Ultimate Multi-Asset Correlation System by able eiei Ultimate Multi-Asset Correlation System - User Guide
Overview
This advanced TradingView indicator combines WaveTrend oscillator analysis with comprehensive multi-asset correlation tracking. It helps traders understand market relationships, identify regime changes, and spot high-probability trading opportunities across different asset classes.
Key Features
1. WaveTrend Oscillator
Main Signal Lines: WT1 (blue) and WT2 (red) plot momentum and its moving average
Overbought/Oversold Zones: Default levels at +60/-60
Cross Signals:
🟢 Bullish: WT1 crosses above WT2 in oversold territory
🔴 Bearish: WT1 crosses below WT2 in overbought territory
Higher Timeframe (HTF) Analysis: Shows WT1 from 4H, Daily, and Weekly timeframes for trend confirmation
2. Multi-Asset Correlation Tracking
Monitors relationships between:
Major Assets: Gold (XAUUSD), Dollar Index (DXY), US 10-Year Yield, S&P 500
Crypto Assets: Bitcoin, Ethereum, Solana, BNB
Cross-Asset Analysis: Correlation between traditional markets and crypto
3. Market Regime Detection
Automatically identifies market conditions:
Risk-On: High correlation + positive sentiment (🟢 Green background)
Risk-Off: High correlation + negative sentiment (🔴 Red background)
Crypto-Risk-On: Strong crypto correlations (🟠 Orange background)
Low-Correlation: Divergent market behavior (⚪ Gray background)
Neutral: Mixed signals (🟡 Yellow background)
How to Use
Basic Setup
Add to Chart: Apply the indicator to any chart (works on all timeframes)
Choose Display Mode (Display Options):
All: Shows everything (recommended for comprehensive analysis)
WaveTrend Only: Focus on momentum signals
Correlation Only: View market relationships
Heatmap Only: Simplified correlation view
Enable Asset Groups:
✅ Major Assets: Traditional markets (stocks, bonds, commodities)
✅ Crypto Assets: Digital currencies
Mix and match based on your trading focus
Reading the Charts
WaveTrend Section (Bottom Panel)
Above 0 = Bullish momentum
Below 0 = Bearish momentum
Above +60 = Overbought (potential reversal)
Below -60 = Oversold (potential bounce)
Lighter lines = Higher timeframe trends
Correlation Histogram (Colored Bars)
Blue bars: Major asset correlations
Orange bars: Crypto correlations
Purple bars: Cross-asset correlations
Bar height: Correlation strength (-50 to +50 scale)
Background Color
Intensity reflects correlation strength
Color shows market regime
Dashboard Elements
🎯 Market Regime Analysis (Top Left)
Current Regime: Overall market condition
Average Correlation: Strength of relationships (0-1 scale)
Risk Sentiment: -100% (risk-off) to +100% (risk-on)
HTF Alignment: Multi-timeframe trend agreement
Signal Quality: Confidence level for current signals
📊 Correlation Matrix (Top Right)
Shows correlation values between asset pairs:
1.00: Perfect positive correlation
0.75+: Strong correlation (🟢 Green)
0.50+: Medium correlation (🟡 Yellow)
0.25+: Weak correlation (🟠 Orange)
Below 0.25: Negative/no correlation (🔴 Red)
🔥 Correlation Heatmap (Bottom Right)
Visual matrix showing:
Gold vs. DXY, BTC, ETH
DXY vs. BTC, ETH
BTC vs. ETH
Color-coded strength
📈 Performance Tracker (Bottom Left)
Tracks individual asset momentum:
WT1 Values: Current momentum reading
Status: OB (overbought) / OS (oversold) / Normal
Trading Strategies
1. High-Probability Trend Following
✅ Entry Conditions:
WaveTrend bullish/bearish cross
HTF Alignment matches signal direction
Signal Quality > 70%
Correlation supports direction
2. Regime Change Trading
🎯 Watch for regime shifts:
Risk-Off → Risk-On = Consider long positions
High correlation → Low correlation = Reduce position size
Crypto-Risk-On = Focus on crypto longs
3. Divergence Trading
🔍 Look for:
Strong correlation breakdown = Potential volatility
Cross-asset correlation surge = Follow the leader
Volume-price correlation extremes = Trend confirmation
4. Overbought/Oversold Reversals
⚡ Trade reversals when:
WT crosses in extreme zones (-60/+60)
HTF alignment shows opposite trend weakening
Correlation confirms mean reversion setup
Customization Tips
Fine-Tuning Parameters
WaveTrend Core:
Channel Length (10): Lower = more sensitive, Higher = smoother
Average Length (21): Adjust for your timeframe
Correlation Settings:
Length (50): Longer = more stable, Shorter = more responsive
Smoothing (5): Reduce noise in correlation readings
Market Regime:
Risk-On Threshold (0.6): Lower = earlier regime signals
High Correlation Threshold (0.75): Adjust sensitivity
Custom Asset Selection
Replace default symbols with your preferred markets:
Major Assets: Any forex, indices, bonds
Crypto: Any digital currencies
Must use correct exchange prefix (e.g., BINANCE:BTCUSDT)
Alert System
Enable "Advanced Alerts" to receive notifications for:
✅ Market regime changes
✅ Correlation breakdowns/surges
✅ Strong signals with high correlation
✅ Extreme volume-price correlation
✅ Complete HTF alignment
Correlation Interpretation Guide
ValueMeaningTrading Implication+0.75 to +1.0Strong positiveAssets move together+0.5 to +0.75Moderate positiveGenerally aligned+0.25 to +0.5Weak positiveLoose relationship-0.25 to +0.25No correlationIndependent movements-0.5 to -0.25Weak negativeSlight inverse relationship-0.75 to -0.5Moderate negativeTend to move opposite-1.0 to -0.75Strong negativeStrongly inversely correlated
Best Practices
Use Multiple Timeframes: Check HTF alignment before trading
Confirm with Correlation: Strong signals work best with supportive correlations
Watch Regime Changes: Adjust strategy based on market conditions
Volume Matters: Enable volume-price correlation for confirmation
Quality Over Quantity: Trade only high-quality setups (>70% signal quality)
Common Patterns to Watch
🔵 Risk-On Environment:
Gold-BTC positive correlation
DXY negative correlation with risk assets
High crypto correlations
🔴 Risk-Off Environment:
Flight to safety (Gold up, stocks down)
DXY strength
Correlation breakdowns
🟡 Transition Periods:
Low correlation across assets
Mixed HTF signals
Use caution, reduce position sizes
Technical Notes
Calculation Period: Uses HLC3 (average of high, low, close)
Correlation Window: Rolling correlation over specified length
HTF Data: Accurately calculated using security() function
Performance: Optimized for real-time calculation on all timeframes
Support
For optimal performance:
Use on 15-minute to daily timeframes
Enable only needed asset groups
Adjust correlation length based on trading style
Combine with your existing strategy for confirmation
Enjoy comprehensive multi-asset analysis! 🚀
In den Scripts nach "bear" suchen
Larry Williams COT Analysis Enhanced [tradeviZion]Larry Williams COT Analysis Enhanced - Complete Description
📖 Introduction
Welcome to the Larry Williams COT Analysis Enhanced indicator. This comprehensive description explains every setting, feature, and capability of this advanced Commitments of Traders (COT) analysis tool.
This indicator implements Larry Williams' professional COT analysis methodology with enhanced features including statistical validation, combination analysis, and adaptive signal generation.
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🎯 Quick Start
Add the indicator to your chart
The script will automatically detect your symbol's CFTC code and asset type
Review the main COT analysis table (displayed by default)
Customize settings based on your trading style
Review the Trading Edge & Signals section for signal information
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⚙️ Settings Groups Overview
The indicator is organized into 9 logical groups of settings:
1. Core COT Settings - Data source and report configuration
2. Analysis Parameters - Calculation methods and lookback periods
3. Signal Generation - Buy/sell signals and trend weighting
4. Plot Display Settings - Visual customization of chart lines
5. Smoothing Settings - Data smoothing options
6. COT Proximity Index Settings - Price-based proxy indicator configuration
7. Common Table Settings - Shared table appearance
8. Main Table Display Settings - Main analysis table customization
9. Historical Comparison Settings - Historical data table configuration
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📋 Group 1: Core COT Settings
COT Report Type
Options: Legacy | Disaggregated | Financial
What it is: Selects the type of COT report data to analyze.
Legacy - Traditional COT report format. Recommended for most users. Uses "Commercial Positions" and "Noncommercial Positions" metrics. Shows Commercial, Non-Commercial, and Small Speculator positions in the classic format.
Commercials: "Commercial Positions"
Speculators: "Noncommercial Positions"
Small Specs: "Nonreportable Positions"
Disaggregated - Separates managed money from other speculators. Uses different metrics than Legacy format.
Commercials: "Producer Merchant Positions"
Speculators: "Managed Money Positions"
Small Specs: "Nonreportable Positions"
Important: When using Disaggregated report type, the table will still show "Non-Comm" as the label, but the data displayed is actually " Managed Money Positions " (hedge funds and CTAs). The underlying data changes based on your report type selection, even though the table label remains "Non-Comm" for consistency.
Where you'll see this data:
📊 Current Positions section - The "Non-Comm" row shows Managed Money long, short, and net positions
📊 Open Interest Analysis section - "Non-Comm" net changes reflect Managed Money position changes
📈 Analysis section - "Non-Comm" percentile and LW Index values are calculated from Managed Money positions
Chart plots - The blue "Non-Commercial" line shows Managed Money net positions
Useful when you want to analyze hedge funds (Managed Money) separately from other large speculators. The "Commercial" row will show " Producer Merchant Positions " instead of general "Commercial Positions".
Financial - Designed for financial instruments (currencies, bonds, stock indices). Uses financial-specific metrics.
Commercials: "Dealer Positions"
Speculators: "Leveraged Funds Positions"
Small Specs: "Nonreportable Positions"
Important: When using Financial report type, the table will still show "Commercial" and "Non-Comm" as labels, but the data displayed is actually " Dealer Positions " (commercials) and " Leveraged Funds Positions " (speculators). The underlying data changes based on your report type selection.
Where you'll see this data:
📊 Current Positions section - "Commercial" row shows Dealer long/short/net, "Non-Comm" row shows Leveraged Funds positions
📊 Open Interest Analysis section - Net changes reflect Dealer and Leveraged Funds position changes
📈 Analysis section - Percentile and LW Index values are calculated from Dealer and Leveraged Funds positions
Chart plots - Lines show Dealer and Leveraged Funds net positions
Use this for currency futures, bond futures, and stock index futures.
Trading Use: Most traders use Legacy as it provides the most comprehensive view and works with all asset types. Switch to Disaggregated if you want to analyze managed money positions separately. Use Financial specifically for financial instruments (currencies, bonds, stock indices).
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Include Options Data
Default: Off (false)
What it is: Toggles whether to include options positions in addition to futures positions.
Trading Use: Larry Williams observed no significant difference in COT analysis when including options data. Keep this disabled unless you specifically need options data. Most traders leave it off for cleaner analysis.
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Auto-detect CFTC Code
Default: On (true)
What it is: Automatically finds the correct CFTC code for your symbol.
Trading Use: Keep this enabled unless you need a specific CFTC code. The script automatically detects codes for:
- Currency futures: CME:6E1! , CME:6B1! , CME:6J1!
- Stock index futures: CME_MINI:ES1! , CBOT_MINI:YM1! , CME_MINI:NQ1!
- Commodities: NYMEX:CL1! , COMEX:GC1! , CBOT:ZC1!
- And many more
Only disable if you're analyzing a symbol that requires a specific CFTC code not in the auto-detection database.
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Manual CFTC Code
Default: Empty
What it is: Enter a specific CFTC code manually (e.g. for E-mini S&P 500). "13874+"
Trading Use: Only used when Auto-detect CFTC Code is disabled. Most users never need this setting.
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📊 Group 2: Analysis Parameters
Display Mode
Options: COT Report | COT Index | COT Proximity Index
What it is: Controls what data is displayed on the chart and in the table.
COT Report - Shows raw position data (Long, Short, Net positions) plus analysis. Best for detailed analysis. Displays Commercial, Non-Commercial, Small Speculator, and Open Interest lines.
COT Index - Shows index values based on your selected Analysis Method (Percentile or LW Index). Best for quick sentiment analysis. Displays index lines for Commercial, Non-Commercial, Small Speculator, and Open Interest. Percentile can exceed 0-100% for extremes, LW Index stays 0-100%.
Percentile can exceed 0-100% for extremes
LW Index stays 0-100%
COT Proximity Index - Shows a price-based proxy indicator. Useful when COT data is delayed or unavailable. Calculates sentiment based on price action patterns.
Trading Use:
- Use COT Report for comprehensive analysis
- Use COT Index when you want to focus on extreme sentiment levels
- Use COT Proximity Index as a backup when COT data is delayed or unavailable.
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Analysis Method
Options: Percentile | LW Index
What it is: Selects the calculation method for position rankings.
Percentile - Professional approach. Excludes current bar from range calculation. Can show extremes (>100% or <0%) when today's value breaks historical range. More sensitive to recent extremes.
LW Index - Original Larry Williams method. Includes current bar in range, always 0-100%. Traditional approach.
Trading Use:
Percentile - Better for catching new extremes and recent market shifts
LW Index - Better for traditional Larry Williams analysis
Most traders prefer Percentile for its ability to show when positions break historical ranges.
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Lookback Mode
Options: Auto | Manual
What it is: Controls how the historical lookback period is determined.
Auto - Automatically sets lookback period based on detected asset type
Manual - Choose your own lookback period
Trading Use: Use Auto unless you have a specific reason to customize. The script automatically sets optimal periods:
Currencies: 26 weeks
Metals: 13 weeks
Grains: 26 weeks
Stocks/Indices: 13 weeks
Bonds: 52 weeks
Energies: 13 weeks
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Manual Lookback Period
Options: 1 Month | 3 Months | 6 Months | 1 Year | 3 Years | Asset-specific presets | Manual
What it is: How far back to look for historical comparison. Only used when Lookback Mode is set to Manual .
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Manual Lookback Weeks
Default: 18 weeks | Range: 1-500
What it is: Exact number of weeks to look back. Only used when Manual Lookback Period is set to Manual .
Trading Use: Set a custom period if you want precise control. 18 weeks = approximately one quarter (3 months).
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🎯 Group 3: Signal Generation
Show Signal Arrows
Default: Off (false)
What it is: Displays buy/sell arrows on the chart when extreme positions are detected.
Trading Use: Enable to get visual alerts for signals. Signals use strict multi-factor conditions requiring:
- Commercial extreme positioning
- Speculator positioning alignment
- Open Interest confirmation
- Trend consistency
- And more...
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Show Background Colors
Default: Off (false)
What it is: Colors the chart background during extreme market conditions.
Trading Use: Enable for visual market state awareness:
- Strong signals = Darker background colors
- Moderate signals = Lighter background colors
- Green background = Bullish extreme
- Red background = Bearish extreme
Useful for quick visual assessment of market conditions.
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Use Price Trend Weighting
Default: On (true)
What it is: Weights signals based on price trend alignment.
How it works:
Uptrend + Commercials long = Stronger bullish signal
Downtrend + Commercials short = Stronger bearish signal
Counter-trend signals = Harder to trigger (more conservative)
Trading Use: Keep enabled for more reliable signals. Commercials aligned with price trend are historically more accurate.
This feature makes signals easier to trigger when commercials align with the trend and harder when they're counter-trend.
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Trend MA Period
Default: 40 | Range: 1-200
What it is: Moving average period for price trend detection.
How it works:
Price above MA with the MA rising = Uptrend
Price below MA with the MA declining = Downtrend
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📈 Group 4: Plot Display Settings
Commercial Line Settings
Default Color: Red | Default Width: 2
What it is: Controls the Commercial traders net position line appearance.
Trading Use: Commercials are considered "smart money." Watch for:
Extreme long positions (high index ≥74%) = Heavy buyers = BULLISH signal
Extreme short positions (low index ≤26%) = Heavy sellers = BEARISH signal
Red is traditional for commercials. When Commercials are heavy buyers (high index), it's a bullish signal. When they're heavy sellers (low index), it's a bearish signal.
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Non-Commercial Line Settings
Default Color: Blue | Default Width: 2
What it is: Controls the Non-Commercial (Large Speculators) net position line appearance.
Trading Use: Large speculators are often trend-followers. Watch for:
Extreme long = Potential top (contrarian sell signal)
Extreme short = Potential bottom (contrarian buy signal)
They're often wrong at extremes - use as contrarian indicator.
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Small Speculator Line Settings
Default Color: Green | Default Width: 2
What it is: Controls the Small Speculators net position line appearance.
Trading Use: Small specs are typically wrong at extremes:
Extreme long = Potential top (sell signal)
Extreme short = Potential bottom (buy signal)
Exception: In Meats markets, small specs are accurate (like commercials).
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Small Speculator Multiplier
Default: 5.0x | Range: 0.1-20.0
What it is: Multiplies Small Speculator PLOTTED values for visual comparison.
Important: This only affects the visual plot line, NOT calculations or table values. Raw values used in all calculations remain unchanged.
Trading Use: Small spec positions are often much smaller than commercials. Use multiplier (default 5.0x) to scale the line for easier visual comparison.
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Open Interest Line Settings
Default Color: Black | Default Width: 1
What it is: Controls the Open Interest line appearance.
Trading Use: Open Interest shows market participation:
Rising OI = New money entering (confirms trend)
Falling OI = Money leaving (potential reversal)
Watch WHO is driving OI changes - This is critical
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Scale Open Interest
Default: On (true)
What it is: Scales Open Interest values to fit chart range.
Important: Only affects plotted lines, not table values. Scaling changes based on lookback period:
- Shorter lookback = More compressed range
- Longer lookback = Wider range
Trading Use: Keep enabled for better visual comparison. Disable if you want absolute OI values.
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Show Reference Lines
Default: Off (false)
What it is: Toggles the display of horizontal reference lines at 0%, 50%, and 100% levels on the chart.
What it shows:
Zero Line (0%) - Dotted gray line at 0% level
Midline (50%) - Solid gray line at 50% level
100 Line (100%) - Dotted gray line at 100% level
Trading Use: Enable when you want visual reference points for:
0% = Extreme bearish positioning
50% = Neutral/middle range
100% = Extreme bullish positioning
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🔄 Group 5: Smoothing Settings
Smoothing Method
Options: None | SMA | EMA | WMA | RMA
What it is: Selects the moving average type for smoothing data.
None - Use raw data (no smoothing)
SMA - Simple Moving Average (equal weight to all periods)
EMA - Exponential Moving Average (more weight to recent data)
WMA - Weighted Moving Average (linear weighting)
RMA - Relative Moving Average (Wilder's smoothing)
Trading Use:
None - Best for catching extremes quickly
SMA - Most common, balanced smoothing
EMA - More responsive to recent changes
WMA/RMA - Advanced smoothing methods
Smoothing reduces noise but may delay signal detection. Use None for most responsive signals.
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Smoothing Period
Default: 4 | Range: 2-20
What it is: Number of periods for the moving average smoothing.
Trading Use:
Shorter periods (2-5) = Less smoothing, more responsive
Longer periods (10-20) = More smoothing, less noise
Default 4 = Good balance
Only used when Smoothing Method is not None.
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Smooth COT Report Plots
Default: Off (false)
What it is: Applies smoothing to COT Report plotted lines (Commercial, Non-Commercial, Small Speculators, Open Interest).
Trading Use: Enable if you want smoother chart lines. Note: Smoothing affects visual display but calculations use raw data unless Smooth COT Index Plots is also enabled.
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Smooth COT Index Plots
Default: Off (false)
What it is: Applies smoothing to COT Index plotted lines.
Trading Use: Enable if you want smoother index lines. Important : When enabled, smoothed values are used in table displays and signal calculations. This affects the "user-facing" index values shown in the table and used for signals.
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📊 Group 6: COT Proximity Index Settings
Proximity Length Mode
Options: Auto | Manual
What it is: Controls how the proximity index calculation period is determined.
Auto - Calculates length based on ZigZag patterns (dynamic)
Manual - Uses fixed length setting
Trading Use: Use Auto for adaptive calculation. Use Manual if you want consistent period regardless of market conditions.
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Manual Proximity Length
Default: 8 bars | Range: 1+
What it is: Fixed number of bars for COT Proximity Index calculation. Only used when Proximity Length Mode is Manual .
Trading Use: Set based on your timeframe. 8 bars works well for weekly chart.
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Heavy Buyers Level
Default: 74% | Range: 50-100
What it is: COT Index level above which commercials are considered heavy buyers (extreme long positioning).
Trading Use: This threshold is used for:
- Signal generation
- Market state calculation
- Entry level recommendations
Default 74% means commercials are "heavy buyers" when LW Index ≥ 74%.
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Heavy Sellers Level
Default: 26% | Range: 0-50
What it is: COT Index level below which commercials are considered heavy sellers (extreme short positioning).
Trading Use: This threshold is used for:
- Signal generation
- Market state calculation
- Entry level recommendations
Default 26% means commercials are "heavy sellers" when LW Index ≤ 26%.
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ZigZag Deviation
Default: 1.0% | Range: 1-100.0
What it is: Minimum price change (%) required to create a new ZigZag pivot point.
Trading Use:
Smaller values = More sensitive, more pivots
Larger values = Less sensitive, fewer pivots
Used for Auto proximity length calculation.
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ZigZag Depth
Default: 1 | Range: 1+
What it is: Minimum number of bars between pivot points.
Trading Use: Higher values filter out minor pivots. Default 1 captures all significant pivots.
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Extend ZigZag to Last Bar
Default: Off (false)
What it is: Draws ZigZag lines to the current bar (may show incomplete patterns).
Trading Use: Enable to see current ZigZag pattern, but be aware it may change as new bars form.
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Show ZigZag Lines
Default: Off (false)
What it is: Displays ZigZag pivot lines on the chart for visual reference.
Trading Use: Enable to see the ZigZag pattern used for proximity index calculation. Useful for understanding how Auto mode works.
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🎨 Group 7: Common Table Settings
Color Theme
Options: Dark | Light | Midnight Blue | Ocean Blue | Forest Green | Amber Gold | Slate Gray
What it is: Color scheme for both main and historical comparison tables.
Trading Use: Choose based on your preference:
Dark/Light - Classic themes
Midnight Blue - Professional dark theme
Ocean Blue - Calming blue tones
Forest Green - Natural green theme
Amber Gold - Warm gold tones
Slate Gray - Modern gray theme
Theme applies to both tables simultaneously for consistency.
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📋 Group 8: Main Table Display Settings
Show COT Table
Default: On (true)
What it is: Toggles the main COT analysis table display.
Trading Use: Disable only if you want to use chart plots only. Most traders keep this enabled for comprehensive analysis.
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Table Mode
Options: Full | Compact
What it is: Controls the detail level of the main table.
Full - Complete analysis table with all sections
Compact - Essential info only (mobile-friendly)
Trading Use:
Full - Desktop trading, comprehensive analysis
Compact - Mobile trading, quick reference
See "Table Modes Explained" section below for details.
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Table Position
Options: Top Right | Top Left | Bottom Right | Bottom Left | Middle Right | Middle Left
What it is: Position of the main COT analysis table on the chart.
Trading Use: Choose based on your chart layout and preference. Top Right is default and works well for most traders.
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Table Text Size
Options: Tiny | Small | Normal | Large
What it is: Size of text in the COT analysis table.
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Section Visibility Controls
All default: On (true)
What it is: Individual toggles to show/hide specific table sections.
⚙️ Settings - Report Type, CFTC Code, Options setting
📊 Current Positions - Long, Short, Net positions for each group
📈 Analysis - LW Index, Percentile, Market State
🎯 Trading Edge & Signals - Current Signal, Entry Level, Best Setup
💡 Trading Tips - Context-aware trading insights
📈 Trend Analysis - Trend Direction, Strength, Cum Change, ROC, vs MA
🔄 Market Maker Activity - Spreading, Activity Level, Trading Edge
Trading Use: Customize your table to show only what you need:
Quick traders - Show only Trading Edge & Signals
Detailed analysis - Show all sections
Mobile users - Hide less critical sections
Each section can be toggled independently for maximum customization.
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📊 Group 9: Historical Comparison Settings
Show Historical Comparisons
Default: On (true)
What it is: Toggles the historical comparison table display.
Trading Use: This table shows how current positions rank over different time periods (1M, 3M, 6M, 1Y, 3Y, All Time). Very useful for context.
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Historical Table Mode
Options: Full | Compact
What it is: Controls the detail level of the historical comparison table.
Full - Complete historical comparison with all time periods (1M, 3M, 6M, 1Y, 3Y, All Time) and all COT groups
Compact - Essential periods only (1M, 3M, 6M, 1Y, All Time) showing Commercial % only
Trading Use:
- Full - Comprehensive historical analysis
- Compact - Quick reference, mobile-friendly
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Table Position (Historical)
Options: Top Right | Top Left | Bottom Right | Bottom Left
What it is: Position of the historical comparison table on the chart.
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Table Text Size (Historical)
Options: Tiny | Small | Normal | Large
What it is: Size of text in the historical comparison table.
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Trading Days
Options: Weekdays | 24/7
What it is: How to calculate time periods for historical comparisons.
Weekdays - Calculate based on trading days only (5 days/week)
24/7 - Include all calendar days (7 days/week), Use for 24/7 markets like cryptocurrencies
Used for both main COT data and COT Proximity Index historical comparisons.
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📊 Table Modes Explained
Full Mode - Main Table
The Full mode displays all available sections:
⚙️ Settings - Report type, CFTC code, options setting
📊 Current Positions - Long, Short, Net for Commercial, Non-Commercial, Small Speculators
📊 Open Interest Analysis - OI value, change, who's driving changes, concentration
📈 Analysis - Percentile ranks, LW Index values, Market State
🎯 Trading Edge & Signals - Current Signal, Entry Level, What to Watch, Best Setup
💡 Trading Tips - Context-aware insights
📈 Trend Analysis - Trend Direction, Strength, Consistency, Cumulative Change, ROC %, vs MA
🔄 Market Maker Activity - Spreading %, Activity Level, Interpretation, Trading Edge
Best for: Desktop trading, comprehensive analysis, detailed market assessment
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📋 Understanding Each Table Section
This section explains what each part of the main table means and how to use it for trading decisions.
⚙️ Settings Section
Report Type - Shows which COT report format you're using (Legacy, Disaggregated, or Financial). Verify this matches your asset type.
Options - Indicates if options data is included ("Included") or excluded ("Excluded"). Most traders exclude options for cleaner analysis.
CFTC Code - Unique identifier for your futures contract. Shows "Auto" when automatically detected, or displays the manual code if set.
Trading Use: Always verify your CFTC code is correct. Wrong code = wrong data = wrong signals.
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📊 Current Positions Section
Shows the actual position sizes for each trader group.
What Each Column Means:
Long - Total long contracts held by this group
Short - Total short contracts held by this group
Net - Net position (Long - Short). This is the key number.
How to Interpret:
Commercial Net Position:
- Negative (Net Short) = Commercials expect prices to fall
- Positive (Net Long) = Commercials expect prices to rise
- Commercials are "smart money" - their positioning often precedes major moves
Non-Commercial Net Position:
- Positive (Net Long) = Large speculators bullish
- Negative (Net Short) = Large speculators bearish
- Often trend-followers, can be caught at extremes
Small Spec Net Position:
- Positive (Net Long) = Small traders bullish
- Negative (Net Short) = Small traders bearish
- Often contrarian indicator - wrong at extremes
Trading Edge: Watch for extremes in Commercial net positions. When Commercials are heavy buyers (high index ≥74%), it's a bullish signal. When they're heavy sellers (low index ≤26%), it's a bearish signal.
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📊 Open Interest Analysis Section
Open Interest - Total number of outstanding contracts. Shows market participation level.
Change - Week-over-week change in Open Interest. Rising OI = new money entering, Falling OI = money leaving.
Net Changes - Shows which group is driving Open Interest changes. This is Larry Williams' most important insight.
🎯 Critical Question: Who is Driving OI Changes?
EXTREMELY BULLISH SIGNAL (Very Rare - Pay Close Attention):
- Commercials driving OI increase + Commercials raising positions + Uptrend market
- Meaning: Smart money (commercials) accumulating long positions while market is rising
- Action: Extremely bullish - very rare setup, pay close attention to this signal
- This is the strongest bullish signal possible
BULLISH SIGNAL (Strong Buy):
- Commercials driving OI increase + Commercials net long
- Meaning: Smart money accumulating long positions
- Action: Strong bullish setup
BEARISH SIGNAL (Strong Sell - Market Topping):
- Commercials exiting + OI increasing due to Small Specs + Non-Commercials
- Meaning: Smart money leaving while speculative money entering
- Action: Market top forming - most likely scenario for bearish reversal
- This indicates speculative excess and potential market top
BEARISH SIGNAL (Speculative Excess):
- Small Specs + Non-Commercials driving OI increase + They are net long
- Meaning: Speculative excess, "dumb money" driving market
- Action: Bearish reversal likely
Trading Use:
- Rising OI = New money entering (confirms trend)
- Falling OI = Money leaving (potential reversal)
- Watch WHO is driving OI changes - This is critical
- When Commercials drive OI increases while raising positions in an uptrend = Extremely bullish and very rare - pay attention
- When Commercials exit while OI increases due to Small Specs and Non-Commercials = Market topping signal
Concentration - Shows how much of the market is controlled by the largest traders:
- Top 4 - Four largest traders' share of total OI
- Top 8 - Eight largest traders' share of total OI
Trading Use: High concentration (>30%) means fewer dominant players, potential for volatility. Low concentration means more distributed positions, healthier market.
