Ergodic Market Divergence (EMD)Ergodic Market Divergence (EMD)
Bridging Statistical Physics and Market Dynamics Through Ensemble Analysis
The Revolutionary Concept: When Physics Meets Trading
After months of research into ergodic theory—a fundamental principle in statistical mechanics—I've developed a trading system that identifies when markets transition between predictable and unpredictable states. This indicator doesn't just follow price; it analyzes whether current market behavior will persist or revert, giving traders a scientific edge in timing entries and exits.
The Core Innovation: Ergodic Theory Applied to Markets
What Makes Markets Ergodic or Non-Ergodic?
In statistical physics, ergodicity determines whether a system's future resembles its past. Applied to trading:
Ergodic Markets (Mean-Reverting)
- Time averages equal ensemble averages
- Historical patterns repeat reliably
- Price oscillates around equilibrium
- Traditional indicators work well
Non-Ergodic Markets (Trending)
- Path dependency dominates
- History doesn't predict future
- Price creates new equilibrium levels
- Momentum strategies excel
The Mathematical Framework
The Ergodic Score combines three critical divergences:
Ergodic Score = (Price Divergence × Market Stress + Return Divergence × 1000 + Volatility Divergence × 50) / 3
Where:
Price Divergence: How far current price deviates from market consensus
Return Divergence: Momentum differential between instrument and market
Volatility Divergence: Volatility regime misalignment
Market Stress: Adaptive multiplier based on current conditions
The Ensemble Analysis Revolution
Beyond Single-Instrument Analysis
Traditional indicators analyze one chart in isolation. EMD monitors multiple correlated markets simultaneously (SPY, QQQ, IWM, DIA) to detect systemic regime changes. This ensemble approach:
Reveals Hidden Divergences: Individual stocks may diverge from market consensus before major moves
Filters False Signals: Requires broader market confirmation
Identifies Regime Shifts: Detects when entire market structure changes
Provides Context: Shows if moves are isolated or systemic
Dynamic Threshold Adaptation
Unlike fixed-threshold systems, EMD's boundaries evolve with market conditions:
Base Threshold = SMA(Ergodic Score, Lookback × 3)
Adaptive Component = StDev(Ergodic Score, Lookback × 2) × Sensitivity
Final Threshold = Smoothed(Base + Adaptive)
This creates context-aware signals that remain effective across different market environments.
The Confidence Engine: Know Your Signal Quality
Multi-Factor Confidence Scoring
Every signal receives a confidence score based on:
Signal Clarity (0-35%): How decisively the ergodic threshold is crossed
Momentum Strength (0-25%): Rate of ergodic change
Volatility Alignment (0-20%): Whether volatility supports the signal
Market Quality (0-20%): Price convergence and path dependency factors
Real-Time Confidence Updates
The Live Confidence metric continuously updates, showing:
- Current opportunity quality
- Market state clarity
- Historical performance influence
- Signal recency boost
- Visual Intelligence System
Adaptive Ergodic Field Bands
Dynamic bands that expand and contract based on market state:
Primary Color: Ergodic state (mean-reverting)
Danger Color: Non-ergodic state (trending)
Band Width: Expected price movement range
Squeeze Indicators: Volatility compression warnings
Quantum Wave Ribbons
Triple EMA system (8, 21, 55) revealing market flow:
Compressed Ribbons: Consolidation imminent
Expanding Ribbons: Directional move developing
Color Coding: Matches current ergodic state
Phase Transition Signals
Clear entry/exit markers at regime changes:
Bull Signals: Ergodic restoration (mean reversion opportunity)
Bear Signals: Ergodic break (trend following opportunity)
Confidence Labels: Percentage showing signal quality
Visual Intensity: Stronger signals = deeper colors
Professional Dashboard Suite
Main Analytics Panel (Top Right)
Market State Monitor
- Current regime (Ergodic/Non-Ergodic)
- Ergodic score with threshold
- Path dependency strength
- Quantum coherence percentage
Divergence Metrics
- Price divergence with severity
- Volatility regime classification
- Strategy mode recommendation
- Signal strength indicator
Live Intelligence
- Real-time confidence score
- Color-coded risk levels
- Dynamic strategy suggestions
Performance Tracking (Left Panel)
Signal Analytics
- Total historical signals
- Win rate with W/L breakdown
- Current streak tracking
- Closed trade counter
Regime Analysis
- Current market behavior
- Bars since last signal
- Recommended actions
- Average confidence trends
Strategy Command Center (Bottom Right)
Adaptive Recommendations
- Active strategy mode
- Primary approach (mean reversion/momentum)
- Suggested indicators ("weapons")
- Entry/exit methodology
- Risk management guidance
- Comprehensive Input Guide
Core Algorithm Parameters
Analysis Period (10-100 bars)
Scalping (10-15): Ultra-responsive, more signals, higher noise
Day Trading (20-30): Balanced sensitivity and stability
Swing Trading (40-100): Smooth signals, major moves only Default: 20 - optimal for most timeframes
Divergence Threshold (0.5-5.0)
Hair Trigger (0.5-1.0): Catches every wiggle, many false signals
Balanced (1.5-2.5): Good signal-to-noise ratio
Conservative (3.0-5.0): Only extreme divergences Default: 1.5 - best risk/reward balance
Path Memory (20-200 bars)
Short Memory (20-50): Recent behavior focus, quick adaptation
Medium Memory (50-100): Balanced historical context
Long Memory (100-200): Emphasizes established patterns Default: 50 - captures sufficient history without lag
Signal Spacing (5-50 bars)
Aggressive (5-10): Allows rapid-fire signals
Normal (15-25): Prevents clustering, maintains flow
Conservative (30-50): Major setups only Default: 15 - optimal trade frequency
Ensemble Configuration
Select markets for consensus analysis:
SPY: Broad market sentiment
QQQ: Technology leadership
IWM: Small-cap risk appetite
DIA: Blue-chip stability
More instruments = stronger consensus but potentially diluted signals
Visual Customization
Color Themes (6 professional options):
Quantum: Cyan/Pink - Modern trading aesthetic
Matrix: Green/Red - Classic terminal look
Heat: Blue/Red - Temperature metaphor
Neon: Cyan/Magenta - High contrast
Ocean: Turquoise/Coral - Calming palette
Sunset: Red-orange/Teal - Warm gradients
Display Controls:
- Toggle each visual component
- Adjust transparency levels
- Scale dashboard text
- Show/hide confidence scores
- Trading Strategies by Market State
- Ergodic State Strategy (Primary Color Bands)
Market Characteristics
- Price oscillates predictably
- Support/resistance hold
- Volume patterns repeat
- Mean reversion dominates
Optimal Approach
Entry: Fade moves at band extremes
Target: Middle band (equilibrium)
Stop: Just beyond outer bands
Size: Full confidence-based position
Recommended Tools
- RSI for oversold/overbought
- Bollinger Bands for extremes
- Volume profile for levels
- Non-Ergodic State Strategy (Danger Color Bands)
Market Characteristics
- Price trends persistently
- Levels break decisively
- Volume confirms direction
- Momentum accelerates
Optimal Approach
Entry: Breakout from bands
Target: Trail with expanding bands
Stop: Inside opposite band
Size: Scale in with trend
Recommended Tools
- Moving average alignment
- ADX for trend strength
- MACD for momentum
- Advanced Features Explained
Quantum Coherence Metric
Measures phase alignment between individual and ensemble behavior:
80-100%: Perfect sync - strong mean reversion setup
50-80%: Moderate alignment - mixed signals
0-50%: Decoherence - trending behavior likely
Path Dependency Analysis
Quantifies how much history influences current price:
Low (<30%): Technical patterns reliable
Medium (30-50%): Mixed influences
High (>50%): Fundamental shift occurring
Volatility Regime Classification
Contextualizes current volatility:
Normal: Standard strategies apply
Elevated: Widen stops, reduce size
Extreme: Defensive mode required
Signal Strength Indicator
Real-time opportunity quality:
- Distance from threshold
- Momentum acceleration
- Cross-validation factors
Risk Management Framework
Position Sizing by Confidence
90%+ confidence = 100% position size
70-90% confidence = 75% position size
50-70% confidence = 50% position size
<50% confidence = 25% or skip
Dynamic Stop Placement
Ergodic State: ATR × 1.0 from entry
Non-Ergodic State: ATR × 2.0 from entry
Volatility Adjustment: Multiply by current regime
Multi-Timeframe Alignment
- Check higher timeframe regime
- Confirm ensemble consensus
- Verify volume participation
- Align with major levels
What Makes EMD Unique
Original Contributions
First Ergodic Theory Trading Application: Transforms abstract physics into practical signals
Ensemble Market Analysis: Revolutionary multi-market divergence system
Adaptive Confidence Engine: Institutional-grade signal quality metrics
Quantum Coherence: Novel market alignment measurement
Smart Signal Management: Prevents clustering while maintaining responsiveness
Technical Innovations
Dynamic Threshold Adaptation: Self-adjusting sensitivity
Path Memory Integration: Historical dependency weighting
Stress-Adjusted Scoring: Market condition normalization
Real-Time Performance Tracking: Built-in strategy analytics
Optimization Guidelines
By Timeframe
Scalping (1-5 min)
Period: 10-15
Threshold: 0.5-1.0
Memory: 20-30
Spacing: 5-10
Day Trading (5-60 min)
Period: 20-30
Threshold: 1.5-2.5
Memory: 40-60
Spacing: 15-20
Swing Trading (1H-1D)
Period: 40-60
Threshold: 2.0-3.0
Memory: 80-120
Spacing: 25-35
Position Trading (1D-1W)
Period: 60-100
Threshold: 3.0-5.0
Memory: 100-200
Spacing: 40-50
By Market Condition
Trending Markets
- Increase threshold
- Extend memory
- Focus on breaks
Ranging Markets
- Decrease threshold
- Shorten memory
- Focus on restores
Volatile Markets
- Increase spacing
- Raise confidence requirement
- Reduce position size
- Integration with Other Analysis
- Complementary Indicators
For Ergodic States
- RSI divergences
- Bollinger Band squeezes
- Volume profile nodes
- Support/resistance levels
For Non-Ergodic States
- Moving average ribbons
- Trend strength indicators
- Momentum oscillators
- Breakout patterns
- Fundamental Alignment
- Check economic calendar
- Monitor sector rotation
- Consider market themes
- Evaluate risk sentiment
Troubleshooting Guide
Too Many Signals:
- Increase threshold
- Extend signal spacing
- Raise confidence minimum
Missing Opportunities
- Decrease threshold
- Reduce signal spacing
- Check ensemble settings
Poor Win Rate
- Verify timeframe alignment
- Confirm volume participation
- Review risk management
Disclaimer
This indicator is for educational and informational purposes only. It does not constitute financial advice. Trading involves substantial risk of loss and is not suitable for all investors. Past performance does not guarantee future results.
