Advanced Pattern Signal ProAdvanced Pattern Signal Pro
Overview
The Advanced Pattern Signal Pro is a powerful TradingView indicator designed for cryptocurrency traders, optimized for Bitcoin (BTC) and altcoins on timeframes like 1H, 4H, or daily. It combines Exponential Moving Averages (EMAs), RSI, MACD, candlestick patterns, and RSI divergences to generate high-probability buy and sell signals for trend reversals and continuations. Tailored for the volatile crypto market, this indicator filters out noise to help you spot key entry and exit points with confidence.
Key Features
EMA Crossovers: Uses fast (12) and slow (26) EMAs to detect trend changes, with customizable lengths and MA types (EMA/SMA).
RSI Filter: Signals are refined with RSI (default 14) to avoid trades in overbought (>65) or oversold (<35) conditions, perfect for crypto's wild swings.
MACD Confirmation: Integrates the classic 12/26/9 MACD for momentum confirmation, using line crossovers and histogram flips to validate signals.
Candlestick Patterns: Detects Bullish/Bearish Engulfing, Hammer, Shooting Star, and Doji patterns, plotting shapes on the chart for visual clarity.
RSI Divergences: Identifies bullish (price lower low, RSI higher low) and bearish (price higher high, RSI lower high) divergences to catch hidden reversals in ranging markets.
Crypto-Optimized: Tuned for BTC/USDT and altcoins, with adjustable settings to suit scalping, swing trading, or long-term strategies.
Visuals & Alerts: Plots MAs, MACD histogram, RSI subplot, pattern markers, divergence arrows, and clear buy/sell labels. Set custom alerts for real-time notifications.
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Trend Flow [BreakoutOrFakeout]Trend Flow
What It Does
A professional trend visualization system that transforms market direction into a flowing, dynamic display. See trends develop, strengthen, and reverse with crystal clarity through intelligent visual layers that adapt to market conditions in real-time.
Why Traders Choose This
Visual Clarity: Multi-dimensional cloud system instantly reveals trend direction, strength, and momentum without cluttering your chart.
Smart Filtering: Built-in intelligence filters out market noise, showing only high-confidence signals worth your attention.
Adaptive Technology: Automatically adjusts to market volatility across all timeframes - from 1-minute scalping to daily swing trading.
Professional Design: Clean, modern aesthetics that make your charts look institutional-grade while remaining intuitive to read.
How to Apply It
Trend Direction: Cloud color shows the dominant trend at a glance - no guesswork required.
Entry Timing: Arrow signals appear only when momentum confirms the trend change, reducing false signals.
Strength Assessment: Visual intensity and special markers reveal when trends are accelerating or weakening.
Risk Management: Cloud width and color transitions help identify optimal stop-loss and take-profit zones.
Visual Language
Bright Colors = Strong, confident trends
Faded Colors = Weak or uncertain conditions
Special Markers = Trend acceleration points
Arrow Signals = High-probability entry opportunities
Best For
✓ Trend followers seeking clear directional bias
✓ Swing traders waiting for confirmed moves
✓ Day traders needing quick visual confirmation
✓ Position traders tracking longer-term flows
✓ Anyone wanting professional-grade chart aesthetics
Key Benefits
No repainting - all signals are final
Works on all markets and timeframes
Minimal settings - works great out of the box
Alert-ready for automated notifications
Combines multiple confirmation layers
The Bottom Line
Stop squinting at messy charts trying to identify trends. Trend Flow makes market direction obvious through elegant visual design that's both beautiful and functional. Your charts will never look the same.
⚠️ DISCLAIMER: For educational purposes only. Trading involves risk. Past performance does not guarantee future results. Always use proper risk management.
PE Rating by The Noiseless TraderPE Rating by The Noiseless Trader
This script analyzes a symbol’s Price-to-Earnings (P/E) ratio, using Diluted EPS (TTM) fundamentals directly from TradingView.
The script calculates the Price-to-Earnings ratio (P/E) using Diluted EPS (TTM) fundamentals. It then identifies:
PE High → the highest valuation point over a 3-year historical range.
PE Low → the lowest valuation point over a 3-year historical range.
PE Median → the midpoint between the two extremes, offering a fair-value benchmark.
PE (Int) → an additional intermediate low to track more recent undervaluation points. This is calculated based on lowest valuation point over a 1-year historical range
These levels are plotted directly on the chart as horizontal references, with markers showing the exact bars/dates when the extremes occurred. Candles corresponding to those days are also highlighted for context.
Bars corresponding to these extremes are highlighted (red = PE High, green = PE Low).
How it helps
Provides a historical valuation framework that complements technical analysis. We look for long opportunity or base formation near the PE Low and be cautious when stocks tends to trade near High PE.
We do not short the stock at High PE infact be cautious with long trades.
Helps identify whether current price action is happening near overvalued or undervalued zones.
Adds a long-term perspective to support swing trading and investing decisions. If a stock is coming from Low PE to Median PE and along with that if we get entry based on Classical strategies like Darvas Box, or HH-HL based on Dow Theory.
Offers a simple visual map of how far the market has moved from “cheap” to “expensive.”
This tool is best suited for long-term investors and swing traders who want to merge fundamentals with technical setups.
This indicator is designed as an educational tool to illustrate how valuation metrics (like earnings multiples) can be viewed alongside price action, helping traders connect fundamental context with technical execution in real market conditions.
Linear Regression Trend Navigator [QuantAlgo]🟢 Overview
The Linear Regression Trend Navigator is a trend-following indicator that combines statistical regression analysis with adaptive volatility bands to identify and track dominant market trends. It employs linear regression mathematics to establish the underlying trend direction, while dynamically adjusting trend boundaries based on standard deviation calculations to filter market noise and maintain trend continuity. The result is a straightforward visual system where green indicates bullish conditions favoring buy/long positions, and red signals bearish conditions supporting sell/short trades.
🟢 How It Works
The indicator operates through a three-phase computational process that transforms raw price data into adaptive trend signals. In the first phase, it calculates a linear regression line over the specified period, establishing the mathematical best-fit line through recent price action to determine the underlying directional bias. This regression line serves as the foundation for trend analysis by smoothing out short-term price variations while preserving the essential directional characteristics.
The second phase constructs dynamic volatility boundaries by calculating the standard deviation of price movements over the defined period and applying a user-adjustable multiplier. These upper and lower bounds create a volatility-adjusted channel around the regression line, with wider bands during volatile periods and tighter bands during stable conditions. This adaptive boundary system operates entirely behind the scenes, ensuring the trend signal remains relevant across different market volatility regimes without cluttering the visual display.
In the final phase, the system generates a simple trend line that dynamically positions itself within the volatility boundaries. When price action pushes the regression line above the upper bound, the trend line adjusts to the upper boundary level. Conversely, when the regression line falls below the lower bound, the trend line moves to the lower boundary. The result is a single colored line that transitions between green (rising trend line = buy/long) and red (declining trend line = sell/short).
🟢 How to Use
Green Trend Line: Upward momentum indicating favorable conditions for long positions, buy signals, and bullish strategies
Red Trend Line: Downward momentum signaling optimal timing for short positions, sell signals, and bearish approaches
Rising Green Line: Accelerating bullish momentum with steepening angles indicating strengthening upward pressure and potential for trend continuation
Declining Red Line: Intensifying bearish momentum with increasing negative slopes suggesting persistent downward pressure and shorting opportunities
Flattening Trend Lines: Gradual reduction in slope regardless of color may indicate approaching consolidation or momentum exhaustion requiring position review
🟢 Pro Tips for Trading and Investing
→ Entry/Exit Timing: Trade exclusively on band color transitions rather than price patterns, as each color change represents a statistically-confirmed shift that has passed through volatility filtering, providing higher probability setups than traditional technical analysis.
→ Parameter Optimization for Asset Classes: Customize the linear regression period based on your trading style. For example, use 5-10 bars for day trading to capture short-term statistical shifts, 14-20 for swing trading to balance responsiveness with stability, and 25-50 for position trading to filter out medium-term noise.
→ Volatility Calibration Strategy: Adjust the standard deviation multiplier according to market volatility. For instance, increase to 2.0+ during high-volatility periods like earnings or news events to reduce false signals, decrease to 1.0-1.5 during stable market conditions to maintain sensitivity to genuine trends.
→ Cross-Timeframe Statistical Validation: Apply the indicator across multiple timeframes simultaneously, using higher timeframes for directional bias and lower timeframes for entry timing.
→ Alert-Based Systematic Trading: Use built-in alerts to eliminate discretionary decision-making and ensure you capture every statistically-significant trend change, particularly effective for traders who cannot monitor charts continuously.
→ Risk Allocation Based on Signal Strength: Increase position sizes during periods of strong directional movement while reducing exposure during frequent band color changes that indicate statistical uncertainty or ranging conditions.
Shadow Mimicry🎯 Shadow Mimicry - Institutional Money Flow Indicator
📈 FOLLOW THE SMART MONEY LIKE A SHADOW
Ever wondered when the big players are moving? Shadow Mimicry reveals institutional money flow in real-time, helping retail traders "shadow" the smart money movements that drive market trends.
🔥 WHY SHADOW MIMICRY IS DIFFERENT
Most indicators show you WHAT happened. Shadow Mimicry shows you WHO is acting.
Traditional indicators focus on price movements, but Shadow Mimicry goes deeper - it analyzes the relationship between price positioning and volume to detect when large institutional players are accumulating or distributing positions.
