Trinity CCI Pro PlusWhat It Is
Trinity CCI Pro Plus is an innovative overlay indicator that reimagines the classic Commodity Channel Index (CCI) by plotting its levels directly on the price chart. No more separate oscillator panel—instead, you get dynamic price-based bands and lines for instant momentum insights.
What You See on the Chart
Orange line: The CCI zero line (20-period SMA of typical price, hlc3)—acts as the baseline.
Aqua line: Dynamic upper band at CCI = +100 (overbought threshold).
Purple line: Dynamic lower band at CCI = -100 (oversold threshold).
Optional thick purple line: The extra SMA of CCI (14-period smooth) scaled back to price—serves as a signal line for crossovers.
Optional outer zones: ±200 bands (aqua/purple extensions) for extreme momentum levels, often added as dotted or filled areas to spot blow-off tops/bottoms.
Key Differences from Regular CCI
Standard CCI lives in a lower pane with fixed horizontal lines at +100, 0, and -100, forcing you to split your focus. This version overlays everything on price: the bands curve with market volatility, the zero line becomes a moving average, and the extra SMA/signal line integrates seamlessly for price-action trading. Plus, it naturally supports outer ±200 zones without extra coding, making extremes visually pop.
How Traders Use It
Momentum breakouts: Buy when price closes above the +100 aqua band (or +200 for aggressive entries); sell below -100 purple (or -200).
Mean reversion: Fade touches on the bands—take profits if price rejects the +100/-100 levels, or watch for exhaustion at ±200.
Trend bias: Price above orange zero = bullish filter; below = bearish. Use the extra SMA for confirmation (e.g., price crossing above it signals upside).
Crossover signals: Price vs. the thick purple SMA line—bullish above, bearish below—pairs perfectly with band breaks.
Range trading: Treat ±100 bands as dynamic support/resistance; outer ±200 zones highlight potential breakout setups.
This setup shines in trending markets (e.g., stocks or forex on 1H/daily charts), turning CCI into a one-glance channel system. Start with the defaults, add the ±200 and extra SMA via simple code tweaks, and backtest for your style—it's versatile and reduces screen clutter dramatically.
More Info
The 20 period MA is the original and still the most common setting for CCI, and it is exactly what the creator of the CCI, Donald Lambert, published it in 1980 with these exact parameters:
Length: 20 periods
Constant: 0.015 (to make CCI fall between +100 and –100 about 70–80 % of the time)
Typical Price: hlc3 (or sometimes (high + low + close)/3)
Deviation measure: Mean Deviation (not standard deviation)
So the “Trinity CCI Pro Plus” you are using is 100 % faithful to Lambert’s original design when the length is set to 20.
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Volume Profile DeltaMap [MHA Finverse]Volume Profile DeltaMap with Session Analysis
SHORT DESCRIPTION (for listing)
Advanced Volume Profile indicator with Delta Analysis, Value Area, Volume Nodes, Imbalance Zones, and Multi-Session Profiles. Professional tool for institutional-style volume analysis and market structure understanding.
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DETAILED DESCRIPTION
📊 OVERVIEW
The Volume Profile DeltaMap is a comprehensive institutional-grade indicator that visualizes volume distribution across price levels, revealing where the most significant trading activity occurred. Unlike traditional indicators that plot data over time, Volume Profile analyzes price levels to identify key support/resistance zones, equilibrium areas, and buyer/seller dominance.
This indicator combines multiple advanced features:
- Volume Profile Analysis with customizable bins
- Delta Heat Map showing buyer vs seller pressure
- Value Area (VAH/VAL) calculations
- High/Low Volume Node Detection
- Imbalance Zone Identification
- Multi-Session Profile Separation (Tokyo, London, NY, Sydney)
- Point of Control (POC) highlighting
---
🎯 KEY FEATURES
1. Volume Profile Core
- Divides price range into customizable bins (10-100 levels)
- Accumulates volume at each price level over a lookback period
- Displays volume distribution horizontally on the chart
- Configurable lookback period (default: 200 bars)
2. Delta Analysis & Heat Map
- Delta (Δ) : Measures the difference between buying and selling pressure
- Color-coded visualization :
- Green/Teal = Buyer dominance
- Red/Pink = Seller dominance
- Heat map intensity : Shows volume concentration with gradient colors
- Percentage labels : Displays exact buyer/seller ratios at each level
3. Point of Control (POC)
- Automatically identifies the price level with maximum volume
- Marked with cyan border and volume label
- Acts as a strong magnetic level where price tends to return
- Often serves as major support/resistance
4. Value Area (VAH/VAL)
- Value Area : Price range containing 70% of total volume (configurable 50-90%)
- VAH (Value Area High) : Upper boundary - resistance level
- VAL (Value Area Low) : Lower boundary - support level
- Displayed with dashed lines and labels
- Represents fair value zone where institutional traders are most active
5. Volume Nodes
- HVN (High Volume Nodes) : Areas with ≥80% of maximum volume
- Highlighted in yellow/amber
- Strong support/resistance zones
- Price tends to consolidate here
- LVN (Low Volume Nodes) : Areas with ≤30% of maximum volume
- Highlighted in orange
- Low liquidity gaps
- Price moves quickly through these zones
- Potential breakout areas
6. Imbalance Zones
- Identifies areas with extreme directional bias (≥70% threshold)
- Buy Imbalance : Green overlay - exhaustion of buying pressure
- Sell Imbalance : Red overlay - exhaustion of selling pressure
- Indicates potential reversal or continuation zones
7. Session-Based Analysis
- Session Background Overlay : Color-codes current trading session
- Separate Session Profiles : Creates individual volume profiles for:
- 🇯🇵 Tokyo Session (00:00-09:00)
- 🇬🇧 London Session (07:00-16:00)
- 🇺🇸 New York Session (13:00-22:00)
- 🇦🇺 Sydney Session (21:00-06:00)
- Compare volume patterns across different market sessions
- Identify session-specific support/resistance levels
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⚙️ CONFIGURATION SETTINGS
Basic Settings
- LookBack : Number of bars to analyze (50-500 recommended)
- Bins : Number of price levels (10-100, default: 30)
- Horizontal Offset : Adjust profile position on chart
#### Features Toggle
- Delta Heat Map
- Delta Labels
- Volume Bars (Buy/Sell split)
- POC Line
- Custom colors for positive/negative volume
Advanced Features
- Value Area calculation with adjustable percentage
- Volume Nodes (HVN/LVN) with custom thresholds
- Imbalance Zones with adjustable sensitivity
- Session backgrounds and separate profiles
- Profile spacing for multi-session view
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📈 HOW TO USE THIS INDICATOR
Installation & Setup
1. Add to Chart :
- Search for "Volume Profile DeltaMap"
- Click "Add to favorites" ⭐
- Apply to your chart
2. Recommended Timeframes :
- Scalping : 1-5 minute charts
- Day Trading : 5-15 minute charts
- Swing Trading : 1-4 hour charts
- Position Trading : Daily charts
3. Initial Settings :
- Start with default settings
- For intraday: Set LookBack to 200-400 bars
- For higher timeframes: Use 100-200 bars
4. Enable Session Profiles (Optional):
- Go to Settings → Advanced Features
- Enable "Separate Profiles Per Session"
- Adjust "Profile Spacing" for better visibility
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🔍 READING THE INDICATOR
Understanding the Display
Main Profile Elements:
- Horizontal bars : Length represents volume at that price
- Color gradient : Shows delta (buyer vs seller dominance)
- Bright cyan line : Point of Control (POC) - highest volume
- Green dashed line : Value Area High (VAH)
- Red dashed line : Value Area Low (VAL)
- Yellow highlights : High Volume Nodes (HVN)
- Orange highlights : Low Volume Nodes (LVN)
Volume Bars (if enabled):
- Top half (Red) : Selling volume percentage
- Bottom half (Teal) : Buying volume percentage
Delta Labels:
- Shows Δ percentage
- Positive = More buyers
- Negative = More sellers
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📊 MARKET ANALYSIS & TRADING STRATEGIES
1. Support & Resistance Trading
POC as Key Level:
- Price tends to return to POC (magnetic effect)
- Strategy :
- When price is above POC → Look for pullbacks to POC for long entries
- When price is below POC → Look for rallies to POC for short entries
- POC acts as dynamic support/resistance
Value Area Trading:
- Inside Value Area (between VAH & VAL):
- Market is in balance/equilibrium
- Range-bound trading strategies
- Look for mean reversion
- Outside Value Area :
- Price accepted above VAH = Bullish breakout
- Price accepted below VAL = Bearish breakdown
- Trend-following strategies
Example Setup:
Price above VAH + Strong buying delta = Bullish trend
→ Wait for pullback to VAH
→ Enter long with stop below VAH
→ Target: Next HVN or previous session high
2. Volume Node Trading
High Volume Nodes (HVN):
- Characteristics : Strong support/resistance, consolidation zones
- Trading Strategy :
- Price approaching HVN from above → Potential support
- Price approaching HVN from below → Potential resistance
- Breakout from HVN → Strong momentum move
- Setup : Place limit orders at HVN boundaries
Low Volume Nodes (LVN):
- Characteristics : Low liquidity, fast price movement
- Trading Strategy :
- Price in LVN = Don't chase, wait for next HVN
- LVN breakout = Rapid moves, use wider stops
- Price rejection from LVN = Quick return to HVN
- Setup : Avoid placing stops in LVN zones
Example:
Price consolidating at HVN (yellow) near $50,000
→ Breakout above with volume
→ Fast move through LVN (orange) gap
→ Next target: Upper HVN at $51,500
3. Delta Analysis for Entry Timing
Strong Buying Delta (Green zones):
- Δ > +20% = Buyers in control
- Bullish Signal : Accumulation zone
- Strategy : Look for long entries on pullbacks
- Confirmation : Rising price + positive delta
Strong Selling Delta (Red zones):
- Δ < -20% = Sellers in control
- Bearish Signal : Distribution zone
- Strategy : Look for short entries on rallies
- Confirmation : Falling price + negative delta
Delta Divergence (Advanced):
- Bullish Divergence : Price making lower lows, but delta improving (less negative)
- Indicates selling pressure weakening
- Potential reversal signal
- Bearish Divergence : Price making higher highs, but delta weakening (less positive)
- Indicates buying pressure exhausting
- Potential reversal signal
4. Imbalance Zone Trading
Buy Imbalance (Bright Green):
- 70%+ buying pressure
- Interpretation :
- Potential exhaustion of buyers
- Smart money distribution
- Strategy :
- Look for reversal signals (bearish candles, resistance)
- Take profits on long positions
- Consider short entries with confirmation
Sell Imbalance (Bright Red):
- 70%+ selling pressure
- Interpretation :
- Potential exhaustion of sellers
- Smart money accumulation
- Strategy :
- Look for reversal signals (bullish candles, support)
- Take profits on short positions
- Consider long entries with confirmation
Example:
```
Price at VAH with 80% sell imbalance
→ Selling exhaustion likely
→ Wait for bullish reversal candle
→ Enter long with stop below VAL
```
5. Multi-Session Analysis
When "Separate Profiles Per Session" is enabled:
Session-Specific Levels:
- Each session creates its own POC and value area
- Compare sessions to identify:
- Where institutions accumulated/distributed
- Which levels each session respected
- Unfinished business from previous sessions
Trading Strategies:
A. Session POC Confluence
London POC: $49,500
NY POC: $49,550
→ Strong support zone at $49,500-$49,550
→ High probability long setup on pullback
B. Value Area Overlap
London VAH: $50,000
NY VAL: $49,800
→ Overlap creates strong consolidation zone
→ Breakout strategy: Enter on break above $50,000
C. Unfinished Business
London session rejected $51,000 (sell imbalance)
NY session hasn't tested this level yet
→ Watch for NY session to revisit $51,000
→ Potential reversal zone
D. Session Handoff
Tokyo session: Sideways, low volume
London session: Strong buying delta, break above VAH
NY session: Continuation or reversal?