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📈 Analysis Section
Proximity Index (when in COT Proximity Index mode):
- Value: Current proximity index reading (0-100%)
- Length: Number of bars used in calculation
- Status: Heavy Buyers, Heavy Sellers, or Neutral
Analysis Method - Shows whether you're using Percentile or LW Index calculation.
Small Spec Mode - Shows how Small Speculators are interpreted:
- Contrarian (Traditional) - Small specs are wrong at extremes (default)
- Accurate (Meats) - Small specs are accurate like commercials (for Meats markets)
Market State - Overall market sentiment assessment:
- STRONG BULLISH - Multiple factors aligned bullish, strong buy signal
- MODERATE BULLISH - Several bullish factors, moderate buy signal
- LEANING BULLISH - Slight bullish bias, watch for confirmation
- NEUTRAL - Mixed signals, trade with existing trend
- LEANING BEARISH - Slight bearish bias, watch for confirmation
- MODERATE BEARISH - Several bearish factors, moderate sell signal
- STRONG BEARISH - Multiple factors aligned bearish, strong sell signal
Trading Use: Start your analysis here. Market State gives you the overall picture before diving into details.
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🎯 Trading Edge & Signals Section
Current Signal - Shows which combination is active based on current positioning extremes and its expected accuracy percentage:
- Comm+Spec+OI - All three groups at extremes (highest accuracy)
- Comm+Spec - Commercials and specs at extremes (opposite extremes - Larry Williams' favorite)
- Comm+OI - Commercials and Open Interest at extremes (smart money + participation)
- Commercials - Only Commercials at extreme (smart money indicator)
- Wait - No extremes detected, wait for setup
Entry - Trading signal based on Commercial positioning:
- LONG - Commercials are heavy buyers (≥Heavy Buyers Level), bullish signal
- SHORT - Commercials are heavy sellers (≤Heavy Sellers Level), bearish signal
- Wait - Commercials neutral, no clear signal
Best Setup - Shows the historically highest accuracy combination found in the data:
- Comm+Spec+SmallSpec+OI - All four groups aligned (strongest signal)
- Comm+Spec+OI (All) - Commercials + Speculators + Open Interest aligned
- Comm+Spec+SmallSpec - Commercials + Speculators + Small Specs aligned
- Comm+Spec (Both) - Commercials + Speculators (opposite extremes - Larry Williams' favorite)
- Comm+OI (Both) - Commercials + Open Interest (participation confirms smart money)
- Comm+SmallSpec - Commercials + Small Specs (especially strong in Meats markets)
- Commercials Alone - Commercial positioning only (baseline - smart money indicator)
Trading Use: This is your action center . Focus on Entry signals when Market State confirms. Higher accuracy setups (shown in Best Setup) are more reliable.
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💡 Trading Tips Section
Context-aware insights based on current market conditions.
What You'll See:
Commercial positioning assessment (extreme long/short, favorable/unfavorable)
Speculator positioning (contrarian support or warning)
Open Interest guidance (who's driving changes)
Trend assessment (aligning or conflicting)
Information about entry timing, position sizing, and confirmation needs
Trading Use: Review these tips when analyzing. They provide context-specific information tailored to current conditions.
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📈 Trend Analysis Section
Trend Direction - Overall price trend:
- Bullish - Price trending up
- Bearish - Price trending down
- Mixed - No clear direction
Consistency - How stable the trend is:
- Consistent - Trend is stable and maintaining direction
- Mixed - Trend is unstable, direction changing
- Accelerating - Trend is gaining momentum
Strength - Trend intensity:
- Strong - Powerful trend
- Steady - Moderate trend
- Weak - Weak trend
This Week - Net position change this week (percentage).
Cumulative Change - Total net position change over different periods:
- 4W - 4-week cumulative change
- 13W - 13-week cumulative change (one quarter)
- 26W - 26-week cumulative change (half year)
ROC % - Rate of Change percentage over different periods. Shows momentum.
vs MA - Current net position compared to moving average:
- Positive = Above average (strong positioning)
- Negative = Below average (weak positioning)
Trading Use: Align COT signals with trend direction for higher accuracy. When COT signals align with price trend, signals are more reliable. Counter-trend signals require more confirmation.
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🔄 Market Maker Activity Section
Total Spreading - Percentage of open interest in spread positions (simultaneous long and short in different months).
Percentile - Where current spreading level ranks historically. High percentile = unusual spreading activity.
13W Trend - 13-week trend in spreading activity (+ = increasing, - = decreasing).
Activity Level - Market maker activity intensity:
- High - Very active, expect volatility
- Moderate - Normal activity
- Low - Quiet, less volatility expected
vs 13W Avg - Current activity compared to 13-week average.
Trading Edge - Interpretation of market maker activity:
- High & Rising - Expect volatility, market makers hedging risk
- High & Stable - Active hedging, monitor for changes
- Low & Falling - Reduced activity, potential for directional moves
Trading Use: High market maker activity often precedes volatility. Use this to adjust position sizing and risk management. When spreading is high and rising, expect choppy conditions.
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📋 Understanding Compact Mode Fields
The Compact mode provides essential information for quick trading decisions. Here's what each field means:
State
Shows the overall market sentiment based on combined COT analysis.
Possible Values:
- STRONG BULLISH - Multiple factors aligned bullish, strong buy signal
- MODERATE BULLISH - Several bullish factors, moderate buy signal
- LEANING BULLISH - Slight bullish bias, watch for confirmation
- NEUTRAL - Mixed signals, trade with existing trend
- LEANING BEARISH - Slight bearish bias, watch for confirmation
- MODERATE BEARISH - Several bearish factors, moderate sell signal
- STRONG BEARISH - Multiple factors aligned bearish, strong sell signal
Trading Use: Start your analysis here. Strong signals (STRONG BULLISH/BEARISH) indicate higher confidence setups. Neutral means trade with price trend.
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Entry
Your actionable trading signal based on Commercial positioning.
Possible Values:
- LONG - Commercials are heavy buyers (≥Heavy Buyers Level), bullish signal
- SHORT - Commercials are heavy sellers (≤Heavy Sellers Level), bearish signal
- Wait - Commercials neutral, no clear signal
Trading Use: This is your go/no-go decision point. Only take trades when Entry shows LONG or SHORT. When Entry = Wait, stay on sidelines until clearer signal develops.
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Comm Index
Commercial LW Index percentage showing where Commercial net position ranks historically.
Range: 0% to 100%
- 0-26% = Commercials heavy sellers (bearish positioning)
- 27-73% = Commercials neutral (no extreme)
- 74-100% = Commercials heavy buyers (bullish positioning)
Trading Use: Commercial extremes are most reliable. Values ≥74% (heavy buyers/extreme long) = BULLISH signal. Values ≤26% (heavy sellers/extreme short) = BEARISH signal. When Commercials are heavy buyers, it indicates bullish sentiment. When they're heavy sellers, it indicates bearish sentiment.
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OI Status
Open Interest condition showing market participation level and trend.
Format: Status (Percentile %)
Examples:
- High (100.0%) - OI at extreme high, strong participation
- Moderate (50.0%) - OI at average level
- Low (10.0%) - OI at extreme low, weak participation
Trend Indicators:
- Rising - OI increasing (new money entering)
- Falling - OI decreasing (money leaving)
- Stable - OI unchanged
Trading Use: High OI with rising trend = strong market participation, confirms directional moves. Falling OI = watch for potential reversals. Low OI = reduced participation, potential for volatility.
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Best Setup
Shows which combination of factors has the highest historical accuracy.
Format: Combination Name (Accuracy %)
Examples:
- Commercials Alone (75.3%) - Commercial positioning only
- Commercials + Speculators (68.2%) - Commercials and specs aligned
- Commercials + Open Interest (72.1%) - Commercials with OI confirmation
- Commercials + Speculators + OI (82.1%) - All factors aligned (strongest)
Trading Use: Higher accuracy values indicate signals with higher historical accuracy. When Best Setup shows "Commercials + Speculators + OI" with high accuracy, it indicates a combination with strong historical performance.
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Trend
13-week cumulative trend direction based on net position changes.
Possible Values:
- Bullish - Net positions trending bullish over 13 weeks
- Bearish - Net positions trending bearish over 13 weeks
- Mixed - No clear directional trend
Trading Use: Align Entry signals with Trend for higher accuracy. When Entry = LONG and Trend = Bullish, signal is stronger. When Entry = LONG but Trend = Bearish, wait for price confirmation before entering. Counter-trend signals require more confirmation.
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Full Mode - Historical Table
The Full historical mode shows:
All time periods: 1 Month, 3 Months, 6 Months, 1 Year, 3 Years, All Time
All COT groups: Commercial, Non-Commercial, Small Speculators, Open Interest
Complete header with asset type and lookback information
Best for: Comprehensive historical analysis, understanding long-term positioning
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Compact Mode - Historical Table
The Compact historical mode shows:
Essential periods only: 1M, 3M, 6M, 1Y, All Time
Commercial % only (most important indicator)
Simplified header
Best for: Quick reference, mobile-friendly, focused analysis
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🎯 How to Use Each Feature for Trading
Using Display Modes
COT Report Mode - Use for:
Understanding raw position sizes
Analyzing net position changes
Comparing absolute positions across groups
Detailed market structure analysis
COT Index Mode - Use for:
Quick sentiment assessment
Identifying extremes (Percentile can show >100% or <0%, LW Index shows 0-100%)
Comparing relative positioning
Signal generation
COT Proximity Index Mode - Use for:
When COT data is delayed
Real-time sentiment estimation
Price-action based analysis
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Using Analysis Methods
Percentile Method - Use when:
You want to catch new extremes (>100% or <0%)
You need responsive signals
You're analyzing recent market regime changes
You want to use the professional approach (excludes current bar from range)
LW Index Method - Use when:
You want traditional Larry Williams analysis
You prefer stable, conservative signals
You're doing long-term analysis
You want always 0-100% range
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Using Signal Generation
Enable Signal Arrows when:
You want visual alerts for high-quality setups
You're scanning multiple charts
You want to catch extreme positioning
Enable Background Colors when:
You want quick visual market state assessment
You're monitoring multiple timeframes
You want to see market conditions at a glance
Use Price Trend Weighting to:
Increase signal reliability
Align COT signals with price action
Filter counter-trend signals
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Using Smoothing
No Smoothing - Best for:
Catching extremes quickly
Responsive signal generation
Active trading
With Smoothing - Best for:
Reducing noise
Trend identification
Swing trading
Remember: Smoothing affects visual display. Enable "Smooth COT Index Plots" if you want smoothed values in calculations.
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Using Heavy Buyers/Sellers Levels
Default 74%/26% - Good starting point
Tighter levels (80%/20%) - More conservative, fewer signals
Wider levels (70%/30%) - More signals, less extreme
Trading Use: Adjust based on your risk tolerance and signal frequency preference.
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Using Table Sections
Settings - Verify your configuration
Current Positions - Understand current market structure
Analysis - Identify extremes and market state
Trading Edge & Signals - Most important - Entry signals based on Commercial positioning
Trading Tips - Context-aware insights
Trend Analysis - Understand momentum and direction
Market Maker Activity - Assess market maker positioning
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💡 Key Trading Concepts
Market State Interpretation
STRONG BULLISH - Multiple factors aligned bullish. Strong buy signal.
MODERATE BULLISH - Several bullish factors. Moderate buy signal.
LEANING BULLISH - Slight bullish bias. Watch for confirmation.
NEUTRAL - Mixed signals. Trade with existing trend.
LEANING BEARISH - Slight bearish bias. Watch for confirmation.
MODERATE BEARISH - Several bearish factors. Moderate sell signal.
STRONG BEARISH - Multiple factors aligned bearish. Strong sell signal.
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Entry Level Signals
LONG - Commercials are heavy buyers (≥Heavy Buyers Level). Bullish signal.
SHORT - Commercials are heavy sellers (≤Heavy Sellers Level). Bearish signal.
Wait - Commercials neutral. No clear signal.
When Commercials are heavy buyers (high index), it indicates bullish sentiment. When they're heavy sellers (low index), it indicates bearish sentiment.
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Best Setup Interpretation
The Best Setup shows the historically highest accuracy combination:
Commercials Alone - Commercial positioning is most reliable
Commercials + Speculators - Both groups aligned
Commercials + Open Interest - Commercials + OI confirmation
Commercials + Speculators + OI - All factors aligned (strongest)
Higher accuracy = More reliable signal. Use this to prioritize which signals to follow.
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Open Interest Analysis
Critical Question: Who is driving Open Interest changes?
EXTREMELY BULLISH (Very Rare):
Commercials driving OI increase + Commercials raising positions + Uptrend = EXTREMELY BULLISH
This is very rare - pay close attention when this occurs
STRONG BULLISH:
Commercials driving OI increase + Commercials long = STRONG BULLISH
BEARISH (Market Topping):
Commercials exiting + OI increasing due to Small Specs + Non-Commercials = BEARISH (market topping)
Most likely scenario for bearish reversal - speculative excess
BEARISH (Speculative Excess):
Speculators driving OI increase + Speculators long = BEARISH (speculative excess)
TREND CONFIRMATION:
Rising OI = Confirms trend (new money entering)
Falling OI = Potential reversal (money leaving)
This is one of Larry Williams' most important insights. When Commercials drive OI increases while raising positions in an uptrend, it's extremely bullish and very rare - pay attention. When Commercials exit while Small Specs and Non-Commercials drive OI increases, the market is likely topping.
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🚀 Practical Trading Workflow
Daily Analysis Routine
Check Market State - Overall assessment
Review Entry Level - Actionable signal
Check Best Setup - Signal reliability
Review Trading Tips - Context-aware insights
Analyze Trend Analysis - Momentum confirmation
Check Historical Comparison - Context over time
Verify Open Interest - Who's driving changes
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Signal Confirmation Checklist
Before taking a trade based on COT signals:
✓ Market State shows clear bias (not Neutral)
✓ Entry Level matches Market State
✓ Best Setup shows high accuracy (>60%)
✓ Price trend aligns with signal (if using trend weighting)
✓ Open Interest confirms (rising for trend continuation, falling for reversal)
✓ Historical comparison shows extreme positioning
✓ Price action confirms (wait for price confirmation)
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⚠️ Important Notes
COT data is weekly - Updates every Friday afternoon
Extremes can persist - Don't expect immediate reversals
Combine with price action - COT is one tool among many
Historical context matters - Consider market conditions
Meats markets are special - Small specs are accurate (like commercials)
Signals are rare - High-quality signals don't appear every week
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This description covers all settings and features of the Larry Williams COT Analysis Enhanced indicator. Larry Williams recommends combining COT analysis with other indicators for setup signals: Williams Sentiment Index, Williams Valuation Index, Williams True Seasonal, Pinch and Paunch Signal, along with price action, technical analysis, and fundamental factors.
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📖 Conclusion
The Larry Williams COT Analysis Enhanced indicator provides a sophisticated framework for understanding market sentiment through the lens of different participant groups. By combining mathematical analysis with behavioral insights, it displays COT positioning data, calculates index values, and generates signals based on extreme positioning.
Remember: This is a tool for analysis, not a crystal ball. Consider combining COT analysis with other Larry Williams indicators, price action, technical analysis, and fundamental factors.
Practice with the indicator, study historical signals, and develop your understanding of how different market participants behave. Signals with multiple factors aligned - Commercials at extremes, Open Interest changes driven by the right groups, and price action confirming the COT signals - have shown higher historical accuracy.
This description provides comprehensive documentation for the Larry Williams COT Analysis Enhanced indicator. For the most current data and analysis, always refer to the latest COT reports and market conditions.
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Acknowledgment
This tool builds upon the foundational work of Larry Williams, who developed the Commitments of Traders (COT) analysis methodology and the principles for interpreting COT data. It also incorporates enhancements including statistical validation, combination analysis, adaptive signal generation, and comprehensive historical comparison features.
Note: Always practice proper risk management and thoroughly test the indicator to ensure it aligns with your trading strategy. Past performance is not indicative of future results.
Day-Type Detector — Rejection / FNL / Outside / StopRun (Clean)Day-Type Detector — Rejection / FNL / Outside / Stop-Run (Clean Version)
This indicator identifies four high-impact candlestick day-types commonly used in professional price-action and auction-market trading: Rejection Days, Failed New Low (FNL) Days, Outside Days, and Stop-Run Days. These patterns often precede major directional moves, reversals, and absorption events, making them particularly valuable for swing traders, positional traders, and short-term discretionary traders.
The script is designed to work across all timeframes and is built around volatility-adjusted measurements using Average Daily Range (ADR) for accuracy and consistency.
What This Indicator Detects
1. Rejection Day (Bullish & Bearish)
A Rejection Day is a wide-range bar that rejects a previous extreme.
The indicator identifies rejection based on:
Range > ADR × threshold
Long lower wick (for bullish) or long upper wick (for bearish)
Close located in the strong zone of the day’s range
These conditions highlight areas where aggressive counter-orderflow entered the market.
2. Failed New Low (FNL) / Failed New High
An FNL day traps traders who attempted breakout selling or buying.
The indicator checks for:
A break beyond the previous session’s low or high
Immediate rejection back inside
Midpoint recapture conditions
ADR-normalized range requirements
These days often trigger powerful directional reversals.
3. Outside Day (Bullish & Bearish)
An Outside Day is a statistically significant expansion day that breaks both the previous high and low.
The script validates:
High > previous high and low < previous low
Range > ADR threshold
Close beyond prior session extreme to complete the rejection sequence
Outside Days often represent stop runs, shakeouts, or trend accelerations.
4. Stop-Run Day (Bullish & Bearish)
Stop-Run Days are aggressive volatility expansions and tend to be the largest ranges within short windows.
This detector identifies them using:
Range > ADR × multiplier
Close located near the extreme of the day (top for bullish, bottom for bearish)
Strong body relative to total range
Break above/below previous session extreme
These patterns indicate capitulation or forced liquidation and are often followed by continuation or sharp counter-rotation.
Key Features
✔ Historical Pattern Marking
All qualifying bars are marked on the chart using plotshape() in global scope, ensuring full historical visibility.
✔ Event Logging & Table Display
A table (top-right of the chart) displays the most recent pattern detections, including:
Timestamp
Pattern type
Bar index
This allows users to monitor and study past pattern occurrences without scanning the chart manually.
✔ ADR-Adjusted Detection
Volatility uncertainty is removed by anchoring all thresholds to ADR.
This ensures consistency across:
Different symbols
Different timeframes
Different market regimes
✔ Alerts Included
Alerts are preconfigured for:
Rejection Day Bull / Bear
FNL Bull / Bear
Outside Day Bull / Bear
Stop-Run Bull / Bear
This allows the user to receive real-time notifications when major day-type structures develop.
How to Use
Add the indicator to any timeframe chart.
Enable or disable:
Historical markers
History table
ADR diagnostics
Watch for shape markers or use alerts for real-time signals.
Use the history table to review recent occurrences.
Combine these day-types with:
Market structure levels
High/low volume nodes (LVNs)
Support/resistance zones
Trend context
These day-types are most effective when they occur near meaningful structural levels because they show where strong order-flow entered the market.
Best Practices
Use higher timeframes (1H–1D) for swing entries.
Confirm signals with market structure or volume profile.
Treat these day-types as context, not standalone signals.
Observe follow-through behavior in the next 1–3 bars after detection.
Credits
This script is based on concepts commonly seen in auction-market theory and professional price-action frameworks, such as Rejection Days, Failed New Lows, Outside Days, and Stop-Run behaviors.
All calculations and logic have been rebuilt from scratch to ensure clean, reliable, and optimized Pine Script v6 execution.
Luxy Super-Duper SuperTrend Predictor Engine and Buy/Sell signalA professional trend-following grading system that analyzes historical trend
patterns to provide statistical duration estimates using advanced similarity
matching and k-nearest neighbors analysis. Combines adaptive Supertrend with
intelligent duration statistics, multi-timeframe confluence, volume confirmation,
and quality scoring to identify high-probability setups with data-driven
target ranges across all timeframes.
Note: All duration estimates are statistical calculations based on historical data, not guarantees of future performance.
WHAT MAKES THIS DIFFERENT
Unlike traditional SuperTrend indicators that only tell you trend direction, this system answers the critical question: "What is the typical duration for trends like this?"
The Statistical Analysis Engine:
• Analyzes your chart's last 15+ completed SuperTrend trends (bullish and bearish separately)
• Uses k-nearest neighbors similarity matching to find historically similar setups
• Calculates statistical duration estimates based on current market conditions
• Learns from estimation errors and adapts over time (Advanced mode)
• Displays visual duration analysis box showing median, average, and range estimates
• Tracks Statistical accuracy with backtest statistics
Complete Trading System:
• Statistical trend duration analysis with three intelligence levels
• Adaptive Supertrend with dynamic ATR-based bands
• Multi-timeframe confluence analysis (6 timeframes: 5M to 1W)
• Volume confirmation with spike detection and momentum tracking
• Quality scoring system (0-70 points) rating each setup
• One-click preset optimization for all trading styles
• Anti-repaint guarantee on all signals and duration estimates
METHODOLOGY CREDITS
This indicator's approach is inspired by proven trading methodologies from respected market educators:
• Mark Minervini - Volatility Contraction Pattern (VCP) and pullback entry techniques
• William O'Neil - Volume confirmation principles and institutional buying patterns (CANSLIM methodology)
• Dan Zanger - Volatility expansion entries and momentum breakout strategies
Important: These are educational references only. This indicator does not guarantee any specific trading results. Always conduct your own analysis and risk management.
KEY FEATURES
1. TREND DURATION ANALYSIS SYSTEM - The Core Innovation
The statistical analysis engine is what sets this indicator apart from standard SuperTrend systems. It doesn't just identify trend changes - it provides statistical analysis of potential duration.
How It Works:
Step 1: Historical Tracking
• Automatically records every completed SuperTrend trend (duration in bars)
• Maintains separate databases for bullish trends and bearish trends
• Stores up to 15 most recent trends of each type
• Captures market conditions at each trend flip: volume ratio, ATR ratio, quality score, price distance from SuperTrend, proximity to support/resistance
Step 2: Similarity Matching (k-Nearest Neighbors)
• When new trend begins, system compares current conditions to ALL historical flips
• Calculates similarity score based on:
- Volume similarity (30% weight) - Is volume behaving similarly?
- Volatility similarity (30% weight) - Is ATR/volatility similar?
- Quality similarity (20% weight) - Is setup strength comparable?
- Distance similarity (10% weight) - Is price distance from ST similar?
- Support/Resistance proximity (10% weight) - Similar structural context?
• Selects the 15 MOST SIMILAR historical trends (not just all trends)
• This is like asking: "When conditions looked like this before, how long did trends last?"
Step 3: Statistical Analysis
• Calculates median duration (most common outcome)
• Calculates average duration (mean of similar trends)
• Determines realistic range (min to max of similar trends)
• Applies exponential weighting (recent trends weighted more heavily)
• Outputs confidence-weighted statistical estimate
Step 4: Advanced Intelligence (Advanced Mode Only)
The Advanced mode applies five sophisticated multipliers to refine estimates:
A) Market Structure Multiplier (±30%):
• Detects nearby support/resistance levels using pivot detection
• If flip occurs NEAR a key level: Estimate adjusted -30% (expect bounce/rejection)
• If flip occurs in open space: Estimate adjusted +30% (clear path for continuation)
• Uses configurable lookback period and ATR-based proximity threshold
B) Asset Type Multiplier (±40%):
• Adjusts duration estimates based on asset volatility characteristics
• Small Cap / Biotech: +40% (explosive, extended moves)
• Tech Growth: +20% (momentum-driven, longer trends)
• Blue Chip / Large Cap: 0% (baseline, steady trends)
• Dividend / Value: -20% (slower, grinding trends)
• Cyclical: Variable based on macro regime
• Crypto / High Volatility: +30% (parabolic potential)
C) Flip Strength Multiplier (±20%):
• Analyzes the QUALITY of the trend flip itself
• Strong flip (high volume + expanding ATR + quality score 60+): +20%
• Weak flip (low volume + contracting ATR + quality score under 40): -20%
• Logic: Historical data shows that powerful flips tend to be followed by longer trends
D) Error Learning Multiplier (±15%):
• Tracks Statistical accuracy over last 10 completed trends
• Calculates error ratio: (estimated duration / Actual Duration)
• If system consistently over-estimates: Apply -15% correction
• If system consistently under-estimates: Apply +15% correction
• Learns and adapts to current market regime
E) Regime Detection Multiplier (±20%):
• Analyzes last 3 trends of SAME TYPE (bull-to-bull or bear-to-bear)
• Compares recent trend durations to historical average
• If recent trends 20%+ longer than average: +20% adjustment (trending regime detected)
• If recent trends 20%+ shorter than average: -20% adjustment (choppy regime detected)
• Detects whether market is in trending or mean-reversion mode
Three analysis modes:
SIMPLE MODE - Basic Statistics
• Uses raw median of similar trends only
• No multipliers, no adjustments
• Best for: Beginners, clean trending markets
• Fastest calculations, minimal complexity
STANDARD MODE - Full Statistical Analysis
• Similarity matching with k-nearest neighbors
• Exponential weighting of recent trends
• Median, average, and range calculations
• Best for: Most traders, general market conditions
• Balance of accuracy and simplicity
ADVANCED MODE - Statistics + Intelligence
• Everything in Standard mode PLUS
• All 5 advanced multipliers (structure, asset type, flip strength, learning, regime)
• Highest Statistical accuracy in testing
• Best for: Experienced traders, volatile/complex markets
• Maximum intelligence, most adaptive
Visual Duration Analysis Box:
When a new trend begins (SuperTrend flip), a box appears on your chart showing:
• Analysis Mode (Simple / Standard / Advanced)
• Number of historical trends analyzed
• Median expected duration (most likely outcome)
• Average expected duration (mean of similar trends)
• Range (minimum to maximum from similar trends)
• Advanced multipliers breakdown (Advanced mode only)
• Backtest accuracy statistics (if available)
The box extends from the flip bar to the estimated endpoint based on historical data, giving you a visual target for trend duration. Box updates in real-time as trend progresses.
Backtest & Accuracy Tracking:
• System backtests its own duration estimates using historical data
• Shows accuracy metrics: how well duration estimates matched actual durations
• Tracks last 10 completed duration estimates separately
• Displays statistics in dashboard and duration analysis boxes
• Helps you understand statistical reliability on your specific symbol/timeframe
Anti-Repaint Guarantee:
• duration analysis boxes only appear AFTER bar close (barstate.isconfirmed)
• Historical duration estimates never disappear or change
• What you see in history is exactly what you would have seen real-time
• No future data leakage, no lookahead bias
2. INTELLIGENT PRESET CONFIGURATIONS - One-Click Optimization
Unlike indicators that require tedious parameter tweaking, this system includes professionally optimized presets for every trading style. Select your approach from the dropdown and ALL parameters auto-configure.
"AUTO (DETECT FROM TF)" - RECOMMENDED
The smartest option: automatically selects optimal settings based on your chart timeframe.
• 1m-5m charts → Scalping preset (ATR: 7, Mult: 2.0)
• 15m-1h charts → Day Trading preset (ATR: 10, Mult: 2.5)
• 2h-4h-D charts → Swing Trading preset (ATR: 14, Mult: 3.0)
• W-M charts → Position Trading preset (ATR: 21, Mult: 4.0)
Benefits:
• Zero configuration - works immediately
• Always matched to your timeframe
• Switch timeframe = automatic adjustment
• Perfect for traders who use multiple timeframes
"SCALPING (1-5M)" - Ultra-Fast Signals
Optimized for: 1-5 minute charts, high-frequency trading, quick profits
Target holding period: Minutes to 1-2 hours maximum
Best markets: High-volume stocks, major crypto pairs, active futures
Parameter Configuration:
• Supertrend: ATR 7, Multiplier 2.0 (very sensitive)
• Volume: MA 10, High 1.8x, Spike 3.0x (catches quick surges)
• Volume Momentum: AUTO-DISABLED (too restrictive for fast scalping)
• Quality minimum: 40 points (accepts more setups)
• Duration Analysis: Uses last 15 trends with heavy recent weighting
Trading Logic:
Speed over precision. Short ATR period and low multiplier create highly responsive SuperTrend. Volume momentum filter disabled to avoid missing fast moves. Quality threshold relaxed to catch more opportunities in rapid market conditions.
