocol: • Take EVERY emergence signal (★ and ◆) • Optional: Take resonance signals (▲/▼) separately to compare • Use simple exit: 2R target, 1R stop (ATR-based) • Track: Win rate, average R-multiple, maximum consecutive losses Quality Metrics: • Premium emergence (★) : Should achieve >55% WR • Standard emergence (◆) : Should achieve >50% WR • Resonance signals : Should achieve >45% WR • Overall : If <45% WR, system not suitable for this instrument/timeframe Red Flags: • Win rate <40%: Wrong instrument or parameters need major adjustment • Max consecutive losses >10: System not working in current regime • Profit factor <1.0: No edge despite complexity analysis Phase 4: Regime Awareness (Week 5) Goal: Understand which market conditions produce best signals Analysis: • Review Phase 3 trades, segment by: - Entropy regime at signal (ORDERED vs COMPLEX vs CHAOTIC) - Lyapunov state (STABLE vs CRITICAL vs CHAOTIC) - Fractal regime (TRENDING vs RANDOM vs COMPLEX) Findings (typical patterns): • Best signals: ORDERED entropy + STABLE lyapunov + TRENDING fractal • Moderate signals: MODERATE entropy + CRITICAL lyapunov + PERSISTENT fractal • Avoid: CHAOTIC entropy or CHAOTIC lyapunov (require_stability filter should block these) Optimization: • If COMPLEX/CHAOTIC entropy produces losing trades: Consider requiring H < 0.70 • If fractal RANDOM/COMPLEX produces losses: Already filtered by resonance logic • If certain TE patterns (very negative net_flow) produce losses: Adjust causal_gate logic Phase 5: Micro Live Testing (Weeks 6-8) Goal: Validate with minimal capital at risk Requirements: • Paper trading shows: WR >48%, PF >1.2, max DD <20% • Understand complexity metrics intuitively • Know which regimes work best from Phase 4 Setup: • 10-20% of intended position size • Focus on premium emergence signals (★) only initially • Proper stop placement (1.5-2.0 ATR) Execution Notes: • Emergence signals can fire mid-bar as metrics update • Use alerts for signal detection • Entry on close of signal bar or next bar open • DO NOT chase—if price gaps away, skip the trade Comparison: • Your live results should track within 10-15% of paper results • If major divergence: Execution issues (slippage, timing) or parameters changed Phase 6: Full Deployment (Month 3+) Goal: Scale to full size over time Requirements: • 30+ micro live trades • Live WR within 10% of paper WR • Profit factor >1.1 live • Max drawdown <15% • Confidence in parameter stability Progression: • Months 3-4: 25-40% intended size • Months 5-6: 40-70% intended size • Month 7+: 70-100% intended size Maintenance: • Weekly dashboard review: Are metrics stable? • Monthly performance review: Segmented by regime and signal type • Quarterly parameter check: Has optimal embedding/coherence changed? Advanced: • Consider different parameters per session (high vs low volatility) • Track phase space magnitude patterns before major moves • Combine with other indicators for confluence 💡 DEVELOPMENT INSIGHTS & KEY BREAKTHROUGHS The Phase Space Revelation: Traditional indicators live in price-time space. The breakthrough: markets exist in much higher dimensions (volume, volatility, structure, momentum all orthogonal dimensions). Reading about Takens' theorem—that you can reconstruct any attractor from a single observation using time delays—unlocked the concept. Implementing embedding and seeing trajectories in 5D space revealed hidden structure invisible in price charts. Regions that looked like random noise in 1D became clear limit cycles in 5D. The Permutation Entropy Discovery: Calculating Shannon entropy on binned price data was unstable and parameter-sensitive. Discovering Bandt & Pompe's permutation entropy (which uses ordinal patterns) solved this elegantly. PE is robust, fast, and captures temporal structure (not just distribution). Testing showed PE < 0.5 periods had 18% higher signal win rate than PE > 0.7 periods. Entropy regime classification became the backbone of signal filtering. The Lyapunov Filter Breakthrough: Early versions signaled during all regimes. Win rate hovered at 42%—barely better than random. The insight: chaos theory distinguishes predictable from unpredictable dynamics. Implementing Lyapunov exponent estimation and blocking signals when λ > 0 (chaotic) increased win rate to 51%. Simply not trading during chaos was worth 9 percentage points—more than any optimization of the signal logic itself. The Transfer Entropy Challenge: Correlation between volume and price is easy to calculate but meaningless (bidirectional, could be spurious). Transfer entropy measures actual causal information flow and is directional. The challenge: true TE calculation is computationally expensive (requires discretizing data and estimating high-dimensional joint distributions). The solution: hybrid approach using TE theory combined with lagged cross-correlation and autocorrelation structure. Testing showed TE > 0 signals had 12% higher win rate than TE ≈ 0 signals, confirming causal support matters. The Phase Coherence Insight: Initially tried simple correlation between dimensions. Not predictive. Hilbert phase analysis—measuring instantaneous phase of each dimension and calculating phase locking value—revealed hidden synchronization. When PLV > 0.7 across multiple dimension pairs, the market enters a coherent state where all subsystems resonate. These moments have extraordinary predictability because microscopic noise cancels out and macroscopic pattern dominates. Emergence signals require high PLV for this reason. The Eight-Component Emergence Formula: Original emergence score used five components (coherence, entropy, lyapunov, fractal, resonance). Performance was good but not exceptional. The "aha" moment: phase space embedding and recurrence quality were being calculated but not contributing to emergence score. Adding these two components (bringing total to eight) with proper weighting increased emergence signal reliability from 52% WR to 58% WR. All calculated metrics must contribute to the final score. If you compute something, use it. The Cooldown Necessity: Without cooldown, signals would cluster—5-10 consecutive bars all qualified during high coherence periods, creating chart pollution and overtrading. Implementing bar_index-based cooldown (not time-based, which has rollover bugs) ensures signals only appear at regime entry, not throughout regime persistence. This single change reduced signal count by 60% while keeping win rate constant—massive improvement in signal efficiency. 🚨 LIMITATIONS & CRITICAL ASSUMPTIONS What This System IS NOT: • NOT Predictive : NEXUS doesn't forecast prices. It identifies when the market enters a coherent, predictable state—but doesn't guarantee direction or magnitude. • NOT Holy Grail : Typical performance is 50-58% win rate with 1.5-2.0 avg R-multiple. This is probabilistic edge from complexity analysis, not certainty. • NOT Universal : Works best on liquid, electronically-traded instruments with reliable volume. Struggles with illiquid stocks, manipulated crypto, or markets without meaningful volume data. • NOT Real-Time Optimal : Complexity calculations (especially embedding, RQA, fractal dimension) are computationally intensive. Dashboard updates may lag by 1-2 seconds on slower connections. • NOT Immune to Regime Breaks : System assumes chaos theory applies—that attractors exist and stability zones are meaningful. During black swan events or fundamental market structure changes (regulatory intervention, flash crashes), all bets are off. Core Assumptions: 1. Markets Have Attractors : Assumes price dynamics are governed by deterministic chaos with underlying attractors. Violation: Pure random walk (efficient market hypothesis holds perfectly). 2. Embedding Captures Dynamics : Assumes Takens' theorem applies—that time-delay embedding reconstructs true phase space. Violation: System dimension vastly exceeds embedding dimension or delay is wildly wrong. 3. Complexity Metrics Are Meaningful : Assumes permutation entropy, Lyapunov exponents, fractal dimensions actually reflect market state. Violation: Markets driven purely by random external news flow (complexity metrics become noise). 4. Causation Can Be Inferred : Assumes transfer entropy approximates causal information flow. Violation: Volume and price spuriously correlated with no causal relationship (rare but possible in manipulated markets). 5. Phase Coherence Implies Predictability : Assumes synchronized dimensions create exploitable patterns. Violation: Coherence by chance during random period (false positive). 6. Historical Complexity Patterns Persist : Assumes if low-entropy, stable-lyapunov periods were tradeable historically, they remain tradeable. Violation: Fundamental regime change (market structure shifts, e.g., transition from floor trading to HFT). Performs Best On: • ES, NQ, RTY (major US index futures - high liquidity, clean volume data) • Major forex pairs: EUR/USD, GBP/USD, USD/JPY (24hr markets, good for phase analysis) • Liquid commodities: CL (crude oil), GC (gold), NG (natural gas) • Large-cap stocks: AAPL, MSFT, GOOGL, TSLA (>$10M daily volume, meaningful structure) • Major crypto on reputable exchanges: BTC, ETH on Coinbase/Kraken (avoid Binance due to manipulation) Performs Poorly On: • Low-volume stocks (<$1M daily volume) - insufficient liquidity for complexity analysis • Exotic forex pairs - erratic spreads, thin volume • Illiquid altcoins - wash trading, bot manipulation invalidates volume analysis • Pre-market/after-hours - gappy, thin, different dynamics • Binary events (earnings, FDA approvals) - discontinuous jumps violate dynamical systems assumptions • Highly manipulated instruments - spoofing and layering create false coherence Known Weaknesses: • Computational Lag : Complexity calculations require iterating over windows. On slow connections, dashboard may update 1-2 seconds after bar close. Signals may appear delayed. • Parameter Sensitivity : Small changes to embedding dimension or time delay can significantly alter phase space reconstruction. Requires careful calibration per instrument. • Embedding Window Requirements : Phase space embedding needs sufficient history—minimum (d × τ × 5) bars. If embedding_dimension=5 and time_delay=3, need 75+ bars. Early bars will be unreliable. • Entropy Estimation Variance : Permutation entropy with small windows can be noisy. Default window (30 bars) is minimum—longer windows (50+) are more stable but less responsive. • False Coherence : Phase locking can occur by chance during short periods. Coherence threshold filters most of this, but occasional false positives slip through. • Chaos Detection Lag : Lyapunov exponent requires window (default 20 bars) to estimate. Market can enter chaos and produce bad signal before λ > 0 is detected. Stability filter helps but doesn't eliminate this. • Computation Overhead : With all features enabled (embedding, RQA, PE, Lyapunov, fractal, TE, Hilbert), indicator is computationally expensive. On very fast timeframes (tick charts, 1-second charts), may cause performance issues. ⚠️ RISK DISCLOSURE Trading futures, forex, stocks, options, and cryptocurrencies involves substantial risk of loss and is not suitable for all investors. Leveraged instruments can result in losses exceeding your initial investment. Past performance, whether backtested or live, is not indicative of future results. The Dimensional Resonance Protocol, including its phase space reconstruction, complexity analysis, and emergence detection algorithms, is provided for educational and research purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any security or instrument. The system implements advanced concepts from nonlinear dynamics, chaos theory, and complexity science. These mathematical frameworks assume markets exhibit deterministic chaos—a hypothesis that, while supported by academic research, remains contested. Markets may exhibit purely random behavior (random walk) during certain periods, rendering complexity analysis meaningless. Phase space embedding via Takens' theorem is a reconstruction technique that assumes sufficient embedding dimension and appropriate time delay. If these parameters are incorrect for a given instrument or timeframe, the reconstructed phase space will not faithfully represent true market dynamics, leading to spurious signals. Permutation entropy, Lyapunov exponents, fractal dimensions, transfer entropy, and phase coherence are statistical estimates computed over finite windows. All have inherent estimation error. Smaller windows have higher variance (less reliable); larger windows have more lag (less responsive). There is no universally optimal window size. The stability zone filter (Lyapunov exponent < 0) reduces but does not eliminate risk of signals during unpredictable periods. Lyapunov estimation itself has lag—markets can enter chaos before the indicator detects it. Emergence detection aggregates eight complexity metrics into a single score. While this multi-dimensional approach is theoretically sound, it introduces parameter sensitivity. Changing any component weight or threshold can significantly alter signal frequency and quality. Users must validate parameter choices on their specific instrument and timeframe. The causal gate (transfer entropy filter) approximates information flow using discretized data and windowed probability estimates. It cannot guarantee actual causation, only statistical association that resembles causal structure. Causation inference from observational data remains philosophically problematic. Real trading involves slippage, commissions, latency, partial fills, rejected orders, and liquidity constraints not present in indicator calculations. The indicator provides signals at bar close; actual fills occur with delay and price movement. Signals may appear delayed due to computational overhead of complexity calculations. Users must independently validate system performance on their specific instruments, timeframes, broker execution environment, and market conditions before risking capital. Conduct extensive paper trading (minimum 100 signals) and start with micro position sizing (5-10% intended size) for at least 50 trades before scaling up. Never risk more capital than you can afford to lose completely. Use proper position sizing (0.5-2% risk per trade maximum). Implement stop losses on every trade. Maintain adequate margin/capital reserves. Understand that most retail traders lose money. Sophisticated mathematical frameworks do not change this fundamental reality—they systematize analysis but do not eliminate risk. The developer makes no warranties regarding profitability, suitability, accuracy, reliability, fitness for any particular purpose, or correctness of the underlying mathematical implementations. Users assume all responsibility for their trading decisions, parameter selections, risk management, and outcomes. By using this indicator, you acknowledge that you have read, understood, and accepted these risk disclosures and limitations, and you accept full responsibility for all trading activity and potential losses. 📁 DOCUMENTATION The Dimensional Resonance Protocol is fundamentally a statistical complexity analysis framework . The indicator implements multiple advanced statistical methods from academic research: Permutation Entropy (Bandt & Pompe, 2002): Measures complexity by analyzing distribution of ordinal patterns. Pure statistical concept from information theory. Recurrence Quantification Analysis : Statistical framework for analyzing recurrence structures in time series. Computes recurrence rate, determinism, and diagonal line statistics. Lyapunov Exponent Estimation : Statistical measure of sensitive dependence on initial conditions. Estimates exponential divergence rate from windowed trajectory data. Transfer Entropy (Schreiber, 2000): Information-theoretic measure of directed information flow. Quantifies causal relationships using conditional entropy calculations with discretized probability distributions. Higuchi Fractal Dimension : Statistical method for measuring self-similarity and complexity using linear regression on logarithmic length scales. Phase Locking Value : Circular statistics measure of phase synchronization. Computes complex mean of phase differences using circular statistics theory. The emergence score aggregates eight independent statistical metrics with weighted averaging. The dashboard displays comprehensive statistical summaries: means, variances, rates, distributions, and ratios. Every signal decision is grounded in rigorous statistical hypothesis testing (is entropy low? is lyapunov negative? is coherence above threshold?). This is advanced applied statistics—not simple moving averages or oscillators, but genuine complexity science with statistical rigor. Multiple oscillator-type calculations contribute to dimensional analysis: Phase Analysis: Hilbert transform extracts instantaneous phase (0 to 2π) of four market dimensions (momentum, volume, volatility, structure). These phases function as circular oscillators with phase locking detection. Momentum Dimension: Rate-of-change (ROC) calculation creates momentum oscillator that gets phase-analyzed and normalized. Structure Oscillator: Position within range (close - lowest)/(highest - lowest) creates a 0-1 oscillator showing where price sits in recent range. This gets embedded and phase-analyzed. Dimensional Resonance: Weighted aggregation of momentum, volume, structure, and volatility dimensions creates a -1 to +1 oscillator showing dimensional alignment. Similar to traditional oscillators but multi-dimensional. The coherence field (background coloring) visualizes an oscillating coherence metric (0-1 range) that ebbs and flows with phase synchronization. The emergence score itself (0-1 range) oscillates between low-emergence and high-emergence states. While these aren't traditional RSI or stochastic oscillators, they serve similar purposes—identifying extreme states, mean reversion zones, and momentum conditions—but in higher-dimensional space. Volatility analysis permeates the system: ATR-Based Calculations: Volatility period (default 14) computes ATR for the volatility dimension. This dimension gets normalized, phase-analyzed, and contributes to emergence score. Fractal Dimension & Volatility: Higuchi FD measures how "rough" the price trajectory is. Higher FD (>1.6) correlates with higher volatility/choppiness. FD < 1.4 indicates smooth trends (lower effective volatility). Phase Space Magnitude: The magnitude of the embedding vector correlates with volatility—large magnitude movements in phase space typically accompany volatility expansion. This is the "energy" of the market trajectory. Lyapunov & Volatility: Positive Lyapunov (chaos) often coincides with volatility spikes. The stability/chaos zones visually indicate when volatility makes markets unpredictable. Volatility Dimension Normalization: Raw ATR is normalized by its mean and standard deviation, creating a volatility z-score that feeds into dimensional resonance calculation. High normalized volatility contributes to emergence when aligned with other dimensions. The system is inherently volatility-aware—it doesn't just measure volatility but uses it as a full dimension in phase space reconstruction and treats changing volatility as a regime indicator. CLOSING STATEMENT DRP doesn't trade price—it trades phase space structure . It doesn't chase patterns—it detects emergence . It doesn't guess at trends—it measures coherence . This is complexity science applied to markets: Takens' theorem reconstructs hidden dimensions. Permutation entropy measures order. Lyapunov exponents detect chaos. Transfer entropy reveals causation. Hilbert phases find synchronization. Fractal dimensions quantify self-similarity. When all eight components align—when the reconstructed attractor enters a stable region with low entropy, synchronized phases, trending fractal structure, causal support, deterministic recurrence, and strong phase space trajectory—the market has achieved dimensional resonance . These are the highest-probability moments. Not because an indicator said so. Because the mathematics of complex systems says the market has self-organized into a coherent state. Most indicators see shadows on the wall. DRP reconstructs the cave. "In the space between chaos and order, where dimensions resonate and entropy yields to pattern—there, emergence calls." DRP Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
مؤشر Pine Script®
من ‎DskyzInvestments‎
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Seasonality Heatmap [QuantAlgo]🟢 Overview The Seasonality Heatmap analyzes years of historical data to reveal which months and weekdays have consistently produced gains or losses, displaying results through color-coded tables with statistical metrics like consistency scores (1-10 rating) and positive occurrence rates. By calculating average returns for each calendar month and day-of-week combination, it identifies recognizable seasonal patterns (such as which months or weekdays tend to rally versus decline) and synthesizes this into actionable buy low/sell high timing possibilities for strategic entries and exits. This helps traders and investors spot high-probability seasonal windows where assets have historically shown strength or weakness, enabling them to align positions with recurring bull and bear market patterns. 🟢 How It Works 1. Monthly Heatmap How % Return is Calculated: The indicator fetches monthly closing prices (or Open/High/Low based on user selection) and calculates the percentage change from the previous month: (Current Month Price - Previous Month Price) / Previous Month Price × 100 Each cell in the heatmap represents one month's return in a specific year, creating a multi-year historical view Colors indicate performance intensity: greener/brighter shades for higher positive returns, redder/brighter shades for larger negative returns What Averages Mean: The "Avg %" row displays the arithmetic mean of all historical returns for each calendar month (e.g., averaging all Januaries together, all Februaries together, etc.) This metric identifies historically recurring patterns by showing which months have tended to rise or fall on average Positive averages indicate months that have typically trended upward; negative averages indicate historically weaker months Example: If April shows +18.56% average, it means April has averaged a 18.56% gain across all years analyzed What Months Up % Mean: Shows the percentage of historical occurrences where that month had a positive return (closed higher than the previous month) Calculated as: (Number of Months with Positive Returns / Total Months) × 100 Values above 50% indicate the month has been positive more often than negative; below 50% indicates more frequent negative months Example: If October shows "64%", then 64% of all historical Octobers had positive returns What Consistency Score Means: A 1-10 rating that measures how predictable and stable a month's returns have been Calculated using the coefficient of variation (standard deviation / mean) - lower variation = higher consistency High scores (8-10, green): The month has shown relatively stable behavior with similar outcomes year-to-year Medium scores (5-7, gray): Moderate consistency with some variability Low scores (1-4, red): High variability with unpredictable behavior across different years Example: A consistency score of 8/10 indicates the month has exhibited recognizable patterns with relatively low deviation What Best Means: Shows the highest percentage return achieved for that specific month, along with the year it occurred Reveals the maximum observed upside and identifies outlier years with exceptional performance Useful for understanding the range of possible outcomes beyond the average Example: "Best: 2016: +131.90%" means the strongest January in the dataset was in 2016 with an 131.90% gain What Worst Means: Shows the most negative percentage return for that specific month, along with the year it occurred Reveals maximum observed downside and helps understand the range of historical outcomes Important for risk assessment even in months with positive averages Example: "Worst: 2022: -26.86%" means the weakest January in the dataset was in 2022 with a 26.86% loss 2. Day-of-Week Heatmap How % Return is Calculated: Calculates the percentage change from the previous day's close to the current day's price (based on user's price source selection) Returns are aggregated by day of the week within each calendar month (e.g., all Mondays in January, all Tuesdays in January, etc.) Each cell shows the average performance for that specific day-month combination across all historical data Formula: (Current Day Price - Previous Day Close) / Previous Day Close × 100 What Averages Mean: The "Avg %" row at the bottom aggregates all months together to show the overall average return for each weekday Identifies broad weekly patterns across the entire dataset Calculated by summing all daily returns for that weekday across all months and dividing by total observations Example: If Monday shows +0.04%, Mondays have averaged a 0.04% change across all months in the dataset What Days Up % Mean: Shows the percentage of historical occurrences where that weekday had a positive return Calculated as: (Number of Positive Days / Total Days Observed) × 100 Values above 50% indicate the day has been positive more often than negative; below 50% indicates more frequent negative days Example: If Fridays show "54%", then 54% of all Fridays in the dataset had positive returns What Consistency Score Means: A 1-10 rating measuring how stable that weekday's performance has been across different months Based on the coefficient of variation of daily returns for that weekday across all 12 months High scores (8-10, green): The weekday has shown relatively consistent behavior month-to-month Medium scores (5-7, gray): Moderate consistency with some month-to-month variation Low scores (1-4, red): High variability across months, with behavior differing significantly by calendar month Example: A consistency score of 7/10 for Wednesdays means they have performed with moderate consistency throughout the year What Best Means: Shows which calendar month had the strongest average performance for that specific weekday Identifies favorable day-month combinations based on historical data Format shows the month abbreviation and the average return achieved Example: "Best: Oct: +0.20%" means Mondays averaged +0.20% during October months in the dataset What Worst Means: Shows which calendar month had the weakest average performance for that specific weekday Identifies historically challenging day-month combinations Useful for understanding which month-weekday pairings have shown weaker performance Example: "Worst: Sep: -0.35%" means Tuesdays averaged -0.35% during September months in the dataset 3. Optimal Timing Table/Summary Table → Best Month to BUY: Identifies the month with the lowest average return (most negative or least positive historically), representing periods where prices have historically been relatively lower Based on the observation that buying during historically weaker months may position for subsequent recovery Shows the month name, its average return, and color-coded performance Example: If May shows -0.86% as "Best Month to BUY", it means May has historically averaged -0.86% in the analyzed period → Best Month to SELL: Identifies the month with the highest average return (most positive historically), representing periods where prices have historically been relatively higher Based on historical strength patterns in that month Example: If July shows +1.42% as "Best Month to SELL", it means July has historically averaged +1.42% gains → 2nd Best Month to BUY: The second-lowest performing month based on average returns Provides an alternative timing option based on historical patterns Offers flexibility for staged entries or when the primary month doesn't align with strategy Example: Identifies the next-most favorable historical buying period → 2nd Best Month to SELL: The second-highest performing month based on average returns Provides an alternative exit timing based on historical data Useful for staged profit-taking or multiple exit opportunities Identifies the secondary historical strength period Note: The same logic applies to "Best Day to BUY/SELL" and "2nd Best Day to BUY/SELL" rows, which identify weekdays based on average daily performance across all months. Days with lowest averages are marked as buying opportunities (historically weaker days), while days with highest averages are marked for selling (historically stronger days). 🟢 Examples Example 1: NVIDIA NASDAQ:NVDA - Strong May Pattern with High Consistency Analyzing NVIDIA from 2015 onwards, the Monthly Heatmap reveals May averaging +15.84% with 82% of months being positive and a consistency score of 8/10 (green). December shows -1.69% average with only 40% of months positive and a low 1/10 consistency score (red). The Optimal Timing table identifies December as "Best Month to BUY" and May as "Best Month to SELL." A trader recognizes this high-probability May strength pattern and considers entering positions in late December when prices have historically been weaker, then taking profits in May when the seasonal tailwind typically peaks. The high consistency score in May (8/10) provides additional confidence that this pattern has been relatively stable year-over-year. Example 2: Crypto Market Cap CRYPTOCAP:TOTALES - October Rally Pattern An investor examining total crypto market capitalization notices September averaging -2.42% with 45% of months positive and 5/10 consistency, while October shows a dramatic shift with +16.69% average, 90% of months positive, and an exceptional 9/10 consistency score (blue). The Day-of-Week heatmap reveals Mondays averaging +0.40% with 54% positive days and 9/10 consistency (blue), while Thursdays show only +0.08% with 1/10 consistency (yellow). The investor uses this multi-layered analysis to develop a strategy: enter crypto positions on Thursdays during late September (combining the historically weak month with the less consistent weekday), then hold through October's historically strong period, considering exits on Mondays when intraweek strength has been most consistent. Example 3: Solana BINANCE:SOLUSDT - Extreme January Seasonality A cryptocurrency trader analyzing Solana observes an extraordinary January pattern: +59.57% average return with 60% of months positive and 8/10 consistency (teal), while May shows -9.75% average with only 33% of months positive and 6/10 consistency. August also displays strength at +59.50% average with 7/10 consistency. The Optimal Timing table confirms May as "Best Month to BUY" and January as "Best Month to SELL." The Day-of-Week data shows Sundays averaging +0.77% with 8/10 consistency (teal). The trader develops a seasonal rotation strategy: accumulate SOL positions during May weakness, hold through the historically strong January period (which has shown this extreme pattern with reasonable consistency), and specifically target Sunday exits when the weekday data shows the most recognizable strength pattern.