→ Monitor NY open for direction confirmation
6. Market Profile Analysis
Profile Shape Interpretation:
A. P-Shape (Peak at Top)
- High volume at top of range
- Interpretation : Distribution, potential reversal down
- Strategy : Look for shorts at resistance
B. b-Shape (Peak at Bottom)
- High volume at bottom of range
- Interpretation : Accumulation, potential reversal up
- Strategy : Look for longs at support
C. D-Shape (Peak in Middle)
- Balanced profile, POC in center
- Interpretation : Equilibrium, neutral market
- Strategy : Range trading between VAH/VAL
D. Thin Profile (LVN Gap)
- Low volume throughout
- Interpretation : Trending market, little acceptance
- Strategy : Trend following, avoid counter-trend trades
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🎯 COMPLETE TRADING WORKFLOW
Step 1: Market Structure Analysis
1. Identify overall profile shape
2. Locate POC, VAH, VAL
3. Note HVN and LVN zones
4. Check current price position relative to value area
Step 2: Delta & Imbalance Check
1. Review delta distribution (where are buyers/sellers?)
2. Identify imbalance zones
3. Look for delta divergences
4. Note any exhaustion signals
Step 3: Session Analysis (if enabled)
1. Compare current session vs previous sessions
2. Identify key levels each session created
3. Look for level confluences or gaps
4. Note unfinished business
Step 4: Trade Setup
1. Define your bias (long/short/neutral)
2. Identify entry zone (HVN, VAH/VAL, POC)
3. Set stop loss (below/above key level or opposite LVN)
4. Set target (next HVN, VAH/VAL, or session high/low)
Step 5: Execution & Management
1. Wait for price to reach entry zone
2. Confirm with price action (candlestick patterns)
3. Enter trade with defined risk
4. Move stop to breakeven at first target
5. Trail stop or take profits at resistance/support
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📋 EXAMPLE TRADE SCENARIOS
Scenario 1: Long Setup at VAL
Setup:
- Price pulled back to VAL ($49,200)
- VAL coincides with HVN (yellow zone)
- Delta showing +15% buying (green)
- London session POC also at $49,200
Entry:
- Buy at $49,200 (VAL/HVN confluence)
- Stop loss: $49,000 (below VAL, in LVN)
- Target 1: $49,800 (POC)
- Target 2: $50,200 (VAH)
Management:
- Move stop to breakeven when Target 1 reached
- Trail stop below recent swing lows
- Exit 50% at VAH, let remainder run
Risk:Reward : 200 points risk / 1000 points potential = 1:5 R:R
---
Scenario 2: Short Setup at Sell Imbalance
Setup:
- Price at VAH ($50,500)
- Sell imbalance zone (85% sellers, bright red)
- Bearish divergence (higher high, weaker delta)
- Previous session rejected this level
Entry:
- Short at $50,500 after bearish engulfing candle
- Stop loss: $50,750 (above VAH + imbalance zone)
- Target 1: $50,000 (POC)
- Target 2: $49,600 (VAL)
Management:
- Take 50% profit at POC
- Trail stop above recent swing highs
- Exit remainder at VAL or if delta turns positive
Risk:Reward : 250 points risk / 900 points potential = 1:3.6 R:R
---
Scenario 3: Range Trading Inside Value Area
Setup:
- Market consolidating between VAH ($50,200) and VAL ($49,600)
- POC at $49,900
- Multiple HVNs creating range boundaries
- Delta oscillating between +/-10%
Long Trade:
- Entry: $49,650 (near VAL)
- Stop: $49,500 (below VAL)
- Target: $50,150 (near VAH)
- Risk:Reward: 150/500 = 1:3.3
Short Trade:
- Entry: $50,150 (near VAH)
- Stop: $50,300 (above VAH)
- Target: $49,700 (near VAL)
- Risk:Reward: 150/450 = 1:3
Management:
- Reduce position size in range trading
- Take profits at opposite boundary
- Exit if breakout occurs (stop hunt possible)
---
Scenario 4: Session Breakout Trade
Setup:
- London session: Range-bound $49,500-$50,000
- London VAH at $50,000 (resistance)
- NY session opens: Strong buying delta (+35%)
- Price breaks above $50,000 with momentum
Entry:
- Buy on breakout above $50,000
- Or buy on retest of $50,000 (old resistance = new support)
- Stop loss: $49,700 (below breakout level + buffer)
- Target 1: $50,500 (next HVN from previous day)
- Target 2: $51,000 (measured move)
Management:
- Enter 50% position on breakout
- Add remaining 50% on successful retest
- Move stop to breakeven when price +$300
- Trail stop below 20 EMA or recent higher lows
Risk:Reward : 300 points risk / 1000 points potential = 1:3.3 R:R
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⚠️ BEST PRACTICES & RISK MANAGEMENT
Do's:
✅ Use on liquid markets (major crypto, forex, indices)
✅ Combine with price action and candlestick patterns
✅ Wait for confirmation before entering trades
✅ Always use stop losses based on volume structure
✅ Take partial profits at key levels (HVN, VAH/VAL)
✅ Adjust lookback period based on timeframe
✅ Use higher timeframe profiles for context
✅ Compare current profile with previous day/session
✅ Consider volume trends (increasing/decreasing)
✅ Backtest strategies on your specific market
Don'ts:
❌ Don't trade solely based on this indicator
❌ Don't ignore price action and market context
❌ Don't place stops in LVN zones (prone to spikes)
❌ Don't chase price in low volume areas
❌ Don't overtrade - wait for quality setups
❌ Don't use on extremely low volume/illiquid assets
❌ Don't forget to adjust for different market conditions
❌ Don't ignore fundamental news events
❌ Don't use excessive leverage even with good setups
❌ Don't force trades - patience is key
Risk Management Rules:
1. Risk per trade : Never risk more than 1-2% of capital
2. Position sizing : Based on stop loss distance
3. Stop placement : Always below/above key volume levels
4. Profit taking : Scale out at multiple targets
5. Drawdown limits : Stop trading after 3 consecutive losses
6. Win rate expectation : 50-60% is realistic
7. Risk:Reward minimum : Aim for 1:2 or better
8. Correlation : Don't take correlated positions
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🔧 TROUBLESHOOTING & OPTIMIZATION
If profiles look too compressed:
- Increase "Bins" to 40-50
- Reduce "LookBack" period
- Adjust "Horizontal Offset"
If too cluttered:
- Disable "Delta Labels"
- Disable "Volume Bars"
- Keep only POC and Value Area
- Use "Session Background Overlay" instead of separate profiles
For scalping (1-5 min):
- LookBack: 300-500 bars
- Bins: 20-30
- Enable separate session profiles
- Focus on imbalance zones
For swing trading (1H-4H):
- LookBack: 100-200 bars
- Bins: 25-35
- Focus on VAH/VAL and HVN
- Disable session features
For position trading (Daily):
- LookBack: 50-100 bars
- Bins: 30-40
- Focus on weekly/monthly POC
- Compare with previous week profiles
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📚 ADVANCED CONCEPTS
1. Composite Profiles
- Build profiles across multiple days
- Increase LookBack to 500+ bars on 15-min chart
- Identifies major support/resistance from weeks of data
- Use for swing trading key levels
2. Profile Migration
- Track how POC moves day over day
- Uptrend : POC migrating higher
- Downtrend : POC migrating lower
- Range : POC oscillating in same area
3. Failed Auctions
- Price briefly leaves value area but quickly returns
- Failed auction high : Bearish signal
- Failed auction low : Bullish signal
- Indicates rejection of new price levels
4. Overnight Inventory
- Compare previous day's close to value area
- Close above VAH : Bullish bias for next day
- Close below VAL : Bearish bias for next day
- Close in value area : Neutral, range expected
5. Volume Delta Momentum
- Track cumulative delta across time
- Rising cumulative delta + rising price : Strong trend
- Falling cumulative delta + rising price : Weak/topping
- Rising cumulative delta + falling price : Potential reversal
---
📊 INTEGRATION WITH OTHER INDICATORS
Complementary Indicators:
1. Moving Averages (20/50/200 EMA)
- Use with POC and VAH/VAL
- Confluence with EMAs = stronger levels
2. RSI/Stochastic
- Overbought at resistance (VAH/HVN) = strong short
- Oversold at support (VAL/HVN) = strong long
3. VWAP
- POC often aligns with VWAP
- Deviation from VWAP + Volume Profile = trade setup
4. Order Flow/Footprint Charts
- Confirm delta analysis
- Detailed buyer/seller pressure
5. Market Profile (TPO)
- Similar concept, different visualization
- Use together for complete picture
Example Multi-Indicator Setup:
Price at VAL ✓
+ 200 EMA support ✓
+ RSI oversold (30) ✓
+ Positive delta zone ✓
+ Bullish engulfing candle ✓
= High probability long entry
---
🎓 LEARNING CURVE & PRACTICE
Week 1-2: Understanding
- Study each feature individually
- Identify POC, VAH, VAL on historical charts
- Note HVN and LVN patterns
- Observe how price reacts to these levels
Week 3-4: Pattern Recognition
- Track different profile shapes
- Identify session-specific patterns
- Note delta distribution patterns
- Document imbalance zone outcomes
Week 5-6: Paper Trading
- Take simulated trades based on setups
- Record entry/exit reasoning
- Track win rate and R:R
- Refine strategy based on results
Week 7-8: Live Trading (Small Size)
- Start with minimal position sizes
- Focus on execution and discipline
- Build confidence with real money
- Gradually increase size as proficiency grows
Ongoing:
- Review trades weekly
- Keep trading journal
- Adapt to changing market conditions
- Continuously refine strategy
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💡 KEY TAKEAWAYS
1. Volume Profile shows WHERE the market is most active (POC, HVN)
2. Delta shows WHO is in control (buyers vs sellers)
3. Value Area shows FAIR VALUE (equilibrium zone)
4. Volume Nodes show STRUCTURE (support/resistance)
5. Imbalances show EXHAUSTION (potential reversals)
6. Sessions show PARTICIPATION (institutional activity)
The indicator is a MAP, not a SIGNAL:
- It shows you the battlefield terrain
- You still need to decide when/how to engage
- Combine with price action for best results
- Risk management is always paramount
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⚖️ DISCLAIMER
This indicator is for educational and informational purposes only.
- Not financial advice
- Past performance does not guarantee future results
- Trading involves substantial risk of loss
- Only trade with capital you can afford to lose
- Always do your own research and due diligence
- Test strategies thoroughly before risking real money
- Consider consulting a licensed financial advisor
The creator is not responsible for any trading losses incurred while using this indicator.
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Happy Trading! 📈🚀
Dark Vector ScalpingThe Dark Vector Scalping indicator is a high-frequency trend-following system designed specifically to capture rapid momentum shifts in the market. It combines a staircase-style breakout logic with volatility-adjusted trailing stops to define market direction.
While the underlying math is robust enough for various asset classes, this specific configuration is optimized for scalping operations on 1-minute and 5-minute timeframes. It aims to filter out the "noise" common in lower timeframes while reacting quickly to genuine breakouts.
Core Components
1. The Apex Engine (Staircase Logic) Unlike traditional moving averages that curve with price, this engine uses a "hard" breakout logic. It looks back at a specific number of bars (Sensitivity) to find the highest highs and lowest lows.
Bullish Flip: Occurs when the price closes below the calculated low of the previous trend.
Bearish Flip: Occurs when the price closes above the calculated high of the previous trend.
Trailing Stop: Once a trend is established, a trailing stop line is drawn. This line only moves in the direction of the trend (up for bullish, down for bearish) and never retraces, acting as a ratchet to lock in paper profits.
2. Volatility Normalization To prevent getting stopped out by random market noise (scam wicks), the indicator calculates the Average True Range (ATR). It multiplies this volatility metric by a user-defined deviation factor to determine exactly how far the stop line should be from the current price action.
3. The Hull Moving Average (HMA) Filter The script includes an optional 50-period Hull Moving Average. The HMA is known for being extremely fast and smooth, reducing lag compared to standard moving averages.
Visual Reference: You can plot the line to see the overall macro trend.
Hard Filter: You can enable a "Safety Filter" in the settings. If enabled, the system will only generate Buy signals if the price is above the HMA, and Sell signals if the price is below the HMA.
4. The Dashboard A data panel is located on the chart (customizable position) to provide instant numerical data without needing to calculate levels manually. It displays the current trend state, the exact price of the trailing stop, and the status of the HMA filter.
Settings & Configuration
Sensitivity (Lookback)
Default: 5
This is the primary setting for the Apex Engine. A setting of 5 is the "sweet spot" for 1-minute and 5-minute charts. It allows the system to react very quickly to sudden volume spikes. Increasing this number (e.g., to 10) will make the signals slower and more conservative.
Stop Deviation
Default: 3.0
This controls the "breathing room" for the trade. A value of 3.0 allows for standard volatility on minute charts without triggering a premature exit. Lowering this to 2.0 will result in tighter stops but more false signals.
HMA Filter
Use HMA as Filter? (Default: OFF):
When OFF, the system signals purely on price action breakouts (fastest).
When ON, the system waits for the price to align with the 50-period HMA before signaling (safest, but may delay entry).
How to Interpret Visuals
Candle Colors
Teal/Green: The market is in a Bullish regime.
Red/Pink: The market is in a Bearish regime.
The Line
The solid stepped line represents the hard invalidation point. If price closes beyond this line, the trend is considered over.
Diamond Signals
Light Green Diamond (Below Bar): Confirmed Buy Signal. A new bullish trend has started.
Light Red/Pink Diamond (Above Bar): Confirmed Sell Signal. A new bearish trend has started.
Trading Strategy Guide
The Scalp Entry
Ensure you are on a 1-minute or 5-minute timeframe.