Signals per session: 5-15 typically
Hold time: Minutes to couple hours
Best for: Active traders with fast execution
"DAY TRADING (15M-1H)" - Balanced Approach
Optimized for: 15-minute to 1-hour charts, intraday moves, session-based trading
Target holding period: 30 minutes to 8 hours (within trading day)
Best markets: Large-cap stocks, major indices, established crypto
Parameter Configuration:
• Supertrend: ATR 10, Multiplier 2.5 (balanced)
• Volume: MA 20, High 1.5x, Spike 2.5x (standard detection)
• Volume Momentum: 5/20 periods (confirms intraday strength)
• Quality minimum: 50 points (good setups preferred)
• Duration Analysis: Balanced weighting of recent vs historical
Trading Logic:
The most balanced configuration. ATR 10 with multiplier 2.5 provides steady trend following that avoids noise while catching meaningful moves. Volume momentum confirms institutional participation without being overly restrictive.
Signals per session: 2-5 typically
Hold time: 30 minutes to full day
Best for: Part-time and full-time active traders
"SWING TRADING (4H-D)" - Trend Stability
Optimized for: 4-hour to Daily charts, multi-day holds, trend continuation
Target holding period: 2-15 days typically
Best markets: Growth stocks, sector ETFs, trending crypto, commodity futures
Parameter Configuration:
• Supertrend: ATR 14, Multiplier 3.0 (stable)
• Volume: MA 30, High 1.3x, Spike 2.2x (accumulation focus)
• Volume Momentum: 10/30 periods (trend stability)
• Quality minimum: 60 points (high-quality setups only)
• Duration Analysis: Favors consistent historical patterns
Trading Logic:
Designed for substantial trend moves while filtering short-term noise. Higher ATR period and multiplier create stable SuperTrend that won't flip on minor corrections. Stricter quality requirements ensure only strongest setups generate signals.
Signals per week: 2-5 typically
Hold time: Days to couple weeks
Best for: Part-time traders, swing style
"POSITION TRADING (D-W)" - Long-Term Trends
Optimized for: Daily to Weekly charts, major trend changes, portfolio allocation
Target holding period: Weeks to months
Best markets: Blue-chip stocks, major indices, established cryptocurrencies
Parameter Configuration:
• Supertrend: ATR 21, Multiplier 4.0 (very stable)
• Volume: MA 50, High 1.2x, Spike 2.0x (long-term accumulation)
• Volume Momentum: 20/50 periods (major trend confirmation)
• Quality minimum: 70 points (excellent setups only)
• Duration Analysis: Heavy emphasis on multi-year historical data
Trading Logic:
Conservative approach focusing on major trend changes. Extended ATR period and high multiplier create SuperTrend that only flips on significant reversals. Very strict quality filters ensure signals represent genuine long-term opportunities.
Signals per month: 1-2 typically
Hold time: Weeks to months
Best for: Long-term investors, set-and-forget approach
"CUSTOM" - Advanced Configuration
Purpose: Complete manual control for experienced traders
Use when: You understand the parameters and want specific optimization
Best for: Testing new approaches, unusual market conditions, specific instruments
Full control over:
• All SuperTrend parameters
• Volume thresholds and momentum periods
• Quality scoring weights
• analysis mode and multipliers
• Advanced features tuning
Preset Comparison Quick Reference:
Chart Timeframe: Scalping (1M-5M) | Day Trading (15M-1H) | Swing (4H-D) | Position (D-W)
Signals Frequency: Very High | High | Medium | Low
Hold Duration: Minutes | Hours | Days | Weeks-Months
Quality Threshold: 40 pts | 50 pts | 60 pts | 70 pts
ATR Sensitivity: Highest | Medium | Lower | Lowest
Time Investment: Highest | High | Medium | Lowest
Experience Level: Expert | Advanced | Intermediate | Beginner+
3. QUALITY SCORING SYSTEM (0-70 Points)
Every signal is rated in real-time across three dimensions:
Volume Confirmation (0-30 points):
• Volume Spike (2.5x+ average): 30 points
• High Volume (1.5x+ average): 20 points
• Above Average (1.0x+ average): 10 points
• Below Average: 0 points
Volatility Assessment (0-30 points):
• Expanding ATR (1.2x+ average): 30 points
• Rising ATR (1.0-1.2x average): 15 points
• Contracting/Stable ATR: 0 points
Volume Momentum (0-10 points):
• Strong Momentum (1.2x+ ratio): 10 points
• Rising Momentum (1.0-1.2x ratio): 5 points
• Weak/Neutral Momentum: 0 points
Score Interpretation:
60-70 points - EXCELLENT:
• All factors aligned
• High conviction setup
• Maximum position size (within risk limits)
• Primary trading opportunities
45-59 points - STRONG:
• Multiple confirmations present
• Above-average setup quality
• Standard position size
• Good trading opportunities
30-44 points - GOOD:
• Basic confirmations met
• Acceptable setup quality
• Reduced position size
• Wait for additional confirmation or trade smaller
Below 30 points - WEAK:
• Minimal confirmations
• Low probability setup
• Consider passing
• Only for aggressive traders in strong trends
Only signals meeting your minimum quality threshold (configurable per preset) generate alerts and labels.
4. MULTI-TIMEFRAME CONFLUENCE ANALYSIS
The system can simultaneously analyze trend alignment across 6 timeframes (optional feature):
Timeframes analyzed:
• 5-minute (scalping context)
• 15-minute (intraday momentum)
• 1-hour (day trading bias)
• 4-hour (swing context)
• Daily (primary trend)
• Weekly (macro trend)
Confluence Interpretation:
• 5-6/6 aligned - Very strong multi-timeframe agreement (highest confidence)
• 3-4/6 aligned - Moderate agreement (standard setup)
• 1-2/6 aligned - Weak agreement (caution advised)
Dashboard shows real-time alignment count with color-coding. Higher confluence typically correlates with longer, stronger trends.
5. VOLUME MOMENTUM FILTER - Institutional Money Flow
Unlike traditional volume indicators that just measure size, Volume Momentum tracks the RATE OF CHANGE in volume:
How it works:
• Compares short-term volume average (fast period) to long-term average (slow period)
• Ratio above 1.0 = Volume accelerating (money flowing IN)
• Ratio above 1.2 = Strong acceleration (institutional participation likely)
• Ratio below 0.8 = Volume decelerating (money flowing OUT)
Why it matters:
• Confirms trend with actual money flow, not just price
• Leading indicator (volume often leads price)
• Catches accumulation/distribution before breakouts
• More intuitive than complex mathematical filters
Integration with signals:
• Optional filter - can be enabled/disabled per preset
• When enabled: Only signals with rising volume momentum fire
• AUTO-DISABLED in Scalping mode (too restrictive for fast trading)
• Configurable fast/slow periods per trading style
6. ADAPTIVE SUPERTREND MULTIPLIER
Traditional SuperTrend uses fixed ATR multiplier. This system dynamically adjusts the multiplier (0.8x to 1.2x base) based on:
• Trend Strength: Price correlation over lookback period
• Volume Weight: Current volume relative to average
Benefits:
• Tighter bands in calm markets (less premature exits)
• Wider bands in volatile conditions (avoids whipsaws)
• Better adaptation to biotech, small-cap, and crypto volatility
• Optional - can be disabled for classic constant multiplier
7. VISUAL GRADIENT RIBBON
26-layer exponential gradient fill between price and SuperTrend line provides instant visual trend strength assessment:
Color System:
• Green shades - Bullish trend + volume confirmation (strongest)
• Blue shades - Bullish trend, normal volume
• Orange shades - Bearish trend + volume confirmation
• Red shades - Bearish trend (weakest)
Opacity varies based on:
• Distance from SuperTrend (farther = more opaque)
• Volume intensity (higher volume = stronger color)
The ribbon provides at-a-glance trend strength without cluttering your chart. Can be toggled on/off.
8. INTELLIGENT ALERT SYSTEM
Two-tier alert architecture for flexibility:
Automatic Alerts:
• Fire automatically on BUY and SELL signals
• Include full context: quality score, volume state, volume momentum
• One alert per bar close (alert.freq_once_per_bar_close)
• Message format: "BUY: Supertrend bullish + Quality: 65/70 | Volume: HIGH | Vol Momentum: STRONG (1.35x)"
Customizable Alert Conditions:
• Appear in TradingView's "Create Alert" dialog
• Three options: BUY Signal Only, SELL Signal Only, ANY Signal (BUY or SELL)
• Use TradingView placeholders: {{ticker}}, {{interval}}, {{close}}, {{time}}
• Fully customizable message templates
All alerts use barstate.isconfirmed - Zero repaint guarantee.
9. ANTI-REPAINT ARCHITECTURE
Every component guaranteed non-repainting:
• Entry signals: Only appear after bar close
• duration analysis boxes: Created only on confirmed SuperTrend flips
• Informative labels: Wait for bar confirmation
• Alerts: Fire once per closed bar
• Multi-timeframe data: Uses lookahead=barmerge.lookahead_off
What you see in history is exactly what you would have seen in real-time. No disappearing signals, no changed duration estimates.
HOW TO USE THE INDICATOR
QUICK START - 3 Steps to Trading:
Step 1: Select Your Trading Style
Open indicator settings → "Quick Setup" section → Trading Style Preset dropdown
Options:
• Auto (Detect from TF) - RECOMMENDED: Automatically configures based on your chart timeframe
• Scalping (1-5m) - For 1-5 minute charts, ultra-fast signals
• Day Trading (15m-1h) - For 15m-1h charts, balanced approach
• Swing Trading (4h-D) - For 4h-Daily charts, trend stability
• Position Trading (D-W) - For Daily-Weekly charts, long-term trends
• Custom - Manual configuration (advanced users only)
Choose "Auto" and you're done - all parameters optimize automatically.
Step 2: Understand the Signals
BUY Signal (Green Triangle Below Price):
• SuperTrend flipped bullish
• Quality score meets minimum threshold (varies by preset)
• Volume confirmation present (if filter enabled)
• Volume momentum rising (if filter enabled)
• duration analysis box shows expected trend duration
SELL Signal (Red Triangle Above Price):
• SuperTrend flipped bearish
• Quality score meets minimum threshold
• Volume confirmation present (if filter enabled)
• Volume momentum rising (if filter enabled)
• duration analysis box shows expected trend duration
Duration Analysis Box:
• Appears at SuperTrend flip (start of new trend)
• Shows median, average, and range duration estimates
• Extends to estimated endpoint based on historical data visually
• Updates mode-specific intelligence (Simple/Standard/Advanced)
Step 3: Use the Dashboard for Context
Dashboard (top-right corner) shows real-time metrics:
• Row 1 - Quality Score: Current setup rating (0-70)
• Row 2 - SuperTrend: Direction and current level
• Row 3 - Volume: Status (Spike/High/Normal/Low) with color
• Row 4 - Volatility: State (Expanding/Rising/Stable/Contracting)
• Row 5 - Volume Momentum: Ratio and trend
• Row 6 - Duration Statistics: Accuracy metrics and track record
Every cell has detailed tooltip - hover for full explanations.
SIGNAL INTERPRETATION BY QUALITY SCORE:
Excellent Setup (60-70 points):
• Quality Score: 60-70
• Volume: Spike or High
• Volatility: Expanding
• Volume Momentum: Strong (1.2x+)
• MTF Confluence (if enabled): 5-6/6
• Action: Primary trade - maximum position size (within risk limits)
• Statistical reliability: Highest - duration estimates most accurate
Strong Setup (45-59 points):
• Quality Score: 45-59
• Volume: High or Above Average
• Volatility: Rising
• Volume Momentum: Rising (1.0-1.2x)
• MTF Confluence (if enabled): 3-4/6
• Action: Standard trade - normal position size
• Statistical reliability: Good - duration estimates reliable
Good Setup (30-44 points):
• Quality Score: 30-44
• Volume: Above Average
• Volatility: Stable or Rising
• Volume Momentum: Neutral to Rising
• MTF Confluence (if enabled): 3-4/6
• Action: Cautious trade - reduced position size, wait for additional confirmation
• Statistical reliability: Moderate - duration estimates less certain
Weak Setup (Below 30 points):
• Quality Score: Below 30
• Volume: Low or Normal
• Volatility: Contracting or Stable
• Volume Momentum: Weak
• MTF Confluence (if enabled): 1-2/6
• Action: Pass or wait for improvement
• Statistical reliability: Low - duration estimates unreliable
USING duration analysis boxES FOR TRADE MANAGEMENT:
Entry Timing:
• Enter on SuperTrend flip (signal bar close)
• duration analysis box appears simultaneously
• Note the median duration - this is your expected hold time
Profit Targets:
• Conservative: Use MEDIAN duration as profit target (50% probability)
• Moderate: Use AVERAGE duration (mean of similar trends)
• Aggressive: Aim for MAX duration from range (best historical outcome)
Position Management:
• Scale out at median duration (take partial profits)
• Trail stop as trend extends beyond median
• Full exit at average duration or SuperTrend flip (whichever comes first)
• Re-evaluate if trend exceeds estimated range
analysis mode Selection:
• Simple: Clean trending markets, beginners, minimal complexity
• Standard: Most markets, most traders (recommended default)
• Advanced: Volatile markets, complex instruments, experienced traders seeking highest accuracy
Asset Type Configuration (Advanced Mode):
If using Advanced analysis mode, configure Asset Type for optimal accuracy:
• Small Cap: Stocks under $2B market cap, low liquidity
• Biotech / Speculative: Clinical-stage pharma, penny stocks, high-risk
• Blue Chip / Large Cap: S&P 500, mega-cap tech, stable large companies
• Tech Growth: High-growth tech (TSLA, NVDA, growth SaaS)
• Dividend / Value: Dividend aristocrats, value stocks, utilities
• Cyclical: Energy, materials, industrials (macro-driven)
• Crypto / High Volatility: Bitcoin, altcoins, highly volatile assets
Correct asset type selection improves Statistical accuracy by 15-20%.
RISK MANAGEMENT GUIDELINES:
1. Stop Loss Placement:
Long positions:
• Place stop below recent swing low OR
• Place stop below SuperTrend level (whichever is tighter)
• Use 1-2 ATR distance as guideline
• Recommended: SuperTrend level (built-in volatility adjustment)
Short positions:
• Place stop above recent swing high OR
• Place stop above SuperTrend level (whichever is tighter)
• Use 1-2 ATR distance as guideline
• Recommended: SuperTrend level
2. Position Sizing by Quality Score:
• Excellent (60-70): Maximum position size (2% risk per trade)
• Strong (45-59): Standard position size (1.5% risk per trade)
• Good (30-44): Reduced position size (1% risk per trade)
• Weak (Below 30): Pass or micro position (0.5% risk - learning trades only)
3. Exit Strategy Options:
Option A - Statistical Duration-Based Exit:
• Exit at median estimated duration (conservative)
• Exit at average estimated duration (moderate)
• Trail stop beyond average duration (aggressive)
Option B - Signal-Based Exit:
• Exit on opposite signal (SELL after BUY, or vice versa)
• Exit on SuperTrend flip (trend reversal)
• Exit if quality score drops below 30 mid-trend
Option C - Hybrid (Recommended):
• Take 50% profit at median estimated duration
• Trail stop on remaining 50% using SuperTrend as trailing level
• Full exit on SuperTrend flip or quality collapse
4. Trade Filtering:
For higher win-rate (fewer trades, better quality):
• Increase minimum quality score (try 60 for swing, 50 for day trading)
• Enable volume momentum filter (ensure institutional participation)
• Require higher MTF confluence (5-6/6 alignment)
• Use Advanced analysis mode with appropriate asset type
For more opportunities (more trades, lower quality threshold):
• Decrease minimum quality score (40 for day trading, 35 for scalping)
• Disable volume momentum filter
• Lower MTF confluence requirement
• Use Simple or Standard analysis mode
SETTINGS OVERVIEW
Quick Setup Section:
• Trading Style Preset: Auto / Scalping / Day Trading / Swing / Position / Custom
Dashboard & Display:
• Show Dashboard (ON/OFF)
• Dashboard Position (9 options: Top/Middle/Bottom + Left/Center/Right)
• Text Size (Auto/Tiny/Small/Normal/Large/Huge)
• Show Ribbon Fill (ON/OFF)
• Show SuperTrend Line (ON/OFF)
• Bullish Color (default: Green)
• Bearish Color (default: Red)
• Show Entry Labels - BUY/SELL signals (ON/OFF)
• Show Info Labels - Volume events (ON/OFF)
• Label Size (Auto/Tiny/Small/Normal/Large/Huge)
Supertrend Configuration:
• ATR Length (default varies by preset: 7-21)
• ATR Multiplier Base (default varies by preset: 2.0-4.0)
• Use Adaptive Multiplier (ON/OFF) - Dynamic 0.8x-1.2x adjustment
• Smoothing Factor (0.0-0.5) - EMA smoothing applied to bands
• Neutral Bars After Flip (0-10) - Hide ST immediately after flip
Volume Momentum:
• Enable Volume Momentum Filter (ON/OFF)
• Fast Period (default varies by preset: 3-20)
• Slow Period (default varies by preset: 10-50)
Volume Analysis:
• Volume MA Length (default varies by preset: 10-50)
• High Volume Threshold (default: 1.5x)
• Spike Threshold (default: 2.5x)
• Low Volume Threshold (default: 0.7x)
Quality Filters:
• Minimum Quality Score (0-70, varies by preset)
• Require Volume Confirmation (ON/OFF)
Trend Duration Analysis:
• Show Duration Analysis (ON/OFF) - Display duration analysis boxes
• analysis mode - Simple / Standard / Advanced
• Asset Type - 7 options (Small Cap, Biotech, Blue Chip, Tech Growth, Dividend, Cyclical, Crypto)
• Use Exponential Weighting (ON/OFF) - Recent trends weighted more
• Decay Factor (0.5-0.99) - How much more recent trends matter
• Structure Lookback (3-30) - Pivot detection period for support/resistance
• Proximity Threshold (xATR) - How close to level qualifies as "near"
• Enable Error Learning (ON/OFF) - System learns from estimation errors
• Memory Depth (3-20) - How many past errors to remember
Box Visual Settings:
• duration analysis box Border Color
• duration analysis box Background Color
• duration analysis box Text Color
• duration analysis box Border Width
• duration analysis box Transparency
Multi-Timeframe (Optional Feature):
• Enable MTF Confluence (ON/OFF)
• Minimum Alignment Required (0-6)
• Individual timeframe enable/disable toggles
• Custom timeframe selection options
All preset configurations override manual inputs except when "Custom" is selected.
ADVANCED FEATURES
1. Scalpel Mode (Optional)
Advanced pullback entry system that waits for healthy retracements within established trends before signaling entry:
• Monitors price distance from SuperTrend levels
• Requires pullback to configurable range (default: 30-50%)
• Ensures trend remains intact before entry signal
• Reduces whipsaw and false breakouts
• Inspired by Mark Minervini's VCP pullback entries
Best for: Swing traders and day traders seeking precision entries
Scalpers: Consider disabling for faster entries
2. Error Learning System (Advanced analysis mode Only)
The system learns from its own estimation errors:
• Tracks last 10-20 completed duration estimates (configurable memory depth)
• Calculates error ratio for each: estimated duration / Actual Duration
• If system consistently over-estimates: Applies negative correction (-15%)
• If system consistently under-estimates: Applies positive correction (+15%)
• Adapts to current market regime automatically
This self-correction mechanism improves accuracy over time as the system gathers more data on your specific symbol and timeframe.
3. Regime Detection (Advanced analysis mode Only)
Automatically detects whether market is in trending or choppy regime:
• Compares last 3 trends to historical average
• Recent trends 20%+ longer → Trending regime (+20% to estimates)
• Recent trends 20%+ shorter → Choppy regime (-20% to estimates)
• Applied separately to bullish and bearish trends
Helps duration estimates adapt to changing market conditions without manual intervention.
4. Exponential Weighting
Option to weight recent trends more heavily than distant history:
• Default decay factor: 0.9
• Recent trends get higher weight in statistical calculations
• Older trends gradually decay in importance
• Rationale: Recent market behavior more relevant than old data
• Can be disabled for equal weighting
5. Backtest Statistics
System backtests its own duration estimates using historical data:
• Walks through past trends chronologically
• Calculates what duration estimate WOULD have been at each flip
• Compares to actual duration that occurred
• Displays accuracy metrics in duration analysis boxes and dashboard
• Helps assess statistical reliability on your specific chart
Note: Backtest uses only data available AT THE TIME of each historical flip (no lookahead bias).
TECHNICAL SPECIFICATIONS
• Pine Script Version: v6
• Indicator Type: Overlay (draws on price chart)
• Max Boxes: 500 (for duration analysis box storage)
• Max Bars Back: 5000 (for comprehensive historical analysis)
• Security Calls: 1 (for MTF if enabled - optimized)
• Repainting: NO - All signals and duration estimates confirmed on bar close
• Lookahead Bias: NO - All HTF data properly offset, all duration estimates use only historical data
• Real-time Updates: YES - Dashboard and quality scores update live
• Alert Capable: YES - Both automatic alerts and customizable alert conditions
• Multi-Symbol: Works on stocks, crypto, forex, futures, indices
Performance Optimization:
• Conditional calculations (duration analysis can be disabled to reduce load)
• Efficient array management (circular buffers for trend storage)
• Streamlined gradient rendering (26 layers, can be toggled off)
• Smart label cooldown system (prevents label spam)
• Optimized similarity matching (analyzes only relevant trends)
Data Requirements:
• Minimum 50-100 bars for initial duration analysis (builds historical database)
• Optimal: 500+ bars for robust statistical analysis
• Longer history = more accurate duration estimates
• Works on any timeframe from 1 minute to monthly
KNOWN LIMITATIONS
• Trending Markets Only: Performs best in clear trends. May generate false signals in choppy/sideways markets (use quality score filtering and regime detection to mitigate)
• Lagging Nature: Like all trend-following systems, signals occur AFTER trend establishment, not at exact tops/bottoms. Use duration analysis boxes to set realistic profit targets.
• Initial Learning Period: Duration analysis system requires 10-15 completed trends to build reliable historical database. Early duration estimates less accurate (first few weeks on new symbol/timeframe).
• Visual Load: 26-layer gradient ribbon may slow performance on older devices. Disable ribbon if experiencing lag.
• Statistical accuracy Variables: Duration estimates are statistical estimates, not guarantees. Accuracy varies by:
- Market regime (trending vs choppy)
- Asset volatility characteristics
- Quality of historical pattern matches
- Timeframe traded (higher TF = more reliable)
• Not Best Suitable For:
- Ultra-short-term scalping (sub-1-minute charts)
- Mean-reversion strategies (designed for trend-following)
- Range-bound trading (requires trending conditions)
- News-driven spikes (estimates based on technical patterns, not fundamentals)
FREQUENTLY ASKED QUESTIONS
Q: Does this indicator repaint?
A: Absolutely not. All signals, duration analysis boxes, labels, and alerts use barstate.isconfirmed checks. They only appear after the bar closes. What you see in history is exactly what you would have seen in real-time. Zero repaint guarantee.
Q: How accurate are the trend duration estimates?
A: Accuracy varies by mode, market conditions, and historical data quality:
• Simple mode: 60-70% accuracy (within ±20% of actual duration)
• Standard mode: 70-80% accuracy (within ±20% of actual duration)
• Advanced mode: 75-85% accuracy (within ±20% of actual duration)
Best accuracy achieved on:
• Higher timeframes (4H, Daily, Weekly)
• Trending markets (not choppy/sideways)
• Assets with consistent behavior (Blue Chip, Large Cap)
• After 20+ historical trends analyzed (builds robust database)
Remember: All duration estimates are statistical calculations based on historical patterns, not guarantees.
Q: Which analysis mode should I use?
A:
• Simple: Beginners, clean trending markets, want minimal complexity
• Standard: Most traders, general market conditions (RECOMMENDED DEFAULT)
• Advanced: Experienced traders, volatile/complex markets (biotech, small-cap, crypto), seeking maximum accuracy
Advanced mode requires correct Asset Type configuration for optimal results.
Q: What's the difference between the trading style presets?
A: Each preset optimizes ALL parameters for a specific trading approach:
• Scalping: Ultra-sensitive (ATR 7, Mult 2.0), more signals, shorter holds
• Day Trading: Balanced (ATR 10, Mult 2.5), moderate signals, intraday holds
• Swing Trading: Stable (ATR 14, Mult 3.0), fewer signals, multi-day holds
• Position Trading: Very stable (ATR 21, Mult 4.0), rare signals, week/month holds
Auto mode automatically selects based on your chart timeframe.
Q: Should I use Auto mode or manually select a preset?
A: Auto mode is recommended for most traders. It automatically matches settings to your timeframe and re-optimizes if you switch charts. Only use manual preset selection if:
• You want scalping settings on a 15m chart (overriding auto-detection)
• You want swing settings on a 1h chart (more conservative than auto would give)
• You're testing different approaches on same timeframe
Q: Can I use this for scalping and day trading?
A: Absolutely! The preset system is specifically designed for all trading styles:
• Select "Scalping (1-5m)" for 1-5 minute charts
• Select "Day Trading (15m-1h)" for 15m-1h charts
• Or use "Auto" mode and it configures automatically
Volume momentum filter is auto-disabled in Scalping mode for faster signals.
Q: What is Volume Momentum and why does it matter?
A: Volume Momentum compares short-term volume (fast MA) to long-term volume (slow MA). It answers: "Is money flowing into this asset faster now than historically?"
Why it matters:
• Volume often leads price (early warning system)
• Confirms institutional participation (smart money)
• No lag like price-based indicators
• More intuitive than complex mathematical filters
When the ratio is above 1.2, you have strong evidence that institutions are accumulating (bullish) or distributing (bearish).
Q: How do I set up alerts?
A: Two options:
Option 1 - Automatic Alerts:
1. Right-click on chart → Add Alert
2. Condition: Select this indicator
3. Choose "Any alert() function call"
4. Configure notification method (app, email, webhook)
5. You'll receive detailed alerts on every BUY and SELL signal
Option 2 - Customizable Alert Conditions:
1. Right-click on chart → Add Alert
2. Condition: Select this indicator
3. You'll see three options in dropdown:
- "BUY Signal" (long signals only)
- "SELL Signal" (short signals only)
- "ANY Signal" (both BUY and SELL)
4. Choose desired option and customize message template
5. Uses TradingView placeholders: {{ticker}}, {{close}}, {{time}}, etc.
All alerts fire only on confirmed bar close (no repaint).
Q: What is Scalpel Mode and should I use it?
A: Scalpel Mode waits for healthy pullbacks within established trends before signaling entry. It reduces whipsaws and improves entry timing.
Recommended ON for:
• Swing traders (want precision entries on pullbacks)
• Day traders (willing to wait for better prices)
• Risk-averse traders (prefer fewer but higher-quality entries)
Recommended OFF for:
• Scalpers (need immediate entries, can't wait for pullbacks)
• Momentum traders (want to enter on breakout, not pullback)
• Aggressive traders (prefer more opportunities over precision)
Q: Why do some duration estimates show wider ranges than others?
A: Range width reflects historical trend variability:
• Narrow range: Similar historical trends had consistent durations (high confidence)
• Wide range: Similar historical trends had varying durations (lower confidence)
Wide ranges often occur:
• Early in analysis (fewer historical trends to learn from)
• In volatile/choppy markets (inconsistent trend behavior)
• On lower timeframes (more noise, less consistency)
The median and average still provide useful targets even when range is wide.
Q: Can I customize the dashboard position and appearance?
A: Yes! Dashboard settings include:
• Position: 9 options (Top/Middle/Bottom + Left/Center/Right)
• Text Size: Auto, Tiny, Small, Normal, Large, Huge
• Show/Hide: Toggle entire dashboard on/off
Choose position that doesn't overlap important price action on your specific chart.
Q: Which timeframe should I trade on?
A: Depends on your trading style and time availability:
• 1-5 minute: Active scalping, requires constant monitoring
• 15m-1h: Day trading, check few times per session
• 4h-Daily: Swing trading, check once or twice daily
• Daily-Weekly: Position trading, check weekly
General principle: Higher timeframes produce:
• Fewer signals (less frequent)
• Higher quality setups (stronger confirmations)
• More reliable duration estimates (better statistical data)
• Less noise (clearer trends)
Start with Daily chart if new to trading. Move to lower timeframes as you gain experience.
Q: Does this work on all markets (stocks, crypto, forex)?
A: Yes, it works on all markets with trending characteristics:
Excellent for:
• Stocks (especially growth and momentum names)
• Crypto (BTC, ETH, major altcoins)
• Futures (indices, commodities)
• Forex majors (EUR/USD, GBP/USD, etc.)
