Session MasterSession Master Indicator
Overview
The "Session Master" indicator is a unique tool designed to enhance trading decisions by providing visual cues and relevant information during the critical last 15 minutes of a trading session. It also integrates advanced trend analysis using the Average Directional Index (ADX) and Directional Movement Index (DI) to offer insights into market trends and potential entry/exit points.
Originality and Functionality
This script combines session timing, visual alerts, and trend analysis in a cohesive manner to give traders a comprehensive view of market behavior as the trading day concludes. Here’s a breakdown of its key features:
Last 15 Minutes Highlight : The script identifies the last 15 minutes of the trading session and highlights this period with a semi-transparent blue background, helping traders focus on end-of-day price movements.
Previous Session High and Low : The script dynamically plots the high and low of the previous trading session. These levels are crucial for identifying support and resistance and are highlighted with dashed lines and labeled for easy identification during the last 15 minutes of the current session.
Directional Movement and Trend Analysis : Using a combination of ADX and DI, the script calculates and plots trend strength and direction. A 21-period Exponential Moving Average (EMA) is plotted with color coding (green for bullish and red for bearish) based on the DI difference, offering clear visual cues about the market trend.
Technical Explanation
Last 15 Minutes Highlight:
The script checks the current time and compares it to the session’s last 15 minutes.
If within this period, the background color is changed to a semi-transparent blue to alert the trader.
Previous Session High and Low:
The script retrieves the high and low of the previous daily session.
During the last 15 minutes of the session, these levels are plotted as dashed lines and labeled appropriately.
ADX and DI Calculation:
The script calculates the True Range, Directional Movement (both positive and negative), and smoothes these values over a specified length (28 periods by default).
It then computes the Directional Indicators (DI+ and DI-) and the ADX to gauge trend strength.
The 21-period EMA is plotted with dynamic color changes based on the DI difference to indicate trend direction.
How to Use
Highlight Key Moments: Use the blue background highlight to concentrate on market movements in the critical last 15 minutes of the trading session.
Identify Key Levels: Pay attention to the plotted high and low of the previous session as they often act as significant support and resistance levels.
Assess Trend Strength: Use the ADX and DI values to understand the strength and direction of the market trend, aiding in making informed trading decisions.
EMA for Entry/Exit: Use the color-coded 21-period EMA for potential entry and exit signals based on the trend direction indicated by the DI.
Conclusion
The "Session Master" indicator is a powerful tool designed to help traders make informed decisions during the crucial end-of-session period. By combining session timing, previous session levels, and advanced trend analysis, it provides a comprehensive overview that is both informative and actionable. This script is particularly useful for intraday traders looking to optimize their strategies around session close times.
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MSSM - Multi-Session Structural Map (Precision Sweeps)MSSM – Multi-Session Structural Map (Precision Sweeps)
This indicator provides a structured view of the market based on four key components:
1). Previous session levels
2). Confirmed fractal swing points
3). Volume pocket highlights
4). Non-repainting precision liquidity sweep markers
It is designed to help analyze how price interacts with important reference areas and structural points. This tool does not generate signals or predictions. All information is visual and educational only.
HOW THE INDICATOR WORKS
PREVIOUS SESSION LEVELS
The script plots the previous session’s High, Low, and Mid. These levels help observe how the current session behaves around the prior day’s range. They act as reference areas only.
FRACTAL SWING MAP (NON-REPAINTING)
Confirmed fractals are used to mark historical swing highs and swing lows. Since fractals confirm after a certain number of bars, the swings do not repaint once formed. These swings provide a clearer view of market structure.
VOLUME POCKETS
The indicator highlights areas where volume expands relative to a rolling volume average. These regions show increased participation or activity. The highlights are informational and do not imply direction.
PRECISION LIQUIDITY SWEEPS (NON-REPAINTING)
A sweep is tagged only when:
• Price trades beyond a confirmed swing high or swing low
• Price closes back inside the previous swing level
• A wick rejection occurs
• Volume expands relative to a recent rolling average
These markers simply show where price interacted with liquidity around prior structural levels. They do not indicate a trading signal or bias.
HOW TO ADD THE INDICATOR
Open the Pine Editor in TradingView
Search the indicator name and add to favorites.
Click “Add to chart”
Adjust settings as needed (fractals, sweeps, volume pockets, or session levels)
HOW TO READ AND USE THE INDICATOR
SESSION LEVELS
Observe whether price respects, rejects, compresses around, or expands beyond the previous session high, low, or midpoint. These are observational reference levels only.
FRACTALS
Fractal highs and lows help visualize structural turning points. They provide a clearer picture of where liquidity may rest above or below past swing levels.
VOLUME POCKETS
When volume expands compared to the recent average, the candle is shaded. These areas may show increased participation, but no directional meaning is implied.
PRECISION SWEEPS
Sweeps highlight when price reaches beyond a prior confirmed swing level and then rejects that area with displacement. These markers identify interactions with liquidity, but they are not signals and do not forecast future outcomes.
CUSTOMIZATION OPTIONS
Users can adjust:
• Session level visibility
• Fractal sensitivity
• Volume pocket threshold
• Sweep sensitivity and visibility
• Transparency and styling
This makes the tool flexible across different symbols and timeframes.
IMPORTANT NOTES AND POLICY COMPLIANCE
• The indicator does not provide buy or sell signals
• The indicator does not predict price or direction
• All plotted elements are based on past price behavior
• All components are informational only
• Users should perform their own analysis and risk evaluation
• Past behavior does not guarantee future performance
SUMMARY
MSSM provides a structured view of price by combining previous session levels, confirmed swing structure, volume expansion zones, and non-repainting sweep identification. Its purpose is to assist traders in visually analyzing market structure while staying fully aligned with TradingView’s House Rules and content policies.
HTF Hi-Lo Zones [CHE]HTF Hi-Lo Zones Indicator
The HTF Hi-Lo Zones Indicator is a Pine Script tool designed to highlight important high and low values from a selected higher timeframe. It provides traders with clear visual zones where price activity has reached significant points, helping in decision-making by identifying potential support and resistance levels. This indicator is customizable, allowing users to select the resolution type, control the visualization of session ranges, and even display detailed information about the chosen timeframe.
Key Functionalities
1. Timeframe Resolution Selection:
- The indicator offers three modes to determine the resolution:
- Automatic: Dynamically calculates the higher timeframe based on the current chart's resolution.
- Multiplier: Allows users to apply a multiplier to the current chart's timeframe.
- Manual: Enables manual input for custom resolution settings.
- Each resolution type ensures flexibility to suit different trading styles and strategies.
2. Data Fetching for High and Low Values:
- The indicator retrieves the current high and low values for the selected higher timeframe using `request.security`.
- It also calculates the lowest and highest values over a configurable lookback period, providing insights into significant price movements within the chosen timeframe.
3. Session High and Low Detection:
- The indicator detects whether the current value represents a new session high or low by comparing the highest and lowest values with the current data.
- This is crucial for identifying breakouts or significant turning points during a session.
4. Visual Representation:
- When a new session high or low is detected:
- Range Zones: A colored box marks the session's high-to-low range.
- Labels: Optional labels indicate "New High" or "New Low" for clarity.
- Users can customize colors, transparency, and whether range outlines or labels should be displayed.
5. Information Box:
- An optional dashboard displays details about the chosen timeframe resolution and current session activity.
- The box's size, position, and colors are fully customizable.
6. Session Tracking:
- Tracks session boundaries, updating the visualization dynamically as the session progresses.
- Displays session-specific maximum and minimum values if enabled.
7. Additional Features:
- Configurable dividers for session or daily boundaries.
- Transparency and styling options for the displayed zones.
- A dashboard for advanced visualization and information overlay.
Key Code Sections Explained
1. Resolution Determination:
- Depending on the user's input (Auto, Multiplier, or Manual), the script determines the appropriate timeframe resolution for higher timeframe analysis.
- The resolution adapts dynamically based on intraday, daily, or higher-period charts.
2. Fetching Security Data:
- Using the `getSecurityDataFunction`, the script fetches high and low values for the chosen timeframe, including historical and real-time data management to avoid repainting issues.
3. Session High/Low Logic:
- By comparing the highest and lowest values over a lookback period, the script identifies whether the current value is a new session high or low, updating session boundaries and initiating visual indicators.
4. Visualization:
- The script creates visual representations using `box.new` for range zones and `label.new` for session labels.
- These elements update dynamically to reflect the most recent data.
5. Customization Options:
- Users can configure the appearance, behavior, and displayed data through multiple input options, ensuring adaptability to individual trading preferences.
This indicator is a robust tool for tracking higher timeframe activity, offering a blend of automation, customization, and visual clarity to enhance trading strategies.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Best regards and happy trading
Chervolino
NDOG + ASIA CONFLUENCENDOG (New Day Opening Gap) Visualization:
The indicator identifies and visualizes New Day Opening Gaps (NDOGs), which are essentially the differences between the opening price of a new trading day and the closing price of the previous day.
For each NDOG identified, it creates a box on the chart that highlights the high and low price range of the NDOG.
The color of these boxes, as well as the number of NDOGs to be displayed, can be customized by the user.
Asia Session Highlighting:
The indicator includes a feature to highlight the Asia trading session, typically spanning from 18:00 to 00:00, but customizable to suit different time zones or preferences.
It does not dynamically calculate or display the Asia session but uses a fixed time input by the user.
The color for highlighting the Asia session can be chosen by the user.
Additional Lines on NDOGs:
The script draws horizontal lines at the high and low of each NDOG, spanning from 18:00 to 00:00, to visually represent the range of the NDOG during the Asia session.
The color of these lines can be customized.
Customizability:
The indicator provides various input options for users to customize the colors of the NDOG boxes and the lines that represent the high and low of the NDOGs.
Purpose and Usage:
This indicator is useful for traders who focus on price gaps between trading days and are particularly interested in the price action during the Asia trading session.
It helps in identifying potential zones of interest where significant price movements or trading activities could occur, especially at the opening of a new trading day.
Asian, UK & NY SessionTimes and Day Highs and LowsWhat It Does
The Asian, UK & NY Sessions indicator automatically identifies and highlights the three major global trading sessions on your chart.
For each session, it:
Detects session time in its local timezone.
Tracks the session’s highest and lowest prices.
Plots colored horizontal lines to show those levels throughout the trading day.
Optionally shades each session’s background in its signature color for instant visual context:
🟡 Asian Session: Yellow background
🔴 London Session: Red background
🔵 New York Session: Blue background
This helps traders see how price reacts within and between sessions — spotting overlaps, liquidity zones, and daily ranges.
⚙️ Inputs and Variables
Input Description
Extend lines until next session start (extendLines) Extends each session’s high/low lines forward until the next session begins.
Show prices in scale column (showScaleValues) Controls whether the price labels for session highs/lows appear on the chart’s right-hand price scale.
Show All Session Highs & Lows (showAllHighsLows) Master switch — turn this off to hide all session lines instantly, keeping the chart clean.
Show Session Backgrounds (showBackgrounds) Turns all background shading on or off. When off, all session colors disappear.
Background Opacity (bgOpacityAll) Adjusts the transparency for all session backgrounds (0 = solid, 100 = fully transparent).
🎨 Visual Color Scheme
Session Background High/Low Line
Asian Yellow Green
London Red Red
New York Blue Blue
Each color has a consistent role — making it easy to distinguish sessions even in replay or live view.
Price Tracking:
For each session, the indicator resets High and Low when the new session starts, then updates them as bars print.
Display Control:
If lines or backgrounds are disabled via settings, they’re completely hidden (no clutter, no partial transparency).
💡 How Traders Use It
Identify daily ranges in each global session.
Compare volatility between markets.
Align entries or exits with session transitions.
Observe how price respects previous session highs/lows.
Volume with Sessions, SMA, and ATR Pine Script creates a custom volume indicator with several features, including:
SMA of Volume: It calculates the simple moving average (SMA) of the volume, which helps identify trends and determine if the current volume is above or below the average.
ATR (Average True Range): It calculates the ATR, which measures market volatility over a defined period.
Bullish/Bearish Volume Coloring: The script colors the volume bars depending on whether the price is moving up (bullish) or down (bearish), and whether the volume is above or below the SMA of volume.
Session Highlighting: It defines two major trading sessions:
NYSE (New York Stock Exchange) session from 9:30 AM to 4:00 PM Eastern Time.
LSE (London Stock Exchange) session from 8:00 AM to 4:30 PM GMT. These sessions are highlighted with background colors for easy identification.
Plotting: The volume is plotted as a histogram with varying colors depending on price movement and volume relative to its SMA. The ATR is also plotted as a purple line, and the SMA of volume is displayed as an orange line.
Background Colors: Background colors are applied during the NYSE and LSE sessions to visually differentiate between these trading periods.
Here's a breakdown of each section:
Key Inputs:
smaLength and atrLength: User-defined values for the lengths of the SMA and ATR calculations.
Main Calculations:
smaVolume: The SMA of the volume over the user-defined length (smaLength).
atrValue: The Average True Range over the user-defined length (atrLength).
Color Logic for Volume Bars:
If the current close is higher than the previous close, the volume is considered bullish, and the bar is colored green. If the volume is above the SMA, it’s a darker green; otherwise, it’s a lighter shade.
If the current close is lower than the previous close, the volume is considered bearish, and the bar is colored red. If the volume is above the SMA, it’s a darker red; otherwise, it’s a lighter red.
Plotting:
The script plots the volume as a histogram with dynamic coloring.
The SMA of the volume is plotted as a line.
ATR is plotted as a purple line for reference.
Background Color Highlighting:
The background is colored green during the NYSE session and blue during the LSE session.
Market DNA: Structure, Volume, Range, and SessionsMarket DNA: Structure, Volume, Range, and Sessions**
The Market DNA indicator combines market structure, volume analysis, trading ranges, and global trading sessions into a single, comprehensive tool for traders. It helps identify key price levels, volume patterns, consolidation phases, and active market periods, enabling informed trading decisions.
Market Structure Detects swing highs and lows using `ta.pivothigh` and `ta.pivotlow`, plotting them as red/green triangles to highlight support/resistance and trend reversals.
- Fractal Volume Zones (FVG): Highlights areas of significant buying/selling pressure by comparing current volume to an average over a lookback period; high-volume zones are marked with a semi-transparent blue background.
- Trading Range: Defines a price channel using the Average True Range (ATR) and a multiplier, creating upper/lower bands to identify consolidation, breakouts, and potential trade levels.
- Market Sessions: Highlights major global trading sessions (Asia, Europe, US) with colored backgrounds (purple, teal, yellow) to indicate liquidity and volatility shifts.
How It Works
- Swing points help analyze trends and reversals.
- FVG confirms price movements with high volume for stronger signals.
- Trading range bands assist in identifying breakout opportunities and setting stops/take-profits.
- Session highlights allow traders to adapt strategies based on regional activity.
Customization
- Adjust `swing_length` for sensitivity in detecting turning points.
- Modify `volume_lookback` to control volume averaging.
- Tune `range_multiplier` for wider/narrower trading bands.
- Enable/disable session highlighting via `session_highlight`.
Use Cases
- Identify trends and key levels using swing points and FVG.
- Spot breakout opportunities with trading range bands.
- Adapt strategies to regional trading sessions for optimal timing.