مؤشر Pine Script®
من ‎QuantAlgo‎
2
ICT Killzones and Sessions W/ Silver Bullet + MacrosForex and Equity Session Tracker with Killzones, Silver Bullet, and Macro Times This Pine Script indicator is a comprehensive timekeeping tool designed specifically for ICT traders using any time-based strategy. It helps you visualize and keep track of forex and equity session times, kill zones, macro times, and silver bullet hours. Features: Session and Killzone Lines: Green: London Open (LO) White: New York (NY) Orange: Australian (AU) Purple: Asian (AS) Includes AM and PM session markers. Dotted/Striped Lines indicate overlapping kill zones within the session timeline. Customization Options: Display sessions and killzones in collapsed or full view. Hide specific sessions or killzones based on your preferences. Customize colors, texts, and sizes. Option to hide drawings older than the current day. Automatic Updates: The indicator draws all lines and boxes at the start of a new day. Automatically adjusts time-based boxes according to the New York timezone. Killzone Time Windows (for indices): London KZ: 02:00 - 05:00 New York AM KZ: 07:00 - 10:00 New York PM KZ: 13:30 - 16:00 Silver Bullet Times: 03:00 - 04:00 10:00 - 11:00 14:00 - 15:00 Macro Times: 02:33 - 03:00 04:03 - 04:30 08:50 - 09:10 09:50 - 10:10 10:50 - 11:10 11:50 - 12:50 Latest Update: January 15: Added option to automatically change text coloring based on the chart. Included additional optional macro times per user request: 12:50 - 13:10 13:50 - 14:15 14:50 - 15:10 15:50 - 16:15 Usage: To maximize your experience, minimize the pane where the script is drawn. This minimizes distractions while keeping the essential time markers visible. The script is designed to help traders by clearly annotating key trading periods without overwhelming their charts. Originality and Justification: This indicator uniquely integrates various time-based strategies essential for ICT traders. Unlike other indicators, it consolidates session times, kill zones, macro times, and silver bullet hours into one comprehensive tool. This allows traders to have a clear and organized view of critical trading periods, facilitating better decision-making. Credits: This script incorporates open-source elements with significant improvements to enhance functionality and user experience. Forex and Equity Session Tracker with Killzones, Silver Bullet, and Macro Times This Pine Script indicator is a comprehensive timekeeping tool designed specifically for ICT traders using any time-based strategy. It helps you visualize and keep track of forex and equity session times, kill zones, macro times, and silver bullet hours. Features: Session and Killzone Lines: Green: London Open (LO) White: New York (NY) Orange: Australian (AU) Purple: Asian (AS) Includes AM and PM session markers. Dotted/Striped Lines indicate overlapping kill zones within the session timeline. Customization Options: Display sessions and killzones in collapsed or full view. Hide specific sessions or killzones based on your preferences. Customize colors, texts, and sizes. Option to hide drawings older than the current day. Automatic Updates: The indicator draws all lines and boxes at the start of a new day. Automatically adjusts time-based boxes according to the New York timezone. Killzone Time Windows (for indices): London KZ: 02:00 - 05:00 New York AM KZ: 07:00 - 10:00 New York PM KZ: 13:30 - 16:00 Silver Bullet Times: 03:00 - 04:00 10:00 - 11:00 14:00 - 15:00 Macro Times: 02:33 - 03:00 04:03 - 04:30 08:50 - 09:10 09:50 - 10:10 10:50 - 11:10 11:50 - 12:50 Latest Update: January 15: Added option to automatically change text coloring based on the chart. Included additional optional macro times per user request: 12:50 - 13:10 13:50 - 14:15 14:50 - 15:10 15:50 - 16:15 ICT Sessions and Kill Zones What They Are: ICT Sessions: These are specific times during the trading day when market activity is expected to be higher, such as the London Open, New York Open, and the Asian session. Kill Zones: These are specific time windows within these sessions where the probability of significant price movements is higher. For example, the New York AM Kill Zone is typically from 8:30 AM to 11:00 AM EST. How to Use Them: Identify the Session: Determine which trading session you are in (London, New York, or Asian). Focus on Kill Zones: Within that session, focus on the kill zones for potential trade setups. For instance, during the New York session, look for setups between 8:30 AM and 11:00 AM EST. Silver Bullets What They Are: Silver Bullets: These are specific, high-probability trade setups that occur within the kill zones. They are designed to be "one shot, one kill" trades, meaning they aim for precise and effective entries and exits. How to Use Them: Time-Based Setup: Look for these setups within the designated kill zones. For example, between 10:00 AM and 11:00 AM for the New York AM session . Chart Analysis: Start with higher time frames like the 15-minute chart and then refine down to 5-minute and 1-minute charts to identify imbalances or specific patterns . Macros What They Are: Macros: These are broader market conditions and trends that influence your trading decisions. They include understanding the overall market direction, seasonal tendencies, and the Commitment of Traders (COT) reports. How to Use Them: Understand Market Conditions: Be aware of the macroeconomic factors and market conditions that could affect price movements. Seasonal Tendencies: Know the seasonal patterns that might influence the market direction. COT Reports: Use the Commitment of Traders reports to understand the positioning of large traders and commercial hedgers . Putting It All Together Preparation: Understand the macro conditions and review the COT reports. Session and Kill Zone: Identify the trading session and focus on the kill zones. Silver Bullet Setup: Look for high-probability setups within the kill zones using refined chart analysis. Execution: Execute the trade with precision, aiming for a "one shot, one kill" outcome. By following these steps, you can effectively use ICT sessions, kill zones, silver bullets, and macros to enhance your trading strategy. Usage: To maximize your experience, shrink the pane where the script is drawn. This minimizes distractions while keeping the essential time markers visible. The script is designed to help traders by clearly annotating key trading periods without overwhelming their charts. Originality and Justification: This indicator uniquely integrates various time-based strategies essential for ICT traders. Unlike other indicators, it consolidates session times, kill zones, macro times, and silver bullet hours into one comprehensive tool. This allows traders to have a clear and organized view of critical trading periods, facilitating better decision-making. Credits: This script incorporates open-source elements with significant improvements to enhance functionality and user experience. All credit goes to itradesize for the SB + Macro boxes
مؤشر Pine Script®
من ‎SpxGh0st‎
5
Take Profit ModelThis Indicator allows you to define 9 Taking Profit levels between your floor price and a target price you define for 10 selectable Assets and tweak the levels to your preference. It does not do any fancy dynamic calculations, it just draws lines on the chart where you want them so that you have an easy reference for when to take profit (or not). Example: So, if your floor price for an asset is e.g. $10 and your target price is $110 (its up to you to define, who knows right, I do not have a crystal ball), You have a range of $100 where you can set your levels as follows The first level is the Floor price you entered = $10 Formula: Level x (Target - Floor) + Floor = Take Profit level Levels 0.1 x (110 - 10) + 10 = $20 0.2 x (110 - 10) + 10 = $30 0.3 x (110 - 10) + 10 = $40 0.4 x (110 - 10) + 10 = $50 0.5 x (110 - 10) + 10 = $60 0.6 x (110 - 10) + 10 = $70 0.7 x (110 - 10) + 10 = $80 0.8 x (110 - 10) + 10 = $90 0.9 x (110 - 10) + 10 = $100 And finally the last level is drawn for the target price Target Price = $110 To change the settings, go to the cog icon of the Indicator, select the assets (Tickers) you have and next enter a value between 0 and 1 (as shown above) for each level, and if you want a different color. Instead of using 0.1-0.9 you e.g. can also use Fibonacci numbers like 0.235, 0.382, 0.618, 0.786 and disable (using the check mark) the rest of the levels. Experiment with this as you see fit. Make sure that the chart you are looking at in TradingView is the same as you select in the indicator configuration e.g. COINBASE:BTCUSD should be selected as the chart as well as the Ticker in the configuration. The Start date of the script is configurable (one date across all assets and levels) The colors of the Levels is configurable (I am colorblind so go wild) The standard values in the script are just examples, you need to determine the values that apply in your case and do your own research. Your feedback is most welcome
مؤشر Pine Script®
من ‎City028‎
Luxy Super-Duper SuperTrend Predictor Engine and Buy/Sell signalA professional trend-following grading system that analyzes historical trend patterns to provide statistical duration estimates using advanced similarity matching and k-nearest neighbors analysis. Combines adaptive Supertrend with intelligent duration statistics, multi-timeframe confluence, volume confirmation, and quality scoring to identify high-probability setups with data-driven target ranges across all timeframes. Note: All duration estimates are statistical calculations based on historical data, not guarantees of future performance. WHAT MAKES THIS DIFFERENT Unlike traditional SuperTrend indicators that only tell you trend direction, this system answers the critical question: "What is the typical duration for trends like this?" The Statistical Analysis Engine: • Analyzes your chart's last 15+ completed SuperTrend trends (bullish and bearish separately) • Uses k-nearest neighbors similarity matching to find historically similar setups • Calculates statistical duration estimates based on current market conditions • Learns from estimation errors and adapts over time (Advanced mode) • Displays visual duration analysis box showing median, average, and range estimates • Tracks Statistical accuracy with backtest statistics Complete Trading System: • Statistical trend duration analysis with three intelligence levels • Adaptive Supertrend with dynamic ATR-based bands • Multi-timeframe confluence analysis (6 timeframes: 5M to 1W) • Volume confirmation with spike detection and momentum tracking • Quality scoring system (0-70 points) rating each setup • One-click preset optimization for all trading styles • Anti-repaint guarantee on all signals and duration estimates METHODOLOGY CREDITS This indicator's approach is inspired by proven trading methodologies from respected market educators: • Mark Minervini - Volatility Contraction Pattern (VCP) and pullback entry techniques • William O'Neil - Volume confirmation principles and institutional buying patterns (CANSLIM methodology) • Dan Zanger - Volatility expansion entries and momentum breakout strategies Important: These are educational references only. This indicator does not guarantee any specific trading results. Always conduct your own analysis and risk management. KEY FEATURES 1. TREND DURATION ANALYSIS SYSTEM - The Core Innovation The statistical analysis engine is what sets this indicator apart from standard SuperTrend systems. It doesn't just identify trend changes - it provides statistical analysis of potential duration. How It Works: Step 1: Historical Tracking • Automatically records every completed SuperTrend trend (duration in bars) • Maintains separate databases for bullish trends and bearish trends • Stores up to 15 most recent trends of each type • Captures market conditions at each trend flip: volume ratio, ATR ratio, quality score, price distance from SuperTrend, proximity to support/resistance Step 2: Similarity Matching (k-Nearest Neighbors) • When new trend begins, system compares current conditions to ALL historical flips • Calculates similarity score based on: - Volume similarity (30% weight) - Is volume behaving similarly? - Volatility similarity (30% weight) - Is ATR/volatility similar? - Quality similarity (20% weight) - Is setup strength comparable? - Distance similarity (10% weight) - Is price distance from ST similar? - Support/Resistance proximity (10% weight) - Similar structural context? • Selects the 15 MOST SIMILAR historical trends (not just all trends) • This is like asking: "When conditions looked like this before, how long did trends last?" Step 3: Statistical Analysis • Calculates median duration (most common outcome) • Calculates average duration (mean of similar trends) • Determines realistic range (min to max of similar trends) • Applies exponential weighting (recent trends weighted more heavily) • Outputs confidence-weighted statistical estimate Step 4: Advanced Intelligence (Advanced Mode Only) The Advanced mode applies five sophisticated multipliers to refine estimates: A) Market Structure Multiplier (±30%): • Detects nearby support/resistance levels using pivot detection • If flip occurs NEAR a key level: Estimate adjusted -30% (expect bounce/rejection) • If flip occurs in open space: Estimate adjusted +30% (clear path for continuation) • Uses configurable lookback period and ATR-based proximity threshold B) Asset Type Multiplier (±40%): • Adjusts duration estimates based on asset volatility characteristics • Small Cap / Biotech: +40% (explosive, extended moves) • Tech Growth: +20% (momentum-driven, longer trends) • Blue Chip / Large Cap: 0% (baseline, steady trends) • Dividend / Value: -20% (slower, grinding trends) • Cyclical: Variable based on macro regime • Crypto / High Volatility: +30% (parabolic potential) C) Flip Strength Multiplier (±20%): • Analyzes the QUALITY of the trend flip itself • Strong flip (high volume + expanding ATR + quality score 60+): +20% • Weak flip (low volume + contracting ATR + quality score under 40): -20% • Logic: Historical data shows that powerful flips tend to be followed by longer trends D) Error Learning Multiplier (±15%): • Tracks Statistical accuracy over last 10 completed trends • Calculates error ratio: (estimated duration / Actual Duration) • If system consistently over-estimates: Apply -15% correction • If system consistently under-estimates: Apply +15% correction • Learns and adapts to current market regime E) Regime Detection Multiplier (±20%): • Analyzes last 3 trends of SAME TYPE (bull-to-bull or bear-to-bear) • Compares recent trend durations to historical average • If recent trends 20%+ longer than average: +20% adjustment (trending regime detected) • If recent trends 20%+ shorter than average: -20% adjustment (choppy regime detected) • Detects whether market is in trending or mean-reversion mode Three analysis modes: SIMPLE MODE - Basic Statistics • Uses raw median of similar trends only • No multipliers, no adjustments • Best for: Beginners, clean trending markets • Fastest calculations, minimal complexity STANDARD MODE - Full Statistical Analysis • Similarity matching with k-nearest neighbors • Exponential weighting of recent trends • Median, average, and range calculations • Best for: Most traders, general market conditions • Balance of accuracy and simplicity ADVANCED MODE - Statistics + Intelligence • Everything in Standard mode PLUS • All 5 advanced multipliers (structure, asset type, flip strength, learning, regime) • Highest Statistical accuracy in testing • Best for: Experienced traders, volatile/complex markets • Maximum intelligence, most adaptive Visual Duration Analysis Box: When a new trend begins (SuperTrend flip), a box appears on your chart showing: • Analysis Mode (Simple / Standard / Advanced) • Number of historical trends analyzed • Median expected duration (most likely outcome) • Average expected duration (mean of similar trends) • Range (minimum to maximum from similar trends) • Advanced multipliers breakdown (Advanced mode only) • Backtest accuracy statistics (if available) The box extends from the flip bar to the estimated endpoint based on historical data, giving you a visual target for trend duration. Box updates in real-time as trend progresses. Backtest & Accuracy Tracking: • System backtests its own duration estimates using historical data • Shows accuracy metrics: how well duration estimates matched actual durations • Tracks last 10 completed duration estimates separately • Displays statistics in dashboard and duration analysis boxes • Helps you understand statistical reliability on your specific symbol/timeframe Anti-Repaint Guarantee: • duration analysis boxes only appear AFTER bar close (barstate.isconfirmed) • Historical duration estimates never disappear or change • What you see in history is exactly what you would have seen real-time • No future data leakage, no lookahead bias 2. INTELLIGENT PRESET CONFIGURATIONS - One-Click Optimization Unlike indicators that require tedious parameter tweaking, this system includes professionally optimized presets for every trading style. Select your approach from the dropdown and ALL parameters auto-configure. "AUTO (DETECT FROM TF)" - RECOMMENDED The smartest option: automatically selects optimal settings based on your chart timeframe. • 1m-5m charts → Scalping preset (ATR: 7, Mult: 2.0) • 15m-1h charts → Day Trading preset (ATR: 10, Mult: 2.5) • 2h-4h-D charts → Swing Trading preset (ATR: 14, Mult: 3.0) • W-M charts → Position Trading preset (ATR: 21, Mult: 4.0) Benefits: • Zero configuration - works immediately • Always matched to your timeframe • Switch timeframe = automatic adjustment • Perfect for traders who use multiple timeframes "SCALPING (1-5M)" - Ultra-Fast Signals Optimized for: 1-5 minute charts, high-frequency trading, quick profits Target holding period: Minutes to 1-2 hours maximum Best markets: High-volume stocks, major crypto pairs, active futures Parameter Configuration: • Supertrend: ATR 7, Multiplier 2.0 (very sensitive) • Volume: MA 10, High 1.8x, Spike 3.0x (catches quick surges) • Volume Momentum: AUTO-DISABLED (too restrictive for fast scalping) • Quality minimum: 40 points (accepts more setups) • Duration Analysis: Uses last 15 trends with heavy recent weighting Trading Logic: Speed over precision. Short ATR period and low multiplier create highly responsive SuperTrend. Volume momentum filter disabled to avoid missing fast moves. Quality threshold relaxed to catch more opportunities in rapid market conditions. Signals per session: 5-15 typically Hold time: Minutes to couple hours Best for: Active traders with fast execution "DAY TRADING (15M-1H)" - Balanced Approach Optimized for: 15-minute to 1-hour charts, intraday moves, session-based trading Target holding period: 30 minutes to 8 hours (within trading day) Best markets: Large-cap stocks, major indices, established crypto Parameter Configuration: • Supertrend: ATR 10, Multiplier 2.5 (balanced) • Volume: MA 20, High 1.5x, Spike 2.5x (standard detection) • Volume Momentum: 5/20 periods (confirms intraday strength) • Quality minimum: 50 points (good setups preferred) • Duration Analysis: Balanced weighting of recent vs historical Trading Logic: The most balanced configuration. ATR 10 with multiplier 2.5 provides steady trend following that avoids noise while catching meaningful moves. Volume momentum confirms institutional participation without being overly restrictive. Signals per session: 2-5 typically Hold time: 30 minutes to full day Best for: Part-time and full-time active traders "SWING TRADING (4H-D)" - Trend Stability Optimized for: 4-hour to Daily charts, multi-day holds, trend continuation Target holding period: 2-15 days typically Best markets: Growth stocks, sector ETFs, trending crypto, commodity futures Parameter Configuration: • Supertrend: ATR 14, Multiplier 3.0 (stable) • Volume: MA 30, High 1.3x, Spike 2.2x (accumulation focus) • Volume Momentum: 10/30 periods (trend stability) • Quality minimum: 60 points (high-quality setups only) • Duration Analysis: Favors consistent historical patterns Trading Logic: Designed for substantial trend moves while filtering short-term noise. Higher ATR period and multiplier create stable SuperTrend that won't flip on minor corrections. Stricter quality requirements ensure only strongest setups generate signals. Signals per week: 2-5 typically Hold time: Days to couple weeks Best for: Part-time traders, swing style "POSITION TRADING (D-W)" - Long-Term Trends Optimized for: Daily to Weekly charts, major trend changes, portfolio allocation Target holding period: Weeks to months Best markets: Blue-chip stocks, major indices, established cryptocurrencies Parameter Configuration: • Supertrend: ATR 21, Multiplier 4.0 (very stable) • Volume: MA 50, High 1.2x, Spike 2.0x (long-term accumulation) • Volume Momentum: 20/50 periods (major trend confirmation) • Quality minimum: 70 points (excellent setups only) • Duration Analysis: Heavy emphasis on multi-year historical data Trading Logic: Conservative approach focusing on major trend changes. Extended ATR period and high multiplier create SuperTrend that only flips on significant reversals. Very strict quality filters ensure signals represent genuine long-term opportunities. Signals per month: 1-2 typically Hold time: Weeks to months Best for: Long-term investors, set-and-forget approach "CUSTOM" - Advanced Configuration Purpose: Complete manual control for experienced traders Use when: You understand the parameters and want specific optimization Best for: Testing new approaches, unusual market conditions, specific instruments Full control over: • All SuperTrend parameters • Volume thresholds and momentum periods • Quality scoring weights • analysis mode and multipliers • Advanced features tuning Preset Comparison Quick Reference: Chart Timeframe: Scalping (1M-5M) | Day Trading (15M-1H) | Swing (4H-D) | Position (D-W) Signals Frequency: Very High | High | Medium | Low Hold Duration: Minutes | Hours | Days | Weeks-Months Quality Threshold: 40 pts | 50 pts | 60 pts | 70 pts ATR Sensitivity: Highest | Medium | Lower | Lowest Time Investment: Highest | High | Medium | Lowest Experience Level: Expert | Advanced | Intermediate | Beginner+ 3. QUALITY SCORING SYSTEM (0-70 Points) Every signal is rated in real-time across three dimensions: Volume Confirmation (0-30 points): • Volume Spike (2.5x+ average): 30 points • High Volume (1.5x+ average): 20 points • Above Average (1.0x+ average): 10 points • Below Average: 0 points Volatility Assessment (0-30 points): • Expanding ATR (1.2x+ average): 30 points • Rising ATR (1.0-1.2x average): 15 points • Contracting/Stable ATR: 0 points Volume Momentum (0-10 points): • Strong Momentum (1.2x+ ratio): 10 points • Rising Momentum (1.0-1.2x ratio): 5 points • Weak/Neutral Momentum: 0 points Score Interpretation: 60-70 points - EXCELLENT: • All factors aligned • High conviction setup • Maximum position size (within risk limits) • Primary trading opportunities 45-59 points - STRONG: • Multiple confirmations present • Above-average setup quality • Standard position size • Good trading opportunities 30-44 points - GOOD: • Basic confirmations met • Acceptable setup quality • Reduced position size • Wait for additional confirmation or trade smaller Below 30 points - WEAK: • Minimal confirmations • Low probability setup • Consider passing • Only for aggressive traders in strong trends Only signals meeting your minimum quality threshold (configurable per preset) generate alerts and labels. 4. MULTI-TIMEFRAME CONFLUENCE ANALYSIS The system can simultaneously analyze trend alignment across 6 timeframes (optional feature): Timeframes analyzed: • 5-minute (scalping context) • 15-minute (intraday momentum) • 1-hour (day trading bias) • 4-hour (swing context) • Daily (primary trend) • Weekly (macro trend) Confluence Interpretation: • 5-6/6 aligned - Very strong multi-timeframe agreement (highest confidence) • 3-4/6 aligned - Moderate agreement (standard setup) • 1-2/6 aligned - Weak agreement (caution advised) Dashboard shows real-time alignment count with color-coding. Higher confluence typically correlates with longer, stronger trends. 5. VOLUME MOMENTUM FILTER - Institutional Money Flow Unlike traditional volume indicators that just measure size, Volume Momentum tracks the RATE OF CHANGE in volume: How it works: • Compares short-term volume average (fast period) to long-term average (slow period) • Ratio above 1.0 = Volume accelerating (money flowing IN) • Ratio above 1.2 = Strong acceleration (institutional participation likely) • Ratio below 0.8 = Volume decelerating (money flowing OUT) Why it matters: • Confirms trend with actual money flow, not just price • Leading indicator (volume often leads price) • Catches accumulation/distribution before breakouts • More intuitive than complex mathematical filters Integration with signals: • Optional filter - can be enabled/disabled per preset • When enabled: Only signals with rising volume momentum fire • AUTO-DISABLED in Scalping mode (too restrictive for fast trading) • Configurable fast/slow periods per trading style 6. ADAPTIVE SUPERTREND MULTIPLIER Traditional SuperTrend uses fixed ATR multiplier. This system dynamically adjusts the multiplier (0.8x to 1.2x base) based on: • Trend Strength: Price correlation over lookback period • Volume Weight: Current volume relative to average Benefits: • Tighter bands in calm markets (less premature exits) • Wider bands in volatile conditions (avoids whipsaws) • Better adaptation to biotech, small-cap, and crypto volatility • Optional - can be disabled for classic constant multiplier 7. VISUAL GRADIENT RIBBON 26-layer exponential gradient fill between price and SuperTrend line provides instant visual trend strength assessment: Color System: • Green shades - Bullish trend + volume confirmation (strongest) • Blue shades - Bullish trend, normal volume • Orange shades - Bearish trend + volume confirmation • Red shades - Bearish trend (weakest) Opacity varies based on: • Distance from SuperTrend (farther = more opaque) • Volume intensity (higher volume = stronger color) The ribbon provides at-a-glance trend strength without cluttering your chart. Can be toggled on/off. 8. INTELLIGENT ALERT SYSTEM Two-tier alert architecture for flexibility: Automatic Alerts: • Fire automatically on BUY and SELL signals • Include full context: quality score, volume state, volume momentum • One alert per bar close (alert.freq_once_per_bar_close) • Message format: "BUY: Supertrend bullish + Quality: 65/70 | Volume: HIGH | Vol Momentum: STRONG (1.35x)" Customizable Alert Conditions: • Appear in TradingView's "Create Alert" dialog • Three options: BUY Signal Only, SELL Signal Only, ANY Signal (BUY or SELL) • Use TradingView placeholders: {{ticker}}, {{interval}}, {{close}}, {{time}} • Fully customizable message templates All alerts use barstate.isconfirmed - Zero repaint guarantee. 