Wait for a signal Diamond to close. Do not enter while the bar is still forming, as the signal may repaint (disappear) if the price retraces before the close.
Long Entry: Enter when a Green Diamond appears and the candle turns Teal.
Short Entry: Enter when a Red Diamond appears and the candle turns Red.
Risk Management
Stop Loss: Your invalidation level is the "Apex Stop" line. You can place your hard stop loss slightly beyond this line.
Take Profit: Because this is a trend-following system, it is often best to hold until the candle color changes, or to take profit at fixed Risk:Reward ratios (e.g., 1:1.5 or 1:2).
The HMA Nuance If you find the market is "choppy" (moving sideways), enable the "Use HMA as Filter" option in the settings. This will force the system to ignore signals that are counter-trend to the longer-term momentum.
Disclaimer
The information provided by the "Dark Vector Scalping" indicator and this accompanying guide is for educational and informational purposes only. It does not constitute financial, investment, or trading advice. Trading cryptocurrencies, stocks, and forex involves a high level of risk and may not be suitable for all investors. You could lose some or all of your initial investment.
Session Opening Range Breakout (ORBO)This strategy automates a classic Opening Range Breakout (ORBO) approach: it builds a price range for the first minutes after the market opens, then looks for strong breakouts above or below that range to catch early directional moves.
Concept
The idea behind ORBO is simple:
The first minutes after the session open are often highly informative.
Price forms an “opening range” that acts as a mini support/resistance zone.
A clean breakout beyond this zone can lead to high-momentum moves.
This script turns that logic into a fully backtestable strategy in TradingView.
How the strategy works
Opening Range Session
Default session: 09:30–09:50 (exchange time)
During this window, the script tracks:
orHigh → highest high within the session
orLow → lowest low within the session
This forms your Opening Range for the day.
Breakout Logic (after the window ends)
Once the defined session ends:
Long Entry:
If the close crosses above the Opening Range High (orHigh),
→ strategy.entry("OR Long", strategy.long) is triggered.
Short Entry:
If the close crosses below the Opening Range Low (orLow),
→ strategy.entry("OR Short", strategy.short) is triggered.
Only one opening range per day is considered, which keeps the logic clean and easy to interpret.
Daily Reset
At the start of a new trading day, the script resets:
orHigh := na
orLow := na
A fresh Opening Range is then built using the next session’s 09:30–09:50 candles.
This ensures entries are always based on today’s structure, not yesterday’s.
Visuals & Inputs
Inputs:
Opening range session → default: "0930-0950"
Show OR levels → toggle visibility of OR High / Low lines
Fill range body → optional shaded zone between OR High and OR Low
Chart visuals:
A green line marks the Opening Range High.
A red line marks the Opening Range Low.
Optional yellow fill highlights the entire OR zone.
Background shading during the session shows when the range is currently being built.
These visuals make it easy to see:
Where the OR sits relative to current price
How clean / noisy the breakout was
How often price respects or rejects the opening zone
Backtesting & Optimization
Because this is written as a strategy():
You can use TradingView’s Strategy Tester to view:
Win rate
Net profit
Drawdown
Profit factor
Equity curve
Ideas to experiment with:
Change the session window (e.g., 09:15–09:45, 10:00–10:30)
Apply to different:
Markets: indices, FX, crypto, stocks
Timeframes: 1m / 5m / 15m
Add your own:
Stop Loss & Take Profit levels
Time filters (only trade certain days / times)
Volatility filters (e.g., ATR, range size thresholds)
Higher-timeframe trend filter (e.g., only take longs above 200 EMA)
Bitcoin Power Law Zones (Dunk)Introduction When viewed on a standard linear chart, Bitcoin’s long-term price action can appear chaotic and exponential. However, when analyzed through the lens of physics and network growth models, a distinct structure emerges.
This indicator implements the Bitcoin Power Law , a mathematical model that suggests Bitcoin’s price evolves in a straight line when plotted against time on a "log-log" scale. By calculating parallel bands around this regression line, we create a "Rainbow" of valuation zones that help investors visualize whether the asset is historically overheated, undervalued, or sitting at fair value.
The Math Behind the Model The Power Law dictates that price scales with time according to the formula: Price = A * (days since genesis)^b
This script uses the specific parameters popularized by recent physics-based analyses of the network: Slope (b): 5.78 (Representing the scaling law of the network adoption). Amplitude (A): 1.45 x 10^-17 (The intercept coefficient).
While simple moving averages react to price, this model is predictive based on time and network growth physics, providing a long-term "gravity" center for the asset.
Guide to the Valuation Zones
Upper Bands (Red/Orange): Extr. Overvalued, High Premium, Overvalued. Historically, these zones have marked cycle peaks where price moved too far, too fast ahead of the network's steady growth. The Baseline (Black Line): Fair Value. The mathematical mean of the Power Law. Price has historically oscillated around this line, treating it as a center of gravity. Lower Bands (Green/Blue): Undervalued, Discount, Deep Discount. These zones represent periods where the market price has historically lagged behind the network's intrinsic value, often marking accumulation phases.
Note: The lowest theoretical tiers ("Bitcoin Dead") have been trimmed from this chart to focus on relevant historical support levels.
How to Use Logarithmic Scale: You MUST set your chart to "Log" scale (bottom right of the TradingView window) for this indicator to function correctly. On a linear chart, the bands will appear to curve upwards aggressively; on a Log chart, they will appear as smooth, parallel channels. Timeframe: This is a macro-economic indicator. It is best viewed on Daily or Weekly timeframes. Overlay Labels: The indicator includes dynamic labels on the right-side axis, allowing you to instantly see the current price requirements for each valuation zone without manually tracing lines.
Credits This script is based on the Power Law theory popularized by Giovanni Santostasi and the original Corridor concepts by Harold Christopher Burger .
Disclaimer This tool is for educational and informational purposes only. It visualizes historical mathematical trends and does not constitute financial advice. Past performance of a model is not indicative of future results.
Further Reading
www.hcburger.com
giovannisantostasi.medium.com
ADX Forecast Colorful [DiFlip]ADX Forecast Colorful
Introducing one of the most advanced ADX indicators available — a fully customizable analytical tool that integrates forward-looking forecasting capabilities. ADX Forecast Colorful is a scientific evolution of the classic ADX, designed to anticipate future trend strength using linear regression. Instead of merely reacting to historical data, this indicator projects the future behavior of the ADX, giving traders a strategic edge in trend analysis.
⯁ Real-Time ADX Forecasting
For the first time, a public ADX indicator incorporates linear regression (least squares method) to forecast the future behavior of ADX. This breakthrough approach enables traders to anticipate trend strength changes based on historical momentum. By applying linear regression to the ADX, the indicator plots a projected trendline n periods ahead — helping users make more accurate and timely trading decisions.
⯁ Highly Customizable
The indicator adapts seamlessly to any trading style. It offers a total of 26 long entry conditions and 26 short entry conditions, making it one of the most configurable ADX tools on TradingView. Each condition is fully adjustable, enabling the creation of statistical, quantitative, and automated strategies. You maintain full control over the signals to align perfectly with your system.
⯁ Innovative and Science-Based
This is the first public ADX indicator to apply least-squares predictive modeling to ADX dynamics. Technically, it embeds machine learning logic into a traditional trend-strength indicator. Using linear regression as a predictive engine adds powerful statistical rigor to the ADX, turning it into an intelligent, forward-looking signal generator.
⯁ Scientific Foundation: Linear Regression
Linear regression is a fundamental method in statistics and machine learning used to model the relationship between a dependent variable y and one or more independent variables x. The basic formula for simple linear regression is:
y = β₀ + β₁x + ε
Where:
y = predicted value (e.g., future ADX)
x = explanatory variable (e.g., bar index or time)
β₀ = intercept
β₁ = slope (rate of change)
ε = random error term
The goal is to estimate β₀ and β₁ by minimizing the sum of squared errors. This is achieved using the least squares method, ensuring the best linear fit to historical data. Once the coefficients are calculated, the model extends the regression line forward, generating the ADX projection based on recent trends.
⯁ Least Squares Estimation
To minimize the error, the regression coefficients are calculated as:
β₁ = Σ((xᵢ - x̄)(yᵢ - ȳ)) / Σ((xᵢ - x̄)²)
β₀ = ȳ - β₁x̄
Where:
Σ = summation
x̄ and ȳ = means of x and y
i ranges from 1 to n (number of data points)
These formulas provide the best linear unbiased estimator under Gauss-Markov conditions — assuming constant variance and linearity.
⯁ Linear Regression in Machine Learning
Linear regression is a foundational algorithm in supervised learning. Its power in producing quantitative predictions makes it essential in AI systems, predictive analytics, time-series forecasting, and automated trading. Applying it to the ADX essentially places an intelligent forecasting engine inside a classic trend tool.
⯁ Visual Interpretation
Imagine an ADX time series like this:
Time →
ADX →
The regression line smooths these values and projects them n periods forward, creating a predictive trajectory. This forecasted ADX line can intersect with the actual ADX, offering smarter buy and sell signals.
⯁ Summary of Scientific Concepts
Linear Regression: Models variable relationships with a straight line.
Least Squares: Minimizes prediction errors for best fit.
Time-Series Forecasting: Predicts future values using historical data.
Supervised Learning: Trains models to predict outcomes from inputs.
Statistical Smoothing: Reduces noise and highlights underlying trends.
⯁ Why This Indicator Is Revolutionary
Scientifically grounded: Based on rigorous statistical theory.
Unprecedented: First public ADX using least-squares forecast modeling.
Smart: Uses machine learning logic.
Forward-Looking: Generates predictive, not just reactive, signals.
Customizable: Flexible for any strategy or timeframe.
⯁ Conclusion
By merging ADX and linear regression, this indicator enables traders to predict market momentum rather than merely follow it. ADX Forecast Colorful is not just another indicator — it’s a scientific leap forward in technical analysis. With 26 fully configurable entry conditions and smart forecasting, this open-source tool is built for creating cutting-edge quantitative strategies.
⯁ Example of simple linear regression with one independent variable
This example demonstrates how a basic linear regression works when there is only one independent variable influencing the dependent variable. This type of model is used to identify a direct relationship between two variables.
⯁ In linear regression, observations (red) are considered the result of random deviations (green) from an underlying relationship (blue) between a dependent variable (y) and an independent variable (x)
This concept illustrates that sampled data points rarely align perfectly with the true trend line. Instead, each observed point represents the combination of the true underlying relationship and a random error component.
⯁ Visualizing heteroscedasticity in a scatterplot with 100 random fitted values using Matlab
Heteroscedasticity occurs when the variance of the errors is not constant across the range of fitted values. This visualization highlights how the spread of data can change unpredictably, which is an important factor in evaluating the validity of regression models.
⯁ The datasets in Anscombe’s quartet were designed to have nearly the same linear regression line (as well as nearly identical means, standard deviations, and correlations) but look very different when plotted
This classic example shows that summary statistics alone can be misleading. Even with identical numerical metrics, the datasets display completely different patterns, emphasizing the importance of visual inspection when interpreting a model.
⯁ Result of fitting a set of data points with a quadratic function
This example illustrates how a second-degree polynomial model can better fit certain datasets that do not follow a linear trend. The resulting curve reflects the true shape of the data more accurately than a straight line.
⯁ What is the ADX?
The Average Directional Index (ADX) is a technical analysis indicator developed by J. Welles Wilder. It measures the strength of a trend in a market, regardless of whether the trend is up or down.
The ADX is an integral part of the Directional Movement System, which also includes the Plus Directional Indicator (+DI) and the Minus Directional Indicator (-DI). By combining these components, the ADX provides a comprehensive view of market trend strength.
⯁ How to use the ADX?
The ADX is calculated based on the moving average of the price range expansion over a specified period (usually 14 periods). It is plotted on a scale from 0 to 100 and has three main zones:
Strong Trend: When the ADX is above 25, indicating a strong trend.
Weak Trend: When the ADX is below 20, indicating a weak or non-existent trend.
Neutral Zone: Between 20 and 25, where the trend strength is unclear.
⯁ Entry Conditions
Each condition below is fully configurable and can be combined to build precise trading logic.
📈 BUY
🅰️ Signal Validity: The signal will remain valid for X bars .
🅰️ Signal Sequence: Configurable as AND or OR .