This all-in-one indicator provides a clear, customizable view of the market, empowering traders to make data-driven decisions across asset classes and timeframes.
Asia Sessions AutoPlotting**Asia Sessions AutoPlotting**
This script is designed to automatically detect and plot the Asia session high and low levels directly on your chart, providing key session data for trading analysis. It is highly customizable, making it an essential tool for traders who rely on session data for decision-making.
### Key Features:
- **Asia Session Detection**: Automatically identifies the Asia session based on user-defined time settings (default: 0000-0845 UTC).
- **High/Low Line Plotting**: Displays high and low price levels for the session with customizable colors and line styles.
- **Line Extensions**: Option to extend session high/low lines for future price action reference.
- **Session Background Fill**: Adds an optional colored background to highlight the Asia session period.
- **Day Labels**: Includes labels for the session high/low levels with the corresponding day of the week.
- **Dynamic Session History**: Limits the display to a user-specified number of past sessions (default: 7) to keep the chart clean and focused.
- **Customizable Colors**: Highlights Mondays with unique colors for easy identification, while other weekdays use a different scheme.
### Use Cases:
- Identify key session levels for trading strategies.
- Monitor Asia session dynamics and their impact on subsequent sessions.
- Spot significant price reactions around session highs/lows.
### Inputs:
- **Session Time**: Adjust the session time to match your preferred Asia trading hours.
- **Toggle High/Low Lines**: Enable or disable the plotting of session highs and lows.
- **Line Extensions**: Extend the session high/low lines into future bars for better visualization.
- **Background Highlight**: Toggle a colored background for the Asia session.
- **Maximum Sessions**: Define how many past sessions to display for clarity.
This script is perfect for intraday traders, scalpers, and swing traders looking to gain insight into the Asia session and its influence on global markets. Fully adjustable and easy to use, it enhances your chart with critical information at a glance.
Simply add it to your TradingView chart, configure your settings, and let it do the work for you!
TLA20 - Multi-Session Box and Level ToolTLA20 is a highly customizable indicator designed to enhance intraday analysis by marking predefined trading sessions, key levels, and midpoints directly on your charts. With its versatile features, TLA20 is ideal for traders looking to visualize multiple time zones, daily price ranges, and historical reference levels efficiently.
Key Features:
Session Visualization: Mark up to three custom trading sessions with distinct start and end times, adjustable for different time zones and weekend inclusions.
Dynamic Highlights: Automatically draw session highs, lows, midlines, and open prices with options to extend beyond session bounds.
Custom Styling: Configure border colors, styles, and fill options for each session box to match your chart preferences.
Historical Levels: Highlight previous daily highs/lows, weekly highs/lows, and monthly highs/lows for improved context in your trading.
Intuitive Adjustments: Enable or disable each feature and customize settings for precise alignment with your trading strategy.
Use Cases:
Track trading sessions across different markets and time zones.
Identify key price levels like session midpoints and opens for entry/exit strategies.
Overlay historical levels to recognize potential support and resistance areas.
This indicator does not provide direct trading signals but serves as a robust tool for enhancing technical analysis.
Disclaimer: The script is provided “as is” without warranties of any kind. Always test on a demo account before applying in live markets.
6-9 session & levels6-9 Session & Levels - Customizable Range Analysis Indicator
Description:
This indicator provides comprehensive session-based range analysis designed for intraday traders. It calculates and displays key levels based on a customizable session period (default 6:00-9:00 AM ET).
Core Features:
Session Tracking
Monitors user-defined session times with timezone support
Displays session open, high, and low levels
Highlights session range with optional box visualization
Shows previous day RTH (Regular Trading Hours: 9:30 AM - 4:00 PM) levels
Range Levels
25%, 50%, and 75% range levels within the session
Range deviations at 0.5x, 1.0x, and 2.0x multiples
Fibonacci extension levels (customizable, default 1.33x and 1.66x)
Optional fill zones between Fibonacci levels
Time Zone Highlighting
Marks the 9:40-9:50 AM period as a potential reversal zone
Vertical lines with shading to identify key time windows
Statistical Analysis
Calculates mean and median extension levels based on historical sessions
Displays statistics table showing current range, average range, range difference, and z-score
Customizable sample size (1-100 sessions) for statistical calculations
Option to anchor extensions from either session open or high/low points
Input Settings Explained:
Session Settings
Levels Session Time: Define your session window in HHMM-HHMM format (default: 0600-0900)
Time Zone: Choose from UTC, America/New_York, America/Chicago, America/Los_Angeles, Europe/London, or Asia/Tokyo
Anchor Settings
Show Session Anchor: Toggle the session anchor line (marks session open price at 6:00 AM)
Anchor Style/Color/Width: Customize appearance (Solid/Dashed/Dotted, color, 1-4 width)
Show Anchor Label: Display price label for the anchor
Session Open Line: Similar options for the session open reference line
Range Box Settings
Show Range Box: Display a shaded rectangle highlighting the session high-to-low range
Range Box Color: Set the box background color and transparency
Range Levels (25%/50%/75%)
Show Range Levels: Toggle all three intermediate levels on/off
Individual Level Styling: Each level (25%, 50%, 75%) has its own color, style, and width settings
Show Range Level Labels: Display price labels for each level
Range Deviations
Show Range Deviations: Toggle deviation levels on/off
0.5x/1.0x/2.0x Settings: Each deviation multiplier can be customized with its own color, line style (Solid/Dashed/Dotted), and width
Show Range Deviation Labels: Display labels showing the deviation price levels
Previous Day RTH Levels
Show Previous RTH Levels: Display yesterday's regular trading hours high and low
RTH High/Low Styling: Separate color, style, and width settings for each level
Show Previous RTH Labels: Toggle price labels for RTH levels
Time Zones
Show 9:40-9:50 AM Zone: Highlight this specific time period with vertical lines and shading
Zone Color: Set the background fill color for the time zone
Zone Label Color/Text: Customize the label appearance and text
Fibonacci Extension Settings
Show Fibonacci Extensions: Toggle Fib levels on/off
Fib Extension Color/Style/Width: Customize line appearance
Show Fib Extension Labels: Display price labels
Fib Ext Level 1/2: Set custom multipliers (default 1.33 and 1.66, range 0-5 in 0.1 increments)
Show Fibonacci Fills: Display shaded zones between Fib levels
Fib Fill Color: Customize the fill color and transparency
Session High/Low Settings
Show Session High/Low Lines: Display the actual session extremes
Style/Color/Width: Customize line appearance
Show Labels: Toggle price labels for high/low levels
Extension Stats Settings
Show Statistical Levels on Chart: Display mean and median extension levels based on historical data
Extension Anchor Point: Choose whether to anchor from "Open" or "High/Low" of the session
Number of Sessions for Statistics: Set sample size (1-100, default 60) for calculating averages
Mean/Median High Extension: Separate styling for each statistical level (color, style, width)
Mean/Median Low Extension: Separate styling for downside statistical levels
Tables
Show Statistics Table: Display a summary table with current range, average range, difference, z-score, and sample size
Table Position: Choose from 9 positions (Bottom/Middle/Top + Center/Left/Right)
Table Text Size: Select from Auto, Tiny, Small, Normal, Large, or Huge
Display Settings
Projection Offset: Number of bars to extend lines forward (default 24)
Label Size: Choose from Tiny, Small, Normal, or Large
Price Decimal Precision: Set decimal places for price labels (0-6)
How It Works:
The indicator tracks the specified session period and calculates the session's open, high, low, and range. At the end of the session (9:00 AM by default), it projects all configured levels forward for the trading day. The statistical features analyze the last N sessions (you choose the number) to calculate typical extension behavior from either the session open or the session high/low points.
The z-score calculation helps identify whether the current session's range is normal, expanded, or contracted compared to recent history, allowing traders to adjust expectations for the rest of the day.
Use Case:
This indicator helps traders identify key support and resistance levels based on early session price action, understand current range context relative to historical averages, and spot potential reversal zones during specific time periods.
Note: This indicator is for informational purposes only and does not constitute investment advice. Always perform your own analysis before making trading decisions.
Scout Regiment - D17# Scout Regiment - D17 Indicator
## English Documentation
### Overview
Scout Regiment - D17 is a comprehensive TradingView indicator that combines multiple technical analysis tools into one powerful overlay indicator. It provides traders with market structure analysis, divergence detection, volume profiling, smart money concepts, and session analysis.
### Key Features
#### 1. **EMA (Exponential Moving Averages)**
- **Purpose**: Trend identification and dynamic support/resistance levels
- **Configuration**: 13 customizable EMAs with adjustable periods
- **Default Active EMAs**: EMA 3 (21), EMA 5 (55), EMA 7 (144), EMA 8 (233)
- **Uses**: Identify trend direction, entry/exit points, and trend strength
- **Color Coding**: Different colors for easy visual distinction
#### 2. **TFMA (Timeframe Moving Averages)**
- **Purpose**: Multi-timeframe trend analysis
- **Features**:
- 3 EMAs on higher timeframes
- Dynamic labels showing trend direction
- Price difference percentage display
- Customizable timeframe settings
- **Default Settings**: 21-period timeframe with lengths 55, 144, and 233
- **Benefits**: Align trades with higher timeframe trends
#### 3. **DFMA (Daily Frame Moving Averages)**
- **Purpose**: Daily timeframe perspective on any chart
- **Features**: Similar to TFMA but specifically for daily analysis
- **Default Timeframe**: 1D (Daily)
- **Use Case**: Long-term trend confirmation and positioning
#### 4. **PMA (Price Moving Averages)**
- **Purpose**: Price channel analysis with filled areas
- **Configuration**: 7 customizable moving averages with fill zones
- **Default Lengths**: 12, 144, 169, 288, 338, 576, 676
- **Visual**: Color-filled zones between selected MAs for channel trading
#### 5. **VWAP (Volume Weighted Average Price)**
- **Purpose**: Institutional trading levels and fair value
- **Features**:
- Multiple anchor periods (Session, Week, Month, Quarter, Year, etc.)
- Standard deviation bands
- Corporate event anchoring (Earnings, Dividends, Splits)
- **Use Case**: Identify institutional support/resistance and mean reversion opportunities
#### 6. **Divergence Detector**
- **Purpose**: Identify potential trend reversals
- **Supported Indicators**: MACD, MACD Histogram, RSI, Stochastic, CCI, Williams %R, Bias, Momentum, OBV, SOBV, VWmacd, CMF, MFI, and external indicators
- **Divergence Types**:
- Regular Bullish/Bearish
- Hidden Bullish/Bearish
- **Features**:
- Automatic divergence line drawing
- Customizable detection parameters
- Color-coded alerts
#### 7. **Volume Profile & Node Detection**
- **Purpose**: Identify key price levels based on volume distribution
- **Features**:
- Volume Profile with POC (Point of Control)
- Value Area High (VAH) and Value Area Low (VAL)
- Peak and trough volume node detection
- Highest/lowest volume node highlighting
- **Lookback**: Configurable (default 377 bars)
- **Use Case**: Identify support/resistance zones and liquidity areas
#### 8. **Smart Money Concepts**
- **Purpose**: Track institutional trading patterns
- **Features**:
- Market Structure (BOS - Break of Structure, CHoCH - Change of Character)
- Internal and Swing structures
- Strong/Weak Highs and Lows
- Equal Highs/Lows detection
- Fair Value Gaps (FVG)
- **Modes**: Historical or Present (latest only)
- **Use Case**: Trade with institutional flow
#### 9. **Trading Sessions**
- **Purpose**: Analyze market behavior during different global sessions
- **Available Sessions**:
- Asian Session
- Sydney, Tokyo, Shanghai, Hong Kong
- European Session
- London, New York, NYSE
- **Features**:
- Session boxes with high/low visualization
- Real-time countdown timers
- Volume and price change tracking
- Information table with session statistics
- **Customization**: Choose which sessions to display, colors, and box styles
### How to Use
#### For Trend Following:
1. Enable EMAs 3, 5, 7, and 8
2. Use TFMA for higher timeframe confirmation
3. Look for price above/below key EMAs for trend direction
4. Use VWAP as additional confirmation
#### For Reversal Trading:
1. Enable Divergence Detector with MACD Histogram and Bias
2. Look for divergences at key support/resistance levels
3. Confirm with Smart Money CHoCH signals
4. Use Volume Profile nodes as entry/exit targets
#### For Intraday Trading:
1. Enable Trading Sessions
2. Focus on high-volume sessions (London, New York overlap)
3. Use session highs/lows as support/resistance
4. Trade Fair Value Gaps during active sessions
#### For Swing Trading:
1. Use DFMA for daily trend
2. Enable PMA for channel identification
3. Look for price reactions at volume profile value areas
4. Confirm with swing structure breaks
### Best Practices
1. **Don't Overcrowd**: Enable only the components you need for your strategy
2. **Multi-Timeframe Analysis**: Always check higher timeframe TFMA/DFMA
3. **Confluence**: Look for multiple signals confirming the same direction
4. **Volume Confirmation**: Use Volume Profile to validate price action
5. **Session Awareness**: Be aware of which session is active for volatility expectations
### Performance Optimization
- Disable unused features to improve chart loading speed
- Use "Present Mode" for Smart Money Concepts if historical data isn't needed
- Reduce Volume Profile lookback period on slower devices
### Alerts
The indicator includes alert conditions for:
- All divergence types (8 conditions)
- Smart Money structure breaks (8 conditions)
- Equal highs/lows detection
- Fair Value Gaps formation
---
## 中文说明文档
### 概述
Scout Regiment - D17 是一款综合性TradingView指标，将多个技术分析工具整合到一个强大的叠加指标中。它为交易者提供市场结构分析、背离检测、成交量分析、聪明钱概念和时区分析。
### 核心功能
#### 1. **EMA（指数移动平均线）**
- **用途**：趋势识别和动态支撑阻力位
- **配置**：13条可自定义周期的EMA
- **默认启用**：EMA 3（21）、EMA 5（55）、EMA 7（144）、EMA 8（233）
- **应用**：识别趋势方向、进出场点位和趋势强度
- **颜色编码**：不同颜色便于视觉区分
#### 2. **TFMA（时间框架移动平均线）**
- **用途**：多时间框架趋势分析
- **特点**：
- 3条更高时间框架的EMA
- 显示趋势方向的动态标签
- 价格差异百分比显示
- 可自定义时间框架设置
- **默认设置**：21周期时间框架，长度为55、144和233
- **优势**：使交易与更高时间框架趋势保持一致
#### 3. **DFMA（日线框架移动平均线）**
- **用途**：在任何图表上提供日线时间框架视角
- **特点**：与TFMA类似，但专门用于日线分析
- **默认时间框架**：1D（日线）
- **使用场景**：长期趋势确认和定位
#### 4. **PMA（价格移动平均线）**
- **用途**：价格通道分析与填充区域
- **配置**：7条可自定义的移动平均线，带填充区域
- **默认长度**：12、144、169、288、338、576、676
- **视觉效果**：选定MA之间的彩色填充区域，用于通道交易
#### 5. **VWAP（成交量加权平均价格）**
- **用途**：机构交易水平和公允价值
- **特点**：
- 多个锚定周期（交易日、周、月、季度、年等）
- 标准差波段
- 企业事件锚定（财报、分红、拆股）
- **使用场景**：识别机构支撑阻力和均值回归机会
#### 6. **背离检测器**
- **用途**：识别潜在趋势反转
- **支持指标**：MACD、MACD柱状图、RSI、随机指标、CCI、威廉指标、乖离率、动量、OBV、SOBV、VWmacd、CMF、MFI及外部指标
- **背离类型**：
- 常规看涨/看跌背离
- 隐藏看涨/看跌背离
- **特点**：
- 自动绘制背离连线
- 可自定义检测参数
- 颜色编码警报
#### 7. **成交量分布与节点检测**
- **用途**：基于成交量分布识别关键价格水平
- **特点**：
- 成交量分布图与POC（控制点）
- 价值区域高点（VAH）和低点（VAL）
- 峰值和低谷成交量节点检测
- 最高/最低成交量节点突出显示
- **回溯期**：可配置（默认377根K线）
- **使用场景**：识别支撑阻力区域和流动性区域
#### 8. **聪明钱概念**
- **用途**：追踪机构交易模式
- **特点**：
- 市场结构（BOS-突破结构、CHoCH-结构转变）
- 内部和摆动结构
- 强/弱高低点
- 等高/等低检测
- 公允价值缺口（FVG）
- **模式**：历史模式或当前模式（仅最新）
- **使用场景**：跟随机构资金流动交易
#### 9. **交易时区**
- **用途**：分析不同全球时段的市场行为
- **可用时段**：
- 亚洲时段
- 悉尼、东京、上海、香港
- 欧洲时段
- 伦敦、纽约、纽交所
- **特点**：
- 时段方框显示高低点
- 实时倒计时
- 成交量和价格变化追踪
- 时段统计信息表格
- **自定义**：选择显示哪些时段、颜色和方框样式
### 使用方法
#### 趋势跟随策略：
1. 启用EMA 3、5、7和8
2. 使用TFMA进行更高时间框架确认
3. 观察价格在关键EMA上方/下方确定趋势方向
4. 使用VWAP作为额外确认
#### 反转交易策略：
1. 启用背离检测器（MACD柱状图和乖离率）
2. 在关键支撑阻力位寻找背离
3. 用聪明钱CHoCH信号确认
4. 使用成交量分布节点作为进出场目标
#### 日内交易策略：
1. 启用交易时区
2. 关注高成交量时段（伦敦、纽约重叠时段）
3. 使用时段高低点作为支撑阻力
4. 在活跃时段交易公允价值缺口
#### 波段交易策略：
1. 使用DFMA确定日线趋势
2. 启用PMA识别通道
3. 观察价格在成交量分布价值区域的反应
4. 用摆动结构突破确认
### 最佳实践
1. **避免过度拥挤**：仅启用策略所需的组件
2. **多时间框架分析**：始终检查更高时间框架的TFMA/DFMA
3. **汇合点**：寻找多个信号确认同一方向
4. **成交量确认**：使用成交量分布验证价格行为
5. **时段意识**：了解当前活跃时段以预期波动性
### 性能优化
- 禁用未使用的功能以提高图表加载速度
- 如果不需要历史数据，对聪明钱概念使用"当前模式"
- 在较慢设备上减少成交量分布回溯期
### 警报
指标包含以下警报条件：
- 所有背离类型（8个条件）
- 聪明钱结构突破（8个条件）
- 等高/等低检测
- 公允价值缺口形成
---
## Technical Support
For questions or issues, please refer to the TradingView community or contact the indicator creator.
