Beast Mode PRO v4.0# Beast Mode PRO v4.0 - Advanced Multi-Regime Trading System
## Overview
Beast Mode PRO v4.0 is a sophisticated technical analysis indicator designed for active traders seeking high-probability setups across multiple timeframes. This system combines machine learning-inspired clustering algorithms with traditional technical analysis to identify market regimes and generate precision entry signals. The indicator adapts to different trading styles through intelligent preset configurations and multiple trading modes.
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## Core Methodology
### Signal Generation Framework
The indicator employs a **multi-component voting system** that analyzes market conditions through several independent technical perspectives:
**Technical Components:**
- **RSI (Relative Strength Index)**: Momentum oscillator measuring overbought/oversold conditions
- **Fisher Transform**: Price transformation technique that normalizes price distributions for clearer turning points
- **DMI (Directional Movement Index)**: Trend strength indicator measuring directional pressure
- **Z-Score Analysis**: Statistical measure identifying price deviations from historical norms
- **Moving Average Ratio**: Price relationship to its moving average baseline
- **MFI (Money Flow Index)**: Volume-weighted momentum indicator
- **Stochastic Oscillator**: Momentum indicator comparing closing price to price range
- **CCI (Commodity Channel Index)**: Measures current price level relative to average price level
### Clustering Engine
The system utilizes a **k-means inspired clustering algorithm** that categorizes each technical indicator's normalized values into distinct market regimes (bullish, bearish, neutral). This approach:
1. **Normalizes** all indicators using z-score transformation over a historical lookback window
2. **Clusters** normalized values using percentile-based thresholds
3. **Aggregates** individual votes into a composite score ranging from -100 to +100
4. **Smooths** the composite score using selectable methods (SMA, EMA, WMA, HMA, TEMA, DEMA)
The clustering percentiles adapt dynamically based on current market volatility (ATR-normalized), ensuring the system remains responsive across different market conditions.
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## Trading Modes
### 1. Normal Mode
Standard crossover-based signals using fixed thresholds (+10/-10). Suitable for balanced trading with moderate signal frequency.
### 2. Scalper Mode
Dynamic threshold adjustment based on recent score volatility. Generates more frequent signals by adapting to short-term price movements.
### 3. Aggressive Mode
Reversal-focused approach that triggers signals when the composite score crosses extreme levels (+80/-80), targeting major trend reversals.
### 4. Hybrid Mode
Combines Normal and Aggressive signals, capturing both standard crossovers and extreme reversals for comprehensive market coverage.
### 5. Super Scalper Mode
Ultra-responsive mode using signal line crossovers (14-period HMA of composite score) for maximum trade frequency.
### 6. Sniper Mode (Premium Feature)
Multi-confirmation system requiring alignment of:
- Composite score threshold breach
- Positive fast momentum (10-period SMI)
- Positive trend momentum (200-period SMI)
- Price above/below smart trend filter MA
This mode prioritizes precision over frequency, filtering out low-probability setups.
---
## Timeframe Presets
Pre-optimized configurations for common trading timeframes:
### 1 Minute Preset
- Fast smoothing (10-period WMA)
- Tight chop filter (61.8 threshold)
- Optimized for rapid scalping with minimal lag
### 2 Minute Preset
- Balanced smoothing (12-period EMA)
- Enhanced volume filtering
- Moderate cooling period (5 bars)
### 3 Minute Preset
- HMA smoothing for reduced lag
- Stochastic and CCI enabled
- Balanced approach for intraday trading
### 5 Minute Preset
- TEMA smoothing for trend following
- Stronger filters to reduce noise
- Extended lookback (1000 bars)
### 15 Minute Preset
- DEMA smoothing for swing positions
- Maximum filtering configuration
- All technical indicators enabled
- Suitable for swing trading and position building
Users can also select "Custom" to manually configure all parameters.
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## Advanced Filtering System
### 1. Choppy Market Filter
Uses Choppiness Index calculation to identify consolidating markets. When CI exceeds the threshold, signals are suppressed to avoid whipsaw trades.
### 2. Smart Trend Filter
Configurable moving average (SMA/EMA/WMA/HMA/TEMA/DEMA/VWMA/RMA) that prevents counter-trend signals. Long signals require price above the MA, shorts require price below.
### 3. Volume Filter
Compares current volume to its moving average. Signals are suppressed when volume falls below the specified multiplier of average volume.
### 4. ATR Volatility Filter
Prevents trading during low volatility periods when ATR falls below its moving average multiplied by the specified factor.
### 5. Session Filter
Time-based filtering for Asia, London, New York, or combined sessions. Ensures trading only during preferred market hours.
### 6. Multi-Timeframe Confirmation
Optionally requires higher timeframe alignment before generating signals, adding confluence for higher probability trades.
### 7. Cooling Off Period
Prevents signal clustering by enforcing a minimum number of bars between consecutive signals.
---
## Smart Money Concepts Integration
### Order Block Detection
Identifies institutional supply/demand zones using multi-timeframe analysis:
- Detects strong directional candles followed by breakout moves
- Volume confirmation ensures significance
- Customizable timeframe selection (current TF or higher TF: 5m, 15m, 30m, 1H, Daily)
- Visual boxes mark active order blocks with automatic expiration after lookback period
- Price interaction alerts when touching active zones
### Liquidity Zones
Marks equal highs (EQH) and equal lows (EQL) where stop losses typically cluster, indicating potential reversal or breakout points.
---
## Momentum Analysis
### Fast Momentum (Default: 10-period)
Short-term momentum oscillator using Stochastic Momentum Index (SMI) calculation. Provides early warning of momentum shifts.
### Trend Momentum (Default: 200-period)
Long-term momentum gauge confirming overall trend direction. Used in Sniper Mode for multi-confirmation.
### Momentum Divergence Detection
Automatically identifies:
- **Regular Divergence**: Price makes new high/low but momentum doesn't (reversal signal)
- **Hidden Divergence**: Price makes higher low/lower high but momentum doesn't (continuation signal)
---
## Visual Components
### Price Chart Overlay
- **Smart Trend MA**: Dynamically colored moving average based on price position
- **EMA Cloud**: 50/200 EMA cloud showing long-term trend (background shading)
- **Trend Background**: Subtle background coloring based on composite score
- **Order Block Boxes**: Institutional supply/demand zones
- **Entry/Exit Markers**: Clear visual signals with emoji labels
- **Liquidity Markers**: EQH/EQL identification
### Bar Coloring
Bars change color based on active mode and market regime:
- **Sniper Mode**: Purple (bull) / Pink (bear)
- **Aggressive Mode**: Bright Green / Bright Red
- **Super Scalper**: Neon Green / Neon Red
- **Timeframe Presets**: Unique color schemes per preset
- **Choppy/Neutral**: Always gray regardless of mode
### Oscillator Pane
- **Composite Score Line**: Gradient-colored stepline showing current regime strength
- **Fast/Trend Momentum**: Optional overlays (gold/cyan colors)
- **Divergence Markers**: Visual alerts for regular, hidden, and momentum divergences
- **Power Zones**: Overbought/oversold regions (80/-80 levels)
- **Dynamic/Fixed Thresholds**: Visual reference lines based on active mode
### Interactive Dashboards
**Main Dashboard** displays:
- Active preset/mode configuration
- Real-time indicator values and votes
- Current market status (active/choppy/counter-trend/low volume/low ATR/MTF misalignment)
- Regime classification (Strong Long/Long/Neutral/Short/Strong Short)
- Smart Trend MA status
**Performance Dashboard** shows:
- Exit strategy (Fixed TP/SL, Trailing Stop, Opposite Signal)
- Total trades and win rate
- Total points and average per NY session
- Profit factor and recovery factor
- Best/worst trades and max drawdown
- Maximum winning/losing streaks
- Sharpe ratio and average risk:reward
**TP Optimizer** (33 variations tested):
- Tests take profit levels from 40 to 200 ticks (5-tick increments)
- Sortable by: Profit Factor, Win Rate, Total Points, Sharpe Ratio
- Displays top 5 configurations with full metrics
- Real-time optimization during backtesting
---
## Backtest Engine
### Exit Strategies
**1. Fixed TP/SL**
- Configurable in Ticks, ATR multiples, or Percentage
- Precise risk management with predefined targets
**2. Exit on Opposite Signal**
- Closes position when counter-signal appears
- Adapts to changing market conditions
- Useful for trend-following approaches
**3. Trailing Stop**
- Dynamic stop loss that follows profitable moves
- Configurable trailing offset percentage
- Locks in profits while allowing trends to develop
### Risk Management
- Optional minimum risk:reward filter
- Prevents trades below specified R:R threshold
- Date range filtering for historical analysis
- Session-based performance tracking
### Performance Metrics
- Win rate, profit factor, Sharpe ratio
- Maximum drawdown and recovery factor
- Consecutive win/loss streaks
- Average win/loss analysis
- Gross profit vs gross loss breakdown
---
## Alert System
Comprehensive alert conditions for:
- Entry signals (Long/Short)
- Exit events (TP/SL/Opposite/Trailing)
- Trend signals (Strong bullish/bearish)
- Divergences (Regular/Hidden/Momentum)
- Order block detection and touches
- Multi-condition strong signals (all confirmations aligned)
---
## How to Use
### Quick Start
1. Select your preferred timeframe preset (1m, 2m, 3m, 5m, 15m, or Custom)
2. Choose a trading mode (Normal, Scalper, Aggressive, Hybrid, Super Scalper, or Sniper)
3. Configure session filter to match your trading hours
4. Enable desired filters (choppy, trend, volume, ATR, MTF)
5. Set your exit strategy and TP/SL levels
6. Monitor signals on price chart and oscillator pane
### Optimization Workflow
1. Enable "Run TP Optimizer" in backtest settings
2. Run backtest on historical data
3. Review Optimizer Dashboard for best TP levels
4. Sort by preferred metric (Profit Factor, Win Rate, Total Points, Sharpe)
5. Apply winning configuration to live trading
### Advanced Configuration
- Customize individual indicator lengths and enable/disable specific components
- Adjust clustering parameters (lookback window, percentiles, cluster count)
- Fine-tune smoothing methods and lengths
- Configure order block detection timeframe and sensitivity
- Set cooling off period to control signal frequency
---
## Unique Features
1. **Adaptive Clustering**: Volatility-adjusted percentiles ensure consistent performance across market conditions
2. **Multi-Mode Architecture**: Six distinct trading modes from conservative to ultra-aggressive
3. **Timeframe Intelligence**: Pre-optimized presets eliminate guesswork for common timeframes
4. **Smart Money Integration**: Order block detection and liquidity zone marking
5. **Comprehensive Backtesting**: Three exit strategies with 33-variation TP optimization
6. **Visual Clarity**: Mode-specific bar coloring and clean chart presentation
7. **Filter Stack**: Seven-layer filtering system prevents low-quality signals
8. **Real-Time Metrics**: Live performance tracking with advanced statistics
---
## Benefits
- **Reduced False Signals**: Multi-confirmation clustering approach filters noise
- **Adaptability**: Works across timeframes and market conditions through preset system
- **Transparency**: Open visualization of all component votes and filtering status
- **Risk Management**: Built-in TP/SL optimization and R:R filtering
- **Time Efficiency**: Preset configurations save hours of manual optimization
- **Educational Value**: Dashboard shows exactly why signals trigger or get filtered
- **Professional Tools**: Institutional concepts (order blocks, liquidity zones) accessible to retail traders
---
## Best Practices
- Use Sniper Mode for high-probability setups during volatile markets
- Enable choppy filter during consolidation periods
- Combine Smart Trend Filter with MTF confirmation for swing trades
- Run TP Optimizer monthly to adapt to changing market dynamics
- Monitor Sharpe Ratio in addition to win rate for risk-adjusted performance
- Use session filters to avoid low-liquidity hours
- Start with preset configurations before custom optimization
---
## Technical Requirements
- TradingView Premium/Pro/Pro+ for full feature access
- Minimum chart history: 500 bars (adjustable in clustering settings)
- Works on all instruments (stocks, forex, crypto, futures)
- Compatible with standard candles (Heikin Ashi optional but not recommended for backtesting)
---
## Disclaimer
This indicator is a technical analysis tool designed to assist trading decisions. It does not guarantee profits and should be used in conjunction with proper risk management, fundamental analysis, and personal trading experience. Past performance does not indicate future results. Users should thoroughly test the indicator on demo accounts before live trading.
---
**Version**: 4.0
**Language**: Pine Script v6
**Type**: Overlay Indicator with Oscillator Pane
**Calculation**: On bar close (default) or real-time (configurable)
In den Scripts nach "take profit" suchen
Adaptive Risk Management [sgbpulse]1. Introduction:
Adaptive Risk Management is an advanced indicator designed to provide traders with a comprehensive risk management tool directly on the chart. Instead of relying on complex manual calculations, the indicator automates all critical steps of trade planning. It dynamically calculates the estimated Entry Price , the Stop Loss location, the required Position Size (Quantity) based on your capital and risk limits, and the three Take Profit targets based on your defined Reward/Risk ratios. The indicator displays all these essential data points clearly and visually on the chart, ensuring you always know the potential risk-reward profile of every trade.
ARM : The A daptive R isk M anagement every trader needs to ARM themselves with.
2. The Critical Importance of Risk Management
Proper risk management is the cornerstone of successful trading. Consistent profitability in the market is impossible without rigorously defining risk limits.
Risk Control: This starts by setting the maximum risk amount you are willing to lose in a single trade (Risk per Trade), and limiting the total capital allocated to the position (Max Capital per Trade).
Defining Boundaries (Stop Loss & Take Profit): It is mandatory to define a technical Stop Loss and a Take Profit target. A fundamental rule of risk management is that the Reward/Risk Ratio (R/R) must be a minimum of 1:1.
3. Core Features, Adaptivity, and Customization
The Adaptive Risk Management indicator is engineered for use across all major trading styles, including Swing Trading, Intraday Trading, and Scalping, providing consistent risk control regardless of the chosen timeframe.