The ergodic framework provides unique market insights but cannot predict future price movements with certainty. Always use proper risk management, conduct your own analysis, and never risk more than you can afford to lose.
This tool should complement, not replace, comprehensive trading strategies and sound judgment. Markets remain inherently unpredictable despite advanced analysis techniques.
Transform market chaos into trading clarity with Ergodic Market Divergence.
Created with passion for the TradingView community
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
Statistics
Palgo Trading - Palgo🎯THE PALGO INDICATOR
The "Palgo Trading - Palgo" indicator, developed by PALGOTRADING is a sophisticated technical analysis tool designed to identify potential buy and sell signals by combining trend analysis with momentum and optional AI-driven sentiment assessment. This indicator provides a clear visual representation of potential trading opportunities directly on the price chart.
At its core, the Palgo indicator synthesizes information from well-established technical analysis concepts with statistical functions, and has optional AI Integration for social analysis of the asset using external data :
Supertrend: This indicator identifies the prevailing trend direction. A positive Supertrend value suggests an upward trend, while a negative value indicates a downward trend. The Palgo indicator utilizes a Supertrend with a customizable multiplier and a user-configurable Average True Range (ATR) length (defaulting to 21).
🛜Signal Generation Logic
The indicator generates buy and sell signals based on a calculated "final direction" value. This value is derived by combining the Supertrend direction and a modified RSI. The modification involves scaling the RSI output to a range of -0.5 to 0.5 and then further adjusting it.
The buy and sell conditions are as follows:
Buy Signal: A buy signal is triggered when the "final direction" crosses above a positive activation threshold while the current signal is not already bullish. Upon signal generation, a "Buy" label (colored green) appears below the bar, and initial Take Profit (TP) and Stop Loss (SL) levels are calculated and stored.
Sell Signal: Conversely, a sell signal is triggered when the "final direction" crosses below a negative activation threshold while the current signal is not already bearish. A "Sell" label (colored red) is plotted above the bar, and corresponding TP and SL levels are determined.
✅ Optimized Take-Profit / Stop-Loss
The Take-Profit (TP) & Stop-Loss (SL) signals are optimized with Kernel Density Estimation (KDE), the script uses KDE activated by gaussian function on previous pivot points and trains the model, then tries to estimate new pivot points early, to determine new TP / SL levels for the current signal. Kernel Density Estimation takes values of the previous confirmed pivots' RSI values, body size & more factors to determine their role. This indicator can generate up to 5 TP signals per signal.
📈 Signal Trail
Palgo also includes a "Signal Trail" that visually shows the market's momentum. This trail is like a dynamic line that follows the price.
When the market is in an uptrend and looking strong, you'll see a green trail.
When it's in a downtrend and looking weak, you'll see a red trail.
This trail helps you see if the market is currently aligned with Palgo's bullish (buy) or bearish (sell) signal. It also acts as a visual guide for potential support or resistance levels.
📊Backtesting Dashboard
The Palgo indicator includes an optional Backtesting Dashboard to help you understand its historical performance. This dashboard appears directly on your chart and provides a quick summary of how the indicator's signals have performed in the past.
Here's what you'll see on the dashboard:
Sensitivity: This shows the specific "Sensitivity" setting you've chosen for the indicator. This setting influences how often signals are generated.
Wins: This number tells you how many trades initiated by the Palgo indicator historically ended in profit (reached a Take-Profit target or closed profitably when the signal reversed).
Loss: This number indicates how many trades historically ended in a loss (hit the Stop-Loss).
Winrate: This is a very important metric, displayed as a percentage. It shows you the proportion of winning trades compared to the total number of trades (Wins / (Wins + Loss)). A higher winrate generally suggests a more effective strategy.
This dashboard is a valuable tool for reviewing the indicator's effectiveness with different settings and helping you make informed decisions about its use in your trading.
🤖AI Integration (Optional):
A unique feature of the Palgo indicator is the optional integration of Artificial Intelligence (AI) sentiment analysis. When the "Use AI" input is enabled, the indicator incorporates two additional user-defined inputs:
Impression Change %: This input represents the percentage change in overall market sentiment as assessed by an external AI.
Positivity Change: This input reflects the change in positive sentiment, also provided by an AI.
These AI inputs are combined to create an "AI Score," which then influences the "final direction" calculation. A positive AI Score amplifies the bullish signals and dampens bearish signals, while a negative AI Score has the opposite effect.
❓Why PALGO ?
All-in-One Analysis: Palgo combines trend, momentum, and advanced statistical analysis into one easy-to-use tool, giving you a complete picture without needing multiple indicators.
Dynamic Profit & Loss Management: Unlike many tools with fixed targets, Palgo's smart profit and stop-loss system adapts to the market using KDE. This helps you potentially capture more gains and limit losses effectively.
Optional AI Insights: For an extra edge, Palgo can tap into Artificial Intelligence (AI) to gauge overall market mood. If the AI sees a lot of positive buzz, it can strengthen buy signals; if it's negative, it can reinforce sell signals. This helps you trade with a better understanding of the market's pulse.
Clear and Customizable: Palgo is designed to be very visual. It changes the color of the price bars, adds clear "Buy" or "Sell" labels, and marks your profit and stop-loss points. You can also change the colors to suit your preference.
Palgo aims to be a comprehensive and adaptable trading tool, giving you clearer insights.
⚙️Visualizations and Customization
The Palgo indicator offers several visual cues to aid traders:
Bar Coloring: The price bars are colored green when the indicator identifies a bullish signal and red during a bearish signal.
Signal Labels: Clear "Buy" and "Sell" labels are plotted at the signal generation points.
Take Profit and Stop Loss Markers: Distinct shapes and labels indicate when the price reaches the calculated TP and SL levels.
Style Options: Users can customize the colors for bullish and bearish bars, text, and TP/SL markers within the indicator's settings.
Volume Profile (PRO) [ActiveQuants]The Volume Profile (PRO) indicator is an advanced analytical tool designed to provide traders with a deep understanding of market dynamics by displaying trading activity across different price levels over a specified period. By meticulously plotting volume distribution , this indicator helps identify significant price zones, such as areas of high acceptance ( High Volume Nodes - HVNs ), rejection ( Low Volume Nodes - LVNs ), Volume Peaks Clusters , Volume Troughs Clusters , the Point of Control (POC) , and the Value Area (VA) . This insight is crucial for spotting potential support/resistance levels, assessing market sentiment, and making more informed trading decisions.
This indicator operates on the principle that price levels with higher traded volume hold greater significance, often acting as pivotal points for future price movements. Conversely, areas with low volume typically indicate less agreement on price, leading to quicker price transitions. The Volume Profile (PRO) offers extensive customization to tailor the analysis to your specific needs and trading style.
█ KEY FEATURES
Comprehensive Volume Analysis: Visualize volume distribution horizontally, revealing key price levels based on actual traded volume.
Dynamic Profile Calculation: Uses a rolling lookback period to keep the profile relevant to recent price action.
Point of Control (POC): Automatically identifies and plots the price level with the highest traded volume within the profile period. Available as a "Regular" (fixed for the current profile) or "Developing" line that tracks its evolution bar-by-bar.
Value Area (VA): Highlights the price range where a specified percentage (typically 70%) of the total volume was traded. Also available as "Regular" or "Developing" VAH (Value Area High) and VAL (Value Area Low) lines.
High and Low Volume Nodes (HVNs & LVNs): Option to automatically detect and highlight a specified number of the highest volume concentration zones (HVNs) and lowest volume zones (LVNs) within the profile. These are crucial for identifying support/resistance and areas of potential quick price movement.
Volume Peaks and Troughs Detection: Identify statistically significant high-volume (Peaks) and low-volume (Troughs) rows relative to their neighbors, either as single rows or clusters. These can pinpoint precise levels of interest.
Multiple Volume Display Types: Choose to display volume as:
- Up/Down: Shows buying and selling volume side-by-side for each row.
- Total: Shows the aggregate volume for each row.
- Delta: Shows the difference between buying and selling volume for each row, highlighting imbalances.
Extensive Customization: Fine-tune lookback period, number of rows, profile width, horizontal placement, Value Area percentage, colors for all elements, and specific parameters for node/peak/trough detection.
Visual Enhancements:
- Optional gradient colors for volume bars.
- Display volume figures directly on rows.
- Background shading for the Value Area and the entire Profile range.
- Price labels for POC, VAH, VAL, Profile High, and Profile Low.
Integrated Alert System: Pre-built alert conditions for critical volume profile events. (See section on "█ SETTING UP ALERTS " for more details).
█ USER INPUTS
The settings panel is organized into distinct sections:
- Calculation Settings:
Lookback: Number of most recent bars for profile calculation.
Number of Rows: Resolution of the volume profile.
Profile Width: Relative horizontal length of the volume bars.
Horizontal Offset: Horizontal positioning of the profile.
Value Area (%): Percentage of volume to include in the Value Area.
Volume: Display type ("Up/Down", "Total", "Delta").
Profile Placement: "Right" or "Left" side of the chart.
- Appearance:
Volume Profile On/Off: Toggle visibility of the entire profile.
Rows Border Width & Color: Customize the outline of volume rows.
Gradient Colors: Enable/disable gradient coloring for volume bars.
Row Volume: Display numerical volume on each row.
VAH (Value Area High): Display type ("None", "Regular", "Developing"), Color, Price Label, Line Width.