## 技术支持
如有问题，请参考TradingView社区或联系指标创建者。
Essa's Sessions IndicatorOverview
This powerful tool is designed to visually map out the key trading sessions: Asia, London, and New York directly on your chart. By highlighting these periods and plotting their respective highs and lows, it helps you identify critical price levels, gauge market sentiment, and pinpoint potential breakout opportunities with ease.
What It Does
Visualizes Key Trading Sessions: Automatically draws colored backgrounds for the Asia, London, and New York sessions to show you exactly when the most important market activity is happening.
Plots Session Highs & Lows: Displays precise horizontal lines for the highest and lowest prices reached during each session, acting as key support and resistance levels.
Dual Timezone Mode: Easily switch between London (GMT/BST) and New York (EST/EDT) timezones with a single click. The indicator automatically adjusts all session times for you, ensuring accuracy no matter where you are.
Interactive & Informative Labels: Hover over any session high or low label to see a detailed tooltip containing:
The exact price level.
The session's price range (calculated in pips or points).
The total daily price range for broader context.
A simple volatility gauge (from "Low Vol 😴" to "High Vol 🔥").
Customizable Alerts: Enable breakout alerts to receive instant notifications the moment the price closes above a session high or below a session low.
Simple, powerful, and highly informative, this indicator is an essential tool for traders looking to build strategies around session-based price action.
LilSpecCodes1. Killzone Background Highlighting:
It highlights 4 key market sessions:
Killzone Time (EST) Color
Silver Bullet 9:30 AM – 12:00 PM Light Blue
London Killzone 2:00 AM – 5:00 AM Light Green
NY PM Killzone 1:30 PM – 4:00 PM Light Purple
Asia Open 7:00 PM – 11:00 PM Light Red
These are meant to help you focus during high-probability trading times.
__________________________________________________
2. Previous Day High/Low (PDH/PDL):
Plots green line = PDH
Plots red line = PDL
Tracks the current day’s session high/low and sets it as PDH/PDL on a new trading day
CHANGES WITH ETH/RTH
3. Inside Bar Marker:
Plots a small black triangle under bars where the high is lower than the previous bar’s high and the low is higher than the previous bar’s low (inside bars)
Useful for spotting potential breakout or continuation setups
4. Vertical Time Markers (White Dashed Lines)
Time (EST) Label
4:00 AM End of London Silver Bullet
9:30 AM NYSE Open
10:00 AM Start of NY Silver Bullet
11:00 AM End of NY Silver Bullet
11:30 AM (Customizable Input)
3:00 PM PM Killzone Ends
3:15 PM Futures Market Close
7:15 PM Asia Session Watch
Multi-VWAP System🚀 Multi-VWAP System — Anchored VWAP & Deviation Bands
Overview
The Multi-VWAP System provides traders with a professional-grade approach to anchored VWAP analysis. Inspired by Brian Shannon's pioneering work on Anchored VWAP, this indicator automatically calculates and plots:
Current Session VWAP
Previous Session VWAP (also known as "2-Day VWAP")
High-of-Day (HOD) Anchored VWAP
Each VWAP can also display optional Standard Deviation Bands to highlight statistically significant deviations from the volume-weighted average price.
🔍 Why Anchored VWAP Matters
Volume Weighted Average Price (VWAP) is among the most critical institutional indicators, as it represents the average price paid for a stock adjusted by trading volume. This makes VWAP crucial for identifying fair value and significant areas of institutional activity.
Institutions utilize VWAP extensively to guide their execution algorithms. For instance, if price dips below a 2-day anchored VWAP (anchored to the previous session's open), many institutions interpret this as a discounted entry, potentially triggering large-scale buy programs. Conversely, sustained movement above VWAP signals strong buying pressure and bullish sentiment.
📌 Why Multiple Anchors?
Traders commonly anchor VWAPs at critical reference points:
Current Session VWAP:
Essential for day traders as a reference for intraday sentiment. Price action above this line generally indicates bullish sentiment, while price below signals bearish sentiment.
Previous Session (2-Day) VWAP:
Heavily used by institutions and swing traders, it provides insight into multi-session sentiment. Institutions commonly activate buy or sell programs based on whether price is trading at a premium or discount relative to this VWAP.
High-of-Day (HOD) VWAP:
Frequently used by momentum traders, this anchor captures sentiment after the most recent intraday high. Price above the HOD VWAP suggests sustained bullish momentum, while price below might signal weakening momentum.
🌟 Standard Deviation Bands
Each anchored VWAP in this indicator includes optional Standard Deviation Bands, highlighting statistical extremes. Traders use these bands to:
Identify potentially overextended moves (beyond +2σ or +3σ).
Gauge momentum strength (holding above +1σ).
Spot mean-reversion setups when price returns to VWAP after extreme moves.
🎨 Dynamic Background and Momentum Colorization
To visually highlight strength or weakness in price action relative to VWAP:
Dynamic Background Fill between Current and Previous VWAPs:
Green background appears when the Current VWAP is above the Previous VWAP and the linear regression slope (adjustable length) is positive, indicating bullish sentiment.
Red background appears when the Current VWAP is below the Previous VWAP and the slope is negative, indicating bearish sentiment.
No fill when conditions are mixed or momentum is uncertain.
Gold Fill above HOD VWAP:
When price action is above the High-of-Day VWAP and momentum (linear regression slope) is positive, a subtle gold shading appears, quickly highlighting bullish momentum.
⚙ Fully Customizable Settings
Session Times: Adjust session start and end times to match your specific market hours.
Standard Deviation Bands: Enable or disable each VWAP’s deviation bands individually and select how many bands (1σ, 2σ, or 3σ) you'd like to display.
Momentum Slope Length: Adjustable lookback for linear regression slope calculation—giving you full control of trend sensitivity.
🎯 Who Should Use This Indicator?
This indicator is perfect for:
Day Traders who want quick insights into intraday sentiment shifts.
Swing Traders tracking institutional footprints and seeking optimal entry/exit points.
Momentum Traders who rely on clearly visible momentum signals from HOD anchored VWAPs.
Institutional Traders and Professionals seeking sophisticated, institutionally-inspired VWAP analysis without manual anchoring.
📈 Summary of Features
✅ Automatic VWAP Anchors (Current Session, Previous Session, High-of-Day)
✅ Optional Standard Deviation Bands for each VWAP anchor
✅ Dynamic Background Coloring based on price action and momentum conditions
✅ Gold Momentum Highlight for quick bullish momentum identification above HOD VWAP
✅ Fully Customizable Inputs for precise personalization and flexibility
📢 Conclusion
The Multi-VWAP System isn't just another VWAP indicator. It's an institutional-level, dynamic, multi-dimensional analysis tool inspired by the work of Brian Shannon and leading institutional traders. It takes the guesswork out of anchoring and analysis, leaving you free to focus on identifying and executing high-probability trade setups.
Enjoy trading smarter—not harder. Happy Trading! 🚀📊
Weekday Colors with Time Highlighting by NabojeetThis script is a Pine Script (version 6) indicator called "Weekday Colors with Time Highlighting" designed for TradingView charts. It has several key functions:
1. **Weekday Color Coding**:
- Assigns different background colors to each trading day (Monday through Friday)
- Allows users to customize the color for each day
- Includes toggles to enable/disable colors for specific days
2. **Time Range Highlighting**:
- Highlights a specific time period (e.g., 18:15-18:30) on every trading day
- Uses a custom color that can be adjusted by the user
- The time range is specified in HHMM-HHMM format
3. **High/Low Line Drawing**:
- Automatically identifies the highest high and lowest low points within the specified time range
- Draws horizontal lines at these levels when the time period ends
- Lines extend forward in time to serve as support/resistance references
- Users can customize the line color, width, and style (solid, dotted, or dashed)
The script is organized into logical sections with input parameters grouped by function (Weekday Colors, Weekday Display, Time Highlighting, and Horizontal Lines). Each section's inputs are customizable through the indicator settings panel.
This indicator would be particularly useful for traders who:
- Want visual distinction between different trading days
- Focus on specific time periods each day (like market opens, closes, or specific sessions)
- Use intraday support/resistance levels from key time periods
- Want to quickly identify session highs and lows
The implementation resets tracking variables at the beginning of each new time range and draws the lines once the time period ends, ensuring accurate high/low marking for each day's specified time window.
Author - Nabojeet
Trading Sessions with Highs and LowsTrading Sessions with Highs and Lows is designed to visually highlight specific trading sessions on the chart, providing traders with key insights into market behavior during these time periods. Here’s a detailed explanation of how the indicator works:
Key Features
1. Session Boxes:
• The indicator plots colored boxes on the chart to represent the price range of defined trading sessions.
• Each box spans the session’s start and end times and encapsulates the high and low prices during that period.
• Two trading sessions are defined by default:
• USA Trading Session: 9:30 AM - 4:00 PM (New York Time).
• UK Trading Session: 8:00 AM - 4:30 PM (London Time).
2. Session Labels:
• The name of the session (e.g., “USA” or “UK”) is displayed above the session box for clear identification.
3. High and Low Markers:
• Markers are added to the chart at the session’s high and low points:
• High Marker: A green label indicating the session high.
• Low Marker: A red label indicating the session low.
4. Dynamic Reset:
• After the session ends, the session high and low values are reset to na to prepare for the next trading day.
5. Customizable Background Colors:
• Each session’s box has a distinct, semi-transparent background color for better visual separation.
How It Works
1. Core Functionality:
• A function, plot_box, takes the session name, start time, end time, and background color as input.
• It calculates whether the current time is within the session.
• During the session:
• It tracks the session’s highest and lowest prices.
• It identifies the bars where the high and low occurred.
• At the session’s end:
• It plots a box on the chart covering the session’s time and price range.
• Labels are created for the session name and its high/low points.
2. Session Timing:
• Timestamps for the USA and UK trading sessions are calculated using the timestamp function with respective time zones.
3. Visual Elements:
• The box.new function draws the session boxes on the chart.
• The label.new function creates session name and high/low labels.
Usage
• Overlay Mode: The indicator is applied directly on the price chart (overlay=true), making it easy to visualize session-specific price behavior.
• Trading Strategy:
• Identify session-specific support and resistance levels.
• Observe price action trends during key trading periods.
• Align trading decisions with session dynamics.
Customization
While the indicator is preset for the USA and UK trading sessions, it can be easily modified:
1. Add/Remove Sessions: Define additional sessions by providing their start and end times.
2. Change Colors: Update the background_color in the plot_box calls to use different colors for sessions.
3. Adjust Time Zones: Replace the current time zones with others relevant to your trading style.
Visualization Example
• USA Session:
• Time: 9:30 AM - 4:00 PM (New York Time).
• Box Color: Semi-transparent orange.
• UK Session:
• Time: 8:00 AM - 4:30 PM (London Time).
• Box Color: Semi-transparent green.
Why Use This Indicator?
1. Market Awareness: Easily spot price behavior during high-liquidity trading periods.
2. Trend Analysis: Analyze how sessions overlap or affect each other.
3. Session Boundaries: Use session high/low levels as dynamic support and resistance zones.
This indicator is an essential tool for intraday and swing traders who want to align their strategies with key market timings.
Custom Hourly Highlight PeriodsThis Pine Script indicator for TradingView allows users to visually highlight up to five distinct periods within a trading day directly on their chart. It's designed to enhance chart analysis by emphasizing specific time frames that may coincide with increased market activity, trading sessions, or personal trading strategies.
Features:
Customizable Highlight Periods: Users can define up to five separate highlight periods, specifying both start and end hours for each. This flexibility supports a wide range of trading strategies and time zones.
Individual Period Activation: Each highlight period can be individually enabled or disabled, allowing users to focus on specific times of interest without cluttering the chart.
Color-Coded Visualization: Each period is highlighted with a different transparent color (blue, red, green, purple, and orange) for clear distinction between different segments of the trading day. Colors are customizable to fit personal preferences or chart themes.