🅰️ +DI > -DI
🅰️ +DI < -DI
🅰️ +DI > ADX
🅰️ +DI < ADX
🅰️ -DI > ADX
🅰️ -DI < ADX
🅰️ ADX > Threshold
🅰️ ADX < Threshold
🅰️ +DI > Threshold
🅰️ +DI < Threshold
🅰️ -DI > Threshold
🅰️ -DI < Threshold
🅰️ +DI (Crossover) -DI
🅰️ +DI (Crossunder) -DI
🅰️ +DI (Crossover) ADX
🅰️ +DI (Crossunder) ADX
🅰️ +DI (Crossover) Threshold
🅰️ +DI (Crossunder) Threshold
🅰️ -DI (Crossover) ADX
🅰️ -DI (Crossunder) ADX
🅰️ -DI (Crossover) Threshold
🅰️ -DI (Crossunder) Threshold
🔮 +DI (Crossover) -DI Forecast
🔮 +DI (Crossunder) -DI Forecast
🔮 ADX (Crossover) +DI Forecast
🔮 ADX (Crossunder) +DI Forecast
📉 SELL
🅰️ Signal Validity: The signal will remain valid for X bars .
🅰️ Signal Sequence: Configurable as AND or OR .
🅰️ +DI > -DI
🅰️ +DI < -DI
🅰️ +DI > ADX
🅰️ +DI < ADX
🅰️ -DI > ADX
🅰️ -DI < ADX
🅰️ ADX > Threshold
🅰️ ADX < Threshold
🅰️ +DI > Threshold
🅰️ +DI < Threshold
🅰️ -DI > Threshold
🅰️ -DI < Threshold
🅰️ +DI (Crossover) -DI
🅰️ +DI (Crossunder) -DI
🅰️ +DI (Crossover) ADX
🅰️ +DI (Crossunder) ADX
🅰️ +DI (Crossover) Threshold
🅰️ +DI (Crossunder) Threshold
🅰️ -DI (Crossover) ADX
🅰️ -DI (Crossunder) ADX
🅰️ -DI (Crossover) Threshold
🅰️ -DI (Crossunder) Threshold
🔮 +DI (Crossover) -DI Forecast
🔮 +DI (Crossunder) -DI Forecast
🔮 ADX (Crossover) +DI Forecast
🔮 ADX (Crossunder) +DI Forecast
🤖 Automation
All BUY and SELL conditions are compatible with TradingView alerts, making them ideal for fully or semi-automated systems.
⯁ Unique Features
Linear Regression: (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Plot Labels in the Graph Above: BUY/SELL
Automate and Monitor Signals/Alerts: BUY/SELL
Background Colors: "bgcolor"
Background Colors: "fill"
Linear Regression (Forecast)
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Table of Conditions: BUY/SELL
Conditions Label: BUY/SELL
Plot Labels in the graph above: BUY/SELL
Automate & Monitor Signals/Alerts: BUY/SELL
Background Colors: "bgcolor"
Background Colors: "fill"
Elite Federal Reserve AIThe Elite Federal Reserve AI indicator provides an analytical framework focused on monitoring economic and market conditions that influence Federal Reserve policy decisions. The indicator examines key relationships and rate-of-change metrics across multiple proxies for monetary policy drivers.
The indicator tracks and analyzes:
• Yield curve dynamics through rate-of-change measurements in short and intermediate-term Treasury yields
• Inflation expectations via TIPS breakeven rate momentum
• Dollar strength and its rate of change over specified periods
• Financial market stress indicators including volatility and sector performance metrics
• Breadth measures through small capitalization stock performance
The indicator calculates momentum and rate-of-change values across these variables to identify shifts in the economic and financial conditions that serve as primary inputs to Federal Reserve decision-making. By monitoring the velocity of change in these key relationships, the indicator provides insight into the changing balance between inflationary pressures, growth expectations, financial stability concerns, and currency dynamics.
This approach focuses on the observable market-based indicators that reflect the underlying economic conditions the Federal Reserve considers in its policy formulation, enabling users to assess the prevailing policy environment through the lens of these critical market relationships and their momentum characteristics.
Price Channel Strategy (Short Only)Please follow my x account to get more info:@CTF_bule_lotus
1. Core Logic: Price Channel Breakout (Downside)
The strategy uses one structural signal:
Lowest Low of the past 20 bars.
When the market breaks below this 20-bar low, a stop entry is triggered to open a short position.
Key design principles:
No prediction
No attempt to call tops
Pure reaction to market-confirmed downward momentum
This makes the strategy a clean representation of short-term downside inertia.
2. Directional Constraint: Short Only
This version trades only short positions, with no long exposure.
Rationale:
To isolate and study ETH’s microstructure during downside moves
To avoid noise from symmetric long/short signal conflicts
To treat this model as part of a controlled long–short comparative study
By eliminating long trades, the strategy provides clearer insight into bearish breakout behavior.
3. Risk Management: Fixed TP / SL
Immediately after entry, two fixed exit conditions are defined:
Take Profit: +10 price units
Stop Loss: –10 price units
Both values automatically convert into tick units using syminfo.mintick.
This reflects a classic scalping pattern:
Small but frequent profits
Fast stop-outs
High turnover
Sensitivity to short bursts of momentum
Such fixed exits are useful for analyzing whether short-lived selloffs contain exploitable structure.
4. Transaction Costs
For this specific analysis, transaction fees are intentionally excluded.
This allows:
A clearer view of the raw statistical edge
Isolation of pure signal behavior
Direct comparison with fee-inclusive results in prior tests
The fee-free backtest highlights the “theoretical edge” before real-market frictions are applied.
5. Data & Testing Window (2016–2025)
The model is tested on the complete ETH dataset from 2016 to 2025, without subjective filtering:
No removal of black swan events
No skipping flash crashes
No curve-fitting on sub-periods
This ensures the results reflect ETH’s full structural history, both stable and chaotic.
6. Interpretation & Research Value
This strategy is not presented as a predictive or production-ready trading system.
Its value lies in research utility:
Understanding ETH’s short-term downward momentum
Validating breakout-based scalping structures
Generating baseline data for more complex models
Supporting long-only vs. short-only comparative system design
Removing fees helps quantify the signal strength itself, while fee-inclusive tests can later show how much of that edge survives realistic trading conditions.
RSI Forecast Colorful [DiFlip]RSI Forecast Colorful
Introducing one of the most complete RSI indicators available — a highly customizable analytical tool that integrates advanced prediction capabilities. RSI Forecast Colorful is an evolution of the classic RSI, designed to anticipate potential future RSI movements using linear regression. Instead of simply reacting to historical data, this indicator provides a statistical projection of the RSI’s future behavior, offering a forward-looking view of market conditions.
⯁ Real-Time RSI Forecasting
For the first time, a public RSI indicator integrates linear regression (least squares method) to forecast the RSI’s future behavior. This innovative approach allows traders to anticipate market movements based on historical trends. By applying Linear Regression to the RSI, the indicator displays a projected trendline n periods ahead, helping traders make more informed buy or sell decisions.
⯁ Highly Customizable
The indicator is fully adaptable to any trading style. Dozens of parameters can be optimized to match your system. All 28 long and short entry conditions are selectable and configurable, allowing the construction of quantitative, statistical, and automated trading models. Full control over signals ensures precise alignment with your strategy.
⯁ Innovative and Science-Based
This is the first public RSI indicator to apply least-squares predictive modeling to RSI calculations. Technically, it incorporates machine-learning logic into a classic indicator. Using Linear Regression embeds strong statistical foundations into RSI forecasting, making this tool especially valuable for traders seeking quantitative and analytical advantages.
⯁ Scientific Foundation: Linear Regression
Linear regression is a fundamental statistical method that models the relationship between a dependent variable y and one or more independent variables x. The general formula for simple linear regression is:
y = β₀ + β₁x + ε
where:
y = predicted variable (e.g., future RSI value)
x = explanatory variable (e.g., bar index or time)
β₀ = intercept (value of y when x = 0)
β₁ = slope (rate of change of y relative to x)
ε = random error term
The goal is to estimate β₀ and β₁ by minimizing the sum of squared errors. This is achieved using the least squares method, ensuring the best linear fit to historical data. Once the coefficients are calculated, the model extends the regression line forward, generating the RSI projection based on recent trends.
⯁ Least Squares Estimation
To minimize the error between predicted and observed values, we use the formulas:
β₁ = Σ((xᵢ - x̄)(yᵢ - ȳ)) / Σ((xᵢ - x̄)²)
β₀ = ȳ - β₁x̄
Σ denotes summation; x̄ and ȳ are the means of x and y; and i ranges from 1 to n (number of observations). These equations produce the best linear unbiased estimator under the Gauss–Markov assumptions — constant variance (homoscedasticity) and a linear relationship between variables.
⯁ Linear Regression in Machine Learning
Linear regression is a foundational component of supervised learning. Its simplicity and precision in numerical prediction make it essential in AI, predictive algorithms, and time-series forecasting. Applying regression to RSI is akin to embedding artificial intelligence inside a classic indicator, adding a new analytical dimension.
⯁ Visual Interpretation
Imagine a time series of RSI values like this:
Time →
RSI →
The regression line smooths these historical values and projects itself n periods forward, creating a predictive trajectory. This projected RSI line can cross the actual RSI, generating sophisticated entry and exit signals. In summary, the RSI Forecast Colorful indicator provides both the current RSI and the forecasted RSI, allowing comparison between past and future trend behavior.
⯁ Summary of Scientific Concepts Used
Linear Regression: Models relationships between variables using a straight line.
Least Squares: Minimizes squared prediction errors for optimal fit.
Time-Series Forecasting: Predicts future values from historical patterns.
Supervised Learning: Predictive modeling based on known output values.
Statistical Smoothing: Reduces noise to highlight underlying trends.
⯁ Why This Indicator Is Revolutionary
Scientifically grounded: Built on statistical and mathematical theory.
First of its kind: The first public RSI with least-squares predictive modeling.
Intelligent: Incorporates machine-learning logic into RSI interpretation.
Forward-looking: Generates predictive, not just reactive, signals.
Customizable: Exceptionally flexible for any strategic framework.
⯁ Conclusion
By combining RSI and linear regression, the RSI Forecast Colorful allows traders to predict market momentum rather than simply follow it. It's not just another indicator: it's a scientific advancement in technical analysis technology. Offering 28 configurable entry conditions and advanced signals, this open-source indicator paves the way for innovative quantitative systems.
⯁ Example of simple linear regression with one independent variable
This example demonstrates how a basic linear regression works when there is only one independent variable influencing the dependent variable. This type of model is used to identify a direct relationship between two variables.
⯁ In linear regression, observations (red) are considered the result of random deviations (green) from an underlying relationship (blue) between a dependent variable (y) and an independent variable (x)
This concept illustrates that sampled data points rarely align perfectly with the true trend line. Instead, each observed point represents the combination of the true underlying relationship and a random error component.
⯁ Visualizing heteroscedasticity in a scatterplot with 100 random fitted values using Matlab
Heteroscedasticity occurs when the variance of the errors is not constant across the range of fitted values. This visualization highlights how the spread of data can change unpredictably, which is an important factor in evaluating the validity of regression models.
⯁ The datasets in Anscombe’s quartet were designed to have nearly the same linear regression line (as well as nearly identical means, standard deviations, and correlations) but look very different when plotted
This classic example shows that summary statistics alone can be misleading. Even with identical numerical metrics, the datasets display completely different patterns, emphasizing the importance of visual inspection when interpreting a model.
⯁ Result of fitting a set of data points with a quadratic function
This example illustrates how a second-degree polynomial model can better fit certain datasets that do not follow a linear trend. The resulting curve reflects the true shape of the data more accurately than a straight line.
⯁ What Is RSI?
The RSI (Relative Strength Index) is a technical indicator developed by J. Welles Wilder. It measures the velocity and magnitude of recent price movements to identify overbought and oversold conditions. The RSI ranges from 0 to 100 and is commonly used to identify potential reversals and evaluate trend strength.
⯁ How RSI Works
RSI is calculated from average gains and losses over a set period (commonly 14 bars) and plotted on a 0–100 scale. It consists of three key zones:
Overbought: RSI above 70 may signal an overbought market.
Oversold: RSI below 30 may signal an oversold market.
Neutral Zone: RSI between 30 and 70, indicating no extreme condition.
These zones help identify potential price reversals and confirm trend strength.
⯁ Entry Conditions
All conditions below are fully customizable and allow detailed control over entry signal creation.
📈 BUY
🧲 Signal Validity: Signal remains valid for X bars.
🧲 Signal Logic: Configurable using AND or OR.
🧲 RSI > Upper
🧲 RSI < Upper
🧲 RSI > Lower
🧲 RSI < Lower
🧲 RSI > Middle
🧲 RSI < Middle
🧲 RSI > MA
🧲 RSI < MA
🧲 MA > Upper
🧲 MA < Upper
🧲 MA > Lower
🧲 MA < Lower
🧲 RSI (Crossover) Upper
🧲 RSI (Crossunder) Upper
🧲 RSI (Crossover) Lower
🧲 RSI (Crossunder) Lower
🧲 RSI (Crossover) Middle
🧲 RSI (Crossunder) Middle
🧲 RSI (Crossover) MA
🧲 RSI (Crossunder) MA
🧲 MA (Crossover)Upper
🧲 MA (Crossunder)Upper
🧲 MA (Crossover) Lower
🧲 MA (Crossunder) Lower
🧲 RSI Bullish Divergence
🧲 RSI Bearish Divergence
🔮 RSI (Crossover) Forecast MA
🔮 RSI (Crossunder) Forecast MA
📉 SELL
🧲 Signal Validity: Signal remains valid for X bars.