VAL (Value Area Low): Display type ("None", "Regular", "Developing"), Color, Price Label, Line Width.
Profile High Price Label & Color: Toggle and customize.
Profile Low Price Label & Color: Toggle and customize.
Value Area Up/Down Color: Colors for up/down volume within VA.
Profile Up/Down Color: Colors for up/down volume outside VA.
Total Volume Color: For "Total" volume display type.
Delta Volume Positive/Negative Color: For "Delta" volume display type.
POC (Point of Control): Display type ("None", "Regular", "Developing"), Color, Line Width, Price Label.
Value Area Background & Color: Enable and customize VA background shading.
Profile Background & Color: Enable and customize profile range background shading.
Volume Nodes:
Highest Volume Nodes & Color: Number of HVNs to highlight and their color.
Lowest Volume Nodes & Color: Number of LVNs to highlight and their color.
Volume Peaks: Detection type ("None", "Single Row", "Cluster"), Color.
Compared Neighbors (Peaks): Number of neighboring rows to compare against for peak detection.
Minimum Peak Ratio (Peaks): Volume ratio required for a row to be considered a peak.
Volume Troughs: Detection type ("None", "Single Row", "Cluster"), Color.
Compared Neighbors (Troughs): Number of neighboring rows to compare against for trough detection.
Minimum Trough Ratio (Troughs): Volume ratio required for a row to be considered a trough.
█ SETTING UP ALERTS
The Volume Profile (PRO) indicator comes with a comprehensive set of pre-configured alert conditions to notify you of key market events related to volume structure. To set up an alert:
Click the " Alert " button (clock icon) on TradingView's right-hand toolbar or top panel.
In the " Condition " dropdown, select " Volume Profile (PRO) ".
A second dropdown will appear, allowing you to choose from the following specific alert conditions built into the script:
- POC Price Change: Triggers when the Point of Control price level changes.
- POC Crossover: Triggers when the closing price crosses over the POC line and is now above it.
- POC Crossunder: Triggers when the closing price crosses under the POC line and is now below it.
- Close Inside Value Area: Triggers when the closing price enters the Value Area.
- Close Outside Value Area: Triggers when the closing price exits the Value Area.
- Close Inside High Volume Node: Triggers when the closing price enters a detected High Volume Node.
- Close Inside Low Volume Node: Triggers when the closing price enters a detected Low Volume Node.
- Close Inside Volume Peak: Triggers when the closing price enters a detected Volume Peak row.
- Close Inside Volume Peak Cluster: Triggers when the closing price enters the area of a Volume Peak cluster.
- Close Inside Volume Trough: Triggers when the closing price enters a detected Volume Trough row.
- Close Inside Volume Trough Cluster: Triggers when the closing price enters the area of a Volume Trough cluster.
Choose your preferred " Trigger " option:
- " Only Once ": The alert triggers the first time the condition is met.
- " Once Per Bar Close ": ( Recommended for most profile signals ) The alert triggers only after the current bar closes if the condition was true on that closed bar. This ensures signals are based on confirmed price action.
Customize the alert name, message, and notification preferences.
Click " Create ".
█ STRATEGY EXAMPLES
The following examples are for illustrative purposes only to demonstrate how the Volume Profile (PRO) can be used. They are not financial advice. Always conduct thorough backtesting and research.
1. POC as Dynamic Support/Resistance
Goal: Identify potential bounces or rejections from the Point of Control.
Setup: Enable "POC Line" (Regular or Developing) and observe price interaction.
Entry (Long):
- Price approaches the POC from above and shows signs of holding (e.g., bullish candlestick patterns, deceleration).
- Enter on confirmation of support at the POC.
Entry (Short):
- Price approaches the POC from below and shows signs of rejection (e.g., bearish candlestick patterns).
- Enter on confirmation of resistance at the POC.
Management: Stop-loss beyond the recent swing pivot or the POC itself after a confirmed break. Target the next significant volume node (HVN/LVN) or Value Area boundary.
2. Trading Low Volume Nodes (LVNs) as "Vacuum Zones"
Goal: Capitalize on rapid price movement through LVNs and their potential to become support/resistance once traversed.
Setup: Enable "Lowest Volume Nodes" to identify LVNs.
Entry (Long):
- Price breaks decisively above an LVN.
- Look for a retest of the top of the LVN as support. Enter long on confirmation.
Entry (Short):
- Price breaks decisively below an LVN.
- Look for a retest of the bottom of the LVN as resistance. Enter short on confirmation.
Concept: Price is expected to move quickly through LVNs (volume vacuum). Once price has passed through an LVN, that area of prior low acceptance can act as a new support/resistance zone.
Management: Stop-loss beyond the retested LVN. Target the next HVN or significant price level.
█ CONCLUSION
The Volume Profile (PRO) indicator offers a sophisticated and highly customizable approach to volume analysis. By providing clear visualizations of POC, Value Area, HVNs, LVNs, and Volume Peaks/Troughs, along with integrated alerts and developing levels, this tool empowers traders to identify critical price zones, understand market structure, and develop more nuanced trading strategies. Whether you're looking for precise entry points, areas of support and resistance, or confirmation of market sentiment, this Volume Profile indicator is an invaluable addition to your technical analysis toolkit.
█ IMPORTANT NOTES
⚠ Lookback vs. Calculated Bars Relationship: The value set in the " Lookback " input ( Calculation Settings ) must be less than half of the number of bars the indicator is set to calculate on your chart (referred to as " Calculated bars " in the script, typically controlled by TradingView's historical data loading or a calc_bars_count setting within the script's indicator() declaration – in this script, it is 1200 bars by default). For example, if "Calculated bars" is 1200, your Lookback should be less than 600. The default Lookback of 500 respects this. Setting a Lookback too high relative to available calculated bars can lead to errors or incorrect profile rendering.
⚠ Parameter Optimization: The default settings are starting points. Always adjust indicator parameters (Lookback, Number of Rows, VA%, etc.) based on the specific asset, its volatility, and the timeframe you are trading. Thorough backtesting is crucial.
⚠ Context is Key: Volume Profile is powerful, but its signals are best interpreted within the broader market context (trend, news, other technical indicators).
⚠ Lookback vs. Profile Stability: A shorter lookback makes the profile very responsive to recent action but less stable. A longer lookback provides more stable levels but may lag in fast-moving markets.
⚠ Number of Rows: Higher row counts offer more granularity but can impact performance and may show too much noise. Lower row counts offer a broader view but may obscure finer details.
⚠ Alert Confirmation: Using " Once Per Bar Close " for alerts is generally recommended to ensure signals are based on confirmed price action.
█ RISK DISCLAIMER
Trading involves a substantial risk of loss and is not suitable for all investors. The Volume Profile (PRO) indicator is provided for educational and informational purposes only . It does NOT constitute financial advice or a recommendation to buy or sell any asset. Indicator signals identify potential patterns based on historical data but do not guarantee future price movements or profitability. Always conduct your own thorough research, utilize multiple sources of information, and implement robust risk management practices before making any trading decisions. Past performance is not indicative of future results.
📊 Happy trading! 🚀
Profit Guard ProProfitGuard Pro
ProfitGuard Pro is a risk management and profit calculation tool that helps traders optimize their trades by handling position sizing, risk management, leverage, and take profit calculations. With support for both cumulative and non-cumulative take profit strategies, this versatile indicator provides the insights you need to maximize your trading strategy.
How to Use ProfitGuard Pro:
Load the Indicator: Add ProfitGuard Pro to your chart in TradingView.
Set Your Entry Position: Input your desired entry price.
Define Your Stop Loss: Enter the price at which your trade will exit to minimize losses.
Add Take Profit Levels: Input your TP1, TP2, TP3, and TP4 levels, as needed.
If you want fewer take profit levels, adjust the number of TPs in the settings menu. You can choose between 1 to 4 take profit levels based on your strategy.
Adjust Risk Settings: Specify your account size and risk percentage to calculate position size and leverage.
Choose Cumulative or Non-Cumulative Mode: Toggle cumulative profit mode to either recalculate position sizes as each take profit is hit or keep position sizes static for each TP.
Once set up, ProfitGuard Pro will automatically calculate your position size, leverage, and potential profits for each take profit level, providing a clear visual on your chart to guide your trading decisions.
Key Features:
Risk Management:
Calculate your risk percentage based on account size and stop loss.
Visualize risk in dollar terms and percentage of your account.
Position Size & Leverage:
Automatically calculate the ideal position size and leverage for your trade based on your entry, stop loss, and risk settings.
Ensure you are trading with the appropriate leverage for your account size.
Cumulative vs Non-Cumulative Profit Mode:
Cumulative Mode: Adjusts position size after each take profit is reached, recalculating for remaining contracts.
Non-Cumulative Mode: Treats each take profit as a separate calculation using the full position size.
Take Profit Levels:
Set up to 4 customizable take profit levels.
Adjust percentage values for each TP target, and visualize them on your chart with easy-to-read lines.
Profit Calculation:
Displays potential profits for each take profit level based on whether cumulative or non-cumulative mode is selected.
Calculate your risk-reward ratio dynamically at each TP.
Customizable Visuals:
Easily customize the table's size, position, and color scheme to fit your chart.
Visualize key trade details like leverage, contracts, margin, and profits directly on your chart.
Short and Long Position Support:
Automatically adjusts calculations based on whether you're trading long or short.
Value at Risk (VaR/CVaR) - Stop Loss ToolThis script calculates Value at Risk (VaR) and Conditional Value at Risk (CVaR) over a configurable T-bar forward horizon, based on historical T-bar log returns. It plots projected price thresholds that reflect the worst X% of historical return outcomes, helping set statistically grounded stop-loss levels.
A 95% 5-day VaR of −3% means: “In the worst 5% of all historical 5-day periods, losses were 3% or more.” If you're bullish, and your thesis is correct, price should not behave like one of those worst-case scenarios. So if the market starts trading below that 5-day VaR level, it may indicate that your long bias is invalidated, and a stop-loss near that level can help protect against further downside consistent with tail-risk behavior.