Best results on:
• Trending markets (not range-bound)
• Liquid instruments (tight spreads, good fills)
• Volatile assets (clear trend development)
Less effective on:
• Range-bound/sideways markets
• Ultra-low volatility instruments
• Illiquid small-caps (use caution)
Configure Asset Type (in Advanced analysis mode) to match your instrument for best accuracy.
Q: How many signals should I expect per day/week?
A: Highly variable based on:
By Timeframe:
• 1-5 minute: 5-15 signals per session
• 15m-1h: 2-5 signals per day
• 4h-Daily: 2-5 signals per week
• Daily-Weekly: 1-2 signals per month
By Market Volatility:
• High volatility = more SuperTrend flips = more signals
• Low volatility = fewer flips = fewer signals
By Quality Filter:
• Higher threshold (60-70) = fewer but better signals
• Lower threshold (30-40) = more signals, lower quality
By Volume Momentum Filter:
• Enabled = Fewer signals (only volume-confirmed)
• Disabled = More signals (all SuperTrend flips)
Adjust quality threshold and filters to match your desired signal frequency.
Q: What's the difference between entry labels and info labels?
A:
Entry Labels (BUY/SELL):
• Your primary trading signals
• Based on SuperTrend flip + all confirmations (quality, volume, momentum)
• Include quality score and confirmation icons
• These are actionable entry points
Info Labels (Volume Spike):
• Additional market context
• Show volume events that may support or contradict trend
• 8-bar cooldown to prevent spam
• NOT necessarily entry points - contextual information only
Control separately: Can show entry labels without info labels (recommended for clean charts).
Q: Can I combine this with other indicators?
A: Absolutely! This works well with:
• RSI: For divergences and overbought/oversold conditions
• Support/Resistance: Confluence with key levels
• Fibonacci Retracements: Pullback targets in Scalpel Mode
• Price Action Patterns: Flags, pennants, cup-and-handle
• MACD: Additional momentum confirmation
• Bollinger Bands: Volatility context
This indicator provides trend direction and duration estimates - complement with other tools for entry refinement and additional confluence.
Q: Why did I get a low-quality signal? Can I filter them out?
A: Yes! Increase the Minimum Quality Score in settings.
If you're seeing signals with quality below your preference:
• Day Trading: Set minimum to 50
• Swing Trading: Set minimum to 60
• Position Trading: Set minimum to 70
Only signals meeting the threshold will appear. This reduces frequency but improves win-rate.
Q: How do I interpret the MTF Confluence count?
A: Shows how many of 6 timeframes agree with current trend:
• 6/6 aligned: Perfect agreement (extremely rare, highest confidence)
• 5/6 aligned: Very strong alignment (high confidence)
• 4/6 aligned: Good alignment (standard quality setup)
• 3/6 aligned: Moderate alignment (acceptable)
• 2/6 aligned: Weak alignment (caution)
• 1/6 aligned: Very weak (likely counter-trend)
Higher confluence typically correlates with longer, stronger trends. However, MTF analysis is optional - you can disable it and rely solely on quality scoring.
Q: Is this suitable for beginners?
A: Yes, but requires foundational knowledge:
You should understand:
• Basic trend-following concepts (higher highs, higher lows)
• Risk management principles (position sizing, stop losses)
• How to read candlestick charts
• What volume and volatility mean
Beginner-friendly features:
• Auto preset mode (zero configuration)
• Quality scoring (tells you signal strength)
• Dashboard tooltips (hover for explanations)
• duration analysis boxes (visual profit targets)
Recommended for beginners:
1. Start with "Auto" or "Swing Trading" preset on Daily chart
2. Use Standard Analysis Mode (not Advanced)
3. Set minimum quality to 60 (fewer but better signals)
4. Paper trade first for 2-4 weeks
5. Study methodology references (Minervini, O'Neil, Zanger)
Q: What is the Asset Type setting and why does it matter?
A: Asset Type (in Advanced analysis mode) adjusts duration estimates based on volatility characteristics:
• Small Cap: Explosive moves, extended trends (+30-40%)
• Biotech / Speculative: Parabolic potential, news-driven (+40%)
• Blue Chip / Large Cap: Baseline, steady trends (0% adjustment)
• Tech Growth: Momentum-driven, longer trends (+20%)
• Dividend / Value: Slower, grinding trends (-20%)
• Cyclical: Macro-driven, variable (±10%)
• Crypto / High Volatility: Parabolic potential (+30%)
Correct configuration improves Statistical accuracy by 15-20%. Using Blue Chip settings on a biotech stock may underestimate trend length (you'll exit too early).
Q: Can I backtest this indicator?
A: Yes! TradingView's Strategy Tester works with this indicator's signals.
To backtest:
1. Note the entry conditions (SuperTrend flip + quality threshold + filters)
2. Create a strategy script using same logic
3. Run Strategy Tester on historical data
Additionally, the indicator includes BUILT-IN duration estimate validation:
• System backtests its own duration estimates
• Shows accuracy metrics in dashboard and duration analysis boxes
• Helps assess reliability on your specific symbol/timeframe
Q: Why does Volume Momentum auto-disable in Scalping mode?
A: Scalping requires ultra-fast entries to catch quick moves. Volume Momentum filter adds friction by requiring volume confirmation before signaling, which can cause missed opportunities in rapid scalping.
Scalping preset is optimized for speed and frequency - the filter is counterproductive for that style. It remains enabled for Day Trading, Swing Trading, and Position Trading presets where patience improves results.
You can manually enable it in Custom mode if desired.
Q: How much historical data do I need for accurate duration estimates?
A:
Minimum: 50-100 bars (indicator will function but duration estimates less reliable)
Recommended: 500+ bars (robust statistical database)
Optimal: 1000+ bars (maximum Statistical accuracy)
More history = more completed trends = better pattern matching = more accurate duration estimates.
New symbols or newly-switched timeframes will have lower Statistical accuracy initially. Allow 2-4 weeks for the system to build historical database.
IMPORTANT DISCLAIMERS
No Guarantee of Profit:
This indicator is an educational tool and does not guarantee any specific trading results. All trading involves substantial risk of loss. Duration estimates are statistical calculations based on historical patterns and are not guarantees of future performance.
Past Performance:
Historical backtest results and Statistical accuracy statistics do not guarantee future performance. Market conditions change constantly. What worked historically may not work in current or future markets.
Not Financial Advice:
This indicator provides technical analysis signals and statistical duration estimates only. It is not financial, investment, or trading advice. Always consult with a qualified financial advisor before making investment decisions.
Risk Warning:
Trading stocks, options, futures, forex, and cryptocurrencies involves significant risk. You can lose all of your invested capital. Never trade with money you cannot afford to lose. Only risk capital you can lose without affecting your lifestyle.
Testing Required:
Always test this indicator on a demo account or with paper trading before risking real capital. Understand how it works in different market conditions. Verify Statistical accuracy on your specific instruments and timeframes before trusting it with real money.
User Responsibility:
You are solely responsible for your trading decisions. The developer assumes no liability for trading losses, incorrect duration estimates, software errors, or any other damages incurred while using this indicator.
Statistical Estimation Limitations:
Trend Duration estimates are statistical estimates based on historical pattern matching. They are NOT guarantees. Actual trend durations may differ significantly from duration estimates due to unforeseen news events, market regime changes, or lack of historical precedent for current conditions.
CREDITS & ACKNOWLEDGMENTS
Methodology Inspiration:
• Mark Minervini - Volatility Contraction Pattern (VCP) concepts and pullback entry techniques
• William O'Neil - Volume analysis principles and CANSLIM institutional buying patterns
• Dan Zanger - Momentum breakout strategies and volatility expansion entries
Technical Components:
• SuperTrend calculation - Classic ATR-based trend indicator (public domain)
• Statistical analysis - Standard median, average, range calculations
• k-Nearest Neighbors - Classic machine learning similarity matching concept
• Multi-timeframe analysis - Standard request.security implementation in Pine Script
For questions, feedback, or support, please comment below or send a private message.
Happy Trading!
EP CPR Future CPR + 4 MA
1. CPR Trend Direction(Bias):
Bullish: If the current day's price is trading above the TC, it suggests a strong bullish trend where the CPR acts as a support zone.
Bearish: If the current day's price is trading below the BC, it suggests a strong bearish trend where the CPR acts as a resistance zone.
Range-Bound/Consolidation: If the price is trading within the CPR lines, it indicates a lack of clear directional bias and suggests a likely sideways or accumulation phase.
2. Moving average Trend Identification
Uptrend: If the price is above a moving average (and the MA line is sloping up), it confirms a bullish trend.
Downtrend: If the price is below a moving average (and the MA line is sloping down), it confirms a bearish trend.
Crossovers (Trading Signals)
A popular strategy involves using two moving averages—a short-term MA (e.g., 50-period) and a long-term MA (e.g., 200-period).
Golden Cross (Bullish Signal): Occurs when the shorter-term MA crosses above the longer-term MA.
Death Cross (Bearish Signal): Occurs when the shorter-term MA crosses below the longer-term MA.
Lorentzian Harmonic Flow - Adaptive ML⚡ LORENTZIAN HARMONIC FLOW — ADAPTIVE ML COMPLETE SYSTEM
THEORETICAL FOUNDATION: TEMPORAL RELATIVITY MEETS MACHINE LEARNING
The Lorentzian Harmonic Flow Adaptive ML system represents a paradigm shift in technical analysis by addressing a fundamental limitation that plagues traditional indicators: they assume time flows uniformly across all market conditions. In reality, markets experience time compression during volatile breakouts and time dilation during consolidation. A 50-period moving average calculated during a quiet overnight session captures vastly different market information than the same calculation during a high-volume news event.
This indicator solves this problem through Lorentzian spacetime modeling , borrowed directly from Einstein's special relativity. By calculating a dynamic gamma factor (γ) that measures market velocity relative to a volatility-based "speed of light," every calculation adapts its effective lookback period to the market's intrinsic clock. Combined with a dual-memory architecture, multi-regime detection, and Bayesian strategy selection, this creates a system that genuinely learns which approaches work in which market conditions.
CRITICAL DISTINCTION: TRUE ADAPTIVE LEARNING VS STATIC CLASSIFICATION
Before diving into the system architecture, it's essential to understand how this indicator fundamentally differs from traditional "Lorentzian" implementations, particularly the well-known Lorentzian Classification indicator.
THE ORIGINAL LORENTZIAN CLASSIFICATION APPROACH:
The pioneering Lorentzian Classification indicator (Jdehorty, 2022) introduced the financial community to Lorentzian distance metrics for pattern matching. However, it used offline training methodology :
• External Training: Required Python scripts or external ML tools to train the model on historical data
• Static Model: Once trained, the model parameters remained fixed
• No Real-Time Learning: The indicator classified patterns but didn't learn from outcomes
• Look-Ahead Bias Risk: Offline training could inadvertently use future data
• Manual Retraining: To adapt to new market conditions, users had to retrain externally and reload parameters
This was groundbreaking for bringing ML concepts to Pine Script, but it wasn't truly adaptive. The model was a snapshot—trained once, deployed, static.
THIS SYSTEM: TRUE ONLINE LEARNING
The Lorentzian Harmonic Flow Adaptive ML system represents a complete architectural departure :
✅ FULLY SELF-CONTAINED:
• Zero External Dependencies: No Python scripts, no external training tools, no data exports
• 100% Pine Script: Entire learning pipeline executes within TradingView
• One-Click Deployment: Load indicator, it begins learning immediately
• No Manual Configuration: System builds its own training data in real-time
✅ GENUINE FORWARD-WALK LEARNING:
• Real-Time Adaptation: Every trade outcome updates the model
• Forward-Only Logic: System uses only past confirmed data—zero look-ahead bias
• Continuous Evolution: Parameters adapt bar-by-bar based on rolling performance
• Regime-Specific Memory: Learns which patterns work in which conditions independently
✅ GETS BETTER WITH TIME:
• Week 1: Bootstrap mode—gathering initial data across regimes
• Month 2-3: Statistical significance emerges, parameter adaptation begins
• Month 4+: Mature learning, regime-specific optimization, confident selection
• Year 2+: Deep pattern library, proven parameter sets, robust to regime shifts
✅ NO RETRAINING REQUIRED:
• Automatic Adaptation: When market structure changes, system detects via performance degradation
• Memory Refresh: Old patterns naturally decay, new patterns replace them
• Parameter Evolution: Thresholds and multipliers adjust to current conditions
• Regime Awareness: If new regime emerges, enters bootstrap mode automatically
THE FUNDAMENTAL DIFFERENCE:
Traditional Lorentzian Classification:
"Here are patterns from the past. Current state matches pattern X, which historically preceded move Y. Signal fired."
→ Static knowledge, fixed rules, periodic retraining required
LHF Adaptive ML:
"In Trending Bull regime, Strategy B has 58% win rate and 1.4 Sharpe over last 30 trades. In High Vol Range, Strategy C performs better with 61% win rate and 1.8 Sharpe. Current state is Trending Bull, so I select Strategy B. If Strategy B starts failing, I'll adapt parameters or switch strategies. I'm learning which patterns matter in which contexts, and I improve every trade."
→ Dynamic learning, contextual adaptation, self-improving system
WHY THIS MATTERS:
Markets are non-stationary. A model trained on 2023 data may fail in 2024 when Fed policy shifts, volatility regime changes, or market structure evolves. Static models require constant human intervention—retraining, re-optimization, parameter updates.
This system learns continuously . It doesn't need you to tell it when markets changed. It discovers regime shifts through performance feedback, adapts parameters accordingly, and rebuilds its pattern library organically. The system running in Month 12 is fundamentally smarter than the system in Month 1—not because you retrained it, but because it learned from 1,000+ real outcomes.
This is the difference between pattern recognition (static ML) and reinforcement learning (adaptive ML). One classifies, the other learns and improves.
PART 1: LORENTZIAN TEMPORAL DYNAMICS
Markets don't experience time uniformly. During explosive volatility, price can compress weeks of movement into minutes. During consolidation, time dilates. Traditional indicators ignore this, using fixed periods regardless of market state.
The Lorentzian approach models market time using the Lorentz factor from special relativity:
γ = 1 / √(1 - v²/c²)
Where:
• v (velocity): Trend momentum normalized by ATR, calculated as (close - close ) / (N × ATR)
• c (speed limit): Realized volatility + volatility bursts, multiplied by c_multiplier parameter
• γ (gamma): Time dilation factor that compresses or expands effective lookback periods
When trend velocity approaches the volatility "speed limit," gamma spikes above 1.0, compressing time. Every calculation length becomes: base_period / γ. This creates shorter, more responsive periods during explosive moves and longer, more stable periods during quiet consolidation.
The system raises gamma to an optional power (gamma_power parameter) for fine control over compression strength, then applies this temporal scaling to every calculation in the indicator. This isn't metaphor—it's quantitative adaptation to the market's intrinsic clock.
PART 2: LORENTZIAN KERNEL SMOOTHING
Traditional moving averages use uniform weights (SMA) or exponential decay (EMA). The Lorentzian kernel uses heavy-tailed weighting:
K(distance, γ) = 1 / (1 + (distance/γ)²)
This Cauchy-like distribution gives more influence to recent extremes than Gaussian assumptions suggest, capturing the fat-tailed nature of financial returns. For any calculation requiring smoothing, the system loops through historical bars, computes Lorentzian kernel weights based on temporal distance and current gamma, then produces weighted averages.
This creates adaptive smoothing that responds to local volatility structure rather than imposing rigid assumptions about price distribution.
PART 3: HARMONIC FLOW (Multi-Timeframe Momentum)
The core directional signal comes from Harmonic Flow (HFL) , which blends three gamma-compressed Lorentzian smooths:
• Short Horizon: base_period × short_ratio / γ (default: 34 × 0.5 / γ ≈ 17 bars, faster with high γ)
• Mid Horizon: base_period × mid_ratio / γ (default: 34 × 1.0 / γ ≈ 34 bars, anchor timeframe)
• Long Horizon: base_period × long_ratio / γ (default: 34 × 2.5 / γ ≈ 85 bars, structural trend)
Each produces a Lorentzian-weighted smooth, converted to a z-score (distance from smooth normalized by ATR). These z-scores are then weighted-averaged:
HFL = (w_short × z_short + w_mid × z_mid + w_long × z_long) / (w_short + w_mid + w_long)
Default weights (0.45, 0.35, 0.20) favor recent momentum while respecting longer structure. Scalpers can increase short weight; swing traders can emphasize long weight. The result is a directional momentum indicator that captures multi-timeframe flow in compressed time.
From HFL, the system derives:
• Flow Velocity: HFL - HFL (momentum acceleration)
• Flow Acceleration: Second derivative (turning points)
• Temporal Compression Index (TCI): base_period / compressed_length (shows how much time is compressed)
PART 4: DUAL MEMORY ARCHITECTURE
Markets have memory—current conditions resonate with past regimes. But memory operates on two timescales, inspiring this indicator's dual-memory design:
SHORT-TERM MEMORY (STM):
• Capacity: 100 patterns (configurable 50-200)
• Decay Rate: 0.980 (50% weight after ~35 bars)
• Update Frequency: Every 10 bars
• Purpose: Capture current regime's tactical patterns
• Storage: Recent market states with 10-bar forward outcomes
• Analogy: Hippocampus (rapid encoding, fast fade)
LONG-TERM MEMORY (LTM):
• Capacity: 512 patterns (configurable 256-1024)
• Decay Rate: 0.997 (50% weight after ~230 bars)
• Quality Gate: Only high-quality patterns admitted (adaptive threshold per regime)
• Purpose: Strategic pattern library validated across regimes
• Storage: Validated patterns from weeks/months of history
• Analogy: Neocortex (slow consolidation, persistent storage)
Each memory stores 6-dimensional feature vectors:
1. HFL (harmonic flow strength)
2. Flow Velocity (momentum)
3. Flow Acceleration (turning points)
4. Volatility (realized vol EMA)
5. Entropy (market uncertainty)
6. Gamma (time compression state)
Plus the actual outcome (10-bar forward return).
K-NEAREST NEIGHBORS (KNN) PATTERN MATCHING:
When evaluating current market state, the system queries both memories using Lorentzian distance :
distance = Σ (1 - K(|feature_current - feature_memory|, γ))
This calculates similarity across all 6 dimensions using the same Lorentzian kernel, weighted by current gamma. The system finds K nearest neighbors (default: 8), weights each by:
• Similarity: Lorentzian kernel distance
• Age: Exponential decay based on bars since pattern
• Regime: Only patterns from similar regimes count
The weighted average of these neighbors' outcomes becomes the prediction. High-confidence predictions require both high similarity and agreement between multiple neighbors.
REGIME-AWARE BLENDING:
STM and LTM predictions are blended adaptively:
• High Vol Range regime: Trust STM 70% (recent matters in chaos)
• Trending regimes: Trust LTM 70% (structure matters in trends)
• Normal regimes: 50/50 blend
Agreement metric: When STM and LTM strongly disagree, the system flags low confidence—often indicating regime transition or novel market conditions requiring caution.
PART 5: FIVE-REGIME MARKET CLASSIFICATION
Traditional regime detection stops at "trending vs ranging." This system detects five distinct market states using linear regression slope and volatility analysis:
REGIME 0: TRENDING BULL ↗
• Detection: LR slope > trend_threshold (default: 0.3)
• Characteristics: Sustained positive HFL, elevated gamma, low entropy
• Best Strategy: B (Flow Momentum)
• Trading Behavior: Follow momentum, trail stops, pyramid winners
REGIME 1: TRENDING BEAR ↘
• Detection: LR slope < -trend_threshold
• Characteristics: Sustained negative HFL, elevated gamma, low entropy
• Best Strategy: B (Flow Momentum)
• Trading Behavior: Follow momentum short, aggressive exits on reversal
REGIME 2: HIGH VOL RANGE ↔
• Detection: |slope| < threshold AND vol_ratio > vol_expansion_threshold (default: 1.5)
• Characteristics: Oscillating HFL, high gamma spikes, high entropy
• Best Strategies: A (Squeeze Breakout) or C (Memory Pattern)
• Trading Behavior: Fade extremes, tight stops, quick profits
REGIME 3: LOW VOL RANGE —
• Detection: |slope| < threshold AND vol_ratio < vol_expansion_threshold
• Characteristics: Low HFL magnitude, gamma ≈ 1, squeeze conditions
• Best Strategy: A (Squeeze Breakout)
• Trading Behavior: Wait for breakout, wide stops on breakout entry
REGIME 4: TRANSITION ⚡
• Detection: Trend reversal OR volatility spike > 1.5× threshold
• Characteristics: Erratic gamma, high entropy, conflicting signals
• Best Strategy: None (often unfavorable)
• Trading Behavior: Stand aside, wait for clarity
Each regime gets a confidence score (0-1) measuring how clearly defined it is. Low confidence indicates messy, ambiguous conditions.
PART 6: THREE INDEPENDENT TRADING STRATEGIES
Rather than one signal logic, the system implements three distinct approaches:
STRATEGY A: SQUEEZE BREAKOUT
• Logic: Bollinger Bands squeeze release + HFL direction + flow velocity confirmation
• Calculation: Compares BB width to Keltner Channel width; fires when BB expands beyond KC
• Strength Score: 70 + compression_strength × 0.3 (tighter squeeze = higher score)
• Best Regimes: Low Vol Range (3), Transition exit (4→0 or 4→1)
• Pattern: Volatility contraction → directional expansion
• Philosophy: Calm before the storm; compression precedes explosion
STRATEGY B: LORENTZIAN FLOW MOMENTUM
• Logic: Strong HFL (×flow_mult) + positive velocity + gamma > 1.1 + NOT squeezing
• Calculation: |HFL × flow_mult| > 0.12, velocity confirms direction, gamma shows acceleration
• Strength Score: |HFL × flow_mult| × 80 + gamma × 10
• Best Regimes: Trending Bull (0), Trending Bear (1)
• Pattern: Established momentum → acceleration in compressed time
• Philosophy: Trend is friend when spacetime curves
STRATEGY C: MEMORY PATTERN MATCHING
• Logic: Dual KNN prediction > threshold + high confidence + agreement + HFL confirms
• Calculation: |memory_pred| > 0.005, memory_conf > 1.0, agreement > 0.5, HFL direction matches
• Strength Score: |prediction| × 800 × agreement
• Best Regimes: High Vol Range (2), sometimes others with sufficient pattern library
• Pattern: Historical similarity → outcome resonance
• Philosophy: Markets rhyme; learn from validated patterns
Each strategy generates independent strength scores. In multi-strategy mode (enabled by default), the system selects one strategy per regime based on risk-adjusted performance. In weighted mode (multi-strategy disabled), all three fire simultaneously with configurable weights.
PART 7: ADAPTIVE LEARNING & BAYESIAN SELECTION
This is where machine learning meets trading. The system maintains 15 independent performance matrices :
3 strategies × 5 regimes = 15 tracking systems
For each combination, it tracks:
• Trade Count: Number of completed trades
• Win Count: Profitable outcomes
• Total Return: Sum of percentage returns
• Squared Returns: For variance/Sharpe calculation
• Equity Curve: Virtual P&L assuming 10% risk per trade
• Peak Equity: All-time high for drawdown calculation
• Max Drawdown: Peak-to-trough decline
RISK-ADJUSTED SCORING:
For current regime, the system scores each strategy:
Sharpe Ratio: (mean_return / std_dev) × √252
Calmar Ratio: total_return / max_drawdown
Win Rate: wins / trades
Combined Score = 0.6 × Sharpe + 0.3 × Calmar + 0.1 × Win_Rate
The strategy with highest score is selected. This is similar to Thompson Sampling (multi-armed bandits) but uses deterministic selection rather than probabilistic sampling due to Pine Script limitations.
BOOTSTRAP MODE (Critical for Understanding):
For the first min_regime_samples trades (default: 10) in each regime:
• Status: "🔥 BOOTSTRAP (X/10)" displayed in dashboard
• Behavior: All signals allowed (gathering data)
• Regime Filter: Disabled (can't judge with insufficient data)
• Purpose: Avoid cold-start problem, build statistical foundation
After reaching threshold:
• Status: "✅ FAVORABLE" (score > 0.5) or "⚠️ UNFAVORABLE" (score ≤ 0.5)
• Behavior: Only trade favorable regimes (if enable_regime_filter = true)
• Learning: Parameters adapt based on outcomes
This solves a critical problem: you can't know which strategy works in a regime without data, but you can't get data without trading. Bootstrap mode gathers initial data safely, then switches to selective mode once statistical confidence emerges.
PARAMETER ADAPTATION (Per Regime):
Three parameters adapt independently for each regime based on outcomes:
1. SIGNAL QUALITY THRESHOLD (30-90):
• Starts: base_quality_threshold (default: 60)
• Adaptation:
Win Rate < 45% → RAISE threshold by learning_rate × 10 (be pickier)
Win Rate > 55% → LOWER threshold by learning_rate × 5 (take more)
• Effect: System becomes more selective in losing regimes, more aggressive in winning regimes
2. LTM QUALITY GATE (0.2-0.8):
• Starts: 0.4 (if adaptive gate enabled)
• Adaptation:
Sharpe < 0.5 → RAISE gate by learning_rate (demand better patterns)
Sharpe > 1.5 → LOWER gate by learning_rate × 0.5 (accept more patterns)
• Effect: LTM fills with high-quality patterns from winning regimes
3. FLOW MULTIPLIER (0.5-2.0):
• Starts: 1.0
• Adaptation:
Strong win (+2%+) → MULTIPLY by (1 + learning_rate × 0.1)
Strong loss (-2%+) → MULTIPLY by (1 - learning_rate × 0.1)
• Effect: Amplifies signal strength in profitable regimes, dampens in unprofitable
Each regime evolves independently. Trending Bull might develop threshold=55, gate=0.35, mult=1.3 while High Vol Range develops threshold=70, gate=0.50, mult=0.9.
PART 8: SHADOW PORTFOLIO VALIDATION
To validate learning objectively, the system runs three virtual portfolios :
Shadow Portfolio A: Trades only Strategy A signals
Shadow Portfolio B: Trades only Strategy B signals
Shadow Portfolio C: Trades only Strategy C signals
When any signal fires:
1. Open virtual position for corresponding strategy
2. On exit, calculate P&L (10% risk per trade)
3. Update equity, win count, profit factor
Dashboard displays:
• Equity: Current virtual balance (starts $10,000)
• Win%: Overall win rate across all regimes
• PF: Profit Factor (gross_profit / gross_loss)
This transparency shows which strategies actually perform, validates the selection logic, and prevents overfitting. If Shadow C shows $12,500 equity while A and B show $9,800, it confirms Strategy C's edge.
PART 9: HISTORICAL PRE-TRAINING
The system includes historical pre-training to avoid cold-start:
On Chart Load (if enabled):
1. Scan past pretrain_bars (default: 200)
2. Calculate historical HFL, gamma, velocity, acceleration, volatility, entropy
3. Compute 10-bar forward returns as outcomes
4. Populate STM with recent patterns
5. Populate LTM with high-quality patterns (quality > 0.4)
Effect:
• Without pre-training: Memories empty, no predictions for weeks, pure bootstrap
• With pre-training: System starts with pattern library, predictions from day one
Pre-training uses only past data (no future peeking) and fills memories with validated outcomes. This dramatically accelerates learning without compromising integrity.