User-Friendly Inputs: Simple input fields make it easy to adjust start/end times and toggle the visibility of each period, requiring no coding experience to customize.
Use Cases:
Identifying Repeating Patterns: Certain regional markets exhibit unique behaviors, with some creating sell pressure in the morning, while others generate buy pressure. This indicator allows for clear visualization of these patterns.
Market Session Highlights: Emphasize the opening and closing hours of major markets (e.g., NYSE, NASDAQ, Forex markets) to identify potential volatility or trading opportunities.
Personal Trading Hours: Mark the time frames when you typically trade or when your trading strategy performs best.
Economic Release Times: Highlight periods when important economic reports are released, which can significantly impact market movement.
Session Levels - Ultimate Range IndicatorSession Levels - Ultimate Range Indicator
Primarily developed for trading the E-MINI Futures Markets like NQ or ES from the CME Group,
but also more than suitable for Crypto or other instruments.
This indicator highlights the chosen session, which can be Globex, Asian, London and New York.
It plots the important levels and also renders the Opening Range as it forms (a.k.a. Initial Balance).
After the 1st hour Opening Range is finished, it can plot the Standard Deviations / Projections.
See below for a complete feature list.
All Opening Ranges on chart and for the New York session the Range Projections are turned on:
s3.tradingview.com
How to use (example):
If you are trading the Nasdaq Futures (NQ!)
Enable the Globex Overnight session. Basically in the Futures Market, the Globex session is everything outside of US trading hours of Stocks. This draws the important overnight levels, like the Low, 25%, 50%, 75% and the High.
Enable the New York Session with Levels and Opening Range. Generally, 70% of the time the 1st hour will put a Low or High of the day.
If the price is trading above the Globex Low, most likely the Low of the Day is formed and the price target for the day will be 1.5x Standard Deviation and 2x Standard Deviation.
[*} Deviation of the Initial Balance depends on the volume ad overall market structure.
** This is not financial advice or any guarantee **
Features:
Show each Session Highlighted on Intraday chart in it's own color (each session can be turned off and has customizable times and color)
Show Line Levels of each session: Low, 25%, 50%, 75% and the High (customizable color)
Show the Opening Range (Initial Balance) of the Asian, London and New York session. Note: NY has more options.
Opening Range is displayed as a box with level lines (customizable color)
Levels are drawn to the end of the NY Cash session (customizable time)
Show IB Standard Deviations 0.5 - 3.0. Calculated from the Opening Range (Initial Balance)
Option to display Higher Timeframe levels: Previous Day Open/Close and Previous Week Open/Close
All level lines and OR boxes size dynamically as the session progresses
Built in Alerts for when price hits key levels. e.g. Alert when price crosses the NY Opening Range High. Or an Alert when the first STDEV is hit.
Option to toggle display of drawings for Today's trading session only, or Show all recent session levels. This keeps the chart clean or not.
Extras:
The NY Opening Range also has a 50% level line
The NY Opening Bar can be highlighted separately
The Level Lines can have small labels turned on/off. Values are only shown on mouse over to keep a clean chart
Keep in mind:
1) This indicator works on all instruments, but on instruments with limited market hours, your chart setting
has to be set to "Extended Hours" otherwise. For example TSLA on NASDAQ.
2) The Exchange Time Zone for the CME Group is Chicago UTC-6. So the session times you configure in the settings menu are based on that timezone too.
3) Globex opens at 5pm CST and closes when the US session starts 8:30CST.
4) When enabling the Alerts in the Indicator settings, be sure to also create an alarm for this indicator using the Alarm function of Tradingview.
Statistcal Daily Profile & Ranges# Statistical Daily Profile & Ranges - TradingView Publication Guide
## Overview
The **Statistical Daily Profile & Ranges** indicator is a comprehensive tool designed to analyze intraday session behavior and daily range characteristics. It combines Average Daily Range (ADR) projection levels with detailed session-by-session statistics and probability-based trading insights derived from historical price action patterns.
## What This Indicator Does
This indicator provides traders with three core analytical components:
1. **ADR Projection Levels** - Dynamic support/resistance levels based on historical daily ranges
2. **Session Range Analysis** - Visual boxes and statistical breakdowns for four key trading sessions
3. **Dynamic Probability Display** - Real-time probability statistics based on overnight session relationships
## How It Works
### Average Daily Range (ADR) Calculation
The indicator calculates the average daily range over a user-defined lookback period (default: 10 days) and projects this range from each day's opening price. This creates two key levels:
- **ADR High**: Opening price + average daily range
- **ADR Low**: Opening price - average daily range
- **ADR Median**: The opening price (middle of the projected range)
These levels are recalculated at the start of each trading day and extend forward, providing dynamic support and resistance zones based on recent volatility characteristics.
### Session Tracking & Statistics
The indicator monitors four distinct trading sessions (times in Eastern Time):
1. **Asia Session** (8:00 PM - 2:00 AM)
2. **London Session** (2:00 AM - 8:00 AM)
3. **NY Open** (8:00 AM - 9:00 AM)
4. **NY Initial Balance** (9:30 AM - 10:30 AM)
For each session, the indicator:
- Draws a colored box showing the session's high-to-low range
- Tracks the opening price, high, and low
- Stores historical data for statistical analysis
- Calculates average ranges by day of week (Monday through Friday)
The session statistics are displayed in a customizable table showing average point ranges for each session across different weekdays, helping traders identify which sessions and days typically produce the most movement.
### Dynamic Probability System
The indicator analyzes the relationship between the Asia and London sessions to determine the current market setup. After the London session closes, it automatically detects one of four possible conditions:
**1. London Engulfs Asia**
- London session breaks both above Asia's high AND below Asia's low
- This indicates strong momentum during the European session
- Most common occurrence pattern
**2. Asia Engulfs London**
- Asia session range completely contains the London session range
- Indicates consolidation during London hours
- Relatively rare pattern (occurs approximately 5.36% of the time)
**3. London Partially Engulfs Upwards**
- London breaks above Asia's high but stays above Asia's low
- Suggests bullish momentum continuation from Asia into London
**4. London Partially Engulfs Downwards**
- London breaks below Asia's low but stays below Asia's high
- Suggests bearish momentum continuation from Asia into London
Once a condition is detected, the indicator displays a probability table showing historically observed outcomes for that specific setup, including:
- Probability of NY session taking out key levels (Asia high/low, London high/low)
- Probability of NY session engulfing the entire overnight range
- Directional bias for NY Cash session (9:30 AM - 4:00 PM)
## How to Use This Indicator
### Initial Setup
1. Add the indicator to your chart (works on any intraday timeframe below Daily)
2. Adjust the **ADR Days** setting (default: 10) to control the lookback period for range calculation
3. Adjust the **Session Lookback Days** setting (default: 50) to determine how much historical data feeds the statistics tables
### Reading the ADR Levels
- Use the **ADR High** and **ADR Low** lines as potential profit targets or areas where price may encounter resistance
- The **ADR Median** line represents the opening price and can act as a pivot point for intraday directional bias
- If price reaches the ADR High early in the session, it suggests strong bullish momentum; conversely for ADR Low
- These levels adapt daily based on recent volatility, making them more responsive than static levels
### Interpreting Session Boxes
- **Session boxes** visually highlight when each trading session is active and its price range
- Larger boxes indicate higher volatility during that session
- Compare current session ranges to the statistical averages shown in the table
- Sessions that are unusually quiet or active relative to historical averages may signal compression or expansion
### Using the Session Statistics Table
- The table shows average point ranges for each session broken down by weekday
- Identify which sessions typically produce the most movement on specific days
- For example, if London on Thursdays averages 40 points while Mondays average 25 points, you can adjust position sizing or expectations accordingly
- The **Total** column shows the overall average across all days
- Sample sizes (shown in brackets if enabled) indicate data reliability
### Trading with the Probability Table
The probability table updates dynamically after the London session closes and shows statistically probable outcomes based on 12 years of NQ futures data.
**Important Limitations:**
- **These probabilities are derived from NQ (Nasdaq E-mini futures) data only**
- **Do NOT apply these probability statistics to other instruments** (ES, stocks, forex, etc.)
- The probabilities represent historical frequencies, not guarantees
- Always combine with your own analysis, risk management, and market context
**How to Apply the Probabilities:**
When **London Engulfs Asia**:
- Watch for NY session to take out London's extremes (72.33% probability for high, 71.12% for low)
- Slight bullish bias in NY Cash session (54.80% vs 45.20%)
- Lower probability of complete overnight engulfment (44.13%)
When **Asia Engulfs London** (rare - 5.36% occurrence):
- Higher probability NY takes Asia's high (75.86%)
- Moderately high probability NY takes Asia's low (65.52%)
- Slight increase in bullish bias (58.42% vs 41.58%)
- Recognize this as an unusual setup
When **London Partially Engulfs Upwards**:
- Very high probability NY takes London high (81.51%)
- Strong probability NY takes London low (64.45%)
- Moderate probability NY takes Asian low (53.16%)
- Slight bullish bias (55.52%)
When **London Partially Engulfs Downwards**:
- Very high probability NY takes London low (75.29%)
- Strong probability NY takes London high (68.80%)
- Moderate probability NY takes Asian high (56.44%)
- Slight bullish bias maintained (52.99%)
### Practical Trading Applications
**Scenario 1: Range Projection**
If the ADR is 500 points and the market opens at 25,000:
- ADR High: 25,500 (potential resistance/target)
- ADR Low: 24,500 (potential support/target)
- Monitor how price interacts with these levels throughout the day
**Scenario 2: Session-Based Trading**
Using the statistics table, you notice London on Wednesdays averages 35 points. During a Wednesday London session:
- If London has already moved 30 points, the session may be exhausting its typical range
- If London has only moved 15 points with an hour remaining, there may be expansion potential
- Adjust stop losses and targets based on typical session behavior
**Scenario 3: Probability-Based Setup**
It's 8:05 AM ET and the indicator shows "London Partially Engulfs Upwards":
- You now know there's an 81.51% historical probability NY will take out London's high
- There's a 53.16% probability NY will reach down to Asia's low
- The NY Cash session has a slight bullish bias (55.52%)
- Consider this alongside your technical analysis for directional bias and level targeting
## Customization Options
### Visual Settings
- **Line Width**: Adjust thickness of ADR levels
- **ADR Color/Style**: Customize appearance of ADR projection lines (solid, dashed, dotted)
- **Median Line**: Toggle visibility and customize appearance separately
- **Session Box Colors**: Customize each session's box color independently
- **Show Session Boxes**: Toggle session box visibility on/off
### Label Settings
- **ADR Labels**: Show/hide labels for ADR High and ADR Low, adjust size
- **Median Label**: Separate control for median line label
- **Session Labels**: Show/hide session name labels, adjust size
- **Label Colors**: Customize text colors for all labels
### Table Settings
- **Session Stats Table**: Position (9 locations available), size (Tiny to Huge), toggle on/off
- **Sample Sizes**: Show/hide the number of historical samples used for each calculation
- **Probabilities Table**: Separate position and size controls, toggle on/off
### Session Times
- Each session's time range can be customized to fit different markets or preferences
- All times are in Eastern Time (America/New_York timezone)
## Technical Notes
### Data Requirements
- The indicator requires sufficient historical data based on your lookback settings
- Minimum recommended: 50+ days of intraday data for reliable statistics
- Works on any timeframe below Daily (1-minute, 5-minute, 15-minute, etc.)
### Calculation Methodology
- **ADR Calculation**: Simple average of absolute daily high-low ranges
- **Session Statistics**: Mean average of ranges for each session filtered by day of week
- **Condition Detection**: Boolean logic comparing session high/low relationships
- All calculations update in real-time as new bars form
### Probability Data Source
The probability statistics displayed in the dynamic table are derived from:
- **Dataset**: 12 years of NQ (Nasdaq E-mini futures) historical data
- **Methodology**: Frequency analysis of outcomes following specific setup conditions
- **Time Period**: Multiple market cycles including various volatility regimes
**Critical Warning**: These probabilities are specific to NQ and reflect that instrument's behavior patterns. Market microstructure, participant behavior, and volatility characteristics differ significantly across instruments. Do not apply these NQ-derived probabilities to other markets (ES, RTY, YM, individual stocks, forex, commodities, etc.).
## Best Practices
1. **Combine with Other Analysis**: Use this indicator as one component of a complete trading methodology, not a standalone system
2. **Respect Risk Management**: Probabilities are not certainties; always use proper position sizing and stop losses
3. **Context Matters**: High-impact news events, holiday trading, and extreme volatility can invalidate typical patterns
4. **Verify Statistics**: Monitor your own results and compare to the displayed probabilities
5. **Adapt Session Times**: If trading instruments with different active hours, adjust session times accordingly
6. **Regular Calibration**: Periodically review if the session averages and probabilities remain relevant to current market conditions
## Understanding Originality
This indicator is original in its approach to combining three analytical frameworks into a single tool:
1. **Dynamic ADR Projection**: Unlike static pivot points, these levels adapt daily based on recent volatility
2. **Session-Specific Statistics**: Goes beyond simple volume profiles by quantifying average ranges for specific time windows across weekdays
3. **Conditional Probability Display**: Automatically detects overnight session relationships and displays relevant probability data rather than showing all scenarios simultaneously
The conditional logic system that determines which probability set to display is a key differentiator—traders only see the statistics relevant to the current market setup, reducing information overload and improving decision-making clarity.
## Summary
The **Statistical Daily Profile & Ranges** indicator provides traders with a comprehensive framework for understanding daily range potential, session-specific behavior patterns, and probability-based setup analysis. By combining ADR projection levels with detailed session statistics and dynamic probability displays, traders gain multiple perspectives on potential price movement within the trading day.
The indicator is most effective when used to:
- Set realistic profit targets based on average daily range
- Identify which sessions typically produce movement on specific weekdays
- Understand probability-weighted outcomes for different overnight setup conditions (NQ only)
- Visualize session ranges and compare them to historical averages
Remember that all statistical analysis reflects historical patterns, and market behavior can change. Always combine indicator signals with sound risk management, proper position sizing, and your own market analysis.
Session Sweep System – WarRoomXYZ V1WarRoom Session Sweep System v1 is a open-source institutional trading framework built to identify liquidity behavior across Asia, London, and New York sessions.
It combines session-based liquidity mapping, sweep detection, daily expansion modeling, and trend confirmation into a unified, timing-driven system optimized for XAUUSD, FX pairs, indices, and any instrument with session-dependent volatility.
This tool does not attempt to predict direction with arbitrary oscillators.
Instead, it focuses on the underlying market mechanisms that drive price:
liquidity, timing, expansion, and trend alignment.
Below is a detailed explanation of what the script does, how its components work, and how traders can use it effectively.
🔹 1. Session Liquidity Mapping
The script automatically identifies the Asia (00:00–06:00 GMT), London (07:00–12:00 GMT), and New York (13:00–17:00 GMT) sessions and builds real-time session ranges.
Each session creates a liquidity pool.
Trading institutions frequently sweep the high or low of one session before delivering the real move in the next session.
This script captures that behavior by:
►Drawing session range boxes
►Tracking previous session highs/lows
►Highlighting high-probability sweep locations
These ranges are essential reference points for timing entries and exits.