How it's different:
Unlike ATR or standard deviation-based methods, which measure recent volatility magnitude, VaR/CVaR incorporate both the magnitude and **likelihood** (5% chance for example) of adverse moves. This makes it better suited for risk-aware position sizing and exits grounded in actual historical return distributions.
How to use for stop placement:
- Set your holding horizon (T) and confidence level (e.g., 95%) in the inputs.
- The script plots a price level below which only the worst 5% (or chosen %) of T-bar returns have historically occurred (VaR).
- If price approaches or breaches the VaR line, your bullish/bearish thesis may be invalidated.
- CVaR gives a deeper threshold: the average loss **if** things go worse than VaR — useful for a secondary or emergency stop.
FURTHER NOTES FROM SOURCE CODE:
//======================================================================//
// If you're bullish (expecting the price to go up), then under normal circumstances, prices should not behave like they do on the worst-case days.
// If they are — you're probably wrong, or something unexpected is happening. Basically, returns shouldn't be exhibiting downside tail-like behavior if you're bullish.
// VaR(95%, T) gives the threshold below which the price falls only 5% of the time historically, over T days/bars and considering N historical samples.
// CVaR tells you the expected/average price level if that adverse move continues
// Caveats:
// For a variety of reasons, VaR underestimates volatility, despite using historical returns directly rather than making normality assumptions
// as is the case with the standard historicalvol/bollinger band/stdev/ATR approaches)
// Volatility begets volatility (volatility clustering), and VaR is not a conditional probability on recent volatility so it likely underestimates the true volatility of an adverse event
// Regieme shifts occur (bullish phase after prolonged bearish behavior), so upside/short VaR would underestimate the best-case days in the beginning of that move, depending on lookahead horizon/sampling period
// News/events happen, and maybe your sampling period doesn't contain enough event-driven returns to form reliable stats
// In general of course, this tool assumes past return distributions are reflective of forward risk (not the case in non-stationary time series)
// Thus, this tool is not predictive — it shows historical tail risk, not guaranteed outcomes.
// Also, when forming log-returns, overlapping windows of returns are used (to get more samples), but this introduces autocorrelation (if it wasn't there already). This means again, the true VaR is underestimated.
// Description:
// This script calculates and plots both Value at Risk (VaR) and
// Conditional Value at Risk (CVaR) for a given confidence level, using
// historical log returns. It computes both long-side (left tail) and
// short-side (right tail) risk, and converts them into price thresholds (red and green lines respectively).
//
// Key Concepts:
// - VaR: "There is a 95% chance the loss will be less than this value over T days. Represents the 95th-percentile worst empirical returns observed in the sampling period, over T bars.
// - CVaR: "Given that the loss exceeds the VaR, the average of those worst 5% losses is this value. (blue line)" Expected tail loss. If the worst case breached, how bad can it get on average
// - For shorts, the script computes the mirror (right-tail) equivalents.
// - Use T-day log returns if estimating risk over multiple days forward.
// - You can see instances where the VaR for time T, was surpassed historically with the "backtest" boolean
//
// Usage for Stop-Loss:
// - LONG POSITIONS:
// • 95th percentile means, 5% of the time (1 in 20 times) you'd expect to get a VaR level loss (touch the red line), over the next T bars.
// • VaR threshold = minimum price expected with (1 – confidence)% chance.
// • CVaR threshold = expected price if that worst-case zone is breached.
// → Use as potential stop-loss (VaR) or disaster stop (CVaR). If you're bullish (and you're right), price should not be exhibiting returns consistent with the worst 5% of days/T_bars historically.
//======================================================================//
1A Monthly P&L Table - Using Library1A Monthly P&L Table: Track Your Performance Month-by-Month
Overview:
The 1A Monthly P&L Table is a straightforward yet powerful indicator designed to give you an immediate overview of your asset's (or strategy's) percentage performance on a monthly basis. Displayed conveniently in the bottom-right corner of your chart, this tool helps you quickly assess historical gains and losses, making it easier to analyze trends in performance over time.
Key Features:
Monthly Performance at a Glance: Clearly see the percentage change for each past month.
Cumulative P&L: A running total of the displayed monthly P&L is provided, giving you a quick sum of performance over the selected period.
Customizable Display:
Months to Display: Choose how many past months you want to see in the table (from 1 to 60 months).
Text Size: Adjust the text size (Tiny, Small, Normal, Large, Huge) to fit your viewing preferences.
Text Color: Customize the color of the text for better visibility against your chart background.
Intraday & Daily Compatibility: The table is optimized to display on daily and intraday timeframes, ensuring it's relevant for various trading styles. (Note: For very long-term analysis on weekly/monthly charts, you might consider other tools, as this focuses on granular monthly P&L.)
How It Works:
The indicator calculates the percentage change from the close of the previous month to the close of the current month. For the very first month displayed, it calculates the P&L from the opening price of the chart's first bar to the close of that month. This data is then neatly organized into a table, updated on the last bar of the day or session.
Ideal For:
Traders and investors who want a quick, visual summary of monthly performance.
Analyzing seasonal trends or consistent periods of profitability/drawdown.
Supplementing backtesting results with a clear month-by-month breakdown.
Settings:
Text Color: Changes the color of all text within the table.
Text Size: Controls the font size of the table content.
Months to Display: Determines the number of recent months included in the table.
Fibonacci & Volume Bell CurveBell Curve + Fibonacci Retracement
This custom indicator combines Fibonacci retracement levels with volume-weighted statistics (VWAP Bell Curve) to provide high-probability trading signals.
Indicator Components:
Fibonacci Retracement
Key Level Used:
Cyan (61.8%) – Golden Ratio: Most significant for identifying potential reversals.
Volume-Weighted Bell Curve (VWAP Bands)
White Line – VWAP (Volume Weighted Average Price).
Orange Bands (±2σ) – Represent two standard deviations above and below VWAP. Indicates the range where approximately 95% of volume-weighted price action occurs.
Trading Strategies:
Support & Resistance Trading
Fibonacci levels act as dynamic support/resistance.
The 61.8% level is especially effective for spotting reversal opportunities.
VWAP Mean Reversion
When price moves outside the ±2σ orange bands, expect a reversion back to the white VWAP line.
High-probability trades occur when price is extended to extremes.
Confluence Trading (High-Probability Setups). Strongest signals occur when Fibonacci levels align with VWAP bands. Look for overlap between Fib levels and VWAP support/resistance zones.
Pro Tips for Best Results:
Volume Confirmation: Look for increased volume at key levels for stronger signals.
Timeframes: Effective on all timeframes; higher timeframes offer more reliable signals.
Market Context: Always consider overall market direction and news events.
Multiple Touches: Levels become more valid when tested multiple times.
My settings:
Fibonacci Settings
Lookback Period: 50
Swing Detection Sensitivity: 5
Show Fibonacci Labels: ✅ Enabled
Bell Curve (VWAP Bands) Settings
Bell Curve Period: 100
VWAP Source: (H + L + C) / 3 (typical price)
Show Bell Curve Bands: ✅ Enabled
Confidence Levels: 2 Standard Deviations (±2σ)
Visual Settings
Fibonacci Line Width: 2
Bell Curve Line Width: 2
Extend Lines Right: ✅ Enabled
Fibonacci Levels
61.8% – ✅ Enabled, Color: Bright Blue
Other levels are disabled
VWAP & Bell Curve Bands
VWAP (White Line) – ✅ Enabled
Upper 1 SD – ✅ Enabled, Color: Gray
Lower 1 SD – ✅ Enabled, Color: Gray
Upper 2 SD – ✅ Enabled, Color: Orange-Red (with transparency)
Lower 2 SD – ✅ Enabled, Color: Orange-Red (with transparency)
Lorentzian Classification - Advanced Trading DashboardLorentzian Classification - Relativistic Market Analysis
A Journey from Theory to Trading Reality
What began as fascination with Einstein's relativity and Lorentzian geometry has evolved into a practical trading tool that bridges theoretical physics and market dynamics. This indicator represents months of wrestling with complex mathematical concepts, debugging intricate algorithms, and transforming abstract theory into actionable trading signals.
The Theoretical Foundation
Lorentzian Distance in Market Space
Traditional Euclidean distance treats all feature differences equally, but markets don't behave uniformly. Lorentzian distance, borrowed from spacetime geometry, provides a more nuanced similarity measure:
d(x,y) = Σ ln(1 + |xi - yi|)
This logarithmic formulation naturally handles:
Scale invariance: Large price moves don't overwhelm small but significant patterns
Outlier robustness: Extreme values are dampened rather than dominating
Non-linear relationships: Captures market behavior better than linear metrics
K-Nearest Neighbors with Relativistic Weighting
The algorithm searches historical market states for patterns similar to current conditions. Each neighbor receives weight inversely proportional to its Lorentzian distance:
w = 1 / (1 + distance)
This creates a "gravitational" effect where closer patterns have stronger influence on predictions.
The Implementation Challenge
Creating meaningful market features required extensive experimentation:
Price Features: Multi-timeframe momentum (1, 2, 3, 5, 8 bar lookbacks) Volume Features: Relative volume analysis against 20-period average
Volatility Features: ATR and Bollinger Band width normalization Momentum Features: RSI deviation from neutral and MACD/price ratio
Each feature undergoes min-max normalization to ensure equal weighting in distance calculations.