PART 10: COMPREHENSIVE INPUT SYSTEM
The indicator provides 50+ inputs organized into logical groups. Here are the key parameters and their market-specific guidance:
🧠 ADAPTIVE LEARNING SYSTEM:
Enable Adaptive Learning (true/false):
• Function: Master switch for regime-specific strategy selection and parameter adaptation
• Enabled: System learns which strategies work in which regimes (recommended)
• Disabled: All strategies fire simultaneously with fixed weights (simpler, less adaptive)
• Recommendation: Keep enabled for all markets; system needs 2-3 months to mature
Learning Rate (0.01-0.20):
• Function: Speed of parameter adaptation based on outcomes
• Stocks/ETFs: 0.03-0.05 (slower, more stable)
• Crypto: 0.05-0.08 (faster, adapts to volatility)
• Forex: 0.04-0.06 (moderate)
• Timeframes:
1-5min scalping: 0.08-0.10 (rapid adaptation)
15min-1H day trading: 0.05-0.07 (balanced)
4H-Daily swing: 0.03-0.05 (conservative)
• Tradeoff: Higher = responsive but may overfit; Lower = stable but slower to adapt
Min Samples Per Regime (5-30):
• Function: Trades required before exiting bootstrap mode
• Active trading (>5 signals/day): 8-10 trades
• Moderate (1-5 signals/day): 10-15 trades
• Swing (few signals/week): 5-8 trades
• Logic: Bootstrap mode until this threshold; then uses Sharpe/Calmar for regime filtering
• Tradeoff: Lower = faster exit (risky, less data); Higher = more validation (safer, slower)
🌍 REGIME DETECTION:
Regime Lookback Period (20-200):
• Function: Bars used for linear regression to classify regime
• By Timeframe:
1-5min: 30-50 bars (~2-4 hour context)
15min: 40-60 bars (daily context)
1H: 50-100 bars (weekly context)
4H: 100-150 bars (monthly context)
Daily: 50-75 bars (quarterly context)
• By Market:
Crypto: 40-60 (faster regime changes)
Forex: 50-75 (moderate stability)
Stocks: 60-100 (slower structural trends)
• Tradeoff: Shorter = more regime switches (reactive); Longer = fewer switches (stable)
Trend Strength Threshold (0.1-0.8):
• Function: Minimum normalized LR slope to classify as trending vs ranging
• Lower (0.1-0.2): More markets classified as trending
• Higher (0.4-0.6): Only strong trends qualify
• Recommendations:
Choppy markets (BTC, small caps): 0.25-0.35
Smooth trends (major FX pairs): 0.30-0.40
Strong trends (indices during bull): 0.20-0.30
• Effect: Controls sensitivity of trending vs ranging classification
Vol Expansion Factor (1.2-3.0):
• Function: Volatility ratio to classify high-vol regimes (current_vol / avg_vol)
• By Asset:
Bitcoin: 1.4-1.6 (frequent vol spikes)
Altcoins: 1.3-1.5 (very volatile)
Major FX (EUR/USD): 1.6-2.0 (stable baseline)
Stocks (SPY): 1.5-1.8 (moderate)
Penny stocks: 1.3-1.4 (always volatile)
• Impact: Higher = fewer "High Vol Range" classifications; Lower = more sensitive to volatility spikes
🎯 SIGNAL GENERATION:
Base Quality Threshold (30-90):
• Function: Starting signal strength requirement (adapts per regime)
• THIS IS YOUR MAIN SIGNAL FREQUENCY CONTROL
• Conservative (70-80): Fewer, higher-quality signals
• Balanced (55-65): Moderate signal flow
• Aggressive (40-50): More signals, more noise
• By Trading Style:
Scalping (1-5min): 50-60
Day trading (15min-1H): 60-70
Swing (4H-Daily): 65-75
• Adaptive Behavior: System raises this in losing regimes (pickier), lowers in winning regimes (take more)
Min Confidence (0.1-0.9):
• Function: Minimum confidence score to fire signal
• Calculation: (Signal_Strength / 100) × Regime_Confidence
• Recommendations:
High-frequency (scalping): 0.2-0.3 (permissive)
Day trading: 0.3-0.4 (balanced)
Swing/position: 0.4-0.6 (selective)
• Interaction: During Transition regime (low regime confidence), even strong signals may fail confidence check; creates natural regime filtering
Only Trade Favorable Regimes (true/false):
• Function: Block signals in unfavorable regimes (where all strategies have negative risk-adjusted scores)
• Enabled (Recommended): Only trades when best strategy has positive Sharpe in current regime; auto-disables during bootstrap; protects capital
• Disabled: Always allows signals regardless of historical performance; use for manual regime assessment
• Bootstrap: Auto-allows trading until min_regime_samples reached, then switches to performance-based filtering
Min Bars Between Signals (1-20):
• Function: Prevents signal spam by enforcing minimum spacing
• By Timeframe:
1min: 3-5 bars (3-5 minutes)
5min: 3-6 bars (15-30 minutes)
15min: 4-8 bars (1-2 hours)
1H: 5-10 bars (5-10 hours)
4H: 3-6 bars (12-24 hours)
Daily: 2-5 bars (2-5 days)
• Logic: After signal fires, no new signals for X bars
• Tradeoff: Lower = more reactive (may overtrade); Higher = more patient (may miss reversals)
🌀 LORENTZIAN CORE:
Base Period (10-100):
• Function: Core time period for flow calculation (gets compressed by gamma)
• THIS IS YOUR PRIMARY TIMEFRAME KNOB
• By Timeframe:
1-5min scalping: 20-30 (fast response)
15min-1H day: 30-40 (balanced)
4H swing: 40-55 (smooth)
Daily position: 50-75 (very smooth)
• By Market Character:
Choppy (crypto, small caps): 25-35 (faster)
Smooth (major FX, indices): 35-50 (moderate)
Slow (bonds, utilities): 45-65 (slower)
• Gamma Effect: Actual length = base_period / gamma; High gamma compresses to ~20 bars, low gamma expands to ~50 bars
• Default 34 (Fibonacci) works well across most assets
Velocity Period (5-50):
• Function: Window for trend velocity calculation: (price_now - price ) / (N × ATR)
• By Timeframe:
1-5min scalping: 8-12 (fast momentum)
15min-1H day: 12-18 (balanced)
4H swing: 14-21 (smooth trend)
Daily: 18-30 (structural trend)
• By Market:
Crypto (fast moves): 10-14
Stocks (moderate): 14-20
Forex (smooth): 18-25
• Impact: Feeds into gamma calculation (v/c ratio); shorter = more sensitive to velocity spikes → higher gamma
• Relationship: Typically vel_period ≈ base_period / 2 to 2/3
Speed-of-Market (c) (0.5-3.0):
• Function: "Speed limit" for gamma calculation: c = realized_vol + vol_burst × c_multiplier
• By Asset Volatility:
High vol (BTC, TSLA): 1.0-1.3 (lower c = more compression)
Medium vol (SPY, EUR/USD): 1.3-1.6 (balanced)
Low vol (bonds, utilities): 1.6-2.5 (higher c = less compression)
• What It Does:
Lower c → velocity hits "speed limit" sooner → higher gamma → more compression
Higher c → velocity rarely hits limit → gamma stays near 1 → less adaptation
• Effect on Signals: More compression (low c) = faster regime detection, more responsive; Less compression (high c) = smoother, less adaptive
• Tuning: Start at 1.4; if gamma always ~1.0, lower to 1.0-1.2; if gamma spikes >5 often, raise to 1.6-2.0
Gamma Power (0.5-2.0):
• Function: Exponent applied to gamma: final_gamma = gamma^power
• Compression Strength:
0.5-0.8: Softens compression (gamma 4 → 2)
1.0: Linear (gamma 4 → 4)
1.2-2.0: Amplifies compression (gamma 4 → 16)
• Use Cases:
Reduce power (<1.0) if adaptive lengths swing too wildly or getting whipsawed
Increase power (>1.0) for more aggressive regime adaptation in fast markets
• Most users should leave at 1.0; only adjust if gamma behavior needs tuning
Max Kernel Lookback (20-200):
• Function: Computational limit for Lorentzian smoothing (performance control)
• Recommendations:
Fast PC / simple chart: 80-100
Slow PC / complex chart: 40-60
Mobile / lots of indicators: 30-50
• Impact: Each kernel smoothing loops through this many bars; higher = more accurate but slower
• Default 60 balances accuracy and speed; lower to 40-50 if indicator is slow
🎼 HARMONIC FLOW:
Short Horizon (0.2-1.0):
• Function: Fast timeframe multiplier: short_length = base_period × short_ratio / gamma
• Default: 0.5 (captures 2× faster flow than base)
• By Style:
Scalping: 0.3-0.4 (very fast)
Day trading: 0.4-0.6 (moderate)
Swing: 0.5-0.7 (balanced)
• Effect: Lower = more weight on micro-moves; Higher = smooths out fast fluctuations
Mid Horizon (0.5-2.0):
• Function: Medium timeframe multiplier: mid_length = base_period × mid_ratio / gamma
• Default: 1.0 (equals base_period, anchor timeframe)
• Usually keep at 1.0 unless specific strategy needs fine-tuning
Long Horizon (1.0-5.0):
• Function: Slow timeframe multiplier: long_length = base_period × long_ratio / gamma
• Default: 2.5 (captures trend/structure)
• By Style:
Scalping: 1.5-2.0 (less long-term influence)
Day trading: 2.0-3.0 (balanced)
Swing: 2.5-4.0 (strong trend component)
• Effect: Higher = more emphasis on larger structure; Lower = more reactive to recent price action
Short Weight (0-1):
Mid Weight (0-1):
Long Weight (0-1):
• Function: Relative importance in HFL calculation (should sum to 1.0)
• Defaults: Short: 0.45, Mid: 0.35, Long: 0.20 (day trading balanced)
• Preset Configurations:
SCALPING (fast response):
Short: 0.60, Mid: 0.30, Long: 0.10
DAY TRADING (balanced):
Short: 0.45, Mid: 0.35, Long: 0.20
SWING (trend-following):
Short: 0.25, Mid: 0.35, Long: 0.40
• Effect: More short weight = responsive but noisier; More long weight = smoother but laggier
🧠 DUAL MEMORY SYSTEM:
Enable Pattern Memory (true/false):
• Function: Master switch for KNN pattern matching via dual memory
• Enabled (Recommended): Strategy C (Memory Pattern) can fire; memory predictions influence all strategies; prediction arcs shown; heatmaps available
• Disabled: Only Strategy A and B available; faster performance (less computation); pure technical analysis (no pattern matching)
• Keep enabled for full system capabilities; disable only if CPU-constrained or testing pure flow signals
STM Size (50-200):
• Function: Short-Term Memory capacity (recent pattern storage)
• Characteristics: Fast decay (0.980), captures current regime, updates every 10 bars, tactical pattern matching
• Sizing:
Active markets (crypto): 80-120
Moderate (stocks): 100-150
Slow (bonds): 50-100
• By Timeframe:
1-15min: 60-100 (captures few hours of patterns)
1H: 80-120 (captures days)
4H-Daily: 100-150 (captures weeks/months)
• Tradeoff: More = better recent pattern coverage; Less = faster computation
• Default 100 is solid for most use cases
LTM Size (256-1024):
• Function: Long-Term Memory capacity (validated pattern storage)
• Characteristics: Slow decay (0.997), only high-quality patterns (gated), regime-specific recall, strategic pattern library
• Sizing:
Fast PC: 512-768
Medium PC: 384-512
Slow PC/Mobile: 256-384
• By Data Needs:
High-frequency (lots of patterns): 512-1024
Moderate activity: 384-512
Low-frequency (swing): 256-384
• Performance Impact: Each KNN search loops through entire LTM; 512 = good balance of coverage and speed; if slow, drop to 256-384
• Fills over weeks/months with validated patterns
STM Decay (0.95-0.995):
• Function: Short-Term Memory age decay rate: age_weight = decay^bars_since_pattern
• Decay Rates:
0.950: Aggressive fade (50% weight after 14 bars)
0.970: Moderate fade (50% after 23 bars)
0.980: Balanced (50% after 35 bars)
0.990: Slow fade (50% after 69 bars)
• By Timeframe:
1-5min: 0.95-0.97 (fast markets, old patterns irrelevant)
15min-1H: 0.97-0.98 (balanced)
4H-Daily: 0.98-0.99 (slower decay)
• Philosophy: STM should emphasize RECENT patterns; lower decay = only very recent matters; 0.980 works well for most cases
LTM Decay (0.99-0.999):
• Function: Long-Term Memory age decay rate
• Decay Rates:
0.990: 50% weight after 69 bars
0.995: 50% weight after 138 bars
0.997: 50% weight after 231 bars
0.999: 50% weight after 693 bars
• Philosophy: LTM should retain value for LONG periods; pattern from 6 months ago might still matter
• Usage:
Fast-changing markets: 0.990-0.995
Stable markets: 0.995-0.998
Structural patterns: 0.998-0.999
• Warning: Be careful with very high decay (>0.998); market structure changes, old patterns may mislead
• 0.997 balances long-term memory with regime evolution
K Neighbors (3-21):
• Function: Number of similar patterns to query in KNN search
• By Sample Size:
Small dataset (<100 patterns): 3-5
Medium dataset (100-300): 5-8
Large dataset (300-1000): 8-13
Very large (>1000): 13-21
• Tradeoff:
Fewer K (3-5): More reactive to closest matches; noisier; outlier-sensitive; better when patterns very distinct
More K (13-21): Smoother, more stable predictions; may dilute strong signals; better when patterns overlap
• Rule of Thumb: K ≈ √(memory_size) / 3; For STM=100, LTM=512: K ≈ 8-10 ideal
Adaptive Quality Gate (true/false):
• Function: Adapts LTM entry threshold per regime based on Sharpe ratio
• Enabled: Quality gate adapts: Low Sharpe → RAISE gate (demand better patterns); High Sharpe → LOWER gate (accept more patterns); each regime has independent gate
• Disabled: Fixed quality gate (0.4 default) for all regimes
• Recommended: Keep ENABLED; helps LTM focus on proven pattern types per regime; prevents weak patterns from polluting memory
🎯 MULTI-STRATEGY SYSTEM:
Enable Strategy Learning (true/false):
• Function: Core learning feature for regime-specific strategy selection
• Enabled: Tracks 3 strategies × 5 regimes = 15 performance matrices; selects best strategy per regime via Sharpe/Calmar/WinRate; adaptive strategy switching
• Disabled: All strategies fire simultaneously (weighted combination); no regime-specific selection; simpler but less adaptive
• Recommended: ENABLED (this is the core of the adaptive system); disable only for testing or simplification
Strategy A Weight (0-1):
• Function: Weight for Strategy A (Squeeze Breakout) when multi-strategy disabled
• Characteristics: Fires on Bollinger squeeze release; best in Low Vol Range, Transition; compression → expansion pattern
• When Multi-Strategy OFF: Default 0.33 (equal weight); increase to 0.4-0.5 for choppy ranges with breakouts; decrease to 0.2-0.3 for trending markets
• When Multi-Strategy ON: This is ignored (system auto-selects based on performance)
Strategy B Weight (0-1):
• Function: Weight for Strategy B (Lorentzian Flow) when multi-strategy disabled
• Characteristics: Fires on strong HFL + velocity + gamma; best in Trending Bull/Bear; momentum → acceleration pattern
• When Multi-Strategy OFF: Default 0.33; increase to 0.4-0.5 for trending markets; decrease to 0.2-0.3 for choppy/ranging markets
• When Multi-Strategy ON: Ignored (auto-selected)
Strategy C Weight (0-1):
• Function: Weight for Strategy C (Memory Pattern) when multi-strategy disabled
• Characteristics: Fires when dual KNN predicts strong move; best in High Vol Range; requires memory system enabled + sufficient data
• When Multi-Strategy OFF: Default 0.34; increase to 0.4-0.6 if strong pattern repetition and LTM has >200 patterns; decrease to 0.2-0.3 if new to system; set to 0.0 if memory disabled
• When Multi-Strategy ON: Ignored (auto-selected)
📚 PRE-TRAINING:
Historical Pre-Training (true/false):
• Function: Bootstrap feature that fills memory on chart load
• Enabled: Scans past bars to populate STM/LTM before live trading; calculates historical outcomes (10-bar forward returns); builds initial pattern library; system starts with context, not blank slate
• Disabled: Memories only populate in real-time; takes weeks to build pattern library
• Recommended: ENABLED (critical for avoiding "cold start" problem); disable only for testing clean learning
Training Bars (50-500):
• Function: How many historical bars to scan on load (limited by available history)
• Recommendations:
1-5min charts: 200-300 (few hours of history)
15min-1H: 200-400 (days/weeks)
4H: 300-500 (months)
Daily: 200-400 (years)
• Performance:
100 bars: ~1 second
300 bars: ~2-3 seconds
500 bars: ~4-5 seconds
• Sweet Spot: 200-300 (enough patterns without slow load)
• If chart loads slowly: Reduce to 100-150
🎨 VISUALIZATION:
Show Regime Background (true/false):
• Function: Color-code background by current regime
• Colors: Trending Bull (green tint), Trending Bear (red tint), High Vol Range (orange tint), Low Vol Range (blue tint), Transition (purple tint)
• Helps visually track regime changes
Show Flow Bands (true/false):
• Function: Plot upper/lower bands based on HFL strength
• Shows dynamic support/resistance zones; green fill = bullish flow; red fill = bearish flow
• Useful for visual trend confirmation
Show Confidence Meter (true/false):
• Function: Plot signal confidence (0-100) in separate pane
• Calculation: (Signal_Strength / 100) × Regime_Confidence
• Gold line = current confidence; dashed line = minimum threshold
• Signals fire when confidence exceeds threshold
Show Prediction Arc (true/false):
• Function: Dashed line projecting expected price move based on memory prediction
• NOT a price target - a probability vector; steep arc = strong expected move; flat arc = weak/uncertain prediction
• Green = bullish prediction; red = bearish prediction
Show Signals (true/false):
• Function: Triangle markers at entry points
• ▲ Green = Long signal; ▼ Red = Short signal
• Markers show on bar close (non-repainting)
🏆 DASHBOARD:
Show Dashboard (true/false):
• Function: Main info panel showing all system metrics
• Sections: Lorentzian Core, Regime, Dual Memory, Adaptive Parameters, Regime Performance, Shadow Portfolios, Current Signal Status
• Essential for understanding system state
Dashboard Position: Top Left, Top Right, Bottom Left, Bottom Right
Individual Section Toggles:
• System Stats: Lorentzian Core section (Gamma, v/c, HFL, TCI)
• Memory Stats: Dual Memory section (STM/LTM predictions, agreement)
• Shadow Portfolios: Shadow Portfolio table (equity, win%, PF)
• Adaptive Params: Adaptive Parameters section (threshold, quality gate, flow mult)
🔥 HEATMAPS:
Show Dual Heatmaps (true/false):
• Function: Visual pattern density maps for STM and LTM
• Layout: X-axis = pattern age (left=recent, right=old); Y-axis = outcome direction (top=bearish, bottom=bullish); Color intensity = pattern count; Color hue = bullish (green) vs bearish (red)
• Warning: Can clutter chart; disable if not using
Heatmap Position: Screen position for heatmaps (STM at selected position, LTM offset)
Resolution (5-15):
• Function: Grid resolution (bins)
• Higher = more detailed but smaller cells; Lower = clearer but less granular
• 10 is good balance; reduce to 6-8 if hard to read
PART 11: DASHBOARD METRICS EXPLAINED
The comprehensive dashboard provides real-time transparency into every aspect of the adaptive system:
⚡ LORENTZIAN CORE SECTION:
Gamma (γ):
• Range: 1.0 to ~10.0 (capped)
• Interpretation:
γ ≈ 1.0-1.2: Normal market time, low velocity
γ = 1.5-2.5: Moderate compression, trending
γ = 3.0-5.0: High compression, explosive moves
γ > 5.0: Extreme compression, parabolic volatility
• Usage: High gamma = system operating in compressed time; expect shorter effective periods and faster adaptation
v/c (Velocity / Speed Limit):
• Range: 0.0 to 0.999 (approaches but never reaches 1.0)
• Interpretation:
v/c < 0.3: Slow market, low momentum
v/c = 0.4-0.7: Moderate trending
v/c > 0.7: Approaching "speed limit," high velocity
v/c > 0.9: Parabolic move, system at limit
• Color Coding: Red (>0.7), Gold (0.4-0.7), Green (<0.4)
• Usage: High v/c warns of extreme conditions where trend may exhaust
HFL (Harmonic Flow):
• Range: Typically -3.0 to +3.0 (can exceed in extremes)
• Interpretation:
HFL > 0: Bullish flow
HFL < 0: Bearish flow
|HFL| > 0.5: Strong directional bias
|HFL| < 0.2: Weak, indecisive
• Color: Green (positive), Red (negative)
• Usage: Primary directional indicator; strategies often require HFL confirmation
TCI (Temporal Compression Index):
• Calculation: base_period / compressed_length
• Interpretation:
TCI ≈ 1.0: No compression, normal time
TCI = 1.5-2.5: Moderate compression
TCI > 3.0: Significant compression
• Usage: Shows how much time is being compressed; mirrors gamma but more intuitive
╔═══ REGIME SECTION ═══╗
Current:
• Display: Regime name with icon (Trending Bull ↗, Trending Bear ↘, High Vol Range ↔, Low Vol Range —, Transition ⚡)
• Color: Gold for visibility
• Usage: Know which regime you're in; check regime performance to see expected strategy behavior
Confidence:
• Range: 0-100%
• Interpretation:
>70%: Very clear regime definition
40-70%: Moderate clarity
<40%: Ambiguous, mixed conditions
• Color: Green (>70%), Gold (40-70%), Red (<40%)
• Usage: High confidence = trust regime classification; low confidence = regime may be transitioning
Mode:
• States:
🔥 BOOTSTRAP (X/10): Still gathering data for this regime
✅ FAVORABLE: Best strategy has positive risk-adjusted score (>0.5)
⚠️ UNFAVORABLE: All strategies have negative scores (≤0.5)
• Color: Orange (bootstrap), Green (favorable), Red (unfavorable)
• Critical Importance: This tells you whether the system will trade or stand aside (if regime filter enabled)
╔═══ DUAL MEMORY KNN SECTION ═══╗
STM (Size):
• Display: Number of patterns currently in STM (0 to stm_size)
• Interpretation: Should fill to capacity within hours/days; if not filling, check that memory is enabled
STM Pred:
• Range: Typically -0.05 to +0.05 (representing -5% to +5% expected 10-bar move)
• Color: Green (positive), Red (negative)
• Usage: STM's prediction based on recent patterns; emphasis on current regime
LTM (Size):
• Display: Number of patterns in LTM (0 to ltm_size)
• Interpretation: Fills slowly (weeks/months); only validated high-quality patterns; check quality gate if not filling
LTM Pred:
• Range: Similar to STM pred
• Color: Green (positive), Red (negative)
• Usage: LTM's prediction based on long-term validated patterns; more strategic than tactical
Agreement:
• Display:
✅ XX%: Strong agreement (>70%) - both memories aligned
⚠️ XX%: Moderate agreement (40-70%) - some disagreement
❌ XX%: Conflict (<40%) - memories strongly disagree
• Color: Green (>70%), Gold (40-70%), Red (<40%)
• Critical Usage: Low agreement often precedes regime change or signals novel conditions; Strategy C won't fire with low agreement
╔═══ ADAPTIVE PARAMS SECTION ═══╗
Threshold:
• Display: Current regime's signal quality threshold (30-90)
• Interpretation: Higher = pickier; lower = more permissive
• Watch For: If steadily rising in a regime, system is struggling (low win rate); if falling, system is confident
• Default: Starts at base_quality_threshold (usually 60)
Quality:
• Display: Current regime's LTM quality gate (0.2-0.8)
• Interpretation: Minimum quality score for pattern to enter LTM
• Watch For: If rising, system demanding higher-quality patterns; if falling, accepting more diverse patterns
• Default: Starts at 0.4
Flow Mult:
• Display: Current regime's flow multiplier (0.5-2.0)
• Interpretation: Amplifies or dampens HFL for Strategy B
• Watch For: If >1.2, system found strong edge in flow signals; if <0.8, flow signals underperforming
• Default: Starts at 1.0
Learning:
• Display: ✅ ON or ❌ OFF
• Shows whether adaptive learning is enabled
• Color: Green (on), Red (off)
╔═══ REGIME PERFORMANCE SECTION ═══╗
This table shows ONLY the current regime's statistics:
S (Strategy):
• Display: A, B, or C
• Color: Gold if selected strategy; gray if not
• Shows which strategies have data in this regime
Trades:
• Display: Number of completed trades for this pair
• Interpretation: Blank or low numbers mean bootstrap mode; >10 means statistical significance building
Win%:
• Display: Win rate percentage
• Color: Green (>55%), White (45-55%), Red (<45%)
• Interpretation: 52%+ is good; 58%+ is excellent; <45% means struggling
• Note: Short-term variance is normal; judge after 20+ trades
Sharpe:
• Display: Annualized Sharpe ratio
• Color: Green (>1.0), White (0-1.0), Red (<0)
• Interpretation:
>2.0: Exceptional (rare)
1.0-2.0: Good
0.5-1.0: Acceptable
0-0.5: Marginal
<0: Losing
• Usage: Primary metric for strategy selection (60% weight in score)
╔═══ SHADOW PORTFOLIOS SECTION ═══╗
Shows virtual equity tracking across ALL regimes (not just current):
S (Strategy):
• Display: A, B, or C
• Color: Gold if currently selected strategy; gray otherwise
Equity:
• Display: Current virtual balance (starts $10,000)
• Color: Green (>$10,000), White ($9,500-$10,000), Red (<$9,500)
• Interpretation: Which strategy is actually making virtual money across all conditions
• Note: 10% risk per trade assumed
Win%:
• Display: Overall win rate across all regimes
• Color: Green (>55%), White (45-55%), Red (<45%)
• Interpretation: Aggregate performance; strategy may do well in some regimes and poorly in others
PF (Profit Factor):
• Display: Gross profit / gross loss
• Color: Green (>1.5), White (1.0-1.5), Red (<1.0)
• Interpretation:
>2.0: Excellent
1.5-2.0: Good
1.2-1.5: Acceptable
1.0-1.2: Marginal
<1.0: Losing
• Usage: Confirms win rate; high PF with moderate win rate means winners >> losers
╔═══ STATUS BAR ═══╗
Display States:
• 🟢 LONG: Currently in long position (green background)
• 🔴 SHORT: Currently in short position (red background)
• ⬆️ LONG SIGNAL: Long signal present but not yet confirmed (waiting for bar close)
• ⬇️ SHORT SIGNAL: Short signal present but not yet confirmed
• ⚪ NEUTRAL: No position, no signal (white background)
Usage: Immediate visual confirmation of system state; check before manually entering/exiting
PART 12: VISUAL ELEMENT INTERPRETATION
REGIME BACKGROUND COLORS:
Green Tint: Trending Bull regime - expect Strategy B (Flow) to dominate; focus on long momentum
Red Tint: Trending Bear regime - expect Strategy B (Flow) shorts; focus on short momentum
Orange Tint: High Vol Range - expect Strategy A (Squeeze) or C (Memory); trade breakouts or patterns
Blue Tint: Low Vol Range - expect Strategy A (Squeeze); wait for compression release
Purple Tint: Transition regime - often unfavorable; system may stand aside; high uncertainty
Usage: Quick visual regime identification without reading dashboard
FLOW BANDS:
Upper Band: close + HFL × ATR × 1.5
Lower Band: close - HFL × ATR × 1.5
Green Fill: HFL positive (bullish flow); bands act as dynamic support/resistance in uptrend
Red Fill: HFL negative (bearish flow); bands act as dynamic resistance/support in downtrend
Usage:
• Bullish flow: Price bouncing off lower band = trend continuation; breaking below = possible reversal
• Bearish flow: Price rejecting upper band = trend continuation; breaking above = possible reversal
CONFIDENCE METER (Separate Pane):
Gold Line: Current signal confidence (0-100)
Dashed Line: Minimum confidence threshold
Interpretation:
• Line above threshold: Signal likely to fire if strength sufficient
• Line below threshold: Even if signal logic met, won't fire (insufficient confidence)
• Gradual rise: Signal building strength
• Sharp spike: Sudden conviction (check if sustainable)
Usage: Real-time signal probability; helps anticipate upcoming entries
PREDICTION ARC:
Dashed Line: Projects from current close to expected price 8 bars forward
Green Arc: Bullish memory prediction
Red Arc: Bearish memory prediction
Steep Arc: High conviction (strong expected move)
Flat Arc: Low conviction (weak/uncertain move)
Important: NOT a price target; this is a probability vector based on KNN outcomes; actual price may differ
Usage: Directional bias from pattern matching; confirms or contradicts flow signals
SIGNAL MARKERS:
▲ Green Triangle (below bar):
• Long signal confirmed on bar close
• Entry on next bar open
• Non-repainting (appears after bar closes)
▼ Red Triangle (above bar):
• Short signal confirmed on bar close
• Entry on next bar open
• Non-repainting
Size: Tiny (unobtrusive)
Text: "L" or "S" in marker
Usage: Historical signal record; alerts should fire on these; verify against dashboard status
DUAL HEATMAPS (If Enabled):
STM HEATMAP:
• X-axis: Pattern age (left = recent, right = older, typically 0-50 bars)
• Y-axis: Outcome direction (top = bearish outcomes, bottom = bullish outcomes)
• Color Intensity: Brightness = pattern count in that cell
• Color Hue: Green tint (bullish), Red tint (bearish), Gray (neutral)
Interpretation:
• Dense bottom-left: Many recent bullish patterns (bullish regime)
• Dense top-left: Many recent bearish patterns (bearish regime)
• Scattered: Mixed outcomes, ranging regime
• Empty areas: Few patterns (low data)
LTM HEATMAP:
• Similar layout but X-axis spans wider age range (0-500+ bars)
• Shows long-term pattern distribution
• Denser = more validated patterns
Comparison Usage:
• If STM and LTM heatmaps look similar: Current regime matches historical patterns (high agreement)
• If STM bottom-heavy but LTM top-heavy: Recent bullish activity contradicts historical bearish patterns (low agreement, transition signal)
PART 13: DEVELOPMENT STORY
The creation of the Lorentzian Harmonic Flow Adaptive ML system represents over six months of intensive research, mathematical exploration, and iterative refinement. What began as a theoretical investigation into applying special relativity to market time evolved into a complete adaptive learning framework.