🧲 Signal Logic: Configurable using AND or OR.
🧲 RSI > Upper
🧲 RSI < Upper
🧲 RSI > Lower
🧲 RSI < Lower
🧲 RSI > Middle
🧲 RSI < Middle
🧲 RSI > MA
🧲 RSI < MA
🧲 MA > Upper
🧲 MA < Upper
🧲 MA > Lower
🧲 MA < Lower
🧲 RSI (Crossover) Upper
🧲 RSI (Crossunder) Upper
🧲 RSI (Crossover) Lower
🧲 RSI (Crossunder) Lower
🧲 RSI (Crossover) Middle
🧲 RSI (Crossunder) Middle
🧲 RSI (Crossover) MA
🧲 RSI (Crossunder) MA
🧲 MA (Crossover)Upper
🧲 MA (Crossunder)Upper
🧲 MA (Crossover) Lower
🧲 MA (Crossunder) Lower
🧲 RSI Bullish Divergence
🧲 RSI Bearish Divergence
🔮 RSI (Crossover) Forecast MA
🔮 RSI (Crossunder) Forecast MA
🤖 Automation
All BUY and SELL conditions can be automated using TradingView alerts. Every configurable condition can trigger alerts suitable for fully automated or semi-automated strategies.
⯁ Unique Features
Linear Regression Forecast
Signal Validity: Keep signals active for X bars
Signal Logic: AND/OR configuration
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Chart Labels: BUY/SELL markers above price
Automation & Alerts: BUY/SELL
Background Colors: bgcolor
Fill Colors: fill
Linear Regression Forecast
Signal Validity: Keep signals active for X bars
Signal Logic: AND/OR configuration
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Chart Labels: BUY/SELL markers above price
Automation & Alerts: BUY/SELL
Background Colors: bgcolor
Fill Colors: fill
ATR Based TMA Bands [NeuraAlgo]ATR-Based TMA Bands
ATR-Based TMA Bands is a volatility-adaptive channel system built around a smoothed Triangular Moving Average (TMA).
It identifies trend direction, momentum shifts, and reversal opportunities using a combination of TMA structure and ATR-driven channel expansion.
Perfect for traders who want a clean, intelligent, and adaptive market framework.
Made by NeuraAlgo.
🔷 How It Works
1. 🔹 TMA Midline (Core Trend)
The indicator builds a smooth and stable midline using:
📐 Triangular Moving Average
🔄 Additional EMA smoothing
This creates a low-noise trend curve that reacts cleanly to real momentum changes.
2. 📈 Volatility-Adjusted Bands
The channels are built from:
📊 Standard Deviation × Expansion Multiplier
📏 Three ATR-based outer layers
These bands:
Expand in high volatility
Contract in stable markets
Reveal pullbacks, breakout zones, and exhaustion points
3. 🔁 Trend Tilt Algorithm
Slope is measured using an ATR-normalized tilt formula:
atrBase = ta.atr(smoothLen)
tilt = (midline - midline ) / (0.1 * atrBase)
This classifies the trend into:
Bullish
Bearish
Neutral
The bar colors and midline adjust automatically to match market direction.
4. 🔄 Reversal Detection (Turn Signals)
The indicator flags directional flips:
Turn Up → bearish → bullish shift
Turn Down → bullish → bearish shift
These are early reversal alerts ideal for swing traders.
5. 🎯 Flip Buy / Flip Sell Signals
Deep volatility extensions create high-probability re-entry zones:
Flip Buy → price rebounds from oversold ATR zone
Flip Sell → price rejects from overbought ATR zone
Great for:
Mean-reversion entries
Trend re-tests
Pullback trades
Exhaustion signals
📌 How to Use This Indicator
✔ Trend Trading
Follow trend using tilt-colored candles
Use midline as dynamic trend filter
Use channels for breakout/pullback entries
✔ Reversal Trading
Watch for Turn Up / Turn Down labels
Flip signals show where the market is over-stretched
✔ Risk Management
ATR channels automatically adjust to volatility
Helps with smarter SL/TP placement
⭐ Best For
Trend traders
Swing traders
Reversal hunters
Volatility lovers
Anyone wanting a smart, clean technical framework
💡 Core Features
TMA-smoothed trend detection
Multi-layer ATR expansion channels
Intelligent trend tilt algorithm
Turn Up / Turn Down reversal markers
Flip Buy / Flip Sell exhaustion signals
Adaptive bar coloring
Clean and professional visual design
Third eye • StrategyThird eye • Strategy – User Guide
1. Idea & Concept
Third eye • Strategy combines three things into one system:
Ichimoku Cloud – to define market regime and support/resistance.
Moving Average (trend filter) – to trade only in the dominant direction.
CCI (Commodity Channel Index) – to generate precise entry signals on momentum breakouts.
The script is a strategy, not an indicator: it can backtest entries, exits, SL, TP and BreakEven logic automatically.
2. Indicators Used
2.1 Ichimoku
Standard Ichimoku settings (by default 9/26/52/26) are used:
Conversion Line (Tenkan-sen)
Base Line (Kijun-sen)
Leading Span A & B (Kumo Cloud)
Lagging Span is calculated but hidden from the chart (for visual simplicity).
From the cloud we derive:
kumoTop – top of the cloud under current price.
kumoBottom – bottom of the cloud under current price.
Flags:
is_above_kumo – price above the cloud.
is_below_kumo – price below the cloud.
is_in_kumo – price inside the cloud.
These conditions are used as trend / regime filters and for stop-loss & trailing stops.
2.2 Moving Average
You can optionally display and use a trend MA:
Types: SMA, EMA, DEMA, WMA
Length: configurable (default 200)
Source: default close
Filter idea:
If MA Direction Filter is ON:
When Close > MA → strategy allows only Long signals.
When Close < MA → strategy allows only Short signals.
The MA is plotted on the chart (if enabled).
2.3 CCI & Panel
The CCI (Commodity Channel Index) is used for entry timing:
CCI length and source are configurable (default length 20, source hlc3).
Two thresholds:
CCI Upper Threshold (Long) – default +100
CCI Lower Threshold (Short) – default –100
Signals:
Long signal:
CCI crosses up through the upper threshold
cci_val < upper_threshold and cci_val > upper_threshold
Short signal:
CCI crosses down through the lower threshold
cci_val > lower_threshold and cci_val < lower_threshold
There is a panel (table) in the bottom-right corner:
Shows current CCI value.
Shows filter status as colored dots:
Green = filter enabled and passed.
Red = filter enabled and blocking trades.
Gray = filter is disabled.
Filters shown in the panel:
Ichimoku Cloud filter (Long/Short)
Ichimoku Lines filter (Conversion/Base vs Cloud)
MA Direction filter
3. Filters & Trade Direction
All filters can be turned ON/OFF independently.
3.1 Ichimoku Cloud Filter
Purpose: trade only when price is clearly above or below the Kumo.
Long Cloud Filter (Use Ichimoku Cloud Filter) – when enabled:
Long trades only if close > cloud top.
Short Cloud Filter – when enabled:
Short trades only if close < cloud bottom.
If the cloud filter is disabled, this condition is ignored.
3.2 Ichimoku Lines Above/Below Cloud
Purpose: stronger trend confirmation: Ichimoku lines should also be on the “correct” side of the cloud.
Long Lines Filter:
Long allowed only if Conversion Line and Base Line are both above the cloud.
Short Lines Filter:
Short allowed only if both lines are below the cloud.
If this filter is OFF, the conditions are not checked.
3.3 MA Direction Filter
As described above:
When ON:
Close > MA → only Longs.
Close < MA → only Shorts.
4. Anti-Re-Entry Logic (Cloud Touch Reset)
The strategy uses internal flags to avoid continuous re-entries in the same direction without a reset.
Two flags:
allowLong
allowShort
After a Long entry, allowLong is set to false, allowShort to true.
After a Short entry, allowShort is set to false, allowLong to true.
Flags are reset when price touches the Kumo:
If Low goes into the cloud → allowLong = true
If High goes into the cloud → allowShort = true
If Close is inside the cloud → both allowLong and allowShort are set to true
There is a key option:
Wait Position Close Before Flag Reset
If ON: cloud touch will reset flags only when there is no open position.
If OFF: flags can be reset even while a trade is open.
This gives a kind of regime-based re-entry control: after a trend leg, you wait for a “cloud interaction” to allow new signals.
5. Risk Management
All risk management is handled inside the strategy.
5.1 Position Sizing
Order Size % of Equity – default 10%
The strategy calculates:
position_value = equity * (Order Size % / 100)
position_qty = position_value / close
So position size automatically adapts to your current equity.
5.2 Take Profit Modes
You can choose one of two TP modes:
Percent
Fibonacci
5.2.1 Percent Mode
Single Take Profit at X% from entry (default 2%).
For Long:
TP = entry_price * (1 + tp_pct / 100)
For Short:
TP = entry_price * (1 - tp_pct / 100)
One strategy.exit per side is used: "Long TP/SL" and "Short TP/SL".
5.2.2 Fibonacci Mode (2 partial TPs)
In this mode, TP levels are based on a virtual Fib-style extension between entry and stop-loss.
Inputs:
Fib TP1 Level (default 1.618)
Fib TP2 Level (default 2.5)
TP1 Share % (Fib) (default 50%)
TP2 share is automatically 100% - TP1 share.
Process for Long:
Compute a reference Stop (see SL section below) → sl_for_fib.
Compute distance: dist = entry_price - sl_for_fib.
TP levels:
TP1 = entry_price + dist * (Fib TP1 Level - 1)
TP2 = entry_price + dist * (Fib TP2 Level - 1)
For Short, the logic is mirrored.
Two exits are used:
TP1 – closes TP1 share % of position.
TP2 – closes remaining TP2 share %.
Same stop is used for both partial exits.
5.3 Stop-Loss Modes
You can choose one of three Stop Loss modes:
Stable – fixed % from entry.
Ichimoku – fixed level derived from the Kumo.
Ichimoku Trailing – dynamic SL following the cloud.
5.3.1 Stable SL
For Long:
SL = entry_price * (1 - Stable SL % / 100)
For Short:
SL = entry_price * (1 + Stable SL % / 100)
Used both for Percent TP mode and as reference for Fib TP if Kumo is not available.
5.3.2 Ichimoku SL (fixed, non-trailing)
At the time of a new trade:
For Long:
Base SL = cloud bottom minus small offset (%)
For Short:
Base SL = cloud top plus small offset (%)
The offset is configurable: Ichimoku SL Offset %.
Once computed, that SL level is fixed for this trade.
5.3.3 Ichimoku Trailing SL
Similar to Ichimoku SL, but recomputed each bar:
For Long:
SL = cloud bottom – offset
For Short:
SL = cloud top + offset
A red trailing SL line is drawn on the chart to visualize current stop level.
This trailing SL is also used as reference for BreakEven and for Fib TP distance.
6. BreakEven Logic (with BE Lines)
BreakEven is optional and supports two modes:
Percent
Fibonacci
Inputs:
Percent mode:
BE Trigger % (from entry) – move SL to BE when price goes this % in profit.
BE Offset % from entry – SL will be set to entry ± this offset.
Fibonacci mode:
BE Fib Level – Fib level at which BE will be activated (default 1.618, same style as TP).
BE Offset % from entry – how far from entry to place BE stop.
The logic:
Before BE is triggered, SL follows its normal mode (Stable/Ichimoku/Ichimoku Trailing).
When BE triggers:
For Long:
New SL = max(current SL, BE SL).
For Short:
New SL = min(current SL, BE SL).
This means BE will never loosen the stop – only tighten it.
When BE is activated, the strategy draws a violet horizontal line at the BreakEven level (once per trade).
BE state is cleared when the position is closed or when a new position is opened.
7. Entry & Exit Logic (Summary)
7.1 Long Entry
Conditions for a Long:
CCI signal:
CCI crosses up through the upper threshold.
Ichimoku Cloud Filter (optional):
If enabled → price must be above the Kumo.
Ichimoku Lines Filter (optional):
If enabled → Conversion Line and Base Line must be above the Kumo.
MA Direction Filter (optional):
If enabled → Close must be above the chosen MA.
Anti-re-entry flag:
allowLong must be true (cloud-based reset).
Position check:
Long entries are allowed when current position size ≤ 0 (so it can also reverse from short to long).
If all these conditions are true, the strategy sends:
strategy.entry("Long", strategy.long, qty = calculated_qty)
After entry:
allowLong = false
allowShort = true
7.2 Short Entry
Same structure, mirrored:
CCI signal:
CCI crosses down through the lower threshold.