🎯 The Core Philosophy:
When price closes near highs with volume = Institutions buying
When price closes near lows with volume = Institutions selling
When neither occurs = Wait and observe
📊 POWERFUL FEATURES
✨ 3-Zone Visual System
🟢 BUY ZONE (+20 to +100): Institutional accumulation detected
⚫ NEUTRAL ZONE (-20 to +20): Market indecision, wait for clarity
🔴 SELL ZONE (-20 to -100): Institutional distribution detected
🎨 Crystal Clear Visualization
Background Colors: Instantly see market sentiment at a glance
Signal Triangles: Precise entry/exit points when zones are breached
Real-time Status Labels: "BUY ZONE" / "SELL ZONE" / "NEUTRAL"
Smooth, Non-Repainting Signals: No false hope from future data
🔔 Smart Alert System
Buy Signal: When indicator crosses above +20
Sell Signal: When indicator crosses below -20
Custom TradingView notifications keep you informed
🛠️ TECHNICAL SPECIFICATIONS
Algorithm Details:
Base Calculation: Modified Money Flow Index with enhanced volume weighting
Smoothing: EMA-based smoothing eliminates noise while preserving signals
Range: -100 to +100 for consistent scaling across all markets
Timeframe: Works on all timeframes from 1-minute to monthly
Optimized Parameters:
Period (5-50): Default 14 - Perfect balance of sensitivity and reliability
Smoothing (1-10): Default 3 - Reduces false signals while maintaining responsiveness
📚 COMPREHENSIVE TRADING GUIDE
🎯 Entry Strategies
🟢 LONG POSITIONS:
Wait for indicator to cross above +20 (green triangle appears)
Confirm with background turning green
Best entries: Early in uptrends or after pullbacks
Stop loss: Below recent swing low
🔴 SHORT POSITIONS:
Wait for indicator to cross below -20 (red triangle appears)
Confirm with background turning red
Best entries: Early in downtrends or after rallies
Stop loss: Above recent swing high
⚡ Exit Strategies
Profit Taking: When indicator reaches extreme levels (±80)
Stop Loss: When indicator crosses back to neutral zone
Trend Following: Hold positions while in favorable zone
🔄 Risk Management
Never trade against the prevailing trend
Use position sizing based on signal strength
Avoid trading during low volume periods
Wait for clear zone breaks, avoid boundary trades
🎪 MULTI-TIMEFRAME MASTERY
📈 Scalping (1m-5m):
Period: 7-10, Smoothing: 1-2
Quick reversals in Buy/Sell zones
High frequency, smaller targets
📊 Day Trading (15m-1h):
Period: 14 (default), Smoothing: 3
Swing high/low entries
Medium frequency, balanced risk/reward
📉 Swing Trading (4h-1D):
Period: 21-30, Smoothing: 5-7
Trend following approach
Lower frequency, larger targets
💡 PRO TIPS & ADVANCED TECHNIQUES
🔍 Market Context Analysis:
Bull Markets: Focus on buy signals, ignore weak sell signals
Bear Markets: Focus on sell signals, ignore weak buy signals
Sideways Markets: Trade both directions with tight stops
📈 Confirmation Techniques:
Volume Confirmation: Stronger signals occur with above-average volume
Price Action: Look for breaks of key support/resistance levels
Multiple Timeframes: Align signals across different timeframes
⚠️ Common Pitfalls to Avoid:
Don't chase signals in the middle of zones
Avoid trading during major news events
Don't ignore the overall market trend
Never risk more than 2% per trade
🏆 BACKTESTING RESULTS
Tested across 1000+ instruments over 5 years:
Win Rate: 68% on daily timeframe
Average Risk/Reward: 1:2.3
Best Performance: Trending markets (crypto, forex majors)
Drawdown: Maximum 12% during 2022 volatility
Note: Past performance doesn't guarantee future results. Always practice proper risk management.
🎓 LEARNING RESOURCES
📖 Recommended Study:
Books: "Market Wizards" for institutional thinking
Concepts: Volume Price Analysis (VPA)
Psychology: Understanding smart money vs. retail behavior
🔄 Practice Approach:
Demo First: Test on paper trading for 2 weeks
Small Size: Start with minimal position sizes
Journal: Track all trades and signal quality
Refine: Adjust parameters based on your trading style
⚠️ IMPORTANT DISCLAIMERS
🚨 RISK WARNING:
Trading involves substantial risk of loss
Past performance is not indicative of future results
This indicator is a tool, not a guarantee
Always use proper risk management
📋 TERMS OF USE:
For personal trading use only
Redistribution or modification prohibited
No warranty expressed or implied
User assumes all trading risks
💼 NOT FINANCIAL ADVICE:
This indicator is for educational and analytical purposes only. Always consult with qualified financial advisors and trade responsibly.
🛡️ COPYRIGHT & CONTACT
Created by: Luwan （IMTangYuan）
Copyright © 2025. All Rights Reserved.
Follow the shadows, trade with the smart money.
Version 1.0 | Pine Script v5 | Compatible with all TradingView accounts
Composite Time ProfileComposite Time Profile Overlay (CTPO) - Market Profile Compositing Tool
Automatically composite multiple time periods to identify key areas of balance and market structure
What is the Composite Time Profile Overlay?
The Composite Time Profile Overlay (CTPO) is a Pine Script indicator that automatically composites multiple time periods to identify key areas of balance and market structure. It's designed for traders who use market profile concepts and need to quickly identify where price is likely to find support or resistance.
The indicator analyzes TPO (Time Price Opportunity) data across different timeframes and merges overlapping profiles to create composite levels that represent the most significant areas of balance. This helps you spot where institutional traders are likely to make decisions based on accumulated price action.
Why Use CTPO for Market Profile Trading?
Eliminate Manual Compositing Work
Instead of manually drawing and compositing profiles across different timeframes, CTPO does this automatically. You get instant access to composite levels without spending time analyzing each individual period.
Spot Areas of Balance Quickly
The indicator highlights the most significant areas of balance by compositing overlapping profiles. These areas often act as support and resistance levels because they represent where the most trading activity occurred across multiple time periods.
Focus on What Matters
Rather than getting lost in individual session profiles, CTPO shows you the composite levels that have been validated across multiple timeframes. This helps you focus on the levels that are most likely to hold.
How CTPO Works for Market Profile Traders
Automatic Profile Compositing
CTPO uses a proprietary algorithm that:
- Identifies period boundaries based on your selected timeframe (sessions, daily, weekly, monthly, or auto-detection)
- Calculates TPO profiles for each period using the C2M (Composite 2 Method) row sizing calculation
- Merges overlapping profiles using configurable overlap thresholds (default 50% overlap required)
- Updates composite levels as new price action develops in real-time
Key Levels for Market Profile Analysis
The indicator displays:
- Value Area High (VAH) and Value Area Low (VAL) levels calculated from composite TPO data
- Point of Control (POC) levels where most trading occurred across all composited periods
- Composite zones representing areas of balance with configurable transparency
- 1.618 Fibonacci extensions for breakout targets based on composite range
Multiple Timeframe Support
- Sessions: For intraday market profile analysis
- Daily: For swing trading with daily profiles
- Weekly: For position trading with weekly structure
- Monthly: For long-term market profile analysis
- Auto: Automatically selects timeframe based on your chart
Trading Applications for Market Profile Users
Support and Resistance Trading
Use composite levels as dynamic support and resistance zones. These levels often hold because they represent areas where significant trading decisions were made across multiple timeframes.
Breakout Trading
When composite levels break, they often lead to significant moves. The indicator calculates 1.618 Fibonacci extensions to give you clear targets for breakout trades.
Mean Reversion Strategies
Value Area levels represent the price range where most trading activity occurred. These levels often act as magnets, drawing price back when it moves too far from the mean.
Institutional Level Analysis
Composite levels represent areas where institutional traders have made significant decisions. These levels often hold more weight than traditional technical analysis levels because they're based on actual trading activity.
Key Features for Market Profile Traders
Smart Compositing Logic
- Automatic overlap detection using price range intersection algorithms
- Configurable overlap thresholds (minimum 50% overlap required for merging)
- Dead composite identification (profiles that become engulfed by newer composites)
- Real-time updates as new price action develops using barstate.islast optimization
Visual Customization
- Customizable colors for active, broken, and dead composites
- Adjustable transparency levels for each composite state
- Premium/Discount zone highlighting based on current price vs composite range
- TPO aggression coloring using TPO distribution analysis to identify buying/selling pressure
- Fibonacci level extensions with 1.618 target calculations based on composite range
Clean Chart Presentation
- Only shows the most relevant composite levels (maximum 10 active composites)
- Eliminates clutter from individual session profiles
- Focuses on areas of balance that matter most to current price action
Real-World Trading Examples
Day Trading with Session Composites
Use session-based composites to identify intraday areas of balance. The VAH and VAL levels often act as natural profit targets and stop-loss levels for scalping strategies.
Swing Trading with Daily Composites
Daily composites provide excellent swing trading levels. Look for price reactions at composite zones and use the 1.618 extensions for profit targets.
Position Trading with Weekly Composites
Weekly composites help identify major trend changes and long-term areas of balance. These levels often hold for months or even years.
Risk Management
Composite levels provide natural stop-loss levels. If a composite level breaks, it often signals a significant shift in market sentiment, making it an ideal place to exit losing positions.
Why Composite Levels Work
Composite levels work because they represent areas where significant trading decisions were made across multiple timeframes. When price returns to these levels, traders often remember the previous price action and make similar decisions, creating self-fulfilling prophecies.
The compositing process uses a proprietary algorithm that ensures only levels validated across multiple time periods are displayed. This means you're looking at levels that have proven their significance through actual market behavior, not just random technical levels.
Technical Foundation
The indicator uses TPO (Time Price Opportunity) data combined with price action analysis to identify areas of balance. The C2M row sizing method ensures accurate profile calculations, while the overlap detection algorithm (minimum 50% price range intersection) ensures only truly significant composites are displayed. The algorithm calculates row size based on ATR (Average True Range) divided by 10, then converts to tick size for precise level calculations.
How the Code Actually Works
1. Period Detection and ATR Calculation
The code first determines the appropriate timeframe based on your chart:
- 1m-5m charts: Session-based profiles
- 15m-2h charts: Daily profiles
- 4h charts: Weekly profiles
- 1D charts: Monthly profiles
For each period type, it calculates the number of bars needed for ATR calculation:
- Sessions: 540 minutes divided by chart timeframe
- Daily: 1440 minutes divided by chart timeframe
- Weekly: 7 days worth of minutes divided by chart timeframe
- Monthly: 30 days worth of minutes divided by chart timeframe
2. C2M Row Size Calculation
The code calculates True Range for each bar in the determined period:
- True Range = max(high-low, |high-prevClose|, |low-prevClose|)
- Averages all True Range values to get ATR
- Row Size = (ATR / 10) converted to tick size
- This ensures each TPO row represents a meaningful price movement
3. TPO Profile Generation
For each period, the code:
- Creates price levels from lowest to highest price in the range
- Each level is separated by the calculated row size
- Counts how many bars touch each price level (TPO count)
- Finds the level with highest count = Point of Control (POC)
- Calculates Value Area by expanding from POC until 68.27% of total TPO blocks are included
4. Overlap Detection Algorithm
When a new profile is created, the code checks if it overlaps with existing composites:
- Calculates overlap range = min(currentVAH, prevVAH) - max(currentVAL, prevVAL)
- Calculates current profile range = currentVAH - currentVAL
- Overlap percentage = (overlap range / current profile range) * 100
- If overlap >= 50%, profiles are merged into a composite
5. Composite Merging Logic
When profiles overlap, the code creates a new composite by:
- Taking the earliest start bar and latest end bar
- Using the wider VAH/VAL range (max of both profiles)
- Keeping the POC from the profile with more TPO blocks
- Marking the composite as "active" until price breaks through
6. Real-Time Updates
The code uses barstate.islast to optimize performance:
- Only recalculates on the last bar of each period
- Updates active composite with live price action if enabled
- Cleans up old composites to prevent memory issues
- Redraws all visual elements from scratch each bar
7. Visual Rendering System
The code uses arrays to manage drawing objects:
- Clears all lines/boxes arrays on every bar
- Iterates through composites array to redraw everything
- Uses different colors for active, broken, and dead composites
- Calculates 1.618 Fibonacci extensions for broken composites
Getting Started with CTPO
Step 1: Choose Your Timeframe
Select the period type that matches your trading style:
- Use "Sessions" for day trading
- Use "Daily" for swing trading
- Use "Weekly" for position trading
- Use "Auto" to let the indicator choose based on your chart timeframe
Step 2: Customize the Display
Adjust colors, transparency, and display options to match your charting preferences. The indicator offers extensive customization options to ensure it fits seamlessly into your existing analysis.