Real-Time Dynamic Adaptivity: The indicator calculates all risk management parameters (Entry, Stop Loss, Quantity) dynamically with every new bar, thus adapting instantly to changing market conditions.
Trend Direction Adjustment: Define the analysis direction (Long/Uptrend or Short/Downtrend).
Intraday Session Data Control: Full control over whether lookback calculations will include data from Extended Trading Hours (ETH), or if the daily calculations will start actively only from the first bar of Regular Trading Hours (RTH).
Status Validation: The indicator performs critical status checks and displays clear Warning Messages if risk conditions are not met.
4. Intuitive Visualization and Real-Time Data
Dynamic Tracking Lines: The Entry Price and Stop Loss lines are updated with every new bar. Crucially, the length of these lines dynamically reflects the calculation's lookback range (e.g., the extent of Lookback Bars or the location of the confirmed Pivot Point), providing a visual anchor for the calculated price.
Risk and Reward Zones: The indicator creates a graphical background fill between Entry and Stop Loss (marked with the risk color) and between Entry and the Reward Targets (marked with the reward color).
Essential Information Labels: Labels are placed at the end of each line, providing critical data: Estimated Entry Price, Stock/Contract Quantity (Quantity), Total Entry Amount, Estimated Stop Loss, Risk per Share, Total Financial Risk (Risk Amount), Exit Amount, Estimated Take Profit 1/2/3, Reward/Risk Ratio 1/2/3, Total Reward 1/2/3, TP Exit Amount 1/2/3.
4.1. Data Window Metrics (16 Full Series)
The indicator displays 16 full data series in the TradingView Data Window, allowing precise tracking of every calculation parameter:
Entry Data: Estimated Entry, Quantity, Entry Amount.
Risk Data (Stop Loss): Estimated Stop Loss, Risk per Share, Risk Amount, Exit Amount.
Reward Data (Take Profit): Estimated Take Profit 1/2/3, Reward/Risk Ratio 1/2/3, Total Reward 1/2/3, TP Exit Amount 1/2/3.
4.2. Instant Tracking in the Status Line
The indicator displays 6 critical parameters continuously in the indicator's Status Line: Estimated Entry, Quantity, Estimated Stop Loss, Estimated Take Profit 1/2/3.
5. Detailed Indicator Inputs
5.1 General
Focused Trend: Defines the analysis direction (Uptrend / Downtrend).
Max Capital per Trade: The maximum amount allocated to purchasing stocks/contracts (in account currency).
Risk per Trade: The maximum amount the user is willing to risk in this single trade (in account currency).
ATR Length: The lookback period for the Average True Range (ATR) calculation.
5.2 Intraday Session Data Control
Regular Hours Limitation : If enabled, all daily lookback calculations (for Entry/Stop Loss anchor points) will begin strictly from the first Regular Trading Hours (RTH) bar. This limits the lookback range to the current RTH session, excluding preceding Extended Trading Hours (ETH) data. Only relevant for Intraday charts. Default: False (Off)
5.3 Entry Inputs
Entry Method: Selects the entry price calculation method:
Current Price: Uses the closing price of the current bar as the estimated entry point (Market Entry).
ATR Real Bodies Margin :
- Uptrend: Calculates the Maximum Real Body over the lookback period + the calculated safety margin.
- Downtrend: Calculates the Minimum Real Body over the lookback period - the calculated safety margin.
ATR Bars Margin :
- Uptrend: Calculates the Maximum High price over the lookback period + the calculated safety margin.
- Downtrend: Calculates the Minimum Low price over the lookback period - the calculated safety margin.
Lookback Bars: The number of bars used to calculate the extremes in the ATR-based entry methods (Relevant only for ATR Real Bodies Margin and ATR Bars Margin methods).
ATR Multiplier (Entry): The multiplier applied to the ATR value. The result of the multiplication is the calculated safety margin used to determine the estimated Entry Price.
5.4 Risk Inputs (Stop Loss)
Risk Method: Selects the Stop Loss price calculation method.
ATR Current Price Margin :
- Uptrend: Entry Price - the calculated safety margin.
- Downtrend: Entry Price + the calculated safety margin.
ATR Current Bar Margin :
- Uptrend: Current Bar's Low price - the calculated safety margin.
- Downtrend: Current Bar's High price + the calculated safety margin.
ATR Bars Margin :
- Uptrend: Lowest Low over lookback period - the calculated safety margin.
- Downtrend: Highest High over lookback period + the calculated safety margin.
ATR Pivot Margin :
- Uptrend: The first confirmed Pivot Low point - the calculated safety margin.
- Downtrend: The first confirmed Pivot High point + the calculated safety margin.
Lookback Bars: The lookback period for finding the extreme price used in the 'ATR Bars Margin' calculation.
ATR Multiplier (Risk): The multiplier applied to the ATR value. The result of the multiplication is the calculated safety margin used to place the estimated Stop Loss. Note: If set to 0, the Stop Loss will be placed exactly at the technical anchor point, provided the Minimum Margin Value is also 0.
Minimum Margin Value: The minimum price value (e.g., $0.01) the Stop Loss margin buffer must be.
Pivot (Left / Right): The number of bars required on either side of the pivot bar for confirmation (relevant only for the ATR Pivot Margin method).
5.5 Reward Inputs (Take Profit)
Show Take Profit 1/2/3: ON/OFF switch to control the visibility of each Take Profit target.
Reward/Risk Ratio 1/ 2/ 3: Defines the R/R ratio for the profit target. Must be ≥1.0.
6. Indicator Status/Warning Messages
In situations where the Stop Loss location cannot be calculated logically and validly, often caused by a mismatch between the configured Focused Trend (Uptrend/Downtrend) and the actual price action, the indicator will display a warning message, explaining the reason and suggesting corrective action.
Status Message 1: Pivot reference unavailable
Condition: The Stop Loss is set to the "ATR Pivot Margin" method, but the anchor point (Pivot) is missing or inaccessible.
Message Displayed: "Pivot reference unavailable. Wait for valid price action, or adjust the Regular Hours Limitation setting or Pivot Left/Right inputs."
Status Message 2: Calculated Stop Loss is unsafe
Condition: The calculated Stop Loss is placed illogically or unsafely relative to the trend direction and the Entry price.
Message Displayed: "Calculated Stop Loss is unsafe for current trend. Wait for valid price action or adjust SL Lookback/Multiplier."
7. Summary
The Adaptive Risk Management (ARM) indicator provides a seamless and systematic approach to trade execution and risk control. By dynamically automating all critical trade parameters—from Entry Price and Stop Loss placement to Position Sizing and Take Profit targets—ARM removes emotional bias and ensures every trade adheres strictly to your predefined risk profile.
Key Benefits:
Systematic Risk Control: Strict enforcement of maximum capital allocation and risk per trade limits.
Adaptivity: Dynamic calculation of prices and quantities based on real-time market data (ATR and Lookback).
Clarity and Trust: Clear on-chart visualization, precise data metrics (16 series), and unambiguous Status/Warning Messages ensure transparency and reliability.
ARM allows traders to focus on strategy and analysis, confident that their execution complies with the core principles of professional risk management.
Important Note: Trading Risk
This indicator is intended for educational and informational purposes only and does not constitute investment advice or a recommendation for trading in any form whatsoever.
Trading in financial markets involves significant risk of capital loss. It is important to remember that past performance is not indicative of future results. All trading decisions are your sole responsibility. Never trade with money you cannot afford to lose.
Gyspy Bot Trade Engine - V1.2B - Alerts - 12-7-25 - SignalLynxGypsy Bot Trade Engine (MK6 V1.2B) - Alerts & Visualization
Brought to you by Signal Lynx | Automation for the Night-Shift Nation 🌙
1. Executive Summary & Architecture
Gypsy Bot (MK6 V1.2B) is not merely a strategy; it is a massive, modular Trade Engine built specifically for the TradingView Pine Script V6 environment. While most tools rely on a single dominant indicator to generate signals, Gypsy Bot functions as a sophisticated Consensus Algorithm.
Note: This is the Indicator / Alerts version of the engine. It is designed for visual analysis and generating live alert signals for automation. If you wish to see Backtest data (Equity Curves, Drawdown, Profit Factors), please use the Strategy version of this script.
The engine calculates data from up to 12 distinct Technical Analysis Modules simultaneously on every bar closing. It aggregates these signals into a "Vote Count" and only fires a signal plot when a user-defined threshold of concurring signals is met. This "Voting System" acts as a noise filter, requiring multiple independent mathematical models—ranging from volume flow and momentum to cyclical harmonics and trend strength—to agree on market direction.
Beyond entries, Gypsy Bot features a proprietary Risk Management suite called the Dump Protection Team (DPT). This logic layer operates independently of the entry modules, specifically scanning for "Moon" (Parabolic) or "Nuke" (Crash) volatility events to signal forced exits, preserving capital during Black Swan events.
2. ⚠️ The Philosophy of "Curve Fitting" (Must Read)
One must be careful when applying Gypsy Bot to new pairs or charts.
To be fully transparent: Gypsy Bot is, by definition, a very advanced curve-fitting engine. Because it grants the user granular control over 12 modules, dozens of thresholds, and specific voting requirements, it is extremely easy to "over-fit" the data. You can easily toggle switches until the charts look perfect in hindsight, only to have the signals fail in live markets because they were tuned to historical noise rather than market structure.
To use this engine successfully:
Visual Verification: Do not just look for "green arrows." Look for signals that occur at logical market structure points.
Stability: Ensure signals are not flickering. This script uses closed-candle logic for key decisions to ensure that once a signal plots, it remains painted.
Regular Maintenance is Mandatory: Markets shift regimes (e.g., from Bull Trend to Crab Range). Gypsy Bot settings should be reviewed and adjusted at regular intervals to ensure the voting logic remains aligned with current market volatility.
Timeframe Recommendations:
Gypsy Bot is optimized for High Time Frame (HTF) trend following. It generally produces the most reliable results on charts ranging from 1-Hour to 12-Hours, with the 4-Hour timeframe historically serving as the "sweet spot" for most major cryptocurrency assets.
3. The Voting Mechanism: How Entries Are Generated
The heart of the Gypsy Bot engine is the ActivateOrders input (found in the "Order Signal Modifier" settings).
The engine constantly monitors the output of all enabled Modules.
Long Votes: GoLongCount
Short Votes: GoShortCount
If you have 10 Modules enabled, and you set ActivateOrders to 7:
The engine will ONLY plot a Buy Signal if 7 or more modules return a valid "Buy" signal on the same closed candle.
If only 6 modules agree, the signal is rejected.
4. Technical Deep Dive: The 12 Modules
Gypsy Bot allows you to toggle the following modules On/Off individually to suit the asset you are trading.
Module 1: Modified Slope Angle (MSA)
Logic: Calculates the geometric angle of a moving average relative to the timeline.
Function: Filters out "lazy" trends. A trend is only considered valid if the slope exceeds a specific steepness threshold.
Module 2: Correlation Trend Indicator (CTI)
Logic: Measures how closely the current price action correlates to a straight line (a perfect trend).
Function: Ensures that we are moving up with high statistical correlation, reducing fake-outs.
Module 3: Ehlers Roofing Filter
Logic: A spectral filter combining High-Pass (trend removal) and Super Smoother (noise removal).
Function: Isolates the "Roof" of price action to catch cyclical turning points before standard moving averages.
Module 4: Forecast Oscillator
Logic: Uses Linear Regression forecasting to predict where price "should" be relative to where it is.
Function: Signals when the regression trend flips. Offers "Aggressive" and "Conservative" calculation modes.
Module 5: Chandelier ATR Stop
Logic: A volatility-based trend follower that hangs a "leash" (ATR multiple) from extremes.
Function: Used as an entry filter. If price is above the Chandelier line, the trend is Bullish.
Module 6: Crypto Market Breadth (CMB)
Logic: Pulls data from multiple major tickers (BTC, ETH, and Perpetual Contracts).
Function: Calculates "Market Health." If Bitcoin is rising but the rest of the market is dumping, this module can veto a trade.
Module 7: Directional Index Convergence (DIC)
Logic: Analyzes the convergence/divergence between Fast and Slow Directional Movement indices.
Function: Identifies when trend strength is expanding.
Module 8: Market Thrust Indicator (MTI)
Logic: A volume-weighted breadth indicator using Advance/Decline and Volume data.
Function: One of the most powerful modules. Confirms that price movement is supported by actual volume flow. Recommended setting: "SSMA" (Super Smoother).
Module 9: Simple Ichimoku Cloud
Logic: Traditional Japanese trend analysis.
Function: Checks for a "Kumo Breakout." Price must be fully above/below the Cloud to confirm entry.
Module 10: Simple Harmonic Oscillator
Logic: Analyzes harmonic wave properties to detect cyclical tops and bottoms.
Function: Serves as a counter-trend or early-reversal detector.
Module 11: HSRS Compression / Super AO
Logic: Detects volatility compression (HSRS) or Momentum/Trend confluence (Super AO).
Function: Great for catching explosive moves resulting from consolidation.
Module 12: Fisher Transform (MTF)
Logic: Converts price data into a Gaussian normal distribution.
Function: Identifies extreme price deviations. Uses Multi-Timeframe (MTF) logic to ensure you aren't trading against the major trend.
5. Global Inhibitors (The Veto Power)
Even if 12 out of 12 modules vote "Buy," Gypsy Bot performs a final safety check using Global Inhibitors.
Bitcoin Halving Logic: Prevents trading during chaotic weeks surrounding Halving events (dates projected through 2040).
Miner Capitulation: Uses Hash Rate Ribbons to identify bearish regimes when miners are shutting down.
ADX Filter: Prevents trading in "Flat/Choppy" markets (Low ADX).
CryptoCap Trend: Checks the total Crypto Market Cap chart for broad market alignment.
6. Risk Management & The Dump Protection Team (DPT)
Even in this Indicator version, the RM logic runs to generate Exit Signals.