Cloud filter: price must be below cloud (if enabled).
Lines filter: conversion & base must be below cloud (if enabled).
MA filter: Close must be below MA (if enabled).
allowShort must be true.
Position check: position size ≥ 0 (allows reversal from long to short).
Then:
strategy.entry("Short", strategy.short, qty = calculated_qty)
Flags update:
allowShort = false
allowLong = true
7.3 Exits
While in a position:
The strategy continuously recalculates SL (depending on chosen mode) and, in Percent mode, TP.
In Fib mode, fixed TP levels are computed at entry.
BreakEven may raise/tighten the SL if its conditions are met.
Exits are executed via strategy.exit:
Percent mode: one TP+SL exit per side.
Fib mode: two partial exits (TP1 and TP2) sharing the same SL.
At position open, the script also draws visual lines:
White line — entry price.
Green line(s) — TP level(s).
Red line — SL (if not using Ichimoku Trailing; with trailing, the red line is updated dynamically).
Maximum of 30 lines are kept to avoid clutter.
8. How to Use the Strategy
Choose market & timeframe
Works well on trending instruments. Try crypto, FX or indices on H1–H4, or intraday if you prefer more trades.
Adjust Ichimoku settings
Keep defaults (9/26/52/26) or adapt to your timeframe.
Configure Moving Average
Typical: EMA 200 as a trend filter.
Turn MA Direction Filter ON if you want to trade only with the main trend.
Set CCI thresholds
Default ±100 is classic.
Lower thresholds → more signals, higher noise.
Higher thresholds → fewer but stronger signals.
Enable/disable filters
Turn on Ichimoku Cloud and Ichimoku Lines if you want only “clean” trend trades.
Use Wait Position Close Before Flag Reset to control how often re-entries are allowed.
Choose TP & SL mode
Percent mode is simpler and easier to understand.
Fibonacci mode is more advanced: it aligns TP levels with the distance to stop, giving asymmetric RR setups (two partial TPs).
Choose Stable SL for fixed-risk trades, or Ichimoku / Ichimoku Trailing to tie stops to the cloud structure.
Set BreakEven
Enable BE if you want to lock in risk-free trades after a certain move.
Percent mode is straightforward; Fib mode keeps BreakEven in harmony with your Fib TP setup.
Run Backtest & Optimize
Press “Add to chart” → go to Strategy Tester.
Adjust parameters to your market and timeframe.
Look at equity curve, PF, drawdown, average trade, etc.
Live / Paper Trading
After you’re satisfied with backtest results, use the strategy to generate signals.
You can mirror entries/exits manually or connect them to alerts (if you build an alert-based execution layer).
Grok/Claude MoneyLine Fusion * Grok/Claude X SeriesMoneyLine Fusion Indicator
This is a technical analysis indicator designed to help traders identify potential buy and sell opportunities in the market. It combines several well-known trading concepts into one unified tool, displaying visual bands on the chart and generating signals when multiple conditions align.
The Core Concept: The "Money Line"
At the heart of this indicator is something called the Money Line, which is essentially a smoothed trend line calculated using linear regression over the last 16 bars (by default). Think of it as a "best fit" line through recent prices that shows you the general direction the market is heading. The indicator colors this line green when the trend is rising, red when it's falling, and yellow when it's essentially flat or undecided.
The Dynamic Bands
Surrounding the Money Line are upper and lower bands that expand and contract based on market volatility. These bands use the ATR (Average True Range) to measure how much the price typically moves. Here's where it gets clever: the bands also factor in the ADX indicator (which measures trend strength). When the market is trending strongly, the bands widen more aggressively to account for bigger price swings. When the trend is weak, they stay tighter. This adaptive behavior helps the indicator adjust to different market conditions automatically.
The area between the bands is shaded in the trend color (green, red, or yellow) to give you a quick visual of the current market bias.
How Buy and Sell Signals Are Generated
The indicator doesn't just look at one thing — it requires multiple conditions to align before triggering a signal. This is designed to filter out false signals and only alert you when several factors agree.
Signal TypeRequired ConditionsBUYFisher Transform is below -2.0 (oversold), Aroon Up is low (below 20), Aroon Down is high (above 80), and optionally a positive TA ScoreSELLFisher Transform is above +2.0 (overbought), Aroon Up is high (above 80), Aroon Down is low (below 20), and optionally a negative TA Score
Fisher Transform is a mathematical technique that converts price data into a bell curve distribution, making extreme readings (overbought/oversold) easier to spot.
Aroon measures how long it's been since the highest high or lowest low. When Aroon Down is high and Aroon Up is low, it suggests recent price action has been dominated by lows — a potential reversal setup for a buy.
The indicator also prevents signal spam by requiring at least 5 bars between signals of the same type.
The TA Scoring System
Behind the scenes, the indicator calculates a composite score based on four different technical indicators:
MACD — Momentum and trend direction (scores -2 to +2)
DMI — Directional movement comparing buyers vs sellers (scores -2 to +2)
MFI — Money Flow Index, similar to RSI but incorporates volume (scores -2 to +2)
RSI — Classic overbought/oversold measure (scores -1 to +1)
These scores are added together, and the result is displayed in the info panel with labels like "very bullish," "slightly bearish," or "neutral." You can optionally require a minimum TA score before signals trigger, adding another layer of confirmation.
Visual Display Elements
The indicator offers several optional display features:
Shaded bands between upper and lower lines
Buy/Sell labels directly on the chart showing the entry price
Bright blue candle highlighting when a signal fires
Info panel in the corner showing the Money Line value, volatility percentile, RSI, and TA score
Score dots at the bottom of the chart (green for bullish, red for bearish, yellow for neutral)
Debug table for troubleshooting that shows real-time values of Fisher, Aroon, and signal conditions
In Summary
This indicator is essentially a multi-factor confirmation system. Rather than relying on a single indicator that might give many false signals, it waits until the trend direction (Money Line), momentum extremes (Fisher Transform), price cycle position (Aroon), and overall technical picture (TA Score) all point in the same direction. The adaptive bands help visualize where price "should" be trading given current volatility and trend strength. It's designed for traders who prefer fewer but higher-conviction signals.
UM Nadaraya-Watson OscillatorDescription
This is a different take on the Nadaraya-Watson Estimator from both Jdhorty and LuxAlgo. Both great scripts, I encourage everyone to check them out. Think of this script as a measure of trend direction, direction change, and trend acceleration or deceleration. It is not a Moving Average, but you could think of it as loosely as an intelligent adaptive regression curve with the focus on trend direction. The Gaussian calculations prefer and add more weight to the most recent bars. The end result is the oscillator is more responsive with less lag and less prone to pure price noise.
How it Works
The indicator was added to the chart twice; once with an MA, once without. The oscillator indicates trend change by crossing up through the zero line or down through the zero line. Once the indicator turns positive, we are in a positive trend until it crosses below zero and then the trend turns negative. I implemented a Moving Average overlay for additional signal determination; if the configured MA (EMA, SMA, WMA, or Nadaraya-Watson Estimator) trends higher, it is green. When trending down, it is red. The indicator also changes the color of the price bars; when the indicator below zero and red, the price bars are red. When the indicator is above zero and green, the price bars are green.
I marked up the chart and indicator to identify LONG, SHORT, and divergences between price and oscillator.
Default Settings
The default settings are 16 for Bandwidth and a WMA with 110. This is shown in the chart example. There directional arrows, but they are off by default. The Price bars are colored green or red to match the oscillator and the bar coloring is on by default.
All settings are user-configurable including bandwidth, MA type, MA length, bar coloring, and arrows.
Suggested Settings and uses
I personally like the 30 min chart with a bandwidth of 16 and a WMA of 110. The bandwidth 8 and 8 period EMA or WMA also work well on 6 hour and daily charts. Add this to your chart arsenal and use your favorite indicators for confirmation. This indicator works well on the 30 minute chart for inverse ETFs as well (SQQQ, SOXS, TZA). Also, the oscillator is good for identifying divergences between price and and indicator. (see chart for illustration)
Experiment with settings and adapt them to your trading style.
Alerts
If you right click the indicator, and select add alert, I have configured 4 standard alerts: A bullish cross above zero, A bearish cross below zero, An MA bullish turned up to trend higher, (green), and an MA bearish turned down to trend lower (red).
Filter Trend1. Indicator Name
Premium EMA Ribbon Filter (Pro Version)
(Advanced Trend & Momentum Filtering System Based on EMA Ribbons)
2. One-Line Introduction
A professional trend-analysis indicator that blends an advanced noise-filtering algorithm with an EMA ribbon system to extract only the pure bullish/bearish trend while smoothing out market noise.
3. Overall Description (7+ lines)
The Premium EMA Ribbon Filter is more than just a set of EMAs.
It analyzes the structure of a fast, medium, and slow EMA ribbon—along with the spacing and alignment between them—to determine whether the market is in a bullish trend, bearish trend, or a neutral/noise-heavy zone.
The core of this indicator is its noise-reduction algorithm and trend-strength calculation system.
Instead of relying on simple EMA cross signals, it evaluates how consistently the ribbon maintains bullish/bearish alignment over a specified period and highlights only strong trends with color coding, while weak or noisy areas are displayed in gray.
This helps traders avoid confusing or false signals and clearly focus only on the “meaningful zones.”
A Triple-Smoothing System is applied to create smoother, more refined ribbon movements, forming a stable “premium trend curve” that is less affected by short-term volatility.
As a result, this indicator works effectively for scalping, swing trading, and long-term trend following—staying true to the principle of removing noise and highlighting only the core market flow.
4. Short Advantages (6 items)
① Complete Noise Filtering
Using EMA ribbon comparison + tolerance logic, false reversals are largely eliminated, leaving only stable trend phases.
② Highly Readable Color System
Bullish trends are mint, bearish trends are red, and neutral/noise zones are gray—instantly visualizing market conditions.
③ Trend Strength Visualization
Not only trend direction but also trend strength is displayed via dynamic color transparency.
④ Smooth, Premium-Style Ribbon Design
Triple-smoothing creates a refined, luxury-level smoothness in movement.
⑤ Works Across All Timeframes
From 1-minute scalping to daily/weekly macro trend analysis.
⑥ Excellent Real-Trading Compatibility
Works extremely well when combined with ATR, SuperTrend, and volume-based indicators.
Indicator Manual (Required Section)
📌 Understanding the Core Concept
The indicator uses three EMAs (e.g., 20/50/100) arranged as a ribbon to analyze the structural alignment of the trend.
When the EMAs are cleanly aligned Top → Middle → Bottom, the market is in a bullish trend.
When aligned Bottom → Middle → Top, the market is in a bearish trend.
The indicator further evaluates the ribbon spread (gap) and the consistency of alignment to compute trend strength.
Noisy market conditions are shaded gray to clearly indicate “uncertain/indecisive” zones.
⚙️ Settings Description
Option Description
Fast EMA Most sensitive EMA; detects early trend signals
Mid EMA Stabilizes the primary trend direction
Slow EMA Defines the broader, long-term trend flow
Trend Lookback The period used to analyze trend strength
Noise Tolerance (%) Higher values = stronger noise removal
Smoothing Steps Controls how smooth the ribbon becomes
📈 Example Recognition
A bullish continuation/entry scenario forms when:
EMAs align in the order Fast → Mid → Slow (top side)
Ribbon color shifts into mint (strong bullish trend)
The ribbon begins to expand while price stays above the ribbon
📉 Example Recognition
A bearish continuation/entry occurs when:
EMAs align Fast → Mid → Slow (bottom side)
Ribbon color remains red
After contracting, the ribbon expands again during renewed downside strength
🧪 Recommended Usage
Combine with volume-based indicators (OBV, Volume Profile) → enhanced strong-trend detection
Use with SuperTrend or ATR Stop → clearer stop-loss placement
Combine with RSI/Stoch → avoid counter-trend entries in overheated conditions
Higher leverage traders should use higher tolerance settings
🔒 Cautions
EMA ribbons are trend-following tools; signals may weaken in ranging/sideways markets.
Never rely solely on this indicator—always confirm with volume, price patterns, or structure.
Very low Lookback values may cause excessive re-entry signals.
In high-volatility environments, ribbon spacing can contract/expand rapidly—use with caution.
Debt-Cycle vs Bitcoin-CycleDebt-Cycle vs Bitcoin-Cycle Indicator
The Debt-Cycle vs Bitcoin-Cycle indicator is a macro-economic analysis tool that compares traditional financial market cycles (debt/credit cycles) against Bitcoin market cycles. It uses Z-score normalization to track the relative positioning of global financial conditions versus cryptocurrency market sentiment, helping identify potential turning points and divergences between traditional finance and digital assets.