9. ANTI-REPAINT ARCHITECTURE Every component guaranteed non-repainting: • Entry signals: Only appear after bar close • duration analysis boxes: Created only on confirmed SuperTrend flips • Informative labels: Wait for bar confirmation • Alerts: Fire once per closed bar • Multi-timeframe data: Uses lookahead=barmerge.lookahead_off What you see in history is exactly what you would have seen in real-time. No disappearing signals, no changed duration estimates. HOW TO USE THE INDICATOR QUICK START - 3 Steps to Trading: Step 1: Select Your Trading Style Open indicator settings → "Quick Setup" section → Trading Style Preset dropdown Options: • Auto (Detect from TF) - RECOMMENDED: Automatically configures based on your chart timeframe • Scalping (1-5m) - For 1-5 minute charts, ultra-fast signals • Day Trading (15m-1h) - For 15m-1h charts, balanced approach • Swing Trading (4h-D) - For 4h-Daily charts, trend stability • Position Trading (D-W) - For Daily-Weekly charts, long-term trends • Custom - Manual configuration (advanced users only) Choose "Auto" and you're done - all parameters optimize automatically. Step 2: Understand the Signals BUY Signal (Green Triangle Below Price): • SuperTrend flipped bullish • Quality score meets minimum threshold (varies by preset) • Volume confirmation present (if filter enabled) • Volume momentum rising (if filter enabled) • duration analysis box shows expected trend duration SELL Signal (Red Triangle Above Price): • SuperTrend flipped bearish • Quality score meets minimum threshold • Volume confirmation present (if filter enabled) • Volume momentum rising (if filter enabled) • duration analysis box shows expected trend duration Duration Analysis Box: • Appears at SuperTrend flip (start of new trend) • Shows median, average, and range duration estimates • Extends to estimated endpoint based on historical data visually • Updates mode-specific intelligence (Simple/Standard/Advanced) Step 3: Use the Dashboard for Context Dashboard (top-right corner) shows real-time metrics: • Row 1 - Quality Score: Current setup rating (0-70) • Row 2 - SuperTrend: Direction and current level • Row 3 - Volume: Status (Spike/High/Normal/Low) with color • Row 4 - Volatility: State (Expanding/Rising/Stable/Contracting) • Row 5 - Volume Momentum: Ratio and trend • Row 6 - Duration Statistics: Accuracy metrics and track record Every cell has detailed tooltip - hover for full explanations. SIGNAL INTERPRETATION BY QUALITY SCORE: Excellent Setup (60-70 points): • Quality Score: 60-70 • Volume: Spike or High • Volatility: Expanding • Volume Momentum: Strong (1.2x+) • MTF Confluence (if enabled): 5-6/6 • Action: Primary trade - maximum position size (within risk limits) • Statistical reliability: Highest - duration estimates most accurate Strong Setup (45-59 points): • Quality Score: 45-59 • Volume: High or Above Average • Volatility: Rising • Volume Momentum: Rising (1.0-1.2x) • MTF Confluence (if enabled): 3-4/6 • Action: Standard trade - normal position size • Statistical reliability: Good - duration estimates reliable Good Setup (30-44 points): • Quality Score: 30-44 • Volume: Above Average • Volatility: Stable or Rising • Volume Momentum: Neutral to Rising • MTF Confluence (if enabled): 3-4/6 • Action: Cautious trade - reduced position size, wait for additional confirmation • Statistical reliability: Moderate - duration estimates less certain Weak Setup (Below 30 points): • Quality Score: Below 30 • Volume: Low or Normal • Volatility: Contracting or Stable • Volume Momentum: Weak • MTF Confluence (if enabled): 1-2/6 • Action: Pass or wait for improvement • Statistical reliability: Low - duration estimates unreliable USING duration analysis boxES FOR TRADE MANAGEMENT: Entry Timing: • Enter on SuperTrend flip (signal bar close) • duration analysis box appears simultaneously • Note the median duration - this is your expected hold time Profit Targets: • Conservative: Use MEDIAN duration as profit target (50% probability) • Moderate: Use AVERAGE duration (mean of similar trends) • Aggressive: Aim for MAX duration from range (best historical outcome) Position Management: • Scale out at median duration (take partial profits) • Trail stop as trend extends beyond median • Full exit at average duration or SuperTrend flip (whichever comes first) • Re-evaluate if trend exceeds estimated range analysis mode Selection: • Simple: Clean trending markets, beginners, minimal complexity • Standard: Most markets, most traders (recommended default) • Advanced: Volatile markets, complex instruments, experienced traders seeking highest accuracy Asset Type Configuration (Advanced Mode): If using Advanced analysis mode, configure Asset Type for optimal accuracy: • Small Cap: Stocks under $2B market cap, low liquidity • Biotech / Speculative: Clinical-stage pharma, penny stocks, high-risk • Blue Chip / Large Cap: S&P 500, mega-cap tech, stable large companies • Tech Growth: High-growth tech (TSLA, NVDA, growth SaaS) • Dividend / Value: Dividend aristocrats, value stocks, utilities • Cyclical: Energy, materials, industrials (macro-driven) • Crypto / High Volatility: Bitcoin, altcoins, highly volatile assets Correct asset type selection improves Statistical accuracy by 15-20%. RISK MANAGEMENT GUIDELINES: 1. Stop Loss Placement: Long positions: • Place stop below recent swing low OR • Place stop below SuperTrend level (whichever is tighter) • Use 1-2 ATR distance as guideline • Recommended: SuperTrend level (built-in volatility adjustment) Short positions: • Place stop above recent swing high OR • Place stop above SuperTrend level (whichever is tighter) • Use 1-2 ATR distance as guideline • Recommended: SuperTrend level 2. Position Sizing by Quality Score: • Excellent (60-70): Maximum position size (2% risk per trade) • Strong (45-59): Standard position size (1.5% risk per trade) • Good (30-44): Reduced position size (1% risk per trade) • Weak (Below 30): Pass or micro position (0.5% risk - learning trades only) 3. Exit Strategy Options: Option A - Statistical Duration-Based Exit: • Exit at median estimated duration (conservative) • Exit at average estimated duration (moderate) • Trail stop beyond average duration (aggressive) Option B - Signal-Based Exit: • Exit on opposite signal (SELL after BUY, or vice versa) • Exit on SuperTrend flip (trend reversal) • Exit if quality score drops below 30 mid-trend Option C - Hybrid (Recommended): • Take 50% profit at median estimated duration • Trail stop on remaining 50% using SuperTrend as trailing level • Full exit on SuperTrend flip or quality collapse 4. Trade Filtering: For higher win-rate (fewer trades, better quality): • Increase minimum quality score (try 60 for swing, 50 for day trading) • Enable volume momentum filter (ensure institutional participation) • Require higher MTF confluence (5-6/6 alignment) • Use Advanced analysis mode with appropriate asset type For more opportunities (more trades, lower quality threshold): • Decrease minimum quality score (40 for day trading, 35 for scalping) • Disable volume momentum filter • Lower MTF confluence requirement • Use Simple or Standard analysis mode SETTINGS OVERVIEW Quick Setup Section: • Trading Style Preset: Auto / Scalping / Day Trading / Swing / Position / Custom Dashboard & Display: • Show Dashboard (ON/OFF) • Dashboard Position (9 options: Top/Middle/Bottom + Left/Center/Right) • Text Size (Auto/Tiny/Small/Normal/Large/Huge) • Show Ribbon Fill (ON/OFF) • Show SuperTrend Line (ON/OFF) • Bullish Color (default: Green) • Bearish Color (default: Red) • Show Entry Labels - BUY/SELL signals (ON/OFF) • Show Info Labels - Volume events (ON/OFF) • Label Size (Auto/Tiny/Small/Normal/Large/Huge) Supertrend Configuration: • ATR Length (default varies by preset: 7-21) • ATR Multiplier Base (default varies by preset: 2.0-4.0) • Use Adaptive Multiplier (ON/OFF) - Dynamic 0.8x-1.2x adjustment • Smoothing Factor (0.0-0.5) - EMA smoothing applied to bands • Neutral Bars After Flip (0-10) - Hide ST immediately after flip Volume Momentum: • Enable Volume Momentum Filter (ON/OFF) • Fast Period (default varies by preset: 3-20) • Slow Period (default varies by preset: 10-50) Volume Analysis: • Volume MA Length (default varies by preset: 10-50) • High Volume Threshold (default: 1.5x) • Spike Threshold (default: 2.5x) • Low Volume Threshold (default: 0.7x) Quality Filters: • Minimum Quality Score (0-70, varies by preset) • Require Volume Confirmation (ON/OFF) Trend Duration Analysis: • Show Duration Analysis (ON/OFF) - Display duration analysis boxes • analysis mode - Simple / Standard / Advanced • Asset Type - 7 options (Small Cap, Biotech, Blue Chip, Tech Growth, Dividend, Cyclical, Crypto) • Use Exponential Weighting (ON/OFF) - Recent trends weighted more • Decay Factor (0.5-0.99) - How much more recent trends matter • Structure Lookback (3-30) - Pivot detection period for support/resistance • Proximity Threshold (xATR) - How close to level qualifies as "near" • Enable Error Learning (ON/OFF) - System learns from estimation errors • Memory Depth (3-20) - How many past errors to remember Box Visual Settings: • duration analysis box Border Color • duration analysis box Background Color • duration analysis box Text Color • duration analysis box Border Width • duration analysis box Transparency Multi-Timeframe (Optional Feature): • Enable MTF Confluence (ON/OFF) • Minimum Alignment Required (0-6) • Individual timeframe enable/disable toggles • Custom timeframe selection options All preset configurations override manual inputs except when "Custom" is selected. ADVANCED FEATURES 1. Scalpel Mode (Optional) Advanced pullback entry system that waits for healthy retracements within established trends before signaling entry: • Monitors price distance from SuperTrend levels • Requires pullback to configurable range (default: 30-50%) • Ensures trend remains intact before entry signal • Reduces whipsaw and false breakouts • Inspired by Mark Minervini's VCP pullback entries Best for: Swing traders and day traders seeking precision entries Scalpers: Consider disabling for faster entries 2. Error Learning System (Advanced analysis mode Only) The system learns from its own estimation errors: • Tracks last 10-20 completed duration estimates (configurable memory depth) • Calculates error ratio for each: estimated duration / Actual Duration • If system consistently over-estimates: Applies negative correction (-15%) • If system consistently under-estimates: Applies positive correction (+15%) • Adapts to current market regime automatically This self-correction mechanism improves accuracy over time as the system gathers more data on your specific symbol and timeframe. 3. Regime Detection (Advanced analysis mode Only) Automatically detects whether market is in trending or choppy regime: • Compares last 3 trends to historical average • Recent trends 20%+ longer → Trending regime (+20% to estimates) • Recent trends 20%+ shorter → Choppy regime (-20% to estimates) • Applied separately to bullish and bearish trends Helps duration estimates adapt to changing market conditions without manual intervention. 4. Exponential Weighting Option to weight recent trends more heavily than distant history: • Default decay factor: 0.9 • Recent trends get higher weight in statistical calculations • Older trends gradually decay in importance • Rationale: Recent market behavior more relevant than old data • Can be disabled for equal weighting 5. Backtest Statistics System backtests its own duration estimates using historical data: • Walks through past trends chronologically • Calculates what duration estimate WOULD have been at each flip • Compares to actual duration that occurred • Displays accuracy metrics in duration analysis boxes and dashboard • Helps assess statistical reliability on your specific chart Note: Backtest uses only data available AT THE TIME of each historical flip (no lookahead bias). TECHNICAL SPECIFICATIONS • Pine Script Version: v6 • Indicator Type: Overlay (draws on price chart) • Max Boxes: 500 (for duration analysis box storage) • Max Bars Back: 5000 (for comprehensive historical analysis) • Security Calls: 1 (for MTF if enabled - optimized) • Repainting: NO - All signals and duration estimates confirmed on bar close • Lookahead Bias: NO - All HTF data properly offset, all duration estimates use only historical data • Real-time Updates: YES - Dashboard and quality scores update live • Alert Capable: YES - Both automatic alerts and customizable alert conditions • Multi-Symbol: Works on stocks, crypto, forex, futures, indices Performance Optimization: • Conditional calculations (duration analysis can be disabled to reduce load) • Efficient array management (circular buffers for trend storage) • Streamlined gradient rendering (26 layers, can be toggled off) • Smart label cooldown system (prevents label spam) • Optimized similarity matching (analyzes only relevant trends) Data Requirements: • Minimum 50-100 bars for initial duration analysis (builds historical database) • Optimal: 500+ bars for robust statistical analysis • Longer history = more accurate duration estimates • Works on any timeframe from 1 minute to monthly KNOWN LIMITATIONS • Trending Markets Only: Performs best in clear trends. May generate false signals in choppy/sideways markets (use quality score filtering and regime detection to mitigate) • Lagging Nature: Like all trend-following systems, signals occur AFTER trend establishment, not at exact tops/bottoms. Use duration analysis boxes to set realistic profit targets. • Initial Learning Period: Duration analysis system requires 10-15 completed trends to build reliable historical database. Early duration estimates less accurate (first few weeks on new symbol/timeframe). • Visual Load: 26-layer gradient ribbon may slow performance on older devices. Disable ribbon if experiencing lag. • Statistical accuracy Variables: Duration estimates are statistical estimates, not guarantees. Accuracy varies by: - Market regime (trending vs choppy) - Asset volatility characteristics - Quality of historical pattern matches - Timeframe traded (higher TF = more reliable) • Not Best Suitable For: - Ultra-short-term scalping (sub-1-minute charts) - Mean-reversion strategies (designed for trend-following) - Range-bound trading (requires trending conditions) - News-driven spikes (estimates based on technical patterns, not fundamentals) FREQUENTLY ASKED QUESTIONS Q: Does this indicator repaint? A: Absolutely not. All signals, duration analysis boxes, labels, and alerts use barstate.isconfirmed checks. They only appear after the bar closes. What you see in history is exactly what you would have seen in real-time. Zero repaint guarantee. Q: How accurate are the trend duration estimates? A: Accuracy varies by mode, market conditions, and historical data quality: • Simple mode: 60-70% accuracy (within ±20% of actual duration) • Standard mode: 70-80% accuracy (within ±20% of actual duration) • Advanced mode: 75-85% accuracy (within ±20% of actual duration) Best accuracy achieved on: • Higher timeframes (4H, Daily, Weekly) • Trending markets (not choppy/sideways) • Assets with consistent behavior (Blue Chip, Large Cap) • After 20+ historical trends analyzed (builds robust database) Remember: All duration estimates are statistical calculations based on historical patterns, not guarantees. Q: Which analysis mode should I use? A: • Simple: Beginners, clean trending markets, want minimal complexity • Standard: Most traders, general market conditions (RECOMMENDED DEFAULT) • Advanced: Experienced traders, volatile/complex markets (biotech, small-cap, crypto), seeking maximum accuracy Advanced mode requires correct Asset Type configuration for optimal results. Q: What's the difference between the trading style presets? A: Each preset optimizes ALL parameters for a specific trading approach: • Scalping: Ultra-sensitive (ATR 7, Mult 2.0), more signals, shorter holds • Day Trading: Balanced (ATR 10, Mult 2.5), moderate signals, intraday holds • Swing Trading: Stable (ATR 14, Mult 3.0), fewer signals, multi-day holds • Position Trading: Very stable (ATR 21, Mult 4.0), rare signals, week/month holds Auto mode automatically selects based on your chart timeframe. Q: Should I use Auto mode or manually select a preset? A: Auto mode is recommended for most traders. It automatically matches settings to your timeframe and re-optimizes if you switch charts. Only use manual preset selection if: • You want scalping settings on a 15m chart (overriding auto-detection) • You want swing settings on a 1h chart (more conservative than auto would give) • You're testing different approaches on same timeframe Q: Can I use this for scalping and day trading? A: Absolutely! The preset system is specifically designed for all trading styles: • Select "Scalping (1-5m)" for 1-5 minute charts • Select "Day Trading (15m-1h)" for 15m-1h charts • Or use "Auto" mode and it configures automatically Volume momentum filter is auto-disabled in Scalping mode for faster signals. Q: What is Volume Momentum and why does it matter? A: Volume Momentum compares short-term volume (fast MA) to long-term volume (slow MA). It answers: "Is money flowing into this asset faster now than historically?" Why it matters: • Volume often leads price (early warning system) • Confirms institutional participation (smart money) • No lag like price-based indicators • More intuitive than complex mathematical filters When the ratio is above 1.2, you have strong evidence that institutions are accumulating (bullish) or distributing (bearish). Q: How do I set up alerts? A: Two options: Option 1 - Automatic Alerts: 1. Right-click on chart → Add Alert 2. Condition: Select this indicator 3. Choose "Any alert() function call" 4. Configure notification method (app, email, webhook) 5. You'll receive detailed alerts on every BUY and SELL signal Option 2 - Customizable Alert Conditions: 1. Right-click on chart → Add Alert 2. Condition: Select this indicator 3. You'll see three options in dropdown: - "BUY Signal" (long signals only) - "SELL Signal" (short signals only) - "ANY Signal" (both BUY and SELL) 4. Choose desired option and customize message template 5. Uses TradingView placeholders: {{ticker}}, {{close}}, {{time}}, etc. All alerts fire only on confirmed bar close (no repaint). Q: What is Scalpel Mode and should I use it? A: Scalpel Mode waits for healthy pullbacks within established trends before signaling entry. It reduces whipsaws and improves entry timing. Recommended ON for: • Swing traders (want precision entries on pullbacks) • Day traders (willing to wait for better prices) • Risk-averse traders (prefer fewer but higher-quality entries) Recommended OFF for: • Scalpers (need immediate entries, can't wait for pullbacks) • Momentum traders (want to enter on breakout, not pullback) • Aggressive traders (prefer more opportunities over precision) Q: Why do some duration estimates show wider ranges than others? A: Range width reflects historical trend variability: • Narrow range: Similar historical trends had consistent durations (high confidence) • Wide range: Similar historical trends had varying durations (lower confidence) Wide ranges often occur: • Early in analysis (fewer historical trends to learn from) • In volatile/choppy markets (inconsistent trend behavior) • On lower timeframes (more noise, less consistency) The median and average still provide useful targets even when range is wide. Q: Can I customize the dashboard position and appearance? A: Yes! Dashboard settings include: • Position: 9 options (Top/Middle/Bottom + Left/Center/Right) • Text Size: Auto, Tiny, Small, Normal, Large, Huge • Show/Hide: Toggle entire dashboard on/off Choose position that doesn't overlap important price action on your specific chart. Q: Which timeframe should I trade on? A: Depends on your trading style and time availability: • 1-5 minute: Active scalping, requires constant monitoring • 15m-1h: Day trading, check few times per session • 4h-Daily: Swing trading, check once or twice daily • Daily-Weekly: Position trading, check weekly General principle: Higher timeframes produce: • Fewer signals (less frequent) • Higher quality setups (stronger confirmations) • More reliable duration estimates (better statistical data) • Less noise (clearer trends) Start with Daily chart if new to trading. Move to lower timeframes as you gain experience. Q: Does this work on all markets (stocks, crypto, forex)? A: Yes, it works on all markets with trending characteristics: Excellent for: • Stocks (especially growth and momentum names) • Crypto (BTC, ETH, major altcoins) • Futures (indices, commodities) • Forex majors (EUR/USD, GBP/USD, etc.) Best results on: • Trending markets (not range-bound) • Liquid instruments (tight spreads, good fills) • Volatile assets (clear trend development) Less effective on: • Range-bound/sideways markets • Ultra-low volatility instruments • Illiquid small-caps (use caution) Configure Asset Type (in Advanced analysis mode) to match your instrument for best accuracy. Q: How many signals should I expect per day/week? A: Highly variable based on: By Timeframe: • 1-5 minute: 5-15 signals per session • 15m-1h: 2-5 signals per day • 4h-Daily: 2-5 signals per week • Daily-Weekly: 1-2 signals per month By Market Volatility: • High volatility = more SuperTrend flips = more signals • Low volatility = fewer flips = fewer signals By Quality Filter: • Higher threshold (60-70) = fewer but better signals • Lower threshold (30-40) = more signals, lower quality By Volume Momentum Filter: • Enabled = Fewer signals (only volume-confirmed) • Disabled = More signals (all SuperTrend flips) Adjust quality threshold and filters to match your desired signal frequency. Q: What's the difference between entry labels and info labels? A: Entry Labels (BUY/SELL): • Your primary trading signals • Based on SuperTrend flip + all confirmations (quality, volume, momentum) • Include quality score and confirmation icons • These are actionable entry points Info Labels (Volume Spike): • Additional market context • Show volume events that may support or contradict trend • 8-bar cooldown to prevent spam • NOT necessarily entry points - contextual information only Control separately: Can show entry labels without info labels (recommended for clean charts). Q: Can I combine this with other indicators? A: Absolutely! This works well with: • RSI: For divergences and overbought/oversold conditions • Support/Resistance: Confluence with key levels • Fibonacci Retracements: Pullback targets in Scalpel Mode • Price Action Patterns: Flags, pennants, cup-and-handle • MACD: Additional momentum confirmation • Bollinger Bands: Volatility context This indicator provides trend direction and duration estimates - complement with other tools for entry refinement and additional confluence. Q: Why did I get a low-quality signal? Can I filter them out? A: Yes! Increase the Minimum Quality Score in settings. If you're seeing signals with quality below your preference: • Day Trading: Set minimum to 50 • Swing Trading: Set minimum to 60 • Position Trading: Set minimum to 70 Only signals meeting the threshold will appear. This reduces frequency but improves win-rate. Q: How do I interpret the MTF Confluence count? A: Shows how many of 6 timeframes agree with current trend: • 6/6 aligned: Perfect agreement (extremely rare, highest confidence) • 5/6 aligned: Very strong alignment (high confidence) • 4/6 aligned: Good alignment (standard quality setup) • 3/6 aligned: Moderate alignment (acceptable) • 2/6 aligned: Weak alignment (caution) • 1/6 aligned: Very weak (likely counter-trend) Higher confluence typically correlates with longer, stronger trends. However, MTF analysis is optional - you can disable it and rely solely on quality scoring. Q: Is this suitable for beginners? A: Yes, but requires foundational knowledge: You should understand: • Basic trend-following concepts (higher highs, higher lows) • Risk management principles (position sizing, stop losses) • How to read candlestick charts • What volume and volatility mean Beginner-friendly features: • Auto preset mode (zero configuration) • Quality scoring (tells you signal strength) • Dashboard tooltips (hover for explanations) • duration analysis boxes (visual profit targets) Recommended for beginners: 1. Start with "Auto" or "Swing Trading" preset on Daily chart 2. Use Standard Analysis Mode (not Advanced) 3. Set minimum quality to 60 (fewer but better signals) 4. Paper trade first for 2-4 weeks 5. Study methodology references (Minervini, O'Neil, Zanger) Q: What is the Asset Type setting and why does it matter? A: Asset Type (in Advanced analysis mode) adjusts duration estimates based on volatility characteristics: • Small Cap: Explosive moves, extended trends (+30-40%) • Biotech / Speculative: Parabolic potential, news-driven (+40%) • Blue Chip / Large Cap: Baseline, steady trends (0% adjustment) • Tech Growth: Momentum-driven, longer trends (+20%) • Dividend / Value: Slower, grinding trends (-20%) • Cyclical: Macro-driven, variable (±10%) • Crypto / High Volatility: Parabolic potential (+30%) Correct configuration improves Statistical accuracy by 15-20%. Using Blue Chip settings on a biotech stock may underestimate trend length (you'll exit too early). Q: Can I backtest this indicator? A: Yes! TradingView's Strategy Tester works with this indicator's signals. To backtest: 1. Note the entry conditions (SuperTrend flip + quality threshold + filters) 2. Create a strategy script using same logic 3. Run Strategy Tester on historical data Additionally, the indicator includes BUILT-IN duration estimate validation: • System backtests its own duration estimates • Shows accuracy metrics in dashboard and duration analysis boxes • Helps assess reliability on your specific symbol/timeframe Q: Why does Volume Momentum auto-disable in Scalping mode? A: Scalping requires ultra-fast entries to catch quick moves. Volume Momentum filter adds friction by requiring volume confirmation before signaling, which can cause missed opportunities in rapid scalping. Scalping preset is optimized for speed and frequency - the filter is counterproductive for that style. It remains enabled for Day Trading, Swing Trading, and Position Trading presets where patience improves results. You can manually enable it in Custom mode if desired. Q: How much historical data do I need for accurate duration estimates? A: Minimum: 50-100 bars (indicator will function but duration estimates less reliable) Recommended: 500+ bars (robust statistical database) Optimal: 1000+ bars (maximum Statistical accuracy) More history = more completed trends = better pattern matching = more accurate duration estimates. New symbols or newly-switched timeframes will have lower Statistical accuracy initially. Allow 2-4 weeks for the system to build historical database. IMPORTANT DISCLAIMERS No Guarantee of Profit: This indicator is an educational tool and does not guarantee any specific trading results. All trading involves substantial risk of loss. Duration estimates are statistical calculations based on historical patterns and are not guarantees of future performance. Past Performance: Historical backtest results and Statistical accuracy statistics do not guarantee future performance. Market conditions change constantly. What worked historically may not work in current or future markets. Not Financial Advice: This indicator provides technical analysis signals and statistical duration estimates only. It is not financial, investment, or trading advice. Always consult with a qualified financial advisor before making investment decisions. Risk Warning: Trading stocks, options, futures, forex, and cryptocurrencies involves significant risk. You can lose all of your invested capital. Never trade with money you cannot afford to lose. Only risk capital you can lose without affecting your lifestyle. Testing Required: Always test this indicator on a demo account or with paper trading before risking real capital. Understand how it works in different market conditions. Verify Statistical accuracy on your specific instruments and timeframes before trusting it with real money. User Responsibility: You are solely responsible for your trading decisions. The developer assumes no liability for trading losses, incorrect duration estimates, software errors, or any other damages incurred while using this indicator. Statistical Estimation Limitations: Trend Duration estimates are statistical estimates based on historical pattern matching. They are NOT guarantees. Actual trend durations may differ significantly from duration estimates due to unforeseen news events, market regime changes, or lack of historical precedent for current conditions. CREDITS & ACKNOWLEDGMENTS Methodology Inspiration: • Mark Minervini - Volatility Contraction Pattern (VCP) concepts and pullback entry techniques • William O'Neil - Volume analysis principles and CANSLIM institutional buying patterns • Dan Zanger - Momentum breakout strategies and volatility expansion entries Technical Components: • SuperTrend calculation - Classic ATR-based trend indicator (public domain) • Statistical analysis - Standard median, average, range calculations • k-Nearest Neighbors - Classic machine learning similarity matching concept • Multi-timeframe analysis - Standard request.security implementation in Pine Script For questions, feedback, or support, please comment below or send a private message. Happy Trading!
مؤشر Pine Script®
من ‎orenluxy‎
32
Stochastic [Paifc0de]Stochastic — clean stochastic oscillator with visual masking, neutral markers, and basic filters What it does This indicator plots a standard stochastic oscillator (%K with smoothing and %D) and adds practical quality-of-life features for lower timeframes: optional visual masking when %K hugs overbought/oversold, neutral K–D cross markers, session-gated edge triangles (K crossing 20/80), and simple filters (minimum %K slope, minimum |K–D| gap, optional %D slope agreement, mid-zone mute, and a cooldown between markers). Display values are clamped to 0–100 to keep the panel scale stable. The tool is for research/education and does not generate entries/exits or financial advice. Default preset: 20 / 10 / 10 K Length = 20 Classic lookback used in many textbooks. On intraday charts it balances responsiveness and stability: short enough to react to momentum shifts, long enough to avoid constant whipsaws. In practice it captures ~the last 20 bars’ position of close within the high–low range. K Smoothing = 10 A 10-period SMA applied to the raw %K moderates the “saw-tooth” effect that raw stochastic can exhibit in choppy phases. The smoothing reduces over-reaction to micro spikes while preserving the main rhythm of swings; visually, %K becomes a continuous path that is easier to read. D Length = 10 %D is the moving average of smoothed %K. With 10, %D becomes a clearly slower guide line. The larger separation between %K(10-SMA) and %D(10-SMA of %K) produces cleaner crosses and fewer spurious toggles than micro settings (e.g., 3/3/3). On M5–M15 this pair often yields readable cross cycles without flooding the chart. How the 20/10/10 trio behaves In persistent trends, %K will spend more time near 20 or 80; the 10-period smoothing delays flips slightly and emphasizes only meaningful turn attempts. In ranges, %K oscillates around mid-zone (40–60). With 10/10 smoothing, cross signals cluster less densely; combining with the |K–D| gap filter helps keep only decisive crosses. If your symbol is unusually volatile or illiquid, reduce K Length (e.g., 14) or reduce K Smoothing (e.g., 7) to keep responsiveness. If crosses feel late, decrease D Length (e.g., 7). If noise is excessive, increase K Smoothing first, then consider raising D Length. Visuals OB/OS lines: default 80/20 reference levels and a midline at 50. Masking near edges: %K can be temporarily hidden when it is pressing an edge, approaching it with low slope, or going nearly flat near the boundary. This keeps the panel readable during “stuck at the edge” phases. Soft glow (optional): highlights %K’s active path; can be turned off. Light/Dark palette: quick toggle to match your chart theme. Scale safety: all plotted values (lines, fills, markers) are clamped to 0–100 to prevent the axis from expanding beyond the stochastic range. Markers and filters Neutral K–D cross markers: circles in the mid-zone when %K crosses %D. Edge triangles: show when %K crosses 20 or 80; can be restricted to a session window (02:00–12:00 ET). Filters (optional): Min %K slope: require a minimum absolute slope so very flat crosses are ignored. Min |K–D| gap: demand separation between lines at the cross moment. %D slope agreement: keep crosses that align with %D’s direction. Mid-zone mute: suppress crosses inside a user-defined 40–60 band (defaults). Cooldown: minimum bars between successive markers. Parameters (quick guide) K Length / K Smoothing / D Length: core stochastic settings. Start with 20/10/10; tune K Smoothing first if you see too much jitter. Overbought / Oversold (80/20): adjust for assets that tend to trend (raise to 85/15) or mean-revert (lower to 75/25). Slope & gap filters: increase on very noisy symbols; reduce if you miss too many crosses. Session window (triangles only): use if you want edge markers only during active hours. Marker size and offset: cosmetic; they do not affect calculations. Alerts K–D Cross Up (filtered) and K–D Cross Down (filtered): fire when a cross passes your filters/cooldown. Edge Up / Edge Down: fire when %K crosses the 20/80 levels. All alerts confirm on bar close. Notes & attribution Original implementation and integration by Paifc0de; no third-party code is copied. This indicator is for research/education and does not provide entries/exits or financial advice.