🔹 2. Liquidity Sweep Detection (Buy & Sell Sweeps)
The indicator identifies when price runs a previous session high/low and rejects back inside the range, which is commonly interpreted as a liquidity sweep.
The following sweep types are monitored:
►London sweeping Asia
►New York sweeping London
►Asia sweeping New York
►Daily sweep of PDH/PDL
Sweeps signal that liquidity has been collected and that a potential reversal or continuation is likely.
These are marked clearly on the chart for real-time decision-making.
🔹 3. Killzone Timing Model (GMT Time)
Market manipulation and expansion often occur during specific time windows.
The script highlights these institutional killzones:
►London Killzone: 07:00–10:00 GMT
►New York Killzone: 13:30–15:30 GMT
►NY PM Session: 19:00–21:00 GMT
Sweeps occurring inside these windows carry a significantly higher probability.
The timing layer helps filter out low-quality setups.
🔹 4. Daily Range & ADR Expansion Engine
A dedicated panel displays:
►Current day range
►ADR (Average Daily Range)
►Expansion stage (Early / Developed / Extended)
►PDH/PDL swept or intact
►Overall session bias
This allows traders to understand whether the daily move is likely to continue or reverse.
For example:
►Early expansion → trend continuation likely
►Extended expansion → reversal setups become more probable
This is useful for intraday targets and risk management.
🔹 5. MA Cloud Trend Model (Fast/Slow Structure)
To align liquidity behavior with directional conviction, the script includes a configurable MA engine:
►Fast & slow MA
►MA cloud
►Slope-based trend coloring
►Trend background
►MA cross alerts
The cloud provides trend confirmation without relying on oscillators.
Trades are higher quality when the sweep direction aligns with the MA trend.
🔹 6. How the Components Work Together
The script integrates several institutional concepts into one coherent model:
►Sessions define liquidity pools
►Sweeps identify stop-hunts and reversals
►Killzones define optimal timing
►MA Cloud confirms directional bias
►ADR engine indicates expansion potential
This creates a structured framework:
Sweep → Timing → Trend → Expansion → Execution
Each component strengthens the others, forming a robust decision-making model.
🔹 7. How to Use the Indicator (Practical Guide)
✔ Look for a sweep of a previous session level
When price runs a session high/low and closes back inside, liquidity has likely been collected.
✔ Confirm timing
Sweeps inside London or NY killzones tend to produce the strongest moves.
✔ Confirm trend
Use MA cloud direction and slope:
►Cloud green → long setups preferred
►Cloud red → short setups preferred
✔ Check ADR panel
If the day has already expanded significantly, reversal setups are more likely.
If expansion is still early, continuation setups are favored.
✔ Plan your trade
Common targets include:
►Opposite side of session range
►ADR High/Low
►PDH/PDL
Stops are typically placed beyond the sweep wick.
This creates a repeatable, rule-based approach to intraday liquidity trading.
🔹 8. Why This Script Is Original
This is not a mashup of existing open-source indicators.
It introduces:
►A custom session-linked liquidity sweep engine
►A structured daily expansion model
►Integrated killzone timing aligned with GMT
►A unified bias panel merging sweeps, ADR, and session manipulation
►A trend confirmation layer designed around session behavior
While it uses known institutional concepts, their integration, execution, and timing framework are unique, purpose-built, and not directly found in open-source scripts.
🔹 9. Suitable Markets
This indicator works best on:
►XAUUSD
►Major FX pairs
►US indices
►Synthetic markets with session cycles
Ideal timeframes: 1m, 5m, 15m, 30m
🔹 10. Limitations / Notes
This is an analytical tool, not a buy/sell signal generator
All sweeps are confirmed at candle close (non-repaint)
The tool assumes GMT session windows unless chart time differs
Users must practice risk management and entry triggers manually
Disclaimer
This script is provided for informational and educational purposes only. It does not provide financial, investment, or trading advice, and it does not guarantee profits or future performance. All decisions made based on this script are solely the responsibility of the user.
This script does not execute trades, manage risk, or replace the need for trader discretion. Market behavior can change quickly, and past behavior detected by the script does not ensure similar future outcomes.
Users should test the script on demo or simulation environments before applying it to live markets and must maintain full responsibility for their own risk management, position sizing, and trade execution.
Trading involves risk, and losses can exceed deposits. By using this script, you acknowledge that you understand and accept all associated risks.
FX OSINT - Institutional Midnight Intelligence For ForexFX OSINT — Institutional Midnight Intelligence For Forex
See Your FX Charts Like an Intelligence Briefing, Not a Guess
If you’ve ever stared at EURUSD or GBPJPY and thought:
Where is the real liquidity?
Is this move sponsored by smart money or just noise?
Am I buying into premium or discount?
…then FX OSINT is designed for you.
FX OSINT (Forex Open Source Intelligence) treats the FX market the way an analyst treats an investigation:
Collect open‑source signals from price, time, and volatility.
Map out liquidity, structure, and sessions in a repeatable way.
Present them in a clean, non‑cluttered dashboard so you can read context quickly.
No rainbow spaghetti. No 12 indicators stacked on top of each other. Just structured information, midnight visuals, and a clear read on what the market is doing right now.
Why FX OSINT Exists
Many FX traders run into the same problems:
Overloaded charts – multiple indicators fighting for space, none talking to each other.
Signals with no context – arrows that ignore structure, sessions, and liquidity.
Tools not tuned for FX – generic indicators that don’t care what pair you are on.
FX OSINT brings this together into one FX‑focused framework that:
Understands structure : BOS/CHOCH, swings, and trend across multiple timeframes.
Respects liquidity : sweeps, order blocks, and FVGs with controlled visibility.
Reads volatility & ADR : how far today’s range has developed.
Knows the clock : London, New York, and key killzones.
Scores confluence : a 0–100 engine that summarizes how much is lining up.
FX OSINT is built for traders who want structured, institutional‑style logic with a disciplined, midnight‑themed UI —not flashing buy/sell buttons.
1. Midnight Dashboard — Top‑Right Intelligence Panel
This panel acts as your compact “situation room”:
CONFLUENCE — 0–100 score blending trend alignment, volatility regime, sessions, liquidity events, order blocks, FVGs, and ADR context.
REGIME — Low / Building / Normal / Expansion / Extreme, driven by ATR relationships, so you know if you’re in chop, trend, or expansion.
HTF / MTF / LTF TREND — Higher‑, medium‑, and current‑timeframe bias in one place, so you see if you are trading with or against the larger flow.
ADR USED — How much of today’s typical range has already been consumed in percentage terms.
PIP VALUE — Approximate pip size per pair, including JPY‑style pairs.
Everything is bold, legible, and color‑coded, but the layout stays minimal so you can:
Look once → understand the context.
2. Structure, BOS, CHOCH — Smart‑Money‑Style Skeleton
FX OSINT tracks swing highs and lows, then shows how structure evolves:
Trend logic based on evolving swings, not just a moving average cross.
BOS (Break of Structure) when price expands in the direction of trend.
CHOCH (Change of Character) when behavior flips and the market structure changes.
Labels are selective, not spammy . You don’t get a tag on every minor wiggle—only when structure meaningfully shifts, so it’s easier to answer:
"Are we continuing the current leg, or did something actually change here?"
3. Liquidity Sweeps, Order Blocks & FVGs — The OSINT Layer
FX OSINT treats liquidity as a key information layer:
Liquidity sweeps — Detects when price spikes through recent highs/lows and then snaps back, flagging potential stop runs.
Order blocks — The last opposite candle before a displacement move, drawn as controlled boxes with limited lifespan to avoid clutter.
Fair Value Gaps (FVGs) — Three‑candle imbalances rendered as precise zones with a cap on how many can exist at once.
Under the hood, boxes are managed so your chart does not become a wall of old zones:
// Draw Order Blocks with overlap prevention
if isBullishOB and showOrderBlocks
if array.size(obBoxes) >= maxBoxes
oldBox = array.shift(obBoxes)
box.delete(oldBox)
newBox = box.new(bar_index , low , bar_index + obvLength, high ,
border_color = bullColor, bgcolor = bullColorTransp,
border_width = 2, extend = extend.none)
array.push(obBoxes, newBox)
Box limits keep the number of zones under control.
Borders and transparency are tuned so you still see price clearly.
You end up with a curated liquidity map , rather than a chart buried under every level price has ever touched.
4. Volatility, ADR & Sessions — Time and Range Intelligence
FX OSINT runs a Volatility Regime Analyzer and an ADR engine in the background:
Volatility regime — Five states (Low → Extreme) derived from fast vs. slow ATR.
ADR bands — Daily high/mid/low projected from the current daily open.
ADR used % — How far today’s move has traveled relative to its typical range.
On the time side:
Asia, London, New York sessions are softly highlighted with a single active background to avoid overlapping colors.
Killzones (e.g., London and New York opens) can be emphasized when you want to focus on where significant moves often begin.
Together, this helps you answer:
"What time is it in the trading day?"
"How stretched are we?"
"Is expansion just starting, or are we late to the move?"
5. ICT‑Style Add‑Ons — BOS/CHOCH, Premium/Discount, and Confluence
For modern FX / ICT‑inspired workflows, FX OSINT includes:
BOS / CHOCH labels — Clear structural shifts based on swings.
Premium / Discount zones — 25%, 50%, 75% levels of the daily range, so you know if you are buying discount in an uptrend or selling premium in a downtrend.
Confluence score — A single number summarizing how many conditions line up in the current context.
Instead of replacing your plan, FX OSINT compresses your checklist into the chart:
Structure
Liquidity
Session / Time
Volatility / ADR
Higher‑timeframe alignment
When these agree, the dashboard reflects it. When they don’t, it stays neutral and lets you see the conflict.
How To Use FX OSINT
FX OSINT is not a signal bot. It is an information engine that organizes context so you can apply your own plan.
A typical workflow might look like:
Start on higher timeframes (e.g., H4/D1) to form directional bias from structure, volatility regime, and ADR context.
Move to intraday timeframes (e.g., M15/H1) around your chosen sessions (London and/or New York).
Look for confluence :
HTF / MTF / LTF trends aligned.
Price in discount for longs or premium for shorts.
Recent liquidity sweep into a meaningful OB or FVG.
Confluence score at or above a level you consider significant.
Then refine entries using BOS/CHOCH on lower timeframes according to your own risk and execution rules.
FX OSINT aims to make sure you do not enter a trade without seeing:
Where you are in the day (ADR and sessions).
Where you are in the volatility cycle (regime).
Who currently appears in control (structure and trend).
Which liquidity was just targeted (sweeps and zones).
Design Choices and Scope
FX OSINT was designed around a few clear constraints:
FX‑focused — Logic and filters tuned for FX majors, minors, exotics, and metals. It is intended for FX markets, not for every possible asset class.
Open‑source — The full Pine Script code is available so you can read it, learn from it, and adapt it to your own workflow if needed.
Clear themes — Two main visual styles (e.g., dark institutional “midnight” and a lighter accent variant) with a focus on readability, not visual noise.
Chart‑friendly — Panels use fixed areas, session highlights avoid overlapping, and boxes are capped/pruned so the chart remains usable.
FX OSINT is for only Forex pairs, not anything else!
Hope you enjoyed and remember your Open Source Intelligence Matters 😉!
-officialjackofalltrades
Dimensional Resonance ProtocolDimensional Resonance Protocol
🌀 CORE INNOVATION: PHASE SPACE RECONSTRUCTION & EMERGENCE DETECTION
The Dimensional Resonance Protocol represents a paradigm shift from traditional technical analysis to complexity science. Rather than measuring price levels or indicator crossovers, DRP reconstructs the hidden attractor governing market dynamics using Takens' embedding theorem, then detects emergence —the rare moments when multiple dimensions of market behavior spontaneously synchronize into coherent, predictable states.
The Complexity Hypothesis:
Markets are not simple oscillators or random walks—they are complex adaptive systems existing in high-dimensional phase space. Traditional indicators see only shadows (one-dimensional projections) of this higher-dimensional reality. DRP reconstructs the full phase space using time-delay embedding, revealing the true structure of market dynamics.
Takens' Embedding Theorem (1981):
A profound mathematical result from dynamical systems theory: Given a time series from a complex system, we can reconstruct its full phase space by creating delayed copies of the observation.
Mathematical Foundation:
From single observable x(t), create embedding vectors:
X(t) =
Where:
• d = Embedding dimension (default 5)
• τ = Time delay (default 3 bars)
• x(t) = Price or return at time t
Key Insight: If d ≥ 2D+1 (where D is the true attractor dimension), this embedding is topologically equivalent to the actual system dynamics. We've reconstructed the hidden attractor from a single price series.
Why This Matters:
Markets appear random in one dimension (price chart). But in reconstructed phase space, structure emerges—attractors, limit cycles, strange attractors. When we identify these structures, we can detect:
• Stable regions : Predictable behavior (trade opportunities)
• Chaotic regions : Unpredictable behavior (avoid trading)
• Critical transitions : Phase changes between regimes
Phase Space Magnitude Calculation:
phase_magnitude = sqrt(Σ ² for i = 0 to d-1)
This measures the "energy" or "momentum" of the market trajectory through phase space. High magnitude = strong directional move. Low magnitude = consolidation.
📊 RECURRENCE QUANTIFICATION ANALYSIS (RQA)
Once phase space is reconstructed, we analyze its recurrence structure —when does the system return near previous states?
Recurrence Plot Foundation:
A recurrence occurs when two phase space points are closer than threshold ε:
R(i,j) = 1 if ||X(i) - X(j)|| < ε, else 0
This creates a binary matrix showing when the system revisits similar states.
Key RQA Metrics:
1. Recurrence Rate (RR):
RR = (Number of recurrent points) / (Total possible pairs)
• RR near 0: System never repeats (highly stochastic)
• RR = 0.1-0.3: Moderate recurrence (tradeable patterns)
• RR > 0.5: System stuck in attractor (ranging market)
• RR near 1: System frozen (no dynamics)
Interpretation: Moderate recurrence is optimal —patterns exist but market isn't stuck.
2. Determinism (DET):
Measures what fraction of recurrences form diagonal structures in the recurrence plot. Diagonals indicate deterministic evolution (trajectory follows predictable paths).
DET = (Recurrence points on diagonals) / (Total recurrence points)
• DET < 0.3: Random dynamics
• DET = 0.3-0.7: Moderate determinism (patterns with noise)
• DET > 0.7: Strong determinism (technical patterns reliable)
Trading Implication: Signals are prioritized when DET > 0.3 (deterministic state) and RR is moderate (not stuck).
Threshold Selection (ε):
Default ε = 0.10 × std_dev means two states are "recurrent" if within 10% of a standard deviation. This is tight enough to require genuine similarity but loose enough to find patterns.
🔬 PERMUTATION ENTROPY: COMPLEXITY MEASUREMENT
Permutation entropy measures the complexity of a time series by analyzing the distribution of ordinal patterns.
Algorithm (Bandt & Pompe, 2002):
1. Take overlapping windows of length n (default n=4)
2. For each window, record the rank order pattern
Example: → pattern (ranks from lowest to highest)
3. Count frequency of each possible pattern
4. Calculate Shannon entropy of pattern distribution
Mathematical Formula:
H_perm = -Σ p(π) · ln(p(π))
Where π ranges over all n! possible permutations, p(π) is the probability of pattern π.