Key Features
Dual-Cycle Analysis: Simultaneously tracks traditional financial cycles and Bitcoin-specific cycles
Z-Score Normalization: Standardizes diverse data sources for meaningful comparison
Multi-Asset Coverage: Analyzes currencies, commodities, bonds, monetary aggregates, and on-chain metrics
Divergence Detection: Identifies when Bitcoin cycles move independently from traditional finance
21-Day Timeframe: Optimized for Long-term cycle analysis
What It Measures
Finance-Cycle (White Line)
Tracks traditional financial market health through:
Currencies: USD strength (DXY), global currency weights (USDWCU, EURWCU)
Commodities: Oil, gold, natural gas, agricultural products, and Bitcoin price
Corporate Bonds: Investment-grade spreads, high-yield spreads, credit conditions
Monetary Aggregates: M2 money supply, foreign exchange reserves (weighted by currency)
Treasury Bonds: Yield curve (2Y/10Y, 3M/10Y), term premiums, long-term rates
Bitcoin-Cycle (Orange Line)
Tracks Bitcoin market positioning through:
On-Chain Metrics:
MVRV Ratio (Market Value to Realized Value)
NUPL (Net Unrealized Profit/Loss)
Profit/Loss Address Distribution
Technical Indicators:
Bitcoin price Z-score
Moving average deviation
Relative Strength:
ETH/BTC ratio (altcoin strength indicator)
Visual Elements
White Line: Finance-Cycle indicator (positive = expansionary conditions, negative = contractionary)
Orange Line: Bitcoin-Cycle indicator (positive = bullish positioning, negative = bearish)
Zero Line: Neutral reference point
Interpretation
Cycle Alignment
Both positive: Risk-on environment, favorable for crypto
Both negative: Risk-off environment, caution warranted
Divergence: Potential opportunities or warning signals
Divergence Signals
Finance positive, Bitcoin negative: Bitcoin may be undervalued relative to macro conditions
Finance negative, Bitcoin positive: Bitcoin may be overextended or decoupling from traditional finance
Important Limitations
This indicator uses some technical and macro data but still has significant gaps:
⚠️ Limited monetary data - missing:
Funding rates (repo, overnight markets)
Comprehensive bond spread analysis
Collateral velocity and quality metrics
Central bank balance sheet details
⚠️ Basic economic coverage - missing:
GDP growth rates
Inflation expectations
Employment data
Manufacturing indices
Consumer confidence
⚠️ Simplified on-chain analysis - missing:
Exchange flow data
Whale wallet movements
Mining difficulty adjustments
Hash rate trends
Network fee dynamics
⚠️ No sentiment data - missing:
Fear & Greed Index
Options positioning
Futures open interest
Social media sentiment
The indicator provides a high-level cycle comparison but should be combined with comprehensive fundamental analysis, detailed on-chain research, and proper risk management.
Settings
Offset: Adjust the horizontal positioning of the indicators (default: 0)
Timeframe: Fixed at 21 days for optimal cycle detection
Use Cases
Macro-crypto correlation analysis: Understand when Bitcoin moves with or against traditional markets
Cycle timing: Identify potential tops and bottoms in both cycles
Risk assessment: Gauge overall market conditions across asset classes
Divergence trading: Spot opportunities when cycles diverge significantly
Portfolio allocation: Balance traditional and crypto assets based on cycle positioning
Technical Notes
Uses Z-score normalization with varying lookback periods (40-60 bars)
Applies HMA (Hull Moving Average) smoothing to reduce noise
Asymmetric multipliers for upside/downside movements in certain metrics
Requires access to FRED economic data, Glassnode, CoinMetrics, and IntoTheBlock feeds
21-day timeframe optimized for cycle analysis
Strategy Applications
This indicator is particularly useful for:
Cross-asset allocation - Decide between traditional finance and crypto exposure
Cycle positioning - Identify where we are in credit/debt cycles vs. Bitcoin cycles
Regime changes - Detect shifts in market leadership and correlation patterns
Risk management - Reduce exposure when both cycles turn negative
Disclaimer: This indicator is a cycle analysis tool and should not be used as the sole basis for investment decisions. It has limited coverage of monetary conditions, economic fundamentals, and on-chain metrics. The indicator provides directional insight but cannot predict exact timing or magnitude of market moves. Always conduct thorough research, consider multiple data sources, and maintain proper risk management in all investment decisions.
2s10s Bull/Bear Steepener/Flattener (Intraday bars)A simple indicator that tracks the curve of the US2y and US10y
Kernel Channel [BackQuant]Kernel Channel
A non-parametric, kernel-weighted trend channel that adapts to local structure, smooths noise without lagging like moving averages, and highlights volatility compressions, expansions, and directional bias through a flexible choice of kernels, band types, and squeeze logic.
What this is
This indicator builds a full trend channel using kernel regression rather than classical averaging. Instead of a simple moving average or exponential weighting, the midline is computed as a kernel-weighted expectation of past values. This allows it to adapt to local shape, give more weight to nearby bars, and reduce distortion from outliers.
You can think of it as a sliding local smoother where you define both the “window” of influence (Window Length) and the “locality strength” (Bandwidth). The result is a flexible midline with optional upper and lower bands derived from kernel-weighted ATR or kernel-weighted standard deviation, letting you visualize volatility in a structurally consistent way.
Three plotting modes help demonstrate this difference:
When the midline is shown alone, you get a smooth, adaptive baseline that behaves almost like a regression moving average, as shown in this view:
When full channels are enabled, you see how standard deviation reacts to local structure with dynamically widening and tightening bands, a mode illustrated here:
When ATR mode is chosen instead of StdDev, band width reflects breadth of movement rather than variance, creating a volatility-aware envelope like the example here:
Why kernels
Classical moving averages allocate fixed weights. Kernels let the user define weighting shape:
Epanechnikov — emphasizes bars near the current bar, fades fast, stable and smooth.
Triangular — linear decay, simple and responsive.
Laplacian — exponential decay from the current point, sharper reactivity.
Cosine — gentle periodic decay, balanced smoothness for trend filters.
Using these in combination with a bandwidth parameter gives fine control over smoothness vs responsiveness. Smaller bandwidths give sharper local sensitivity, larger bandwidths give smoother curvature.
How it works (core logic)
The indicator computes three building blocks:
1) Kernel-weighted midline
For every bar, a sliding window looks back Window Length bars. Each bar in this window receives a kernel weight depending on:
its index distance from the present
the chosen kernel shape
the bandwidth parameter (locality)
Weights form the denominator, weighted values form the numerator, and the resulting ratio is the kernel regression mean. This midline is the central trend.
2) Kernel-based width
You choose one of two band types:
Kernel ATR — ATR values are kernel-averaged, producing a smooth, volatility-based width that is not dependent on variance. Ideal for directional trend channels and regime separation.
Kernel StdDev — local variance around the midline is computed through kernel weighting. This produces a true statistical envelope that narrows in quiet periods and widens in noisy areas.
Width is scaled using Band Multiplier , controlling how far the envelope extends.
3) Upper and lower channels
Provided midline and width exist, the channel edges are:
Upper = midline + bandMult × width
Lower = midline − bandMult × width
These create smooth structures around price that adapt continuously.
Plotting modes
The indicator supports multiple visual styles depending on what you want to emphasize.
When only the midline is displayed, you get a pure kernel trend: a smooth regression-like curve that reacts to local structure while filtering noise, demonstrated here: This provides a clean read on direction and slope.
With full channels enabled, the behavior of the bands becomes visible. Standard deviation mode creates elastic boundaries that tighten during compressions and widen during turbulence, which you can see in the band-focused demonstration: This helps identify expansion events, volatility clusters, and breakouts.
ATR mode shifts interpretation from statistical variance to raw movement amplitude. This makes channels less sensitive to outliers and more consistent across trend phases, as shown in this ATR variation example: This mode is particularly useful for breakout systems and bar-range regimes.
Regime detection and bar coloring
The slope of the midline defines directional bias:
Up-slope → green
Down-slope → red
Flat → gray
A secondary regime filter compares close to the channel:
Trend Up Strong — close above upper band and midline rising.
Trend Down Strong — close below lower band and midline falling.
Trend Up Weak — close between midline and upper band with rising slope.
Trend Down Weak — close between lower band and midline with falling slope.
Compression mode — squeeze conditions.
Bar coloring is optional and can be toggled for cleaner charts.
Squeeze logic
The indicator includes non-standard squeeze detection based on relative width , defined as:
width / |midline|
This gives a dimensionless measure of how “tight” or “loose” the channel is, normalized for trend level.
A rolling window evaluates the percentile rank of current width relative to past behavior. If the width is in the lowest X% of its last N observations, the script flags a squeeze environment. This highlights compression regions that may precede breakouts or regime shifts.
Deviation highlighting
When using Kernel StdDev mode, you may enable deviation flags that highlight bars where price moves outside the channel:
Above upper band → bullish momentum overextension
Below lower band → bearish momentum overextension
This is turned off in ATR mode because ATR widths do not represent distributional variance.
Alerts included
Kernel Channel Long — midline turns up.
Kernel Channel Short — midline turns down.
Price Crossed Midline — crossover or crossunder of the midline.
Price Above Upper — early momentum expansion.
Price Below Lower — downward volatility expansion.
These help automate regime changes and breakout detection.
How to use it
Trend identification
The midline acts as a bias filter. Rising midline means trend strength upward, falling midline means downward behavior. The channel width contextualizes confidence.
Breakout anticipation
Kernel StdDev compressions highlight areas where price is coiling. Breakouts often follow narrow relative width. ATR mode provides structural expansion cues that are smooth and robust.
Mean reversion
StdDev mode is suitable for fade setups. Moves to outer bands during low volatility often revert to the midline.
Continuation logic
If price breaks above the upper band while midline is rising, the indicator flags strong directional expansion. Same logic for breakdowns on the lower band.
Volatility characterization
Kernel ATR maps raw bar movements and is excellent for identifying regime shifts in markets where variance is unstable.
Tuning guidance
For smoother long-term trend tracking
Larger window (150–300).
Moderate bandwidth (1.0–2.0).
Epanechnikov or Cosine kernel.
ATR mode for stable envelopes.
For swing trading / short-term structure
Window length around 50–100.
Bandwidth 0.6–1.2.
Triangular for speed, Laplacian for sharper reactions.
StdDev bands for precise volatility compression.
For breakout systems
Smaller bandwidth for sharp local detection.
ATR mode for stable envelopes.
Enable squeeze highlighting for identifying setups early.
For mean-reversion systems
Use StdDev bands.
Moderate window length.
Highlight deviations to locate overextended bars.
Settings overview
Kernel Settings
Source
Window Length
Bandwidth
Kernel Type (Epanechnikov, Triangular, Laplacian, Cosine)
Channel Width
Band Type (Kernel ATR or Kernel StdDev)
Band Multiplier
Visuals
Show Bands
Color Bars By Regime
Highlight Squeeze Periods
Highlight Deviation
Lookback and Percentile settings
Colors for uptrend, downtrend, squeeze, flat
Trading applications
Trend filtering — trade only in direction of the midline slope.
Breakout confirmation — expansion outside the bands while slope agrees.
Squeeze timing — compression periods often precede the next directional leg.
Volatility-aware stops — ATR mode makes channel edges suitable for adaptive stop placement.
Structural swing mapping — StdDev bands help locate midline pullbacks vs distributional extremes.
Bias rotation — bar coloring highlights when regime shifts occur.
Notes
The Kernel Channel is not a signal generator by itself, but a structural map. It helps classify trend direction, volatility environment, distribution shape, and compression cycles. Combine it with your entry and exit framework, risk parameters, and higher-timeframe confirmation.
It is designed to behave consistently across markets, to avoid the bluntness of classical averages, and to reveal subtle curvature in price that traditional channels miss. Adjust kernel type, bandwidth, and band source to match the noise profile of your instrument, then use squeeze logic and deviation highlighting to guide timing.
Super momentum DBSISuper momentum DBSI: The Ultimate Guide
1. What is this Indicator?
The Super momentum DBSI is a "Consensus Engine." Instead of relying on a single line (like an RSI) to tell you where the market is going, this tool calculates 33 distinct technical indicators simultaneously for every single candle.
It treats the market like a democracy. It asks 33 mathematical "voters" (Momentum, Trend, Volume, Volatility) if they are Bullish or Bearish.
If 30 out of 33 say "Buy," the score is high (Yellow), and the trend is extremely strong.
If only 15 say "Buy," the score is low (Teal), and the trend is weak or choppy.
2. Visual Guide: How to Read the Numbers
The Scores
Top Number (Bears): Represents Selling Pressure.
Bottom Number (Bulls): Represents Buying Pressure.
The Colors (The Traffic Lights)
The colors are your primary signal. They tell you who is currently winning the war.
🟡 YELLOW (Dominance):
This indicates the Winning Side.
If the Bottom Number is Yellow, Bulls are in control.
If the Top Number is Yellow, Bears are in control.
🔴 RED (Weakness):
This appears on the Top. It means Bears are present but losing.