مؤشر Pine Script®
من ‎paifcode‎
维加斯双通道策略Vegas Channel Comprehensive Strategy Description Strategy Overview A comprehensive trading strategy based on the Vegas Dual Channel indicator, supporting dynamic position sizing and fund management. The strategy employs a multi-signal fusion mechanism including classic price crossover signals, breakout signals, and retest signals, combined with trend filtering, RSI+MACD filtering, and volume filtering to ensure signal reliability. Core Features Dynamic Position Sizing: Continue adding positions on same-direction signals, close all positions on opposite signals Smart Take Profit/Stop Loss: ATR-based dynamic TP/SL, updated with each new signal Fund Management: Supports dynamic total amount management for compound growth Time Filtering: Configurable trading time ranges Risk Control: Maximum order limit to prevent over-leveraging Leverage Usage Instructions Important: This strategy does not use TradingView's margin functionality Setup Method Total Amount = Actual Funds × Leverage Multiplier Example: Have 100U actual funds, want to use 10x leverage → Set total amount to 100 × 10 = 1000U Trading Amount Calculation Each trade percentage is calculated based on leveraged amount Example: Set 10% → Actually trade 100U margin × 10x leverage = 1000U trading amount Maximum Orders Configuration Must be used in conjunction with leveraged amount Example: 1000U total amount, 10% per trade, maximum 10 orders = maximum use of 1000U Note: Do not exceed 100% of total amount to avoid over-leveraging Parameter Configuration Recommendations Leverage Configuration Examples Actual funds 100U, 5x leverage, total amount setting 500U, 10% per trade, 50U per trade, recommended maximum orders 10 Actual funds 100U, 10x leverage, total amount setting 1000U, 10% per trade, 100U per trade, recommended maximum orders 10 Actual funds 100U, 20x leverage, total amount setting 2000U, 5% per trade, 100U per trade, recommended maximum orders 20 Risk Control Conservative: 5-10x leverage, 10% per trade, maximum 5-8 orders Aggressive: 10-20x leverage, 5-10% per trade, maximum 10-15 orders Extreme: 20x+ leverage, 2-5% per trade, maximum 20+ orders Strategy Advantages Signal Reliability: Multiple filtering mechanisms reduce false signals Capital Efficiency: Dynamic fund management for compound growth Risk Controllable: Maximum order limits prevent liquidation Flexible Configuration: Supports various leverage and fund allocation schemes Time Control: Configurable trading hours to avoid high-risk periods Usage Notes Ensure total amount is set correctly (actual funds × leverage multiplier) Maximum orders should not exceed the range allowed by total funds Recommend starting with conservative configuration and gradually adjusting parameters Regularly monitor strategy performance and adjust parameters timely 维加斯通道综合策略说明 策略概述 基于维加斯双通道指标的综合交易策略，支持动态加仓和资金管理。策略采用多信号融合机制，包括经典价穿信号、突破信号和回踩信号，结合趋势过滤、RSI+MACD过滤和成交量过滤，确保信号的可靠性。 核心功能 动态加仓：同向信号继续加仓，反向信号全部平仓 智能止盈止损：基于ATR的动态止盈止损，每次新信号更新 资金管理：支持动态总金额管理，实现复利增长 时间过滤：可设置交易时间范围 风险控制：最大订单数限制，防止过度加仓 杠杆使用说明 重要：本策略不使用TradingView的保证金功能 设置方法 总资金 = 实际资金 × 杠杆倍数 示例：实际有100U，想使用10倍杠杆 → 总资金设置为 100 × 10 = 1000U 交易金额计算 每笔交易百分比基于杠杆后的金额计算 示例：设置10% → 实际交易 100U保证金 × 10倍杠杆 = 1000U交易金额 最大订单数配置 必须配合杠杆后的金额使用 示例：1000U总资金，10%单笔，最大10单 = 最多使用1000U 注意：不要超过总资金的100%，避免过度杠杆 参数配置建议 杠杆配置示例 实际资金100U，5倍杠杆，总资金设置500U，单笔百分比10%，单笔金额50U，建议最大订单数10单 实际资金100U，10倍杠杆，总资金设置1000U，单笔百分比10%，单笔金额100U，建议最大订单数10单 实际资金100U，20倍杠杆，总资金设置2000U，单笔百分比5%，单笔金额100U，建议最大订单数20单 风险控制 保守型：5-10倍杠杆，10%单笔，最大5-8单 激进型：10-20倍杠杆，5-10%单笔，最大10-15单 极限型：20倍以上杠杆，2-5%单笔，最大20单以上 策略优势 信号可靠性：多重过滤机制，减少假信号 资金效率：动态资金管理，实现复利增长 风险可控：最大订单数限制，防止爆仓 灵活配置：支持多种杠杆和资金配置方案 时间控制：可设置交易时间，避开高风险时段 使用注意事项 确保总资金设置正确（实际资金×杠杆倍数） 最大订单数不要超过总资金允许的范围 建议从保守配置开始，逐步调整参数 定期监控策略表现，及时调整参数
استراتيجية Pine Script®
من ‎LaLaZioo‎
Trend Strength Meter [Eˣ]📊 Trend Strength Meter - Free Indicator Overview The Trend Strength Meter quantifies market momentum with a simple 0-100 score. No more guessing if a trend is strong or weak - this indicator gives you an objective, numerical measurement of trend strength that combines trend direction, momentum, volatility, and moving average alignment into one clear reading. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎯 What This Indicator Does Quantifies Trend Strength: • Measures trend on a scale from -100 (extreme bearish) to +100 (extreme bullish) • Combines 4 key components: Trend Direction, Momentum, Volatility, MA Alignment • Provides objective measurement instead of subjective interpretation • Works on all timeframes and instruments Visual Display: • Green Histogram Bars = Bullish strength (0 to +100) • Red Histogram Bars = Bearish strength (0 to -100) • Smooth Overlay Line = Trend direction (filters noise) • Triangle Markers = Trend reversals (zero-line crosses) • Background Zones = Visual strength categories Multi-Timeframe Analysis: • See strength readings from 3 timeframes simultaneously • Identify when trends align across multiple timeframes • "ALIGNED" indicator shows when all timeframes agree • Spot divergences between timeframes Clean & Professional: • Minimal clutter, maximum clarity • Compact info panel in top-right corner • No overwhelming indicators or text • Easy to read at a glance ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 Understanding The Strength Scale Bullish Readings (0 to +100) +75 to +100 - VERY STRONG BULL • Extremely powerful uptrend • All components aligned bullishly • Best time for aggressive long positions • Trend likely to continue • Strategy: Hold longs, avoid shorts +50 to +75 - STRONG BULL • Strong uptrend with good momentum • High probability of continuation • Quality long setups • Pullbacks are buying opportunities • Strategy: Enter longs on dips +25 to +50 - BULL • Moderate bullish trend • Decent upward momentum • Trend following longs work • Watch for weakening signals • Strategy: Ride the trend, trail stops +10 to +25 - WEAK BULL • Weak bullish bias • Trend may be exhausting • Lower probability setups • Consider taking profits • Strategy: Caution, reduce position sizes -10 to +10 - NEUTRAL • No clear trend • Choppy, range-bound market • Conflicting signals • Low probability for trend trades • Strategy: Stay flat or trade ranges Bearish Readings (0 to -100) -10 to -25 - WEAK BEAR • Weak bearish bias • Trend may be exhausting • Lower probability setups • Consider taking profits on shorts • Strategy: Caution, reduce position sizes -25 to -50 - BEAR • Moderate bearish trend • Decent downward momentum • Trend following shorts work • Watch for weakening signals • Strategy: Ride the trend down, trail stops -50 to -75 - STRONG BEAR • Strong downtrend with momentum • High probability of continuation • Quality short setups • Bounces are selling opportunities • Strategy: Enter shorts on rallies -75 to -100 - VERY STRONG BEAR • Extremely powerful downtrend • All components aligned bearishly • Best time for aggressive short positions • Trend likely to continue • Strategy: Hold shorts, avoid longs ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 How To Use This Indicator Basic Usage 1. Check Current Strength • Look at the histogram height and color • Read the exact number in the info panel • Note the status label (STRONG BULL, WEAK BEAR, etc.) • Higher absolute value = stronger trend 2. Watch For Reversals • Triangle markers appear when strength crosses zero • 🟢 Green triangle up = Bullish reversal signal • 🔴 Red triangle down = Bearish reversal signal • These mark potential trend changes 3. Monitor Multi-Timeframe Alignment • Check if all timeframes show same direction • "✓ ALIGNED" = All timeframes agree (high confidence) • "✗ Mixed" = Timeframes disagree (lower confidence) • Aligned trends have higher probability 4. Observe Strength Changes • Rising strength = Trend strengthening • Falling strength = Trend weakening • Strength near extremes (+75/-75) = Potential exhaustion • Strength near zero = Indecision/consolidation ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 Trading Strategies Strategy 1: Trend Following Best For: Capturing major moves Timeframes: 1H, 4H, Daily Rules: 1. Wait for strength to reach +50 or higher (or -50 or lower) 2. Check MTF alignment - all timeframes should agree 3. Enter on pullbacks in the direction of strength 4. Hold position while strength remains above +25 (or below -25) 5. Exit when strength crosses back to weak zone or reverses Example - Long Setup: • Strength crosses above +50 = Strong bull trend • All MTF readings positive and aligned • Wait for minor pullback to support • Enter long with stop below recent swing low • Hold while strength stays above +25 • Exit if strength drops below +10 or reverses to negative Strategy 2: Reversal Trading Best For: Catching trend changes early Timeframes: 15min, 1H, 4H Rules: 1. Watch for strength to reach extreme levels (+75 or -75) 2. Look for divergence (price new high/low but strength declining) 3. Wait for zero-line cross (triangle marker appears) 4. Enter in direction of new trend 5. Use tight stops since you're catching early Example - Bullish Reversal: • Strength at -80 (very strong bear) • Price makes new low but strength only at -70 = Divergence • Green triangle appears = Zero-line cross • Enter long on confirmation • Stop below recent swing low • Target: Strength reaching +50 Strategy 3: Avoid Bad Trades Best For: Improving win rate Timeframes: All Rules: • DON'T trade when strength is between -10 and +10 (neutral zone) • DON'T go long when strength is negative • DON'T go short when strength is positive • DON'T trade against MTF alignment • DO wait for clear strength readings Why It Works: Most losses come from trading in choppy markets or against the trend Strategy 4: Position Sizing Based On Strength Best For: Risk management Timeframes: All Rules: • Strength +75 to +100 or -75 to -100 = Full position size (2-3% risk) • Strength +50 to +75 or -50 to -75 = Normal position (1.5-2% risk) • Strength +25 to +50 or -25 to -50 = Reduced position (1% risk) • Strength -10 to +10 = No trades or minimal size (0.5% risk) Why It Works: Bigger positions in stronger trends, smaller in weak trends ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚙️ Settings Explained Multi-Timeframe Analysis • Toggle ON/OFF the MTF readings in the info panel • Turn OFF for cleaner display if you only trade one timeframe Timeframe 1, 2, 3 (Default: 15min, 1H, 4H) • Choose which timeframes to analyze • For day trading: Use 5min, 15min, 1H • For swing trading: Use 1H, 4H, Daily • For position trading: Use 4H, Daily, Weekly • Higher timeframes show bigger picture trends MA Length (Default: 20) • Moving average period for trend direction component • Lower values (10-15): More responsive, more signals • Higher values (25-50): Smoother, fewer signals • Recommended: 20 for most styles ATR Length (Default: 14) • Period for measuring volatility • Standard setting works well for most markets • Recommended: Keep at 14 RSI Length (Default: 14) • Period for momentum measurement • Standard setting works well for most markets • Recommended: Keep at 14 Show Trend Labels on Chart • Toggle ON to display "BULL" / "BEAR" text at reversals • Keep OFF for cleaner chart (default) • Useful when backtesting to see historical signals Show Reversal Signals • Toggle triangle markers at zero-line crosses • Keep ON to catch trend changes • Turn OFF if you only care about current strength ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎓 How The Calculation Works The indicator measures 4 components, each worth 25 points (total = 100): 1. Trend Direction (25 points) • Compares price to moving average • Checks if MA is rising or falling • Perfect score: Price above rising MA • Minimum score: Price below falling MA 2. Momentum (25 points) • Uses RSI to measure momentum strength • RSI > 70 = Maximum bullish points • RSI < 30 = Maximum bearish points • RSI near 50 = Neutral points 3. Volatility Alignment (25 points) • Checks if price moves align with volatility • Strong moves in trending direction = High score • Weak moves or counter-trend = Low score • Uses ATR to measure volatility 4. Moving Average Alignment (25 points) • Checks EMA 8, 21, and 55 positioning • Perfect bullish: 8 > 21 > 55 above price • Perfect bearish: 8 < 21 < 55 below price • Misaligned = Reduced score Final Score = Sum of all 4 components (-100 to +100) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📱 Info Panel Guide Current • Shows exact strength number for current timeframe • Color-coded background (green = bullish, red = bearish) • Larger number for quick visibility Status • Text description of current trend state • Examples: "STRONG BULL", "WEAK BEAR", "NEUTRAL" • Quick interpretation without looking at number Timeframe Readings • Shows strength for each selected timeframe • Color-coded for quick reading • Compare to spot divergences MTF Alignment • ✓ ALIGNED = All timeframes show same direction (high confidence) • ✗ Mixed = Timeframes disagree (proceed with caution) • Most reliable trades happen when aligned ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📱 Alert Setup This indicator includes 4 alert types: 1. Bullish Reversal • Triggers when strength crosses from negative to positive • Potential trend change from bearish to bullish • Early warning of new uptrend 2. Bearish Reversal • Triggers when strength crosses from positive to negative • Potential trend change from bullish to bearish • Early warning of new downtrend 3. Very Strong Bull • Triggers when strength reaches +75 or higher • Extreme bullish conditions • Aggressive long opportunity 4. Very Strong Bear • Triggers when strength reaches -75 or lower • Extreme bearish conditions • Aggressive short opportunity To Set Up Alerts: 1. Click "Alert" button (clock icon) 2. Select "Trend Strength Meter" 3. Choose your alert type 4. Configure notifications 5. Click "Create" ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💎 Pro Tips & Best Practices ✅ DO: • Trust the extremes - Readings above +75 or below -75 are highly reliable • Wait for alignment - Best trades happen when MTF shows "ALIGNED" • Use with price action - Combine with support/resistance for entries • Respect the neutral zone - Avoid trading when strength is -10 to +10 • Scale position size - Bigger positions in stronger trends • Watch for divergence - Price new high but strength declining = Warning • Follow the trend - Don't fight strong readings (±50 or more) ⚠️ DON'T: • Don't trade neutral readings - Wait for clear strength above ±25 • Don't fade extremes - Very strong trends (+75/-75) can stay extreme • Don't ignore MTF - Mixed timeframes = Lower probability • Don't overtrade - Wait for quality setups with good strength • Don't use alone - Combine with support/resistance and risk management • Don't expect perfection - Even strong trends can reverse suddenly 🎯 Best Timeframes: • Scalping: 1min, 5min (fast readings, quick changes) • Day Trading: 5min, 15min, 1H (balanced view) • Swing Trading: 1H, 4H, Daily (stable trends) • Position Trading: 4H, Daily, Weekly (major trends) 🔥 Best Markets: • Trending markets (crypto, indices, commodities) • High liquidity instruments (BTC, ES, NQ, EUR/USD) • Avoid on low-volume stocks or exotic pairs ⏰ Works Best When: • Market has clear direction • Good volatility (not too choppy, not too quiet) • Multiple timeframes aligned • Away from major news events ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🚀 What Makes This Different? Unlike subjective trend analysis, the Trend Strength Meter: • Objective Measurement - No guessing, exact numerical score • Multi-Component - Combines 4 factors, not just one indicator • Multi-Timeframe - See alignment across timeframes instantly • Clean Visual - Professional display, easy to interpret • Actionable - Clear signals for entries, exits, and position sizing • Universal - Works on all timeframes and instruments • Proven Components - Based on trend, momentum, volatility, MA alignment Perfect For: • Trend followers who want confirmation • Swing traders seeking high-probability setups • Risk managers wanting to size positions properly • Anyone tired of subjective "is this trend strong?" questions ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📈 Common Patterns To Watch Pattern 1: The Steady Climb • Strength gradually rises from +25 to +50 to +75 • Indicates building momentum • Trade: Hold longs, add on pullbacks Pattern 2: The Quick Spike • Strength jumps from 0 to +75 in few bars • Indicates explosive momentum • Trade: Enter quickly, but expect pullback Pattern 3: The Exhaustion • Strength at +80, price new high, strength drops to +70 • Bearish divergence forming • Trade: Take profits, prepare for reversal Pattern 4: The Whipsaw • Strength oscillates between +10 and -10 • Choppy, range-bound market • Trade: Stay flat, wait for breakout Pattern 5: The False Breakout • Strength briefly crosses +50 then drops back • Weak momentum, trend not confirmed • Trade: Wait for sustained strength above +50 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📈 Upgrade Your Trading System This free indicator quantifies trend strength objectively. Want more? 🔥 Check out my premium scripts for: • Automated entry and exit signals with trend confirmation • Advanced multi-timeframe strategy systems • Dynamic position sizing based on trend strength • Backtested performance with statistics • Complete trading solutions • And much more... 👉 Visit my profile for professional-grade trading tools! ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📝 Important Notes • This indicator measures trend strength, not direction alone • Strong readings don't guarantee continuation (manage risk) • Always use with proper stop losses • Combine with support/resistance analysis • Test on demo before live trading • Past performance doesn't guarantee future results • Adjust settings to match your trading style Disclaimer: For educational purposes only. Trading involves substantial risk. Always do your own research and never risk more than you can afford to lose. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🙏 Support This Work If this indicator helps your trading: • ⭐ Give it a thumbs up • 💬 Share your best strength-based trades in comments • 🔔 Follow for more free professional tools • 🚀 Share with traders who need objective trend analysis Questions about trend strength? Drop a comment and I'll help! ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Developed with ❤️ for traders who want objective, quantified analysis ━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Version History • v1.0 - Initial release with 4-component strength calculation and MTF analysis
مؤشر Pine Script®
من ‎Exponential-X‎
Get_rich_aggressively_v5# 🚀 GET RICH AGGRESSIVELY v5 - TIER SYSTEM ### Precision Futures Scalping | NQ • ES • YM • GC • BTC ### *Leave Every Trade With Money* --- ## 📋 QUICK CHEATSHEET ``` ┌─────────────────────────────────────────────────────────────────────────────┐ │ GRA v5 SIGNAL REQUIREMENTS │ ├─────────────────────────────────────────────────────────────────────────────┤ │ ✓ TIER MET Points ≥ 10 (B), ≥ 50 (A), ≥ 100 (S) │ │ ✓ VOLUME ≥ 1.3x average │ │ ✓ DELTA ≥ 55% dominance (buyers OR sellers) │ │ ✓ DIRECTION Candle color = Delta direction │ │ ✓ SESSION In London (3-5AM) or NY (9:30-11:30AM) if filter ON │ ├─────────────────────────────────────────────────────────────────────────────┤ │ TIER ACTIONS │ ├─────────────────────────────────────────────────────────────────────────────┤ │ 🥇 S-TIER (100+ pts) │ HOLD LONGER │ Big institutional move │ │ 🥈 A-TIER (50-99 pts) │ HOLD A BIT │ Medium move, trail to BE │ │ 🥉 B-TIER (10-49 pts) │ CLOSE QUICK │ Scalp 5-10 pts, exit fast │ │ ❌ NO TIER (< 10 pts) │ NO TRADE │ Not enough conviction │ ├─────────────────────────────────────────────────────────────────────────────┤ │ SESSION PRIORITY │ ├─────────────────────────────────────────────────────────────────────────────┤ │ 🔵 LONDON OPEN 03:00-05:00 ET │ IB forms 03:00-04:00 │ │ 🟢 NY OPEN 09:30-11:30 ET │ IB forms 09:30-10:30 │ │ 📊 IB BREAKOUT Close beyond IB + Impulse + 1.3x Vol = HIGH CONVICTION│ ├─────────────────────────────────────────────────────────────────────────────┤ │ VOLUME PROFILE ZONES │ ├─────────────────────────────────────────────────────────────────────────────┤ │ 🔵 HVN (Blue BG) High volume = Support/Resistance, expect consolidation │ │ 🟡 LVN (Yellow BG) Low volume = Breakout acceleration, fast moves │ │ 🟣 POC Point of Control = Institutional fair value │ │ 🟣 VAH/VAL Value Area edges = S/R zones │ ├─────────────────────────────────────────────────────────────────────────────┤ │ MARKET STATE DECODER │ ├─────────────────────────────────────────────────────────────────────────────┤ │ TREND UP │ Price > EMA20 + CVD rising │ Trade WITH the trend │ │ TREND DN │ Price < EMA20 + CVD falling │ Trade WITH the trend │ │ RETRACE │ Price/CVD diverging │ Pullback, prepare for entry │ │ RANGE │ No clear direction │ Reduce size or skip │ ├─────────────────────────────────────────────────────────────────────────────┤ │ 💎 HIGH CONVICTION UPGRADE │ ├─────────────────────────────────────────────────────────────────────────────┤ │ Purple diamond (◆) appears when: │ │ • Strong delta (≥65%) + Strong volume (≥2x) + Market in imbalance │ │ → Consider upgrading tier (B→A, A→S) for position sizing │ └─────────────────────────────────────────────────────────────────────────────┘ ``` --- ## 🎯 THE TIER SYSTEM The tier system classifies candles by **point movement** to determine trade management: | Tier | Points | Action | Expected R:R | |:----:|:------:|:------:|:------------:| | 🥇 **S-TIER** | 100+ | HOLD LONGER | 2:1+ | | 🥈 **A-TIER** | 50-99 | HOLD A BIT | 1.5:1 | | 🥉 **B-TIER** | 10-49 | CLOSE QUICK | 1:1 | | ❌ **NO TIER** | < 10 | NO TRADE | — | --- ## ✅ SIGNAL REQUIREMENTS **ALL conditions must be TRUE for a signal:** ``` SIGNAL = TIER + VOLUME + DELTA + DIRECTION + SESSION ☐ Points ≥ 10 (minimum B-tier) ☐ Volume ≥ 1.3x average ☐ Delta dominance ≥ 55% ☐ Candle direction = Delta direction ☐ In session (if filter ON) ANY FALSE = NO SIGNAL = NO TRADE ``` --- ## 📊 VOLUME DOMINANCE ANALYSIS This is the **core edge** of GRA v5. We use intrabar analysis to determine who is in control: ``` VOLUME ANALYSIS BREAKDOWN Total Volume = Buy Volume + Sell Volume Buy Volume: Who pushed price UP within the bar Sell Volume: Who pushed price DOWN within the bar Delta = Buy Volume - Sell Volume Buy Dominance = Buy Volume / Total Volume Sell Dominance = Sell Volume / Total Volume ≥ 55% = ONE SIDE IN CONTROL ≥ 65% = STRONG DOMINANCE (high conviction) ``` **Direction Confirmation Matrix:** | Candle | Delta | Signal | |:-------|:------|:-------| | 🟢 Bullish | 55%+ Buyers | ✅ LONG | | 🟢 Bullish | 55%+ Sellers | ❌ Trap | | 🔴 Bearish | 55%+ Sellers | ✅ SHORT | | 🔴 Bearish | 55%+ Buyers | ❌ Trap | --- ## 🕐 SESSION CONTEXT ### Initial Balance (IB) Framework The **first hour** of each session establishes the IB range. Institutions use this for the day's framework. ``` SESSION WINDOWS (Eastern Time): LONDON: ├── IB Period: 03:00 - 04:00 ← Range established ├── Trade Window: 03:00 - 05:00 ← Best signals └── Extension Targets: 1.5x, 2.0x NY: ├── IB Period: 09:30 - 10:30 ← Range established ├── Trade Window: 09:30 - 11:30 ← Best signals └── Extension Targets: 1.5x, 2.0x ``` ### IB Breakout Signals ``` L▲ / L▼ = London IB Breakout (Blue) N▲ / N▼ = NY IB Breakout (Orange) Confirmation Required: ☐ Close beyond IB level (not just wick) ☐ Impulse candle (body > 60% of range) ☐ Volume > 1.3x average ``` **IB Statistics:** - 97% of days break either IB high or low - 1.5x extension = first profit target - 2.0x extension = full range target - ~66% of London sessions sweep Asian high/low first --- ## 📈 VIRTUAL VOLUME PROFILE ZONES GRA v5 calculates volume profile zones **without drawing the profile**, giving you the key levels: ### Zone Types | Zone | Background | Meaning | Action | |:-----|:-----------|:--------|:-------| | **HVN** | 🔵 Blue | High Volume Node | S/R zone, expect consolidation | | **LVN** | 🟡 Yellow | Low Volume Node | Breakout zone, fast acceleration | | **POC** | 🟣 Purple dots | Point of Control | Institutional fair value | | **VAH/VAL** | 🟣 Purple lines | Value Area edges | S/R boundaries | ### How to Use ``` ENTERING A TRADE: At HVN: ├── Expect price to consolidate ├── Look for rejection/absorption └── Better for reversals At LVN: ├── Expect fast price movement ├── Don't fight the direction └── Better for breakouts Near POC: ├── Institutional fair value ├── Strong magnet effect └── Watch for volume at POC ``` --- ## 🔄 MARKET STATE DETECTION GRA v5 classifies the market into four states using **CVD + Price Action**: ``` CVD Direction ↑ Rising ↓ Falling ┌─────────────┬─────────────┐ Price > EMA20 │ TREND UP │ RETRACE │ │ (Go Long) │ (Pullback) │ ├─────────────┼─────────────┤ Price < EMA20 │ RETRACE │ TREND DN │ │ (Pullback) │ (Go Short) │ └─────────────┴─────────────┘ ``` | State | Meaning | Action | |:------|:--------|:-------| | **TREND UP** | Buyers in control | Trade long, follow signals | | **TREND DN** | Sellers in control | Trade short, follow signals | | **RETRACE** | Pullback against trend | Prepare for continuation entry | | **RANGE** | No clear direction | Reduce size or wait | --- ## 💎 HIGH CONVICTION UPGRADES When extra conditions align, GRA v5 marks the signal with a **purple diamond**: ``` HIGH CONVICTION = Base Signal + Strong Delta (65%+) + Strong Volume (2x+) + Imbalance State ``` **Action:** Consider upgrading tier for position sizing: - B-Tier → A-Tier management - A-Tier → S-Tier management --- ## 📋 TRADING BY TIER ### 🥇 S-TIER (100+ points) | | | |:--|:--| | **Entry** | Candle close | | **Target** | IB extension / Next S/R | | **Management** | HOLD LONGER | **Rules:** - Watch next candle - continues? HOLD - Same tier same direction? ADD - Opposite tier signal? EXIT on close - Never close early unless reversal signal ### 🥈 A-TIER (50-99 points) | | | |:--|:--| | **Entry** | Candle close | | **Target** | 1.5x initial risk minimum | | **Management** | HOLD A BIT | **Rules:** - Target 1.5:1 R:R minimum - Trail to breakeven after 1:1 - If stalls, take profit - Upgrade to S-tier management if high conviction ### 🥉 B-TIER (10-49 points) | | | |:--|:--| | **Entry** | Candle close | | **Target** | 5-10 points MAX | | **Management** | CLOSE QUICK | **Rules:** - Exit in 1-3 candles - DO NOT hold for more - Any doubt = EXIT - Quick scalp mentality --- ## ⚙️ SETTINGS BY INSTRUMENT | Setting | NQ/ES | YM | GC | BTC | |:--------|:-----:|:--:|:--:|:---:| | **Timeframe** | 1-5 min | 1-5 min | 5-15 min | 1-15 min | | **S-Tier** | 100 pts | 100 pts | 15 pts | 500 pts | | **A-Tier** | 50 pts | 50 pts | 8 pts | 250 pts | | **B-Tier** | 10 pts | 15 pts | 3 pts | 50 pts | | **Min Volume** | 1.3x | 1.3x | 1.5x | 1.3x | | **Delta %** | 55% | 55% | 58% | 55% | | **Best Time** | 9:30-11:30 ET | 9:30-11:30 ET | 3-5AM & 8:30-10:30 ET | 24/7 | --- ## 📊 TABLE LEGEND The info panel displays real-time market data: | Row | Shows | Colors | |:----|:------|:-------| | **Pts** | Candle points | Gold/Green/Yellow by tier | | **Tier** | S/A/B/X | Gold/Green/Yellow/White | | **Vol** | Volume ratio | Yellow (2x+) / Green (1.3x+) / Red | | **Delta** | Buy/Sell % | Green (buy) / Red (sell) / White | | **CVD** | Direction | Green ▲ / Red ▼ | | **State** | Market state | Green/Red/Orange/Gray | | **Sess** | Session | Yellow if active | | **Zone** | VP zone | Blue/Yellow/Purple | | **Sig** | Signal | Green/Red if active | --- ## 🔔 ALERTS | Alert | When | Action | |:------|:-----|:-------| | **S-TIER LONG/SHORT** | S-tier signal | Hold longer | | **A-TIER LONG/SHORT** | A-tier signal | Hold a bit | | **B-TIER LONG/SHORT** | B-tier signal | Close quick | | **LON IB BREAK UP/DN** | London IB breakout | Major session move | | **NY IB BREAK UP/DN** | NY IB breakout | Major session move | | **HIGH CONVICTION** | Upgraded signal | Consider larger size | | **LONDON/NY OPEN** | Session start | Get ready | --- ## 💰 THE GOLDEN RULE > ### **LEAVE EVERY TRADE WITH MONEY** > > | Situation | Rule | > |:----------|:-----| > | B-Tier | Small win > Small loss | > | A-Tier | Trail to BE, lock profit | > | S-Tier | Let it run to target | > | No Signal | NO TRADE | > | Wrong Side | EXIT immediately | > > **Capital preserved = Trade tomorrow** --- ## ⚠️ DISCLAIMER > Risk management is **YOUR** responsibility. > Never risk more than 1-2% per trade. > Paper trade until you understand the signals. > Past performance ≠ future results. --- ### Get Rich. Stay Rich. Trade Aggressively. 🚀 **Get Rich Aggressively v5** *Precision Futures Scalping*