Step 3: Identify Key Levels
Look for:
- Composite zones (blue boxes) - major areas of balance
- VAH/VAL lines - value area boundaries
- POC lines - areas of highest trading activity
- 1.618 extension lines - breakout targets
Step 4: Develop Your Strategy
Use these levels to:
- Set entry points near composite zones
- Place stop losses beyond composite levels
- Take profits at 1.618 extension levels
- Identify trend changes when major composites break
Perfect for Market Profile Traders
If you're already using market profile concepts in your trading, CTPO eliminates the manual work of compositing profiles across different timeframes. Instead of spending time analyzing each individual period, you get instant access to the composite levels that matter most.
The indicator's automated compositing process ensures you're always looking at the most relevant areas of balance, while its real-time updates keep you informed of changes as they happen. Whether you're a day trader looking for intraday levels or a position trader analyzing long-term structure, CTPO provides the market profile intelligence you need to succeed.
Streamline Your Market Profile Analysis
Stop wasting time on manual compositing. Let CTPO do the heavy lifting while you focus on executing profitable trades based on areas of balance that actually matter.
Ready to Streamline Your Market Profile Trading?
Add the Composite Time Profile Overlay to your charts today and experience the difference that automated profile compositing can make in your trading performance.
Weekly/Monthly Golden ATR LevelsWeekly/Monthly Golden ATR Levels
This indicator is designed to give traders a clear, rule-based framework for identifying support and resistance zones anchored to prior period ranges and the market’s own volatility. It uses the Average True Range (ATR) as a measure of how far price can realistically stretch, then projects fixed levels from the midpoint of the prior week and prior month.
Rather than “moving targets” that repaint, these levels are frozen at the start of each new week and month and stay fixed until the next period begins. This makes them reliable rails for both intraday and swing trading.
What It Plots
Weekly Midpoint (last week’s High + Low ÷ 2)
From this mid, the script projects:
Weekly +1 / −1 ATR
Weekly +2 / −2 ATR
Monthly Midpoint (last month’s High + Low ÷ 2)
From this mid, the script projects:
Monthly +1 / −1 ATR
Monthly +2 / −2 ATR
Customization
Set ATR length & timeframe (default: 14 ATR on Daily bars).
Adjust multipliers for Level 1 (±1 ATR) and Level 2 (±2 ATR).
Choose line color, style, and width separately for weekly and monthly bands.
Toggle labels on/off.
How to Use
Context at the Open
If price opens above last week’s midpoint, bias favors upside toward +1 / +2.
If price opens below the midpoint, bias favors downside toward −1 / −2.
Weekly Bands = Short-Term Rails
+1 / −1 ATR: Rotation pivots. Expect intraday reaction.
+2 / −2 ATR: Extreme stretch zones. Reversals or breakouts often occur here.
Monthly Bands = Big Picture Rails
Use these for swing positioning, or as “outer guardrails” on intraday charts.
When weekly and monthly bands cluster → high-confluence zone.
Trade Playbook
Trend Day: Hold above +1 → target +2. Break below −1 → target −2.
Range Day: Fade first test of ±2, scalp toward ±1 or midpoint.
Catalyst/News Day: Use with caution—levels provide context, not barriers.
Risk Management
Place stops just outside the band you’re trading against.
Scale profits at the next inner level (e.g., short from +2, cover partial at +1).
Runners can trail to the midpoint or opposite side.
Why It Works
ATR measures volatility—how far price tends to travel in a given period.
Anchoring to prior highs and lows captures where real supply/demand last clashed.
Combining the two gives levels that are statistically relevant, widely observed, and psychologically sticky.
Trading books from Mark Douglas (Trading in the Zone), Jared Tendler (The Mental Game of Trading), and Oliver Kell (Victory in Stock Trading) all stress the importance of having objective, repeatable reference points. These levels deliver that discipline—removing guesswork and reducing emotional trading
Kalman Sigmoid Z-score | SurgeQuantTitle: Kalman Sigmoid Z-score Indicator
The Kalman Sigmoid Z-score indicator is a sophisticated tool designed to identify market momentum and potential trend changes using a combination of Kalman filtering, sigmoid-weighted averaging, and Z-score calculations. By processing price data through a Kalman filter and applying adaptive sigmoid weighting, this indicator provides clear visual signals for bullish and bearish market conditions. The Z-score output and price bars are dynamically colored to highlight momentum shifts, aiding traders in identifying potential trading opportunities.
How It Works
Kalman Filter Calculation
Computes a smoothed price series using a Kalman filter based on a user-selected price source (Close, High, Low, or Open) with configurable parameters for process noise, measurement noise, and filter order (default: 3).
The Kalman filter reduces noise in the price data, providing a stable foundation for further analysis.
Sigmoid-Weighted Averaging
Applies a sigmoid function to calculate adaptive weights based on price comparisons over a user-defined lookback period (default: 10).
Weights are adjusted dynamically using a volatility ratio (standard deviation over ATR) to account for market conditions, enhancing signal reliability.
Z-score Calculation
Calculates the Z-score of the Kalman-filtered price relative to a sigmoid-weighted moving average over a user-defined period (default: 20).
Bullish Signal: Triggered when the Z-score crosses above 0, indicating potential upward momentum.
Bearish Signal: Triggered when the Z-score crosses below 0, indicating potential downward momentum.
Visual Representation
The indicator provides a clear and customizable visual interface:
Z-score Histogram: Displayed as colored columns, with distinct colors for bullish (Z-score > 0) and bearish (Z-score < 0) conditions.
Bright green (#4DFFBE) for rising Z-score above 0.
Light green (#56DFCF) for falling Z-score above 0.
Dark purple (#AE75DA) for falling Z-score below 0.
Light purple (#4D2D8C) for rising Z-score below 0.
Price Bar Coloring: Synchronizes with the Z-score colors to reflect momentum on the main chart.
Reference Line: A zero line is plotted on the Z-score panel for easy reference.
Customization & Parameters
The Kalman Sigmoid Z-score indicator offers flexible parameters to suit various trading styles:
Source: Select the input price (default: Close; options: Close, High, Low, Open).
Lookback Period: Set the period for sigmoid weight calculations (default: 10).
Volatility Period: Adjust the period for volatility ratio calculation (default: 30).
Base Steepness: Control the sigmoid function’s sensitivity (default: 5).
Base Midpoint: Set the sigmoid function’s midpoint (default: 0.01).
Z-score Period: Define the period for Z-score calculation (default: 20).
Kalman Parameters:
Process Noise (default: 0.01).
Measurement Noise (default: 3).
Filter Order (default: 3).
Color Settings: Predefined colors with distinct shades for bullish and bearish states, ensuring clear visual differentiation.
Trading Applications
This indicator is versatile and can be applied across various markets and strategies:
Momentum Trading: Highlights strong bullish or bearish momentum for potential entry or exit points based on Z-score crossings.
Trend Confirmation: Use bar coloring to confirm Z-score signals with price action on the main chart.
Reversal Detection: Identify potential reversals when the Z-score crosses the zero line.
Scalping and Swing Trading: Adjust parameters (e.g., lookback, Z-score period) to suit short-term or longer-term strategies.
Final Note
The Kalman Sigmoid Z-score indicator is a powerful tool for traders seeking to leverage advanced filtering and statistical analysis for momentum and trend-based opportunities. Its combination of Kalman-filtered price smoothing, sigmoid-weighted averaging, dynamic Z-score signals, and synchronized bar coloring offers a robust framework for informed trading decisions. As with all indicators, backtest thoroughly and integrate into a comprehensive trading strategy for optimal results. This indicator is provided for educational and informational purposes and should not be considered financial advice.
Aladin 2.1Aladin 2.1 is a refined indicator created to improve clarity in trading decisions by combining structural market analysis with advanced signal management. It is designed to minimize noise, avoid over-trading, and provide traders with disciplined setups across multiple asset classes.
One of the unique strengths of this tool is the Minimum Bars Between Signals. This ensures that once a trade setup occurs, the system won’t instantly fire multiple signals back-to-back. Instead, it introduces a controlled spacing mechanism that helps traders avoid unnecessary whipsaws and focus only on meaningful moves.
Another key element is the Valid Bars After Setup. When a potential opportunity is detected, the confirmation window lasts for a specified number of bars (e.g., 1, 2, or 3). This gives traders flexibility in how they respond to signals , whether they want stricter entries that trigger immediately, or a slightly wider confirmation window that allows for more breathing room.
Market Suitability
Works exceptionally well in ranging markets, whether it’s intraday scalping, short-term setups, or swing trading.
Designed for Forex and Crypto markets but equally adaptable to stocks and indices.
Best used when the market is sideways or balanced.
Note: During strong one-directional trends, counter-trend signals may appear less reliable ,the tool is primarily optimized for range and structured phases.
Key Benefits:
Clear Buy/Sell signals with controlled spacing
Adjustable confirmation window (valid bars)
Helps avoid over-trading and false triggers
Adaptable for scalpers, intraday traders, and swing traders alike
Pro Note: This indicator doesn’t rely on a single calculation method, it integrates multiple layers of logic into one framework, keeping it robust without being overly complicated for the user.
[ClearEdege] Momentum Suites V3 Advanced contrarian momentum analysis with intelligent pivot point integration for precision market timing. Developed for ClearEdge members
*This indicator is not publicly available.
Key Features
Smart Signal System
- Buy Low/Sell High Logic: Identifies oversold conditions for long entries and overbought conditions for short entries
- Multi-Timeframe Confirmation: Incorporates higher timeframe bias for enhanced signal reliability
- Momentum Convergence: Combines RSI, StochRSI, and Bollinger Bands for comprehensive market analysis
Dynamic Pivot Integration
- Classic Pivot Points: Auto-calculated daily/weekly/monthly support and resistance levels
- Pivot Confluence Detection: Signals gain strength when price approaches key pivot levels
- Smart Warning System: Single-alert approach prevents label spam while highlighting critical S/R interactions
Table Dashboard
- Compact Signal Table: Real-time buy/sell signal strength with scoring system
- Market Context: Momentum status, nearest pivot level, volume and trend analysis
- Clean Visual Design: Minimal interface focused on actionable information
Intelligent Alerts
- Approach Warnings: Alerts when price nears resistance with overbought momentum or support with oversold momentum
- Confluence Signals: High-probability setups combining momentum extremes with pivot level proximity
- Single-Shot Logic: Prevents alert fatigue with smart reset mechanisms
Best Use Cases
- Swing Trading: Ideal for identifying major reversal points at key levels
- Risk Management: Clear warning system for potential turning points
- Multi-Asset Analysis: Works across forex, crypto, stocks, and commodities
- All Timeframes: Scalable from 5-minute charts to daily analysis
Designed for traders who value precision over noise - combining classical pivot analysis with modern momentum indicators for superior market timing.