Normalized to :
H_norm = H_perm / ln(n!)
Interpretation:
• H < 0.3 : Very ordered, crystalline structure (strong trending)
• H = 0.3-0.5 : Ordered regime (tradeable with patterns)
• H = 0.5-0.7 : Moderate complexity (mixed conditions)
• H = 0.7-0.85 : Complex dynamics (challenging to trade)
• H > 0.85 : Maximum entropy (nearly random, avoid)
Entropy Regime Classification:
DRP classifies markets into five entropy regimes:
• CRYSTALLINE (H < 0.3): Maximum order, persistent trends
• ORDERED (H < 0.5): Clear patterns, momentum strategies work
• MODERATE (H < 0.7): Mixed dynamics, adaptive required
• COMPLEX (H < 0.85): High entropy, mean reversion better
• CHAOTIC (H ≥ 0.85): Near-random, minimize trading
Why Permutation Entropy?
Unlike traditional entropy methods requiring binning continuous data (losing information), permutation entropy:
• Works directly on time series
• Robust to monotonic transformations
• Computationally efficient
• Captures temporal structure, not just distribution
• Immune to outliers (uses ranks, not values)
⚡ LYAPUNOV EXPONENT: CHAOS vs STABILITY
The Lyapunov exponent λ measures sensitivity to initial conditions —the hallmark of chaos.
Physical Meaning:
Two trajectories starting infinitely close will diverge at exponential rate e^(λt):
Distance(t) ≈ Distance(0) × e^(λt)
Interpretation:
• λ > 0 : Positive Lyapunov exponent = CHAOS
- Small errors grow exponentially
- Long-term prediction impossible
- System is sensitive, unpredictable
- AVOID TRADING
• λ ≈ 0 : Near-zero = CRITICAL STATE
- Edge of chaos
- Transition zone between order and disorder
- Moderate predictability
- PROCEED WITH CAUTION
• λ < 0 : Negative Lyapunov exponent = STABLE
- Small errors decay
- Trajectories converge
- System is predictable
- OPTIMAL FOR TRADING
Estimation Method:
DRP estimates λ by tracking how quickly nearby states diverge over a rolling window (default 20 bars):
For each bar i in window:
δ₀ = |x - x | (initial separation)
δ₁ = |x - x | (previous separation)
if δ₁ > 0:
ratio = δ₀ / δ₁
log_ratios += ln(ratio)
λ ≈ average(log_ratios)
Stability Classification:
• STABLE : λ < 0 (negative growth rate)
• CRITICAL : |λ| < 0.1 (near neutral)
• CHAOTIC : λ > 0.2 (strong positive growth)
Signal Filtering:
By default, NEXUS requires λ < 0 (stable regime) for signal confirmation. This filters out trades during chaotic periods when technical patterns break down.
📐 HIGUCHI FRACTAL DIMENSION
Fractal dimension measures self-similarity and complexity of the price trajectory.
Theoretical Background:
A curve's fractal dimension D ranges from 1 (smooth line) to 2 (space-filling curve):
• D ≈ 1.0 : Smooth, persistent trending
• D ≈ 1.5 : Random walk (Brownian motion)
• D ≈ 2.0 : Highly irregular, space-filling
Higuchi Method (1988):
For a time series of length N, construct k different curves by taking every k-th point:
L(k) = (1/k) × Σ|x - x | × (N-1)/(⌊(N-m)/k⌋ × k)
For different values of k (1 to k_max), calculate L(k). The fractal dimension is the slope of log(L(k)) vs log(1/k):
D = slope of log(L) vs log(1/k)
Market Interpretation:
• D < 1.35 : Strong trending, persistent (Hurst > 0.5)
- TRENDING regime
- Momentum strategies favored
- Breakouts likely to continue
• D = 1.35-1.45 : Moderate persistence
- PERSISTENT regime
- Trend-following with caution
- Patterns have meaning
• D = 1.45-1.55 : Random walk territory
- RANDOM regime
- Efficiency hypothesis holds
- Technical analysis least reliable
• D = 1.55-1.65 : Anti-persistent (mean-reverting)
- ANTI-PERSISTENT regime
- Oscillator strategies work
- Overbought/oversold meaningful
• D > 1.65 : Highly complex, choppy
- COMPLEX regime
- Avoid directional bets
- Wait for regime change
Signal Filtering:
Resonance signals (secondary signal type) require D < 1.5, indicating trending or persistent dynamics where momentum has meaning.
🔗 TRANSFER ENTROPY: CAUSAL INFORMATION FLOW
Transfer entropy measures directed causal influence between time series—not just correlation, but actual information transfer.
Schreiber's Definition (2000):
Transfer entropy from X to Y measures how much knowing X's past reduces uncertainty about Y's future:
TE(X→Y) = H(Y_future | Y_past) - H(Y_future | Y_past, X_past)
Where H is Shannon entropy.
Key Properties:
1. Directional : TE(X→Y) ≠ TE(Y→X) in general
2. Non-linear : Detects complex causal relationships
3. Model-free : No assumptions about functional form
4. Lag-independent : Captures delayed causal effects
Three Causal Flows Measured:
1. Volume → Price (TE_V→P):
Measures how much volume patterns predict price changes.
• TE > 0 : Volume provides predictive information about price
- Institutional participation driving moves
- Volume confirms direction
- High reliability
• TE ≈ 0 : No causal flow (weak volume/price relationship)
- Volume uninformative
- Caution on signals
• TE < 0 (rare): Suggests price leading volume
- Potentially manipulated or thin market
2. Volatility → Momentum (TE_σ→M):
Does volatility expansion predict momentum changes?
• Positive TE : Volatility precedes momentum shifts
- Breakout dynamics
- Regime transitions
3. Structure → Price (TE_S→P):
Do support/resistance patterns causally influence price?
• Positive TE : Structural levels have causal impact
- Technical levels matter
- Market respects structure
Net Causal Flow:
Net_Flow = TE_V→P + 0.5·TE_σ→M + TE_S→P
• Net > +0.1 : Bullish causal structure
• Net < -0.1 : Bearish causal structure
• |Net| < 0.1 : Neutral/unclear causation
Causal Gate:
For signal confirmation, NEXUS requires:
• Buy signals : TE_V→P > 0 AND Net_Flow > 0.05
• Sell signals : TE_V→P > 0 AND Net_Flow < -0.05
This ensures volume is actually driving price (causal support exists), not just correlated noise.
Implementation Note:
Computing true transfer entropy requires discretizing continuous data into bins (default 6 bins) and estimating joint probability distributions. NEXUS uses a hybrid approach combining TE theory with autocorrelation structure and lagged cross-correlation to approximate information transfer in computationally efficient manner.
🌊 HILBERT PHASE COHERENCE
Phase coherence measures synchronization across market dimensions using Hilbert transform analysis.
Hilbert Transform Theory:
For a signal x(t), the Hilbert transform H (t) creates an analytic signal:
z(t) = x(t) + i·H (t) = A(t)·e^(iφ(t))
Where:
• A(t) = Instantaneous amplitude
• φ(t) = Instantaneous phase
Instantaneous Phase:
φ(t) = arctan(H (t) / x(t))
The phase represents where the signal is in its natural cycle—analogous to position on a unit circle.
Four Dimensions Analyzed:
1. Momentum Phase : Phase of price rate-of-change
2. Volume Phase : Phase of volume intensity
3. Volatility Phase : Phase of ATR cycles
4. Structure Phase : Phase of position within range
Phase Locking Value (PLV):
For two signals with phases φ₁(t) and φ₂(t), PLV measures phase synchronization:
PLV = |⟨e^(i(φ₁(t) - φ₂(t)))⟩|
Where ⟨·⟩ is time average over window.
Interpretation:
• PLV = 0 : Completely random phase relationship (no synchronization)
• PLV = 0.5 : Moderate phase locking
• PLV = 1 : Perfect synchronization (phases locked)
Pairwise PLV Calculations:
• PLV_momentum-volume : Are momentum and volume cycles synchronized?
• PLV_momentum-structure : Are momentum cycles aligned with structure?
• PLV_volume-structure : Are volume and structural patterns in phase?
Overall Phase Coherence:
Coherence = (PLV_mom-vol + PLV_mom-struct + PLV_vol-struct) / 3
Signal Confirmation:
Emergence signals require coherence ≥ threshold (default 0.70):
• Below 0.70: Dimensions not synchronized, no coherent market state
• Above 0.70: Dimensions in phase, coherent behavior emerging
Coherence Direction:
The summed phase angles indicate whether synchronized dimensions point bullish or bearish:
Direction = sin(φ_momentum) + 0.5·sin(φ_volume) + 0.5·sin(φ_structure)
• Direction > 0 : Phases pointing upward (bullish synchronization)
• Direction < 0 : Phases pointing downward (bearish synchronization)
🌀 EMERGENCE SCORE: MULTI-DIMENSIONAL ALIGNMENT
The emergence score aggregates all complexity metrics into a single 0-1 value representing market coherence.
Eight Components with Weights:
1. Phase Coherence (20%):
Direct contribution: coherence × 0.20
Measures dimensional synchronization.
2. Entropy Regime (15%):
Contribution: (0.6 - H_perm) / 0.6 × 0.15 if H < 0.6, else 0
Rewards low entropy (ordered, predictable states).
3. Lyapunov Stability (12%):
• λ < 0 (stable): +0.12
• |λ| < 0.1 (critical): +0.08
• λ > 0.2 (chaotic): +0.0
Requires stable, predictable dynamics.
4. Fractal Dimension Trending (12%):
Contribution: (1.45 - D) / 0.45 × 0.12 if D < 1.45, else 0
Rewards trending fractal structure (D < 1.45).
5. Dimensional Resonance (12%):
Contribution: |dimensional_resonance| × 0.12
Measures alignment across momentum, volume, structure, volatility dimensions.
6. Causal Flow Strength (9%):
Contribution: |net_causal_flow| × 0.09
Rewards strong causal relationships.
7. Phase Space Embedding (10%):
Contribution: min(|phase_magnitude_norm|, 3.0) / 3.0 × 0.10 if |magnitude| > 1.0
Rewards strong trajectory in reconstructed phase space.
8. Recurrence Quality (10%):
Contribution: determinism × 0.10 if DET > 0.3 AND 0.1 < RR < 0.8
Rewards deterministic patterns with moderate recurrence.
Total Emergence Score:
E = Σ(components) ∈
Capped at 1.0 maximum.
Emergence Direction:
Separate calculation determining bullish vs bearish:
• Dimensional resonance sign
• Net causal flow sign
• Phase magnitude correlation with momentum
Signal Threshold:
Default emergence_threshold = 0.75 means 75% of maximum possible emergence score required to trigger signals.
Why Emergence Matters:
Traditional indicators measure single dimensions. Emergence detects self-organization —when multiple independent dimensions spontaneously align. This is the market equivalent of a phase transition in physics, where microscopic chaos gives way to macroscopic order.
These are the highest-probability trade opportunities because the entire system is resonating in the same direction.
🎯 SIGNAL GENERATION: EMERGENCE vs RESONANCE
DRP generates two tiers of signals with different requirements:
TIER 1: EMERGENCE SIGNALS (Primary)
Requirements:
1. Emergence score ≥ threshold (default 0.75)
2. Phase coherence ≥ threshold (default 0.70)
3. Emergence direction > 0.2 (bullish) or < -0.2 (bearish)
4. Causal gate passed (if enabled): TE_V→P > 0 and net_flow confirms direction
5. Stability zone (if enabled): λ < 0 or |λ| < 0.1
6. Price confirmation: Close > open (bulls) or close < open (bears)
7. Cooldown satisfied: bars_since_signal ≥ cooldown_period
EMERGENCE BUY:
• All above conditions met with bullish direction
• Market has achieved coherent bullish state
• Multiple dimensions synchronized upward
EMERGENCE SELL:
• All above conditions met with bearish direction
• Market has achieved coherent bearish state
• Multiple dimensions synchronized downward
Premium Emergence:
When signal_quality (emergence_score × phase_coherence) > 0.7:
• Displayed as ★ star symbol
• Highest conviction trades
• Maximum dimensional alignment
Standard Emergence:
When signal_quality 0.5-0.7:
• Displayed as ◆ diamond symbol
• Strong signals but not perfect alignment
TIER 2: RESONANCE SIGNALS (Secondary)
Requirements:
1. Dimensional resonance > +0.6 (bullish) or < -0.6 (bearish)
2. Fractal dimension < 1.5 (trending/persistent regime)
3. Price confirmation matches direction
4. NOT in chaotic regime (λ < 0.2)
5. Cooldown satisfied
6. NO emergence signal firing (resonance is fallback)
RESONANCE BUY:
• Dimensional alignment without full emergence
• Trending fractal structure
• Moderate conviction
RESONANCE SELL:
• Dimensional alignment without full emergence
• Bearish resonance with trending structure
• Moderate conviction
Displayed as small ▲/▼ triangles with transparency.
Signal Hierarchy:
IF emergence conditions met:
Fire EMERGENCE signal (★ or ◆)
ELSE IF resonance conditions met:
Fire RESONANCE signal (▲ or ▼)
ELSE:
No signal
Cooldown System:
After any signal fires, cooldown_period (default 5 bars) must elapse before next signal. This prevents signal clustering during persistent conditions.
Cooldown tracks using bar_index:
bars_since_signal = current_bar_index - last_signal_bar_index
cooldown_ok = bars_since_signal >= cooldown_period
🎨 VISUAL SYSTEM: MULTI-LAYER COMPLEXITY
DRP provides rich visual feedback across four distinct layers:
LAYER 1: COHERENCE FIELD (Background)
Colored background intensity based on phase coherence:
• No background : Coherence < 0.5 (incoherent state)
• Faint glow : Coherence 0.5-0.7 (building coherence)
• Stronger glow : Coherence > 0.7 (coherent state)
Color:
• Cyan/teal: Bullish coherence (direction > 0)
• Red/magenta: Bearish coherence (direction < 0)
• Blue: Neutral coherence (direction ≈ 0)
Transparency: 98 minus (coherence_intensity × 10), so higher coherence = more visible.
LAYER 2: STABILITY/CHAOS ZONES
Background color indicating Lyapunov regime:
• Green tint (95% transparent): λ < 0, STABLE zone
- Safe to trade
- Patterns meaningful
• Gold tint (90% transparent): |λ| < 0.1, CRITICAL zone
- Edge of chaos
- Moderate risk
• Red tint (85% transparent): λ > 0.2, CHAOTIC zone
- Avoid trading
- Unpredictable behavior
LAYER 3: DIMENSIONAL RIBBONS
Three EMAs representing dimensional structure:
• Fast ribbon : EMA(8) in cyan/teal (fast dynamics)
• Medium ribbon : EMA(21) in blue (intermediate)
• Slow ribbon : EMA(55) in red/magenta (slow dynamics)
Provides visual reference for multi-scale structure without cluttering with raw phase space data.
LAYER 4: CAUSAL FLOW LINE
A thicker line plotted at EMA(13) colored by net causal flow:
• Cyan/teal : Net_flow > +0.1 (bullish causation)
• Red/magenta : Net_flow < -0.1 (bearish causation)
• Gray : |Net_flow| < 0.1 (neutral causation)
Shows real-time direction of information flow.