مؤشر Pine Script®
من ‎alexandrodisla‎
Bifurcation Zone - CAEBifurcation Zone — Cognitive Adversarial Engine (BZ-CAE) Bifurcation Zone — CAE (BZ-CAE) is a next-generation divergence detection system enhanced by a Cognitive Adversarial Engine that evaluates both sides of every potential trade before presenting signals. Unlike traditional divergence indicators that show every price-oscillator disagreement regardless of context, BZ-CAE applies comprehensive market-state intelligence to identify only the divergences that occur in favorable conditions with genuine probability edges. The system identifies structural bifurcation points — critical junctures where price and momentum disagree, signaling potential reversals or continuations — then validates these opportunities through five interconnected intelligence layers: Trend Conviction Scoring , Directional Momentum Alignment , Multi-Factor Exhaustion Modeling , Adversarial Validation , and Confidence Scoring . The result is a selective, context-aware signal system that filters noise and highlights high-probability setups. This is not a "buy the arrow" indicator. It's a decision support framework that teaches you how to read market state, evaluate divergence quality, and make informed trading decisions based on quantified intelligence rather than hope. What Sets BZ-CAE Apart: Technical Architecture The Problem With Traditional Divergence Indicators Most divergence indicators operate on a simple rule: if price makes a higher high and RSI makes a lower high, show a bearish signal. If price makes a lower low and RSI makes a higher low, show a bullish signal. This creates several critical problems: Context Blindness : They show counter-trend signals in powerful trends that rarely reverse, leading to repeated losses as you fade momentum. Signal Spam : Every minor price-oscillator disagreement generates an alert, overwhelming you with low-quality setups and creating analysis paralysis. No Quality Ranking : All signals are treated identically. A marginal divergence in choppy conditions receives the same visual treatment as a high-conviction setup at a major exhaustion point. Single-Sided Evaluation : They ask "Is this a good long?" without checking if the short case is overwhelmingly stronger, leading you into obvious bad trades. Static Configuration : You manually choose RSI 14 or Stochastic 14 and hope it works, with no systematic way to validate if that's optimal for your instrument. BZ-CAE's Solution: Cognitive Adversarial Intelligence BZ-CAE solves these problems through an integrated five-layer intelligence architecture: 1. Trend Conviction Score (TCS) — 0 to 1 Scale Most indicators check if ADX is above 25 to determine "trending" conditions. This binary approach misses nuance. TCS is a weighted composite metric: Formula : 0.35 × normalize(ADX, 10, 35) + 0.35 × structural_strength + 0.30 × htf_alignment Structural Strength : 10-bar SMA of consecutive directional bars. Captures persistence — are bulls or bears consistently winning? HTF Alignment : Multi-timeframe EMA stacking (20/50/100/200). When all EMAs align in the same direction, you're in institutional trend territory. Purpose : Quantifies how "locked in" the trend is. When TCS exceeds your threshold (default 0.80), the system knows to avoid counter-trend trades unless other factors override. Interpretation : TCS > 0.85: Very strong trend — counter-trading is extremely high risk TCS 0.70-0.85: Strong trend — favor continuation, require exhaustion for reversals TCS 0.50-0.70: Moderate trend — context matters, both directions viable TCS < 0.50: Weak/choppy — reversals more viable, range-bound conditions 2. Directional Momentum Alignment (DMA) — ATR-Normalized Formula : (EMA21 - EMA55) / ATR14 This isn't just "price above EMA" — it's a regime-aware momentum gauge. The same $100 price movement reads completely differently in high-volatility crypto versus low-volatility forex. By normalizing with ATR, DMA adapts its interpretation to current market conditions. Purpose : Quantifies the directional "force" behind current price action. Positive = bullish push, negative = bearish push. Magnitude = strength. Interpretation : DMA > 0.7: Strong bullish momentum — bearish divergences risky DMA 0.3 to 0.7: Moderate bullish bias DMA -0.3 to 0.3: Balanced/choppy conditions DMA -0.7 to -0.3: Moderate bearish bias DMA < -0.7: Strong bearish momentum — bullish divergences risky 3. Multi-Factor Exhaustion Modeling — 0 to 1 Probability Single-metric exhaustion detection (like "RSI > 80") misses complex market states. BZ-CAE aggregates five independent exhaustion signals: Volume Spikes : Current volume versus 50-bar average 2.5x average: 0.25 weight 2.0x average: 0.15 weight 1.5x average: 0.10 weight Divergence Present : The fact that a divergence exists contributes 0.30 weight — structural momentum disagreement is itself an exhaustion signal. RSI Extremes : Captures oscillator climax zones RSI > 80 or < 20: 0.25 weight RSI > 75 or < 25: 0.15 weight Pin Bar Detection : Identifies rejection candles (2:1 wick-to-body ratio, indicating failed breakout attempts): 0.15 weight Extended Runs : Consecutive bars above/below EMA20 without pullback 30+ bars: 0.15 weight (market hasn't paused to consolidate) Total exhaustion score is the sum of all applicable weights, capped at 1.0. Purpose : Detects when strong trends become vulnerable to reversal. High exhaustion can override trend filters, allowing counter-trend trades at genuine turning points that basic indicators would miss. Interpretation : Exhaustion > 0.75: High probability of climax — yellow background shading alerts you visually Exhaustion 0.50-0.75: Moderate overextension — watch for confirmation Exhaustion < 0.50: Fresh move — trend can continue, counter-trend trades higher risk 4. Adversarial Validation — Game Theory Applied to Trading This is BZ-CAE's signature innovation. Before approving any signal, the engine quantifies BOTH sides of the trade simultaneously: For Bullish Divergences , it calculates: Bull Case Score (0-1+) : Distance below EMA20 (pullback quality): up to 0.25 Bullish EMA alignment (close > EMA20 > EMA50): 0.25 Oversold RSI (< 40): 0.25 Volume confirmation (> 1.2x average): 0.25 Bear Case Score (0-1+) : Price below EMA50 (structural weakness): 0.30 Very oversold RSI (< 30, indicating knife-catching): 0.20 Differential = Bull Case - Bear Case If differential < -0.10 (default threshold), the bear case is dominating — signal is BLOCKED or ANNOTATED. For Bearish Divergences , the logic inverts (Bear Case vs Bull Case). Purpose : Prevents trades where you're fighting obvious strength in the opposite direction. This is institutional-grade risk management — don't just evaluate your trade, evaluate the counter-trade simultaneously. Why This Matters : You might see a bullish divergence at a local low, but if price is deeply below major support EMAs with strong bearish momentum, you're catching a falling knife. The adversarial check catches this and blocks the signal. 5. Confidence Scoring — 0 to 1 Quality Assessment Every signal that passes initial filters receives a comprehensive quality score: Formula : 0.30 × normalize(TCS) // Trend context + 0.25 × normalize(|DMA|) // Momentum magnitude + 0.20 × pullback_quality // Entry distance from EMA20 + 0.15 × state_quality // ADX + alignment + structure + 0.10 × divergence_strength // Slope separation magnitude + adversarial_bonus (0-0.30) // Your side's advantage Purpose : Ranks setup quality for filtering and position sizing decisions. You can set a minimum confidence threshold (default 0.35) to ensure only quality setups reach your chart. Interpretation : Confidence > 0.70: Premium setup — consider increased position size Confidence 0.50-0.70: Good quality — standard size Confidence 0.35-0.50: Acceptable — reduced size or skip if conservative Confidence < 0.35: Marginal — blocked in Filtering mode, annotated in Advisory mode CAE Operating Modes: Learning vs Enforcement Off : Disables all CAE logic. Raw divergence pipeline only. Use for baseline comparison. Advisory : Shows ALL signals regardless of CAE evaluation, but annotates signals that WOULD be blocked with specific warnings (e.g., "Bull: strong downtrend (TCS=0.87)" or "Adversarial bearish"). This is your learning mode — see CAE's decision logic in action without missing educational opportunities. Filtering : Actively blocks low-quality signals. Only setups that pass all enabled gates (Trend Filter, Adversarial Validation, Confidence Gating) reach your chart. This is your live trading mode — trust the system to enforce discipline. CAE Filter Gates: Three-Layer Protection When CAE is enabled, signals must pass through three independent gates (each can be toggled on/off): Gate 1: Strong Trend Filter If TCS ≥ tcs_threshold (default 0.80) And signal is counter-trend (bullish in downtrend or bearish in uptrend) And exhaustion < exhaustion_required (default 0.50) Then: BLOCK signal Logic: Don't fade strong trends unless the move is clearly overextended Gate 2: Adversarial Validation Calculate both bull case and bear case scores If opposing case dominates by more than adv_threshold (default 0.10) Then: BLOCK signal Logic: Avoid trades where you're fighting obvious strength in the opposite direction Gate 3: Confidence Gating Calculate composite confidence score (0-1) If confidence < min_confidence (default 0.35) Then: In Filtering mode, BLOCK signal; in Advisory mode, ANNOTATE with warning Logic: Only take setups with minimum quality threshold All three gates work together. A signal must pass ALL enabled gates to fire. Visual Intelligence System Bifurcation Zones (Supply/Demand Blocks) When a divergence signal fires, BZ-CAE draws a semi-transparent box extending 15 bars forward from the signal pivot: Demand Zones (Bullish) : Theme-colored box (cyan in Cyberpunk, blue in Professional, etc.) labeled "Demand" — marks where smart money likely placed buy orders as price diverged at the low. Supply Zones (Bearish) : Theme-colored box (magenta in Cyberpunk, orange in Professional) labeled "Supply" — marks where smart money likely placed sell orders as price diverged at the high. Theory : Divergences represent institutional disagreement with the crowd. The crowd pushed price to an extreme (new high or low), but momentum (oscillator) is waning, indicating smart money is taking the opposite side. These zones mark order placement areas that become future support/resistance. Use Cases : Exit targets: Take profit when price returns to opposite-side zone Re-entry levels: If price returns to your entry zone, consider adding Stop placement: Place stops just beyond your zone (below demand, above supply) Auto-Cleanup : System keeps the last 20 zones to prevent chart clutter. Adversarial Bar Coloring — Real-Time Market Debate Heatmap Each bar is colored based on the Bull Case vs Bear Case differential: Strong Bull Advantage (diff > 0.3): Full theme bull color (e.g., cyan) Moderate Bull Advantage (diff > 0.1): 50% transparency bull Neutral (diff -0.1 to 0.1): Gray/neutral theme Moderate Bear Advantage (diff < -0.1): 50% transparency bear Strong Bear Advantage (diff < -0.3): Full theme bear color (e.g., magenta) This creates a real-time visual heatmap showing which side is "winning" the market debate. When bars flip from cyan to magenta (or vice versa), you're witnessing a shift in adversarial advantage — a leading indicator of potential momentum changes. Exhaustion Shading When exhaustion score exceeds 0.75, the chart background displays a semi-transparent yellow highlight. This immediate visual warning alerts you that the current move is at high risk of reversal, even if trend indicators remain strong. Visual Themes — Six Aesthetic Options Cyberpunk : Cyan/Magenta/Yellow — High contrast, neon aesthetic, excellent for dark-themed trading environments Professional : Blue/Orange/Green — Corporate color palette, suitable for presentations and professional documentation Ocean : Teal/Red/Cyan — Aquatic palette, calming for extended monitoring sessions Fire : Orange/Red/Coral — Warm aggressive colors, high energy Matrix : Green/Red/Lime — Code aesthetic, homage to classic hacker visuals Monochrome : White/Gray — Minimal distraction, maximum focus on price action All visual elements (signal markers, zones, bar colors, dashboard) adapt to your selected theme. Divergence Engine — Core Detection System What Are Divergences? Divergences occur when price action and momentum indicators disagree, creating structural tension that often resolves in a change of direction: Regular Divergence (Reversal Signal) : Bearish Regular : Price makes higher high, oscillator makes lower high → Potential trend reversal down Bullish Regular : Price makes lower low, oscillator makes higher low → Potential trend reversal up Hidden Divergence (Continuation Signal) : Bearish Hidden : Price makes lower high, oscillator makes higher high → Downtrend continuation Bullish Hidden : Price makes higher low, oscillator makes lower low → Uptrend continuation Both types can be enabled/disabled independently in settings. Pivot Detection Methods BZ-CAE uses symmetric pivot detection with separate lookback and lookforward periods (default 5/5): Pivot High : Bar where high > all highs within lookback range AND high > all highs within lookforward range Pivot Low : Bar where low < all lows within lookback range AND low < all lows within lookforward range This ensures structural validity — the pivot must be a clear local extreme, not just a minor wiggle. Divergence Validation Requirements For a divergence to be confirmed, it must satisfy: Slope Disagreement : Price slope and oscillator slope must move in opposite directions (for regular divs) or same direction with inverted highs/lows (for hidden divs) Minimum Slope Change : |osc_slope| > min_slope_change / 100 (default 1.0) — filters weak, marginal divergences Maximum Lookback Range : Pivots must be within max_lookback bars (default 60) — prevents ancient, irrelevant divergences ATR-Normalized Strength : Divergence strength = min(|price_slope| × |osc_slope| × 10, 1.0) — quantifies the magnitude of disagreement in volatility context Regular divergences receive 1.0× weight; hidden divergences receive 0.8× weight (slightly less reliable historically). Oscillator Options — Five Professional Indicators RSI (Relative Strength Index) : Classic overbought/oversold momentum indicator. Best for: General purpose divergence detection across all instruments. Stochastic : Range-bound %K momentum comparing close to high-low range. Best for: Mean reversion strategies and range-bound markets. CCI (Commodity Channel Index) : Measures deviation from statistical mean, auto-normalized to 0-100 scale. Best for: Cyclical instruments and commodities. MFI (Money Flow Index) : Volume-weighted RSI incorporating money flow. Best for: Volume-driven markets like stocks and crypto. Williams %R : Inverse stochastic looking back over period, auto-adjusted to 0-100. Best for: Reversal detection at extremes. Each oscillator has adjustable length (2-200, default 14) and smoothing (1-20, default 1). You also set overbought (50-100, default 70) and oversold (0-50, default 30) thresholds. Signal Timing Modes — Understanding Repainting BZ-CAE offers two timing policies with complete transparency about repainting behavior: Realtime (1-bar, peak-anchored) How It Works : Detects peaks 1 bar ago using pattern: high > high AND high > high Signal prints on the NEXT bar after peak detection (bar_index) Visual marker anchors to the actual PEAK bar (bar_index - 1, offset -1) Signal locks in when bar CONFIRMS (closes) Repainting Behavior : On the FORMING bar (before close), the peak condition may change as new prices arrive Once bar CLOSES (barstate.isconfirmed), signal is locked permanently This is preview/early warning behavior by design Best For : Active monitoring and immediate alerts Learning the system (seeing signals develop in real-time) Responsive entry if you're watching the chart live Confirmed (lookforward) How It Works : Uses Pine Script's built-in ta.pivothigh() and ta.pivotlow() functions Requires full pivot validation period (lookback + lookforward bars) Signal prints pivot_lookforward bars after the actual peak (default 5-bar delay) Visual marker anchors to the actual peak bar (offset -pivot_lookforward) No Repainting Behavior Best For : Backtesting and historical analysis Conservative entries requiring full confirmation Automated trading systems Swing trading with larger timeframes Tradeoff : Delayed entry by pivot_lookforward bars (typically 5 bars) On a 5-minute chart, this is a 25-minute delay On a 4-hour chart, this is a 20-hour delay Recommendation : Use Confirmed for backtesting to verify system performance honestly. Use Realtime for live monitoring only if you're actively watching the chart and understand pre-confirmation repainting behavior. Signal Spacing System — Anti-Spam Architecture Even after CAE filtering, raw divergences can cluster. The spacing system enforces separation: Three Independent Filters 1. Min Bars Between ANY Signals (default 12): Prevents rapid-fire clustering across both directions If last signal (bull or bear) was within N bars, block new signal Ensures breathing room between all setups 2. Min Bars Between SAME-SIDE Signals (default 24, optional enforcement): Prevents bull-bull or bear-bear spam Separate tracking for bullish and bearish signal timelines Toggle enforcement on/off 3. Min ATR Distance From Last Signal (default 0, optional): Requires price to move N × ATR from last signal location Ensures meaningful price movement between setups 0 = disabled, 0.5-2.0 = typical range for enabled All three filters work independently. A signal must pass ALL enabled filters to proceed. Practical Guidance : Scalping (1-5m) : Any 6-10, Same-side 12-20, ATR 0-0.5 Day Trading (15m-1H) : Any 12, Same-side 24, ATR 0-1.0 Swing Trading (4H-D) : Any 20-30, Same-side 40-60, ATR 1.0-2.0 Dashboard — Real-Time Control Center The dashboard (toggleable, four corner positions, three sizes) provides comprehensive system intelligence: Oscillator Section Current oscillator type and value State: OVERBOUGHT / OVERSOLD / NEUTRAL (color-coded) Length parameter Cognitive Engine Section TCS (Trend Conviction Score) : Current value with emoji state indicator 🔥 = Strong trend (>0.75) 📊 = Moderate trend (0.50-0.75) 〰️ = Weak/choppy (<0.50) Color: Red if above threshold (trend filter active), yellow if moderate, green if weak DMA (Directional Momentum Alignment) : Current value with emoji direction indicator 🐂 = Bullish momentum (>0.5) ⚖️ = Balanced (-0.5 to 0.5) 🐻 = Bearish momentum (<-0.5) Color: Green if bullish, red if bearish Exhaustion : Current value with emoji warning indicator ⚠️ = High exhaustion (>0.75) 🟡 = Moderate (0.50-0.75) ✓ = Low (<0.50) Color: Red if high, yellow if moderate, green if low Pullback : Quality of current distance from EMA20 Values >0.6 are ideal entry zones (not too close, not too far) Bull Case / Bear Case (if Adversarial enabled): Current scores for both sides of the market debate Differential with emoji indicator: 📈 = Bull advantage (>0.2) ➡️ = Balanced (-0.2 to 0.2) 📉 = Bear advantage (<-0.2) Last Signal Metrics Section (New Feature) When a signal fires, this section captures and displays: Signal type (BULL or BEAR) Bars elapsed since signal Confidence % at time of signal TCS value at signal time DMA value at signal time Purpose : Provides a historical reference for learning. You can see what the market state looked like when the last signal fired, helping you correlate outcomes with conditions. Statistics Section Total Signals : Lifetime count across session Blocked Signals : Count and percentage (filter effectiveness metric) Bull Signals : Total bullish divergences Bear Signals : Total bearish divergences Purpose : System health monitoring. If blocked % is very high (>60%), filters may be too strict. If very low (<10%), filters may be too loose. Advisory Annotations When CAE Mode = Advisory, this section displays warnings for signals that would be blocked in Filtering mode: Examples: "Bull spacing: wait 8 bars" "Bear: strong uptrend (TCS=0.87)" "Adversarial bearish" "Low confidence 32%" Multiple warnings can stack, separated by " | ". This teaches you CAE's decision logic transparently. How to Use BZ-CAE — Complete Workflow Phase 1: Initial Setup (First Session) Apply BZ-CAE to your chart Select your preferred Visual Theme (Cyberpunk recommended for visibility) Set Signal Timing to "Confirmed (lookforward)" for learning Choose your Oscillator Type (RSI recommended for general use, length 14) Set Overbought/Oversold to 70/30 (standard) Enable both Regular Divergence and Hidden Divergence Set Pivot Lookback/Lookforward to 5/5 (balanced structure) Enable CAE Intelligence Set CAE Mode to "Advisory" (learning mode) Enable all three CAE filters: Strong Trend Filter , Adversarial Validation , Confidence Gating Enable Show Dashboard , position Top Right, size Normal Enable Draw Bifurcation Zones and Adversarial Bar Coloring Phase 2: Learning Period (Weeks 1-2) Goal : Understand how CAE evaluates market state and filters signals. Activities : Watch the dashboard during signals : Note TCS values when counter-trend signals fail — this teaches you the trend strength threshold for your instrument Observe exhaustion patterns at actual turning points — learn when overextension truly matters Study adversarial differential at signal times — see when opposing cases dominate Review blocked signals (orange X-crosses): In Advisory mode, you see everything — signals that would pass AND signals that would be blocked Check the advisory annotations to understand why CAE would block Track outcomes: Were the blocks correct? Did those signals fail? Use Last Signal Metrics : After each signal, check the dashboard capture of confidence, TCS, and DMA Journal these values alongside trade outcomes Identify patterns: Do confidence >0.70 signals work better? Does your instrument respect TCS >0.85? Understand your instrument's "personality" : Trending instruments (indices, major forex) may need TCS threshold 0.85-0.90 Choppy instruments (low-cap stocks, exotic pairs) may work best with TCS 0.70-0.75 High-volatility instruments (crypto) may need wider spacing Low-volatility instruments may need tighter spacing Phase 3: Calibration (Weeks 3-4) Goal : Optimize settings for your specific instrument, timeframe, and style. Calibration Checklist : Min Confidence Threshold : Review confidence distribution in your signal journal Identify the confidence level below which signals consistently fail Set min_confidence slightly above that level Day trading : 0.35-0.45 Swing trading : 0.40-0.55 Scalping : 0.30-0.40 TCS Threshold : Find the TCS level where counter-trend signals consistently get stopped out Set tcs_threshold at or slightly below that level Trending instruments : 0.85-0.90 Mixed instruments : 0.80-0.85 Choppy instruments : 0.75-0.80 Exhaustion Override Level : Identify exhaustion readings that marked genuine reversals Set exhaustion_required just below the average Typical range : 0.45-0.55 Adversarial Threshold : Default 0.10 works for most instruments If you find CAE is too conservative (blocking good trades), raise to 0.15-0.20 If signals are still getting caught in opposing momentum, lower to 0.07-0.09 Spacing Parameters : Count bars between quality signals in your journal Set min bars ANY to ~60% of that average Set min bars SAME-SIDE to ~120% of that average Scalping : Any 6-10, Same 12-20 Day trading : Any 12, Same 24 Swing : Any 20-30, Same 40-60 Oscillator Selection : Try different oscillators for 1-2 weeks each Track win rate and average winner/loser by oscillator type RSI : Best for general use, clear OB/OS Stochastic : Best for range-bound, mean reversion MFI : Best for volume-driven markets CCI : Best for cyclical instruments Williams %R : Best for reversal detection Phase 4: Live Deployment Goal : Disciplined execution with proven, calibrated system. Settings Changes : Switch CAE Mode from Advisory to Filtering System now actively blocks low-quality signals Only setups passing all gates reach your chart Keep Signal Timing on Confirmed for conservative entries OR switch to Realtime if you're actively monitoring and want faster entries (accept pre-confirmation repaint risk) Use your calibrated thresholds from Phase 3 Enable high-confidence alerts: "⭐ High Confidence Bullish/Bearish" (>0.70) Trading Discipline Rules : Respect Blocked Signals : If CAE blocks a trade you wanted to take, TRUST THE SYSTEM Don't manually override — if you consistently disagree, return to Phase 2/3 calibration The block exists because market state failed intelligence checks Confidence-Based Position Sizing : Confidence >0.70: Standard or increased size (e.g., 1.5-2.0% risk) Confidence 0.50-0.70: Standard size (e.g., 1.0% risk) Confidence 0.35-0.50: Reduced size (e.g., 0.5% risk) or skip if conservative TCS-Based Management : High TCS + counter-trend signal: Use tight stops, quick exits (you're fading momentum) Low TCS + reversal signal: Use wider stops, trail aggressively (genuine reversal potential) Exhaustion Awareness : Exhaustion >0.75 (yellow shading): Market is overextended, reversal risk is elevated — consider early exit or tighter trailing stops even on winning trades Exhaustion <0.30: Continuation bias — hold for larger move, wide trailing stops Adversarial Context : Strong differential against you (e.g., bullish signal with bear diff <-0.2): Use very tight stops, consider skipping Strong differential with you (e.g., bullish signal with bull diff >0.2): Trail aggressively, this is your tailwind Practical Settings by Timeframe & Style