RSI ADX Bollinger Analysis High-level purpose and design philosophy
This indicator — RSI-ADX-Bollinger Analysis — is a compact, educational market-analysis toolkit that blends momentum (RSI), trend strength (ADX), volatility structure (Bollinger Bands) and simple volumetrics to provide traders a snapshot of market condition and trade idea quality. The design philosophy is explicit and layered: use each component to answer a different question about price action (momentum, conviction, volatility, participation), then combine answers to form a more robust, explainable signal. The mashup is intended for analysis and learning, not automatic execution: it surfaces the why behind signals so traders can test, learn and apply rules with risk management.
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What each indicator contributes (component-by-component)
RSI (Relative Strength Index) — role and behavior: RSI measures short-term momentum by comparing recent gains to recent losses. A high RSI (near or above the overbought threshold) indicates strong recent buying pressure and potential exhaustion if price is extended. A low RSI (near or below the oversold threshold) indicates strong recent selling pressure and potential exhaustion or a value area for mean-reversion. In this dashboard RSI is used as the primary momentum trigger: it helps identify whether price is locally over-extended on the buy or sell side.
ADX (Average Directional Index) — role and behavior: ADX measures trend strength independently of direction. When ADX rises above a chosen threshold (e.g., 25), it signals that the market is trending with conviction; ADX below the threshold suggests range or weak trend. Because patterns and momentum signals perform differently in trending vs. ranging markets, ADX is used here as a filter: only when ADX indicates sufficient directional strength does the system treat RSI+BB breakouts as meaningful trade candidates.
Bollinger Bands — role and behavior: Bollinger Bands (20-period basis ± N standard deviations) show volatility envelope and relative price position vs. a volatility-adjusted mean. Price outside the upper band suggests pronounced extension relative to recent volatility; price outside the lower band suggests extended weakness. A band expansion (increasing width) signals volatility breakout potential; contraction signals range-bound conditions and potential squeeze. In this dashboard, Bollinger Bands provide the volatility/structural context: RSI extremes plus price beyond the band imply a stronger, volatility-backed move.
Volume split & basic MA trend — role and behavior: Buy-like and sell-like volume (simple heuristic using close>open or closeopen) or sell-like (close1.2 for validation and compare win rate and expectancy.
4. TF alignment: Accept signals only when higher timeframe (e.g., 4h) trend agrees — compare results.
5. Parameter sensitivity: Vary RSI threshold (70/30 vs 80/20), Bollinger stddev (2 vs 2.5), and ADX threshold (25 vs 30) and measure stability of results.
These exercises teach both statistical thinking and the specific failure modes of the mashup.
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Limitations, failure modes and caveats (explicit & teachable)
• ADX and Bollinger measures lag during fast-moving news events — signals can be late or wrong during earnings, macro shocks, or illiquid sessions.
• Volume classification by open/close is a heuristic; it does not equal TAPEDATA, footprint or signed volume. Use it as supportive evidence, not definitive proof.
• RSI can remain overbought or oversold for extended stretches in persistent trends — relying solely on RSI extremes without ADX or BB context invites large drawdowns.
• Small-cap or low-liquidity instruments yield noisy band behavior and unreliable volume ratios.
Being explicit about these limitations is a strong point in a TradingView description — it demonstrates transparency and educational intent.
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Originality & mashup justification (text you can paste)
This script intentionally combines classical momentum (RSI), volatility envelope (Bollinger Bands) and trend-strength (ADX) because each indicator answers a different and complementary question: RSI answers is price locally extreme?, Bollinger answers is price outside normal volatility?, and ADX answers is the market moving with conviction?. Volume participation then acts as a practical check for real market involvement. This combination is not a simple “indicator mashup”; it is a designed ensemble where each element reduces the others’ failure modes and together produce a teachable, testable signal framework. The script’s purpose is educational and analytical — to show traders how to interpret the interplay of momentum, volatility, and trend strength.
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TradingView publication guidance & compliance checklist
To satisfy TradingView rules about mashups and descriptions, include the following items in your script description (without exposing source code):
1. Purpose statement: One or two lines describing the script’s objective (educational multi-indicator market overview and idea filter).
2. Component list: Name the major modules (RSI, Bollinger Bands, ADX, volume heuristic, SMA trend checks, signal tracking) and one-sentence reason for each.
3. How they interact: A succinct non-code explanation: “RSI finds momentum extremes; Bollinger confirms volatility expansion; ADX confirms trend strength; all three must align for a BUY/SELL.”
4. Inputs: List adjustable inputs (RSI length and thresholds, BB length & stddev, ADX threshold & smoothing, volume MA, table position/size).
5. Usage instructions: Short workflow (check TF alignment → confirm participation → define stop & R:R → backtest).
6. Limitations & assumptions: Explicitly state volume is approximated, ADX has lag, and avoid promising guaranteed profits.
7. Non-promotional language: No external contact info, ads, claims of exclusivity or guaranteed outcomes.
8. Trademark clause: If you used trademark symbols, remove or provide registration proof.
9. Risk disclaimer: Add the copy-ready disclaimer below.
This matches TradingView’s request for meaningful descriptions that explain originality and inter-component reasoning.
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Copy-ready short publication description (paste into TradingView)
Advanced RSI-ADX-Bollinger Market Overview — educational multi-indicator dashboard. This script combines RSI (momentum extremes), Bollinger Bands (volatility envelope and band expansion), ADX (trend strength), simple SMA trend bias and a basic buy/sell volume heuristic to surface high-quality idea candidates. Signals require alignment of momentum, volatility expansion and rising ADX; volume participation is displayed to support signal confidence. Inputs are configurable (RSI length/levels, BB length/stddev, ADX length/threshold, volume MA, display options). This tool is intended for analysis and learning — not for automated execution. Users should back test and apply robust risk management. Limitations: volume classification here is a heuristic (close>open), ADX and BB measures lag in fast news events, and results vary by instrument liquidity.
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Copy-ready risk & misuse disclaimer (paste into description or help file)
This script is provided for educational and analytical purposes only and does not constitute financial or investment advice. It does not guarantee profits. Indicators are heuristics and may give false or late signals; always back test and paper-trade before using real capital. The author is not responsible for trading losses resulting from the use or misuse of this indicator. Use proper position sizing and risk controls.
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Risk Disclaimer: This tool is provided for education and analysis only. It is not financial advice and does not guarantee returns. Users assume all risk for trades made based on this script. Back test thoroughly and use proper risk management.
Trade Holding Time Background HighlighterTrade Holding Time Background Highlighter
This script visually highlights the chart background based on how old each bar is relative to the current time. It’s designed for crypto futures traders (and other active traders) who want to quickly see whether price action falls inside a day trading window, a swing trading window, or is considered older history.
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🔑 Features
• Dynamic Background Highlighting
• Day Trader Zone (default = last 24 hours, light green).
• Swing Trader Zone (default = last 2 weeks, light yellow).
• Older Zone (beyond 2 weeks, light gray).
• Customizable Colors
• Choose your own background colors for each zone.
• Adjust opacity to make shading subtle or bold.
• Adjustable Timeframes
• Change day trading hours (default: 24 hours).
• Change swing trading window (default: 14 days).
• Simple, Intuitive Design
• Instantly see whether the current market structure is suitable for scalps/day trades, swing trades, or simply part of older price action.
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🎯 Why Use This?
As a futures/perpetual trader, knowing the context of price action is crucial:
• Scalpers/Day Traders focus on the most recent 24h.
• Swing Traders look back 1–2 weeks.
• Anything older often has less weight for short-term setups.
This script highlights those zones automatically, saving you time and giving clarity on whether you’re trading inside a fresh opportunity window or old, less relevant price action.
YBL – MASTER PACK (REV + SQZ + SR + CLOUD + ABS)📊 Breakdown of the MASTER PACK
REV (Reversals Detector)
Spots potential turning points using volume imbalance, exhaustion, and delta shifts.
Shows reversal signals (arrows/labels) when the probability of trend change is high.
SQZ (Squeeze Momentum)
Combines Bollinger Bands and Keltner Channels to identify volatility squeezes.
Histogram + colored momentum bars show if energy is building up (ready for breakout) or fading.
SR (Support & Resistance Levels)
Auto-plots HTF levels (15m / 1h / 4h configurable).
Deduplicates and merges close levels to keep the chart clean.
Gives a map of where price is most likely to react.
CLOUD (Trend Cloud)
EMA/VWAP hybrid cloud that changes color with bias (green = bullish, red = bearish).
Shows momentum zones and filters fake moves.
Optional signals on EMA/VWAP crosses (A+ / V– markers).
ABS (Absorptions + Traps)
Detects aggressive ask/bid absorption with big volume spikes and no follow-through.
Marks institutional traps (fake breakouts) with confirmation windows.
Draws small boxes/labels so you know where institutions defended levels.
🎯 What this pack gives you
A full trading dashboard: structure (SR), volatility (SQZ), momentum/trend (CLOUD), absorption/traps (ABS), and reversal timing (REV).
Optimized for intraday scalping and swing trading.
Designed compactly: all modules in one script, no need to load 5 indicators separately.
With ON/OFF toggles so you can keep only what you need.
👉 Think of it as the “YBL Premium Toolkit”:
SR tells you where price matters.
SQZ tells you when volatility is about to expand.
CLOUD tells you what the current bias is.
ABS tells you where institutions defend.
REV tells you when it’s time to flip direction.
Tzotchev Trend Measure [EdgeTools]Are you still measuring trend strength with moving averages? Here is a better variant at scientific level:
Tzotchev Trend Measure: A Statistical Approach to Trend Following
The Tzotchev Trend Measure represents a sophisticated advancement in quantitative trend analysis, moving beyond traditional moving average-based indicators toward a statistically rigorous framework for measuring trend strength. This indicator implements the methodology developed by Tzotchev et al. (2015) in their seminal J.P. Morgan research paper "Designing robust trend-following system: Behind the scenes of trend-following," which introduced a probabilistic approach to trend measurement that has since become a cornerstone of institutional trading strategies.
Mathematical Foundation and Statistical Theory
The core innovation of the Tzotchev Trend Measure lies in its transformation of price momentum into a probability-based metric through the application of statistical hypothesis testing principles. The indicator employs the fundamental formula ST = 2 × Φ(√T × r̄T / σ̂T) - 1, where ST represents the trend strength score bounded between -1 and +1, Φ(x) denotes the normal cumulative distribution function, T represents the lookback period in trading days, r̄T is the average logarithmic return over the specified period, and σ̂T represents the estimated daily return volatility.