The Prediction Mechanism
For each current market state:
Feature Vector Construction: 12-dimensional representation of market conditions
Historical Search: Scan lookback period for similar patterns using Lorentzian distance
Neighbor Selection: Identify K nearest historical matches
Outcome Analysis: Examine what happened N bars after each match
Weighted Prediction: Combine outcomes using distance-based weights
Confidence Calculation: Measure agreement between neighbors
Technical Hurdles Overcome
Array Management: Complex indexing to prevent look-ahead bias
Distance Calculations: Optimizing nested loops for performance
Memory Constraints: Balancing lookback depth with computational limits
Signal Filtering: Preventing clustering of identical signals
Advanced Dashboard System
Main Control Panel
The primary dashboard provides real-time market intelligence:
Signal Status: Current prediction with confidence percentage
Neighbor Analysis: How many historical patterns match current conditions
Market Regime: Trend strength, volatility, and volume analysis
Temporal Context: Real-time updates with timestamp
Performance Analytics
Comprehensive tracking system monitors:
Win Rate: Percentage of successful predictions
Signal Count: Total predictions generated
Streak Analysis: Current winning/losing sequence
Drawdown Monitoring: Maximum equity decline
Sharpe Approximation: Risk-adjusted performance estimate
Risk Assessment Panel
Multi-dimensional risk analysis:
RSI Positioning: Overbought/oversold conditions
ATR Percentage: Current volatility relative to price
Bollinger Position: Price location within volatility bands
MACD Alignment: Momentum confirmation
Confidence Heatmap
Visual representation of prediction reliability:
Historical Confidence: Last 10 periods of prediction certainty
Strength Analysis: Magnitude of prediction values over time
Pattern Recognition: Color-coded confidence levels for quick assessment
Input Parameters Deep Dive
Core Algorithm Settings
K Nearest Neighbors (1-20): More neighbors create smoother but less responsive signals. Optimal range 5-8 for most markets.
Historical Lookback (50-500): Deeper history improves pattern recognition but reduces adaptability. 100-200 bars optimal for most timeframes.
Feature Window (5-30): Longer windows capture more context but reduce sensitivity. Match to your trading timeframe.
Feature Selection
Price Changes: Essential for momentum and reversal detection Volume Profile: Critical for institutional activity recognition Volatility Measures: Key for regime change detection Momentum Indicators: Vital for trend confirmation
Signal Generation
Prediction Horizon (1-20): How far ahead to predict. Shorter horizons for scalping, longer for swing trading.
Signal Threshold (0.5-0.9): Confidence required for signal generation. Higher values reduce false signals but may miss opportunities.
Smoothing (1-10): EMA applied to raw predictions. More smoothing reduces noise but increases lag.
Visual Design Philosophy
Color Themes
Professional: Corporate blue/red for institutional environments Neon: Cyberpunk cyan/magenta for modern aesthetics
Matrix: Green/red hacker-inspired palette Classic: Traditional trading colors
Information Hierarchy
The dashboard system prioritizes information by importance:
Primary Signals: Largest, most prominent display
Confidence Metrics: Secondary but clearly visible
Supporting Data: Detailed but unobtrusive
Historical Context: Available but not distracting
Trading Applications
Signal Interpretation
Long Signals: Prediction > threshold with high confidence
Look for volume confirmation
- Check trend alignment
- Verify support levels
Short Signals: Prediction < -threshold with high confidence
Confirm with resistance levels
- Check for distribution patterns
- Verify momentum divergence
- Market Regime Adaptation
Trending Markets: Higher confidence in directional signals
Ranging Markets: Focus on reversal signals at extremes
Volatile Markets: Require higher confidence thresholds
Low Volume: Reduce position sizes, increase caution
Risk Management Integration
Confidence-Based Sizing: Larger positions for higher confidence signals
Regime-Aware Stops: Wider stops in volatile regimes
Multi-Timeframe Confirmation: Align signals across timeframes
Volume Confirmation: Require volume support for major signals
Originality and Innovation
This indicator represents genuine innovation in several areas:
Mathematical Approach
First application of Lorentzian geometry to market pattern recognition. Unlike Euclidean-based systems, this naturally handles market non-linearities.
Feature Engineering
Sophisticated multi-dimensional feature space combining price, volume, volatility, and momentum in normalized form.
Visualization System
Professional-grade dashboard system providing comprehensive market intelligence in intuitive format.
Performance Tracking
Real-time performance analytics typically found only in institutional trading systems.
Development Journey
Creating this indicator involved overcoming numerous technical challenges:
Mathematical Complexity: Translating theoretical concepts into practical code
Performance Optimization: Balancing accuracy with computational efficiency
User Interface Design: Making complex data accessible and actionable
Signal Quality: Filtering noise while maintaining responsiveness
The result is a tool that brings institutional-grade analytics to individual traders while maintaining the theoretical rigor of its mathematical foundation.
Best Practices
- Parameter Optimization
- Start with default settings and adjust based on:
Market Characteristics: Volatile vs. stable
Trading Timeframe: Scalping vs. swing trading
Risk Tolerance: Conservative vs. aggressive
Signal Confirmation
Never trade on Lorentzian signals alone:
Price Action: Confirm with support/resistance
Volume: Verify with volume analysis
Multiple Timeframes: Check higher timeframe alignment
Market Context: Consider overall market conditions
Risk Management
Position Sizing: Scale with confidence levels
Stop Losses: Adapt to market volatility
Profit Targets: Based on historical performance
Maximum Risk: Never exceed 2-3% per trade
Disclaimer
This indicator is for educational and research purposes only. It does not constitute financial advice or guarantee profitable trading results. The Lorentzian classification system reveals market patterns but cannot predict future price movements with certainty. Always use proper risk management, conduct your own analysis, and never risk more than you can afford to lose.
Market dynamics are inherently uncertain, and past performance does not guarantee future results. This tool should be used as part of a comprehensive trading strategy, not as a standalone solution.
Bringing the elegance of relativistic geometry to market analysis through sophisticated pattern recognition and intuitive visualization.
Thank you for sharing the idea. You're more than a follower, you're a leader!
@vasanthgautham1221
Trade with precision. Trade with insight.
— Dskyz , for DAFE Trading Systems
SectorRotationRadarThe Sector Rotation Radar is a powerful visual analysis tool designed to track the relative strength and momentum of a stock compared to a benchmark index and its associated sector ETF. It helps traders and investors identify where an asset stands within the broader market cycle and spot rotation patterns across sectors and timeframes.
🔧 Key Features:
Benchmark Comparison: Measures the relative performance (strength and momentum) of the current symbol against a chosen benchmark (default: SPX), highlighting over- or underperformance.
Automatic Sector Detection: Automatically links stocks to their relevant sector ETFs (e.g., XLK, XLF, XLU), based on an extensive internal symbol map.
Multi-Timeframe Analysis: Supports simultaneous comparison across the current, next, and even third-higher timeframes (e.g., Daily → Weekly → Monthly), providing a bigger-picture perspective of trend shifts.
Tail Visualization: Displays a "trail" of price behavior over time, visualizing how the asset has moved in terms of relative strength and momentum across a user-defined period.
Quadrant-Based Layout: The chart is divided into four dynamic main zones, each representing a phase in the strength/momentum cycle:
🔄 Improving: Gaining strength and momentum
🚀 Leading: High strength and high momentum — top performers
💤 Weakening: Losing momentum while still strong
🐢 Lagging: Low strength and low momentum — underperformers
Clean Chart Visualization:
Background grid with axis labels
Dynamic tails and data points for each symbol
Option to include the associated sector ETF for context
Descriptive labels showing exact strength/momentum values per point
⚙️ Customization Options:
Benchmark Selector: Choose any symbol to compare against (e.g., SPX, Nasdaq, custom index)
Start Date Control: Option to fix a historical start point or use the current data range
Trail Length: Set the number of previous data points to display
Additional Timeframes: Enable analysis of one or two higher timeframes beyond the current
Sector ETF Display: Toggle to show or hide the related sector ETF alongside the asset
📚 Technical Architecture:
The indicator relies on external modules for:
Statistical modeling
Relative strength and momentum calculations
Chart rendering and label drawing
These components work together to compute and display a dynamic, real-time map of asset performance over time.
🧠 Use Case:
Sector Rotation Radar is ideal for traders looking to:
Spot stocks or sectors rotating into strength or weakness
Confirm alignment across multiple timeframes
Identify sector leaders and laggards
Understand how a symbol is positioned relative to the broader market and its peers
This tool is especially valuable for swing traders, sector rotation strategies, and macro-aware investors who want a visual edge in decision-making.
VWAP Fibonacci S&R with Bell CurveThis indicator is a sophisticated trading tool that combines three powerful technical analysis concepts to identify high-probability trading opportunities. Let me break down how it works:
Core Components:
1. VWAP (Volume Weighted Average Price)
Calculates the average price weighted by volume over a specified period
Acts as a dynamic support/resistance level that institutions often use
Can reset daily, weekly, or monthly depending on your trading timeframe
The yellow line on your chart represents the current VWAP
2. Bell Curve Probability Analysis
Measures how far the current price deviates from the VWAP in statistical terms
Calculates a Z-score (standard deviations away from the mean)
Creates probability bands around the VWAP based on price volatility
The theory: extreme deviations from VWAP tend to revert back to the mean
3. Fibonacci Retracement Levels
Uses recent highs and lows to calculate key Fibonacci levels (38.2%, 50%, 61.8%)
These levels often act as support and resistance zones
Combined with VWAP analysis for confluence trading
How the Signals Work:
BUY Signals (Green arrows below candles)
Generated when either condition is met:
Mean Reversion Buy: Price is below VWAP + high probability of reversion + extreme statistical deviation
Fibonacci Support Buy: Price is above VWAP + near key Fibonacci support levels (38.2% or 50%)
SELL Signals (Red arrows above candles)
Generated when either condition is met:
Mean Reversion Sell: Price is above VWAP + high probability of reversion + extreme statistical deviation
Fibonacci Resistance Sell: Price is below VWAP + near key Fibonacci resistance levels (61.8% or 50%)
Visual Elements
Yellow Line: Main VWAP
Blue Bands: Probability zones based on standard deviation
Orange/White/Purple Lines: Key Fibonacci levels (38.2%, 50%, 61.8%)
Yellow Background: High probability mean reversion zones
⚠ Symbol: Extreme deviation warning (Z-score > 2.5)
The Information Table
Shows real-time statistics:
VWAP: Current VWAP value
Distance: How far price is from VWAP (percentage)
Z-Score: Statistical measure of deviation (>2 is significant)
Reversion %: Probability of mean reversion
Fib 50%: Key Fibonacci midpoint level
Status: Current signal state
Trading Logic
The indicator works on the principle that:
Extreme deviations from VWAP are unsustainable and tend to revert
Fibonacci levels provide natural support/resistance zones
Volume confirmation ensures the move has institutional backing
Statistical probability helps time entries when odds are favorable
Best Use Cases
Scalping: Quick mean reversion trades when price gets too far from VWAP
Swing Trading: Using Fibonacci levels with VWAP for longer-term positions
Risk Management: Avoiding trades when probability is low
Confluence Trading: Waiting for multiple signals to align
Eigenvector Centrality Drift (ECD) - Market State Network What is Eigenvector Centrality Drift (ECD)?