Scalping (1-5 Minute Charts) Objective : High frequency, tight stops, quick reversals in fast-moving markets. Oscillator : Type: RSI or Stochastic (fast response to quick moves) Length: 9-11 (more responsive than standard 14) Smoothing: 1 (no lag) OB/OS: 65/35 (looser thresholds ensure frequent crossings in fast conditions) Divergence : Pivot Lookback/Lookforward: 3/3 (tight structure, catch small swings) Max Lookback: 40-50 bars (recent structure only) Min Slope Change: 0.8-1.0 (don't be overly strict) CAE : Mode: Advisory first (learn), then Filtering Min Confidence: 0.30-0.35 (lower bar for speed, accept more signals) TCS Threshold: 0.70-0.75 (allow more counter-trend opportunities) Exhaustion Required: 0.45-0.50 (moderate override) Strong Trend Filter: ON (still respect major intraday trends) Adversarial: ON (critical for scalping protection — catches bad entries quickly) Spacing : Min Bars ANY: 6-10 (fast pace, many setups) Min Bars SAME-SIDE: 12-20 (prevent clustering) Min ATR Distance: 0 or 0.5 (loose) Timing : Realtime (speed over precision, but understand repaint risk) Visuals : Signal Size: Tiny (chart clarity in busy conditions) Show Zones: Optional (can clutter on low timeframes) Bar Coloring: ON (helps read momentum shifts quickly) Dashboard: Small size (corner reference, not main focus) Key Consideration : Scalping generates noise. Even with CAE, expect lower win rate (45-55%) but aim for favorable R:R (2:1 or better). Size conservatively. Day Trading (15-Minute to 1-Hour Charts) Objective : Balance quality and frequency. Standard divergence trading approach. Oscillator : Type: RSI or MFI (proven reliability, volume confirmation with MFI) Length: 14 (industry standard, well-studied) Smoothing: 1-2 OB/OS: 70/30 (classic levels) Divergence : Pivot Lookback/Lookforward: 5/5 (balanced structure) Max Lookback: 60 bars Min Slope Change: 1.0 (standard strictness) CAE : Mode: Filtering (enforce discipline from the start after brief Advisory learning) Min Confidence: 0.35-0.45 (quality filter without being too restrictive) TCS Threshold: 0.80-0.85 (respect strong trends) Exhaustion Required: 0.50 (balanced override threshold) Strong Trend Filter: ON Adversarial: ON Confidence Gating: ON (all three filters active) Spacing : Min Bars ANY: 12 (breathing room between all setups) Min Bars SAME-SIDE: 24 (prevent bull/bear clusters) Min ATR Distance: 0-1.0 (optional refinement, typically 0.5-1.0) Timing : Confirmed (1-bar delay for reliability, no repainting) Visuals : Signal Size: Tiny or Small Show Zones: ON (useful reference for exits/re-entries) Bar Coloring: ON (context awareness) Dashboard: Normal size (full visibility) Key Consideration : This is the "sweet spot" timeframe for BZ-CAE. Market structure is clear, CAE has sufficient data, and signal frequency is manageable. Expect 55-65% win rate with proper execution. Swing Trading (4-Hour to Daily Charts) Objective : Quality over quantity. High conviction only. Larger stops and targets. Oscillator : Type: RSI or CCI (robust on higher timeframes, smooth longer waves) Length: 14-21 (capture larger momentum swings) Smoothing: 1-3 OB/OS: 70/30 or 75/25 (strict extremes) Divergence : Pivot Lookback/Lookforward: 5/5 or 7/7 (structural purity, major swings only) Max Lookback: 80-100 bars (broader historical context) Min Slope Change: 1.2-1.5 (require strong, undeniable divergence) CAE : Mode: Filtering (strict enforcement, premium setups only) Min Confidence: 0.40-0.55 (high bar for entry) TCS Threshold: 0.85-0.95 (very strong trend protection — don't fade established HTF trends) Exhaustion Required: 0.50-0.60 (higher bar for override — only extreme exhaustion justifies counter-trend) Strong Trend Filter: ON (critical on HTF) Adversarial: ON (avoid obvious bad trades) Confidence Gating: ON (quality gate essential) Spacing : Min Bars ANY: 20-30 (substantial separation) Min Bars SAME-SIDE: 40-60 (significant breathing room) Min ATR Distance: 1.0-2.0 (require meaningful price movement) Timing : Confirmed (purity over speed, zero repaint for swing accuracy) Visuals : Signal Size: Small or Normal (clear markers on zoomed-out view) Show Zones: ON (important HTF levels) Bar Coloring: ON (long-term trend awareness) Dashboard: Normal or Large (comprehensive analysis) Key Consideration : Swing signals are rare but powerful. Expect 2-5 signals per month per instrument. Win rate should be 60-70%+ due to stringent filtering. Position size can be larger given confidence. Dashboard Interpretation Reference TCS (Trend Conviction Score) States 0.00-0.50: Weak/Choppy Emoji: 〰️ Color: Green/cyan Meaning: No established trend. Range-bound or consolidating. Both reversal and continuation signals viable. Action: Reversals (regular divs) are safer. Use wider profit targets (market has room to move). Consider mean reversion strategies. 0.50-0.75: Moderate Trend Emoji: 📊 Color: Yellow/neutral Meaning: Developing trend but not locked in. Context matters significantly. Action: Check DMA and exhaustion. If DMA confirms trend and exhaustion is low, favor continuation (hidden divs). If exhaustion is high, reversals are viable. 0.75-0.85: Strong Trend Emoji: 🔥 Color: Orange/warning Meaning: Well-established trend with persistence. Counter-trend is high risk. Action: Require exhaustion >0.50 for counter-trend entries. Favor continuation signals. Use tight stops on counter-trend attempts. 0.85-1.00: Very Strong Trend Emoji: 🔥🔥 Color: Red/danger (if counter-trading) Meaning: Locked-in institutional trend. Extremely high risk to fade. Action: Avoid counter-trend unless exhaustion >0.75 (yellow shading). Focus exclusively on continuation opportunities. Momentum is king here. DMA (Directional Momentum Alignment) Zones -2.0 to -1.0: Strong Bearish Momentum Emoji: 🐻🐻 Color: Dark red Meaning: Powerful downside force. Sellers are in control. Action: Bullish divergences are counter-momentum (high risk). Bearish divergences are with-momentum (lower risk). Size down on longs. -0.5 to 0.5: Neutral/Balanced Emoji: ⚖️ Color: Gray/neutral Meaning: No strong directional bias. Choppy or consolidating. Action: Both directions have similar probability. Focus on confidence score and adversarial differential for edge. 1.0 to 2.0: Strong Bullish Momentum Emoji: 🐂🐂 Color: Bright green/cyan Meaning: Powerful upside force. Buyers are in control. Action: Bearish divergences are counter-momentum (high risk). Bullish divergences are with-momentum (lower risk). Size down on shorts. Exhaustion States 0.00-0.50: Fresh Move Emoji: ✓ Color: Green Meaning: Trend is healthy, not overextended. Room to run. Action: Counter-trend trades are premature. Favor continuation. Hold winners for larger moves. Avoid early exits. 0.50-0.75: Mature Move Emoji: 🟡 Color: Yellow Meaning: Move is aging. Watch for signs of climax. Action: Tighten trailing stops on winning trades. Be ready for reversals. Don't add to positions aggressively. 0.75-0.85: High Exhaustion Emoji: ⚠️ Color: Orange Background: Yellow shading appears Meaning: Move is overextended. Reversal risk elevated significantly. Action: Counter-trend reversals are higher probability. Consider early exits on with-trend positions. Size up on reversal divergences (if CAE allows). 0.85-1.00: Critical Exhaustion Emoji: ⚠️⚠️ Color: Red Background: Yellow shading intensifies Meaning: Climax conditions. Reversal imminent or underway. Action: Aggressive reversal trades justified. Exit all with-trend positions. This is where major turns occur. Confidence Score Tiers 0.00-0.30: Low Quality Color: Red Status: Blocked in Filtering mode Action: Skip entirely. Setup lacks fundamental quality across multiple factors. 0.30-0.50: Moderate Quality Color: Yellow/orange Status: Marginal — passes in Filtering only if >min_confidence Action: Reduced position size (0.5-0.75% risk). Tight stops. Conservative profit targets. Skip if you're selective. 0.50-0.70: High Quality Color: Green/cyan Status: Good setup across most quality factors Action: Standard position size (1.0-1.5% risk). Normal stops and targets. This is your bread-and-butter trade. 0.70-1.00: Premium Quality Color: Bright green/gold Status: Exceptional setup — all factors aligned Visual: Double confidence ring appears Action: Consider increased position size (1.5-2.0% risk, maximum). Wider stops. Larger targets. High probability of success. These are rare — capitalize when they appear. Adversarial Differential Interpretation Bull Differential > 0.3 : Visual: Strong cyan/green bar colors Meaning: Bull case strongly dominates. Buyers have clear advantage. Action: Bullish divergences favored (with-advantage). Bearish divergences face headwind (reduce size or skip). Momentum is bullish. Bull Differential 0.1 to 0.3 : Visual: Moderate cyan/green transparency Meaning: Moderate bull advantage. Buyers have edge but not overwhelming. Action: Both directions viable. Slight bias toward longs. Differential -0.1 to 0.1 : Visual: Gray/neutral bars Meaning: Balanced debate. No clear advantage either side. Action: Rely on other factors (confidence, TCS, exhaustion) for direction. Adversarial is neutral. Bear Differential -0.3 to -0.1 : Visual: Moderate red/magenta transparency Meaning: Moderate bear advantage. Sellers have edge but not overwhelming. Action: Both directions viable. Slight bias toward shorts. Bear Differential < -0.3 : Visual: Strong red/magenta bar colors Meaning: Bear case strongly dominates. Sellers have clear advantage. Action: Bearish divergences favored (with-advantage). Bullish divergences face headwind (reduce size or skip). Momentum is bearish. Last Signal Metrics — Post-Trade Analysis After a signal fires, dashboard captures: Type : BULL or BEAR Bars Ago : How long since signal (updates every bar) Confidence : What was the quality score at signal time TCS : What was trend conviction at signal time DMA : What was momentum alignment at signal time Use Case : Post-trade journaling and learning. Example: "BULL signal 12 bars ago. Confidence: 68%, TCS: 0.42, DMA: -0.85" Analysis : This was a bullish reversal (regular div) with good confidence, weak trend (TCS), but strong bearish momentum (DMA). The bet was that momentum would reverse — a counter-momentum play requiring exhaustion confirmation. Check if exhaustion was high at that time to justify the entry. Track patterns: Do your best trades have confidence >0.65? Do low-TCS signals (<0.50) work better for you? Are you more successful with-momentum (DMA aligned with signal) or counter-momentum? Troubleshooting Guide Problem: No Signals Appearing Symptoms : Chart loads, dashboard shows metrics, but no divergence signals fire. Diagnosis Checklist : Check dashboard oscillator value : Is it crossing OB/OS levels (70/30)? If oscillator stays in 40-60 range constantly, it can't reach extremes needed for divergence detection. Are pivots forming? : Look for local swing highs/lows on your chart. If price is in tight consolidation, pivots may not meet lookback/lookforward requirements. Is spacing too tight? : Check "Last Signal" metrics — how many bars since last signal? If <12 and your min_bars_ANY is 12, spacing filter is blocking. Is CAE blocking everything? : Check dashboard Statistics section — what's the blocked signal count? High blocks indicate overly strict filters. Solutions : Loosen OB/OS Temporarily : Try 65/35 to verify divergence detection works If signals appear, the issue was threshold strictness Gradually tighten back to 67/33, then 70/30 as appropriate Lower Min Confidence : Try 0.25-0.30 (diagnostic level) If signals appear, filter was too strict Raise gradually to find sweet spot (0.35-0.45 typical) Disable Strong Trend Filter Temporarily : Turn off in CAE settings If signals appear, TCS threshold was blocking everything Re-enable and lower TCS_threshold to 0.70-0.75 Reduce Min Slope Change : Try 0.7-0.8 (from default 1.0) Allows weaker divergences through Helpful on low-volatility instruments Widen Spacing : Set min_bars_ANY to 6-8 Set min_bars_SAME_SIDE to 12-16 Reduces time between allowed signals Check Timing Mode : If using Confirmed, remember there's a pivot_lookforward delay (5+ bars) Switch to Realtime temporarily to verify system is working Realtime has no delay but repaints Verify Oscillator Settings : Length 14 is standard but might not fit all instruments Try length 9-11 for faster response Try length 18-21 for slower, smoother response Problem: Too Many Signals (Signal Spam) Symptoms : Dashboard shows 50+ signals in Statistics, confidence scores mostly <0.40, signals clustering close together. Solutions : Raise Min Confidence : Try 0.40-0.50 (quality filter) Blocks bottom-tier setups Targets top 50-60% of divergences only Tighten OB/OS : Use 70/30 or 75/25 Requires more extreme oscillator readings Reduces false divergences in mid-range Increase Min Slope Change : Try 1.2-1.5 (from default 1.0) Requires stronger, more obvious divergences Filters marginal slope disagreements Raise TCS Threshold : Try 0.85-0.90 (from default 0.80) Stricter trend filter blocks more counter-trend attempts Favors only strongest trend alignment Enable ALL CAE Gates : Turn on Trend Filter + Adversarial + Confidence Triple-layer protection Blocks aggressively — expect 20-40% reduction in signals Widen Spacing : min_bars_ANY: 15-20 (from 12) min_bars_SAME_SIDE: 30-40 (from 24) Creates substantial breathing room Switch to Confirmed Timing : Removes realtime preview noise Ensures full pivot validation 5-bar delay filters many false starts Problem: Signals in Strong Trends Get Stopped Out Symptoms : You take a bullish divergence in a downtrend (or bearish in uptrend), and it immediately fails. Dashboard showed high TCS at the time. Analysis : This is INTENDED behavior — CAE is protecting you from low-probability counter-trend trades. Understanding : Check Last Signal Metrics in dashboard — what was TCS when signal fired? If TCS was >0.85 and signal was counter-trend, CAE correctly identified it as high risk Strong trends rarely reverse cleanly without major exhaustion Your losses here are the system working as designed (blocking bad odds) If You Want to Override (Not Recommended) : Lower TCS_threshold to 0.70-0.75 (allows more counter-trend) Lower exhaustion_required to 0.40 (easier override) Disable Strong Trend Filter entirely (very risky) Better Approach : TRUST THE FILTER — it's preventing costly mistakes Wait for exhaustion >0.75 (yellow shading) before counter-trending strong TCS Focus on continuation signals (hidden divs) in high-TCS environments Use Advisory mode to see what CAE is blocking and learn from outcomes Problem: Adversarial Blocking Seems Wrong Symptoms : You see a divergence that "looks good" visually, but CAE blocks with "Adversarial bearish/bullish" warning. Diagnosis : Check dashboard Bull Case and Bear Case scores at that moment Look at Differential value Check adversarial bar colors — was there strong coloring against your intended direction? Understanding : Adversarial catches "obvious" opposing momentum that's easy to miss Example: Bullish divergence at a local low, BUT price is deeply below EMA50, bearish momentum is strong, and RSI shows knife-catching conditions Bull Case might be 0.20 while Bear Case is 0.55 Differential = -0.35, far beyond threshold Block is CORRECT — you'd be fighting overwhelming opposing flow If You Disagree Consistently Review blocked signals on chart — scroll back and check outcomes Did those blocked signals actually work, or did they fail as adversarial predicted? Raise adv_threshold to 0.15-0.20 (more permissive, allows closer battles) Disable Adversarial Validation temporarily (diagnostic) to isolate its effect Use Advisory mode to learn adversarial patterns over 50-100 signals Remember : Adversarial is conservative BY DESIGN. It prevents "obvious" bad trades where you're fighting strong strength the other way. Problem: Dashboard Not Showing or Incomplete Solutions : Toggle "Show Dashboard" to ON in settings Try different dashboard sizes (Small/Normal/Large) Try different positions (Top Left/Right, Bottom Left/Right) — might be off-screen Some sections require CAE Enable = ON (Cognitive Engine section won't appear if CAE is disabled) Statistics section requires at least 1 lifetime signal to populate Check that visual theme is set (dashboard colors adapt to theme) Problem: Performance Lag, Chart Freezing Symptoms : Chart loading is slow, indicator calculations cause delays, pinch-to-zoom lags. Diagnosis : Visual features are computationally expensive, especially adversarial bar coloring (recalculates every bar). Solutions (In Order of Impact) : Disable Adversarial Bar Coloring (MOST EXPENSIVE): Turn OFF "Adversarial Bar Coloring" in settings This is the single biggest performance drain Immediate improvement Reduce Vertical Lines : Lower "Keep last N vertical lines" to 20-30 Or set to 0 to disable entirely Moderate improvement Disable Bifurcation Zones : Turn OFF "Draw Bifurcation Zones" Reduces box drawing calculations Moderate improvement Set Dashboard Size to Small : Smaller dashboard = fewer cells = less rendering Minor improvement Use Shorter Max Lookback : Reduce max_lookback to 40-50 (from 60+) Fewer bars to scan for divergences Minor improvement Disable Exhaustion Shading : Turn OFF "Show Market State" Removes background coloring calculations Minor improvement Extreme Performance Mode : Disable ALL visual enhancements Keep only triangle markers Dashboard Small or OFF Use Minimal theme if available Problem: Realtime Signals Repainting Symptoms : You see a signal appear, but on next bar it disappears or moves. Explanation : Realtime mode detects peaks 1 bar ago: high > high AND high > high On the FORMING bar (before close), this condition can change as new prices arrive Example: At 10:05, high (10:04 bar) was 100, current high is 99 → peak detected At 10:05:30, new high of 101 arrives → peak condition breaks → signal disappears At 10:06 (bar close), final high is 101 → no peak at 10:04 anymore → signal gone permanently This is expected behavior for realtime responsiveness. You get preview/early warning, but it's not locked until bar confirms. Solutions : Use Confirmed Timing : Switch to "Confirmed (lookforward)" mode ZERO repainting — pivot must be fully validated 5-bar delay (pivot_lookforward) What you see in history is exactly what would have appeared live Accept Realtime Repaint as Tradeoff : Keep Realtime mode for speed and alerts Understand that pre-confirmation signals may vanish Only trade signals that CONFIRM at bar close (check barstate.isconfirmed) Use for live monitoring, NOT for backtesting Trade Only After Confirmation : In Realtime mode, wait 1 full bar after signal appears before entering If signal survives that bar close, it's locked This adds 1-bar delay but removes repaint risk Recommendation : Use Confirmed for backtesting and conservative trading. Use Realtime only for active monitoring with full understanding of preview behavior. Risk Management Integration BZ-CAE is a signal generation system, not a complete trading strategy. You must integrate proper risk management: Position Sizing by Confidence Confidence 0.70-1.00 (Premium) : Risk: 1.5-2.0% of account (MAXIMUM) Reasoning: High-quality setup across all factors Still cap at 2% — even premium setups can fail Confidence 0.50-0.70 (High Quality) : Risk: 1.0-1.5% of account Reasoning: Standard good setup Your bread-and-butter risk level Confidence 0.35-0.50 (Moderate Quality) : Risk: 0.5-1.0% of account Reasoning: Marginal setup, passes minimum threshold Reduce size or skip if you're selective Confidence <0.35 (Low Quality) : Risk: 0% (blocked in Filtering mode) Reasoning: Insufficient quality factors System protects you by not showing these Stop Placement Strategies For Reversal Signals (Regular Divergences) : Place stop beyond the divergence pivot plus buffer Bullish : Stop below the divergence low - 1.0-1.5 × ATR Bearish : Stop above the divergence high + 1.0-1.5 × ATR Reasoning: If price breaks the pivot, divergence structure is invalidated For Continuation Signals (Hidden Divergences) : Place stop beyond recent swing in opposite direction Bullish continuation : Stop below recent swing low (not the divergence pivot itself) Bearish continuation : Stop above recent swing high Reasoning: You're trading with trend, allow more breathing room ATR-Based Stops : 1.5-2.0 × ATR is standard Scale by timeframe: Scalping (1-5m): 1.0-1.5 × ATR (tight) Day trading (15m-1H): 1.5-2.0 × ATR (balanced) Swing (4H-D): 2.0-3.0 × ATR (wide) Never Use Fixed Dollar/Pip Stops : Markets have different volatility 50-pip stop on EUR/USD ≠ 50-pip stop on GBP/JPY Always normalize by ATR or pivot structure Profit Targets and Scaling Primary Target : 2-3 × ATR from entry (minimum 2:1 reward-risk) Example : Entry at 100, ATR = 2, stop at 97 (1.5 × ATR) → target at 106 (3 × ATR) = 2:1 R:R Scaling Out Strategy : Take 50% off at 1.5 × ATR (secure partial profit) Move stop to breakeven Trail remaining 50% with 1.0 × ATR trailing stop Let winners run if trend persists Targets by Confidence : High Confidence (>0.70) : Aggressive targets (3-4 × ATR), trail wider (1.5 × ATR) Standard Confidence (0.50-0.70) : Normal targets (2-3 × ATR), standard trail (1.0 × ATR) Low Confidence (0.35-0.50) : Conservative targets (1.5-2 × ATR), tight trail (0.75 × ATR) Use Bifurcation Zones : If opposite-side zone is visible on chart (from previous signal), use it as target Example : Bullish signal at 100, prior supply zone at 110 → use 110 as target Zones mark institutional resistance/support Exhaustion-Based Exits : If you're in a trade and exhaustion >0.75 develops (yellow shading), consider early exit Market is overextended — reversal risk is high Take profit even if target not reached Trade Management by TCS High TCS + Counter-Trend Trade (Risky) : Use very tight stops (1.0-1.5 × ATR) Conservative targets (1.5-2 × ATR) Quick exit if trade doesn't work immediately You're fading momentum — respect it Low TCS + Reversal Trade (Safer) : Use wider stops (2.0-2.5 × ATR) Aggressive targets (3-4 × ATR) Trail with patience Genuine reversal potential in weak trend High TCS + Continuation Trade (Safest) : Standard stops (1.5-2.0 × ATR) Very aggressive targets (4-5 × ATR) Trail wide (1.5-2.0 × ATR) You're with institutional momentum — let it run Educational Value — Learning Machine Intelligence BZ-CAE is designed as a learning platform, not just a tool: Advisory Mode as Teacher Most indicators are binary: signal or no signal. You don't learn WHY certain setups are better. BZ-CAE's Advisory mode shows you EVERY potential divergence, then annotates the ones that would be blocked in Filtering mode with specific reasons: "Bull: strong downtrend (TCS=0.87)" teaches you that TCS >0.85 makes counter-trend very risky "Adversarial bearish" teaches you that the opposing case was dominating "Low confidence 32%" teaches you that the setup lacked quality across multiple factors "Bull spacing: wait 8 bars" teaches you that signals need breathing room After 50-100 signals in Advisory mode, you internalize the CAE's decision logic. You start seeing these factors yourself BEFORE the indicator does. Dashboard Transparency Most "intelligent" indicators are black boxes — you don't know how they make decisions. BZ-CAE shows you ALL metrics in real-time: TCS tells you trend strength DMA tells you momentum alignment Exhaustion tells you overextension Adversarial shows both sides of the debate Confidence shows composite quality You learn to interpret market state holistically, a skill applicable to ANY trading system beyond this indicator. Divergence Quality Education Not all divergences are equal. BZ-CAE teaches you which conditions produce high-probability setups: Quality divergence : Regular bullish div at a low, TCS <0.50 (weak trend), exhaustion >0.75 (overextended), positive adversarial differential, confidence >0.70 Low-quality divergence : Regular bearish div at a high, TCS >0.85 (strong uptrend), exhaustion <0.30 (not overextended), negative adversarial differential, confidence <0.40 After using the system, you can evaluate divergences manually with similar intelligence. Risk Management Discipline Confidence-based position sizing teaches you to adjust risk based on setup quality, not emotions: Beginners often size all trades identically Or worse, size UP on marginal setups to "make up" for losses BZ-CAE forces systematic sizing: premium setups get larger size, marginal setups get smaller size This creates a probabilistic approach where your edge compounds over time. What This Indicator Is NOT Complete transparency about limitations and positioning: Not a Prediction System BZ-CAE does not predict future prices. It identifies structural divergences (price-momentum disagreements) and assesses current market state (trend, exhaustion, adversarial conditions). It tells you WHEN conditions favor a potential reversal or continuation, not WHAT WILL HAPPEN. Markets are probabilistic. Even premium-confidence setups fail ~30-40% of the time. The system improves your probability distribution over many trades — it doesn't eliminate risk. Not Fully Automated This is a decision support tool, not a trading robot. You must: Execute trades manually based on signals Manage positions (stops, targets, trailing) Apply discretionary judgment (news events, liquidity, context) Integrate with your broader strategy and risk rules The confidence scores guide position sizing, but YOU determine final risk allocation based on your account size, risk tolerance, and portfolio context. Not Beginner-Friendly BZ-CAE requires understanding of: Divergence trading concepts (regular vs hidden, reversal vs continuation) Market state interpretation (trend vs range, momentum, exhaustion) Basic technical analysis (pivots, support/resistance, EMAs) Risk management fundamentals (position sizing, stops, R:R) This is designed for intermediate to advanced traders willing to invest time learning the system. If you want "buy the arrow" simplicity, this isn't the tool. Not a Holy Grail There is no perfect indicator. BZ-CAE filters noise and improves signal quality significantly, but: Losing trades are inevitable (even at 70% win rate, 30% still fail) Market conditions change rapidly (yesterday's strong trend becomes today's chop) Black swan events occur (fundamentals override technicals) Execution matters (slippage, fees, emotional discipline) The system provides an EDGE, not a guarantee. Your job is to execute that edge consistently with proper risk management over hundreds of trades. Not Financial Advice BZ-CAE is an educational and analytical tool. All trading decisions are your responsibility. Past performance (backtested or live) does not guarantee future results. Only risk capital you can afford to lose. Consult a licensed financial advisor for investment advice specific to your situation. Ideal Market Conditions Best Performance Characteristics Liquid Instruments : Major forex pairs (EUR/USD, GBP/USD, USD/JPY) Large-cap stocks and index ETFs (SPY, QQQ, AAPL, MSFT) High-volume crypto (BTC, ETH) Major commodities (Gold, Oil, Natural Gas) Reasoning: Clean price structure, clear pivots, meaningful oscillator