🔵 TEAL (Weakness):
This appears on the Bottom. It means Bulls are present but losing.
3. Trading Strategy
Scenario A: The "Strong Buy" (Long Entry)
The Setup: You are looking for a shift in momentum where Buyers overwhelm Sellers.
Watch the Bottom Number: Wait for it to turn Yellow.
Confirm Strength: Ensure the score is above 15 and rising (e.g., 12 → 18 → 22).
Check the Top: The Top Number should be Red and low (below 10).
Trigger: Enter on the candle close.
Scenario B: The "Strong Sell" (Short Entry)
The Setup: You are looking for Sellers to crush the Buyers.
Watch the Top Number: Wait for it to turn Yellow.
Confirm Strength: Ensure the score is above 15 and rising.
Check the Bottom: The Bottom Number should be Teal and low.
Trigger: Enter on the candle close.
Scenario C: The "No Trade Zone" (Choppy Market)
The Setup: The market is confused.
Visual: Top is Red, Bottom is Teal.
Meaning: NOBODY IS WINNING. There is no Yellow number.
Action: Do not trade. This usually happens during lunch hours, weekends, or right before big news. This filter alone will save you from many false breakouts.
4. What is Inside? (The 33 Indicators)
To give you confidence in the signals, here is exactly what the script is checking:
Group 1: Momentum (Oscillators)
Detects if price is moving fast.
RSI (Relative Strength Index)
CCI (Commodity Channel Index)
Stochastic
Williams %R
Momentum
Rate of Change (ROC)
Ultimate Oscillator
Awesome Oscillator
True Strength Index (TSI)
Stoch RSI
TRIX
Chande Momentum Oscillator
Group 2: Trend Direction
Detects the general path of the market.
13. MACD
14. Parabolic SAR
15. SuperTrend
16. ALMA (Moving Average)
17. Aroon
18. ADX (Directional Movement)
19. Coppock Curve
20. Ichimoku Conversion Line
21. Hull Moving Average
Group 3: Price Action
Detects where price is relative to averages.
22. Price vs EMA 20
23. Price vs EMA 50
24. Price vs EMA 200
Group 4: Volume & Force
Detects if there is money behind the move.
25. Money Flow Index (MFI)
26. On Balance Volume (OBV)
27. Chaikin Money Flow (CMF)
28. VWAP (Intraday)
29. Elder Force Index
30. Ease of Movement
Group 5: Volatility
Detects if price is pushing the outer limits.
31. Bollinger Bands
32. Keltner Channels
33. Donchian Channels
5. Pro Tips for Success
Don't Catch Knives: If the Bear score (Top) is Yellow and 25+, do not try to buy the dip. Wait for the Yellow score to break.
Exit Early: If you are Long and the Yellow Bull score drops from 28 to 15 in one candle, TAKE PROFIT. The momentum has died.
Use Higher Timeframes: This indicator works best on 15m, 1H, and 4H charts. On the 1m chart, it may be too volatile.
Advanced Market Profile & S/R Zones (Pro)Advanced Market Profile & S/R Zones
This indicator brings professional Auction Market Theory to your chart using a custom rolling Volume Profile algorithm. Unlike standard profiles that remain fixed, this tool dynamically calculates the "Fair Value" of the asset based on your specific lookback period (e.g., the last 100 bars).
It automatically highlights the Point of Control (POC), Value Area (VA), and suggests statistical Discount (Buy) and Premium (Sell) zones.
Key Features
Volume Splitting Algorithm:
Most basic scripts dump the entire volume of a candle into a single price point (the average). This script splits the volume across the candle's entire High-Low range. This results in a much smoother, higher-resolution bell curve that accurately reflects price action, especially on higher timeframes like Monthly charts.
Auto-generated Zones:
Green Zone (Discount): Prices below the Value Area Low (VAL). Statistically "cheap."
Red Zone (Premium): Prices above the Value Area High (VAH). Statistically "expensive."
Real-Time Dashboard:
A built-in panel displays the exact price levels for the POC, VAH, and VAL for precise limit order placement, along with the current Market Trend.
How to Use
For Intraday (Day Trading):
Settings: Set Lookback to 100 - 300.
Strategy: Watch for price to open outside the Value Area. If price breaks back inside the Value Area, target the POC (Red Line).
For Macro (Monthly/Weekly Charts):
Settings: Set Lookback to 12 (1 Year) or 60 (5 Years).
Strategy: Identify multi-year structural support. When a monthly candle enters the Green Discount Zone of a 5-year profile, it is often a high-probability institutional entry point.
Trend Logic
The Dashboard indicates trend based on price location relative to value:
Strong Bullish: Price is accepted ABOVE the Value Area.
Strong Bearish: Price is accepted BELOW the Value Area.
Neutral / In VA: Price is chopping inside the Value Area.
Disclaimer
This is a "Rolling Profile." It calculates the profile based on the current lookback window relative to the latest bar. As new bars form, the lookback window shifts, and the profile updates to reflect the new dataset.
Advanced Linear Regression Pro [PointAlgo]Advanced Linear Regression Pro is an open-source tool designed to visualize market structure using linear regression, volatility bands, and optional volume-weighted calculations.
The indicator expands the concept of regression channels by adding higher-timeframe confluence, slope analysis, imbalance detection, and breakout highlighting.
Key Features
• Volume-Weighted Regression
Weights the regression curve based on volume to highlight periods of strong participation.
• Dynamic Standard-Deviation Bands
Upper and lower bands are derived from volatility to help visualize potential expansion or contraction zones.
• Multi-Timeframe (MTF) Regression
Plots higher-timeframe regression lines and bands for additional trend context.
• Slope Strength Analysis
Helps identify whether the current regression slope is trending upward, downward, or in a neutral range.
• Order Flow Imbalance Detection
Highlights bars where price and volume move unusually fast, which may indicate liquidity voids or imbalance zones.
• Breakout Markers
Shows simple visual markers when the price closes beyond volatility bands with volume confirmation.
These are visual signals only, not trading signals.
How to Use
This indicator is meant for visual market analysis, such as:
Observing trend direction through regression slope
Spotting volatility expansions
Comparing price against higher-timeframe regression structure
Identifying areas where price moves rapidly with volume
It can be used on any market or timeframe.
No part of this script is intended as financial advice or a complete trading system.
Global M2 ex-China MonitorGlobal M2 Monitor - Ultimate Edition
🎯 OVERVIEW
Advanced global M2 money supply monitoring indicator, offering a unique macroeconomic view of global liquidity. Real-time tracking of M2 evolution in major developed economies.
📊 KEY FEATURES
Global M2 Aggregation : USA, Japan, Canada, Eurozone, United Kingdom
Currency Conversion : All data converted to USD for consistent analysis
High Resolution Display : Daily curve by default
Technical Analysis : 50-period moving average (SMA/EMA/WMA)
Accurate YoY Calculation : Annual variation based on monthly data
Advanced Signal System : Multi-condition color codes
🎨 COLOR SYSTEM - DEFAULT SETTINGS
🟢 GREEN : YoY ≥ 7% AND M2 ≥ SMA → Strong growth + Bullish momentum
🔴 RED : YoY ≤ 2% AND M2 ≤ SMA → Weak growth + Bearish momentum
🟢 LIGHT GREEN : YoY ≥ 7% BUT M2 < SMA → Good fundamentals, temporarily weak momentum
🔴 LIGHT RED : YoY ≤ 2% BUT M2 > SMA → Weak fundamentals, price still supported
🔵 BLUE : YoY between 2% and 7% → Neutral zone of moderate growth
🇨🇳 WHY IS CHINA EXCLUDED BY DEFAULT?
Chinese M2 data presents methodological reliability and transparency issues. Exclusion allows for more consistent analysis of mature market economies.
Different M2 definition vs Western standards
Capital controls affecting real convertibility
Frequent monetary manipulations by authorities
✅ Available option : Can be activated in settings
⚙️ OPTIMIZED DEFAULT PARAMETERS
// DISPLAY SETTINGS
Candle Period: D (Daily)
// MOVING AVERAGE
MA Period: 50, Type: SMA
// BACKGROUND LOGIC
YoY Bullish: 7%, YoY Bearish: 2%
SMA Method: absolute, Threshold: 0.2%
// COLORS
Transparency: 5%
China M2: Disabled
📈 RECOMMENDED USAGE
Traders : Anticipate sector rotations
Investors : Identify abundant/restricted liquidity phases
Macro-analysts : Monitor monetary policy impacts
Portfolio managers : Understand inflationary pressures
🔍 ADVANCED INTERPRETATION
M2 ↗️ + YoY ≥ 7% → Favorable risk-on environment
M2 ↘️ + YoY ≤ 2% → Defensive risk-off environment
Divergences → Early warning signals for trend changes
💡 WHY THIS INDICATOR?
Global money supply is the lifeblood of the financial economy . Its growth or contraction typically precedes market movements by 6 to 12 months.
"Don't fight the Fed... nor the world's central banks"
🛠️ ADVANCED CUSTOMIZATION
All parameters are customizable:
YoY bullish/bearish thresholds
SMA comparison method (absolute/percentage)
Colors and transparency
Moving average period and type
Optional China inclusion
📋 TECHNICAL INFORMATION
YoY Calculation : Based on monthly data for consistency
Sources : FRED, ECONOMICS, official data
Updates : Real-time with publications
Currencies : Updated exchange rates
Proyeccion Cuantitativa 6m - 3 escenarios“The chart displays three 6-month projected price paths based on trend and volatility: a conservative lower curve, a moderate expected path, and an aggressive upper scenario.”
ECG PRICE - mauricioofsousa📉 ECG PRICE – The Price Electrocardiogram
(explained for traders, scientists, and complete beginners)
🔍 1. WHAT IS THE ECG PRICE?
The ECG PRICE protocol is a market-reading system based on the RSI, but with a surgical twist:
👉 You don’t just calculate RSI from price.
👉 You adjust the price using the RSI, and then calculate RSI over this adjusted price.
This creates a filtered, amplified signal that behaves like a heart monitor for price, detecting micro-impulses and subtle market movements long before they show up in the standard RSI.
🧬 2. CORE IDEA
Just like a real ECG amplifies and reveals electrical rhythms hidden inside the heartbeat,
the ECG PRICE amplifies micro-deformations hidden inside the price’s momentum.
It works in three stages:
Compute the regular RSI
Use the RSI to adjust the price (creating an electrocardiographic price)
Compute a second RSI over this modified price
The result is a meta-derived oscillator—more sensitive, more precise, and better at detecting structural changes.
🧩 3. TECHNICAL BREAKDOWN
3.1. First RSI (classic)
The script calculates:
average gains
average losses
relative strength (RS)
and then the standard 0–100 RSI
This is the “normal heart rate monitor” everyone uses.
3.2. Creating the “Adjusted Price”
adjustedPrice = close * (rsi / 100)
This means:
➡️ When RSI is high (strong buying momentum), price is amplified.
➡️ When RSI is low (strong selling momentum), price is compressed.
This converts raw price into a bio-electrical signal, where the price itself is modulated by its own internal momentum.
It’s the financial equivalent of ECG gain adjustment.
3.3. RSI of the Adjusted Price
Now the script calculates a new RSI from this modified price.
That is the actual ECG PRICE.
This second-order oscillator becomes extremely sensitive to:
micro-momentum shifts
early trend fading
volatility shocks
micro-divergences
institutional pressure waves
It reads the electrical pattern behind the price rather than the superficial movement.
🟩🟥 4. Diagnostic Lines of the Protocol
35 (green dotted)
Pre-oversold fatigue zone.
65 (red dotted)
Pre-overbought exhaustion zone.
30 (white solid)
Classic oversold.
70 (white solid)
Classic overbought.
Together they create two diagnostic corridors:
1. Medical corridor (30–70):
Standard RSI clinical range.
2. Electrical corridor (35–65):
The ECG-sensitive zone where micro-shifts appear first.
🧠 5. In Engineering Language (MGO style)
The ECG PRICE is essentially:
A nonlinear second-order oscillator where the RSI feeds back into price, creating a recursive momentum-modulated signal.
It functions like a:
bioinformational modulator
feedback-driven wave processor
impulse amplifier
micro-PID sensitivity enhancer
Very similar to the informational-wave transformations inside the MGO pipeline.
👨⚕️📉 6. Explained for a Total Beginner
Imagine the price is a heart.
The normal RSI shows if the heart is beating fast or slow.
But the ECG PRICE takes that heartbeat…
feeds it back into the heart…
and then measures the new heartbeat.
This creates a much more sensitive exam that detects problems before the normal test would.
💡 7. What It Gives You in Practice
earlier reversal signals
better trend-fatigue detection
clearer micro-divergences
a clean RSI with reduced noise
a smoother momentum curve
advanced behavioral readings before breakouts
It’s an upgrade.
A second-layer RSI that “hears” the inner electrical impulses of price.