Dump Protection Team (DPT): Detects "Nuke" (Crash) or "Moon" (Pump) volatility signatures. If triggered, it plots an immediate Exit Signal (Yellow Plot).
Advanced Adaptive Trailing Stop (AATS): Dynamically tightens stops in low volatility ("Dungeon") and loosens them in high volatility ("Penthouse").
Staged Take Profits: Plots TP1, TP2, and TP3 events on the chart for visual confirmation or partial exit alerts.
7. Recommended Setup Guide
When applying Gypsy Bot to a new chart, follow this sequence:
Set Timeframe: 4 Hours (4H).
Tune DPT: Adjust "Dump/Moon Protection" inputs first. These filter out bad signals during high volatility.
Tune Module 8 (MTI): Experiment with the MA Type (SSMA is recommended).
Select Modules: Enable/Disable modules based on the asset's personality (Trending vs. Ranging).
Voting Threshold: Adjust ActivateOrders to filter out noise.
Alert Setup: Once visually satisfied, use the "Any Alert Function Call" option when creating an alert in TradingView to capture all Buy/Sell/Close events generated by the engine.
8. Technical Specs
Engine Version: Pine Script V6
Repainting: This indicator uses Closed Candle data for all Risk Management and Entry decisions. This ensures that signals do not vanish after the candle closes.
Visuals:
Blue Plot: Buy/Sell Signal.
Yellow Plot: Risk Management (RM) / DPT Close Signal.
Green/Lime/Olive Plots: Take Profit hits.
Disclaimer:
This script is a complex algorithmic tool for market analysis. Past performance is not indicative of future results. Cryptocurrency trading involves substantial risk of loss. Use this tool to assist your own decision-making, not to replace it.
9. About Signal Lynx
Automation for the Night-Shift Nation 🌙
Signal Lynx focuses on helping traders and developers bridge the gap between indicator logic and real-world automation. The same RM engine you see here powers multiple internal systems and templates, including other public scripts like the Super-AO Strategy with Advanced Risk Management.
We provide this code open source under the Mozilla Public License 2.0 (MPL-2.0) to:
Demonstrate how Adaptive Logic and structured Risk Management can outperform static, one-layer indicators
Give Pine Script users a battle-tested RM backbone they can reuse, remix, and extend
If you are looking to automate your TradingView strategies, route signals to exchanges, or simply want safer, smarter strategy structures, please keep Signal Lynx in your search.
License: Mozilla Public License 2.0 (Open Source).
If you make beneficial modifications, please consider releasing them back to the community so everyone can benefit.
Market Analysis Pro [Trademy]OVERVIEW
Trademy Market Analysis Pro is a professional-grade trading system that combines advanced momentum analysis with institutional-level Supply/Demand zone mapping. This indicator is designed to provide crystal-clear market analysis with precise risk management tools, creating a complete trading framework within a single, streamlined interface.
Unlike complex indicators that overwhelm traders with information, Trademy focuses on what matters: high-probability setups with clear entry points, defined risk levels, and multiple profit targets. The system is built to eliminate guesswork and provide actionable signals that work across multiple timeframes and asset classes eg: ( INDEX:BTCUSD , NASDAQ:NVDA and more )
CORE CONCEPTS
Advanced Momentum Engine: The foundation of Trademy Market Analysis Pro is a proprietary momentum detection system that identifies true directional shifts in the market. The algorithm analyzes price behavior relative to volatility-adjusted dynamic levels, generating signals only when genuine momentum reversals occur. The "Signal Sensitivity" control allows you to adapt the system from conservative (fewer, higher-quality signals) to aggressive (more frequent opportunities) based on your trading style and market conditions.
Institutional Supply/Demand Zones: The system automatically identifies and plots key institutional levels where significant buying (Demand) or selling (Supply) pressure has occurred. These zones are calculated using advanced price structure analysis, filtered through intelligent overlap detection to ensure only the most relevant zones appear on your chart. When price approaches these levels, they often act as strong support or resistance, providing logical areas for entries and exits.
Intelligent Signal Classification: Not all signals are created equal. Trademy categorizes every signal as either "Normal" or "Strong" based on its alignment with the broader market structure and trend context. Strong signals represent higher-conviction setups where momentum and trend align perfectly, while normal signals indicate counter-trend or early reversal opportunities.
Non-Repainting Architecture: Every signal is locked in at bar close (when enabled), and all TP/SL levels are calculated using volatility measurements captured at the moment of signal generation.
KEY FEATURES
Precision Signal System
Dual Signal Modes: Choose between Normal signals (standard momentum reversals) or Strong signals (high-conviction trend-aligned setups), or view both simultaneously
Wait for Bar Close: Optional no-repaint mode ensures signals only appear after candle confirmation
Visual Signal Hierarchy: Normal signals shown with standard arrows (▲/▼), Strong signals marked with distinctive colors for instant recognition
Adjustable Arrow Sizes: Customize signal display from tiny to large based on your chart preferences
Professional Risk Management
Automated TP/SL Calculation: Three take-profit levels (TP1, TP2, TP3) and one stop-loss level automatically calculated using advanced volatility measurement
Fixed Risk Levels: TP/SL lines are locked at signal generation and never move—providing consistent, reliable risk parameters
Visual Risk Zones: Optional colored zones highlight your risk and reward areas for instant position assessment
Adjustable Risk Multiplier: Scale your targets up or down with a single parameter while maintaining proper risk-reward ratios
Clear On-Chart Labels: Every level displays exact price values in an easy-to-read format
Supply/Demand Zone Mapping
Automatic Zone Detection: System identifies high-probability supply and demand zones using advanced price structure analysis
Anti-Overlap Algorithm: Intelligent filtering prevents zone clutter by removing overlapping levels
Extended Zone Projection: Zones extend into the future, showing you key levels before price reaches them
Break-of-Structure Tracking: Monitors when zones are broken and removes invalidated levels
Fully Customizable: Adjust zone colors, swing length, history depth, and box width to match your analysis style
Visual Customization
Flexible Color Schemes: Customize colors for bull/bear signals, TP/SL levels, and supply/demand zones
Trend Background: Optional background coloring to instantly visualize the current market bias
Support/Resistance Lines: Toggle automatic S/R level plotting from key price pivots
Multiple Arrow Sizes: Choose from tiny, small, normal, or large signal arrows
WHAT MAKES TRADEMY MARKET ANALYSIS PRO DIFFERENT
✅ Simplicity Meets Power
✅ TP/SL Levels
✅ Institutional Zone Integration
✅ Universal Indicator for all markets
✅ Multi-Timeframe Flexibility
BEST PRACTICES
📌 Always Use Stop-Loss: Enable the TP/SL system and respect your stop-loss levels,risk management is key to long-term success
📌 Backtest First: Before live trading, replay historical charts to understand signal behavior on your specific asset and timeframe
📌 Combine Timeframes: Use higher timeframe signals as your bias, enter on lower timeframe signals in the same direction
📌 Watch the Zones: Highest probability setups occur when signals align with supply/demand zones (buy near demand, sell near supply)
📌 Don't Chase: If you miss a signal, wait for the next one,forcing trades leads to losses
📌 Partial Profits: Consider taking partial profits at TP1, moving stop to breakeven, and letting the rest run to TP2/TP3
📩 ACCESS & SUPPORT
This is an invite-only indicator. For access inquiries, please contact via TradingView private message.
Important Disclaimers:
This indicator is a tool for technical analysis and does not constitute financial advice
Past performance does not guarantee future results
Always practice proper risk management and never risk more than you can afford to lose
Trading carries substantial risk of loss and is not suitable for all investors
Multi-Timeframe Smart Analysis [Abusuhil]الوصف بالعربي في الاسفل .
📊 Multi-Timeframe Smart Analysis
🇬🇧 ENGLISH DESCRIPTION
Overview
Multi-Timeframe Smart Analysis is a professional trading indicator designed for cryptocurrency and forex markets, combining RSI and MACD with multi-timeframe (MTF) confirmation to generate high-probability trading signals. The indicator provides clear entry points, automatic Fibonacci-based targets, and risk management levels.
Key Features
1. Multi-Timeframe Analysis (MTF)
Analyzes up to 3 higher timeframes simultaneously
Provides trend confirmation from HTF1, HTF2, and HTF3
Real-time dashboard showing current trend status
Optional: Can be disabled to trade based on current timeframe only
2. Smart Signal Generation
Buy Signals: Generated when MACD crosses above signal line with bullish RSI and HTF confirmation
Sell Signals: Generated when MACD crosses below signal line with bearish RSI and HTF confirmation
Anti-spam system: Minimum bars between signals (default: 10 bars)
Optional: Show only last signal to keep chart clean
3. Automatic Risk Management
Entry Line: Displays exact entry price
Stop Loss: Calculated using ATR (default: 1.5x ATR)
Take Profit Levels:
T1: 1.618x ATR (First target)
T2: 2.618x ATR (Second target)
T3: 4.236x ATR (Final target)
4. Visual Dashboard
Shows current timeframe RSI and MACD status
Displays HTF1 and HTF2 trend direction (BULL/BEAR)
Real-time signal status (🟢 BUY / 🔴 SELL / ⚪ WAIT)
Clean, professional interface in top-right corner
5. Customization Options
Multiple signal styles: Label, Triangle, Arrow, Circle
Adjustable signal size: Tiny, Small, Normal, Large
Customizable colors for buy/sell signals
Flexible target extension bars
Toggle all features on/off independently
📋 Recommended Settings by Timeframe
For 1-Minute Chart (Scalping)
HTF1: 5 minutes
HTF2: 15 minutes
HTF3: 1 hour
RSI Length: 14
MACD: 12/26/9
Stop Loss ATR: 1.0
Best for: High-frequency scalping on volatile pairs like BTC/USDT, ETH/USDT
For 5-Minute Chart (Day Trading)
HTF1: 15 minutes
HTF2: 1 hour
HTF3: 4 hours
RSI Length: 14
MACD: 12/26/9
Stop Loss ATR: 1.5
Best for: Intraday trading on major crypto pairs and forex
For 15-Minute Chart (Swing Trading)
HTF1: 1 hour
HTF2: 4 hours
HTF3: 1 day
RSI Length: 14
MACD: 12/26/9
Stop Loss ATR: 1.5
Best for: Short-term swing trades, ideal for crypto and forex
For 1-Hour Chart (Position Trading)
HTF1: 4 hours
HTF2: 1 day
HTF3: 3 days
RSI Length: 14
MACD: 12/26/9
Stop Loss ATR: 2.0
Best for: Medium-term positions, suitable for all markets
For 4-Hour Chart (Swing/Position)
HTF1: 1 day
HTF2: 3 days
HTF3: 1 week
RSI Length: 14
MACD: 12/26/9
Stop Loss ATR: 2.5
Best for: Swing trading with lower frequency, higher accuracy
For Daily Chart (Long-Term)
HTF1: 3 days
HTF2: 1 week
HTF3: 1 month
RSI Length: 14
MACD: 12/26/9
Stop Loss ATR: 3.0
Best for: Position trading and long-term investments
🎯 How to Trade with This Indicator
Entry Rules
For LONG (Buy) Entries:
Wait for 🟢 BUY signal to appear
Verify HTF1 and HTF2 show BULL trend in dashboard
Check RSI is below 70 (not overbought)
Enter at the displayed Entry Line price
Place stop loss at SL level
Set take profit at T1, T2, T3 (scale out)
For SHORT (Sell) Entries:
Wait for 🔴 SELL signal to appear
Verify HTF1 and HTF2 show BEAR trend in dashboard
Check RSI is above 30 (not oversold)
Enter at the displayed Entry Line price
Place stop loss at SL level
Set take profit at T1, T2, T3 (scale out)
Exit Strategy (Recommended)
Conservative Approach:
Close 50% position at T1
Move SL to breakeven
Close 30% at T2
Let 20% run to T3 with trailing stop
Aggressive Approach:
Hold full position to T2
Close 70% at T2
Trail remaining 30% to T3
Quick Scalp:
Close entire position at T1
Re-enter on next signal
⚙️ Settings Guide
Timeframe Settings
Enable Higher Timeframe Analysis: Toggle MTF confirmation on/off
HTF1, HTF2, HTF3: Set your desired higher timeframes
RSI Settings
RSI Length: Period for RSI calculation (default: 14)
RSI Overbought: Upper threshold (default: 70)
RSI Oversold: Lower threshold (default: 30)
Use RSI Filter: Enable/disable RSI confirmation
MACD Settings
Fast Length: Fast EMA period (default: 12)
Slow Length: Slow EMA period (default: 26)
Signal Length: Signal line period (default: 9)
Use MACD Filter: Enable/disable MACD confirmation
Target Settings
Show Price Targets: Toggle target lines on/off
Fib Target 1/2/3: Customize Fibonacci multipliers
Target Extension Bars: How far targets extend (default: 50)
Stop Loss ATR: Stop loss distance multiplier (default: 1.5)
Signal Settings
Show Buy/Sell Signals: Toggle signals independently
Show Only Last Signal: Hide previous signals, show only latest
Signal Style: Choose visual style (Label/Triangle/Arrow/Circle)
Minimum Bars Between Signals: Anti-spam filter (default: 10)
📌 Important Notes
Not a Holy Grail: This indicator is a tool, not a guarantee. Always use proper risk management
Backtest First: Test on historical data before live trading
Combine with Price Action: Use support/resistance levels for additional confirmation
Adjust to Market Conditions: Volatile markets may need wider stops, ranging markets need tighter targets
News Events: Avoid trading during major news releases
Risk Management: Never risk more than 1-2% of your capital per trade
🎓 Best Practices
Start Conservative: Begin with default settings
One Timeframe at a Time: Master one chart before expanding
Journal Your Trades: Track which settings work best for your style
Use Demo Account: Practice before risking real money
Stay Disciplined: Follow your trading plan strictly
🔔 Alert System
The indicator includes built-in alerts:
Buy Signal Alert: Notifies when long opportunity appears
Sell Signal Alert: Notifies when short opportunity appears
To activate alerts:
Click "Create Alert" in TradingView
Select "Multi-Timeframe Smart Analysis"
Choose "Buy Signal" or "Sell Signal"
Set notification preferences
💡 Pro Tips
Confluence Trading: Wait for signals that align with key S/R levels
Trend Trading: In strong trends, prioritize signals in trend direction
Multiple Timeframe Entries: Use HTF for bias, lower TF for precise entry
Partial Profits: Always secure some profit at T1
Trailing Stops: Move SL to breakeven after T1 is hit
⚠️ Risk Disclaimer
Trading cryptocurrencies, forex, and other financial instruments involves substantial risk of loss and is not suitable for all investors. Past performance is not indicative of future results. The indicator provides technical analysis only and should not be considered financial advice. You are solely responsible for your trading decisions. Always conduct your own research and consider consulting with a licensed financial advisor.