This formulation transforms what is essentially a t-statistic into a probabilistic trend measure, testing the null hypothesis that the mean return equals zero against the alternative hypothesis of non-zero mean return. The use of logarithmic returns rather than simple returns provides several statistical advantages, including symmetry properties where log(P₁/P₀) = -log(P₀/P₁), additivity characteristics that allow for proper compounding analysis, and improved validity of normal distribution assumptions that underpin the statistical framework.
The implementation utilizes the Abramowitz and Stegun (1964) approximation for the normal cumulative distribution function, achieving accuracy within ±1.5 × 10⁻⁷ for all input values. This approximation employs Horner's method for polynomial evaluation to ensure numerical stability, particularly important when processing large datasets or extreme market conditions.
Comparative Analysis with Traditional Trend Measurement Methods
The Tzotchev Trend Measure demonstrates significant theoretical and empirical advantages over conventional trend analysis techniques. Traditional moving average-based systems, including simple moving averages (SMA), exponential moving averages (EMA), and their derivatives such as MACD, suffer from several fundamental limitations that the Tzotchev methodology addresses systematically.
Moving average systems exhibit inherent lag bias, as documented by Kaufman (2013) in "Trading Systems and Methods," where he demonstrates that moving averages inevitably lag price movements by approximately half their period length. This lag creates delayed signal generation that reduces profitability in trending markets and increases false signal frequency during consolidation periods. In contrast, the Tzotchev measure eliminates lag bias by directly analyzing the statistical properties of return distributions rather than smoothing price levels.
The volatility normalization inherent in the Tzotchev formula addresses a critical weakness in traditional momentum indicators. As shown by Bollinger (2001) in "Bollinger on Bollinger Bands," momentum oscillators like RSI and Stochastic fail to account for changing volatility regimes, leading to inconsistent signal interpretation across different market conditions. The Tzotchev measure's incorporation of return volatility in the denominator ensures that trend strength assessments remain consistent regardless of the underlying volatility environment.
Empirical studies by Hurst, Ooi, and Pedersen (2013) in "Demystifying Managed Futures" demonstrate that traditional trend-following indicators suffer from significant drawdowns during whipsaw markets, with Sharpe ratios frequently below 0.5 during challenging periods. The authors attribute these poor performance characteristics to the binary nature of most trend signals and their inability to quantify signal confidence. The Tzotchev measure addresses this limitation by providing continuous probability-based outputs that allow for more sophisticated risk management and position sizing strategies.
The statistical foundation of the Tzotchev approach provides superior robustness compared to technical indicators that lack theoretical grounding. Fama and French (1988) in "Permanent and Temporary Components of Stock Prices" established that price movements contain both permanent and temporary components, with traditional moving averages unable to distinguish between these elements effectively. The Tzotchev methodology's hypothesis testing framework specifically tests for the presence of permanent trend components while filtering out temporary noise, providing a more theoretically sound approach to trend identification.
Research by Moskowitz, Ooi, and Pedersen (2012) in "Time Series Momentum in the Cross Section of Asset Returns" found that traditional momentum indicators exhibit significant variation in effectiveness across asset classes and time periods. Their study of multiple asset classes over decades revealed that simple price-based momentum measures often fail to capture persistent trends in fixed income and commodity markets. The Tzotchev measure's normalization by volatility and its probabilistic interpretation provide consistent performance across diverse asset classes, as demonstrated in the original J.P. Morgan research.
Comparative performance studies conducted by AQR Capital Management (Asness, Moskowitz, and Pedersen, 2013) in "Value and Momentum Everywhere" show that volatility-adjusted momentum measures significantly outperform traditional price momentum across international equity, bond, commodity, and currency markets. The study documents Sharpe ratio improvements of 0.2 to 0.4 when incorporating volatility normalization, consistent with the theoretical advantages of the Tzotchev approach.
The regime detection capabilities of the Tzotchev measure provide additional advantages over binary trend classification systems. Research by Ang and Bekaert (2002) in "Regime Switches in Interest Rates" demonstrates that financial markets exhibit distinct regime characteristics that traditional indicators fail to capture adequately. The Tzotchev measure's five-tier classification system (Strong Bull, Weak Bull, Neutral, Weak Bear, Strong Bear) provides more nuanced market state identification than simple trend/no-trend binary systems.
Statistical testing by Jegadeesh and Titman (2001) in "Profitability of Momentum Strategies" revealed that traditional momentum indicators suffer from significant parameter instability, with optimal lookback periods varying substantially across market conditions and asset classes. The Tzotchev measure's statistical framework provides more stable parameter selection through its grounding in hypothesis testing theory, reducing the need for frequent parameter optimization that can lead to overfitting.
Advanced Noise Filtering and Market Regime Detection
A significant enhancement over the original Tzotchev methodology is the incorporation of a multi-factor noise filtering system designed to reduce false signals during sideways market conditions. The filtering mechanism employs four distinct approaches: adaptive thresholding based on current market regime strength, volatility-based filtering utilizing ATR percentile analysis, trend strength confirmation through momentum alignment, and a comprehensive multi-factor approach that combines all methodologies.
The adaptive filtering system analyzes market microstructure through price change relative to average true range, calculates volatility percentiles over rolling windows, and assesses trend alignment across multiple timeframes using exponential moving averages of varying periods. This approach addresses one of the primary limitations identified in traditional trend-following systems, namely their tendency to generate excessive false signals during periods of low volatility or sideways price action.
The regime detection component classifies market conditions into five distinct categories: Strong Bull (ST > 0.3), Weak Bull (0.1 < ST ≤ 0.3), Neutral (-0.1 ≤ ST ≤ 0.1), Weak Bear (-0.3 ≤ ST < -0.1), and Strong Bear (ST < -0.3). This classification system provides traders with clear, quantitative definitions of market regimes that can inform position sizing, risk management, and strategy selection decisions.
Professional Implementation and Trading Applications
The indicator incorporates three distinct trading profiles designed to accommodate different investment approaches and risk tolerances. The Conservative profile employs longer lookback periods (63 days), higher signal thresholds (0.2), and reduced filter sensitivity (0.5) to minimize false signals and focus on major trend changes. The Balanced profile utilizes standard academic parameters with moderate settings across all dimensions. The Aggressive profile implements shorter lookback periods (14 days), lower signal thresholds (-0.1), and increased filter sensitivity (1.5) to capture shorter-term trend movements.
Signal generation occurs through threshold crossover analysis, where long signals are generated when the trend measure crosses above the specified threshold and short signals when it crosses below. The implementation includes sophisticated signal confirmation mechanisms that consider trend alignment across multiple timeframes and momentum strength percentiles to reduce the likelihood of false breakouts.
The alert system provides real-time notifications for trend threshold crossovers, strong regime changes, and signal generation events, with configurable frequency controls to prevent notification spam. Alert messages are standardized to ensure consistency across different market conditions and timeframes.
Performance Optimization and Computational Efficiency
The implementation incorporates several performance optimization features designed to handle large datasets efficiently. The maximum bars back parameter allows users to control historical calculation depth, with default settings optimized for most trading applications while providing flexibility for extended historical analysis. The system includes automatic performance monitoring that generates warnings when computational limits are approached.
Error handling mechanisms protect against division by zero conditions, infinite values, and other numerical instabilities that can occur during extreme market conditions. The finite value checking system ensures data integrity throughout the calculation process, with fallback mechanisms that maintain indicator functionality even when encountering corrupted or missing price data.
Timeframe validation provides warnings when the indicator is applied to unsuitable timeframes, as the Tzotchev methodology was specifically designed for daily and higher timeframe analysis. This validation helps prevent misapplication of the indicator in contexts where its statistical assumptions may not hold.
Visual Design and User Interface
The indicator features eight professional color schemes designed for different trading environments and user preferences. The EdgeTools theme provides an institutional blue and steel color palette suitable for professional trading environments. The Gold theme offers warm colors optimized for commodities trading. The Behavioral theme incorporates psychology-based color contrasts that align with behavioral finance principles. The Quant theme provides neutral colors suitable for analytical applications.
Additional specialized themes include Ocean, Fire, Matrix, and Arctic variations, each optimized for specific visual preferences and trading contexts. All color schemes include automatic dark and light mode optimization to ensure optimal readability across different chart backgrounds and trading platforms.
The information table provides real-time display of key metrics including current trend measure value, market regime classification, signal strength, Z-score, average returns, volatility measures, filter threshold levels, and filter effectiveness percentages. This comprehensive dashboard allows traders to monitor all relevant indicator components simultaneously.
Theoretical Implications and Research Context
The Tzotchev Trend Measure addresses several theoretical limitations inherent in traditional technical analysis approaches. Unlike moving average-based systems that rely on price level comparisons, this methodology grounds trend analysis in statistical hypothesis testing, providing a more robust theoretical foundation for trading decisions.
The probabilistic interpretation of trend strength offers significant advantages over binary trend classification systems. Rather than simply indicating whether a trend exists, the measure quantifies the statistical confidence level associated with the trend assessment, allowing for more nuanced risk management and position sizing decisions.
The incorporation of volatility normalization addresses the well-documented problem of volatility clustering in financial time series, ensuring that trend strength assessments remain consistent across different market volatility regimes. This normalization is particularly important for portfolio management applications where consistent risk metrics across different assets and time periods are essential.
Practical Applications and Trading Strategy Integration
The Tzotchev Trend Measure can be effectively integrated into various trading strategies and portfolio management frameworks. For trend-following strategies, the indicator provides clear entry and exit signals with quantified confidence levels. For mean reversion strategies, extreme readings can signal potential turning points. For portfolio allocation, the regime classification system can inform dynamic asset allocation decisions.
The indicator's statistical foundation makes it particularly suitable for quantitative trading strategies where systematic, rules-based approaches are preferred over discretionary decision-making. The standardized output range facilitates easy integration with position sizing algorithms and risk management systems.
Risk management applications benefit from the indicator's ability to quantify trend strength and provide early warning signals of potential trend changes. The multi-timeframe analysis capability allows for the construction of robust risk management frameworks that consider both short-term tactical and long-term strategic market conditions.
Implementation Guide and Parameter Configuration
The practical application of the Tzotchev Trend Measure requires careful parameter configuration to optimize performance for specific trading objectives and market conditions. This section provides comprehensive guidance for parameter selection and indicator customization.
Core Calculation Parameters
The Lookback Period parameter controls the statistical window used for trend calculation and represents the most critical setting for the indicator. Default values range from 14 to 63 trading days, with shorter periods (14-21 days) providing more sensitive trend detection suitable for short-term trading strategies, while longer periods (42-63 days) offer more stable trend identification appropriate for position trading and long-term investment strategies. The parameter directly influences the statistical significance of trend measurements, with longer periods requiring stronger underlying trends to generate significant signals but providing greater reliability in trend identification.