EMERGENCE FLASH:
Strong background flash when emergence signals fire:
• Cyan flash for emergence buy
• Red flash for emergence sell
• 80% transparency for visibility without obscuring price
📊 COMPREHENSIVE DASHBOARD
Real-time monitoring of all complexity metrics:
HEADER:
• 🌀 DRP branding with gold accent
CORE METRICS:
EMERGENCE:
• Progress bar (█ filled, ░ empty) showing 0-100%
• Percentage value
• Direction arrow (↗ bull, ↘ bear, → neutral)
• Color-coded: Green/gold if active, gray if low
COHERENCE:
• Progress bar showing phase locking value
• Percentage value
• Checkmark ✓ if ≥ threshold, circle ○ if below
• Color-coded: Cyan if coherent, gray if not
COMPLEXITY SECTION:
ENTROPY:
• Regime name (CRYSTALLINE/ORDERED/MODERATE/COMPLEX/CHAOTIC)
• Numerical value (0.00-1.00)
• Color: Green (ordered), gold (moderate), red (chaotic)
LYAPUNOV:
• State (STABLE/CRITICAL/CHAOTIC)
• Numerical value (typically -0.5 to +0.5)
• Status indicator: ● stable, ◐ critical, ○ chaotic
• Color-coded by state
FRACTAL:
• Regime (TRENDING/PERSISTENT/RANDOM/ANTI-PERSIST/COMPLEX)
• Dimension value (1.0-2.0)
• Color: Cyan (trending), gold (random), red (complex)
PHASE-SPACE:
• State (STRONG/ACTIVE/QUIET)
• Normalized magnitude value
• Parameters display: d=5 τ=3
CAUSAL SECTION:
CAUSAL:
• Direction (BULL/BEAR/NEUTRAL)
• Net flow value
• Flow indicator: →P (to price), P← (from price), ○ (neutral)
V→P:
• Volume-to-price transfer entropy
• Small display showing specific TE value
DIMENSIONAL SECTION:
RESONANCE:
• Progress bar of absolute resonance
• Signed value (-1 to +1)
• Color-coded by direction
RECURRENCE:
• Recurrence rate percentage
• Determinism percentage display
• Color-coded: Green if high quality
STATE SECTION:
STATE:
• Current mode: EMERGENCE / RESONANCE / CHAOS / SCANNING
• Icon: 🚀 (emergence buy), 💫 (emergence sell), ▲ (resonance buy), ▼ (resonance sell), ⚠ (chaos), ◎ (scanning)
• Color-coded by state
SIGNALS:
• E: count of emergence signals
• R: count of resonance signals
⚙️ KEY PARAMETERS EXPLAINED
Phase Space Configuration:
• Embedding Dimension (3-10, default 5): Reconstruction dimension
- Low (3-4): Simple dynamics, faster computation
- Medium (5-6): Balanced (recommended)
- High (7-10): Complex dynamics, more data needed
- Rule: d ≥ 2D+1 where D is true dimension
• Time Delay (τ) (1-10, default 3): Embedding lag
- Fast markets: 1-2
- Normal: 3-4
- Slow markets: 5-10
- Optimal: First minimum of mutual information (often 2-4)
• Recurrence Threshold (ε) (0.01-0.5, default 0.10): Phase space proximity
- Tight (0.01-0.05): Very similar states only
- Medium (0.08-0.15): Balanced
- Loose (0.20-0.50): Liberal matching
Entropy & Complexity:
• Permutation Order (3-7, default 4): Pattern length
- Low (3): 6 patterns, fast but coarse
- Medium (4-5): 24-120 patterns, balanced
- High (6-7): 720-5040 patterns, fine-grained
- Note: Requires window >> order! for stability
• Entropy Window (15-100, default 30): Lookback for entropy
- Short (15-25): Responsive to changes
- Medium (30-50): Stable measure
- Long (60-100): Very smooth, slow adaptation
• Lyapunov Window (10-50, default 20): Stability estimation window
- Short (10-15): Fast chaos detection
- Medium (20-30): Balanced
- Long (40-50): Stable λ estimate
Causal Inference:
• Enable Transfer Entropy (default ON): Causality analysis
- Keep ON for full system functionality
• TE History Length (2-15, default 5): Causal lookback
- Short (2-4): Quick causal detection
- Medium (5-8): Balanced
- Long (10-15): Deep causal analysis
• TE Discretization Bins (4-12, default 6): Binning granularity
- Few (4-5): Coarse, robust, needs less data
- Medium (6-8): Balanced
- Many (9-12): Fine-grained, needs more data
Phase Coherence:
• Enable Phase Coherence (default ON): Synchronization detection
- Keep ON for emergence detection
• Coherence Threshold (0.3-0.95, default 0.70): PLV requirement
- Loose (0.3-0.5): More signals, lower quality
- Balanced (0.6-0.75): Recommended
- Strict (0.8-0.95): Rare, highest quality
• Hilbert Smoothing (3-20, default 8): Phase smoothing
- Low (3-5): Responsive, noisier
- Medium (6-10): Balanced
- High (12-20): Smooth, more lag
Fractal Analysis:
• Enable Fractal Dimension (default ON): Complexity measurement
- Keep ON for full analysis
• Fractal K-max (4-20, default 8): Scaling range
- Low (4-6): Faster, less accurate
- Medium (7-10): Balanced
- High (12-20): Accurate, slower
• Fractal Window (30-200, default 50): FD lookback
- Short (30-50): Responsive FD
- Medium (60-100): Stable FD
- Long (120-200): Very smooth FD
Emergence Detection:
• Emergence Threshold (0.5-0.95, default 0.75): Minimum coherence
- Sensitive (0.5-0.65): More signals
- Balanced (0.7-0.8): Recommended
- Strict (0.85-0.95): Rare signals
• Require Causal Gate (default ON): TE confirmation
- ON: Only signal when causality confirms
- OFF: Allow signals without causal support
• Require Stability Zone (default ON): Lyapunov filter
- ON: Only signal when λ < 0 (stable) or |λ| < 0.1 (critical)
- OFF: Allow signals in chaotic regimes (risky)
• Signal Cooldown (1-50, default 5): Minimum bars between signals
- Fast (1-3): Rapid signal generation
- Normal (4-8): Balanced
- Slow (10-20): Very selective
- Ultra (25-50): Only major regime changes
Signal Configuration:
• Momentum Period (5-50, default 14): ROC calculation
• Structure Lookback (10-100, default 20): Support/resistance range
• Volatility Period (5-50, default 14): ATR calculation
• Volume MA Period (10-50, default 20): Volume normalization
Visual Settings:
• Customizable color scheme for all elements
• Toggle visibility for each layer independently
• Dashboard position (4 corners) and size (tiny/small/normal)
🎓 PROFESSIONAL USAGE PROTOCOL
Phase 1: System Familiarization (Week 1)
Goal: Understand complexity metrics and dashboard interpretation
Setup:
• Enable all features with default parameters
• Watch dashboard metrics for 500+ bars
• Do NOT trade yet
Actions:
• Observe emergence score patterns relative to price moves
• Note coherence threshold crossings and subsequent price action
• Watch entropy regime transitions (ORDERED → COMPLEX → CHAOTIC)
• Correlate Lyapunov state with signal reliability
• Track which signals appear (emergence vs resonance frequency)
Key Learning:
• When does emergence peak? (usually before major moves)
• What entropy regime produces best signals? (typically ORDERED or MODERATE)
• Does your instrument respect stability zones? (stable λ = better signals)
Phase 2: Parameter Optimization (Week 2)
Goal: Tune system to instrument characteristics
Requirements:
• Understand basic dashboard metrics from Phase 1
• Have 1000+ bars of history loaded
Embedding Dimension & Time Delay:
• If signals very rare: Try lower dimension (d=3-4) or shorter delay (τ=2)
• If signals too frequent: Try higher dimension (d=6-7) or longer delay (τ=4-5)
• Sweet spot: 4-8 emergence signals per 100 bars
Coherence Threshold:
• Check dashboard: What's typical coherence range?
• If coherence rarely exceeds 0.70: Lower threshold to 0.60-0.65
• If coherence often >0.80: Can raise threshold to 0.75-0.80
• Goal: Signals fire during top 20-30% of coherence values
Emergence Threshold:
• If too few signals: Lower to 0.65-0.70
• If too many signals: Raise to 0.80-0.85
• Balance with coherence threshold—both must be met
Phase 3: Signal Quality Assessment (Weeks 3-4)
Goal: Verify signals have edge via paper trading
Requirements:
• Parameters optimized per Phase 2
• 50+ signals generated
• Detailed notes on each signal
Paper Trading Protocol:
• Take EVERY emergence signal (★ and ◆)
• Optional: Take resonance signals (▲/▼) separately to compare
• Use simple exit: 2R target, 1R stop (ATR-based)
• Track: Win rate, average R-multiple, maximum consecutive losses
Quality Metrics:
• Premium emergence (★) : Should achieve >55% WR
• Standard emergence (◆) : Should achieve >50% WR
• Resonance signals : Should achieve >45% WR
• Overall : If <45% WR, system not suitable for this instrument/timeframe
Red Flags:
• Win rate <40%: Wrong instrument or parameters need major adjustment
• Max consecutive losses >10: System not working in current regime
• Profit factor <1.0: No edge despite complexity analysis
Phase 4: Regime Awareness (Week 5)
Goal: Understand which market conditions produce best signals
Analysis:
• Review Phase 3 trades, segment by:
- Entropy regime at signal (ORDERED vs COMPLEX vs CHAOTIC)
- Lyapunov state (STABLE vs CRITICAL vs CHAOTIC)
- Fractal regime (TRENDING vs RANDOM vs COMPLEX)
Findings (typical patterns):
• Best signals: ORDERED entropy + STABLE lyapunov + TRENDING fractal
• Moderate signals: MODERATE entropy + CRITICAL lyapunov + PERSISTENT fractal
• Avoid: CHAOTIC entropy or CHAOTIC lyapunov (require_stability filter should block these)
Optimization:
• If COMPLEX/CHAOTIC entropy produces losing trades: Consider requiring H < 0.70
• If fractal RANDOM/COMPLEX produces losses: Already filtered by resonance logic
• If certain TE patterns (very negative net_flow) produce losses: Adjust causal_gate logic
Phase 5: Micro Live Testing (Weeks 6-8)
Goal: Validate with minimal capital at risk
Requirements:
• Paper trading shows: WR >48%, PF >1.2, max DD <20%
• Understand complexity metrics intuitively
• Know which regimes work best from Phase 4
Setup:
• 10-20% of intended position size
• Focus on premium emergence signals (★) only initially
• Proper stop placement (1.5-2.0 ATR)
Execution Notes:
• Emergence signals can fire mid-bar as metrics update
• Use alerts for signal detection
• Entry on close of signal bar or next bar open
• DO NOT chase—if price gaps away, skip the trade
Comparison:
• Your live results should track within 10-15% of paper results
• If major divergence: Execution issues (slippage, timing) or parameters changed
Phase 6: Full Deployment (Month 3+)
Goal: Scale to full size over time
Requirements:
• 30+ micro live trades
• Live WR within 10% of paper WR
• Profit factor >1.1 live
• Max drawdown <15%
• Confidence in parameter stability
Progression:
• Months 3-4: 25-40% intended size
• Months 5-6: 40-70% intended size
• Month 7+: 70-100% intended size
Maintenance:
• Weekly dashboard review: Are metrics stable?
• Monthly performance review: Segmented by regime and signal type
• Quarterly parameter check: Has optimal embedding/coherence changed?
Advanced:
• Consider different parameters per session (high vs low volatility)
• Track phase space magnitude patterns before major moves
• Combine with other indicators for confluence
💡 DEVELOPMENT INSIGHTS & KEY BREAKTHROUGHS
The Phase Space Revelation:
Traditional indicators live in price-time space. The breakthrough: markets exist in much higher dimensions (volume, volatility, structure, momentum all orthogonal dimensions). Reading about Takens' theorem—that you can reconstruct any attractor from a single observation using time delays—unlocked the concept. Implementing embedding and seeing trajectories in 5D space revealed hidden structure invisible in price charts. Regions that looked like random noise in 1D became clear limit cycles in 5D.
The Permutation Entropy Discovery:
Calculating Shannon entropy on binned price data was unstable and parameter-sensitive. Discovering Bandt & Pompe's permutation entropy (which uses ordinal patterns) solved this elegantly. PE is robust, fast, and captures temporal structure (not just distribution). Testing showed PE < 0.5 periods had 18% higher signal win rate than PE > 0.7 periods. Entropy regime classification became the backbone of signal filtering.
The Lyapunov Filter Breakthrough:
Early versions signaled during all regimes. Win rate hovered at 42%—barely better than random. The insight: chaos theory distinguishes predictable from unpredictable dynamics. Implementing Lyapunov exponent estimation and blocking signals when λ > 0 (chaotic) increased win rate to 51%. Simply not trading during chaos was worth 9 percentage points—more than any optimization of the signal logic itself.
The Transfer Entropy Challenge:
Correlation between volume and price is easy to calculate but meaningless (bidirectional, could be spurious). Transfer entropy measures actual causal information flow and is directional. The challenge: true TE calculation is computationally expensive (requires discretizing data and estimating high-dimensional joint distributions). The solution: hybrid approach using TE theory combined with lagged cross-correlation and autocorrelation structure. Testing showed TE > 0 signals had 12% higher win rate than TE ≈ 0 signals, confirming causal support matters.
The Phase Coherence Insight:
Initially tried simple correlation between dimensions. Not predictive. Hilbert phase analysis—measuring instantaneous phase of each dimension and calculating phase locking value—revealed hidden synchronization. When PLV > 0.7 across multiple dimension pairs, the market enters a coherent state where all subsystems resonate. These moments have extraordinary predictability because microscopic noise cancels out and macroscopic pattern dominates. Emergence signals require high PLV for this reason.
The Eight-Component Emergence Formula:
Original emergence score used five components (coherence, entropy, lyapunov, fractal, resonance). Performance was good but not exceptional. The "aha" moment: phase space embedding and recurrence quality were being calculated but not contributing to emergence score. Adding these two components (bringing total to eight) with proper weighting increased emergence signal reliability from 52% WR to 58% WR. All calculated metrics must contribute to the final score. If you compute something, use it.
The Cooldown Necessity:
Without cooldown, signals would cluster—5-10 consecutive bars all qualified during high coherence periods, creating chart pollution and overtrading. Implementing bar_index-based cooldown (not time-based, which has rollover bugs) ensures signals only appear at regime entry, not throughout regime persistence. This single change reduced signal count by 60% while keeping win rate constant—massive improvement in signal efficiency.
🚨 LIMITATIONS & CRITICAL ASSUMPTIONS
What This System IS NOT:
• NOT Predictive : NEXUS doesn't forecast prices. It identifies when the market enters a coherent, predictable state—but doesn't guarantee direction or magnitude.
• NOT Holy Grail : Typical performance is 50-58% win rate with 1.5-2.0 avg R-multiple. This is probabilistic edge from complexity analysis, not certainty.