📞 Support & Updates
For questions, suggestions, or bug reports, please contact via TradingView messages.
Version: 1.0
Author: Abusuhil
Last Updated: December 2024
📊 التحليل الذكي متعدد الأطر الزمنية
🇸🇦 الوصف بالعربية
نظرة عامة
التحليل الذكي متعدد الأطر الزمنية هو مؤشر تداول احترافي مصمم لأسواق العملات الرقمية والفوركس، يجمع بين مؤشري RSI و MACD مع تأكيد من أطر زمنية أعلى لتوليد إشارات تداول عالية الاحتمالية. يوفر المؤشر نقاط دخول واضحة، أهداف تلقائية مبنية على فيبوناتشي، ومستويات إدارة المخاطر.
المزايا الرئيسية
1. التحليل متعدد الأطر الزمنية (MTF)
يحلل حتى 3 أطر زمنية أعلى في وقت واحد
يوفر تأكيد الاتجاه من HTF1، HTF2، و HTF3
لوحة معلومات فورية تظهر حالة الاتجاه الحالي
اختياري: يمكن تعطيله للتداول بناءً على الإطار الزمني الحالي فقط
2. توليد إشارات ذكية
إشارات الشراء: تُنشأ عندما يعبر MACD فوق خط الإشارة مع RSI صاعد وتأكيد HTF
إشارات البيع: تُنشأ عندما يعبر MACD تحت خط الإشارة مع RSI هابط وتأكيد HTF
نظام مضاد للإزعاج: حد أدنى من الشموع بين الإشارات (افتراضي: 10 شموع)
اختياري: إظهار آخر إشارة فقط للحفاظ على نظافة الشارت
3. إدارة تلقائية للمخاطر
خط الدخول: يعرض سعر الدخول الدقيق
وقف الخسارة: محسوب باستخدام ATR (افتراضي: 1.5x ATR)
مستويات جني الأرباح:
T1: 1.618x ATR (الهدف الأول)
T2: 2.618x ATR (الهدف الثاني)
T3: 4.236x ATR (الهدف النهائي)
4. لوحة معلومات مرئية
تعرض حالة RSI و MACD للإطار الزمني الحالي
تظهر اتجاه HTF1 و HTF2 (صاعد/هابط)
حالة الإشارة الفورية (🟢 شراء / 🔴 بيع / ⚪ انتظار)
واجهة نظيفة واحترافية في الزاوية العلوية اليمنى
5. خيارات التخصيص
أنماط إشارات متعددة: تسمية، مثلث، سهم، دائرة
حجم إشارة قابل للتعديل: صغير جداً، صغير، عادي، كبير
ألوان قابلة للتخصيص لإشارات الشراء/البيع
أشرطة تمديد الهدف مرنة
تبديل جميع الميزات تشغيل/إيقاف بشكل مستقل
📋 الإعدادات الموصى بها حسب الإطار الزمني
لشارت دقيقة واحدة (سكالبينج)
HTF1: 5 دقائق
HTF2: 15 دقيقة
HTF3: 1 ساعة
طول RSI: 14
MACD: 12/26/9
وقف الخسارة ATR: 1.0
الأفضل لـ: السكالبينج عالي التردد على الأزواج المتقلبة مثل BTC/USDT، ETH/USDT
لشارت 5 دقائق (التداول اليومي)
HTF1: 15 دقيقة
HTF2: 1 ساعة
HTF3: 4 ساعات
طول RSI: 14
MACD: 12/26/9
وقف الخسارة ATR: 1.5
الأفضل لـ: التداول اليومي على أزواج العملات الرقمية الرئيسية والفوركس
لشارت 15 دقيقة (التداول المتأرجح)
HTF1: 1 ساعة
HTF2: 4 ساعات
HTF3: 1 يوم
طول RSI: 14
MACD: 12/26/9
وقف الخسارة ATR: 1.5
الأفضل لـ: صفقات التأرجح قصيرة المدى، مثالي للعملات الرقمية والفوركس
لشارت ساعة واحدة (التداول بالمراكز)
HTF1: 4 ساعات
HTF2: 1 يوم
HTF3: 3 أيام
طول RSI: 14
MACD: 12/26/9
وقف الخسارة ATR: 2.0
الأفضل لـ: المراكز متوسطة المدى، مناسب لجميع الأسواق
لشارت 4 ساعات (التأرجح/المراكز)
HTF1: 1 يوم
HTF2: 3 أيام
HTF3: 1 أسبوع
طول RSI: 14
MACD: 12/26/9
وقف الخسارة ATR: 2.5
الأفضل لـ: التداول المتأرجح بتردد أقل ودقة أعلى
للشارت اليومي (طويل المدى)
HTF1: 3 أيام
HTF2: 1 أسبوع
HTF3: 1 شهر
طول RSI: 14
MACD: 12/26/9
وقف الخسارة ATR: 3.0
الأفضل لـ: تداول المراكز والاستثمارات طويلة المدى
🎯 كيفية التداول باستخدام هذا المؤشر
قواعد الدخول
لصفقات الشراء (LONG):
انتظر ظهور إشارة 🟢 شراء
تحقق من أن HTF1 و HTF2 تظهر اتجاه صاعد في لوحة المعلومات
تأكد من أن RSI أقل من 70 (ليس في منطقة التشبع الشرائي)
ادخل عند سعر خط الدخول المعروض
ضع وقف الخسارة عند مستوى SL
اضبط جني الأرباح عند T1، T2، T3 (اخرج تدريجياً)
لصفقات البيع (SHORT):
انتظر ظهور إشارة 🔴 بيع
تحقق من أن HTF1 و HTF2 تظهر اتجاه هابط في لوحة المعلومات
تأكد من أن RSI أعلى من 30 (ليس في منطقة التشبع البيعي)
ادخل عند سعر خط الدخول المعروض
ضع وقف الخسارة عند مستوى SL
اضبط جني الأرباح عند T1، T2، T3 (اخرج تدريجياً)
استراتيجية الخروج (موصى بها)
النهج المحافظ:
أغلق 50% من المركز عند T1
حرك وقف الخسارة إلى نقطة التعادل
أغلق 30% عند T2
دع 20% يعمل حتى T3 مع وقف خسارة متحرك
النهج العدواني:
احتفظ بالمركز الكامل حتى T2
أغلق 70% عند T2
تتبع الـ 30% المتبقية حتى T3
سكالبينج سريع:
أغلق المركز بالكامل عند T1
أعد الدخول عند الإشارة التالية
⚙️ دليل الإعدادات
إعدادات الإطار الزمني
تفعيل تحليل الإطار الزمني الأعلى: تبديل تأكيد MTF تشغيل/إيقاف
HTF1، HTF2، HTF3: اضبط الأطر الزمنية الأعلى المرغوبة
إعدادات RSI
طول RSI: فترة حساب RSI (افتراضي: 14)
RSI في التشبع الشرائي: العتبة العليا (افتراضي: 70)
RSI في التشبع البيعي: العتبة السفلى (افتراضي: 30)
استخدام فلتر RSI: تمكين/تعطيل تأكيد RSI
إعدادات MACD
الطول السريع: فترة المتوسط المتحرك السريع (افتراضي: 12)
الطول البطيء: فترة المتوسط المتحرك البطيء (افتراضي: 26)
طول الإشارة: فترة خط الإشارة (افتراضي: 9)
استخدام فلتر MACD: تمكين/تعطيل تأكيد MACD
إعدادات الأهداف
إظهار أهداف الأسعار: تبديل خطوط الأهداف تشغيل/إيقاف
هدف فيبوناتشي 1/2/3: تخصيص مضاعفات فيبوناتشي
أشرطة تمديد الأهداف: مدى امتداد الأهداف (افتراضي: 50)
وقف الخسارة ATR: مضاعف مسافة وقف الخسارة (افتراضي: 1.5)
إعدادات الإشارات
إظهار إشارات الشراء/البيع: تبديل الإشارات بشكل مستقل
إظهار آخر إشارة فقط: إخفاء الإشارات السابقة، إظهار الأحدث فقط
نمط الإشارة: اختر النمط المرئي (تسمية/مثلث/سهم/دائرة)
الحد الأدنى من الشموع بين الإشارات: فلتر مضاد للإزعاج (افتراضي: 10)
📌 ملاحظات مهمة
ليس الكأس المقدسة: هذا المؤشر أداة، وليس ضماناً. استخدم دائماً إدارة مخاطر مناسبة
اختبار رجعي أولاً: اختبر على البيانات التاريخية قبل التداول المباشر
ادمج مع حركة السعر: استخدم مستويات الدعم/المقاومة لتأكيد إضافي
تكيّف مع ظروف السوق: الأسواق المتقلبة قد تحتاج إلى وقف خسارة أوسع، الأسواق الجانبية تحتاج إلى أهداف أضيق
أحداث الأخبار: تجنب التداول أثناء إصدارات الأخبار الكبرى
إدارة المخاطر: لا تخاطر أبداً بأكثر من 1-2% من رأس مالك لكل صفقة
🎓 أفضل الممارسات
ابدأ بحذر: ابدأ بالإعدادات الافتراضية
إطار زمني واحد في كل مرة: أتقن شارت واحد قبل التوسع
سجل صفقاتك: تتبع أي الإعدادات تعمل بشكل أفضل لأسلوبك
استخدم حساب تجريبي: تدرب قبل المخاطرة بأموال حقيقية
التزم بالانضباط: اتبع خطة تداولك بصرامة
🔔 نظام التنبيهات
يتضمن المؤشر تنبيهات مدمجة:
تنبيه إشارة الشراء: يُعلمك عند ظهور فرصة شراء
تنبيه إشارة البيع: يُعلمك عند ظهور فرصة بيع
لتفعيل التنبيهات:
انقر على "إنشاء تنبيه" في TradingView
اختر "Multi-Timeframe Smart Analysis"
اختر "Buy Signal" أو "Sell Signal"
اضبط تفضيلات الإشعارات
💡 نصائح احترافية
تداول التقاء: انتظر الإشارات التي تتماشى مع مستويات الدعم والمقاومة الرئيسية
تداول الاتجاه: في الاتجاهات القوية، أعط الأولوية للإشارات في اتجاه الترند
مداخل الإطار الزمني المتعدد: استخدم HTF للتحيز، إطار زمني أقل للدخول الدقيق
أرباح جزئية: احفظ دائماً بعض الربح عند T1
وقف خسارة متحرك: حرك وقف الخسارة إلى التعادل بعد الوصول إلى T1
⚠️ إخلاء مسؤولية المخاطر
تداول العملات الرقمية والفوركس وغيرها من الأدوات المالية ينطوي على مخاطر كبيرة للخسارة وليس مناسباً لجميع المستثمرين. الأداء السابق لا يشير إلى النتائج المستقبلية. يوفر المؤشر التحليل الفني فقط ولا ينبغي اعتباره نصيحة مالية. أنت المسؤول الوحيد عن قرارات التداول الخاصة بك. قم دائماً بإجراء بحثك الخاص وفكر في استشارة مستشار مالي مرخص.
📞 الدعم والتحديثات
للأسئلة أو الاقتراحات أو الإبلاغ عن الأخطاء، يرجى التواصل عبر رسائل TradingView.
الإصدار: 1.0
المطور: Abusuhil
آخر تحديث: ديسمبر 2024
TrategyMulti-Indicator Trading System - Detailed Description
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OVERVIEW
This indicator combines four proven technical analysis tools (EMA, RSI, MACD, ATR) with a specific logic that filters out low-probability setups. Unlike simple indicator mashups, this system requires all conditions to align simultaneously before generating a signal, significantly reducing false entries.
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CORE COMPONENTS & LOGIC
1. Trend Detection - Triple EMA Filter
The system uses three Exponential Moving Averages (5, 10, 20 periods) to establish trend direction and strength:
For LONG signals:
• EMA(5) must be above EMA(10)
• EMA(10) must be above EMA(20)
• Price must be trading above all three EMAs
This creates a "stacked EMA" configuration that confirms a strong uptrend.
For SHORT signals:
• EMA(5) must be below EMA(10)
• EMA(10) must be below EMA(20)
• Price must be trading below all three EMAs
This inverse configuration confirms a strong downtrend.
2. Momentum Confirmation - RSI Filter
The RSI (14-period) acts as a momentum filter to avoid entering during exhausted moves:
For LONG signals:
• RSI must be above 40 (avoiding oversold extremes)
• RSI must be rising (current RSI > previous RSI)
For SHORT signals:
• RSI must be below 60 (avoiding overbought extremes)
• RSI must be falling (current RSI < previous RSI)
This prevents entries at extreme overbought/oversold levels while confirming momentum direction.
3. Entry Trigger - MACD Crossover
The MACD (12, 26, 9) provides the precise entry timing:
LONG trigger: MACD line crosses above Signal line
SHORT trigger: MACD line crosses below Signal line
The signal only fires when this crossover occurs while all other conditions are already met.
4. Risk Management - ATR-Based TP/SL
Take Profit and Stop Loss levels are calculated dynamically using the 14-period ATR (Average True Range), adjusted for timeframe:
5-Minute Charts:
• Take Profit: 1.0 × ATR
• Stop Loss: 0.5 × ATR
4-Hour Charts and above:
• Take Profit: 2.0 × ATR
• Stop Loss: 1.0 × ATR
This adaptive approach accounts for different volatility levels across timeframes.