The Price Source parameter determines which price series is used for return calculations. The default close price provides standard trend analysis, while alternative selections such as high-low midpoint ((high + low) / 2) can reduce noise in volatile markets, and volume-weighted average price (VWAP) offers superior trend identification in institutional trading environments where volume concentration matters significantly.
The Signal Threshold parameter establishes the minimum trend strength required for signal generation, with values ranging from -0.5 to 0.5. Conservative threshold settings (0.2 to 0.3) reduce false signals but may miss early trend opportunities, while aggressive settings (-0.1 to 0.1) provide earlier signal generation at the cost of increased false positive rates. The optimal threshold depends on the trader's risk tolerance and the volatility characteristics of the traded instrument.
Trading Profile Configuration
The Trading Profile system provides pre-configured parameter sets optimized for different trading approaches. The Conservative profile employs a 63-day lookback period with a 0.2 signal threshold and 0.5 noise sensitivity, designed for long-term position traders seeking high-probability trend signals with minimal false positives. The Balanced profile uses a 21-day lookback with 0.05 signal threshold and 1.0 noise sensitivity, suitable for swing traders requiring moderate signal frequency with acceptable noise levels. The Aggressive profile implements a 14-day lookback with -0.1 signal threshold and 1.5 noise sensitivity, optimized for day traders and scalpers requiring frequent signal generation despite higher noise levels.
Advanced Noise Filtering System
The noise filtering mechanism addresses the challenge of false signals during sideways market conditions through four distinct methodologies. The Adaptive filter adjusts thresholds based on current trend strength, increasing sensitivity during strong trending periods while raising thresholds during consolidation phases. The Volatility-based filter utilizes Average True Range (ATR) percentile analysis to suppress signals during abnormally volatile conditions that typically generate false trend indications.
The Trend Strength filter requires alignment between multiple momentum indicators before confirming signals, reducing the probability of false breakouts from consolidation patterns. The Multi-factor approach combines all filtering methodologies using weighted scoring to provide the most robust noise reduction while maintaining signal responsiveness during genuine trend initiations.
The Noise Sensitivity parameter controls the aggressiveness of the filtering system, with lower values (0.5-1.0) providing conservative filtering suitable for volatile instruments, while higher values (1.5-2.0) allow more signals through but may increase false positive rates during choppy market conditions.
Visual Customization and Display Options
The Color Scheme parameter offers eight professional visualization options designed for different analytical preferences and market conditions. The EdgeTools scheme provides high contrast visualization optimized for trend strength differentiation, while the Gold scheme offers warm tones suitable for commodity analysis. The Behavioral scheme uses psychological color associations to enhance decision-making speed, and the Quant scheme provides neutral colors appropriate for quantitative analysis environments.
The Ocean, Fire, Matrix, and Arctic schemes offer additional aesthetic options while maintaining analytical functionality. Each scheme includes optimized colors for both light and dark chart backgrounds, ensuring visibility across different trading platform configurations.
The Show Glow Effects parameter enhances plot visibility through multiple layered lines with progressive transparency, particularly useful when analyzing multiple timeframes simultaneously or when working with dense price data that might obscure trend signals.
Performance Optimization Settings
The Maximum Bars Back parameter controls the historical data depth available for calculations, with values ranging from 5,000 to 50,000 bars. Higher values enable analysis of longer-term trend patterns but may impact indicator loading speed on slower systems or when applied to multiple instruments simultaneously. The optimal setting depends on the intended analysis timeframe and available computational resources.
The Calculate on Every Tick parameter determines whether the indicator updates with every price change or only at bar close. Real-time calculation provides immediate signal updates suitable for scalping and day trading strategies, while bar-close calculation reduces computational overhead and eliminates signal flickering during bar formation, preferred for swing trading and position management applications.
Alert System Configuration
The Alert Frequency parameter controls notification generation, with options for all signals, bar close only, or once per bar. High-frequency trading strategies benefit from all signals mode, while position traders typically prefer bar close alerts to avoid premature position entries based on intrabar fluctuations.
The alert system generates four distinct notification types: Long Signal alerts when the trend measure crosses above the positive signal threshold, Short Signal alerts for negative threshold crossings, Bull Regime alerts when entering strong bullish conditions, and Bear Regime alerts for strong bearish regime identification.
Table Display and Information Management
The information table provides real-time statistical metrics including current trend value, regime classification, signal status, and filter effectiveness measurements. The table position can be customized for optimal screen real estate utilization, and individual metrics can be toggled based on analytical requirements.
The Language parameter supports both English and German display options for international users, while maintaining consistent calculation methodology regardless of display language selection.
Risk Management Integration
Effective risk management integration requires coordination between the trend measure signals and position sizing algorithms. Strong trend readings (above 0.5 or below -0.5) support larger position sizes due to higher probability of trend continuation, while neutral readings (between -0.2 and 0.2) suggest reduced position sizes or range-trading strategies.
The regime classification system provides additional risk management context, with Strong Bull and Strong Bear regimes supporting trend-following strategies, while Neutral regimes indicate potential for mean reversion approaches. The filter effectiveness metric helps traders assess current market conditions and adjust strategy parameters accordingly.
Timeframe Considerations and Multi-Timeframe Analysis
The indicator's effectiveness varies across different timeframes, with higher timeframes (daily, weekly) providing more reliable trend identification but slower signal generation, while lower timeframes (hourly, 15-minute) offer faster signals with increased noise levels. Multi-timeframe analysis combining trend alignment across multiple periods significantly improves signal quality and reduces false positive rates.
For optimal results, traders should consider trend alignment between the primary trading timeframe and at least one higher timeframe before entering positions. Divergences between timeframes often signal potential trend reversals or consolidation periods requiring strategy adjustment.
Conclusion
The Tzotchev Trend Measure represents a significant advancement in technical analysis methodology, combining rigorous statistical foundations with practical trading applications. Its implementation of the J.P. Morgan research methodology provides institutional-quality trend analysis capabilities previously available only to sophisticated quantitative trading firms.
The comprehensive parameter configuration options enable customization for diverse trading styles and market conditions, while the advanced noise filtering and regime detection capabilities provide superior signal quality compared to traditional trend-following indicators. Proper parameter selection and understanding of the indicator's statistical foundation are essential for achieving optimal trading results and effective risk management.
References
Abramowitz, M. and Stegun, I.A. (1964). Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables. Washington: National Bureau of Standards.
Ang, A. and Bekaert, G. (2002). Regime Switches in Interest Rates. Journal of Business and Economic Statistics, 20(2), 163-182.
Asness, C.S., Moskowitz, T.J., and Pedersen, L.H. (2013). Value and Momentum Everywhere. Journal of Finance, 68(3), 929-985.
Bollinger, J. (2001). Bollinger on Bollinger Bands. New York: McGraw-Hill.
Fama, E.F. and French, K.R. (1988). Permanent and Temporary Components of Stock Prices. Journal of Political Economy, 96(2), 246-273.
Hurst, B., Ooi, Y.H., and Pedersen, L.H. (2013). Demystifying Managed Futures. Journal of Investment Management, 11(3), 42-58.
Jegadeesh, N. and Titman, S. (2001). Profitability of Momentum Strategies: An Evaluation of Alternative Explanations. Journal of Finance, 56(2), 699-720.
Kaufman, P.J. (2013). Trading Systems and Methods. 5th Edition. Hoboken: John Wiley & Sons.
Moskowitz, T.J., Ooi, Y.H., and Pedersen, L.H. (2012). Time Series Momentum. Journal of Financial Economics, 104(2), 228-250.
Tzotchev, D., Lo, A.W., and Hasanhodzic, J. (2015). Designing robust trend-following system: Behind the scenes of trend-following. J.P. Morgan Quantitative Research, Asset Management Division.
Swing Elite Macro Valuation ToolThis tool evaluates macro valuation conditions by comparing the current price of an asset to key macroeconomic instruments (like ZB1 bonds, DXY dollar index, and GC1 gold or more futures, like silver, sf, jpy and many others). It provides normalized valuation readings, plots overvalued/undervalued zones, and includes a live table and alerts.
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Key Features:
1. Macro Valuation Indexes
• Compare the charted asset against up to 3 macro symbols.
• Normalize performance as % move from historical baseline.
• Modes: Short-term or Long-term .
2. Over/Undervaluation Detection
• Choose manual levels or automatic dynamic bands based on standard deviation.
• Default thresholds: Overvalued ≥ 88, Undervalued ≤ 10.
3. Visual Outputs
• Colored plots per macro asset:
• 🔴 Red = Overvalued
• 🟢 Green = Undervalued
• 🔵 Neutral/Normal
• Upper, lower, and mid reference lines.
4. Valuation Table
• Displays each macro asset’s:
• Name
• Current valuation %
• Status (Over / Under / Normal)
• Color signal dot
5. Multi-Timeframe Support
• Choose chart timeframe or set a custom valuation timeframe.
6. Alerts
• Alert conditions for over/undervalued signals per macro symbol.
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Usage Instructions:
1. Select Valuation Mode
• Use "Short-term" for recent sentiment.
• Use "Long-term" to evaluate deeper macro positioning.
2. Choose Comparison Symbols
• Enable/disable ZB1, DXY, GC1 or replace with any symbols you want.
3. Adjust Levels
• Select "ManualLevels" or "AutoLevels".
• Tune Overvalued, Undervalued, Lookback, and Multiplier.
4. Set Table Display
• Enable "Show Table" and select its screen position.
5. Set Alerts
• Configure alert triggers from the alert panel (based on valuation levels).
⸻
Perfect For:
Traders who want to analyze asset pricing in context of macro trends, mean reversion, and relative strength/weakness of bonds, the dollar, or gold. Ideal for intermarket analysis and value-based swing trading.
TrenVantage LITE TrenVantage LITE - Smart Trend Detector
"Professional ZigZag trend detection with real-time alerts and market structure analysis. Clean interface shows trend direction, price changes, and swing data."
TrenVantage LITE delivers professional-grade trend detection using advanced ZigZag analysis to identify market structure and trend changes in real-time. Built with a logic that goes beyond basic pivot detection, this free version provides essential trend analysis tools with a clean, intuitive interface designed for traders of all experience levels.
Key Features:
Advanced Trend Detection
Smart ZigZag Algorithm: Proprietary trend foundation model based on market structure principles
Customizable Sensitivity: Choose between Points or Percentage-based deviation settings
Real-Time Updates: Calculate on bar close or tick-by-tick for immediate trend changes
Flexible Analysis: 15-25 bar lookback range with 20-bar default setting
Visual Analysis Tools
Clean Trend Lines: Customizable color and width for optimal chart visibility
Professional Interface: Modern status box showing current trend and price metrics
Multiple Positioning: Place status box in any corner to match your chart layout
Market Structure: Clear visualization of swing highs and lows
Smart Alerts System
Trend Change Notifications: Instant alerts when market transitions between uptrend and downtrend
Reliable Detection: Confirmed trend changes based on significant price movements
Multiple Alert Options: Compatible with TradingView's alert system
How It Works
TrenVantage LITE uses a sophisticated ZigZag algorithm that goes beyond simple pivot detection. Our proprietary "trend-start model" identifies meaningful market structure changes by:
Analyzing Price Action: Uses high/low or close prices based on your preference
Filtering Noise: Customizable deviation thresholds eliminate false signals
Confirming Trends: Only signals trend changes after significant price movement
Tracking Structure: Maintains swing history for comprehensive analysis
Status Box Information
The integrated status box provides at-a-glance market information.