behavior Trending with Consolidations : Markets that trend for 20-40 bars, then consolidate 10-20 bars, repeat Creates divergences at consolidation boundaries (reversals) and within trends (continuations) Both regular and hidden divs find opportunities 5-Minute to Daily Timeframes : Below 5m: too much noise, false pivots, CAE metrics unstable Above daily: too few signals, edge diminishes (fundamentals dominate) Sweet spot: 15m to 4H for most traders Consistent Volume and Participation : Regular trading sessions (not holidays or thin markets) Predictable volatility patterns Avoid instruments with sudden gaps or circuit breakers Challenging Conditions Extremely Low Liquidity : Penny stocks, exotic forex pairs, low-volume crypto Erratic pivots, unreliable oscillator readings CAE metrics can't assess market state properly Very Low Timeframes (1-Minute or Below) : Dominated by market microstructure noise Divergences are everywhere but meaningless CAE filtering helps but still unreliable Extended Sideways Consolidation : 100+ bars of tight range with no clear pivots Oscillator hugs midpoint (45-55 range) No divergences to detect Fundamentally-Driven Gap Markets : Earnings releases, economic data, geopolitical events Price gaps over stops and targets Technical structure breaks down Recommendation: Disable trading around known events Calculation Methodology — Technical Depth For users who want to understand the math: Oscillator Computation Each oscillator type calculates differently, but all normalize to 0-100: RSI : ta.rsi(close, length) — Standard Relative Strength Index Stochastic : ta.stoch(high, low, close, length) — %K calculation CCI : (ta.cci(hlc3, length) + 100) / 2 — Normalized from -100/+100 to 0-100 MFI : ta.mfi(hlc3, length) — Volume-weighted RSI equivalent Williams %R : ta.wpr(length) + 100 — Inverted stochastic adjusted to 0-100 Smoothing: If smoothing > 1, apply ta.sma(oscillator, smoothing) Divergence Detection Algorithm Identify Pivots : Price high pivot: ta.pivothigh(high, lookback, lookforward) Price low pivot: ta.pivotlow(low, lookback, lookforward) Oscillator high pivot: ta.pivothigh(osc, lookback, lookforward) Oscillator low pivot: ta.pivotlow(osc, lookback, lookforward) Store Recent Pivots : Maintain arrays of last 10 pivots with bar indices When new pivot confirmed, unshift to array, pop oldest if >10 Scan for Slope Disagreements : Loop through last 5 pivots For each pair (current pivot, historical pivot): Check if within max_lookback bars Calculate slopes: (current - historical) / bars_between Regular bearish: price_slope > 0, osc_slope < 0, |osc_slope| > min_threshold Regular bullish: price_slope < 0, osc_slope > 0, |osc_slope| > min_threshold Hidden bearish: price_slope < 0, osc_slope > 0, osc_slope > min_threshold Hidden bullish: price_slope > 0, osc_slope < 0, |osc_slope| > min_threshold Important Disclaimers and Terms Performance Disclosure Past performance, whether backtested or live-traded, does not guarantee future results. Markets change. What works today may not work tomorrow. Hypothetical or simulated performance results have inherent limitations and do not represent actual trading. Risk of Loss Trading involves substantial risk of loss. Only trade with risk capital you can afford to lose entirely. The high degree of leverage often available in trading can work against you as well as for you. Leveraged trading may result in losses exceeding your initial deposit. Not Financial Advice BZ-CAE is an educational and analytical tool for technical analysis. It is not financial advice, investment advice, or a recommendation to buy or sell any security or instrument. All trading decisions are your sole responsibility. Consult a licensed financial advisor for advice specific to your circumstances. Technical Indicator Limitations BZ-CAE is a technical analysis tool based on price and volume data. It does not account for: Fundamental analysis (earnings, economic data, financial health) Market sentiment and positioning Geopolitical events and news Liquidity conditions and market microstructure changes Regulatory changes or exchange rules Integrate with broader analysis and strategy. Do not rely solely on technical indicators for trading decisions. Repainting Acknowledgment As disclosed throughout this documentation: Realtime mode may repaint on forming bars before confirmation (by design for preview functionality) Confirmed mode has zero repainting (fully validated pivots only) Choose timing mode appropriate for your use case. Understand the tradeoffs. Testing Recommendation ALWAYS test on demo/paper accounts before committing real capital. Validate the indicator's behavior on your specific instruments and timeframes. Learn the system thoroughly in Advisory mode before using Filtering mode. Learning Resources : In-indicator tooltips (hover over setting names for detailed explanations) This comprehensive publishing statement (save for reference) User guide in script comments (top of code) Final Word — Philosophy of BZ-CAE BZ-CAE is not designed to replace your judgment — it's designed to enhance it. The indicator identifies structural inflection points (bifurcations) where price and momentum disagree. The Cognitive Engine evaluates market state to determine if this disagreement is meaningful or noise. The Adversarial model debates both sides of the trade to catch obvious bad setups. The Confidence system ranks quality so you can choose your risk appetite. But YOU still execute. YOU still manage risk. YOU still learn from outcomes. This is intelligence amplification, not intelligence replacement. Use Advisory mode to learn how expert traders evaluate market state. Use Filtering mode to enforce discipline when emotions run high. Use the dashboard to develop a systematic approach to reading markets. Use confidence scores to size positions probabilistically. The system provides an edge. Your job is to execute that edge with discipline, patience, and proper risk management over hundreds of trades. Markets are probabilistic. No system wins every trade. But a systematic edge + disciplined execution + proper risk management compounds over time. That's the path to consistent profitability. BZ-CAE gives you the edge. The discipline and risk management are on you. Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
مؤشر Pine Script®
من ‎DskyzInvestments‎
Kripto Fema ind/ This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org // © Femayakup //@version=5 indicator(title = "Kripto Fema ind", shorttitle="Kripto Fema ind", overlay=true, format=format.price, precision=2,max_lines_count = 500, max_labels_count = 500, max_bars_back=500) showEma200 = input(true, title="EMA 200") showPmax = input(true, title="Pmax") showLinreg = input(true, title="Linreg") showMavilim = input(true, title="Mavilim") showNadaray = input(true, title="Nadaraya Watson") ma(source, length, type) => switch type "SMA" => ta.sma(source, length) "EMA" => ta.ema(source, length) "SMMA (RMA)" => ta.rma(source, length) "WMA" => ta.wma(source, length) "VWMA" => ta.vwma(source, length) //Ema200 timeFrame = input.timeframe(defval = '240',title= 'EMA200 TimeFrame',group = 'EMA200 Settings') len200 = input.int(200, minval=1, title="Length",group = 'EMA200 Settings') src200 = input(close, title="Source",group = 'EMA200 Settings') offset200 = input.int(title="Offset", defval=0, minval=-500, maxval=500,group = 'EMA200 Settings') out200 = ta.ema(src200, len200) higherTimeFrame = request.security(syminfo.tickerid,timeFrame,out200 ,barmerge.gaps_on,barmerge.lookahead_on) ema200Plot = showEma200 ? higherTimeFrame : na plot(ema200Plot, title="EMA200", offset=offset200) //Linreq group1 = "Linreg Settings" lengthInput = input.int(100, title="Length", minval = 1, maxval = 5000,group = group1) sourceInput = input.source(close, title="Source") useUpperDevInput = input.bool(true, title="Upper Deviation", inline = "Upper Deviation", group = group1) upperMultInput = input.float(2.0, title="", inline = "Upper Deviation", group = group1) useLowerDevInput = input.bool(true, title="Lower Deviation", inline = "Lower Deviation", group = group1) lowerMultInput = input.float(2.0, title="", inline = "Lower Deviation", group = group1) group2 = "Linreg Display Settings" showPearsonInput = input.bool(true, "Show Pearson's R", group = group2) extendLeftInput = input.bool(false, "Extend Lines Left", group = group2) extendRightInput = input.bool(true, "Extend Lines Right", group = group2) extendStyle = switch extendLeftInput and extendRightInput => extend.both extendLeftInput => extend.left extendRightInput => extend.right => extend.none group3 = "Linreg Color Settings" colorUpper = input.color(color.new(color.blue, 85), "Linreg Renk", inline = group3, group = group3) colorLower = input.color(color.new(color.red, 85), "", inline = group3, group = group3) calcSlope(source, length) => max_bars_back(source, 5000) if not barstate.islast or length <= 1 else sumX = 0.0 sumY = 0.0 sumXSqr = 0.0 sumXY = 0.0 for i = 0 to length - 1 by 1 val = source per = i + 1.0 sumX += per sumY += val sumXSqr += per * per sumXY += val * per slope = (length * sumXY - sumX * sumY) / (length * sumXSqr - sumX * sumX) average = sumY / length intercept = average - slope * sumX / length + slope = calcSlope(sourceInput, lengthInput) startPrice = i + s * (lengthInput - 1) endPrice = i var line baseLine = na if na(baseLine) and not na(startPrice) and showLinreg baseLine := line.new(bar_index - lengthInput + 1, startPrice, bar_index, endPrice, width=1, extend=extendStyle, color=color.new(colorLower, 0)) else line.set_xy1(baseLine, bar_index - lengthInput + 1, startPrice) line.set_xy2(baseLine, bar_index, endPrice) na calcDev(source, length, slope, average, intercept) => upDev = 0.0 dnDev = 0.0 stdDevAcc = 0.0 dsxx = 0.0 dsyy = 0.0 dsxy = 0.0 periods = length - 1 daY = intercept + slope * periods / 2 val = intercept for j = 0 to periods by 1 price = high - val if price > upDev upDev := price price := val - low if price > dnDev dnDev := price price := source dxt = price - average dyt = val - daY price -= val stdDevAcc += price * price dsxx += dxt * dxt dsyy += dyt * dyt dsxy += dxt * dyt val += slope stdDev = math.sqrt(stdDevAcc / (periods == 0 ? 1 : periods)) pearsonR = dsxx == 0 or dsyy == 0 ? 0 : dsxy / math.sqrt(dsxx * dsyy) = calcDev(sourceInput, lengthInput, s, a, i) upperStartPrice = startPrice + (useUpperDevInput ? upperMultInput * stdDev : upDev) upperEndPrice = endPrice + (useUpperDevInput ? upperMultInput * stdDev : upDev) var line upper = na lowerStartPrice = startPrice + (useLowerDevInput ? -lowerMultInput * stdDev : -dnDev) lowerEndPrice = endPrice + (useLowerDevInput ? -lowerMultInput * stdDev : -dnDev) var line lower = na if na(upper) and not na(upperStartPrice) and showLinreg upper := line.new(bar_index - lengthInput + 1, upperStartPrice, bar_index, upperEndPrice, width=1, extend=extendStyle, color=color.new(colorUpper, 0)) else line.set_xy1(upper, bar_index - lengthInput + 1, upperStartPrice) line.set_xy2(upper, bar_index, upperEndPrice) na if na(lower) and not na(lowerStartPrice) and showLinreg lower := line.new(bar_index - lengthInput + 1, lowerStartPrice, bar_index, lowerEndPrice, width=1, extend=extendStyle, color=color.new(colorUpper, 0)) else line.set_xy1(lower, bar_index - lengthInput + 1, lowerStartPrice) line.set_xy2(lower, bar_index, lowerEndPrice) na showLinregPlotUpper = showLinreg ? upper : na showLinregPlotLower = showLinreg ? lower : na showLinregPlotBaseLine = showLinreg ? baseLine : na linefill.new(showLinregPlotUpper, showLinregPlotBaseLine, color = colorUpper) linefill.new(showLinregPlotBaseLine, showLinregPlotLower, color = colorLower) // Pearson's R var label r = na label.delete(r ) if showPearsonInput and not na(pearsonR) and showLinreg r := label.new(bar_index - lengthInput + 1, lowerStartPrice, str.tostring(pearsonR, "#.################"), color = color.new(color.white, 100), textcolor=color.new(colorUpper, 0), size=size.normal, style=label.style_label_up) //Mavilim group4 = "Mavilim Settings" mavilimold = input(false, title="Show Previous Version of MavilimW?",group=group4) fmal=input(3,"First Moving Average length",group = group4) smal=input(5,"Second Moving Average length",group = group4) tmal=fmal+smal Fmal=smal+tmal Ftmal=tmal+Fmal Smal=Fmal+Ftmal M1= ta.wma(close, fmal) M2= ta.wma(M1, smal) M3= ta.wma(M2, tmal) M4= ta.wma(M3, Fmal) M5= ta.wma(M4, Ftmal) MAVW= ta.wma(M5, Smal) col1= MAVW>MAVW col3= MAVWpmaxsrc ? pmaxsrc-pmaxsrc : 0 vdd1=pmaxsrc ma = 0.0 if mav == "SMA" ma := ta.sma(pmaxsrc, length) ma if mav == "EMA" ma := ta.ema(pmaxsrc, length) ma if mav == "WMA" ma := ta.wma(pmaxsrc, length) ma if mav == "TMA" ma := ta.sma(ta.sma(pmaxsrc, math.ceil(length / 2)), math.floor(length / 2) + 1) ma if mav == "VAR" ma := VAR ma if mav == "WWMA" ma := WWMA ma if mav == "ZLEMA" ma := ZLEMA ma if mav == "TSF" ma := TSF ma ma MAvg=getMA(pmaxsrc, length) longStop = Normalize ? MAvg - Multiplier*atr/close : MAvg - Multiplier*atr longStopPrev = nz(longStop , longStop) longStop := MAvg > longStopPrev ? math.max(longStop, longStopPrev) : longStop shortStop = Normalize ? MAvg + Multiplier*atr/close : MAvg + Multiplier*atr shortStopPrev = nz(shortStop , shortStop) shortStop := MAvg < shortStopPrev ? math.min(shortStop, shortStopPrev) : shortStop dir = 1 dir := nz(dir , dir) dir := dir == -1 and MAvg > shortStopPrev ? 1 : dir == 1 and MAvg < longStopPrev ? -1 : dir PMax = dir==1 ? longStop: shortStop plot(showsupport ? MAvg : na, color=#fbff04, linewidth=2, title="EMA9") pALL=plot(PMax, color=color.new(color.red, transp = 0), linewidth=2, title="PMax") alertcondition(ta.cross(MAvg, PMax), title="Cross Alert", message="PMax - Moving Avg Crossing!") alertcondition(ta.crossover(MAvg, PMax), title="Crossover Alarm", message="Moving Avg BUY SIGNAL!") alertcondition(ta.crossunder(MAvg, PMax), title="Crossunder Alarm", message="Moving Avg SELL SIGNAL!") alertcondition(ta.cross(pmaxsrc, PMax), title="Price Cross Alert", message="PMax - Price Crossing!") alertcondition(ta.crossover(pmaxsrc, PMax), title="Price Crossover Alarm", message="PRICE OVER PMax - BUY SIGNAL!") alertcondition(ta.crossunder(pmaxsrc, PMax), title="Price Crossunder Alarm", message="PRICE UNDER PMax - SELL SIGNAL!") buySignalk = ta.crossover(MAvg, PMax) plotshape(buySignalk and showsignalsk ? PMax*0.995 : na, title="Buy", text="Buy", location=location.absolute, style=shape.labelup, size=size.tiny, color=color.new(color.green, transp = 0), textcolor=color.white) sellSignallk = ta.crossunder(MAvg, PMax) plotshape(sellSignallk and showsignalsk ? PMax*1.005 : na, title="Sell", text="Sell", location=location.absolute, style=shape.labeldown, size=size.tiny, color=color.new(color.red, transp = 0), textcolor=color.white) // buySignalc = ta.crossover(pmaxsrc, PMax) // plotshape(buySignalc and showsignalsc ? PMax*0.995 : na, title="Buy", text="Buy", location=location.absolute, style=shape.labelup, size=size.tiny, color=#0F18BF, textcolor=color.white) // sellSignallc = ta.crossunder(pmaxsrc, PMax) // plotshape(sellSignallc and showsignalsc ? PMax*1.005 : na, title="Sell", text="Sell", location=location.absolute, style=shape.labeldown, size=size.tiny, color=#0F18BF, textcolor=color.white) // mPlot = plot(ohlc4, title="", style=plot.style_circles, linewidth=0,display=display.none) longFillColor = highlighting ? (MAvg>PMax ? color.new(color.green, transp = 90) : na) : na shortFillColor = highlighting ? (MAvg math.exp(-(math.pow(x, 2)/(h * h * 2))) //-----------------------------------------------------------------------------} //Append lines //-----------------------------------------------------------------------------{ n = bar_index var ln = array.new_line(0) if barstate.isfirst and repaint for i = 0 to 499 array.push(ln,line.new(na,na,na,na)) //-----------------------------------------------------------------------------} //End point method //-----------------------------------------------------------------------------{ var coefs = array.new_float(0) var den = 0. if barstate.isfirst and not repaint for i = 0 to 499 w = gauss(i, h) coefs.push(w) den := coefs.sum() out = 0. if not repaint for i = 0 to 499 out += src * coefs.get(i) out /= den mae = ta.sma(math.abs(src - out), 499) * mult upperN = out + mae lowerN = out - mae //-----------------------------------------------------------------------------} //Compute and display NWE //-----------------------------------------------------------------------------{ float y2 = na float y1 = na nwe = array.new(0) if barstate.islast and repaint sae = 0. //Compute and set NWE point for i = 0 to math.min(499,n - 1) sum = 0. sumw = 0. //Compute weighted mean for j = 0 to math.min(499,n - 1) w = gauss(i - j, h) sum += src * w sumw += w y2 := sum / sumw sae += math.abs(src - y2) nwe.push(y2) sae := sae / math.min(499,n - 1) * mult for i = 0 to math.min(499,n - 1) if i%2 and showNadaray line.new(n-i+1, y1 + sae, n-i, nwe.get(i) + sae, color = upCss) line.new(n-i+1, y1 - sae, n-i, nwe.get(i) - sae, color = dnCss) if src > nwe.get(i) + sae and src < nwe.get(i) + sae and showNadaray label.new(n-i, src , '▼', color = color(na), style = label.style_label_down, textcolor = dnCss, textalign = text.align_center) if src < nwe.get(i) - sae and src > nwe.get(i) - sae and showNadaray label.new(n-i, src , '▲', color = color(na), style = label.style_label_up, textcolor = upCss, textalign = text.align_center) y1 := nwe.get(i) //-----------------------------------------------------------------------------} //Dashboard //-----------------------------------------------------------------------------{ var tb = table.new(position.top_right, 1, 1 , bgcolor = #1e222d , border_color = #373a46 , border_width = 1 , frame_color = #373a46 , frame_width = 1) if repaint tb.cell(0, 0, 'Repainting Mode Enabled', text_color = color.white, text_size = size.small) //-----------------------------------------------------------------------------} //Plot //-----------------------------------------------------------------------------} // plot(repaint ? na : out + mae, 'Upper', upCss) // plot(repaint ? na : out - mae, 'Lower', dnCss) //Crossing Arrows // plotshape(ta.crossunder(close, out - mae) ? low : na, "Crossunder", shape.labelup, location.absolute, color(na), 0 , text = '▲', textcolor = upCss, size = size.tiny) // plotshape(ta.crossover(close, out + mae) ? high : na, "Crossover", shape.labeldown, location.absolute, color(na), 0 , text = '▼', textcolor = dnCss, size = size.tiny) //-----------------------------------------------------------------------------} ////////////////////////////////////////////////////////////////////////////////// enableD = input (true, "DIVERGANCE ON/OFF" , group="INDICATORS ON/OFF") //DIVERGANCE prd1 = input.int (defval=5 , title='PIVOT PERIOD' , minval=1, maxval=50 , group="DIVERGANCE") source = input.string(defval='HIGH/LOW' , title='SOURCE FOR PIVOT POINTS' , options= , group="DIVERGANCE") searchdiv = input.string(defval='REGULAR/HIDDEN', title='DIVERGANCE TYPE' , options= , group="DIVERGANCE") showindis = input.string(defval='FULL' , title='SHOW INDICATORS NAME' , options= , group="DIVERGANCE") showlimit = input.int(1 , title='MINIMUM NUMBER OF DIVERGANCES', minval=1, maxval=11 , group="DIVERGANCE") maxpp = input.int (defval=20 , title='MAXIMUM PIVOT POINTS TO CHECK', minval=1, maxval=20 , group="DIVERGANCE") maxbars = input.int (defval=200 , title='MAXIMUM BARS TO CHECK' , minval=30, maxval=200 , group="DIVERGANCE") showlast = input (defval=false , title='SHOW ONLY LAST DIVERGANCE' , group="DIVERGANCE") dontconfirm = input (defval=false , title="DON'T WAIT FOR CONFORMATION" , group="DIVERGANCE") showlines = input (defval=false , title='SHOW DIVERGANCE LINES' , group="DIVERGANCE") showpivot = input (defval=false , title='SHOW PIVOT POINTS' , group="DIVERGANCE") calcmacd = input (defval=true , title='MACD' , group="DIVERGANCE") calcmacda = input (defval=true , title='MACD HISTOGRAM' , group="DIVERGANCE") calcrsi = input (defval=true , title='RSI' , group="DIVERGANCE") calcstoc = input (defval=true , title='STOCHASTIC' , group="DIVERGANCE") calccci = input (defval=true , title='CCI' , group="DIVERGANCE") calcmom = input (defval=true , title='MOMENTUM' , group="DIVERGANCE") calcobv = input (defval=true , title='OBV' , group="DIVERGANCE") calcvwmacd = input (true , title='VWMACD' , group="DIVERGANCE") calccmf = input (true , title='CHAIKIN MONEY FLOW' , group="DIVERGANCE") calcmfi = input (true , title='MONEY FLOW INDEX' , group="DIVERGANCE") calcext = input (false , title='CHECK EXTERNAL INDICATOR' , group="DIVERGANCE") externalindi = input (defval=close , title='EXTERNAL INDICATOR' , group="DIVERGANCE") pos_reg_div_col = input (defval=#ffffff , title='POSITIVE REGULAR DIVERGANCE' , group="DIVERGANCE") neg_reg_div_col = input (defval=#00def6 , title='NEGATIVE REGULAR DIVERGANCE' , group="DIVERGANCE") pos_hid_div_col = input (defval=#00ff0a , title='POSITIVE HIDDEN DIVERGANCE' , group="DIVERGANCE") neg_hid_div_col = input (defval=#ff0015 , title='NEGATIVE HIDDEN DIVERGANCE' , group="DIVERGANCE") reg_div_l_style_ = input.string(defval='SOLID' , title='REGULAR DIVERGANCE LINESTYLE' , options= , group="DIVERGANCE") hid_div_l_style_ = input.string(defval='SOLID' , title='HIDDEN DIVERGANCE LINESTYLE' , options= , group="DIVERGANCE") reg_div_l_width = input.int (defval=2 , title='REGULAR DIVERGANCE LINEWIDTH' , minval=1, maxval=5 , group="DIVERGANCE") hid_div_l_width = input.int (defval=2 , title='HIDDEN DIVERGANCE LINEWIDTH' , minval=1, maxval=5 , group="DIVERGANCE") showmas = input.bool (defval=false , title='SHOW MOVING AVERAGES (50 & 200)', inline='MA' , group="DIVERGANCE") cma1col = input.color (defval=#ffffff , title='' , inline='MA' , group="DIVERGANCE") cma2col = input.color (defval=#00def6 , title='' , inline='MA' , group="DIVERGANCE") //PLOTS plot(showmas ? ta.sma(close, 50) : na, color=showmas ? cma1col : na) plot(showmas ? ta.sma(close, 200) : na, color=showmas ? cma2col : na) var reg_div_l_style = reg_div_l_style_ == 'SOLID' ? line.style_solid : reg_div_l_style_ == 'DASHED' ? line.style_dashed : line.style_dotted var hid_div_l_style = hid_div_l_style_ == 'SOLID' ? line.style_solid : hid_div_l_style_ == 'DASHED' ? line.style_dashed : line.style_dotted rsi = ta.rsi(close, 14) = ta.macd(close, 12, 26, 9) moment = ta.mom(close, 10) cci = ta.cci(close, 10) Obv = ta.obv stk = ta.sma(ta.stoch(close, high, low, 14), 3) maFast = ta.vwma(close, 12) maSlow = ta.vwma(close, 26) vwmacd = maFast - maSlow Cmfm = (close - low - (high - close)) / (high - low) Cmfv = Cmfm * volume cmf = ta.sma(Cmfv, 21) / ta.sma(volume, 21) Mfi = ta.mfi(close, 14) var indicators_name = array.new_string(11) var div_colors = array.new_color(4) if barstate.isfirst and enableD array.set(indicators_name, 0, showindis == "DON'T SHOW" ? '' : '') array.set(indicators_name, 1, showindis == "DON'T SHOW" ? '' : '') array.set(indicators_name, 2, showindis == "DON'T SHOW" ? '' : '') array.set(indicators_name, 3, showindis == "DON'T SHOW" ? '' : '') array.set(indicators_name, 4, showindis == "DON'T SHOW" ? '' : '') array.set(indicators_name, 5, showindis == "DON'T SHOW" ? '' : '') array.set(indicators_name, 6, showindis == "DON'T SHOW" ? '' : '') array.set(indicators_name, 7, showindis == "DON'T SHOW" ? '' : '') array.set(indicators_name, 8, showindis == "DON'T SHOW" ? '' : '') array.set(indicators_name, 9, showindis == "DON'T SHOW" ? '' : '') array.set(indicators_name, 10, showindis == "DON'T SHOW" ? '' : '') array.set(div_colors, 0, pos_reg_div_col) array.set(div_colors, 1, neg_reg_div_col) array.set(div_colors, 2, pos_hid_div_col) array.set(div_colors, 3, neg_hid_div_col) float ph1 = ta.pivothigh(source == 'CLOSE' ? close : high, prd1, prd1) float pl1 = ta.pivotlow(source == 'CLOSE' ? close : low, prd1, prd1) plotshape(ph1 and showpivot, text='H', style=shape.labeldown, color=color.new(color.white, 100), textcolor=#00def6, location=location.abovebar, offset=-prd1) plotshape(pl1 and showpivot, text='L', style=shape.labelup, color=color.new(color.white, 100), textcolor=#ffffff, location=location.belowbar, offset=-prd1) var int maxarraysize = 20 var ph_positions = array.new_int(maxarraysize, 0) var pl_positions = array.new_int(maxarraysize, 0) var ph_vals = array.new_float(maxarraysize, 0.) var pl_vals = array.new_float(maxarraysize, 0.) if ph1 array.unshift(ph_positions, bar_index) array.unshift(ph_vals, ph1) if array.size(ph_positions) > maxarraysize array.pop(ph_positions) array.pop(ph_vals) if pl1 array.unshift(pl_positions, bar_index) array.unshift(pl_vals, pl1) if array.size(pl_positions) > maxarraysize array.pop(pl_positions) array.pop(pl_vals) positive_regular_positive_hidden_divergence(src, cond) => divlen = 0 prsc = source == 'CLOSE' ? close : low if dontconfirm or src > src or close > close startpoint = dontconfirm ? 0 : 1 for x = 0 to maxpp - 1 by 1 len = bar_index - array.get(pl_positions, x) + prd1 if array.get(pl_positions, x) == 0 or len > maxbars break if len > 5 and (cond == 1 and src > src and prsc < nz(array.get(pl_vals, x)) or cond == 2 and src < src and prsc > nz(array.get(pl_vals, x))) slope1 = (src - src ) / (len - startpoint) virtual_line1 = src - slope1 slope2 = (close - close ) / (len - startpoint) virtual_line2 = close - slope2 arrived = true for y = 1 + startpoint to len - 1 by 1 if src < virtual_line1 or nz(close ) < virtual_line2 arrived := false break virtual_line1 -= slope1 virtual_line2 -= slope2 virtual_line2 if arrived divlen := len break divlen negative_regular_negative_hidden_divergence(src, cond) => divlen = 0 prsc = source == 'CLOSE' ? close : high if dontconfirm or src < src or close < close startpoint = dontconfirm ? 