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SIGNAL GENERATION LOGIC
A signal is only generated when ALL four conditions are simultaneously true:
LONG Signal Requirements:
1. ✓ Triple EMA alignment (bullish stack)
2. ✓ Price above all EMAs
3. ✓ RSI > 40 and rising
4. ✓ MACD bullish crossover
SHORT Signal Requirements:
1. ✓ Triple EMA alignment (bearish stack)
2. ✓ Price below all EMAs
3. ✓ RSI < 60 and falling
4. ✓ MACD bearish crossover
This multi-layered filtering approach is what differentiates this system from basic indicator combinations.
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WHY THIS COMBINATION WORKS
Trend + Momentum + Timing:
• EMAs establish the overall trend context
• RSI confirms momentum is present (not exhausted)
• MACD provides precise entry timing
• ATR adapts risk management to current volatility
Key Innovation: The system waits for all filters to align rather than acting on individual signals, which significantly reduces whipsaws and false breakouts common in single-indicator strategies.
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OPTIMIZED TIMEFRAMES
While the indicator works on all timeframes, it has been specifically optimized and backtested on:
• 5-minute charts (for scalping/day trading)
• 4-hour charts (for swing trading)
The ATR multipliers automatically adjust based on the selected timeframe.
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VISUAL FEATURES
• Green arrows below bars: Long signal
• Red arrows above bars: Short signal
• Green line: Take Profit level
• Red line: Stop Loss level
• Alert capability: Configurable alerts for paid TradingView subscriptions
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HOW TO USE
1. Add the indicator to your chart
2. Wait for a colored arrow to appear
3. Enter the trade in the direction of the arrow
4. Set your Take Profit at the green line
5. Set your Stop Loss at the red line
6. (Optional) Set up alerts to receive notifications
Note: Not every arrow will show TP/SL lines. Lines only appear when the ATR-based calculation determines there is sufficient volatility to justify the trade setup.
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WHAT MAKES THIS INVITE-ONLY WORTHY
Unlike free indicators that simply plot standard EMAs, RSI, or MACD separately, this system:
1. Integrates all four indicators with specific thresholds designed to work together
2. Uses adaptive risk management that adjusts to timeframe and volatility
The value lies not in the individual components (which are public domain) but in the specific combination logic, thresholds, and ATR-based risk system that took months of testing to optimize.
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ACCESS INFORMATION
This is an invite-only indicator. To request access:
• Visit our website
We offer both monthly subscriptions and lifetime access.
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RISK DISCLAIMER
This indicator is a technical analysis tool and does not constitute financial advice. All trading involves substantial risk of loss. Past performance does not guarantee future results. The indicator provides signals based on historical price patterns, but cannot predict future market movements. Always use proper risk management and never risk more than you can afford to lose.
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Questions? Feel free to message us on TradingView, or to email us.
Apex Trend & Liquidity Master with TP/SLThe Apex Trend & Liquidity Master is a systematic trading framework that identifies trend direction and key structural price levels for entry and exit decisions. The system uses a volatility-adaptive trend detection mechanism built on Hull Moving Averages with ATR-based bands to filter consolidation periods and isolate directional moves.
The liquidity detection engine identifies potential reversal zones by marking swing highs and lows that meet statistical significance thresholds. These zones represent areas where institutional order flow previously caused price rejection. Zones remain active until price closes through them, indicating mitigation of the level.
This implementation is an enhanced derivative of the original system with fully automated risk management. Stop losses are calculated using ATR multiples with entry candle wick protection as a minimum threshold, while take profits maintain a fixed 3:1 risk-reward ratio. An additional exit mechanism closes profitable positions when price reaches opposing supply or demand zones, providing early profit-taking at probable reversal points before full target completion.
Entry signals generate only on trend changes when volume exceeds average levels, reducing false breakouts in ranging conditions. The system includes complete position tracking with three distinct exit types: take profit hits, stop loss hits, and profitable zone contact exits. All calculations use confirmed historical data with no forward-looking bias, though supply/demand zone identification operates with a confirmation lag inherent to pivot point detection.
HTF/CTF High/Low Mitigation with SignalsHTF/CTF High/Low Mitigation with Signals Indicator
Overview
HTF/CTF High/Low Mitigation with Signals (shortened as "H/L Signals+") is an advanced overlay indicator for TradingView, designed to identify and visualize higher timeframe (HTF) and current timeframe (CTF) swing highs/lows, track their mitigation, and generate filtered buy/sell signals using an EMA ribbon trend filter. It incorporates automated trade simulation with risk/reward (RR) visualization, position sizing based on user-defined risk, and a statistics table for performance evaluation. This tool is ideal for multi-timeframe traders focusing on swing trading, breakout strategies, or trend reversals across assets like forex, futures, metals (e.g., XAU/USD, XAG/USD), stocks, or cryptocurrencies.
The "meshup" (mashup) integrates several complementary elements: Multi-timeframe swing level detection (HTF for broader structure, CTF for finer details) with mitigation logic ensures signals align with market structure breaks; an EMA ribbon provides a dynamic trend bias to filter counter-trend trades; risk management automates position sizing and RR calculations for disciplined trading; and built-in backtesting stats offer quick insights into hypothetical performance. This combination reduces noise from isolated indicators—e.g., raw swings can be choppy, EMAs alone lag structure, and manual RR is error-prone—creating a cohesive system for spotting high-probability setups where structure, trend, and risk align. By meshing these, it aims to enhance decision-making in trending or ranging markets, though it's reactive and best used with confirmation. Note: This is a technical tool for educational purposes only; it does not provide financial advice, guarantees of profitability, or trading recommendations. Past performance is not indicative of future results, and users should backtest thoroughly on their specific assets/timeframes, in compliance with TradingView's house rules.
Key Features
• HTF Swing Levels: Detects and draws session highs/lows from a user-selected higher timeframe (e.g., Daily), extends lines until mitigated (by wick or body close), with alerts on mitigation.
• CTF Swing Levels: Identifies local swing highs/lows on the chart timeframe using a pivot candle formation (default 5-candle), with separate limits for unmitigated/mitigated lines.
• EMA Ribbon: A three-EMA system (fast 8, mid 13, slow 21) with gradient fills (green for bullish, red for bearish) to visualize trend strength and filter signals.
• Signal Generation: Buy/sell labels ("BUY"/"SELL") triggered post-mitigation when price aligns with EMA trend (e.g., above slow EMA with stacked bulls for buys).
• Trade Simulation & Risk Management: On signals, calculates stop-loss (SL) from recent extremes, position size based on fixed risk amount (e.g., $100 per trade, adjusted for asset type like futures point value or forex lots), and full take-profit (TP) at user-defined RR level (1-5). Draws RR boxes for visuals.
• Statistics Table: Displays total trades, wins/losses, win rate (%), net R-return, and max consecutive losses in a top-right table.
• Alerts: Customizable alerts for HTF mitigations and new trades (including entry, SL, TP, size).
• Visual Customizations: Toggle lines/ribbon/boxes, adjust colors/styles/widths for unmitigated/mitigated lines (HTF/CTF), min box width.
• Performance Optimization: Automatically cleans up excess lines to stay within max limits (e.g., 15 unmitigated HTF, 5 CTF).
How It Works
• HTF Logic: On new HTF bars (via time(htf_timeframe)), captures session high/low and draws extendable lines. Lines extend rightward until mitigated (high/close > high level for highs, low/close < low level for lows, toggle wick/body). Mitigation sets "waiting" flags for signals and triggers alerts.
• CTF Logic: Scans for pivot highs/lows using a user-defined candle count (e.g., 2 left/right for 5-candle swings). Draws and extends lines similarly, mitigating on wick touches, with separate styles for mitigated (e.g., dotted gray).
• EMA Ribbon Logic: Computes 8/13/21 EMAs; fills mid-slow and fast-mid with bullish green (close > slow EMA) or bearish red gradients.
• Signal Conditions: Post-mitigation (waiting_for_buy/sell true), checks EMA stack—buys require close > slow, fast > mid > slow; sells require close < slow, fast < mid < slow. Signals only on confirmed bars.
• Trade Execution: On signal, sets entry at close, scans back to mitigation bar for tightest SL (lowest low for buys, highest high for sells). Calculates risk points (entry - SL for buys), then position size via helper function (asset-specific: e.g., XAU *100, futures *pointvalue, forex 100000pointvalue). Sets full TP at entry ± (risk * full_tp_level). Draws risk/reward boxes (e.g., long: dark risk below entry, blue reward above) with RR and size text. Alerts with trade details.
• Trade Management: Monitors for SL hit (low <= SL for longs) or TP hit (high >= TP for longs); updates stats (wins if TP, losses if SL, tracks consec losses, net R as +full_tp_level or -1). Places summary label ("Hit TP5 (Win)" or "Stopped Out (Loss)").
• Cleanup: Counts unmitigated/mitigated lines; deletes oldest excess to respect max limits (e.g., max_lines_input=15 for HTF unmitigated, max_mit_lines_ctf=5 for CTF mitigated).
• Why This Meshup?: Standalone tools often fall short—HTF swings ignore local noise, but without CTF, miss entries; EMAs filter trends but overlook structure; manual RR lacks automation. Meshing them creates a "mitigation-to-signal" flow: HTF/CTF provide structural context (e.g., BOS/CHOCH), EMA ensures trend alignment (reducing whipsaws), and RR simulation adds practical risk control with stats for optimization. This holistic approach potentially improves edge in structure-based trading, especially in volatile markets, by combining macro/micro analysis with quantifiable risk—though it may lag in ranges or require tuning.
All logic uses arrays for line management, barstate.isconfirmed for reliability, and syminfo for asset-specific sizing. No repainting, but historical trades simulate based on chart data.
Settings and Customization
Inputs are grouped for usability:
1. Higher Timeframe (HTF) Settings:
o Show HTF Lines: Toggle visibility (default: true).
o Use Wick for Mitigation: True for wick touch, false for body close (default: false; tooltip explains).
o Timeframe: HTF period (default: "D").
o Max Unmitigated HTF Lines: Limit for active lines (default: 15, min 1, max 250).
2. Current Timeframe (CTF) Settings:
o Show CTF Swings: Toggle (default: true).
o CTF Swing Candle Count: Left/right candles for pivot (default: 2, min 1; tooltip: '2' = 5-candle formation).
o Max Unmitigated CTF Lines: (default: 5, min 1, max 250).
o Max Mitigated CTF Lines: (default: 5, min 1, max 250).
3. EMA Settings:
o Show EMA Ribbon: Toggle (default: true).
o Fast/Middle/Slow EMA Length: Defaults 8/13/21.
4. Risk/Reward Settings:
o Risk Amount per Trade ($): Fixed risk (default: 100.0, min 0.1; tooltip: for position sizing).
o Full Take Profit Level (1-5): RR for full win (default: 5; tooltip: counts as win in stats).
o Show Trade Visuals & Stats: Toggle boxes, labels, table (default: true).
5. 🎨 Visuals:
o Draw Risk/Reward Box: Toggle (default: true).
o Minimum Box Width (in bars): (default: 5, min 1).
o Long - Risk/Reward Box Colors: Defaults dark gray (risk), blue (reward).
o Short - Risk/Reward Box Colors: Defaults dark gray (risk), orange (reward).
6. Alert Settings:
o Alert on HTF Level Mitigation: Toggle (default: true).
7. HTF Line Style Settings:
o High (Unmitigated): Color (maroon 20%), width (1).
o High (Mitigated): Color (gray 40%), style (dotted/dashed, default dotted).
o Low (Unmitigated): Color (teal 20%), width (1).
o Low (Mitigated): Color (gray 40%), style (dotted/dashed, default dotted).
8. CTF Line Styles:
o CTF High (Unmitigated): Color (purple #8d198d 25%), width (1), style (Solid/Dotted/Dashed, default Solid).
o CTF High (Mitigated): Color (gray 50%), width (1), style (default Dotted).
o CTF Low (Unmitigated): Color (teal #008080 25%), width (1), style (default Solid).
o CTF Low (Mitigated): Color (gray 50%), width (1), style (default Dotted).
Usage Tips
• Multi-Timeframe Strategy: Use HTF (e.g., D1) for major levels, CTF for entries. Signals post-mitigation with EMA filter—enter on "BUY"/"SELL" labels, use boxes for RR visualization.
• Risk Management: Set risk_amount_per_trade to 1-2% of capital; adjust full_tp_level for strategy (e.g., 3 for conservative). Position size auto-adapts to asset (e.g., smaller for high-vol like XAU).
• Customization: Enable wick mitigation for aggressive setups; increase max lines in trending markets. Tune EMAs for asset (shorter for crypto).
• Alerts Integration: Use for notifications on mitigations or trades; messages include all details for quick action.
• Stats Analysis: Table shows hypothetical results—use for optimization (e.g., aim for >50% win rate, low consec losses). Reset on chart reload.
• Chart Compatibility: Best on candlestick charts; test on lower TFs with higher HTF for confluence.
Limitations
• Reactive Signals: Waits for mitigation + EMA alignment, so may miss early reversals or lag in fast markets.
• Chop in Ranges: Frequent mitigations without trend can generate false signals; EMA helps but not foolproof.
• Simulation Only: Trades are backtested on visible data—no live execution; stats assume full TP or SL hits, ignoring partials or slippage.
• Line Limits: Caps at user max to prevent overload; oldest deleted first.
• Asset Specificity: Position sizing tailored to forex/futures/metals; may need tweaks for others.
• Disclaimer: For informational use only. Trading involves risk of loss; results vary by market, timeframe, and settings. Consult professionals and backtest extensively. No profitability claims per TradingView rules.
Dark Vector ScalpingThe Dark Vector Scalping indicator is a high-frequency trend-following system designed specifically to capture rapid momentum shifts in the market. It combines a staircase-style breakout logic with volatility-adjusted trailing stops to define market direction.