Eigenvector Centrality Drift (ECD) is a groundbreaking indicator that applies concepts from network science to financial markets. Instead of viewing price as a simple series, ECD models the market as a dynamic network of “micro-states”—distinct combinations of price, volatility, and volume. By tracking how the influence of these states changes over time, ECD helps you spot regime shifts and transitions in market character before they become obvious in price.
This is not another moving average or momentum oscillator. ECD is inspired by eigenvector centrality—a measure of influence in network theory—and adapts it to the world of price action, volatility, and volume. It’s about understanding which market states are “in control” and when that control is about to change.
Theoretical Foundation
Network Science: In complex systems, nodes (states) and edges (transitions) form a network. Eigenvector centrality measures how influential a node is, not just by its direct connections, but by the influence of the nodes it connects to.
Market Micro-States: Each bar is classified into a “state” based on price change, volatility, and volume. The market transitions between these states, forming a network of possible regimes.
Centrality Drift: By tracking the centrality (influence) of the current state, and how it changes (drifts) over time, ECD highlights when the market’s “center of gravity” is shifting—often a precursor to major moves or regime changes.
How ECD Works
State Classification: Each bar is assigned to one of N market micro-states, based on a weighted combination of normalized price change, volatility, and volume.
Transition Matrix: Over a rolling window, ECD tracks how often the market transitions from each state to every other state, forming a transition probability matrix.
Centrality Calculation: Using a simplified eigenvector approach, ECD calculates the “influence” score for each state, reflecting how central it is to the network of recent market behavior.
Centrality Drift: The indicator tracks the Z-score of the change in centrality for the current state. Rapid increases or decreases, or a shift in the dominant state, signal a potential regime shift.
Dominant State: ECD also highlights which state currently has the highest influence, providing insight into the prevailing market character.
Inputs:
🌐 Market State Configuration
Number of Market States (n_states, default 6): Number of distinct micro-states to track.
3–4: Simple (Up/Down/Sideways)
5–6: Balanced (recommended)
7–9: Complex, more nuanced
Price Change Weight (price_weight, default 0.4):
How much price movement defines a state. Higher = more directional.
Volatility Weight (vol_weight, default 0.3):
How much volatility defines a state. Higher = more regime focus.
Volume Weight (volume_weight, default 0.3):
How much volume defines a state. Higher = more participation focus.
🔗 Network Analysis
Transition Matrix Window (transition_window, default 50): Lookback for building the state transition matrix.
Shorter: Adapts quickly
Longer: More stable
Influence Decay Factor (influence_decay, default 0.85): How much influence propagates through the network.
Higher: Distant transitions matter more
Lower: Only immediate transitions matter
Drift Detection Sensitivity (drift_sensitivity, default 1.5): Z-score threshold for significant centrality drift.
Lower: More signals
Higher: Only major shifts
🎨 Visualization
Show Network Visualization (show_network, default true): Background color and effects based on network structure.
Show Centrality Score (show_centrality, default true): Plots the current state’s centrality measure.
Show Drift Indicator (show_drift, default true): Plots the centrality drift Z-score.
Show State Map (show_state_map, default true): Dashboard showing all state centralities and which is dominant.
Color Scheme (color_scheme, default "Quantum"):
“Quantum”: Cyan/Magenta
“Neural”: Green/Blue
“Plasma”: Yellow/Pink
“Matrix”: Green/Black
Color Schemes
Dynamic gradients reflect the current state’s centrality and drift, using your chosen color palette.
Background network effect: The more central the current state, the more intense the background.
Centrality and drift lines: Color-coded for clarity and regime shift detection.
Visual Logic
Centrality Score Line: Plots the influence of the current state, with glow for emphasis.
Drift Indicator: Histogram of centrality drift Z-score, green for positive, red for negative.
Threshold Lines: Dotted lines mark the drift sensitivity threshold for regime shift alerts.
State Map Dashboard: Top-right panel shows all state centralities, highlights the current and dominant state, and visualizes influence with bars.
Information Panel: Bottom-left panel summarizes current state, centrality, dominant state, drift Z-score, and regime shift status.
How to Use ECD
Centrality Score: High = current state is highly influential; low = state is peripheral.
Drift Z-Score:
Large positive/negative = rapid change in influence, regime shift likely.
Near zero = stable network, no major shift.
Dominant State: The state with the highest centrality is “in control” of the market’s transitions.
State Map: Use to see which states are rising or falling in influence.
Tips:
Use fewer states for simple markets, more for nuanced analysis.
Watch for drift Z-score crossing the threshold—these are your regime shift signals.
Combine with your own system for confirmation.
Alerts:
ECD Regime Shift: Significant centrality drift detected—potential regime change.
ECD State Change: Market state transition occurred.
ECD Dominance Shift: Dominant market state has changed.
Originality & Usefulness
ECD is not a mashup or rehash of standard indicators. It is a novel application of network science and eigenvector centrality to market microstructure, providing a new lens for understanding regime shifts and market transitions. The state network, centrality drift, and dashboard are unique to this script. ECD is designed for anticipation, not confirmation—helping you see the market’s “center of gravity” shift before price action makes it obvious.
Chart Info
Script Name: Eigenvector Centrality Drift (ECD) – Market State Network
Recommended Use: Any asset, any timeframe. Tune parameters to your style.
Disclaimer
This script is for research and educational purposes only. It does not provide financial advice or direct buy/sell signals. Always use proper risk management and combine with your own strategy. Past performance is not indicative of future results.
See the market as a network. Anticipate the shift in influence.
— Dskyz , for DAFE Trading Systems
H4 Swing Grade Checklist English V.1✅ H4 Swing Grade Checklist – Auto Grading for Smart Money Setups
This script helps manual traders assess the quality of a Smart Money swing trade setup by checking 7 key criteria. The system assigns a grade (A+, A, A−, or B) based on how many and which checklist items are met.
📋 Checklist Items (7 total):
✅ Sweep occurs within 4 candles
✅ MSS (strong break candle)
✅ Entry is placed outside the wick of the sweep
✅ FVG is fresh (not previously used)
✅ FVG overlaps Fibonacci 0.705 level
✅ FVG lies within Premium or Discount zone
✅ Entry is placed at 0.705 Fibonacci retracement
🏅 Grading Criteria:
A+ → All 7 checklist items are satisfied
A → Only missing #5 (FVG Overlap with 0.705)
A− → Only missing #4 (FVG Fresh)
B → Only missing #2 (MSS – clear break of structure)
– → Any other combinations / fewer than 6 conditions met
⚙️ Features:
Toggle visibility with one click
Fixed display in top-right or bottom-right of the chart
Color-coded grading logic (Green, Yellow, Orange, Blue)
Clear checklist feedback for trade journaling or evaluation
🚀 Ideal For:
ICT / Smart Money traders
Prop firm evaluations
Swing trade quality control
Information Asymmetry Gradient (IAG) What is the Information Asymmetry Gradient (IAG)?
The Information Asymmetry Gradient (IAG) is a unique market regime and imbalance detector that quantifies the subtle, directional “information flow” in price and volume. Inspired by information theory and market microstructure, IAG is designed to help traders spot the early buildup of conviction or surprise—the kind of hidden imbalance that often precedes major price moves.
Unlike traditional volume or momentum indicators, IAG focuses on the efficiency and directionality of information transfer: how much “informational energy” is being revealed by up-moves versus down-moves, normalized by price movement. It’s not just about net flow, but about the quality and asymmetry of that flow.
Theoretical Foundation
Information Asymmetry: Markets move when new information is revealed. If one side (buyers or sellers) is consistently more “informationally efficient” per unit of price change, an imbalance is building—even if price hasn’t moved much yet.
Gradient: By tracking the rate of change (gradient) between fast and slow information flows, IAG highlights when a subtle imbalance is accelerating.
Volatility of Asymmetry: Sudden spikes in the volatility of information asymmetry often signal regime uncertainty or the approach of a “surprise” move.
How IAG Works
Directional Information Content: For each bar, IAG estimates the “information per unit of price change” for both up-moves and down-moves, using volume and price action.
Asymmetry Calculation: Computes the difference (or ratio) between up and down information content, revealing directional bias.
Gradient Detection: Calculates both a fast and slow EMA of the asymmetry, then measures their difference (the “gradient”), normalized as a Z-score.
Volatility of Asymmetry: Tracks the standard deviation of asymmetry over a rolling window, with Z-score normalization to spot “information shocks.”
Flow Strength: Quantifies the conviction of the current information flow on a 0–100 scale.
Regime Detection: Flags “extreme” asymmetry, “building” flow, and “high volatility” states.
Inputs:
🌌 Core Asymmetry Parameters
Fast Information Period (short_len, default 8): EMA period for detecting immediate information flow changes.
5–8: Scalping (1–5min)
8–12: Day trading (15min–1hr)
12–20: Swing trading (4hr+)
Slow Information Period (long_len, default 34): EMA period for baseline information context. Should be 3–5x fast period.
Default (34): Fibonacci number, stable for most assets.
Gradient Smoothing (gradient_smooth, default 3): Smooths the gradient calculation.
1–2: Raw, responsive
3–5: Balanced
6–10: Very smooth
📊 Asymmetry Method
Calculation Mode (calc_mode, default "Weighted"):
“Simple”: Basic volume split by direction
“Weighted”: Volume × price movement (default, most robust)
“Logarithmic”: Log-scaled for large moves
Use Ratio (show_ratio, default false):
“Difference”: UpInfo – DownInfo (additive)
“Ratio”: UpInfo / DownInfo (multiplicative, better for comparing volatility regimes)
🌊 Volatility Analysis
Volatility Window (stdev_len, default 21): Lookback for measuring asymmetry volatility.
Volatility Alert Level (vol_threshold, default 1.5): Z-score threshold for volatility alerts.