THE CHALLENGE:
The fundamental problem was this: markets don't experience time uniformly, yet every indicator treats a 50-period calculation the same whether markets are exploding or sleeping. Traditional adaptive indicators adjust parameters based on volatility, but this is reactive—by the time you measure high volatility, the explosive move is over. What was needed was a framework that measured the market's intrinsic velocity relative to its own structural limits, then compressed time itself proportionally.
THE LORENTZIAN INSIGHT:
Einstein's special relativity provides exactly this framework through the Lorentz factor. When an object approaches the speed of light, time dilates—but from the object's reference frame, it experiences time compression. By treating price velocity as analogous to relativistic velocity and volatility structure as the "speed limit," we could calculate a gamma factor that compressed lookback periods during explosive moves.
The mathematics were straightforward in theory but devilishly complex in implementation. Pine Script has no native support for dynamically-sized arrays or recursive functions, forcing creative workarounds. The Lorentzian kernel smoothing required nested loops through historical bars, calculating kernel weights on the fly—a computational nightmare. Early versions crashed or produced bizarre artifacts (negative gamma values, infinite loops during volatility spikes).
Optimization took weeks. Limiting kernel lookback to 60 bars while still maintaining smoothing quality. Pre-calculating gamma once per bar and reusing it across all calculations. Caching intermediate results. The final implementation balances mathematical purity with computational reality.
THE MEMORY ARCHITECTURE:
With temporal compression working, the next challenge was pattern memory. Simple moving average systems have no memory—they forget yesterday's patterns immediately. But markets are non-stationary; what worked last month may not work today. The solution: dual-memory architecture inspired by cognitive neuroscience.
Short-Term Memory (STM) would capture tactical patterns—the hippocampus of the system. Fast encoding, fast decay, always current. Long-Term Memory (LTM) would store validated strategic patterns—the neocortex. Slow consolidation, persistent storage, regime-spanning wisdom.
The KNN implementation nearly broke me. Calculating Lorentzian distance across 6 dimensions for 500+ patterns per query, applying age decay, filtering by regime, finding K nearest neighbors without native sorting functions—all while maintaining sub-second execution. The breakthrough came from realizing we could use destructive sorting (marking found neighbors as "infinite distance") rather than maintaining separate data structures.
Pre-training was another beast. To populate memory with historical patterns, the system needed to scan hundreds of past bars, calculate forward outcomes, and insert patterns—all on chart load without timing out. The solution: cap at 200 bars, optimize loops, pre-calculate features. Now it works seamlessly.
THE REGIME DETECTION:
Five-regime classification emerged from empirical observation. Traditional trending/ranging dichotomy missed too much nuance. Markets have at least four distinct states: trending up, trending down, volatile range, quiet range—plus a chaotic transition state. Linear regression slope quantifies trend; volatility ratio quantifies expansion; combining them creates five natural clusters.
But classification is useless without regime-specific learning. That meant tracking 15 separate performance matrices (3 strategies × 5 regimes), computing Sharpe ratios and Calmar ratios for sparse data, implementing Bayesian-like strategy selection. The bootstrap mode logic alone took dozens of iterations—too strict and you never get data, too permissive and you blow up accounts during learning.
THE ADAPTIVE LAYER:
Parameter adaptation was conceptually elegant but practically treacherous. Each regime needed independent thresholds, quality gates, and multipliers that adapted based on outcomes. But naive gradient descent caused oscillations—win a few trades, lower threshold, take worse signals, lose trades, raise threshold, miss good signals. The solution: exponential smoothing via learning rate (α) and separate scoring for selection vs adaptation.
Shadow portfolios provided objective validation. By running virtual accounts for all strategies simultaneously, we could see which would have won even when not selected. This caught numerous bugs where selection logic was sound but execution was flawed, or vice versa.
THE DASHBOARD & VISUALIZATION:
A learning system is useless if users can't understand what it's doing. The dashboard went through five complete redesigns. Early versions were information dumps—too much data, no hierarchy, impossible to scan. The final version uses visual hierarchy (section headers, color coding, strategic whitespace) and progressive disclosure (show current regime first, then performance, then parameters).
The dual heatmaps were a late addition but proved invaluable for pattern visualization. Seeing STM cluster in one corner while LTM distributed broadly immediately signals regime novelty. Traders grasp this visually faster than reading disagreement percentages.
THE TESTING GAUNTLET:
Testing adaptive systems is uniquely challenging. Static backtest results mean nothing—the system should improve over time. Early "tests" showed abysmal performance because bootstrap periods were included. The breakthrough: measure pre-learning baseline vs post-learning performance. A system going from 48% win rate (first 50 trades) to 56% win rate (trades 100-200) is succeeding even if absolute performance seems modest.
Edge cases broke everything repeatedly. What happens when a regime never appears in historical data? When all strategies fail simultaneously? When memory fills with only bearish patterns during a bull run? Each required careful handling—bootstrap modes, forced diversification, quality gates.
THE DOCUMENTATION:
This isn't an indicator you throw on a chart with default settings and trade immediately. It's a learning system that requires understanding. The input tooltips alone contain over 10,000 words of guidance—market-specific recommendations, timeframe-specific settings, tradeoff explanations. Every parameter needed not just a description but a philosophical justification and practical tuning guide.
The code comments span 500+ lines explaining theory, implementation decisions, edge cases. Future maintainers (including myself in six months) need to understand not just what the code does but why certain approaches were chosen over alternatives.
WHAT ALMOST DIDN'T WORK:
The entire project nearly collapsed twice. First, when initial Lorentzian smoothing produced complete noise—hours of debugging revealed a simple indexing error where I was accessing instead of in the kernel loop. One character, entire system broken.
Second, when memory predictions showed zero correlation with outcomes. Turned out the KNN distance metric was dominated by the gamma dimension (values 1-10) drowning out normalized features (values -1 to 1). Solution: apply kernel transformation to all dimensions, not just final distance. Obvious in retrospect, maddening at the time.
THE PHILOSOPHY:
This system embodies a specific philosophy: markets are learnable but non-stationary. No single strategy works forever, but regime-specific patterns persist. Time isn't uniform, memory isn't perfect, prediction isn't possible—but probabilistic edges exist for those willing to track them rigorously.
It rejects the premise that indicators should give universal advice. Instead, it says: "In this regime, based on similar past states, Strategy B has a 58% win rate and 1.4 Sharpe. Strategy A has 45% and 0.2 Sharpe. I recommend B. But we're still in bootstrap for Strategy C, so I'm gathering data. Check back in 5 trades."
That humility—knowing what it knows and what it doesn't—is what makes it robust.
PART 14: PROFESSIONAL USAGE PROTOCOL
PHASE 1: DEPLOYMENT (Week 1-4)
Initial Setup:
1. Load indicator on primary trading chart with default settings
2. Verify historical pre-training enabled (should see ~200 patterns in STM/LTM on first load)
3. Enable all dashboard sections for maximum transparency
4. Set alerts but DO NOT trade real money
Observation Checklist:
• Dashboard Validation:
✓ Lorentzian Core shows reasonable gamma (1-5 range, not stuck at 1.0 or spiking to 10)
✓ HFL oscillates with price action (not flat or random)
✓ Regime classifications make intuitive sense
✓ Confidence scores vary appropriately
• Memory System:
✓ STM fills within first few hours/days of real-time bars
✓ LTM grows gradually (few patterns per day, quality-gated)
✓ Predictions show directional bias (not always 0.0)
✓ Agreement metric fluctuates with regime changes
• Bootstrap Tracking:
✓ Dashboard shows "🔥 BOOTSTRAP (X/10)" for each regime
✓ Trade counts increment on regime-specific signals
✓ Different regimes reach threshold at different rates
Paper Trading:
• Take EVERY signal (ignore unfavorable warnings during bootstrap)
• Log each trade: entry price, regime, selected strategy, outcome
• Calculate your actual P&L assuming proper risk management (1-2% risk per trade)
• Do NOT judge system performance yet—focus on understanding behavior
Troubleshooting:
• No signals for days:
- Check base_quality_threshold (try lowering to 50-55)
- Verify enable_regime_filter not blocking all regimes
- Confirm signal confidence threshold not too high (try 0.25)
• Signals every bar:
- Raise base_quality_threshold to 65-70
- Increase min_bars_between to 8-10
- Check if gamma spiking excessively (raise c_multiplier)
• Memory not filling:
- Confirm enable_memory = true
- Verify historical pre-training completed (check STM size after load)
- May need to wait 10 bars for first real-time update
PHASE 2: VALIDATION (Week 5-12)
Statistical Emergence:
By week 5-8, most regimes should exit bootstrap. Look for:
✓ Regime Performance Clarity:
- At least 2-3 strategies showing positive Sharpe in their favored regimes
- Clear separation (Strategy B strong in Trending, Strategy A strong in Low Vol Range, etc.)
- Win rates stabilizing around 50-60% for winning strategies
✓ Shadow Portfolio Divergence:
- Virtual portfolios showing clear winners ($10K → $11K+) and losers ($10K → $9K-)
- Profit factors >1.3 for top strategy
- System selection aligning with best shadow portfolio
✓ Parameter Adaptation:
- Thresholds varying per regime (not stuck at initial values)
- Quality gates adapting (some regimes higher, some lower)
- Flow multipliers showing regime-specific optimization
Validation Questions:
1. Do patterns make intuitive sense?
- Strategy B (Flow) dominating Trending Bull/Bear? ✓ Expected
- Strategy A (Squeeze) succeeding in Low Vol Range? ✓ Expected
- Strategy C (Memory) working in High Vol Range? ✓ Expected
- Random strategy winning everywhere? ✗ Problem
2. Is unfavorable filtering working?
- Regimes with negative Sharpe showing "⚠️ UNFAVORABLE"? ✓ System protecting capital
- Transition regime often unfavorable? ✓ Expected
- All regimes perpetually unfavorable? ✗ Settings too strict or asset unsuitable
3. Are memories agreeing appropriately?
- High agreement during stable regimes? ✓ Expected
- Low agreement during transitions? ✓ Expected (novel conditions)
- Perpetual conflict? ✗ Check memory sizes or decay rates
Fine-Tuning (If Needed):
Too Many Signals in Losing Regimes:
→ Increase learning_rate to 0.07-0.08 (faster adaptation)
→ Raise base_quality_threshold by 5-10 points
→ Enable regime filter if disabled
Missing Profitable Setups:
→ Lower base_quality_threshold by 5-10 points
→ Reduce min_confidence to 0.25-0.30
→ Check if bootstrap mode blocking trades (let it complete)
Excessive Parameter Swings:
→ Reduce learning_rate to 0.03-0.04
→ Increase min_regime_samples to 15-20 (more data before adaptation)
Memory Disagreement Too Frequent:
→ Increase LTM size to 768-1024 (broader pattern library)
→ Lower adaptive_quality_gate requirement (allow more patterns)
→ Increase K neighbors to 10-12 (smoother predictions)
PHASE 3: LIVE TRADING (Month 4+)
Pre-Launch Checklist:
1. ✓ At least 3 regimes show positive Sharpe (>0.8)
2. ✓ Top shadow portfolio shows >53% win rate and >1.3 profit factor
3. ✓ Parameters have stabilized (not changing more than 10% per month)
4. ✓ You understand every dashboard metric and can explain regime/strategy behavior
5. ✓ You have proper risk management plan independent of this system
Position Sizing:
Conservative (Recommended for Month 4-6):
• Risk per trade: 0.5-1.0% of account
• Max concurrent positions: 1-2
• Total exposure: 10-25% of intended full size
Moderate (Month 7-12):
• Risk per trade: 1.0-1.5% of account
• Max concurrent positions: 2-3
• Total exposure: 25-50% of intended size
Full Scale (Year 2+):
• Risk per trade: 1.5-2.0% of account
• Max concurrent positions: 3-5
• Total exposure: 100% (still following risk limits)
Entry Execution:
On Signal Confirmation:
1. Verify dashboard shows signal type (▲ LONG or ▼ SHORT)
2. Check regime mode (avoid if "⚠️ UNFAVORABLE" unless testing)
3. Note selected strategy (A/B/C) and its regime Sharpe
4. Verify memory agreement if Strategy C selected (want >60%)
Entry Method:
• Market entry: Next bar open after signal (for exact backtest replication)
• Limit entry: Slight improvement (2-3 ticks) if confident in direction
Stop Loss Placement:
• Strategy A (Squeeze): Beyond opposite band or recent swing point
• Strategy B (Flow): 1.5-2.0 ATR from entry against direction
• Strategy C (Memory): Based on predicted move magnitude (tighter if pred > 2%)
Exit Management:
System Exit Signals:
• Opposite signal fires: Immediate exit, potential reversal entry
• 20 bars no exit signal: System implies position stale, consider exiting
• Regime changes to unfavorable: Tighten stop, consider partial exit
Manual Exit Conditions:
• Stop loss hit: Take loss, log for validation (system expects some losses)
• Profit target hit: If using fixed targets (2-3R typical)
• Major news event: Flatten during high-impact news (system can't predict these)
Warning Signs (Exit Criteria):
🚨 Stop Trading If:
1. All regimes show negative Sharpe for 4+ weeks (market structure changed)
2. Your results >20% worse than shadow portfolios (execution problem)
3. Parameters hitting extremes (thresholds >85 or <35 across all regimes)
4. Memory agreement <30% for extended periods (unprecedented conditions)
5. Account drawdown >20% (risk management failure, system or otherwise)
⚠️ Reduce Size If:
1. Win rate drops 10%+ from peak (temporary regime shift)
2. Selected strategy underperforming another by >30% (selection lag)
3. Consecutive losses >5 (variance or problem, reduce until clarity)
4. Major market regime change (Fed policy shift, war, etc. - let system re-adapt)
PART 15: THEORETICAL IMPLICATIONS & LIMITATIONS
WHAT THIS SYSTEM REPRESENTS:
Contextual Bandits:
The regime-specific strategy selection implements a contextual multi-armed bandit problem. Each strategy is an "arm," each regime is a "context," and we select arms to maximize expected reward given context. This is reinforcement learning applied to trading.
Experience Replay:
The dual-memory architecture mirrors DeepMind's DQN breakthrough. STM = recent experience buffer; LTM = validated experience replay. This prevents catastrophic forgetting while enabling rapid adaptation—a key challenge in neural network training.
Meta-Learning:
The system learns how to learn. Parameter adaptation adjusts the system's own sensitivity and selectivity based on outcomes. This is "learning to learn"—optimizing the optimization process itself.
Non-Stationary Optimization:
Traditional backtesting assumes stationarity (past patterns persist). This system assumes non-stationarity and continuously adapts. The goal isn't finding "the best parameters" but tracking the moving optimum.
Regime-Conditional Policies:
Rather than a single strategy for all conditions, this implements regime-specific policies. This is contextual decision-making—environment state determines action selection.
FINAL WISDOM:
"The market is a complex adaptive system. To trade it successfully, one must also adapt. This indicator provides the framework—memory, learning, regime awareness—but wisdom comes from understanding when to trade, when to stand aside, and when to defer to conditions the system hasn't yet learned. The edge isn't in the algorithm alone; it's in the partnership between mathematical rigor and human judgment."
— Inspired by the intersection of Einstein's relativity, Kahneman's behavioral economics, and decades of quantitative trading research
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
COT Index by Luis TrompeterThe COT Index transforms the weekly COT net positions of Commercial traders into a normalized mathematical model.
Instead of displaying raw net positioning, the COT Index processes the data through a cyclical normalization algorithm (commonly using a 26-week or alternatively a 52-week cycle).
This makes it easier to identify bullish or bearish extremes in Commercial activity.
The index is plotted as a color-coded line:
• Green Zone – Commercials are mathematically classified as bullish.
Historically, bullish Commercial positioning often aligns with upward market pressure.
• Red Zone – Commercials are mathematically classified as bearish.
This typically corresponds with increased downward pressure in the underlying market.
• Neutral Zone – Neither bull nor bear dominance; positioning is mid-range.
Since COT data is published only once per week and the COT Index is built on cyclical multi-week analysis, the indicator is intended to be used exclusively on the weekly timeframe.
Using lower timeframes will not reflect the structure of the data accurately.
The selected cycle length (typically 26 weeks, optionally 52 weeks) determines how net positions are compared and normalized, and can influence how quickly extreme zones appear.
The COT Index provides an objective way to interpret Commercial trader sentiment and to identify potential directional bias in the market.
EMA & MA Alert Strategies8 Trading Strategies for Alerts:
Strategy 1: EMA Golden Cross / Death Cross
EMA1 crosses above EMA2 → bullish momentum
EMA1 crosses below EMA2 → bearish momentum
Stronger: EMA1 crosses EMA3
Strategy 2: MA Golden Cross / Death Cross
MA1 crosses above MA2 → trend reversal up
MA1 crosses below MA2 → trend reversal down
Strategy 3: EMA Alignment (Trend Direction)
Bullish: EMA1 > EMA2 > EMA3 (uptrend)
Bearish: EMA1 < EMA2 < EMA3 (downtrend)
Alerts when alignment changes
Strategy 4: Price vs EMA (Support/Resistance)
Price breaks above EMA2/EMA3 → bullish breakout
Price breaks below EMA2/EMA3 → bearish breakdown
Strategy 5: EMA vs MA Crossover
EMA1 crosses above MA1 → momentum exceeds trend
EMA2 crosses above MA2 → stronger momentum signal
Strategy 6: Pullback to EMA (Buy the Dip)
Price pulls back to EMA2/EMA3 and bounces → buy signal
Useful for entry during uptrends
Strategy 7: EMA Squeeze/Expansion
EMAs converging → potential breakout
EMAs expanding → trend acceleration
Strategy 8: Multi-Timeframe Confirmation
Price above all EMAs and MAs → strong uptrend
Price below all EMAs and MAs → strong downtrend
TradeBeard Larry Williams A/D + Classic DivergenceName: TradeBeard – Larry Williams A/D + Classic Divergence
What it does:
This indicator plots a classic Larry Williams Accumulation/Distribution (A/D) line, using:
(Close−Open)/(High−Low)×Volume
It then looks at price swings vs. A/D swings and marks true Larry-style divergences:
Bull Div – Price makes a lower low, but the A/D line makes a higher low → buying pressure/accumulation.
Bear Div – Price makes a higher high, but the A/D line makes a lower high → selling pressure/distribution.
Lines are drawn between the two pivots on the A/D line, with a label at the most recent pivot.
How to use / read it:
Use on any timeframe; the logic is the same.
Look for Bull Div near potential bottoms as confirmation that smart money is quietly buying.
Look for Bear Div near potential tops as confirmation that smart money is unloading.
Settings:
Pivot left bars (price) / Pivot right bars (price)
Controls how “wide” a swing high/low must be.
1 / 1 ≈ very sensitive (ICT/Larry-style 3-bar swings).
Higher values = fewer but cleaner swings and fewer signals.
Show bullish divergences / Show bearish divergences
Turn each signal type on or off.
Bullish color (line + label) / Bearish color (line + label)
Color of the divergence lines and label background.
Bullish label text color / Bearish label text color
Text color inside the Bull Div / Bear Div labels.
That’s it: pure Larry Williams A/D flow, price-based pivots, and clean visual divergence signals, wrapped in a TradeBeard skin.
I hope this will help you in your trading.
// Disclaimer:
// This script is for educational and informational purposes only.
// Trading and investing involve risk. You are fully responsible for your own decisions,
HTF EMA Ribbon Bias by HammerGeekThis indicator displays a higher-timeframe EMA-ribbon bias directly on any lower-timeframe chart. It uses four EMAs (5, 9, 13, 21) computed on the selected higher timeframe and detects the directional “stacking” of those EMAs to determine trend bias:
Bullish: EMAs are strictly stacked 5 > 9 > 13 > 21 (fully separated, no overlap)
Bearish: EMAs are strictly stacked 5 < 9 < 13 < 21
Neutral: Any overlap, crossing, or mixed order between the four EMAs
The indicator shades the background to show the bias: green for bullish, red for bearish, yellow for neutral. A built-in toggle lets you choose whether the bias should update live from the current higher-timeframe candle (faster, but may repaint) or only after the higher-timeframe candle closes (slower, but non-repainting).
Designed for traders who want clean, instantly readable higher-timeframe context—especially when working on lower-timeframe charts such as 30m, 15m, or 5m.
All settings can be modified to suit users' desires.
Advanced Market Profile & S/R Zones (Pro)Advanced Market Profile & S/R Zones
This indicator brings professional Auction Market Theory to your chart using a custom rolling Volume Profile algorithm. Unlike standard profiles that remain fixed, this tool dynamically calculates the "Fair Value" of the asset based on your specific lookback period (e.g., the last 100 bars).
It automatically highlights the Point of Control (POC), Value Area (VA), and suggests statistical Discount (Buy) and Premium (Sell) zones.
Key Features
Volume Splitting Algorithm:
Most basic scripts dump the entire volume of a candle into a single price point (the average). This script splits the volume across the candle's entire High-Low range. This results in a much smoother, higher-resolution bell curve that accurately reflects price action, especially on higher timeframes like Monthly charts.
Auto-generated Zones:
Green Zone (Discount): Prices below the Value Area Low (VAL). Statistically "cheap."
Red Zone (Premium): Prices above the Value Area High (VAH). Statistically "expensive."
Real-Time Dashboard:
A built-in panel displays the exact price levels for the POC, VAH, and VAL for precise limit order placement, along with the current Market Trend.
How to Use
For Intraday (Day Trading):
Settings: Set Lookback to 100 - 300.
Strategy: Watch for price to open outside the Value Area. If price breaks back inside the Value Area, target the POC (Red Line).
For Macro (Monthly/Weekly Charts):
Settings: Set Lookback to 12 (1 Year) or 60 (5 Years).
Strategy: Identify multi-year structural support. When a monthly candle enters the Green Discount Zone of a 5-year profile, it is often a high-probability institutional entry point.
Trend Logic
The Dashboard indicates trend based on price location relative to value:
Strong Bullish: Price is accepted ABOVE the Value Area.
Strong Bearish: Price is accepted BELOW the Value Area.
Neutral / In VA: Price is chopping inside the Value Area.
Disclaimer
This is a "Rolling Profile." It calculates the profile based on the current lookback window relative to the latest bar. As new bars form, the lookback window shifts, and the profile updates to reflect the new dataset.
Piku Pips📌 Piku Pips — Multi-Confluence Smart Signal System (EMA + Supertrend + Volume Profile + ATR Trailing + SR + RSI Climax Engine)
Piku Pips is a complete multi-confluence trading system designed for scalpers, intraday traders, and swing traders who rely on precision entries and institutional-grade confirmation layers.
This indicator combines trend, momentum, volatility, volume imbalance, structure breaks, smart money pivots, and exhaustion events—into a single unified charting system.
It does NOT repaint, supports alerts, and works across all assets (crypto, forex, indices, stocks).
🔥 What Makes This Indicator Special?
Piku Pips is built on stacked confluences instead of single-indicator signals.
Each signal is only printed when multiple conditions align, significantly increasing accuracy and reducing noise.
It includes:
✔ Trend Identification
Fast & Slow EMA cross
SuperTrend with custom ATR & factor
Parabolic SAR for micro-trend confirmation
ATR-based trailing stop engine (dual version for Buy & Sell)
✔ Momentum Confirmation
RSI Midline model
HH/LL structure detection
Bull/Bear volume imbalance model
✔ Smart Volume Analysis
Bullish vs Bearish VWMA volume
Flat-volume filters
RSI + Volume Spike + MFI exhaustion detection (Climax Module)
✔ Institutional Structure Mapping
Dynamic Support & Resistance
Automatic Zone Strength Ranking
Breakout detection with zone coloring
Pivot-based structure scanning
✔ Exhaustion + Divergence Engine (Climax Module)
RSI / Stochastic RSI hybrid
Macro trend smoothing (EMA/RMA/SMA/WMA selectable)
High-precision RSI divergence detection (HH/LH and LL/HL)
Volume spike detection
Buy Climax (potential top)
Sell Climax (potential bottom)
This module acts like a “smart momentum brain” that identifies major reversals.
🎯 Signal Logic (Simplified)
🔹 Buy Signal (Green Triangle)
Triggered when:
Fast EMA crosses above Slow EMA
Higher High structure forms
RSI > midline or crosses above it
Volume profile is bullish
SuperTrend is bullish (direction < 0)
🔹 Sell Signal (Red Triangle)
Triggered when:
Fast EMA crosses below Slow EMA
Lower Low structure forms
RSI < midline or crosses below it
Volume profile is bearish
SuperTrend is bearish (direction > 0)
🔸 Secondary ATR Signals (Orange & Maroon)
Uses Heikin-Ashi ATR trailing stop
Detects micro-shifts in trend momentum
Works excellent in scalping timeframes
🧠 Support & Resistance Engine
The script builds dynamic SR zones based on:
Pivot clustering
Channel width filtering
Strength scoring
Automated sorting and plotting
Zones:
Red tint = Resistance
Green tint = Support
Gray tint = Neutral / In-Play
Alerts trigger on clean SR breaks.
⚡ Climax Module (Exhaustion System)
This system overlays major exhaustion points:
🔻 Buy Climax
High-volume upward exhaustion → potential top.
🔺 Sell Climax
High-volume downward exhaustion → potential bottom.
🔼 RSI Divergences
Bullish divergence labeled "RSI⬆"
Bearish divergence labeled "RSI⬇"
Combined, these give early insight into possible reversals.
🛠 Inputs Overview
📌 Trend Inputs
Fast EMA Length
Slow EMA Length
SuperTrend ATR + Factor
SAR multipliers
Buy/Sell ATR trailing stop parameters
📌 Momentum Inputs
RSI length / midline
Bull/Bear volume variance filter
HH/LL confirmation
📌 Structure Inputs
Pivot sensitivity
Max SR Zones
Loopback length
Zone strength minimum
📌 Climax Module Inputs
RSI / Stochastic lengths
Smoothing method (EMA, SMA, RMA, WMA)
Macro trend slope settings
Pivot sensitivity for divergence
Volume spike multiplier
MFI thresholds
Bull/Bear RSI levels
📈 How to Use Piku Pips
Best Use-Cases:
Scalping (1m–15m)
Intraday (15m–1H)
Swing trading (4H–1D)
Crypto / Forex / Indices / Stocks
Recommended Approach
Trade in direction of EMA + Supertrend + Macro RSI regime.
Enter when Piku Buy/Sell signal aligns with the trend.
Use SR zones as targets or invalidation levels.
Watch Climax signals for tops & bottoms.
Use divergence signals for early reversals.
🔔 Alerts Included
Buy Signal
Sell Signal
ATR Buy / Sell
Buy Climax
Sell Climax
RSI Divergence (bullish & bearish)
All-Signals alert
⚠️ Disclaimer
This indicator is created for educational purposes only and does not constitute financial advice.
Trading involves risk. Do your own research and backtesting before using any tool in live markets.
Timeframe Fast EMA Slow EMA ATR Period Factor RSI Length Overbought/Oversold
5 Min 9 21 10 2 8 80 / 20
15 Min 10 25 10 2.5 10 75/25
1 Hour 20 50 14 3 12 70/30
4 Hour 21 50 14 3 14 70/30
1 Day 20 100 14 3.5 14 70/30
Please use this settings for accurate results
RT-Anchored OBVOBV, or On Balance Volume, is a classic tool for traders who want to pick up on subtle shifts in buying and selling pressure that price alone may not show. It accumulates volume up or down depending on whether price closes higher or lower, creating a running total of “who is in control” behind the candles.
Introduction
This Anchored OBV builds on the base OBV concept and pushes it a step further by anchoring the OBV calculation to a specific lookback window. It also adds color coding and a bull/bear midpoint line so traders can more easily see when the trend in Anchored OBV is tilting bullish or bearish over the selected window.
How The Anchor Works
Traditional OBV is cumulative from the start of the chart, which means very old data can still influence the current line. Anchored OBV instead focuses on a moving “anchor” window:
Anchored OBV is recalculated over a sliding lookback range defined by the Anchor Historical Length (in bars).
As each new candle forms, the window rolls forward, effectively re-anchoring Anchored OBV to recent data.
A central bull/bear trend line is drawn as a midpoint so traders can see when Anchored OBV is spending more time above (bullish) or below (bearish) that level.
This approach allows the indicator to respond to changes in trend over a defined period, rather than carrying the full history of older market regimes. In the example image, the built-in OBV is shown alongside Anchored OBV so you can see how the anchored version reacts differently to recent data.
Reading The Color States
The Anchored OBV line is color-coded so trend states are easy to read at a glance:
Bull Trend – Anchored OBV is rising and holding above the midpoint line, suggesting sustained accumulation over the anchor window.
Bear Trend – Anchored OBV is falling and holding below the midpoint line, suggesting sustained distribution over the anchor window.
Neutral / Transition Zone – Anchored OBV is flat or choppy around the midpoint, often marking consolidation or a potential shift in control.
By watching how long Anchored OBV stays in each state, traders can quickly judge whether a move is being supported or faded by underlying volume.