While the underlying math is robust enough for various asset classes, this specific configuration is optimized for scalping operations on 1-minute and 5-minute timeframes. It aims to filter out the "noise" common in lower timeframes while reacting quickly to genuine breakouts.
Core Components
1. The Apex Engine (Staircase Logic) Unlike traditional moving averages that curve with price, this engine uses a "hard" breakout logic. It looks back at a specific number of bars (Sensitivity) to find the highest highs and lowest lows.
Bullish Flip: Occurs when the price closes below the calculated low of the previous trend.
Bearish Flip: Occurs when the price closes above the calculated high of the previous trend.
Trailing Stop: Once a trend is established, a trailing stop line is drawn. This line only moves in the direction of the trend (up for bullish, down for bearish) and never retraces, acting as a ratchet to lock in paper profits.
2. Volatility Normalization To prevent getting stopped out by random market noise (scam wicks), the indicator calculates the Average True Range (ATR). It multiplies this volatility metric by a user-defined deviation factor to determine exactly how far the stop line should be from the current price action.
3. The Hull Moving Average (HMA) Filter The script includes an optional 50-period Hull Moving Average. The HMA is known for being extremely fast and smooth, reducing lag compared to standard moving averages.
Visual Reference: You can plot the line to see the overall macro trend.
Hard Filter: You can enable a "Safety Filter" in the settings. If enabled, the system will only generate Buy signals if the price is above the HMA, and Sell signals if the price is below the HMA.
4. The Dashboard A data panel is located on the chart (customizable position) to provide instant numerical data without needing to calculate levels manually. It displays the current trend state, the exact price of the trailing stop, and the status of the HMA filter.
Settings & Configuration
Sensitivity (Lookback)
Default: 5
This is the primary setting for the Apex Engine. A setting of 5 is the "sweet spot" for 1-minute and 5-minute charts. It allows the system to react very quickly to sudden volume spikes. Increasing this number (e.g., to 10) will make the signals slower and more conservative.
Stop Deviation
Default: 3.0
This controls the "breathing room" for the trade. A value of 3.0 allows for standard volatility on minute charts without triggering a premature exit. Lowering this to 2.0 will result in tighter stops but more false signals.
HMA Filter
Use HMA as Filter? (Default: OFF):
When OFF, the system signals purely on price action breakouts (fastest).
When ON, the system waits for the price to align with the 50-period HMA before signaling (safest, but may delay entry).
How to Interpret Visuals
Candle Colors
Teal/Green: The market is in a Bullish regime.
Red/Pink: The market is in a Bearish regime.
The Line
The solid stepped line represents the hard invalidation point. If price closes beyond this line, the trend is considered over.
Diamond Signals
Light Green Diamond (Below Bar): Confirmed Buy Signal. A new bullish trend has started.
Light Red/Pink Diamond (Above Bar): Confirmed Sell Signal. A new bearish trend has started.
Trading Strategy Guide
The Scalp Entry
Ensure you are on a 1-minute or 5-minute timeframe.
Wait for a signal Diamond to close. Do not enter while the bar is still forming, as the signal may repaint (disappear) if the price retraces before the close.
Long Entry: Enter when a Green Diamond appears and the candle turns Teal.
Short Entry: Enter when a Red Diamond appears and the candle turns Red.
Risk Management
Stop Loss: Your invalidation level is the "Apex Stop" line. You can place your hard stop loss slightly beyond this line.
Take Profit: Because this is a trend-following system, it is often best to hold until the candle color changes, or to take profit at fixed Risk:Reward ratios (e.g., 1:1.5 or 1:2).
The HMA Nuance If you find the market is "choppy" (moving sideways), enable the "Use HMA as Filter" option in the settings. This will force the system to ignore signals that are counter-trend to the longer-term momentum.
Disclaimer
The information provided by the "Dark Vector Scalping" indicator and this accompanying guide is for educational and informational purposes only. It does not constitute financial, investment, or trading advice. Trading cryptocurrencies, stocks, and forex involves a high level of risk and may not be suitable for all investors. You could lose some or all of your initial investment.
Super-AO with Risk Management Alerts Template - 11-29-25Super-AO with Risk Management: ALERTS & AUTOMATION Edition
Signal Lynx | Free Scripts supporting Automation for the Night-Shift Nation 🌙
1. Overview
This is the Indicator / Alerts companion to the Super-AO Strategy.
While the Strategy version is built for backtesting (verifying profitability and checking historical performance), this Indicator version is built for Live Execution.
We understand the frustration of finding a great strategy, only to realize you can't easily hook it up to your trading bot. This script solves that. It contains the exact same "Super-AO" logic and "Risk Management Engine" as the strategy version, but it is optimized to send signals to automation platforms like Signal Lynx, 3Commas, or any Webhook listener.
2. Quick Action Guide (TL;DR)
Purpose: Live Signal Generation & Automation.
Workflow:
Use the Strategy Version to find profitable settings.
Copy those settings into this Indicator Version.
Set a TradingView Alert using the "Any Alert() function call" condition.
Best Timeframe: 4 Hours (H4) and above.
Compatibility: Works with any webhook-based automation service.
3. Why Two Scripts?
Pine Script operates in two distinct modes:
Strategy Mode: Calculates equity, drawdowns, and simulates orders. Great for research, but sometimes complex to automate.
Indicator Mode: Plots visual data on the chart. This is the preferred method for setting up robust alerts because it is lighter weight and plots specific values that automation services can read easily.
The Golden Rule: Always backtest on the Strategy, but trade on the Indicator. This ensures that what you see in your history matches what you execute in real-time.
4. How to Automate This Script
This script uses a "Visual Spike" method to trigger alerts. Instead of drawing equity curves, it plots numerical values at the bottom of your chart when a trade event occurs.
The Signal Map:
Blue Spike (2 / -2): Entry Signal (Long / Short).
Yellow Spike (1 / -1): Risk Management Close (Stop Loss / Trend Reversal).
Green Spikes (1, 2, 3): Take Profit Levels 1, 2, and 3.
Setup Instructions:
Add this indicator to your chart.
Open your TradingView "Alerts" tab.
Create a new Alert.
Condition: Select SAO - RM Alerts Template.
Trigger: Select Any Alert() function call.
Message: Paste your JSON webhook message (provided by your bot service).
5. The Logic Under the Hood
Just like the Strategy version, this indicator utilizes:
SuperTrend + Awesome Oscillator: High-probability swing trading logic.
Non-Repainting Engine: Calculates signals based on confirmed candle closes to ensure the alert you get matches the chart reality.
Advanced Adaptive Trailing Stop (AATS): Internally calculates volatility to determine when to send a "Close" signal.
6. About Signal Lynx
Automation for the Night-Shift Nation 🌙
We are providing this code open source to help traders bridge the gap between manual backtesting and live automation. This code has been in action since 2022.
If you are looking to automate your strategies, please take a look at Signal Lynx in your search.
License: Mozilla Public License 2.0 (Open Source). If you make beneficial modifications, please release them back to the community!
Confluence Engine [BullByte]CONFLUENCE ENGINE
Multi-Factor Technical Analysis Framework
OVERVIEW
Confluence Engine is a multi-dimensional technical analysis framework that evaluates market conditions across five distinct analytical pillars simultaneously. Rather than relying on a single indicator or signal source, this tool synthesizes Structure, Momentum, Volume, Volatility, and Pattern analysis into a unified scoring system that identifies high-probability trading opportunities when multiple technical factors align.
The core philosophy behind this indicator stems from a fundamental observation: isolated signals frequently fail, but when multiple independent analytical methods agree, the probability of a successful trade increases substantially. This indicator was developed after extensive research into why traders often receive conflicting signals from different indicators on their charts, leading to analysis paralysis and poor decision-making.
THE PROBLEM AND SOLUTION
The Problem:
Most traders use multiple indicators independently, often receiving contradictory signals. One indicator says "buy" while another says "wait." This creates confusion and leads to missed opportunities, premature entries based on incomplete analysis, difficulty quantifying how strong a setup actually is, and inconsistent decision-making across different market conditions.
The Solution:
Confluence Engine addresses this by providing a single, unified score (0-100) that represents the aggregate strength of a trading setup. Instead of mentally weighing five different indicators, traders receive a clear numerical score indicating setup quality, visual tier classification (ULTRA, HIGH, STANDARD), specific identification of which factors are strong or weak, and actionable guidance on what to watch for next.
THE FIVE ANALYTICAL DIMENSIONS
Each dimension was selected because it measures a fundamentally different aspect of market behavior:
STRUCTURE ANALYSIS
Evaluates price position relative to key levels and recent swing points. Markets respect structure - previous highs, lows, and areas where price reversed. This dimension identifies when price interacts with these critical levels and measures the quality of that interaction.
What it detects: Price approaching or sweeping swing highs/lows, reclaim patterns after false breakouts, EMA alignment and trend structure, exhaustion after extended moves.
MOMENTUM ANALYSIS
Measures the underlying strength and direction of price movement. Strong moves are characterized by momentum preceding price. This dimension evaluates whether momentum supports the current price direction.
What it detects: Oversold/overbought conditions with reversal potential, momentum divergence states, directional movement strength (ADX-based), momentum shifts before price confirmation.
VOLUME ANALYSIS
Volume validates price movement. Significant moves require participation. This dimension measures current volume relative to recent averages to determine if market participants are genuinely committing to the move.
What it detects: Volume spikes confirming price action, below-average volume warning of weak moves, climactic volume at potential reversals, volume confirmation of rejection patterns.
VOLATILITY ANALYSIS
Markets alternate between compression (low volatility) and expansion (high volatility). This dimension identifies these phases and recognizes when compression is likely to resolve into directional movement.
What it detects: Volatility squeeze conditions (Bollinger inside Keltner), squeeze release direction, ATR expansion indicating breakout potential, compression duration for timing breakouts.
PATTERN ANALYSIS
Candlestick patterns reflect the battle between buyers and sellers within each bar. This dimension evaluates the quality and context of reversal and continuation patterns.
What it detects: Engulfing patterns with quality scoring, hammer and shooting star formations, rejection wicks indicating trapped traders, pattern confluence with other factors.
WHAT MAKES THIS INDICATOR ORIGINAL Not a mashup
This is NOT a mashup of indicators displayed together. The Confluence Engine represents an integrated analytical framework with the following unique characteristics:
Unified Scoring System: All five dimensions feed into a proprietary scoring algorithm that weights and combines their signals. The output is a single 0-100 score, not five separate readings.
Multi-Factor Gate: Beyond just scoring, the system requires a minimum number of factors to be "active" (meeting their individual thresholds) before allowing signals. This prevents signals based on one extremely strong factor masking four weak ones.
Regime-Aware Adjustments: The engine detects the current market regime (trending, ranging, volatile, weak) and automatically adjusts factor weights and score multipliers. A structure signal means something different in a trending market versus a ranging market.
Adaptive Risk Management: Take-profit and stop-loss levels are not static. They adapt based on current volatility, market regime, and signal quality - providing tighter targets in low-volatility environments and wider targets when volatility expands.
Liquidity Sweep Detection: A distinctive feature that identifies when price has swept beyond a swing high/low and then reclaimed back inside. This pattern often indicates stop hunts followed by reversals.
Signal Quality Tiers: Rather than just "signal" or "no signal," the engine classifies setups into tiers. ULTRA (80+) represents highest probability setups with all factors aligned. HIGH (70-79) represents strong setups with multiple factors confirming. STANDARD meets minimum threshold for acceptable setups.
HOW THE SCORING WORKS
Each of the five factors generates a raw score from 0-100 based on current market conditions. These raw scores are then weighted according to the selected trading style (Balanced, Scalper, Swing, Range, Trend), adjusted based on current market regime detection, modified by higher timeframe alignment (if enabled), bonused when multiple factors exceed their activation thresholds simultaneously, and multiplied by session factors (if session filter is enabled).
The result is a final Bull Score and Bear Score, each ranging from 0-100, representing the current strength of long and short setups respectively.
Signal Generation Requirements:
- Score meets minimum threshold (configurable: 60-95)
- Required number of factors are "active" (default: 3 of 5)
- Market regime is not blocked (if blocking enabled)
- Higher timeframe alignment passes (if required)
- Cooldown period from last signal has elapsed
UNDERSTANDING THE DASHBOARDS
Main Dashboard (Top Right)
The main dashboard displays real-time scores and market context:
LONG Score - Current bullish setup strength (0-100) with quality tier displayed
SHORT Score - Current bearish setup strength (0-100) with quality tier displayed
Regime - Current market state showing TREND UP, TREND DN, VOLATILE, RANGE, or WEAK
HTF - Higher timeframe alignment showing BULL, BEAR, NEUT, or OFF
Squeeze - Volatility state showing SQZ (in squeeze), REL+ (bullish release), REL- (bearish release), or NORM
Gate - Factor count versus requirement, for example 4/3 means 4 factors active with 3 required
Sweep L/S - Liquidity sweep status for long and short setups
ATR% - Current ATR as percentile of recent range indicating relative volatility
Vol - Current volume relative to 20-period average
R:R - Current risk-reward ratio based on adaptive TP/SL calculations
Trade - Active trade status and unrealized profit/loss percentage
Analysis Dashboard (Bottom Left)
The analysis dashboard provides actionable guidance:
Signal Readiness - Visual progress bars showing how close each direction is to generating a signal
Blocking Factors - Identifies which specific factor is weakest and preventing signals
Recommended Action - Context-aware guidance such as WATCH, WAIT, MANAGE, or SCAN
Watch For - Specific events to monitor for setup completion
Opportunity Level - Overall market opportunity rating from EXCELLENT to VERY POOR
Timing - Contextual timing guidance based on current conditions
Status Bar (Bottom Center)
Compact view displaying Long Score, Gate Status, Current State, Gate Status, and Short Score in a single row for quick reference.