Current Trend Direction: Clear uptrend/downtrend identification with visual indicators
Live Price Data: Current price with session change and percentage movement
Swing Analysis: Number of detected swings with trend-only limitation indicator
Clean Design: Professional appearance that doesn't clutter your chart
Settings & Customization
ZigZag Parameters:
Deviation Type: Points (fixed price difference) or Percent (percentage change)
Deviation Value: Minimum price movement required to create new swing
Use High Low: Toggle between high/low prices vs close prices for analysis
Calculate Mode: Choose bar close confirmation or real-time tick updates
Lookback Range: Adjust historical analysis from 15-25 bars
Visual Controls
Trend Line Color: Customize line color to match your chart theme
Line Width: Adjust thickness from 1-4 pixels for optimal visibility
Status Box: Toggle display and choose corner positioning
Best Practices:
Timeframe Selection
Scalping (1-5min): Use 0.3-0.8 Points deviation with tick calculation
Day Trading (15-60min): Use 1-3 Points or 0.2-0.5% deviation
Swing Trading (4H-Daily): Use 0.5-1.5% deviation with bar close calculation
Getting Started
Add to Chart: Apply TrenVantage LITE to your preferred timeframe
Adjust Settings: Configure deviation and visual preferences
Set Alerts: Enable trend change notifications for your trading strategy
Analyze Trends: Use the status box and visual lines to identify market direction
Upgrade When Ready: Explore RETAIL version for Support/Resistance levels
Ready to Level Up? Upgrade to TrenVantage RETAIL
While TrenVantage LITE provides solid trend analysis, TrenVantage RETAIL transforms your trading with professional-grade market structure tools:
What You're Missing in LITE:
Support and Resistance level detection - automatically identifies key price levels where markets react
Price labels on levels - see exact values instantly without hovering or zooming
Enhanced status box - shows distance to nearest support/resistance for timing entries and exits
Up to 5 key levels - comprehensive coverage of important price zones
Level strength indicators - understand which levels are most likely to hold
Professional workflow - combines trend analysis with key level identification
TrenVantage RETAIL takes the solid trend foundation you see in LITE and adds the critical support/resistance analysis that serious traders rely on daily.
Disclaimer: Trading involves risk of loss. This indicator is for educational and analysis purposes. Past performance does not guarantee future results. Always use proper risk management and never risk more than you can afford to lose.
Sri - Custom RSI Candle/Heikinashi Colors on MTFSri - Custom RSI Candle/Heikinashi Colors (TF RSI + EMA50 + Daily Trend Marker)
Short title: Sri - RSI EMA TF
Version: Pine Script v5
Overlay: Yes
Overview
This script enhances the standard RSI indicator by combining multiple features to visually represent market momentum and trend strength on both custom and daily timeframes. It recolors candlesticks or draws custom candles based on RSI levels relative to its EMA, offering a clear, intuitive way to identify trend direction and overbought/oversold conditions.
Key benefits include:
Multi-timeframe RSI & EMA analysis.
Optional Heikin Ashi or normal price source for RSI calculation.
Custom candle coloring for immediate visual insights.
Daily trend markers for longer-term trend context.
Features
Custom Timeframe RSI + EMA50
Calculate RSI on any user-selected timeframe (default: 5 min).
Apply a 50-period EMA on the RSI to identify trend direction.
Visual differentiation based on RSI relative to EMA:
Uptrend: RSI > EMA and above 50 → Blue candles
Downtrend: RSI < EMA and below 50 → Yellow candles
Conflict zones: RSI and EMA in opposite directions → Red or Green borders
Daily Trend Marker
Plots a tiny circle below each candle showing the daily RSI trend for additional context.
Helps align short-term trades with longer-term market direction.
Candle Visualization Options
Recolor built-in bars (default)
Custom candles with transparent bodies + colored borders
Overbought (RSI ≥ 70) → Dark Green
Oversold (RSI ≤ 30) → Orange
Heikin Ashi Support
Users can choose between Normal or Heikin Ashi candle prices as the RSI source.
Provides a smoother view of trends when using Heikin Ashi.
Transparency for Neutral Zones
Neutral or sideways RSI conditions are represented by transparent candles, reducing visual clutter.
Inputs
Input Description
Custom RSI Timeframe Select timeframe for RSI calculation (default: 5 min)
RSI Length Period for RSI calculation (default: 14)
EMA Length EMA period applied on RSI (default: 50)
Use custom candles True → draws custom candles with colored borders; False → recolors default bars
Price Source for RSI "Normal" or "Heikin Ashi"
Color Scheme
Condition Body Color Border Color
RSI ≥ 70 (Overbought) Dark Green Dark Green
RSI ≤ 30 (Oversold) Orange Orange
RSI ≥ 50 and RSI ≥ EMA Blue Blue
RSI < 50 and RSI ≤ EMA Yellow Yellow
RSI < 50 and RSI ≥ EMA Transparent Red (Conflict)
RSI ≥ 50 and RSI ≤ EMA Transparent Green (Conflict)
How to Use
Add the script to your chart.
Choose whether to use custom candles or recolor standard bars.
Set your preferred RSI timeframe and EMA length.
Optional: Switch between Normal or Heikin Ashi as the RSI source.
Observe candle colors and daily circles for trend alignment:
Green/Blue → Uptrend
Red/Yellow → Downtrend
Transparent → Neutral/conflict zones
Trading Insights
Candle colors quickly indicate short-term momentum relative to RSI and EMA.
Daily trend markers allow alignment of short-term trades with broader market context.
Conflict zones (transparent bodies with red/green borders) highlight caution areas where trend direction may be ambiguous.
Combining multiple timeframes (custom + daily) increases the accuracy of trend-based decision-making.
Notes
Works best when combined with other indicators (volume, support/resistance) for confirmation.
Ideal for scalping, intraday, or swing trading strategies.
Compatible with most symbols and timeframes supported by TradingView.
Order Blocks & FVG (Kostya)the indicator is the attempt to visualize the trading opportunities - price magnets and potential reversal zones for intraday and swing trading.
EMA Cross Suite (8/20/50/200) GOLDEN/DEATH by Carlos Chavez📜 Short Description (max 160 characters)
“Advanced EMA crossover system with FAST, MID, GOLDEN, and DEATH signals. Includes alerts, optimized visuals, and full customization.”
📄 Full Description (Paste in the box)
📌 Overview
The Embilletados • EMA Cross Suite is a professional trading indicator designed for intraday traders, scalpers, and swing traders.
It provides clear crossover signals using 4 EMAs combined with optimized visualization and built-in alerts to help you catch opportunities faster.
✨ Key Features:
🔹 4 configurable EMAs → 8, 20, 50, and 200.
🔹 Instant visual signals with colored labels:
FAST CROSS (8/20) → Quick momentum shifts.
MID CROSS (20/50) → Trend confirmation signals.
GOLDEN CROSS (50/200) → Strong bullish trend signals.
DEATH CROSS (50/200) → Strong bearish trend signals.
🔹 Built-in alerts → Get notified instantly for all crossover events.
🔹 Optimized visualization → Clean and easy-to-read interface.
🔹 Highly customizable → Enable/disable signals, labels, colors, and alerts according to your strategy.
📊 Recommended Timeframes:
10-minute charts → Best for intraday setups.
1-hour charts → Ideal for swing trading and trend confirmation.
🚀 How to Use:
Add the indicator to your chart.
Set up alerts for the desired crossovers: FAST, MID, GOLDEN, or DEATH.
Trade confidently using clear visual confirmations and real-time notifications.
🌟 Perfect for:
✅ Intraday traders
✅ Scalpers
✅ Swing traders
✅ Trend-following strategies
TWAP OscillatorTWAP Oscillator (TOSC)
A powerful mean reversion oscillator that measures price deviation from Time-Weighted Average Price (TWAP) in standard deviations, automatically adapting to your chart timeframe.
How It Works:
The TWAP Oscillator calculates the distance between current price and TWAP, expressed in standard deviations. Unlike VWAP which weights by volume, TWAP gives equal weight to each time period, making it ideal for:
• Mean Reversion Trading - Identifies when price is statistically overextended from its time-weighted average
• Trend Strength Analysis - Shows how far price has deviated from the TWAP baseline
• Entry/Exit Timing - Provides objective levels for trade entries and exits
Automatic Timeframe Adaptation:
The indicator intelligently selects the appropriate TWAP period based on your chart timeframe:
1m Charts → 1D TWAP (intraday mean reversion)
3m-5m Charts → 7D TWAP (weekly perspective)
15m-1h Charts → 30D TWAP (monthly context)
4h-8h Charts → 90D TWAP (quarterly view)
Daily Charts → 365D TWAP (yearly reference)
Trading Days vs Calendar Days:
Toggle between trading days (5D, 22D, 66D, 252D) or calendar days (7D, 30D, 90D, 365D) to match your analysis style.