🎨 Visual Settings
Color Theme (color_theme, default "Starry Night"):
Van Gogh-inspired palettes:
“Starry Night”: Deep blues and yellows
“Sunflowers”: Warm yellows and browns
“Café Terrace”: Night blues and warm lights
“Wheat Field”: Golden and sky blue
Show Swirl Effects (show_swirls, default true): Adds swirling background to visualize information turbulence.
Show Signal Stars (show_stars, default true): Star markers at significant asymmetry points.
Show Info Dashboard (show_dashboard, default true): Top-right panel with current metrics and market state.
Show Flow Visualization (show_flow, default true): Main gradient line with artistic effects.
Color Schemes
Dynamic color gradients adapt to both the direction and intensity of the information gradient, using Van Gogh-inspired palettes for visual clarity and artistic flair.
Glow and aura effects: The main line is layered with glows for depth and to highlight strong signals.
Swirl background: Visualizes the “turbulence” of information flow, darker and more intense as flow strength and volatility rise.
Visual Logic
Main Gradient Line: Plots the normalized information gradient (Z-score), color-coded by direction and intensity.
Glow/Aura: Multiple layers for visual depth and to highlight strong signals.
Threshold Zones: Dotted lines and filled areas mark “Building” and “Extreme” asymmetry zones.
Volatility Ribbon: Area plot of volatility Z-score, highlighting information shocks.
Signal Stars: Circular markers at each “Extreme” event, color-coded for bullish/bearish; cross markers for volatility spikes.
Dashboard: Top-right panel shows current status (Extreme, Building, High Volatility, Balanced), gradient value, flow strength, information balance, and volatility status.
Trading Guide: Bottom-left panel explains all states and how to interpret them.
How to Use IAG
🌟 EXTREME: Major information imbalance—potential for explosive move or reversal.
🌙 BUILDING: Asymmetry is forming—watch for a breakout or trend acceleration.
🌪️ HIGH VOLATILITY: Information flow is unstable—expect regime uncertainty or “surprise” moves.
☁️ BALANCED: No clear bias—market is in equilibrium.
Positive Gradient: Bullish information flow (buyers have the edge).
Negative Gradient: Bearish information flow (sellers have the edge).
Flow >66%: Strong conviction—crowd is acting in unison.
Volatility Spike: Regime uncertainty—be alert for sudden moves.
Tips:
- Use lower periods for scalping, higher for swing trading.
- “Weighted” mode is most robust for most assets.
- Combine with price action or your own system for confirmation.
- Works on all assets and timeframes—tune to your style.
Alerts
IAG Extreme Asymmetry: Extreme information asymmetry detected.
IAG Building Flow: Information flow building.
IAG High Volatility: Information volatility spike.
IAG Bullish/Bearish Extreme: Directional extreme detected.
Originality & Usefulness
IAG is not a mashup of existing indicators. It is a novel approach to quantifying the “surprise” or “conviction” element in market moves, focusing on the efficiency and directionality of information transfer per unit of price change. The multi-layered color logic, artistic visual effects, and regime dashboard are unique to this script. IAG is designed for anticipation, not confirmation—helping you see subtle imbalances before they become obvious in price.
Chart Info
Script Name: Information Asymmetry Gradient (IAG) – Starry Night
Recommended Use: Any asset, any timeframe. Tune parameters to your style.
Disclaimer
This script is for research and educational purposes only. It does not provide financial advice or direct buy/sell signals. Always use proper risk management and combine with your own strategy. Past performance is not indicative of future results.
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
multi-tf standard devs [keypoems]Multi-Timeframe Standard Deviations Levels
A visual map of “how far is too far” across any three higher time-frames.
1. What it does
This script plots dynamic price “rails” built from standard deviation (StDev)—the same math that underpins the bell curve—on up to three higher-time-frames (HTFs) at once.
• It measures the volatility of intraday open-to-close increments, reaching back as far as 5000 bars (≈ 20 years on daily data).
• Each HTF can be extended to the next session or truncated at session close for tidy dashboards.
• Lines can be mirrored so you see symmetric positive/negative bands, and optional background fills shade the “probability cone.”
Because ≈ 68 % of moves live inside ±1 StDev, ≈ 95 % inside ±2, and ≈ 99.7 % inside ±3, the plot instantly shows when price is statistically stretched or compressed.
3. Key settings
Higher Time-Frame #1-3 Turn each HTF on/off, pick the interval (anything from 1 min to 1 year), and decide whether lines should extend into the next period.
Show levels for last X days Keep your chart clean by limiting how many historical sessions are displayed (1-50).
Based on last X periods Length of the StDev sample. Long look-backs (e.g. 5 000) iron-out day-to-day noise; short look-backs make the bands flex with recent volatility.
Fib Settings Toggle each multiple, line thickness/style/colour, label size, whether to print the numeric level, the live price, the HTF label, and whether to tint the background (choose your own opacity).
4. Under-the-hood notes
StDev is calculated on (close – open) / open rather than absolute prices, making the band width scale-agnostic.
Watch for tests of ±1:
Momentum traders ride the breakout with a target at the next band.
Mean-reversion traders wait for the first stall candle and trade back to zero line or VWAP.
Bottom line: Multi-Timeframe Standard-Deviations turns raw volatility math into an intuitive “price terrain map,” helping you instantly judge whether a move is ordinary, stretched, or extreme—across the time-frames that matter to you.
Original code by fadizeidan and stats by NQStats's ProbableChris.
Bullish Volume AnomalyAnomaly is designed to spot hidden bullish accumulation before price actually breaks out, by blending a trend-aware volume measure with a volatility-adjusted price channel. Here’s how it works:
First, it runs a simple ATR-based zigzag to identify the current swing direction. Volume is then signed (+ for up-trends, – for down-trends) and cumulatively summed. By converting that cumulative signed volume into a z-score over the past 480 bars, we get a sense of when buying or selling pressure is unusually strong relative to its own history.
At the same time, price itself is normalized into a z-score over the same 480-bar window, and its change over that period is also tracked. These two measures—volume z-score (s) and price z-score (p)—are compared, and the indicator looks for moments when s outpaces p by at least two standard deviations (s – p > 2), while price momentum change remains low (c < 1) and the net volume is positive (s > 0). That combination flags instances where heavy buying is taking place but price hasn’t yet reacted.
To define a dynamic trading zone, it plots a 288-bar EMA of price as the middle band (t2), and builds upper and lower bands around it using the average close-to-open range multiplied by a user-set factor. The lower band (t1) sits beneath the EMA by that volatility-based margin. A signal fires only when the bar’s high stays below t1—meaning price is still “sleeping” under the lower volatility boundary even as bullish volume builds up.
Together, these filters home in on anomalies: strong, trend-aligned volume surges that outstrip price movement, occurring while price sits below its lower volatility band. In practice, that often marks early accumulation before a breakout. You can tweak the ATR length and multiplier for the zigzag, as well as the channel period and range factor, to suit different markets or timeframes.
Normalized DXY+Custom USD Index (DXY+) – Normalized Dollar Strength with Bitcoin, Gold, and Yuan.
This custom USD strength index replicates the structure of the official U.S. Dollar Index (DXY), while expanding it to include modern financial assets such as Bitcoin (BTC), Ethereum (ETH), gold (XAU), and the Chinese yuan (CNY).
Weights for the core fiat currencies (EUR, JPY, GBP, CAD, SEK, CHF) follow the official ICE DXY methodology. Additional components are weighted proportionally based on their estimated global economic influence.
The index is normalized from its initial valid data point, meaning it starts at 100 on the first day all asset inputs are available. From that point forward, it tracks the relative strength of the U.S. dollar against this expanded basket.
This provides a more comprehensive and modernized view of the dollar's strength—not only against traditional fiat currencies, but also in the context of rising decentralized assets and non-Western trade power.
HGDA Hany Ghazy Digital Analytics area zone'sIndicator Name: HGDA Hany Ghazy Digital Analytics area zones
Description:
This indicator plots several key price zones based on the highest high and lowest low over a user-defined lookback period.
The plotted zones represent dynamic support and resistance levels calculated using specific ratios of the price range (High - Low), as follows:
- Zone 1 (Light Red): Represents an upper resistance zone.
- Zone 2 (Medium Green): Represents a medium support zone.
- Zone 3 (Dark Red): Represents a lower resistance zone.
- Zone 4 (Dark Green): Represents a strong support zone.
Additionally, the indicator plots a yellow "Zero" line representing the midpoint price of the selected period, serving as a balance point for price action.
This indicator is ideal for identifying the overall market trend, as prices typically move from the upper resistance zones (light red) downwards to the end of the wave in the lower zones (dark green). This helps traders better understand wave nature and direction.
Usage:
- The colored zones assist in identifying potential reversal or continuation areas.
- These zones can be used to plan entries, exits, and risk management.
- Default lookback period is 20 bars, adjustable in the settings to suit the timeframe.
Notes:
- This indicator relies on historical price data and does not guarantee market predictions.
- It is recommended to combine it with other indicators and analytical tools for improved trading decisions.
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Developed by Hany Ghazy Digital Analytics (HGDA).
Custom USD IndexThis is a modernized, expanded version of the U.S. Dollar Index (DXY), designed to provide a more accurate representation of the dollar’s global strength in today’s diversified economy.
Unlike the traditional DXY, which excludes major players like China and entirely omits real-world stores of value, this custom index (DXY+) includes:
Fiat Currencies (78.3% total weight):
EUR, JPY, GBP, CAD, AUD, CHF, and CNY — equally weighted to reflect the global currency landscape.
Gold (17.5%):
Gold (XAUUSD) is included as a traditional reserve asset and inflation hedge, acknowledging its continued monetary relevance.
Cryptocurrencies (2.8% total weight):
Bitcoin (BTC) and Ethereum (ETH) represent the emerging digital monetary layer.
The index rises when the U.S. dollar strengthens relative to this blended basket, and falls when the dollar weakens against it. This is ideal for traders, economists, and macro analysts seeking a more inclusive and up-to-date measure of dollar performance.
Float, Daily % Change & Short %This TradingView Pine Script displays a compact table on your chart showing four key metrics for any stock:
📊 What It Shows:
Float – Number of publicly available shares, formatted in K/M/B.