Dashboard Size - Auto Mode Explained
When Dashboard Size is set to "Auto", the indicator intelligently adjusts text size based on your current chart timeframe to optimize readability:
Auto-Sizing Logic:
1-Minute to 5-Minute Charts → Tiny
- Lower timeframes show more bars on screen
- Tiny text prevents dashboard from obscuring price action
- Recommended for scalping and high-frequency monitoring
15-Minute Charts → Small
- Balanced size for intraday trading
- Readable without being intrusive
1-Hour to Daily Charts → Normal
- Standard size for most trading styles
- Optimal readability for swing trading
Weekly and Monthly Charts → Large
- Larger text for position trading
- Fewer bars visible so space is available
Manual Override:
You can override auto-sizing for any dashboard individually:
- Dashboard Size (All): Sets master size applied to all dashboards
- Main Dashboard Size: Override for top-right dashboard specifically
- Analysis Panel Size: Override for bottom-left panel specifically
- Status Bar Size: Override for bottom-center bar specifically
Example Use Case:
Trading on 5m chart (default = Tiny) but you have good eyesight and large monitor:
- Set "Dashboard Size (All)" to "Small" or "Normal" for better readability
- Individual dashboards will use your override instead of auto-sizing
Recommendation:
Start with Auto mode and only adjust if dashboards are too large or too small for your monitor/eyesight.
UNDERSTANDING SIGNAL LABELS
When a signal generates, a label appears with trade information:
Minimal Style Example:
LONG 85
Shows tier icon, direction, and score only.
Detailed Style Example:
ULTRA LONG
Score: 85
Entry: 50250.50
TP1: 50650.25
TP2: 51500.75
SL: 49850.25
R:R 1:2.5
Regime: TREND UP
HTF: BULL
Tier Icons Explained:
indicates ULTRA quality with score 80 or higher
indicates HIGH quality with score between 70 and 79
indicates STANDARD quality with score meeting minimum threshold
UNDERSTANDING TRADE ZONES
When a signal generates, visual elements appear on the chart:
Entry Line (Purple) marks the entry price level
TP1 Line (Blue Dashed) marks the first take-profit target
TP2 Line (Cyan Dashed) marks the final take-profit target
SL Line (Orange Dotted) marks the stop-loss level
Trade Zone Box shows shaded area from SL to TP2
These elements extend forward as price progresses. When TP1 is hit, its line becomes solid to indicate achievement. When the trade completes at either TP2 or SL, all elements are cleaned up and the entry label converts to a compact ghost label for historical reference.
Exit Labels Explained:
+X.XX% indicates first target reached with partial profit secured
+X.XX% indicates full target reached with maximum profit achieved
-X.XX% indicates stop-loss triggered
TP1 Hit, SL... indicates stopped out after TP1 was already hit (optional display)
OPPOSITE SIGNAL HANDLING
When market conditions shift dramatically, the engine may generate a signal in the opposite direction while an existing trade is active. This represents a significant change in confluence and is handled automatically:
Automatic Trade Reversal Process:
1. Detection: New signal triggers opposite to current trade direction (e.g., SHORT signal while LONG trade is active)
2. Current Trade Closure:
- All visual elements (entry line, TP/SL lines, trade zone) are deleted
- Current trade is marked as closed
3. Entry Label Conversion:
- The detailed entry label is converted to a compact ghost label
- Ghost label shows direction + score (e.g., "LONG 75")
- Marked with "OPP" outcome to indicate opposite signal closure
- Moved to a non-interfering position below/above price
4. New Trade Initialization:
- Fresh entry label created for new direction
- New TP1, TP2, SL levels calculated based on new signal quality
- Trade zone and price lines drawn for new trade
Example Scenario:
You enter a LONG trade at score 72. Price moves sideways for 8 bars, then market structure breaks down. Confluence shifts heavily bearish with a sweep reclaim bear + momentum + volume spike, generating a SHORT signal at score 81. The engine automatically:
- Closes the LONG trade
- Converts "LONG 72" entry label to a small ghost label
- Opens new SHORT trade at current price
- Displays new SHORT entry label with full trade details
Trading Implication:
This behavior ensures the engine is always aligned with the highest-probability direction based on current confluence. It prevents you from holding a position when all five factors have flipped against you.
Note: This does NOT happen for every small score change. The opposite signal must meet all signal generation requirements (minimum score, gate pass, regime check, HTF alignment) before triggering. Typically occurs during strong trend reversals or major support/resistance breaks.
EXAMPLE TRADE : LONG
Instrument and Exchange: Bitcoin / TetherUS (BTC/USDT) on Binance
Timeframe: 5-minute
Timestamp: Nov 27, 2025 12:39 UTC
Indicator Script: Confluence Engine v1.0
Trade Type: Long (Example Trade)
Setting Used: Default
Signal Details:
- Tier: HIGH
- Score: 70
- Entry Price: 90040.70
- TP1 Target: 90868.63
- TP2 Target: 92110.52
- Stop Loss: 89325.94
- Risk Reward: 1:2.9
Trade Outcome:
- TP1 hit after 12 bars (+0.95%)
- TP2 hit after 28 bars (+2.85%)
- Total gain: +2.85% on full position
EXAMPLE TRADE : SHORT with Dashboard Explanation and interpretation
Instrument and Exchange: Ethereum / U.S. Dollar (ETH/USD) — Coinbase
Timeframe: 1-hour
Timestamp (screenshot): Nov 28, 2025 16:41 UTC
Indicator Script: Confluence Engine v1.0
Trade Type: Short (Example Trade)
Setting Used: Default
Signal Details
-Tier: STANDARD (STD)
-Score: 64
-Entry Price: 3037.26
-TP1 Target: 2981.61 (-55.65 pts)
-TP2 Target: 2898.12 (-139.14 pts)
-Stop Loss: 3099.79 (+62.53 pts)
-Risk:Reward: ≈ 1 : 2.2 (TP2/SL)
-Market Context at Signal
-Regime: TREND UP (contextual regime at time of signal) — mixed environment for shorts
-HTF Alignment: OFF (no higher-timeframe confirmation)
-Gate Status: 3 / 3 (minimum factor groups active — gate passed)
-Squeeze Status: NORM (no active compression breakout)
-Volume: ~1.8× average (elevated participation)
-ATR%: 57% (elevated volatility)
Analysis Dashboard Reading (what the user sees)
-Long Readiness: Needs +36 points to qualify.
-Short Readiness: Needs +11 points to qualify (closer but not auto-entering).
-Blocking Factors: Structure = 0 — the single decisive blocker preventing fresh signals.
-Opportunity Level: VERY POOR (roughly 20 / 100) — low quality environment for adding positions.
-Timing: Wait for better setup (do not add new positions).
-Trade Outcome (screenshot moment)
-Trade state: Active SHORT (opened earlier).
-Live P&L (snapshot): +0.14% (managing trade).
-TP1/TP2: Targets shown on chart (TP1 2981.61, TP2 2898.12). Not closed yet at screenshot.
-Visuals: Entry label, TP/SL lines and trade zone are displayed and being extended while trade is active.
Interpretation
The engine produced a standard short (Score 64) while the market showed elevated volume and volatility but no HTF confirmation. Although the Gate passed (3/3), Structure = 0 blocks the indicator from issuing fresh entries — this is intentional and by design: one missing factor (structure) is enough to prevent new signals even when other factors look supportive. The currently open short is being managed (partial targets and SL visible), but the system's recommendation is to manage the existing trade only and not open new shorts until structure or HTF alignment improves.
Why this example matters (teaching point)
-Gate ≠ Go: Gate pass (factor count) alone does not force fresh trades — the system enforces additional checks (structure, regime, HTF) to avoid lower-quality setups.
-Volume & Volatility are necessary but not sufficient: High volume and wide ATR create movement but do not replace structural validation.
-Active trade vs new entries: The script will continue to manage an already open trade but will not create a new signal while a blocking factor remains. This prevents overtrading and reduces false positives.
-Practical trader actions shown by the example
-Manage existing SHORT only: Trail to breakeven if TP1 is taken; scale out at TP1; hold remaining if price respects trend and structure reclaims.
-Do not add fresh positions: Wait for Structure > 0 or a HTF alignment that lifts the block.
-Watch for signals that matter: Sweep reclaim, HTF alignment turning bullish for shorts (i.e., HTF changes to BEAR), or a squeeze release with volume spike — these can clear the blocker and validate new entries.
RECOMMENDED TIMEFRAMES
For Scalping on 1m, 5m, or 15m charts: Use higher factor thresholds and shorter cooldowns. The faster pace requires stricter filtering.
For Day Trading on 15m, 30m, or 1H charts: This provides a balance of signal frequency and reliability suitable for most active traders.
For Swing Trading on 1H, 4H, or Daily charts: Expect higher quality signals with longer hold periods and fewer false signals.
For Position Trading on Daily or Weekly charts: Focus on ULTRA signals only for maximum conviction on longer-term positions.
Higher Timeframe Alignment Recommendations:
When trading 5m, use 1H as your HTF
When trading 15m, use 1H or 4H as your HTF
When trading 1H, use 4H or Daily as your HTF
When trading 4H, use Daily as your HTF
The general rule is to select an HTF that is 4 to 12 times your trading timeframe.
TRADING STYLE PRESETS
Balanced (Default)
Equal weighting across all five factors at 20% each. Suitable for most market conditions and recommended as starting point.
Scalper
Emphasizes Volume at 30% and Volatility at 30%. Designed for quick in-and-out trades on lower timeframes where immediate momentum and volatility expansion matter most.
Swing Trader
Emphasizes Structure at 30% and Momentum at 30%. Focuses on catching larger moves where trend direction and key levels are paramount.
Range Trader
Emphasizes Structure at 35% and Pattern at 25%. Optimized for sideways markets where support/resistance levels and reversal patterns dominate.
Trend Follower
Emphasizes Momentum at 40%. Designed for trending markets where staying with the dominant direction is the priority.
QUALITY MODE SETTINGS
Custom Mode
Set your own minimum score threshold. Lower thresholds between 60 and 65 generate more signals but with lower average quality. Higher thresholds of 75 or above generate fewer but higher-quality signals.
High Quality Mode
Uses minimum score of 70. Recommended for most users as it filters out marginal setups while still providing reasonable signal frequency.
Ultra Only Mode
Uses minimum score of 80 for maximum selectivity. Only the highest-conviction setups generate signals. Recommended for swing and position traders or during uncertain market conditions.
REGIME DETECTION
The engine continuously evaluates market conditions and classifies them into five states:
TREND UP
Characteristics: Strong ADX reading with EMAs aligned in bullish order
Trading Implications: Long signals receive score boost while short signals are suppressed. Momentum factor gains additional weight.
TREND DN
Characteristics: Strong ADX reading with EMAs aligned in bearish order
Trading Implications: Short signals receive score boost while long signals are suppressed. Momentum factor gains additional weight.
VOLATILE
Characteristics: High ATR percentile, wide Bollinger Bands, elevated volume
Trading Implications: Both directions remain viable but wider stops are recommended. Volume factor gains additional weight.
RANGE
Characteristics: Low ADX reading, narrow Bollinger Bands, low ATR percentile
Trading Implications: Structure signals are emphasized while momentum signals are suppressed. Pattern recognition becomes more important.
WEAK
Characteristics: Unclear or mixed conditions that do not fit other categories
Trading Implications: Reduced confidence in all signals. Consider waiting for clearer market conditions.
Filter Mode Options:
Off - Regime is detected and displayed but no score adjustments are applied
Adjust Scores - Automatically modifies factor weights based on current regime
Block Weak Regimes - Prevents signals from generating when regime is RANGE or WEAK
VOLATILITY SQUEEZE DETECTION
A volatility squeeze occurs when Bollinger Bands contract inside the Keltner Channel, indicating reduced volatility and potential energy building for a breakout.
Squeeze States Explained:
SQZ with bar count (example: SQZ 15)
Indicates currently in squeeze for the displayed number of bars. A score penalty is applied during this phase because compression represents uncertainty about direction.
REL+ (Release Bullish)
Indicates squeeze has released with price above the basis line. Score bonus is applied for long setups as this often precedes strong upward moves.
REL- (Release Bearish)
Indicates squeeze has released with price below the basis line. Score bonus is applied for short setups as this often precedes strong downward moves.
NORM (Normal)
No active squeeze detected. Standard scoring applies.
Trading Implication:
Squeeze releases often produce strong directional moves. The engine detects both the squeeze duration and the release direction, awarding bonus points to signals that align with the release. Longer squeeze duration often corresponds to more powerful breakouts.
LIQUIDITY SWEEP DETECTION
Markets often sweep beyond obvious support and resistance levels to trigger stops before reversing. The engine detects these patterns:
Bullish Sweep Reclaim
Price sweeps below recent swing low, triggering stop losses, then reclaims back above the swing low. This often indicates smart money accumulation after retail stops are collected.
Bearish Sweep Reclaim
Price sweeps above recent swing high, triggering stop losses, then reclaims back below the swing high. This often indicates smart money distribution after retail stops are collected.
Sweep Status in Dashboard:
RCL (Reclaim) - Reclaim has been confirmed. This receives highest structure score as the pattern is complete.
PND (Pending) - Sweep has occurred and price is near the level but full reclaim not yet confirmed. Watching for completion.
ACT (Active) - Sweep is currently in progress with price beyond the swing level.
Dash (-) - No sweep activity detected.
MULTI-FACTOR GATE SYSTEM
Beyond overall score, the engine counts how many individual factors meet their activation threshold.
Example Calculation:
Structure score 45 with threshold 35 equals ACTIVE
Momentum score 25 with threshold 30 equals INACTIVE
Volume score 50 with threshold 35 equals ACTIVE
Volatility score 40 with threshold 30 equals ACTIVE
Pattern score 35 with threshold 30 equals ACTIVE
Result: 4 of 5 factors are active
If minimum required factors is set to 3, this example passes the gate and receives a 4-factor bonus.