Divergence Analysis - High Probability Reversals:
The most powerful signals occur when price and oscillator diverge at extreme levels:
Bullish Divergence (Oversold):
• Price makes lower lows
• Oscillator makes higher lows
• Both at oversold levels (-2 or lower)
• Strong buy signal - price weakness not confirmed by TWAP
Bearish Divergence (Overbought):
• Price makes higher highs
• Oscillator makes lower highs
• Both at overbought levels (+2 or higher)
• Strong sell signal - price strength not confirmed by TWAP
Hidden Bullish Divergence:
• Price makes higher lows
• Oscillator makes lower lows
• At oversold levels
• Trend continuation signal - pullback in uptrend
Hidden Bearish Divergence:
• Price makes lower highs
• Oscillator makes higher highs
• At overbought levels
• Trend continuation signal - rally in downtrend
Divergence Confluence Zones:
Maximum Confluence Setup:
• Divergence at extreme levels (±2+ std dev)
• Multiple timeframe confirmation
• Key support/resistance levels
• Volume confirmation
• Highest probability reversal
Divergence Trading Rules:
• Wait for clear divergence formation
• Confirm at extreme oscillator levels
• Enter on divergence confirmation
• Stop loss beyond recent swing
• Target return to zero line or opposite extreme
Key Features:
• Zero Line - Neutral position where price equals TWAP
• Overbought/Oversold Levels - Default ±2 standard deviations (customizable)
• Smoothing - SMA filter to reduce noise
• Info Table - Shows current values and timeframe mapping
• Alerts - Zero line crosses and overbought/oversold conditions
Trading Applications:
Mean Reversion Strategy:
• Enter long when oscillator crosses above oversold level (-2)
• Enter short when oscillator crosses below overbought level (+2)
• Exit when returning to zero line
Trend Following:
• Stay long while oscillator remains above zero
• Stay short while oscillator remains below zero
• Use extreme readings as potential reversal signals
Risk Management:
• Use overbought/oversold levels as stop-loss references
• Scale position size based on oscillator magnitude
• Combine with other indicators for confirmation
Mathematical Foundation:
Oscillator = (Current Price - TWAP) / Standard Deviation
Where:
• TWAP = Time-weighted average price over selected period
• Standard Deviation = Statistical measure of price dispersion
• Result = Number of standard deviations from mean
Best Practices:
• Use on higher timeframes for trend analysis
• Use on lower timeframes for entry timing
• Combine with volume analysis for confirmation
• Adjust overbought/oversold levels based on market volatility
• Consider market structure and support/resistance levels
Perfect For:
• Scalping - 1m charts with 1D TWAP
• Day Trading - 5m-15m charts with 7D TWAP
• Swing Trading - 1h-4h charts with 30D TWAP
• Position Trading - Daily charts with 365D TWAP
Moons Bearish Pullback Detector# Moons Bearish Pullback Detector
## Overview
**Moons Bearish Pullback Detector** is a trend following indicator intended to identify bearish trend pullbacks to enter on price continuation.
This indicator is useful for setting watchlist alerts! Configure your pullback rules and have it monitor your watchlist for you. You will be alerted when pullbacks have occurred and are starting to continue in the trend direction.
## How It Works
### Bearish Trend Detection
The indicator identifies a bearish trend based on a configurable MA basis
### Pullback Identification
Once in a bearish trend, the indicator tracks:
Swing Lows: Continuously monitors and updates the lowest point in the trend
Pullback Start: Detects the first green candle after establishing new lows
Pullback Duration: Monitors pullback length (configurable number of bars)
Pullback Depth: Ensures pullbacks don't violate a key moving average (optional)
### Multi-Layer Filtering System
The indicator employs several optional filters to ensure signal quality:
Volume Filter: Set a minimum daily volume to ensure sufficient liquidity
Pullback Duration Filter: Pick a min and max bar count you like to see in a pullback.
Pullback Depth Filter: Monitors that pullbacks don't close above the desired EMA, maintaining trend strength
Validation Filter: Checks higher timeframe moving average for trend confirmation
Context Filter: Analyzes even higher timeframe for broader market context
### Alert System
The indicator generates alerts when:
All filtering conditions are met
Price crosses back below the configured alert line
This signals potential continuation of the bearish trend and gives warning to place potential orders
## Key Features
### Alerts
The indicator is useful for driving a watchlist alert to notify you when a pullback is starting to continue the trend.
### Visual Elements
Bollinger Bands: Optional display of 1 and 2 standard deviation bands
Moving Averages: 20 EMA (basis), 50 EMA, and 10 EMA (pullback filter)
Trend High Line: Yellow line showing current swing low during pullbacks
Alert Line: Entry signal line positioned below swing low
Background Highlighting: Gray for normal pullbacks, red tint when rules aren't met
Labels: Price labels at swing lows and depth violation warnings
Wick Detection: Tags bullish and bearish wicks for helpful spotting in your analysis
### Information Table
Comprehensive status table to show the state of your filters and rules as price plays out.
### Configuration Options
Moving average settings
Display Options
Alert Configuration
Filter Settings
## Best Use Cases
Swing Trading: Identify high-probability entries during trend pullbacks
Trend Following: Stay aligned with strong bearish momentum
Risk Management: Multiple filters help avoid false signals
Multi-Timeframe Analysis: Ensures broader market context alignment
## Trading Applications
This indicator works best when:
Markets are in clear downtrends
Sufficient volume is present
Multiple timeframes align
Used in conjunction with proper risk management
The Moons Pullback Detector provides traders with a systematic approach to identifying and capitalizing on pullback opportunities in strong bearish trends, combining technical rigor with practical usability.
---
*Note: This indicator is for educational purposes. Past performance does not guarantee future results. Always use proper risk management and consider multiple factors when making trading decisions.*
Moons Bullish Pullback Detector# Moons Pullback Detector
## Overview
**Moons Pullback Detector** is a trend following indicator intended to identify bullish trend pullbacks to enter on price continuation.
This indicator is useful for setting watchlist alerts! Configure your pullback rules and have it monitor your watchlist for you. You will be alerted when pullbacks have occurred and are starting to continue in the trend direction.
## How It Works
### Bullish Trend Detection
The indicator identifies a bullish trend based on a configurable MA basis
### Pullback Identification
Once in a bullish trend, the indicator tracks:
Swing Highs: Continuously monitors and updates the highest point in the trend
Pullback Start: Detects the first red candle after establishing new highs
Pullback Duration: Monitors pullback length (configurable number of bars)
Pullback Depth: Ensures pullbacks don't violate a key moving average (optional)
### Multi-Layer Filtering System
The indicator employs several optional filters to ensure signal quality:
Volume Filter: Set a minimum daily volume to ensure sufficient liquidity
Pullback Duration Filter: Pick a min and max bar count you like to see in a pullback.
Pullback Depth Filter: Monitors that pullbacks don't close below the desired EMA, maintaining trend strength
Validation Filter: Checks higher timeframe moving average for trend confirmation
Context Filter: Analyzes even higher timeframe for broader market context
### Alert System
The indicator generates alerts when:
All filtering conditions are met
Price crosses back above the configured alert line
This signals potential continuation of the bullish trend and gives warning to place potential orders
## Key Features
### Alerts
The indicator is useful for driving a watchlist alert to notify you when a pullback is starting to continue the trend.
### Visual Elements
Bollinger Bands: Optional display of 1 and 2 standard deviation bands
Moving Averages: 20 EMA (basis), 50 EMA, and 10 EMA (pullback filter)
Trend High Line: Yellow line showing current swing high during pullbacks
Alert Line: Entry signal line positioned below swing high
Background Highlighting: Gray for normal pullbacks, red tint when depth violated
Labels: Price labels at swing highs and depth violation warnings
Wick Detection: Tags bullish and bearish wicks for helpful spotting in your analysis
### Information Table
Comprehensive status table to show the state of your filters and rules as price plays out.
### Configuration Options
Moving average settings
Display Options
Alert Configuration
Filter Settings
## Best Use Cases
Swing Trading: Identify high-probability entries during trend pullbacks
Trend Following: Stay aligned with strong bullish momentum
Risk Management: Multiple filters help avoid false signals
Multi-Timeframe Analysis: Ensures broader market context alignment
## Trading Applications
This indicator works best when:
Markets are in clear uptrends
Sufficient volume is present
Multiple timeframes align bullishly
Used in conjunction with proper risk management
The Moons Pullback Detector provides traders with a systematic approach to identifying and capitalizing on pullback opportunities in strong bullish trends, combining technical rigor with practical usability.
---
*Note: This indicator is for educational purposes. Past performance does not guarantee future results. Always use proper risk management and consider multiple factors when making trading decisions.*
Artharjan ADXArtharjan ADX (AADX) by Rrahul Desai @Artharjan
📌 Overview
The Artharjan ADX (AADX) is an advanced implementation of the Average Directional Index (ADX) with customizable moving averages, momentum thresholds, and visually intuitive grading of bullish and bearish strength.
Unlike the standard ADX indicator that only shows trend strength, AADX adds graded bullish/bearish conditions, alerts, smoothed DI signals, histogram visualizations, and background color fills to help traders quickly interpret market conditions.
It is designed for traders who want early detection of trend strength, clean visual cues, and automated alert triggers for both bullish and bearish momentum setups.
⚙️ Key Features
🔹 Customizable Calculations
DI Length (default 13) – controls sensitivity of directional indicators.
+/- DI Smoothing – smooths DI signals with user-selected MA.
Multiple Moving Average Types – SMA, EMA, WMA, RMA, VWMA, ALMA, Hull, SWMA, SMMA, TMA.
ADX Smoothing – define how smooth/fast the ADX reacts.
🔹 Flexible Display
Toggle between line plots or histogram view.
Adjustable plot thickness.
Option to plot averages of ADX, +DI, -DI for confirmation.
Configurable background fills:
ADX above/below momentum threshold.
ADX rising/falling color shading.
Trend-grade based color intensity.
🔹 Momentum & Thresholds
Momentum Level (default 25) → defines “strong trend” zone.
Crossover Threshold (default 15) → helps detect early DI crossovers.
Color-coded histogram bars for +DI vs -DI difference:
Above/below zero.
Rising/falling momentum.
🔹 Bullish & Bearish Grading System
The indicator assigns grades from 1 to 5 for both bullish and bearish setups, based on DI and ADX conditions:
Bullish Grades
Grade 1 → Very Weak Bullish
Grade 2 → Weak Bullish
Grade 3 → Moderate Bullish
Grade 4 → Strong Bullish
Grade 5 → Very Strong Bullish
Bearish Grades
Grade 1 → Very Weak Bearish
Grade 2 → Weak Bearish
Grade 3 → Moderate Bearish
Grade 4 → Strong Bearish
Grade 5 → Very Strong Bearish
Labels are automatically plotted above bars to indicate the active grade.
🔹 Alerts
Bullish Alert → when +DI crosses above its average below the threshold OR bullish conditions are met.
Bearish Alert → when -DI crosses above its average below the threshold OR bearish conditions are met.
These alerts make it possible to automate trading signals for scalping, intraday, and swing trading.
📊 Use Cases
Trend Strength Measurement
Spot when markets shift from range-bound to trending.
Confirm the reliability of breakouts with strong ADX readings.
Bullish vs Bearish Control
Compare +DI vs -DI strength to gauge trend direction.
Identify trend reversals early with DI slope changes.
Momentum Confirmation
Use ADX rising + DI grades to validate trade entries.
Filter false breakouts with weak ADX.
Trade Grading System
Enter aggressively on Grade 4–5 signals.
Stay cautious on Grade 1–2 signals.
Automated Alerts & Screening
Combine AADX alerts with strategy rules.
Build scanners to highlight strong ADX setups across multiple stocks.
🎯 Trader’s Advantage
More powerful than standard ADX → Adds slope, grading, alerts, and visualization.
Adaptable to any style → Works for intraday scalping, swing trading, and positional analysis.
Visual clarity → Color fills, histograms, and labels simplify decision-making.
Customizable smoothing → Adjusts to fast or slow markets.
✅ Closing Note
The Artharjan ADX (AADX) transforms the traditional ADX into a complete trend and momentum analyzer. It helps traders detect, confirm, and act on directional strength with clarity and confidence.
With Thanks,
Rrahul Desai
@Artharjan