Spotting BART / Distribution Style Setups
One practical use for Anchored OBV is to help identify situations where price chops sideways but volume is quietly bleeding in one direction. For example:
Price may move sideways in a tight range while Anchored OBV trends lower below the midpoint, which can hint at stealth distribution before a breakdown.
Conversely, price can drift sideways while Anchored OBV trends higher above the midpoint, hinting at accumulation before an upside expansion.
These types of “OBV diverging while price is flat” sequences are easier to see when Anchored OBV is anchored to a fixed window instead of the entire chart history. In the example image, we can see Anchored OBV trending downwards and holding below the midpoint before price breaks down from the sideways range; the Bart doodle on the price pane highlights that structure visually.
Settings
Three main settings can be adjusted by the trader:
Rainbow Color Threshold – Adjusts the threshold that controls when the Anchored OBV line changes color between bullish, bearish, or neutral states.
Rainbow Color Sensitivity – Adjusts how sensitive the color changes are to shifts in Anchored OBV. Higher sensitivity will flip colors more quickly; lower sensitivity will require stronger moves in Anchored OBV.
Anchor Historical Length (bars) – Controls how far back the Anchored OBV “anchor” looks in time. Shorter windows make the tool more reactive to recent activity; longer windows smooth out the line and focus on bigger trends.
Different markets and timeframes may benefit from different combinations of these settings. Many traders will use a longer anchor on higher timeframes and a shorter one for intraday work.
What Makes This Tool Different
While standard OBV is widely available, this Anchored OBV is tailored for traders who want a more localized, regime-aware view of volume pressure:
It recalculates Anchored OBV over a rolling anchor window instead of relying on the entire chart history.
It introduces a clear bull/bear midpoint line to separate accumulation from distribution within that window.
It adds a configurable color-coding layer so trend states and transitions are visually obvious without needing additional oscillators.
It is designed to work alongside price structure, volume profile, or other tools as a dedicated “volume trend lens” rather than a generic momentum overlay.
Important Note
This indicator is intended to provide additional context around volume trends and accumulation/distribution behavior. It is not a standalone signal generator and should always be used together with your own analysis, testing, and risk management. Historical Anchored OBV behavior does not guarantee future results.
🐋 Tight lines and happy trading!
Raymond Swing Day [Qanexra] - The Multi-Timeframe Level PlannerThe Raymond Swing Day indicator is the essential final piece of the Qanexra trading suite. While RaymondTrending confirms momentum and RaymondRatio filters noise, this tool provides the critical price levels necessary to execute trades with precision.
It automatically calculates and plots Fibonacci Pivot Points across various timeframes, transforming static price action into a dynamic roadmap for the trading day or week.
Why Use Pivot Points? Pivot Points are foundational tools, acting as gravitational price levels where supply and demand are expected to meet or reverse. They are crucial for setting:
Entry Zones
Stop-Loss (Invalidation)
Take-Profit Targets
Core Features & Calculation:
Advanced Fibonacci Pivots: Calculates the central , three Resistance , and three Support levels using the widely respected Fibonacci formula.
Flexible Timeframe Engine: Choose a major anchor timeframe (Daily, Weekly, Monthly, etc.) or set it to Auto for adaptive level calculation.
Multi-Layer Overlay: Simultaneously view price levels from up to three different timeframes (e.g., Daily, overlaid with 120m/H2, and 30m/M30 levels) to identify areas of confluence—the strongest decision zones.
Clear Trading Interpretation: Each level comes with a label indicating its suggested use:
Look for Entry: The central decision point.
Bullish/Bearish Try to Extend: The initial boundary for a directional move.
Bullish/Bearish Take Profit: Common targets for intraday or swing moves.
Aggressive Bullish/Bearish: Extreme levels for high-volatility moves or max extension targets.
Integration with the Qanexra Suite: Combine Raymond Swing Day levels with:
RaymondTrending confirmation of momentum.
RaymondRatio filter for noise avoidance.
When your volatility indicators confirm a breakout, the Raymond Swing Day levels tell you exactly where to enter and where to target your exit.
RSI VWAP EMA ON CHART1. Understand the components
VWAP (Volume Weighted Average Price)
Green: price is above VWAP → bullish trend
Red: price is below VWAP → bearish trend
Blue: price exactly at VWAP → neutral
Acts as a dynamic trend line and support/resistance.
4 Moving Averages (MA1–MA4)
Customizable lengths and type (SMA or EMA).
Useful for trend confirmation and dynamic support/resistance.
Typically:
MA1 = fastest (short-term)
MA4 = slowest (long-term)
When price is above multiple MAs → strong bullish trend; below → bearish trend.
RSI Overlay with VWAP Alignment
RSI line normalized to price scale.
Background shading indicates momentum aligned with VWAP trend:
Green shading: RSI > 50 and price above VWAP → bullish momentum
Red shading: RSI < 50 and price below VWAP → bearish momentum
Gray areas: neutral or momentum does not align with VWAP.
2. Basic usage workflow
Trend Confirmation
Look at VWAP color: price above → bullish, below → bearish.
Check RSI + VWAP shading: green confirms bullish momentum, red confirms bearish momentum.
Check MA alignment: shorter MAs above longer MAs = stronger bullish trend; vice versa for bearish.
Entry Signals (Scalping)
Long (Buy) Setup
Price above VWAP (green)
RSI green shading (RSI > 50)
Shorter MAs above longer MAs (trend support)
Short (Sell) Setup
Price below VWAP (red)
RSI red shading (RSI < 50)
Shorter MAs below longer MAs
Exits / Stops
Exit if price closes against VWAP trend (e.g., price drops below VWAP during a bullish trade).
Use nearest MA support/resistance as stop-loss or take-profit zones.
3. Optional adjustments for scalping
RSI length / thresholds
Shorter RSI (7–10) → faster response for scalping.
Standard RSI (14) → smoother, fewer false signals.
MA lengths
Short-term: 20–50
Medium-term: 50–100
Long-term: 100–200
Can tweak for the timeframe you trade (1m, 5m, 15m).
Timeframe
VWAP works best on intraday charts (1m, 5m, 15m).
Use higher timeframe (e.g., 15m or 1h) for trend direction and lower timeframe (1m–5m) for entries.
4. Example Scalping Setup
Bullish setup (buy):
Price above VWAP → VWAP green
RSI > 50 and green shading
Shorter MAs above longer MAs
Enter on small pullback or breakout
Stop: below nearest MA or VWAP
Bearish setup (sell):
Price below VWAP → VWAP red
RSI < 50 and red shading
Shorter MAs below longer MAs
Enter on minor bounce or breakdown
Stop: above nearest MA or VWAP
5. Visual cues summary
Element Interpretation
VWAP Green Price above VWAP → bullish trend
VWAP Red Price below VWAP → bearish trend
RSI Green Shading Bullish momentum aligns with VWAP
RSI Red Shading Bearish momentum aligns with VWAP
MA Alignment Trend strength (short above long = bullish, short below long = bearish)
VWAP + 4 MAs with RSI Overlay & VWAP Alignment1. Understand the components
VWAP (Volume Weighted Average Price)
Green: price is above VWAP → bullish trend
Red: price is below VWAP → bearish trend
Blue: price exactly at VWAP → neutral
Acts as a dynamic trend line and support/resistance.
4 Moving Averages (MA1–MA4)
Customizable lengths and type (SMA or EMA).
Useful for trend confirmation and dynamic support/resistance.
Typically:
MA1 = fastest (short-term)
MA4 = slowest (long-term)
When price is above multiple MAs → strong bullish trend; below → bearish trend.
RSI Overlay with VWAP Alignment
RSI line normalized to price scale.
Background shading indicates momentum aligned with VWAP trend:
Green shading: RSI > 50 and price above VWAP → bullish momentum
Red shading: RSI < 50 and price below VWAP → bearish momentum
Gray areas: neutral or momentum does not align with VWAP.
2. Basic usage workflow
Trend Confirmation
Look at VWAP color: price above → bullish, below → bearish.
Check RSI + VWAP shading: green confirms bullish momentum, red confirms bearish momentum.
Check MA alignment: shorter MAs above longer MAs = stronger bullish trend; vice versa for bearish.
Entry Signals (Scalping)
Long (Buy) Setup
Price above VWAP (green)
RSI green shading (RSI > 50)
Shorter MAs above longer MAs (trend support)
Short (Sell) Setup
Price below VWAP (red)
RSI red shading (RSI < 50)
Shorter MAs below longer MAs
Exits / Stops
Exit if price closes against VWAP trend (e.g., price drops below VWAP during a bullish trade).
Use nearest MA support/resistance as stop-loss or take-profit zones.
3. Optional adjustments for scalping
RSI length / thresholds
Shorter RSI (7–10) → faster response for scalping.
Standard RSI (14) → smoother, fewer false signals.
MA lengths
Short-term: 20–50
Medium-term: 50–100
Long-term: 100–200
Can tweak for the timeframe you trade (1m, 5m, 15m).
Timeframe
VWAP works best on intraday charts (1m, 5m, 15m).
Use higher timeframe (e.g., 15m or 1h) for trend direction and lower timeframe (1m–5m) for entries.
4. Example Scalping Setup
Bullish setup (buy):
Price above VWAP → VWAP green
RSI > 50 and green shading
Shorter MAs above longer MAs
Enter on small pullback or breakout
Stop: below nearest MA or VWAP
Bearish setup (sell):
Price below VWAP → VWAP red
RSI < 50 and red shading
Shorter MAs below longer MAs
Enter on minor bounce or breakdown
Stop: above nearest MA or VWAP
5. Visual cues summary
Element Interpretation
VWAP Green Price above VWAP → bullish trend
VWAP Red Price below VWAP → bearish trend
RSI Green Shading Bullish momentum aligns with VWAP
RSI Red Shading Bearish momentum aligns with VWAP
MA Alignment Trend strength (short above long = bullish, short below long = bearish)
XAUUSD Sniper Setup (Pre-Arrows + SL/TP)//@version=5
indicator("XAUUSD Sniper Setup (Pre-Arrows + SL/TP)", overlay=true)
// === Inputs ===
rangePeriod = input.int(20, "Lookback Bars for Zone", minval=5)
maxRangePercent = input.float(0.08, "Max Range % for Consolidation", step=0.01)
tpMultiplier = input.float(1.5, "TP Multiplier")
slMultiplier = input.float(1.0, "SL Multiplier")
// === Consolidation Detection ===
highestPrice = ta.highest(high, rangePeriod)
lowestPrice = ta.lowest(low, rangePeriod)
priceRange = highestPrice - lowestPrice
percentRange = (priceRange / close) * 100
isConsolidation = percentRange < maxRangePercent
// === Zones ===
demandZone = lowestPrice
supplyZone = highestPrice
// === Plot Consolidation Zone Background ===
bgcolor(isConsolidation ? color.new(color.gray, 85) : na)
// === Plot Potential Buy/Sell Levels ===
plot(isConsolidation ? demandZone : na, color=color.green, title="Potential Buy Level", linewidth=2)
plot(isConsolidation ? supplyZone : na, color=color.red, title="Potential Sell Level", linewidth=2)
// === Liquidity Sweep ===
liquidityTakenBelow = low < demandZone
liquidityTakenAbove = high > supplyZone
// === Engulfing Candles ===
bullishEngulfing = close > open and close < open and close > open
bearishEngulfing = close < open and close > open and close < open
// === Break of Structure ===
bosUp = high > ta.highest(high , 5)
bosDown = low < ta.lowest(low , 5)
// === Sniper Entry Conditions ===
buySignal = isConsolidation and liquidityTakenBelow and bullishEngulfing and bosUp
sellSignal = isConsolidation and liquidityTakenAbove and bearishEngulfing and bosDown
// === SL & TP Levels ===
slBuy = demandZone - (priceRange * slMultiplier)
tpBuy = close + (priceRange * tpMultiplier)
slSell = supplyZone + (priceRange * slMultiplier)
tpSell = close - (priceRange * tpMultiplier)
// === PRE-ARROWS (Show Before Breakout) ===
preBuyArrow = isConsolidation ? 1 : na
preSellArrow = isConsolidation ? -1 : na
plotarrow(preBuyArrow, colorup=color.new(color.green, 50), maxheight=20, minheight=20, title="Pre-Buy Arrow")
plotarrow(preSellArrow, colordown=color.new(color.red, 50), maxheight=20, minheight=20, title="Pre-Sell Arrow")
// === SNIPER CONFIRMATION ARROWS ===
buyArrow = buySignal ? 1 : na
sellArrow = sellSignal ? -1 : na
plotarrow(buyArrow, colorup=color.green, maxheight=60, minheight=60, title="Sniper BUY Arrow")
plotarrow(sellArrow, colordown=color.red, maxheight=60, minheight=60, title="Sniper SELL Arrow")
// === BUY SIGNAL ===
if buySignal
label.new(bar_index, low, "BUY\nSL/TP Added", style=label.style_label_up, color=color.green, textcolor=color.white)
line.new(bar_index, slBuy, bar_index + 5, slBuy, color=color.red, style=line.style_dotted)
line.new(bar_index, tpBuy, bar_index + 5, tpBuy, color=color.green, style=line.style_dotted)
label.new(bar_index, slBuy, "SL", color=color.red, style=label.style_label_down)
label.new(bar_index, tpBuy, "TP", color=color.green, style=label.style_label_up)
// === SELL SIGNAL ===
if sellSignal
label.new(bar_index, high, "SELL\nSL/TP Added", style=label.style_label_down, color=color.red, textcolor=color.white)
line.new(bar_index, slSell, bar_index + 5, slSell, color=color.red, style=line.style_dotted)
line.new(bar_index, tpSell, bar_index + 5, tpSell, color=color.green, style=line.style_dotted)
label.new(bar_index, slSell, "SL", color=color.red, style=label.style_label_up)
label.new(bar_index, tpSell, "TP", color=color.green, style=label.style_label_down)
// === Alerts ===
alertcondition(buySignal, title="Sniper BUY", message="Sniper BUY setup on XAUUSD")
alertcondition(sellSignal, title="Sniper SELL", message="Sniper SELL setup on XAUUSD")
OANDA:XAUUSD
FxAST Ichi ProSeries Enhanced Full Market Regime EngineFxAST Ichi ProSeries v1.x is a modernized Ichimoku engine that keeps the classic logic but adds a full market regime engine for any market and instrument.”
Multi-timeframe cloud overlay
Oracle long-term baseline
Trend regime classifier (Bull / Bear / Transition / Range)
Chikou & Cloud breakout signals
HTF + Oracle + Trend dashboard
Alert-ready structure for automation
No repainting: all HTF calls use lookahead_off.
1. Core Ichimoku Engine
Code sections:
Input group: Core Ichimoku
Function: ichiCalc()
Variables: tenkan, kijun, spanA, spanB, chikou
What it does
Calculates the classic Ichimoku components:
Tenkan (Conversion Line) – fast Donchian average (convLen)
Kijun (Base Line) – slower Donchian average (baseLen)
Senkou Span A (Span A / Lead1) – (Tenkan + Kijun)/2
Senkou Span B (Span B / Lead2) – Donchian over spanBLen
Chikou – current close shifted back in time (displace)
Everything else in the indicator builds on this engine.
How to use it (trading)
Tenkan vs Kijun = short-term vs medium-term balance.
Tenkan above Kijun = short-term bullish control; below = bearish control.
Span A / B defines the cloud, which represents equilibrium and support/resistance.
Price above cloud = bullish bias; price below cloud = bearish bias.
Graphic
2. Display & Cloud Styling
Code sections:
Input groups: Display Options, Cloud Styling, Lagging Span & Signals
Variables: showTenkan, showKijun, showChikou, showCloud, bullCloudColor, bearCloudColor, cloudLineWidth, laggingColor
Plots: plot(tenkan), plot(kijun), plot(chikou), p1, p2, fill(p1, p2, ...)
What it does
Lets you toggle individual components:
Show/hide Tenkan, Kijun, Chikou, and the cloud.
Customize cloud colors & opacity:
bullCloudColor when Span A > Span B
bearCloudColor when Span A < Span B
Adjust cloud line width for clarity.
How to use it
Turn off components you don’t use (e.g., hide Chikou if you only want cloud + Tenkan/Kijun).
For higher-timeframe or noisy charts, use thicker Kijun & cloud so structure is easier to see.
Graphic
Before
After
3. HTF Cloud Overlay (Multi-Timeframe)
Code sections:
Input group: HTF Cloud Overlay
Vars: showHTFCloud, htfTf, htfAlpha
Logic: request.security(..., ichiCalc(...)) → htfSpanA, htfSpanB
Plots: pHTF1, pHTF2, fill(pHTF1, pHTF2, ...)
What it does
Pulls higher-timeframe Ichimoku cloud (e.g., 1H, 4H, Daily) onto your current chart.
Uses the same Ichimoku settings but aggregates on htfTf.
Plots an extra, semi-transparent cloud ahead of price:
Greenish when HTF Span A > Span B
Reddish when HTF Span B > Span A
How to use it
Trade LTF (e.g., 5m/15m) only in alignment with HTF trend:
HTF cloud bullish + LTF Ichi bullish → look for longs
HTF cloud bearish + LTF Ichi bearish → look for shorts
Treat HTF cloud boundaries as major S/R zones.
Graphic
4. Oracle Module
Code sections:
Input group: Oracle Module
Vars: useOracle, oracleLen, oracleColor, oracleWidth, oracleSlopeLen
Logic: oracleLine = donchian(oracleLen); slope check vs oracleLine
Plot: plot(useOracle ? oracleLine : na, "Oracle", ...)
What it does
Creates a long-term Donchian baseline (default 208 bars).
Uses a simple slope check:
Current Oracle > Oracle oracleSlopeLen bars ago → Oracle Bull
Current Oracle < Oracle oracleSlopeLen bars ago → Oracle Bear
Slope state is also shown in the dashboard (“Bull / Bear / Flat”).
How to use it
Think of Oracle as your macro anchor :
Only take longs when Oracle is sloping up or flat.
Only take shorts when Oracle is sloping down or flat.
Works well combined with HTF cloud:
HTF cloud bullish + Oracle Bull = higher conviction long bias.
Ideal for Gold / Indices swing trades as a trend filter.
Graphic idea
5. Trend Regime Classifier
Code sections:
Input group: Trend Regime Logic
Vars: useTrendRegime, bgTrendOpacity, minTrendScore
Logic:
priceAboveCloud, priceBelowCloud, priceInsideCloud
Tenkan vs Kijun alignment
Cloud bullish/bearish
bullScore / bearScore (0–3)
regime + regimeLabel + regimeColor
Visuals: bgcolor(regimeColor) and optional barcolor() in priceColoring mode.
What it does
Scores the market in three dimensions :
Price vs Cloud
Tenkan vs Kijun
Cloud Direction (Span A vs Span B)
Each condition contributes +1 to either bullScore or bearScore .
Then:
Bull regime when:
bullScore >= minTrendScore and bullScore > bearScore
Price in cloud → “Range”
Everything else → “Transition”
These regimes are shown as:
Background colors:
Teal = Bull
Maroon = Bear
Orange = Range
Silver = Transition
Optional candle recoloring when priceColoring = true.
How to use it
Filters:
Only buy when regime = Bull or Transition and Oracle/HTF agree.
Only sell when regime = Bear or Transition and Oracle/HTF agree.
No trade zone:
When regime = Range (price inside cloud), avoid new entries; wait for break.
Aggressiveness:
Adjust minTrendScore to be stricter (3) or looser (1).
Graphic
6. Signals: Chikou & Cloud Breakout
Code sections :
Logic:
chikouBuySignal = ta.crossover(chikou, close)
chikouSellSignal = ta.crossunder(chikou, close)
cloudBreakUp = priceInsideCloud and priceAboveCloud
cloudBreakDown = priceInsideCloud and priceBelowCloud
What it does
1. Two key signal groups:
Chikou Cross Signals
Buy when Chikou crosses up through price.
Sell when Chikou crosses down through price.
Classic Ichi confirmation idea: Chikou breaking free of price cluster.
2. Cloud Breakout Signals
Long trigger: yesterday inside cloud → today price breaks above cloud.
Short trigger: yesterday inside cloud → today price breaks below cloud.
Captures “equilibrium → expansion” moves.
These are conditions only in this version (no chart shapes yet) but are fully wired for alerts. (Future Updates)
How to use it
Use Chikou signals as confirmation, not standalone entries:
Eg., Bull regime + Oracle Bull + cloud breakout + Chikou Buy.
Use Cloud Breakouts to catch the first impulsive leg after consolidation.
Graphic
7. Alerts (Automation Ready)
[
b]Code sections:
Input group: Alerts
Vars: useAlertTrend, useAlertChikou, useAlertCloudBO
Alert lines like: "FxAST Ichi Bull Trend", "FxAST Ichi Bull Trend", "FxAST Ichi Cloud Break Up"
What it does
Provides ready-made alert hooks for:
Trend regime (Bull / Bear)
Chikou cross buy/sell
Cloud breakout up/down
Each type can be globally toggled on/off via the inputs (helpful if a user only wants one kind).
How to use it
In TradingView: set alerts using “Any alert() function call” on this indicator.
Then filter which ones fire by:
Turning specific alert toggles on/off in input panel, or
Filtering text in your external bot / webhook side.
Example simple workflow ---> Indicator ---> TV Alert ---> Webhook ---> Bot/Broker
8. FxAST Dashboard
Code sections:
Input group: Dashboard
Vars: showDashboard, dashPos, dash, dashInit
Helper: getDashPos() → position.*
Table cells (updated on barstate.islast):
Row 0: Regime + label
Row 1: Oracle status (Bull / Bear / Flat / Off)
Row 2: HTF Cloud (On + TF / Off)
Row 3: Scores (BullScore / BearScore)
What it does
Displays a compact panel with the state of the whole system :
Current Trend Regime (Bull / Bear / Transition / Range)
Oracle slope state
Whether HTF Cloud is active + which timeframe
Raw Bull / Bear scores (0–3 each)
Position can be set: Top Right, Top Left, Bottom Right, Bottom Left.
How to use it
Treat it like a pilot instrument cluster :
Quick glance: “Are my trend, oracle and HTF all aligned?”
Great for streaming / screenshots: everything important is visible in one place without reading the code.
Graphic (lower right of chart )
Global M2 ex-China MonitorGlobal M2 Monitor - Ultimate Edition
🎯 OVERVIEW
Advanced global M2 money supply monitoring indicator, offering a unique macroeconomic view of global liquidity. Real-time tracking of M2 evolution in major developed economies.
📊 KEY FEATURES
Global M2 Aggregation : USA, Japan, Canada, Eurozone, United Kingdom
Currency Conversion : All data converted to USD for consistent analysis
High Resolution Display : Daily curve by default
Technical Analysis : 50-period moving average (SMA/EMA/WMA)
Accurate YoY Calculation : Annual variation based on monthly data
Advanced Signal System : Multi-condition color codes
🎨 COLOR SYSTEM - DEFAULT SETTINGS
🟢 GREEN : YoY ≥ 7% AND M2 ≥ SMA → Strong growth + Bullish momentum
🔴 RED : YoY ≤ 2% AND M2 ≤ SMA → Weak growth + Bearish momentum
🟢 LIGHT GREEN : YoY ≥ 7% BUT M2 < SMA → Good fundamentals, temporarily weak momentum
🔴 LIGHT RED : YoY ≤ 2% BUT M2 > SMA → Weak fundamentals, price still supported
🔵 BLUE : YoY between 2% and 7% → Neutral zone of moderate growth
🇨🇳 WHY IS CHINA EXCLUDED BY DEFAULT?
Chinese M2 data presents methodological reliability and transparency issues. Exclusion allows for more consistent analysis of mature market economies.
Different M2 definition vs Western standards
Capital controls affecting real convertibility
Frequent monetary manipulations by authorities
✅ Available option : Can be activated in settings
⚙️ OPTIMIZED DEFAULT PARAMETERS
// DISPLAY SETTINGS
Candle Period: D (Daily)
// MOVING AVERAGE
MA Period: 50, Type: SMA
// BACKGROUND LOGIC
YoY Bullish: 7%, YoY Bearish: 2%
SMA Method: absolute, Threshold: 0.2%
// COLORS
Transparency: 5%
China M2: Disabled
📈 RECOMMENDED USAGE
Traders : Anticipate sector rotations
Investors : Identify abundant/restricted liquidity phases
Macro-analysts : Monitor monetary policy impacts
Portfolio managers : Understand inflationary pressures
🔍 ADVANCED INTERPRETATION
M2 ↗️ + YoY ≥ 7% → Favorable risk-on environment
M2 ↘️ + YoY ≤ 2% → Defensive risk-off environment
Divergences → Early warning signals for trend changes
💡 WHY THIS INDICATOR?
Global money supply is the lifeblood of the financial economy . Its growth or contraction typically precedes market movements by 6 to 12 months.
"Don't fight the Fed... nor the world's central banks"
🛠️ ADVANCED CUSTOMIZATION
All parameters are customizable:
YoY bullish/bearish thresholds
SMA comparison method (absolute/percentage)
Colors and transparency
Moving average period and type
Optional China inclusion
📋 TECHNICAL INFORMATION
YoY Calculation : Based on monthly data for consistency
Sources : FRED, ECONOMICS, official data
Updates : Real-time with publications
Currencies : Updated exchange rates
Market Breadth Decision HelperMarket Breadth Decision Helper (NYSE/NASDAQ VOLD, ADD, TICK)
Combines NYSE VOLD, NASDAQ VOLD (VOLDQ), NYSE/NASDAQ ADD, and TICK into a single intraday dashboard for tactical bias and risk management.
Tiered pressure scale (sign shows direction, abs(tier) shows intensity): 0 = Neutral, 1 = Mild, 2 = Strong, 3 = Severe, 4 = Panic. On-chart legend makes this explicit.
Table view highlights value, tier, bull/bear point contributions, and notes (PANIC, OVERRIDE, DIVERGENCE). VOLD and ADD panic trigger “stand down”; VOLD ±2 triggers bull/bear overrides; NYSE vs NASDAQ ADD divergence triggers “scalp only.”
Bull/bear points: VOLD 2 pts, ADD NYSE 2 pts, ADD NASDAQ 1 pt, TICK 1 pt. ≥3 pts on a side lifts that side’s multiplier to 1.5. Bias flips Bullish/Bearish only if a side leads and has ≥2 pts; otherwise Neutral.
Breadth modes: PANIC_NO_TRADE → DIVERGENCE_SCALP_ONLY → VOLD_OVERRIDE_BULL/BEAR → NORMAL/NO_EDGE.
Intraday context: tracks current session day_high / day_low for the chart symbol.
JSON/Alert export (optional) sends raw values plus *_tier and *_tier_desc labels (NEUTRAL/MILD/STRONG/SEVERE/PANIC) with sign/magnitude hints, so agents/bots never have to guess what “1 vs 2 vs 3 vs 4” mean.
Customizable bands for VOLD/ADD/TICK, table styling, label placement, and dashboard bias input to align with higher-timeframe context.
Best use
Quick read on internal participation and pressure magnitude.
Guardrails: respect PANIC and overrides; treat divergence as “scalp only.”
Pair with your strategy entries; let breadth govern when to press, scale back, or stand down.
Symbols (defaults)
VOLD (NYSE volume diff), VOLDQ (NASDAQ volume diff), ADD (NYSE), ADDQ (NASDAQ), TICK (NYSE). Adjust in Inputs as needed.
Alerts
Panic, divergence, strong bullish/bearish breadth. Enable JSON export to feed algo/agent workflows.
CandelaCharts - Trend Concepts 📝 Overview
Trend Concepts is a comprehensive trend analysis toolkit that combines four powerful components to identify market direction, strength, and trading opportunities.
The indicator features Bias Magnet —an adaptive baseline that tracks trend direction with dynamic strength visualization and momentum polarity bars. Flux Trend uses ATR-based bands with gradient-filled zones to mark trend reversals and continuation exits. Surge Waves applies a two-pole filter to detect sustained momentum runs and highlight strong directional moves. Velocity Bands creates dynamic deviation-based support and resistance levels with re-entry and rejection signals for mean reversion and reversal setups.
Each component operates independently, allowing you to build a custom trend analysis system tailored to your trading style. The integrated dashboard provides real-time market context through trend consensus (majority vote from enabled components), ADX strength, volatility analysis, volume trends, and momentum indicators. Trading profiles automatically optimize all component parameters for Scalping, Intraday, Swing, or Investment strategies, while Custom mode gives you full manual control. Multiple color themes and comprehensive alert options make this a complete solution for trend-following traders across all timeframes.
📦 Features
This section highlights the core capabilities you'll rely on most.
Bias Magnet — Adaptive baseline that hugs price without whipsaws, using half-trend style logic. Calculates trend strength (0–100) from slope and momentum, displays dynamic line transparency based on intensity, and provides flip signals (▲/▼) when trend changes. Includes polarity bars (☰) that show MFI-based momentum direction with intensity-based transparency.