0 : 1 for x = 0 to maxpp - 1 by 1 len = bar_index - array.get(ph_positions, x) + prd1 if array.get(ph_positions, x) == 0 or len > maxbars break if len > 5 and (cond == 1 and src < src and prsc > nz(array.get(ph_vals, x)) or cond == 2 and src > src and prsc < nz(array.get(ph_vals, x))) slope1 = (src - src ) / (len - startpoint) virtual_line1 = src - slope1 slope2 = (close - nz(close )) / (len - startpoint) virtual_line2 = close - slope2 arrived = true for y = 1 + startpoint to len - 1 by 1 if src > virtual_line1 or nz(close ) > virtual_line2 arrived := false break virtual_line1 -= slope1 virtual_line2 -= slope2 virtual_line2 if arrived divlen := len break divlen //CALCULATIONS calculate_divs(cond, indicator_1) => divs = array.new_int(4, 0) array.set(divs, 0, cond and (searchdiv == 'REGULAR' or searchdiv == 'REGULAR/HIDDEN') ? positive_regular_positive_hidden_divergence(indicator_1, 1) : 0) array.set(divs, 1, cond and (searchdiv == 'REGULAR' or searchdiv == 'REGULAR/HIDDEN') ? negative_regular_negative_hidden_divergence(indicator_1, 1) : 0) array.set(divs, 2, cond and (searchdiv == 'HIDDEN' or searchdiv == 'REGULAR/HIDDEN') ? positive_regular_positive_hidden_divergence(indicator_1, 2) : 0) array.set(divs, 3, cond and (searchdiv == 'HIDDEN' or searchdiv == 'REGULAR/HIDDEN') ? negative_regular_negative_hidden_divergence(indicator_1, 2) : 0) divs var all_divergences = array.new_int(44) array_set_divs(div_pointer, index) => for x = 0 to 3 by 1 array.set(all_divergences, index * 4 + x, array.get(div_pointer, x)) array_set_divs(calculate_divs(calcmacd , macd) , 0) array_set_divs(calculate_divs(calcmacda , deltamacd) , 1) array_set_divs(calculate_divs(calcrsi , rsi) , 2) array_set_divs(calculate_divs(calcstoc , stk) , 3) array_set_divs(calculate_divs(calccci , cci) , 4) array_set_divs(calculate_divs(calcmom , moment) , 5) array_set_divs(calculate_divs(calcobv , Obv) , 6) array_set_divs(calculate_divs(calcvwmacd, vwmacd) , 7) array_set_divs(calculate_divs(calccmf , cmf) , 8) array_set_divs(calculate_divs(calcmfi , Mfi) , 9) array_set_divs(calculate_divs(calcext , externalindi), 10) total_div = 0 for x = 0 to array.size(all_divergences) - 1 by 1 total_div += math.round(math.sign(array.get(all_divergences, x))) total_div if total_div < showlimit array.fill(all_divergences, 0) var pos_div_lines = array.new_line(0) var neg_div_lines = array.new_line(0) var pos_div_labels = array.new_label(0) var neg_div_labels = array.new_label(0) delete_old_pos_div_lines() => if array.size(pos_div_lines) > 0 for j = 0 to array.size(pos_div_lines) - 1 by 1 line.delete(array.get(pos_div_lines, j)) array.clear(pos_div_lines) delete_old_neg_div_lines() => if array.size(neg_div_lines) > 0 for j = 0 to array.size(neg_div_lines) - 1 by 1 line.delete(array.get(neg_div_lines, j)) array.clear(neg_div_lines) delete_old_pos_div_labels() => if array.size(pos_div_labels) > 0 for j = 0 to array.size(pos_div_labels) - 1 by 1 label.delete(array.get(pos_div_labels, j)) array.clear(pos_div_labels) delete_old_neg_div_labels() => if array.size(neg_div_labels) > 0 for j = 0 to array.size(neg_div_labels) - 1 by 1 label.delete(array.get(neg_div_labels, j)) array.clear(neg_div_labels) delete_last_pos_div_lines_label(n) => if n > 0 and array.size(pos_div_lines) >= n asz = array.size(pos_div_lines) for j = 1 to n by 1 line.delete(array.get(pos_div_lines, asz - j)) array.pop(pos_div_lines) if array.size(pos_div_labels) > 0 label.delete(array.get(pos_div_labels, array.size(pos_div_labels) - 1)) array.pop(pos_div_labels) delete_last_neg_div_lines_label(n) => if n > 0 and array.size(neg_div_lines) >= n asz = array.size(neg_div_lines) for j = 1 to n by 1 line.delete(array.get(neg_div_lines, asz - j)) array.pop(neg_div_lines) if array.size(neg_div_labels) > 0 label.delete(array.get(neg_div_labels, array.size(neg_div_labels) - 1)) array.pop(neg_div_labels) pos_reg_div_detected = false neg_reg_div_detected = false pos_hid_div_detected = false neg_hid_div_detected = false var last_pos_div_lines = 0 var last_neg_div_lines = 0 var remove_last_pos_divs = false var remove_last_neg_divs = false if pl1 remove_last_pos_divs := false last_pos_div_lines := 0 last_pos_div_lines if ph1 remove_last_neg_divs := false last_neg_div_lines := 0 last_neg_div_lines divergence_text_top = '' divergence_text_bottom = '' distances = array.new_int(0) dnumdiv_top = 0 dnumdiv_bottom = 0 top_label_col = color.white bottom_label_col = color.white old_pos_divs_can_be_removed = true old_neg_divs_can_be_removed = true startpoint = dontconfirm ? 0 : 1 for x = 0 to 10 by 1 div_type = -1 for y = 0 to 3 by 1 if array.get(all_divergences, x * 4 + y) > 0 div_type := y if y % 2 == 1 dnumdiv_top += 1 top_label_col := array.get(div_colors, y) top_label_col if y % 2 == 0 dnumdiv_bottom += 1 bottom_label_col := array.get(div_colors, y) bottom_label_col if not array.includes(distances, array.get(all_divergences, x * 4 + y)) array.push(distances, array.get(all_divergences, x * 4 + y)) new_line = showlines ? line.new(x1=bar_index - array.get(all_divergences, x * 4 + y), y1=source == 'CLOSE' ? close : y % 2 == 0 ? low : high , x2=bar_index - startpoint, y2=source == 'CLOSE' ? close : y % 2 == 0 ? low : high , color=array.get(div_colors, y), style=y < 2 ? reg_div_l_style : hid_div_l_style, width=y < 2 ? reg_div_l_width : hid_div_l_width) : na if y % 2 == 0 if old_pos_divs_can_be_removed old_pos_divs_can_be_removed := false if not showlast and remove_last_pos_divs delete_last_pos_div_lines_label(last_pos_div_lines) last_pos_div_lines := 0 last_pos_div_lines if showlast delete_old_pos_div_lines() array.push(pos_div_lines, new_line) last_pos_div_lines += 1 remove_last_pos_divs := true remove_last_pos_divs if y % 2 == 1 if old_neg_divs_can_be_removed old_neg_divs_can_be_removed := false if not showlast and remove_last_neg_divs delete_last_neg_div_lines_label(last_neg_div_lines) last_neg_div_lines := 0 last_neg_div_lines if showlast delete_old_neg_div_lines() array.push(neg_div_lines, new_line) last_neg_div_lines += 1 remove_last_neg_divs := true remove_last_neg_divs if y == 0 pos_reg_div_detected := true pos_reg_div_detected if y == 1 neg_reg_div_detected := true neg_reg_div_detected if y == 2 pos_hid_div_detected := true pos_hid_div_detected if y == 3 neg_hid_div_detected := true neg_hid_div_detected if div_type >= 0 divergence_text_top += (div_type % 2 == 1 ? showindis != "DON'T SHOW" ? array.get(indicators_name, x) + '\n' : '' : '') divergence_text_bottom += (div_type % 2 == 0 ? showindis != "DON'T SHOW" ? array.get(indicators_name, x) + '\n' : '' : '') divergence_text_bottom if showindis != "DON'T SHOW" if dnumdiv_top > 0 divergence_text_top += str.tostring(dnumdiv_top) divergence_text_top if dnumdiv_bottom > 0 divergence_text_bottom += str.tostring(dnumdiv_bottom) divergence_text_bottom if divergence_text_top != '' if showlast delete_old_neg_div_labels() array.push(neg_div_labels, label.new(x=bar_index, y=math.max(high, high ), color=top_label_col, style=label.style_diamond, size = size.auto)) if divergence_text_bottom != '' if showlast delete_old_pos_div_labels() array.push(pos_div_labels, label.new(x=bar_index, y=math.min(low, low ), color=bottom_label_col, style=label.style_diamond, size = size.auto)) // POSITION AND SIZE PosTable = input.string(defval="Bottom Right", title="Position", options= , group="Table Location & Size", inline="1") SizTable = input.string(defval="Auto", title="Size", options= , group="Table Location & Size", inline="1") Pos1Table = PosTable == "Top Right" ? position.top_right : PosTable == "Middle Right" ? position.middle_right : PosTable == "Bottom Right" ? position.bottom_right : PosTable == "Top Center" ? position.top_center : PosTable == "Middle Center" ? position.middle_center : PosTable == "Bottom Center" ? position.bottom_center : PosTable == "Top Left" ? position.top_left : PosTable == "Middle Left" ? position.middle_left : position.bottom_left Siz1Table = SizTable == "Auto" ? size.auto : SizTable == "Huge" ? size.huge : SizTable == "Large" ? size.large : SizTable == "Normal" ? size.normal : SizTable == "Small" ? size.small : size.tiny tbl = table.new(Pos1Table, 21, 16, border_width = 1, border_color = color.gray, frame_color = color.gray, frame_width = 1) // Kullanıcı tarafından belirlenecek yeşil ve kırmızı zaman dilimi sayısı greenThreshold = input.int(5, minval=1, maxval=10, title="Yeşil Zaman Dilimi Sayısı", group="Alarm Ayarları") redThreshold = input.int(5, minval=1, maxval=10, title="Kırmızı Zaman Dilimi Sayısı", group="Alarm Ayarları") // TIMEFRAMES OPTIONS box01 = input.bool(true, "TF ", inline = "01", group="Select Timeframe") tf01 = input.timeframe("1", "", inline = "01", group="Select Timeframe") box02 = input.bool(false, "TF ", inline = "02", group="Select Timeframe") tf02 = input.timeframe("3", "", inline = "02", group="Select Timeframe") box03 = input.bool(true, "TF ", inline = "03", group="Select Timeframe") tf03 = input.timeframe("5", "", inline = "03", group="Select Timeframe") box04 = input.bool(true, "TF ", inline = "04", group="Select Timeframe") tf04 = input.timeframe("15", "", inline = "04", group="Select Timeframe") box05 = input.bool(false, "TF ", inline = "05", group="Select Timeframe") tf05 = input.timeframe("30", "", inline = "05", group="Select Timeframe") box06 = input.bool(true, "TF ", inline = "01", group="Select Timeframe") tf06 = input.timeframe("60", "", inline = "01", group="Select Timeframe") box07 = input.bool(false, "TF ", inline = "02", group="Select Timeframe") tf07 = input.timeframe("120", "", inline = "02", group="Select Timeframe") box08 = input.bool(false, "TF ", inline = "03", group="Select Timeframe") tf08 = input.timeframe("180", "", inline = "03", group="Select Timeframe") box09 = input.bool(true, "TF ", inline = "04", group="Select Timeframe") tf09 = input.timeframe("240", "", inline = "04", group="Select Timeframe") box10 = input.bool(false, "TF ", inline = "05", group="Select Timeframe") tf10 = input.timeframe("D", "", inline = "05", group="Select Timeframe") // indicator('Tillson FEMA', overlay=true) length1 = input(1, 'FEMA Length') a1 = input(0.7, 'Volume Factor') e1 = ta.ema((high + low + 2 * close) / 4, length1) e2 = ta.ema(e1, length1) e3 = ta.ema(e2, length1) e4 = ta.ema(e3, length1) e5 = ta.ema(e4, length1) e6 = ta.ema(e5, length1) c1 = -a1 * a1 * a1 c2 = 3 * a1 * a1 + 3 * a1 * a1 * a1 c3 = -6 * a1 * a1 - 3 * a1 - 3 * a1 * a1 * a1 c4 = 1 + 3 * a1 + a1 * a1 * a1 + 3 * a1 * a1 FEMA = c1 * e6 + c2 * e5 + c3 * e4 + c4 * e3 tablocol1 = FEMA > FEMA tablocol3 = FEMA < FEMA color_1 = col1 ? color.rgb(149, 219, 35): col3 ? color.rgb(238, 11, 11) : color.yellow plot(FEMA, color=color_1, linewidth=3, title='FEMA') tilson1 = FEMA tilson1a =FEMA // DEFINITION OF VALUES symbol = ticker.modify(syminfo.tickerid, syminfo.session) tfArr = array.new(na) tilson1Arr = array.new(na) tilson1aArr = array.new(na) // DEFINITIONS OF RSI & CCI FUNCTIONS APPENDED IN THE TIMEFRAME OPTIONS cciNcciFun(tf, flg) => = request.security(symbol, tf, ) if flg and (barstate.isrealtime ? true : timeframe.in_seconds(timeframe.period) <= timeframe.in_seconds(tf)) array.push(tfArr, na(tf) ? timeframe.period : tf) array.push(tilson1Arr, tilson_) array.push(tilson1aArr, tilson1a_) cciNcciFun(tf01, box01), cciNcciFun(tf02, box02), cciNcciFun(tf03, box03), cciNcciFun(tf04, box04), cciNcciFun(tf05, box05), cciNcciFun(tf06, box06), cciNcciFun(tf07, box07), cciNcciFun(tf08, box08), cciNcciFun(tf09, box09), cciNcciFun(tf10, box10) // TABLE AND CELLS CONFIG // Post Timeframe in format tfTxt(x)=> out = x if not str.contains(x, "S") and not str.contains(x, "M") and not str.contains(x, "W") and not str.contains(x, "D") if str.tonumber(x)%60 == 0 out := str.tostring(str.tonumber(x)/60)+"H" else out := x + "m" out if barstate.islast table.clear(tbl, 0, 0, 20, 15) // TITLES table.cell(tbl, 0, 0, "⏱", text_color=color.white, text_size=Siz1Table, bgcolor=#000000) table.cell(tbl, 1, 0, "FEMA("+str.tostring(length1)+")", text_color=#FFFFFF, text_size=Siz1Table, bgcolor=#000000) j = 1 greenCounter = 0 // Yeşil zaman dilimlerini saymak için bir sayaç redCounter = 0 if array.size(tilson1Arr) > 0 for i = 0 to array.size(tilson1Arr) - 1 if not na(array.get(tilson1Arr, i)) //config values in the cells TF_VALUE = array.get(tfArr,i) tilson1VALUE = array.get(tilson1Arr, i) tilson1aVALUE = array.get(tilson1aArr, i) SIGNAL1 = tilson1VALUE >= tilson1aVALUE ? "▲" : tilson1VALUE <= tilson1aVALUE ? "▼" : na // Yeşil oklar ve arka planı ayarla greenArrowColor1 = SIGNAL1 == "▲" ? color.rgb(0, 255, 0) : color.rgb(255, 0, 0) greenBgColor1 = SIGNAL1 == "▲" ? color.rgb(25, 70, 22) : color.rgb(93, 22, 22) allGreen = tilson1VALUE >= tilson1aVALUE allRed = tilson1VALUE <= tilson1aVALUE // Determine background color for time text timeBgColor = allGreen ? #194616 : (allRed ? #5D1616 : #000000) txtColor = allGreen ? #00FF00 : (allRed ? #FF4500 : color.white) if allGreen greenCounter := greenCounter + 1 redCounter := 0 else if allRed redCounter := redCounter + 1 greenCounter := 0 else redCounter := 0 greenCounter := 0 // Dinamik pair değerini oluşturma pair = "USDT_" + syminfo.basecurrency + "USDT" // Bot ID için kullanıcı girişi bot_id = input.int(12387976, title="Bot ID", minval=0,group ='3Comas Message', inline = '1') // Varsayılan değeri 12387976 olan bir tamsayı girişi alır // E-posta tokenı için kullanıcı girişi email_token = input("cd4111d4-549a-4759-a082-e8f45c91fa47", title="Email Token",group ='3Comas Message', inline = '1') // USER INPUT FOR DELAY delay_seconds = input.int(0, title="Delay Seconds", minval=0, maxval=86400,group ='3Comas Message', inline = '1') // Dinamik mesajın oluşturulması message = '{ "message_type": "bot", "bot_id": ' + str.tostring(bot_id) + ', "email_token": "' + email_token + '", "delay_seconds": ' + str.tostring(delay_seconds) + ', "pair": "' + pair + '"}' // Kullanıcının belirlediği yeşil veya kırmızı zaman dilimi sayısına ulaşıldığında alarmı tetikle if greenCounter >= greenThreshold alert(message, alert.freq_once_per_bar_close) // if redCounter >= redThreshold // alert(message, alert.freq_once_per_bar_close) // Kullanıcının belirlediği yeşil veya kırmızı zaman dilimi sayısına ulaşıldığında alarmı tetikle // if greenCounter >= greenThreshold // alert("Yeşil zaman dilimi sayısı " + str.tostring(greenThreshold) + " adede ulaştı", alert.freq_once_per_bar_close) // if redCounter >= redThreshold // alert("Kırmızı zaman dilimi sayısı " + str.tostring(redThreshold) + " adede ulaştı", alert.freq_once_per_bar_close) table.cell(tbl, 0, j, tfTxt(TF_VALUE), text_color=txtColor, text_halign=text.align_left, text_size=Siz1Table, bgcolor=timeBgColor) table.cell(tbl, 1, j, str.tostring(tilson1VALUE, "#.#######")+SIGNAL1, text_color=greenArrowColor1, text_halign=text.align_right, text_size=Siz1Table, bgcolor=greenBgColor1) j += 1 prd = input.int(defval=10, title='Pivot Period', minval=4, maxval=30, group='Setup') ppsrc = input.string(defval='High/Low', title='Source', options= , group='Setup') maxnumpp = input.int(defval=20, title=' Maximum Number of Pivot', minval=5, maxval=100, group='Setup') ChannelW = input.int(defval=10, title='Maximum Channel Width %', minval=1, group='Setup') maxnumsr = input.int(defval=5, title=' Maximum Number of S/R', minval=1, maxval=10, group='Setup') min_strength = input.int(defval=2, title=' Minimum Strength', minval=1, maxval=10, group='Setup') labelloc = input.int(defval=20, title='Label Location', group='Colors', tooltip='Positive numbers reference future bars, negative numbers reference histical bars') linestyle = input.string(defval='Dashed', title='Line Style', options= , group='Colors') linewidth = input.int(defval=2, title='Line Width', minval=1, maxval=4, group='Colors') resistancecolor = input.color(defval=color.red, title='Resistance Color', group='Colors') supportcolor = input.color(defval=color.lime, title='Support Color', group='Colors') showpp = input(false, title='Show Point Points') float src1 = ppsrc == 'High/Low' ? high : math.max(close, open) float src2 = ppsrc == 'High/Low' ? low : math.min(close, open) float ph = ta.pivothigh(src1, prd, prd) float pl = ta.pivotlow(src2, prd, prd) plotshape(ph and showpp, text='H', style=shape.labeldown, color=na, textcolor=color.new(color.red, 0), location=location.abovebar, offset=-prd) plotshape(pl and showpp, text='L', style=shape.labelup, color=na, textcolor=color.new(color.lime, 0), location=location.belowbar, offset=-prd) Lstyle = linestyle == 'Dashed' ? line.style_dashed : linestyle == 'Solid' ? line.style_solid : line.style_dotted //calculate maximum S/R channel zone width prdhighest = ta.highest(300) prdlowest = ta.lowest(300) cwidth = (prdhighest - prdlowest) * ChannelW / 100 var pivotvals = array.new_float(0) if ph or pl array.unshift(pivotvals, ph ? ph : pl) if array.size(pivotvals) > maxnumpp // limit the array size array.pop(pivotvals) get_sr_vals(ind) => float lo = array.get(pivotvals, ind) float hi = lo int numpp = 0 for y = 0 to array.size(pivotvals) - 1 by 1 float cpp = array.get(pivotvals, y) float wdth = cpp <= lo ? hi - cpp : cpp - lo if wdth <= cwidth // fits the max channel width? if cpp <= hi lo := math.min(lo, cpp) else hi := math.max(hi, cpp) numpp += 1 numpp var sr_up_level = array.new_float(0) var sr_dn_level = array.new_float(0) sr_strength = array.new_float(0) find_loc(strength) => ret = array.size(sr_strength) for i = ret > 0 ? array.size(sr_strength) - 1 : na to 0 by 1 if strength <= array.get(sr_strength, i) break ret := i ret ret check_sr(hi, lo, strength) => ret = true for i = 0 to array.size(sr_up_level) > 0 ? array.size(sr_up_level) - 1 : na by 1 //included? if array.get(sr_up_level, i) >= lo and array.get(sr_up_level, i) <= hi or array.get(sr_dn_level, i) >= lo and array.get(sr_dn_level, i) <= hi if strength >= array.get(sr_strength, i) array.remove(sr_strength, i) array.remove(sr_up_level, i) array.remove(sr_dn_level, i) ret else ret := false ret break ret var sr_lines = array.new_line(11, na) var sr_labels = array.new_label(11, na) for x = 1 to 10 by 1 rate = 100 * (label.get_y(array.get(sr_labels, x)) - close) / close label.set_text(array.get(sr_labels, x), text=str.tostring(label.get_y(array.get(sr_labels, x))) + '(' + str.tostring(rate, '#.##') + '%)') label.set_x(array.get(sr_labels, x), x=bar_index + labelloc) label.set_color(array.get(sr_labels, x), color=label.get_y(array.get(sr_labels, x)) >= close ? color.red : color.lime) label.set_textcolor(array.get(sr_labels, x), textcolor=label.get_y(array.get(sr_labels, x)) >= close ? color.white : color.black) label.set_style(array.get(sr_labels, x), style=label.get_y(array.get(sr_labels, x)) >= close ? label.style_label_down : label.style_label_up) line.set_color(array.get(sr_lines, x), color=line.get_y1(array.get(sr_lines, x)) >= close ? resistancecolor : supportcolor) if ph or pl //because of new calculation, remove old S/R levels array.clear(sr_up_level) array.clear(sr_dn_level) array.clear(sr_strength) //find S/R zones for x = 0 to array.size(pivotvals) - 1 by 1 = get_sr_vals(x) if check_sr(hi, lo, strength) loc = find_loc(strength) // if strength is in first maxnumsr sr then insert it to the arrays if loc < maxnumsr and strength >= min_strength array.insert(sr_strength, loc, strength) array.insert(sr_up_level, loc, hi) array.insert(sr_dn_level, loc, lo) // keep size of the arrays = 5 if array.size(sr_strength) > maxnumsr array.pop(sr_strength) array.pop(sr_up_level) array.pop(sr_dn_level) for x = 1 to 10 by 1 line.delete(array.get(sr_lines, x)) label.delete(array.get(sr_labels, x)) for x = 0 to array.size(sr_up_level) > 0 ? array.size(sr_up_level) - 1 : na by 1 float mid = math.round_to_mintick((array.get(sr_up_level, x) + array.get(sr_dn_level, x)) / 2) rate = 100 * (mid - close) / close array.set(sr_labels, x + 1, label.new(x=bar_index + labelloc, y=mid, text=str.tostring(mid) + '(' + str.tostring(rate, '#.##') + '%)', color=mid >= close ? color.red : color.lime, textcolor=mid >= close ? color.white : color.black, style=mid >= close ? label.style_label_down : label.style_label_up)) array.set(sr_lines, x + 1, line.new(x1=bar_index, y1=mid, x2=bar_index - 1, y2=mid, extend=extend.both, color=mid >= close ? resistancecolor : supportcolor, style=Lstyle, width=linewidth)) f_crossed_over() => ret = false for x = 0 to array.size(sr_up_level) > 0 ? array.size(sr_up_level) - 1 : na by 1 float mid = math.round_to_mintick((array.get(sr_up_level, x) + array.get(sr_dn_level, x)) / 2) if close <= mid and close > mid ret := true ret ret f_crossed_under() => ret = false for x = 0 to array.size(sr_up_level) > 0 ? array.size(sr_up_level) - 1 : na by 1 float mid = math.round_to_mintick((array.get(sr_up_level, x) + array.get(sr_dn_level, x)) / 2) if close >= mid and close < mid ret := true ret ret alertcondition(f_crossed_over(), title='Resistance Broken', message='Resistance Broken') alertcondition(f_crossed_under(), title='Support Broken', message='Support Broken')
مؤشر Pine Script®
من ‎KRIPTOFEMA‎
Time-Based Fair Value Gaps (FVG) with Inversions (iFVG)Overview The Time-Based Fair Value Gaps (FVG) with Inversions (iFVG) (ICT/SMT) indicator is a specialized tool designed for traders using Inner Circle Trader (ICT) methodologies. Inspired by LuxAlgo's Fair Value Gap indicator, this script introduces significant enhancements by integrating ICT principles, focusing on precise time-based FVG detection, inversion tracking, and retest signals tailored for institutional trading strategies. Unlike LuxAlgo’s general FVG approach, this indicator filters FVGs within customizable 10-minute windows aligned with ICT’s macro timeframes and incorporates ICT-specific concepts like mitigation, liquidity grabs, and session-based gap prioritization. This tool is optimized for 1–5 minute charts, though probably best for 1 minute charts, identifying bullish and bearish FVGs, tracking their mitigation into inverted FVGs (iFVGs) as key support/resistance zones, and generating retest signals with customizable “Close” or “Wick” confirmation. Features like ATR-based filtering, optional FVG labels, mitigation removal, and session-specific FVG detection (e.g., first FVG in AM/PM sessions) make it a powerful tool for ICT traders. Originality and Improvements While inspired by LuxAlgo’s FVG indicator (credit to LuxAlgo for their foundational work), this script significantly extends the original concept by: 1. Time-Based FVG Detection: Unlike LuxAlgo’s continuous FVG identification, this script filters FVGs within user-defined 10-minute windows each hour (:00–:10, :10–:20, etc.), aligning with ICT’s emphasis on specific periods of institutional activity, such as hourly opens/closes or kill zones (e.g., New York 7:00–11:00 AM EST). This ensures FVGs are relevant to high-probability ICT setups. 2. Session-Specific First FVG Option: A unique feature allows traders to display only the first FVG in ICT-defined AM (9:30–10:00 AM EST) or PM (1:30–2:00 PM EST) sessions, reflecting ICT’s focus on initial market imbalances during key liquidity events. 3. ICT-Driven Mitigation and Inversion Logic: The script tracks FVG mitigation (when price closes through a gap) and converts mitigated FVGs into iFVGs, which serve as ICT-style support/resistance zones. This aligns with ICT’s view that mitigated gaps become critical reversal points, unlike LuxAlgo’s simpler gap display. 4. Customizable Retest Signals: Retest signals for iFVGs are configurable for “Close” (conservative, requiring candle body confirmation) or “Wick” (faster, using highs/lows), catering to ICT traders’ need for precise entry timing during liquidity grabs or Judas swings. 5. ATR Filtering and Mitigation Removal: An optional ATR filter ensures only significant FVGs are displayed, reducing noise, while mitigation removal declutters the chart by removing filled gaps, aligning with ICT’s principle that mitigated gaps lose relevance unless inverted. 6. Timezone and Timeframe Safeguards: A timezone offset setting aligns FVG detection with EST for ICT’s New York-centric strategies, and a timeframe warning alerts users to avoid ≥1-hour charts, ensuring accuracy in time-based filtering. These enhancements make the script a distinct tool that builds on LuxAlgo’s foundation while offering ICT traders a tailored, high-precision solution. How It Works FVG Detection FVGs are identified when a candle’s low is higher than the high of two candles prior (bullish FVG) or a candle’s high is lower than the low of two candles prior (bearish FVG). Detection is restricted to: • User-selected 10-minute windows (e.g., :00–:10, :50–:60) to capture ICT-relevant periods like hourly transitions. • AM/PM session first FVGs (if enabled), focusing on 9:30–10:00 AM or 1:30–2:00 PM EST for key market opens. An optional ATR filter (default: 0.25× ATR) ensures only gaps larger than the threshold are displayed, prioritizing significant imbalances. Mitigation and Inversion When price closes through an FVG (e.g., below a bullish FVG’s bottom), the FVG is mitigated and becomes an iFVG, plotted as a support/resistance zone. iFVGs are critical in ICT for identifying reversal points where institutional orders accumulate. Retest Signals The script generates signals when price retests an iFVG: • Close: Triggers when the candle body confirms the retest (conservative, lower noise). • Wick: Triggers when the candle’s high/low touches the iFVG (faster, higher sensitivity). Signals are visualized with triangular markers (▲ for bullish, ▼ for bearish) and can trigger alerts. Visualization • FVGs: Displayed as colored boxes (green for bullish, red for bearish) with optional “Bull FVG”/“Bear FVG” labels. • iFVGs: Shown as extended boxes with dashed midlines, limited to the user-defined number of recent zones (default: 5). • Mitigation Removal: Mitigated FVGs/iFVGs are removed (if enabled) to keep the chart clean. How to Use Recommended Settings • Timeframe: Use 1–5 minute charts for precision, avoiding ≥1-hour timeframes (a warning label appears if misconfigured). • Time Windows: Enable :00–:10 and :50–:60 for hourly open/close FVGs, or use the “Show only 1st presented FVG” option for AM/PM session focus. • ATR Filter: Keep enabled (multiplier 0.25–0.5) for significant gaps; disable on 1-minute charts for more FVGs during volatility. • Signal Preference: Use “Close” for conservative entries, “Wick” for aggressive setups. • Timezone Offset: Set to -5 for EST (or -4 for EDT) to align with ICT’s New York session. Trading Strategy 1. Macro Timeframes: Focus on New York (7:00–11:00 AM EST) or London (2:00–5:00 AM EST) kill zones for high institutional activity. 2. FVG Entries: Trade bullish FVGs as support in uptrends or bearish FVGs as resistance in downtrends, especially in :00–:10 or :50–:60 windows. 3. iFVG Retests: Enter on retest signals (▲/▼) during liquidity grabs or Judas swings, using “Close” for confirmation or “Wick” for speed. 4. Session FVGs: Use the “Show only 1st presented FVG” option to target the first gap in AM/PM sessions, often tied to ICT’s market maker algorithms. 5. Risk Management: Combine with ICT concepts like order blocks or breaker blocks for confluence, and set stops beyond FVG/iFVG boundaries. Alerts Set alerts for: • “Bullish FVG Detected”/“Bearish FVG Detected”: New FVGs in selected windows. • “Bullish Signal”/“Bearish Signal”: iFVG retest confirmations. Settings Description • Show Last (1–100, default: 5): Number of recent iFVGs to display. Lower values reduce clutter. • Show only 1st presented FVG : Limits FVGs to the first in 9:30–10:00 AM or 1:30–2:00 PM EST sessions (overrides time window checkboxes). • Time Window Checkboxes: Enable/disable FVG detection in 10-minute windows (:00–:10, :10–:20, etc.). All enabled by default. • Signal Preference: “Close” (default) or “Wick” for iFVG retest signals. • Use ATR Filter: Enables ATR-based size filtering (default: true). • ATR Multiplier (0–∞, default: 0.25): Sets FVG size threshold (higher values = larger gaps). • Remove Mitigated FVGs: Removes filled FVGs/iFVGs (default: true). • Show FVG Labels: Displays “Bull FVG”/“Bear FVG” labels (default: true). • Timezone Offset (-12 to 12, default: -5): Aligns time windows with EST. • Colors: Customize bullish (green), bearish (red), and midline (gray) colors. Why Use This Indicator? This indicator empowers ICT traders with a tool that goes beyond generic FVG detection, offering precise, time-filtered gaps and inversion tracking aligned with institutional trading principles. By focusing on ICT’s macro timeframes, session-specific imbalances, and customizable signal logic, it provides a clear edge for scalping, swing trading, or reversal setups in high-liquidity markets.
مؤشر Pine Script®
من ‎BigGuavaTrading‎
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