Daily % Change – Price change from yesterday’s close to the current price.
Intraday % Change – Price change from today’s open to the current price.
Short Volume % – Estimated short volume as a percentage of total daily volume.
⚙️ How to Use:
Add the script to your TradingView chart.
Choose table size and screen position from the settings panel.
The values update in real-time on the latest candle only, so they stay out of the way but always visible.
Ideal for momentum traders, short float hunters, and day traders who need quick access to real-time float, price action, and short volume stats.
SOFR Spread (proxy: FEDFUNDS - US03MY)📊 SOFR Spread (Proxy: FEDFUNDS - US03MY) – Monitoring USD Money Market Liquidity
In 2008, the spread exhibits a sharp vertical spike, signaling a severe liquidity dislocation: investors rushed into short-term U.S. Treasuries, pushing their yields down dramatically, while the FEDFUNDS rate remained relatively high.
This behavior indicates extreme systemic stress in the interbank lending market, preceding massive Federal Reserve interventions such as rate cuts, emergency liquidity operations, and the launch of quantitative easing (QE).
Description:
This indicator plots the spread between the Effective Federal Funds Rate (FEDFUNDS) and the 3-Month US Treasury Bill yield (US03MY), used here as a proxy for the SOFR spread.
It serves as a simple yet powerful tool to detect liquidity dislocations and stress signals in the US short-term funding markets.
Interpretation:
🔴 Spread > 0.20% → Possible liquidity stress: elevated repo rates, cash shortage, interbank distrust.
🟡 Spread ≈ 0% → Normal market conditions, balanced liquidity.
🟢 Spread < 0% → Excess liquidity: strong demand for T-Bills, “flight to safety”, or distortion due to expansionary monetary policy.
Ideal for:
Monitoring Fed policy impact
Anticipating market-wide liquidity squeezes
Correlation with DXY, SPX, VIX, MOVE Index, and risk sentiment
🧠 Note: As SOFR is not directly available on TradingView, FEDFUNDS is used as a reliable proxy, closely tracking the same trends in most macro conditions.
Statistical Pairs Trading IndicatorZ-Score Stat Trading — Statistical Pairs Trading Indicator
📊🔗
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What is it?
Z-Score Stat Trading is a powerful indicator for statistical pairs trading and quantitative analysis of two correlated assets.
It calculates the Z-Score of the log-price spread between any two symbols you choose, providing both long-term and short-term Z-Score signals.
You’ll also see real-time correlation, volatility, spread, and the number of long/short signals in a handy on-chart table!
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How to Use 🛠️
1. Add the indicator to your chart.
2. Select two assets (symbols) to analyze in the settings.
3. Watch the Z-Score plots (blue and orange lines) and threshold levels (+2, -2 by default).
4. Check the info table for:
- Correlation
- Volatility
- Spread
- Number of long (NL) and short (NS) signals in the last 1000 bars
5. Set up alerts for signal generation or threshold crossings if you want to be notified automatically.
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Trading Strategy 💡
- This indicator is designed for statistical arbitrage (mean reversion) strategies.
- Long Signal (🟢):
When both Z-Scores drop below the negative threshold (e.g., -2), a long signal is generated.
→ Buy Symbol A, Sell Symbol B, expecting the spread to revert to the mean.
- Short Signal (🔴):
When both Z-Scores rise above the positive threshold (e.g., +2), a short signal is generated.
→ Sell Symbol A, Buy Symbol B, again expecting mean reversion.
- The info table helps you quickly assess the frequency of signals and the current statistical relationship between your chosen assets.
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Best Practices & Warnings 🚦
- Avoid high leverage! Pairs trading can be risky, especially during periods of divergence. Use conservative position sizing.
- Check for cointegration: Before using this indicator, make sure both assets are cointegrated or have a strong historical relationship. This increases the reliability of mean reversion signals.
- Check correlation: Only use asset pairs with a high correlation (preferably 0.8–0.9 or higher) for best results. The correlation value is shown in the info table.
- Scale in and out gradually: When entering or exiting positions, consider doing so in parts rather than all at once. This helps manage slippage and risk, especially in volatile markets.
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⚠️ Note on Performance:
This indicator may work a bit slowly, especially on large timeframes or long chart histories, because the calculation of NL and NS (number of long/short signals) is computationally intensive.
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Disclaimer ⚠️
This script is provided for educational and informational purposes only .
It is not financial advice or a recommendation to buy or sell any asset.
Use at your own risk. The author assumes no responsibility for any trading decisions or losses.
Fibo Normalized RSI & RSI RibbonPlots both standard and Z-score normalized RSI ribbons using Fibonacci-based periods. Supports adjustable normalization, optional 0–100 scaling, and multi-line visualizations for momentum and deviation analysis.
This tool is designed for traders who want to go beyond standard RSI by adding:
Statistical normalization (Z-score)
Multi-period analysis (Fibonacci structure)
Advanced divergence and exhaustion detection
It gives you both classical momentum context and mathematically rigorous deviation insight, making it ideal for:
Swing traders
Quant-inclined discretionary traders
Multi-timeframe analysts
Trend Confirmation
When both RSI and normalized RSI across short and long periods are stacked in the same direction (e.g., above 50 or with high Z-scores), the trend is likely strong.
Disagreement between the two ribbons (e.g., RSI high but normalized RSI flat) may indicate late-stage trend or false strength.
Mean Reversion Trades
Look for normalized RSI values > +2 or < -2 (i.e., ~2 standard deviations).
Cross-check with standard RSI to see if the move aligns with a traditional overbought/oversold level.
Great for fade/reversal setups when Z-score RSI is extreme but classic RSI is just beginning to turn.
Divergence Detection
Compare the slope of RSI vs. normalized RSI over same period:
If RSI is rising but normalized RSI is falling → momentum is fading despite apparent strength.
Excellent for early warnings before reversals.
Multi-Timeframe Confluence
Use short-period ribbons (e.g., 3–13) for tactical entries/exits.
Use long-period ribbons (e.g., 55–233) for macro trend bias.
Alignment across both = high-confidence zone.
ATS DELTABAR V5.0ATS DeltaBar Indicator: Volume Trend Momentum Analysis System
——Precisely Capturing "Price-Volume Resonance" Signals for Trend Reversals
Core Positioning
The ATS DeltaBar is a sub-chart indicator focused on the synergy between volume trends and price action. It dynamically monitors changes in volume momentum and price deviations to identify trend strengthening, exhaustion, and reversal signals. Its core value lies in:
Red/Green Bars: Visually reflect volume increases/decreases, revealing capital flow direction.
Divergence Signals: Warn of potential trend reversals (top/bottom divergence).
Resonance Breakouts/Breakdowns: Confirm high-probability trend continuation signals.
Red/Green Zones: Clearly define bullish/bearish phases (red = bearish, green = bullish).
I. Core Logic & Algorithm
1. Volume Trend Visualization
Bar Color Volume State Market Implication
Green Bar Volume ↑ vs. prior period Capital inflow, trend momentum strengthens
Red Bar Volume ↓ vs. prior period Capital outflow, trend momentum weakens
Bar Height Magnitude of volume change Quantifies intensity (higher = stronger shift)
📌 Key Insight:
Green bars + rising price = Healthy uptrend.
Red bars + price新高 = Potential top divergence risk.
2. Divergence Detection
Top Divergence: Price makes higher highs, but DeltaBar peaks lower (red bars accumulate) → Bullish exhaustion.
Bottom Divergence: Price makes lower lows, but DeltaBar troughs rise (green bars accumulate) → Bearish exhaustion.
3. Resonance Signal System
Resonance Breakout: Price breaks resistance + DeltaBar green volume spike → Confirmed uptrend acceleration.
Resonance Breakdown: Price breaks support + DeltaBar red volume spike → Confirmed downtrend weakness.
4. Bullish/Bearish Zone划分
Green Zone: DeltaBar consistently above neutral line → Bullish dominance (favor longs).
Red Zone: DeltaBar consistently below neutral line → Bearish dominance (caution for downside).
II. Signal Types & Practical Applications
1. Basic Trading Signals
Signal Type DeltaBar Behavior Trading Suggestion
Green Zone + Green Bar Price & volume rise together Hold/add to longs
Red Zone + Red Bar Price & volume decline together Short/exit longs
Top Divergence Price ↑ + DeltaBar peaks ↓ (red bars) Reduce longs/test shorts
Bottom Divergence Price ↓ + DeltaBar troughs ↑ (green bars) Prepare for reversal/cover shorts
2. Advanced Resonance Strategies
Breakout Trade: Enter when price breaks a key level + DeltaBar shows green volume spike (resonance breakout) → High-probability long.
Breakdown Trade: Enter when price breaks support + DeltaBar shows red volume spike (resonance breakdown) → High-probability short.
III. Comparison with Traditional Indicators
Aspect Traditional Volume (e.g., OBV) ATS DeltaBar
Signal Dimension Single cumulative volume direction 3D analysis: divergence + resonance + zone划分
Visualization Monotonic curve Dynamic dual-color bars + zones + threshold lines
Practicality Lags price action Real-time捕捉 divergence/resonance points
IV. Usage Scenarios & Tips
1. Trend Following
In Green Zone: Price above MA + DeltaBar green bars expanding → Hold longs.
In Red Zone: Price below MA + DeltaBar red bars expanding → Stay short/avoid longs.
2. Reversal Trading
Top Divergence + Bearish candlestick (e.g., Evening Star) + red bars → Short.
Bottom Divergence + Bullish engulfing + green bars → Long.
3. Breakout Filtering
Only trade breakouts where price and DeltaBar confirm共振 (avoids false breakouts).
V. Case Study (BTC/USDT 1H Chart)
Successful Long: Price broke resistance + DeltaBar green volume spike → 15% rally.
Successful Short: Price consolidated with red bar accumulation (top divergence) → 8% drop.
VI.注意事项
Combine with price structure (support/resistance) for higher accuracy.
Prioritize divergence in ranging markets; focus on共振 signals in trending markets.
"Volume is the fuel of price" — ATS DeltaBar quantifies this relationship to pinpoint trend ignition and reversal points.