Flux Trend — ATR-based trend bands that flip between bullish and bearish regimes. Creates gradient-filled zones between main and secondary bands, marks trend flips with symbols (✦/❖) and connecting lines, and detects exit signals when price leaves the zone after touching it. Ideal for identifying trend reversals and continuation setups.
Surge Waves — Two-pole filter that smooths price action and detects sustained momentum runs. Tracks consecutive rising or falling bars, marks sustained runs (5+ bars) with shapes, and provides confirmation signals when runs begin. The filled tube envelope provides visual context for momentum direction and strength.
Velocity Bands — Dynamic deviation-based bands that adapt to market conditions. Uses outlier-filtered standard deviation to create +1/+2 and -1/-2 bands around a weighted moving average. Detects re-entry signals when price returns from extreme zones and rejection signals when price enters bands but fails to hold. Enhanced gradient fills highlight when price is outside bands.
Trading Profiles — Pre-configured settings that automatically adjust component parameters: Scalping (fast, responsive), Intraday (balanced), Swing (slower, stable), Investment (long-term focus), or Custom (manual control). Profiles optimize Flux Trend length, Surge Waves length, and Velocity Bands deviation period for your trading style.
Dashboard — Real-time market analysis panel showing ticker, timeframe, active profile, trend direction (majority vote from enabled components), ADX strength (0–100), volatility state (High/Normal/Low based on ATR), volume trend (Bullish/Bearish/Neutral), and momentum (RSI-based). Color-coded for quick visual assessment.
Color Themes — Choose from 8 preset themes (Default, Blue-Orange, Green-Orange, Teal-Fuchsia, Aqua-Purple, Black-Green, Black-Aqua, Black-White) or create a custom color scheme. Themes apply consistently across all components for a cohesive visual experience.
Alerts — Individual alert toggles for each component's key signals: Bias Magnet flips (bull/bear), Flux Trend flips (bull/bear), Surge Waves sustained runs (bull/bear), Velocity Bands re-entries (bull/bear), and Velocity Bands rejections (bull/bear). All alerts include the symbol and timeframe in the message.
⚙️ Settings
Use these controls to customize the indicator's appearance, behavior, and component parameters.
Theme — Select a color theme: Default, Blue-Orange, Green-Orange, Teal-Fuchsia, Aqua-Purple, Black-Green, Black-Aqua, Black-White, or Custom. When Custom is selected, use the three color inputs below.
Trading Profile — Select your trading style: Scalping (fast, 30/30/300), Intraday (balanced, 50/50/500), Swing (slower, 80/70/800), Investment (long-term, 100/100/1200), or Custom (use manual component inputs). Profiles automatically adjust Flux Trend length, Surge Waves length, and Velocity Bands deviation period.
Bias Magnet — Enable/disable the adaptive baseline component. Amplitude controls the sensitivity (default: 5, higher = more responsive). Polarity Bars toggles the MFI-based momentum indicators (☰) that appear above/below the baseline.
Flux Trend — Enable/disable the ATR-based trend bands. Length sets the SMA period for the baseline (default: 60, only used in Custom profile). Bands Distance controls the ATR multiplier for band width (default: 3.0, higher = wider bands).
Surge Waves — Enable/disable the two-pole filter component. Length sets the filter period (default: 50, only used in Custom profile). Tube Width controls the ATR multiplier for the filled envelope width (default: 0.14, higher = wider tube).
Velocity Bands — Enable/disable the deviation-based bands. Deviation Length sets the period for standard deviation calculation (default: 500, only used in Custom profile). Higher values create more stable but slower-adapting bands.
Dashboard — Toggle to show/hide the integrated market analysis panel in the middle-right of the chart.
⚡️ Showcase
Bias Magnet
Flux Trend
Surge Waves
Velocity Bands
Dashboard
📒 Usage
Follow these steps to effectively use Trend Concepts for trend analysis and trading decisions.
1) Select your trading profile — Choose the profile that matches your trading style: Scalping for fast intraday trades, Intraday for day trading, Swing for multi-day positions, or Investment for long-term holds. The profile automatically optimizes all component parameters. Use Custom only if you need specific manual settings.
2) Enable components strategically — Start with one or two components to avoid visual clutter. Enable the dashboard to see the overall trend consensus.
3) Interpret Bias Magnet — The adaptive baseline shows trend direction: below price = bullish (acts as support), above price = bearish (acts as resistance). Line transparency indicates trend strength (darker = stronger). Watch for ▲ (bullish flip) and ▼ (bearish flip) signals. Polarity bars (☰) show momentum direction: above baseline = bullish momentum, below = bearish momentum. Intensity of bars reflects momentum strength.
4) Use Flux Trend for reversals — The gradient-filled zones between bands act as support (bullish) or resistance (bearish). Trend flips are marked with ✦ (bull to bear) or ❖ (bear to bull) symbols. Exit signals (✦/❖ outside bands) indicate when price leaves the zone after touching it, suggesting continuation. Trade flips for reversals or exits for continuations.
5) Track Surge Waves momentum — The filled tube shows momentum direction (green = bullish, red = bearish). Sustained runs of 5+ consecutive bars in one direction are marked with shapes (square = rising, diamond = falling). Confirmation signals appear when runs begin. Use these to identify strong momentum moves and potential continuation setups.
6) Trade Velocity Bands extremes — Price beyond +2/-2 bands indicates extreme conditions. Re-entry signals (▼ from above, ▲ from below) suggest mean reversion opportunities. Rejection signals occur when price enters a band but fails to hold, indicating potential reversals. The enhanced gradient fills highlight when price is outside bands, drawing attention to extreme moves.
7) Use dashboard for context — The dashboard provides a quick market snapshot. Trend shows the majority vote from enabled components (useful when multiple components disagree). Strength (ADX) indicates trend quality: < 20 = weak, 20–40 = moderate, ≥ 40 = strong. Volatility, Volume, and Momentum help assess market conditions before entering trades.
8) Combine components for confirmation — When multiple components agree on trend direction, confidence increases. For example, if Bias Magnet flips bullish, Flux Trend is in bull mode, and Surge Waves shows rising momentum, you have strong confirmation. Divergences between components can signal potential reversals or weak trends.
9) Set up alerts strategically — Enable alerts for the components you actively trade. Bias Magnet and Flux Trend alerts catch trend changes early. Surge Waves alerts identify momentum shifts. Velocity Bands alerts catch mean reversion and rejection setups. Use alerts to monitor multiple charts without constant watching.
10) Adjust for your timeframe — Higher timeframes (daily, weekly) provide more reliable signals but fewer opportunities. Lower timeframes (15m, 1h) offer more signals but require faster decisions. Consider using a higher timeframe profile (e.g., Swing) on lower timeframes for more stable signals, or a lower timeframe profile (e.g., Scalping) on higher timeframes for more responsive signals.
🚨 Alerts
Trend Concepts provides comprehensive alert options for each component's key signals. Alerts fire once per bar close to avoid spam.
Bias Magnet Alerts
BM Bull — Triggers when Bias Magnet trend flips to bullish (baseline crosses above price and confirms).
BM Bear — Triggers when Bias Magnet trend flips to bearish (baseline crosses below price and confirms).
Flux Trend Alerts
FT Bull — Triggers when Flux Trend flips from bearish to bullish (price crosses above upper band).
FT Bear — Triggers when Flux Trend flips from bullish to bearish (price crosses below lower band).
Surge Waves Alerts
SW Bull — Triggers when Surge Waves detects a sustained rising run (5+ consecutive bars rising, confirmed on bar close).
SW Bear — Triggers when Surge Waves detects a sustained falling run (5+ consecutive bars falling, confirmed on bar close).
Velocity Bands Alerts
VB Re-entry Bull — Triggers when price re-enters Velocity Bands from below the lower -2 band (bullish mean reversion signal).
VB Re-entry Bear — Triggers when price re-enters Velocity Bands from above the upper +2 band (bearish mean reversion signal).
VB Rejection Bull — Triggers when price enters the lower band but rejects back above it (bullish reversal signal).
VB Rejection Bear — Triggers when price enters the upper band but rejects back below it (bearish reversal signal).
⚠️ Disclaimer
These tools are exclusively available on the TradingView platform.
Our charting tools are intended solely for informational and educational purposes and should not be regarded as financial, investment, or trading advice. They are not designed to predict market movements or offer specific recommendations. Users should be aware that past performance is not indicative of future results and should not rely on these tools for financial decisions. By using these charting tools, the purchaser agrees that the seller and creator hold no responsibility for any decisions made based on information provided by the tools. The purchaser assumes full responsibility and liability for any actions taken and their consequences, including potential financial losses or investment outcomes that may result from the use of these products.
By purchasing, the customer acknowledges and accepts that neither the seller nor the creator is liable for any undesired outcomes stemming from the development, sale, or use of these products. Additionally, the purchaser agrees to indemnify the seller from any liability. If invited through the Friends and Family Program, the purchaser understands that any provided discount code applies only to the initial purchase of Candela's subscription. The purchaser is responsible for canceling or requesting cancellation of their subscription if they choose not to continue at the full retail price. In the event the purchaser no longer wishes to use the products, they must unsubscribe from the membership service, if applicable.
We do not offer reimbursements, refunds, or chargebacks. Once these Terms are accepted at the time of purchase, no reimbursements, refunds, or chargebacks will be issued under any circumstances.
By continuing to use these charting tools, the user confirms their understanding and acceptance of these Terms as outlined in this disclaimer.
CandelaCharts - Trend Oscillator 📝 Overview
Trend Oscillator is a simple yet effective trend identification tool that uses the relationship between two exponential moving averages (EMAs) to determine market direction. It calculates the spread between a fast and slow EMA, applies a bias multiplier, and smooths the result to produce a clean oscillator that oscillates above and below a zero line. When the oscillator is above zero, the trend is considered bullish (upward); when below zero, it's bearish (downward). The indicator provides clear visual feedback through color-coded plots and optional price bar coloring, making it easy to identify trend direction at a glance.
📦 Features
This section highlights the core capabilities you'll rely on most.
Dual EMA system — Uses a fast EMA (default 9) and slow EMA (default 21) to capture trend momentum and direction.
Bias multiplier — Applies a small multiplier (default 1.001) to the EMA spread, providing a slight bias that helps filter noise and confirm trend strength.
Smoothed output — Applies an additional EMA smoothing (default 5 periods) to the raw spread, creating a cleaner, less choppy oscillator line.
Zero-line reference — Plots a horizontal zero line that serves as the critical threshold between bullish and bearish conditions.
Color-coded visualization — Automatically colors the oscillator line green/lime when bullish (above zero) and red when bearish (below zero).
Price bar coloring — Optional feature to color price bars based on the current trend direction, providing immediate visual context on the main chart.
Customizable parameters — Adjust EMA lengths, bias multiplier, smoothing period, and colors to match your trading style and timeframe.
⚙️ Settings
Use these controls to fine-tune the oscillator's sensitivity, appearance, and behavior.
Fast EMA Length — Period for the fast exponential moving average (default: 9). Lower values make the indicator more responsive to price changes.
Slow EMA Length — Period for the slow exponential moving average (default: 21). Higher values create a smoother baseline for trend identification.
Bias Multiplier — Multiplier applied to the EMA spread (default: 1.001). Small adjustments can help filter minor whipsaws and confirm trend strength.
Smoothing Length — Period for smoothing the raw spread calculation (default: 5). Higher values create a smoother oscillator line but may lag price action.
Colors — Set the bullish (default: lime) and bearish (default: red) colors for the oscillator line.
Color Price Bars — Toggle to enable/disable coloring of price bars based on the current trend direction.
⚡️ Showcase
Oscillator Line
Bar Coloring
Divergences
📒 Usage
Follow these steps to effectively use Trend Oscillator for trend identification and trading decisions.
1) Select your timeframe — The indicator works across all timeframes, but higher timeframes (daily, weekly, monthly) typically provide more reliable trend signals with less noise. Lower timeframes (1m, 5m, 15m) may produce more frequent but potentially less reliable signals. Consider your trading style: swing traders benefit from daily/weekly charts, while day traders can use 15m/1h timeframes. Always align the indicator's sensitivity with your timeframe choice.
2) Adjust EMA lengths — The default 9/21 combination works well for most cases. For faster signals, try 5/13; for slower, more conservative signals, try 12/26 or 20/50. Match the lengths to your trading style and timeframe.
3) Interpret the zero line — When the oscillator is above zero (green/lime), the trend is bullish. When below zero (red), the trend is bearish. The further from zero, the stronger the trend.
4) Watch for crossovers — Trend changes occur when the oscillator crosses the zero line. A cross from below to above indicates a shift to bullish; from above to below indicates a shift to bearish.
5) Identify divergences — Divergences can signal potential trend reversals. Bullish divergence : price makes lower lows while the oscillator makes higher lows (suggests weakening bearish momentum). Bearish divergence : price makes higher highs while the oscillator makes lower highs (suggests weakening bullish momentum). Divergences are most reliable when they occur near extreme levels and should be confirmed with price action before taking trades.
6) Use smoothing wisely — The smoothing parameter helps reduce noise but adds lag. Lower smoothing (3-5) is more responsive; higher smoothing (7-10) is more stable but slower to react.
7) Combine with price action — Use the oscillator to confirm trend direction, then look for entry opportunities when price pulls back in the direction of the trend. The optional price bar coloring helps visualize trend alignment on the main chart.
8) Filter with bias multiplier — The bias multiplier can help reduce false signals. Experiment with values between 1.000 and 1.005 to find the sweet spot for your instrument and timeframe.
🚨 Alerts
There are no built-in alerts in this version.
⚠️ Disclaimer
Trading involves significant risk, and many participants may incur losses. The content on this site is not intended as financial advice and should not be interpreted as such. Decisions to buy, sell, hold, or trade securities, commodities, or other financial instruments carry inherent risks and are best made with guidance from qualified financial professionals. Past performance is not indicative of future results.
LE LevelsGENERAL OVERVIEW:
The LE Levels indicator plots yesterday’s high/low and today’s pre-market high/low directly on your chart, then layers signal logic around those levels and a set of EMA waves. You can choose “Inside” setups, “Outside” setups, or both. You can also pick entries that trigger at levels, entries that trigger off the EMA wave, or both.
This indicator was developed by Flux Charts in collaboration with Ellis Dillinger (Ellydtrades).
What is the purpose of the indicator?:
The purpose of the LE Levels indicator is to give traders a clear view of how price is behaving around key session levels and EMA structure. It follows the same model EllyD teaches by showing where price is relative to the Previous Day High and Low and the Pre-Market High and Low, then printing signals when specific reactions occur around those levels.
What is the theory behind the indicator?:
The theory behind the LE Levels indicator is based on the concept of inside and outside days. An inside day occurs when price trades within the previous day’s high and low, signaling compression and potential breakout conditions. An outside day occurs when price moves beyond those boundaries, confirming expansion and directional bias. When price trades above the PDH or PMH, it reflects bullish control and potential continuation if supported by volume and momentum. When price trades below the PDL or PML, it shows bearish control and possible downside continuation. The idea is to combine this logic with tickers that have catalysts or news, since these events often bring higher-than-normal volume.
LE SCANNER FEATURES:
Key Levels
Signals
EMA Waves
Key Levels:
The LE Levels indicator automatically plots four key levels each day:
Previous Day High (PDH)
Previous Day Low (PDL)
Pre-Market High (PMH)
Pre-Market Low (PML)
🔹How are Key Levels used in the indicator?:
The key levels are a crucial factor in determining if the trend is bullish, bearish, or neutral trend bias. The indicator uses the key levels as a condition for identifying inside or outside setups (explained below). After determining a trend bias and setup type, the indicator prints long and short entry signals based on how price interacts with the key levels and 8 EMA Wave. (explained below).
These levels define where price previously reacted or reversed, helping traders visualize how current price action relates to prior session structure. They update automatically each day and pre-market session, allowing traders to see if price is trading inside, above, or below prior key ranges without manually drawing them.
Please Note: Pre-market times are based on U.S. market hours (Eastern Standard Time) and may vary for non-U.S. tickers or exchanges.
🔹Previous Day High (PDH):
The PDH marks the highest price reached during the previous regular trading session. It shows where buyers pushed price to its highest point before the market closed. This value is automatically pulled from the daily chart and projected forward onto intraday timeframes.
🔹Previous Day Low (PDL):
The PDL marks the lowest price reached during the previous regular trading session. It shows where selling pressure reached its lowest point before buyers stepped in. Like the PDH, this level is retrieved from the prior day’s data and extended into the current session.
🔹Pre-Market High (PMH):
The PMH is the highest price reached between 4:00 AM and 9:29 AM EST, before the regular market open. It shows how far buyers managed to push price up during the pre-market session.
🔹Pre-Market Low (PML):
The PML is the lowest price reached between 4:00 AM and 9:29 AM EST, before the regular market open. It shows how far sellers were able to drive price down during the pre-market session.
🔹Customization Options:
Extend Levels:
Extends each plotted line a user-defined number of bars into the future, keeping them visible even as new candles print. This helps maintain a clear visual reference as the session progresses.
Extend PDH/L Left & Extend PMH/L Left:
These settings let you extend the Previous Day and Pre-Market levels back to their origin point, so you can see exactly where each level was formed on the prior trading day. This makes it easy to understand the context of each level and how it developed. When this option is disabled, the lines begin at the regular session open instead of extending backward into the previous day’s data.
Show Name / Show Price:
Enabling Show Name displays labels (PDH, PDL, PMH, PML) beside each line, while Show Price adds the exact price value. You can choose to show just the name, just the price, or both for a complete label format.
Line Color and Style:
Each level can be fully customized. You can change the line color and select between solid, dashed, or dotted styles to visually distinguish each level type.
At the bottom of the indicator settings, under the ‘Miscellaneous’ section, two additional options allow further control over how levels are displayed:
Hide Previous Day Highs/Lows:
When enabled, the previous day’s high and low levels aren’t shown. When disabled, users can view previous day levels without using replay mode. By default, this setting is enabled.
Disabled:
Enabled:
Hide Previous Pre-Market Highs/Lows:
When enabled, the previous pre-market high and low levels aren’t shown. When disabled, users can view previous pre-market levels without using replay mode. By default, this setting is enabled.
Disabled:
Enabled:
Signals:
The LE Levels indicator automatically prints long and short entry signals based on how price interacts with its key levels (PDH, PDL, PMH, PML) and the EMA Waves. It identifies moments when price either breaks out beyond prior ranges or retests those levels in alignment with momentum shown by the EMA Waves.
There are two types of setups (Inside and Outside) and two entry types ((L)evels and (E)MAs). Together, these settings allow traders to customize the type of structure the indicator recognizes and how signals are generated.
🔹What is an Inside Setup?
An Inside Setup occurs when the current trading session forms entirely within the previous day’s range, meaning price has not yet broken above the Previous Day High (PDH) or below the Previous Day Low (PDL). In the LE Levels indicator, inside setups are recognized when price trades within the previous day’s boundaries while also considering the pre-market range (Pre-Market High and Pre-Market Low).
Inside Setups have two main conditions, depending on directional bias:
Bullish Inside Setup:
Price trades above the Pre-Market High (PMH) and above the Previous Day Low (PDL), while still below the Previous Day High (PDH).
Bearish Inside Setup:
Price trades below the Pre-Market Low (PML) and below the Previous Day High (PDH), while still above the Previous Day Low (PDL).
🔹What is an Outside Setup?
An Outside Setup occurs when the current trading session extends beyond the previous day’s range, meaning price has broken above the Previous Day High (PDH) or below the Previous Day Low (PDL). This structure reflects expansion and directional control, showing that either buyers or sellers have taken price into new territory beyond the prior session’s boundaries.
In the indicator, an Outside Setup forms once price closes beyond both the previous day and pre-market boundaries, showing bias in one direction.
Bullish Outside Setup:
Price closes above both the PDH and the PMH, confirming buyers have pushed through every key resistance from the prior session and the pre-market.
Bearish Outside Setup:
Price closes below both the PDL and the PML, showing sellers have pushed price beneath all key support levels from the previous session and the pre-market.
🔹Entry Types: (L)evels and (E)MAs
Once a setup type (Inside or Outside) has been established, the LE Levels indicator generates trade signals using one of two entry confirmation methods: (L) for Key Level based Entries and (E) for EMA Wave based Entries. These determine how the signal prints and what triggers it within.
🔹(L)evels Entry:
The (L)evels entry type is built around how price reacts to the key levels (PDH, PDL, PMH, PML). It prints when price retests those levels during an active setup. The logic focuses on retests, where price returns to confirm a previous breakout or breakdown before continuing in the same direction.
Bullish Outside (L)evels Setup:
A Bullish Outside Setup forms when price breaks above both the PDH and PMH. Once this breakout occurs, the indicator waits for a pullback to one of those levels. For a signal to print, the 8 EMA Wave must also be near that level, showing momentum is supporting the structure. A small buffer is applied between price and the level so that even if price only comes close, without fully touching, the retest still counts. When price holds above the PDH or PMH with the 8 EMA nearby, the indicator prints an (L) ▲ entry.
Bearish Outside (L)evels Setup:
A Bearish Outside Setup forms when price breaks below both the PDL and PML. Once this breakdown occurs, the indicator waits for a pullback to one of those levels. For a signal to print, the 8 EMA Wave must also be near that area, confirming momentum is aligned with the move. A small buffer is included so that even if price comes close but doesn’t fully touch the level, the retest still qualifies. When price holds below the PDL or PML with the 8 EMA nearby, the indicator prints an (L) ▼ entry.
Bullish Inside (L)evels Setup:
A Bullish Inside Setup forms when price trades above the PMH but stays below the PDH and above the PDL. Once this condition is met, the indicator waits for a pullback to the PMH. For a signal to print, the 8 EMA Wave must also be near that level. A small buffer is applied so that even if price only comes close to the level, the retest still counts. When price holds above the PMH with the 8 EMA nearby, the indicator prints an (L) ▲ entry.
Bearish Inside (L)evels Setup:
A Bearish Inside Setup forms when price trades below the PML but stays above the PDL and below the PDH. Once this condition is met, the indicator waits for a pullback to the PML. For a signal to print, the 8 EMA Wave must also be near that level. A small buffer is applied so that even if price only comes close, the retest still counts. When price holds below the PML with the 8 EMA nearby, the indicator prints an (L) ▼ entry.
🔹(E)MAs Entry:
The (E)MA Entry type focuses on how price reacts to the 8 EMA Wave. It identifies when price first interacts with the EMAs, then confirms continuation once momentum resumes in the setup’s direction. The first candle that touches the EMA prints an (E) marker, and the confirmation signal triggers only after price breaks above or below that candle, depending on the bias.
Bullish Outside (E)MA Setup:
A Bullish Outside Setup forms when price is trading above both the PDH and PMH. Once this breakout occurs, the indicator waits for price to pull back and touch the 8 EMA Wave, which prints the initial (E) label. If price then breaks above that candle’s high, the continuation setup is confirmed.
Bearish Outside (E)MA Setup:
A Bearish Outside Setup forms when price is trading below both the PDL and PML. After the breakdown, the indicator waits for price to pull back to the 8 EMA Wave, marking the candle that touches it with an (E) label. If price then breaks below that candle’s low, the continuation setup is confirmed.
Bullish Inside (E)MA Setup:
A Bullish Inside Setup forms when price trades above the PMH but remains below the PDH and above the PDL. The indicator waits for price to retrace and touch the 8 EMA Wave, which prints the initial (E) label. If price then breaks above that candle’s high, the continuation setup is confirmed.
Bearish Inside (E)MA Setup:
A Bearish Inside Setup forms when price trades below the PML but remains above the PDL and below the PDH. Once price touches the 8 EMA Wave, the indicator prints an (E) marker. If price then breaks below that candle’s low, the continuation setup is confirmed.
🔹Signal Settings:
At the bottom of the indicator settings panel, three core controls define how signals are displayed and which setups the indicator actively scans for. These settings allow you to refine signal generation based on your trading approach and chart preference.
Setup Type:
This setting determines which structural conditions the indicator tracks.
Inside Setups: Signals only appear when price is trading within the previous day’s range (between PDH and PDL).
Outside Setups: Signals only appear when price breaks outside the previous day’s range (above PDH/PMH or below PDL/PML).
Both: Enables signals for both Inside and Outside setups.
Entry Type:
Controls how the indicator confirms entries.
(E)MAs: Prints signals based on price interacting with the 8 EMA Wave.
(L)evels: Prints signals based on price retesting key levels such as PDH, PDL, PMH, or PML.
Both: Allows both EMA and Level-based signals to appear on the same chart.
Signal Filters (Long, Short, and Re-Entry):
These toggles let you control which trade directions are active.
Long: Displays only bullish entries and ignores all short setups.
Short: Displays only bearish entries and ignores long setups.
Re-Entry: Enables or disables repeated signals in the same direction after the first valid setup has printed. When off, only the initial signal is shown until conditions reset.
EMA Waves:
The EMA Waves help identify potential entries and show directional bias. They’re made of grouped EMAs that form shaded areas to create a “wave” look. The color-coding on the waves allows users to view when price is consolidating, in a bullish trend, or in a bearish trend. The wave updates in real time as new candles form and does not repaint historical data.
🔹8 EMA Wave
The 8 EMA Wave is used directly in the indicator’s signal logic described earlier. It reacts fastest to price compared to the other EAM Waves and determines when (L) and (E) signals can trigger.
How It Works:
The wave is made from the 8, 9, and 10 EMAs and fills the space between them to create a “wave” look. The 8 EMA Wave continuously updates its color based on where price trades relative to the key levels (PDH, PDL, PMH, PML). The color changes are conditional and based solely on price position relative to key levels.
Price is above both PDH and PMH: The wave is bright green, and the top half is purple.
Price is between PDH and PMH: The wave is dark green, and the top half is purple.
Price is below both PDL and PML: The wave is bright red, and the bottom half is purple.
Price is between PDL and PML: The wave is dark red, and the bottom half is purple.
Price is between all four levels: The wave is gray to represent consolidation or neutral bias.
🔹8 EMA Wave Signal Function:
For (L)evels entries, the 8 EMA must be close to the key level being retested, with a small buffer that allows near touches to qualify.
For (E)MA entries, the first candle that touches the wave prints an (E), and the confirmation signal appears when price breaks that candle’s high or low.
🔹8 EMA Wave Customization:
Users can customize all colors for bullish, bearish, and neutral conditions directly in the settings. The purple overlay color cannot be changed, as it is hard-coded into the indicator. The 8 EMA Wave can also be toggled on or off. Turning it off only removes the visual display from the chart and does not affect signals.
🔹20 EMA Wave
The 20 EMA Wave measures medium-term momentum and helps visualize larger pullbacks. It reacts more slowly than the 8 EMA Wave, giving a smoother wave look. No signals are generated from it. It’s purely a visual guide for spotting potential pullback areas for continuation setups.
How It Works:
The wave is made from the 19, 20, and 21 EMAs and fills the space between them to create a shaded “wave.” The color updates continuously based on where price trades relative to the key levels (PDH, PDL, PMH, PML). The color changes are conditional and based only on price position relative to these levels.
Price is above both PDH and PMH: The wave is bright green, and the top half is blue.
Price is between PDH and PMH: The wave is dark green, and the top half is blue.
Price is below both PDL and PML: The wave is bright red, and the bottom half is blue.
Price is between PDL and PML: The wave is dark red, and the bottom half is blue.
Price is between all four levels: The wave is gray to represent consolidation or neutral bias.
🔹20 EMA Wave Use Case:
After 12:00 PM EST, the 20 EMA Wave is used to spot larger pullbacks that form later in the session. No signals are generated from it; it only serves as a visual guide for identifying potential continuation areas.
Bullish Continuation Pullback:
Bearish Continuation Pullback:
🔹20 EMA Wave Customization:
Users can customize all colors for bullish, bearish, and neutral conditions directly in the settings. The blue overlay color cannot be changed, as it is hard-coded into the indicator. The 20 EMA Wave can also be toggled on or off.
🔹200 EMA Wave
The 200 EMA Wave is used to determine long-term trend bias. When price is above it, the bias is bullish; when price is below it, the bias is bearish. It updates automatically in real time and is used to define the broader directional bias for the day.
How it Works:
The 200 EMA Wave is created using the 190, 199, and 200 EMAs, with the area between them shaded to form a “wave.”
🔹200 EMA Wave Use Case:
When price is above the 200 EMA Wave and both the 8 and 20 EMA Waves are stacked above it, the overall trend is bullish.
When price is below the 200 EMA Wave and both shorter-term waves are also below it, the overall trend is bearish.
🔹200 EMA Wave Customization:
Users can customize both colors that form the 200 EMA Wave. The entire wave can also be toggled on or off in the settings.
Uniqueness:
The LE Levels indicator is unique because it combines signal logic with a clear visual structure. It automatically detects inside and outside setups, printing (L) and (E) entries based on how price reacts to key levels and the EMA Waves. Each signal follows strict conditions tied to the 8 EMA and key levels. The color-coded EMA Waves make it simple to understand where price is in relation to the key levels and getting a quick trend bias overview.