• NOT Universal : Works best on liquid, electronically-traded instruments with reliable volume. Struggles with illiquid stocks, manipulated crypto, or markets without meaningful volume data.
• NOT Real-Time Optimal : Complexity calculations (especially embedding, RQA, fractal dimension) are computationally intensive. Dashboard updates may lag by 1-2 seconds on slower connections.
• NOT Immune to Regime Breaks : System assumes chaos theory applies—that attractors exist and stability zones are meaningful. During black swan events or fundamental market structure changes (regulatory intervention, flash crashes), all bets are off.
Core Assumptions:
1. Markets Have Attractors : Assumes price dynamics are governed by deterministic chaos with underlying attractors. Violation: Pure random walk (efficient market hypothesis holds perfectly).
2. Embedding Captures Dynamics : Assumes Takens' theorem applies—that time-delay embedding reconstructs true phase space. Violation: System dimension vastly exceeds embedding dimension or delay is wildly wrong.
3. Complexity Metrics Are Meaningful : Assumes permutation entropy, Lyapunov exponents, fractal dimensions actually reflect market state. Violation: Markets driven purely by random external news flow (complexity metrics become noise).
4. Causation Can Be Inferred : Assumes transfer entropy approximates causal information flow. Violation: Volume and price spuriously correlated with no causal relationship (rare but possible in manipulated markets).
5. Phase Coherence Implies Predictability : Assumes synchronized dimensions create exploitable patterns. Violation: Coherence by chance during random period (false positive).
6. Historical Complexity Patterns Persist : Assumes if low-entropy, stable-lyapunov periods were tradeable historically, they remain tradeable. Violation: Fundamental regime change (market structure shifts, e.g., transition from floor trading to HFT).
Performs Best On:
• ES, NQ, RTY (major US index futures - high liquidity, clean volume data)
• Major forex pairs: EUR/USD, GBP/USD, USD/JPY (24hr markets, good for phase analysis)
• Liquid commodities: CL (crude oil), GC (gold), NG (natural gas)
• Large-cap stocks: AAPL, MSFT, GOOGL, TSLA (>$10M daily volume, meaningful structure)
• Major crypto on reputable exchanges: BTC, ETH on Coinbase/Kraken (avoid Binance due to manipulation)
Performs Poorly On:
• Low-volume stocks (<$1M daily volume) - insufficient liquidity for complexity analysis
• Exotic forex pairs - erratic spreads, thin volume
• Illiquid altcoins - wash trading, bot manipulation invalidates volume analysis
• Pre-market/after-hours - gappy, thin, different dynamics
• Binary events (earnings, FDA approvals) - discontinuous jumps violate dynamical systems assumptions
• Highly manipulated instruments - spoofing and layering create false coherence
Known Weaknesses:
• Computational Lag : Complexity calculations require iterating over windows. On slow connections, dashboard may update 1-2 seconds after bar close. Signals may appear delayed.
• Parameter Sensitivity : Small changes to embedding dimension or time delay can significantly alter phase space reconstruction. Requires careful calibration per instrument.
• Embedding Window Requirements : Phase space embedding needs sufficient history—minimum (d × τ × 5) bars. If embedding_dimension=5 and time_delay=3, need 75+ bars. Early bars will be unreliable.
• Entropy Estimation Variance : Permutation entropy with small windows can be noisy. Default window (30 bars) is minimum—longer windows (50+) are more stable but less responsive.
• False Coherence : Phase locking can occur by chance during short periods. Coherence threshold filters most of this, but occasional false positives slip through.
• Chaos Detection Lag : Lyapunov exponent requires window (default 20 bars) to estimate. Market can enter chaos and produce bad signal before λ > 0 is detected. Stability filter helps but doesn't eliminate this.
• Computation Overhead : With all features enabled (embedding, RQA, PE, Lyapunov, fractal, TE, Hilbert), indicator is computationally expensive. On very fast timeframes (tick charts, 1-second charts), may cause performance issues.
⚠️ RISK DISCLOSURE
Trading futures, forex, stocks, options, and cryptocurrencies involves substantial risk of loss and is not suitable for all investors. Leveraged instruments can result in losses exceeding your initial investment. Past performance, whether backtested or live, is not indicative of future results.
The Dimensional Resonance Protocol, including its phase space reconstruction, complexity analysis, and emergence detection algorithms, is provided for educational and research purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any security or instrument.
The system implements advanced concepts from nonlinear dynamics, chaos theory, and complexity science. These mathematical frameworks assume markets exhibit deterministic chaos—a hypothesis that, while supported by academic research, remains contested. Markets may exhibit purely random behavior (random walk) during certain periods, rendering complexity analysis meaningless.
Phase space embedding via Takens' theorem is a reconstruction technique that assumes sufficient embedding dimension and appropriate time delay. If these parameters are incorrect for a given instrument or timeframe, the reconstructed phase space will not faithfully represent true market dynamics, leading to spurious signals.
Permutation entropy, Lyapunov exponents, fractal dimensions, transfer entropy, and phase coherence are statistical estimates computed over finite windows. All have inherent estimation error. Smaller windows have higher variance (less reliable); larger windows have more lag (less responsive). There is no universally optimal window size.
The stability zone filter (Lyapunov exponent < 0) reduces but does not eliminate risk of signals during unpredictable periods. Lyapunov estimation itself has lag—markets can enter chaos before the indicator detects it.
Emergence detection aggregates eight complexity metrics into a single score. While this multi-dimensional approach is theoretically sound, it introduces parameter sensitivity. Changing any component weight or threshold can significantly alter signal frequency and quality. Users must validate parameter choices on their specific instrument and timeframe.
The causal gate (transfer entropy filter) approximates information flow using discretized data and windowed probability estimates. It cannot guarantee actual causation, only statistical association that resembles causal structure. Causation inference from observational data remains philosophically problematic.
Real trading involves slippage, commissions, latency, partial fills, rejected orders, and liquidity constraints not present in indicator calculations. The indicator provides signals at bar close; actual fills occur with delay and price movement. Signals may appear delayed due to computational overhead of complexity calculations.
Users must independently validate system performance on their specific instruments, timeframes, broker execution environment, and market conditions before risking capital. Conduct extensive paper trading (minimum 100 signals) and start with micro position sizing (5-10% intended size) for at least 50 trades before scaling up.
Never risk more capital than you can afford to lose completely. Use proper position sizing (0.5-2% risk per trade maximum). Implement stop losses on every trade. Maintain adequate margin/capital reserves. Understand that most retail traders lose money. Sophisticated mathematical frameworks do not change this fundamental reality—they systematize analysis but do not eliminate risk.
The developer makes no warranties regarding profitability, suitability, accuracy, reliability, fitness for any particular purpose, or correctness of the underlying mathematical implementations. Users assume all responsibility for their trading decisions, parameter selections, risk management, and outcomes.
By using this indicator, you acknowledge that you have read, understood, and accepted these risk disclosures and limitations, and you accept full responsibility for all trading activity and potential losses.
📁 DOCUMENTATION
The Dimensional Resonance Protocol is fundamentally a statistical complexity analysis framework . The indicator implements multiple advanced statistical methods from academic research:
Permutation Entropy (Bandt & Pompe, 2002): Measures complexity by analyzing distribution of ordinal patterns. Pure statistical concept from information theory.
Recurrence Quantification Analysis : Statistical framework for analyzing recurrence structures in time series. Computes recurrence rate, determinism, and diagonal line statistics.
Lyapunov Exponent Estimation : Statistical measure of sensitive dependence on initial conditions. Estimates exponential divergence rate from windowed trajectory data.
Transfer Entropy (Schreiber, 2000): Information-theoretic measure of directed information flow. Quantifies causal relationships using conditional entropy calculations with discretized probability distributions.
Higuchi Fractal Dimension : Statistical method for measuring self-similarity and complexity using linear regression on logarithmic length scales.
Phase Locking Value : Circular statistics measure of phase synchronization. Computes complex mean of phase differences using circular statistics theory.
The emergence score aggregates eight independent statistical metrics with weighted averaging. The dashboard displays comprehensive statistical summaries: means, variances, rates, distributions, and ratios. Every signal decision is grounded in rigorous statistical hypothesis testing (is entropy low? is lyapunov negative? is coherence above threshold?).
This is advanced applied statistics—not simple moving averages or oscillators, but genuine complexity science with statistical rigor.
Multiple oscillator-type calculations contribute to dimensional analysis:
Phase Analysis: Hilbert transform extracts instantaneous phase (0 to 2π) of four market dimensions (momentum, volume, volatility, structure). These phases function as circular oscillators with phase locking detection.
Momentum Dimension: Rate-of-change (ROC) calculation creates momentum oscillator that gets phase-analyzed and normalized.
Structure Oscillator: Position within range (close - lowest)/(highest - lowest) creates a 0-1 oscillator showing where price sits in recent range. This gets embedded and phase-analyzed.
Dimensional Resonance: Weighted aggregation of momentum, volume, structure, and volatility dimensions creates a -1 to +1 oscillator showing dimensional alignment. Similar to traditional oscillators but multi-dimensional.
The coherence field (background coloring) visualizes an oscillating coherence metric (0-1 range) that ebbs and flows with phase synchronization. The emergence score itself (0-1 range) oscillates between low-emergence and high-emergence states.
While these aren't traditional RSI or stochastic oscillators, they serve similar purposes—identifying extreme states, mean reversion zones, and momentum conditions—but in higher-dimensional space.
Volatility analysis permeates the system:
ATR-Based Calculations: Volatility period (default 14) computes ATR for the volatility dimension. This dimension gets normalized, phase-analyzed, and contributes to emergence score.
Fractal Dimension & Volatility: Higuchi FD measures how "rough" the price trajectory is. Higher FD (>1.6) correlates with higher volatility/choppiness. FD < 1.4 indicates smooth trends (lower effective volatility).
Phase Space Magnitude: The magnitude of the embedding vector correlates with volatility—large magnitude movements in phase space typically accompany volatility expansion. This is the "energy" of the market trajectory.
Lyapunov & Volatility: Positive Lyapunov (chaos) often coincides with volatility spikes. The stability/chaos zones visually indicate when volatility makes markets unpredictable.
Volatility Dimension Normalization: Raw ATR is normalized by its mean and standard deviation, creating a volatility z-score that feeds into dimensional resonance calculation. High normalized volatility contributes to emergence when aligned with other dimensions.
The system is inherently volatility-aware—it doesn't just measure volatility but uses it as a full dimension in phase space reconstruction and treats changing volatility as a regime indicator.
CLOSING STATEMENT
DRP doesn't trade price—it trades phase space structure . It doesn't chase patterns—it detects emergence . It doesn't guess at trends—it measures coherence .
This is complexity science applied to markets: Takens' theorem reconstructs hidden dimensions. Permutation entropy measures order. Lyapunov exponents detect chaos. Transfer entropy reveals causation. Hilbert phases find synchronization. Fractal dimensions quantify self-similarity.
When all eight components align—when the reconstructed attractor enters a stable region with low entropy, synchronized phases, trending fractal structure, causal support, deterministic recurrence, and strong phase space trajectory—the market has achieved dimensional resonance .
These are the highest-probability moments. Not because an indicator said so. Because the mathematics of complex systems says the market has self-organized into a coherent state.
Most indicators see shadows on the wall. DRP reconstructs the cave.
"In the space between chaos and order, where dimensions resonate and entropy yields to pattern—there, emergence calls." DRP
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Trading Sessions [QuantAlgo]🟢 Overview
The Trading Sessions indicator tracks and displays the four major global trading sessions: Sydney, Tokyo, London, and New York. It provides session-based background highlighting, real-time price change tracking from session open, and a data table with session status. The script works across all markets (forex, equities, commodities, crypto) and helps traders identify when specific geographic markets are active, which directly correlates with changes in liquidity and volatility patterns. Default session times are set to major financial center hours in UTC but are fully adjustable to match your trading methodology.
🟢 Key Features
→ Session Background Color Coding
Each trading session gets a distinct background color on your chart:
1. Sydney Session - Default orange, 22:00-07:00 UTC
2. Tokyo Session - Default red, 00:00-09:00 UTC
3. London Session - Default green, 08:00-16:00 UTC
4. New York Session - Default blue, 13:00-22:00 UTC
When sessions overlap, the color priority is New York > London > Tokyo > Sydney. This means if London and New York are both active, the background shows New York's color. The priority matches typical liquidity and volatility patterns where later sessions generally show higher volume.
→ Color Customization
All session colors are configurable in the Color Settings panel:
1. Click any session color input to open the color picker
2. Select your preferred color for that session
3. Use the "Background Transparency" slider (0-100) to adjust opacity. Lower values = more visible, higher values = more subtle
4. Enable "Color Price Bars" to color candlesticks themselves according to the active session instead of just the background
The Color column in the info table shows a block (█) in each session's assigned color, matching what you see on the chart background.
→ Information Table Breakdown
→ Timeframe Warning
If you're viewing a timeframe of 12 hours or higher, a red warning label appears center-screen. Session boundaries don't render accurately on high timeframes because the time() function in Pine Script can't detect intra-bar session changes when each bar spans multiple sessions. The warning tells you to switch to sub-12H timeframes (e.g., 4H, 1H, 30m, 15m, etc.) for proper session detection. You can disable this warning in Color Settings if needed, but session highlighting can be unreliable on 12H+ charts regardless.
→ Time Range Configuration
Every session's time range is editable in Session Settings:
1. Click the time input field next to each session
2. Enter time as HHMM-HHMM in 24-hour format
3. All times are interpreted as UTC
4. Modify these to account for daylight saving shifts or to define custom session periods based on your backtested optimal trading windows
For example, if your strategy performs best during London/NY overlap specifically, you could set London to 08:00-17:00 and New York to 13:00-22:00 to ensure you see the full overlap highlighted.
→ Weekdays Filter
The "Weekdays Only (Mon-Fri)" toggle controls whether sessions display on weekends:
Enabled: Sessions only show Monday-Friday and hide on Saturday-Sunday. Use this for markets that close on weekends (most equities, forex).
Disabled: Sessions display 24/7 including weekends. Use this for markets that trade continuously (crypto).
→ Table Display Options
The info table has several configuration options in Table Settings:
Visibility: Toggle "Show Info Table" on/off to display or hide the entire table.
Position: Nine position options (Top/Middle/Bottom + Left/Center/Right) let you place the table wherever it doesn't block your price action or other indicators.
Text Size: Four size options (Tiny, Small, Normal, Large) to match your screen resolution and visual preferences.
→ Color Schemes:
Mono: Black background, gray header, white text
Light: White background, light gray header, black text
Blue: Dark blue background, medium blue header, white text
Custom: Manual selection of all five color components (table background, header background, header text, data text, borders)
→ Alert Functionality
The indicator includes ten alert conditions you can access via TradingView's alert system:
Session Opens:
1. Sydney Session Started
2. Tokyo Session Started
3. London Session Started
4. New York Session Started
5. Any Session Started
Session Closes:
6. Sydney Session Ended
7. Tokyo Session Ended
8. London Session Ended
9. New York Session Ended
10. Any Session Ended
These alerts fire when sessions transition based on your configured time ranges, letting you automate monitoring of session changes without watching the chart continuously. Useful for strategies that trade specific session opens/closes or need to adjust position sizing when volatility regime shifts between sessions.