Gate Bonuses:
4 factors active adds 8 points to final score (default setting)
5 factors active adds 15 points to final score (perfect confluence)
Purpose:
This mechanism prevents scenarios where one extremely high factor score masks four weak factors. A score of 75 with only 2 active factors is less reliable than a score of 70 with 4 active factors.
ADAPTIVE RISK MANAGEMENT
Take-profit and stop-loss distances adjust dynamically based on three inputs:
Volatility Influence (default 40% weight)
Low ATR percentile produces tighter targets
High ATR percentile produces wider targets
This ensures stops are not too tight in volatile conditions or too wide in calm conditions.
Regime Influence (default 30% weight)
Trending market with aligned signal produces extended targets
Ranging market produces contracted targets
Volatile regime produces wider stops for protection
Score Influence (default 30% weight)
ULTRA signals (high conviction) receive extended targets
STANDARD signals receive standard targets
Higher conviction justifies larger profit expectations.
You can configure the weight of each influence in settings to match your trading style.
SESSION FILTER (Optional Feature)
When enabled, the engine applies score multipliers based on the trading session:
Asian Session (default 0.9x multiplier)
Characterized by lower volatility and ranging tendency. Score reduction reflects reduced opportunity.
London Session (default 1.1x multiplier)
Characterized by high volatility and trend initiation. Score boost reflects increased opportunity.
London/NY Overlap (default 1.2x multiplier)
Characterized by highest liquidity and strongest moves. Maximum score boost reflects peak trading conditions.
New York Session (default 1.05x multiplier)
Characterized by volatility but typically after initial moves have occurred.
Configure your UTC offset in settings to align session detection with your chart timezone.
ALERT SYSTEM
The indicator provides comprehensive alerts with dynamic data:
Signal Alerts:
- ULTRA Long Signal with full trade details
- ULTRA Short Signal with full trade details
- HIGH Long Signal with key levels
- HIGH Short Signal with key levels
- Any Long Signal with basic info
- Any Short Signal with basic info
Trade Management Alerts:
- TP1 Reached with profit percentage
- TP2 Full Target with total profit
- Stop Loss Hit with loss percentage and status
Technical Event Alerts:
- Squeeze Release
- Liquidity Sweep
- Perfect Confluence
- Regime Change
All alerts include actual calculated values such as score, entry price, target levels, stop level, and risk-reward ratio at the time of trigger.
AUTOMATIC SETTINGS VALIDATION
The indicator performs comprehensive validation when first loaded on a chart. If configuration errors are detected, a warning label appears on the chart with specific guidance.
Critical Errors (Prevent Signal Generation):
ULTRA threshold must exceed HIGH threshold
- Example error: HIGH = 75, ULTRA = 70
- Fix: Ensure ULTRA threshold is higher than HIGH threshold
- Default safe values: HIGH = 70, ULTRA = 80
Minimum factors cannot exceed 5
- The gate requires 3 to 5 factors (you cannot require 6 of 5 factors)
- Fix: Set minimum active factors to 3, 4, or 5
TP2 multiplier must exceed TP1 multiplier
- Example error: TP1 = 3.0 ATR, TP2 = 2.0 ATR
- Fix: Ensure TP2 (final target) is farther than TP1 (partial target)
- Default safe values: TP1 = 2.0, TP2 = 5.0
Swing lookback minimum is 3 bars
- Liquidity sweep detection requires at least 3 bars to identify swing highs/lows
- Fix: Increase swing lookback period to 3 or higher
ATR period minimum is 5 bars
- ATR calculation requires sufficient data for accuracy
- Fix: Increase ATR period to 5 or higher (14 recommended)
Higher timeframe must be larger than chart timeframe
- Example error: Trading on 1H chart with MTF set to 15m
- Fix: Select HTF that is 4-12x your chart timeframe
- Example: If trading 15m, use 1H or 4H as HTF
Warnings (Signal Generation Continues):
Score threshold below 50 generates many signals
- Lower thresholds increase signal frequency but reduce quality
- Recommendation: Use minimum 60 for active trading, 70+ for swing trading
Cooldown below 3 bars may cause signal clustering
- Very short cooldowns can produce multiple signals in quick succession
- Recommendation: Use 5+ bars for lower timeframes, 3+ for higher timeframes
Validation Label Display:
When errors are detected, a label appears at the top of the chart showing:
SETTINGS QUICK REFERENCE
Signal Quality Section:
Quality Mode: High Quality recommended for most users
Custom Minimum Score: Used when Quality Mode is set to Custom (range 30-95)
HIGH Threshold: Score required for HIGH tier classification (default 70)
ULTRA Threshold: Score required for ULTRA tier classification (default 80)
Regime Engine Section:
Enable Regime Detection: Activates automatic market state classification
Filter Mode: Off, Adjust Scores, or Block Weak Regimes
ADX Strong Threshold: ADX level indicating strong trend (default 25)
ADX Weak Threshold: ADX level indicating ranging conditions (default 15)
Show Regime Background: Displays subtle background color for current regime
Liquidity and Squeeze Section:
Enable Liquidity Sweep Detection: Activates sweep and reclaim pattern detection
Swing Lookback Period: Bars used to identify swing highs and lows (default 8)
Reclaim Threshold: Percentage of range price must reclaim after sweep (default 15%)
Enable Volatility Squeeze Detection: Activates Bollinger/Keltner squeeze detection
Keltner Channel Multiplier: Width multiplier for Keltner Channel (default 1.5)
Squeeze Penalty: Points subtracted during active squeeze (default 25)
Squeeze Release Bonus: Points added on squeeze release (default 20)
Enable Multi-Factor Gate: Requires minimum factors active before signaling
Minimum Active Factors: How many factors must meet threshold (default 3)
Individual Factor Thresholds: Customize activation threshold for each factor
4-Factor Bonus: Points added when 4 of 5 factors active (default 8)
5-Factor Bonus: Points added when all 5 factors active (default 15)
MTF Confluence Section:
Enable MTF Confluence: Activates higher timeframe trend analysis
Higher Timeframe: Select timeframe for trend alignment (recommend 4-12x chart TF)
Require HTF Alignment: Block signals opposing higher timeframe trend
Show HTF EMAs: Display higher timeframe EMA 21 and EMA 50 on chart
Trading Style Section:
Enable Style Weighting: Activates factor weight adjustments based on style
Trading Style: Balanced, Scalper, Swing Trader, Range Trader, or Trend Follower
Custom Weights: Individual weight sliders when fine-tuning is needed
Session Filter Section:
Enable Session Filter: Activates session-based score multipliers
Your UTC Offset: Your timezone offset for accurate session detection
Session Multipliers: Individual multipliers for Asian, London, New York, and Overlap sessions
Risk Parameters Section:
ATR Period: Period for Average True Range calculation (default 14)
TP1 ATR Multiple: First target distance as ATR multiple (default 2.0)
TP2 ATR Multiple: Final target distance as ATR multiple (default 5.0)
SL ATR Multiple: Stop loss distance as ATR multiple (default 2.0)
Enable Adaptive TP/SL: Activates dynamic adjustment based on conditions
Volatility Weight: Influence of ATR percentile on adaptive calculation (default 40%)
Regime Weight: Influence of market regime on adaptive calculation (default 30%)
Score Weight: Influence of signal score on adaptive calculation (default 30%)
Appearance Section:
Color Theme: Matrix (green/red), Dark (modern dark), or Light (clean light)
Label Detail: Minimal (score only), Standard (key info), or Detailed (full breakdown)
Dashboard Size Controls: Master size and individual overrides for each dashboard
Show Trade Zones: Display shaded box from SL to TP2 for active trades
Show TP/SL Labels: Display price labels on target and stop lines
Show Trailing Exit Labels: Display exit label when stopped after TP1 hit
Show Main Dashboard: Toggle main dashboard visibility (top right)
Show Analysis Dashboard: Toggle analysis panel visibility (bottom left)
Show Status Bar: Toggle compact status bar visibility (bottom center)
Performance Section:
Performance Mode: Reduces visual elements on lower timeframes automatically
Max Ghost Labels: Maximum historical signal labels to retain (default 50)
Signal Cooldown: Minimum bars between signals in same direction (default 5)
Enable Script Alerts: Controls whether alert() calls fire automatically (default ON)
- ON: Dynamic alerts with calculated values fire automatically
- OFF: alert() suppressed, alertcondition() still available for manual creation
- Use OFF when testing settings or monitoring multiple instruments visually
- Toggle per-chart for selective alert coverage across watchlist
Show Factor Markers: Display shapes on chart when 3, 4, or 5 factors align
Show Score Breakdown: Display detailed factor scores table in debug panel
Show Regime Debug: Display regime state and ADX value in debug panel
Show MTF Debug: Display higher timeframe status in debug panel
DEBUG MODE AND FACTOR MARKERS
The indicator includes optional debug tools for traders who want deeper insight into the scoring mechanics and factor analysis. These features are disabled by default to keep the chart clean but can be enabled in the Debug Mode settings group.
FACTOR MARKERS
When "Show Factor Markers" is enabled, visual shapes appear on the chart indicating confluence states:
Perfect Confluence (5/5 Factors Active)
A circle appears below the bar for bullish or above the bar for bearish setups. This represents maximum confluence where all five analytical dimensions meet their activation thresholds simultaneously. A small label showing "5/5" also appears. This is a rare occurrence and typically precedes the highest quality signals. Background color shifts to highlight this exceptional alignment.
Strong Confluence (4/5 Factors Active)
A diamond shape appears below the bar for bullish or above the bar for bearish setups. This represents strong confluence with four of five factors active. A label showing "4/5" appears when this state is first achieved. This level of confluence is associated with high-quality setups.
Ready Confluence (3/5 Factors Active)
A triangle appears below the bar (pointing up) for bullish or above the bar (pointing down) for bearish setups. This represents the minimum confluence level required when gate is set to 3 factors. No label appears for this level to reduce visual clutter.
Confluence Background
When factor markers are enabled, a subtle background color appears indicating the current confluence state. Stronger colors indicate higher confluence levels. Bullish confluence shows green tints while bearish confluence shows red tints.
Purpose of Factor Markers:
These markers help traders visualize when confluence is building before a signal triggers. You might see a 4/5 diamond appear one or two bars before the actual signal, giving you advance notice that conditions are aligning. This can help with preparation and timing.
DEBUG PANEL (Bottom Right)
When any debug option is enabled, a debug panel appears in the bottom right corner of the chart providing detailed scoring information.
Score Breakdown Table
When "Show Score Breakdown" is enabled, the panel displays:
Factor column showing Structure, Momentum, Volume, Volatility, and Pattern
Bull column showing raw score (0-100) for each bullish factor
Bear column showing raw score (0-100) for each bearish factor
Weight column showing current percentage weight for each factor
Below the factor rows :
FINAL row shows the calculated final Bull and Bear scores after all adjustments
Adj row shows total adjustments applied including gate bonus, squeeze adjustment, and exhaustion adjustment with positive or negative sign
This breakdown allows you to see exactly which factors are contributing to the score and which are lagging. If you notice Structure consistently low, you know to wait for better price positioning relative to swing levels.
Regime Debug
When "Show Regime Debug" is enabled, the panel displays:
Current regime state (TREND UP, TREND DN, VOLATILE, RANGE, WEAK)
Current ADX value driving the regime classification
This helps you understand why certain score adjustments are being applied and verify the regime detection is working as expected for current market conditions.
MTF Debug
When "Show MTF Debug" is enabled, the panel displays:
Current MTF alignment status (BULL, BEAR, NEUT)
The higher timeframe being analyzed
This confirms the higher timeframe data is being read correctly and shows you the trend bias from the larger timeframe perspective.
Using Debug Mode Effectively
For Learning: Enable all debug options when first using the indicator to understand how scores are calculated and what drives signal generation.
For Optimization: Use score breakdown to identify which factors are consistently weak in your chosen market and timeframe. This can inform whether to adjust factor thresholds or switch trading styles.
For Troubleshooting: If signals seem inconsistent, enable debug to see exactly what values the engine is working with. This helps identify if a specific factor is behaving unexpectedly.
For Live Trading: Disable debug features to keep chart clean and reduce visual distraction. The main dashboards provide sufficient information for trade execution.
Debug Settings Summary:
Show Factor Markers - Displays shapes on chart when 3, 4, or 5 factors align. Useful for seeing confluence build before signals trigger.
Show Score Breakdown - Displays detailed table with all raw factor scores, weights, and adjustments. Useful for understanding exactly how final score is calculated.
Show Regime Debug - Adds regime state and ADX value to debug panel. Useful for verifying regime detection accuracy.
Show MTF Debug - Adds higher timeframe status and timeframe to debug panel. Useful for confirming MTF data is loading correctly.
PERFORMANCE CONSIDERATIONS
On lower timeframes such as 1-minute and 5-minute charts, the indicator creates visual elements including labels, lines, and boxes that may impact performance on slower devices.
Performance Mode automatically reduces visual elements, optimizes calculation frequency, and limits historical ghost labels when enabled.
Configure Max Ghost Labels (default 50) to control how many historical signal labels are retained on the chart.
NON-REPAINTING DESIGN
Signal Integrity:
All entry and exit signals generate only on confirmed (closed) bars using barstate.isconfirmed checks. This ensures signals do not appear and disappear during bar formation.
Higher Timeframe Data:
MTF analysis uses request.security with lookahead disabled (barmerge.lookahead_off) to prevent future data from influencing current calculations.
Visual Elements:
Lines, boxes, and labels for active trades update in real-time for monitoring purposes but this visual updating does not affect signal generation logic. Entry decisions are made solely on confirmed bar data.
DISCLAIMER
Trading financial instruments involves substantial risk of loss and is not suitable for all investors. Past performance does not guarantee future results. This indicator is a technical analysis tool provided for educational purposes only. It does not constitute financial advice, trading recommendations, or solicitation to buy or sell any financial instrument.
The developer makes no representations regarding the accuracy of signals or the profitability of trading based on this indicator. Users assume full responsibility for their trading decisions and should conduct their own analysis before entering any trade.
Always use proper risk management. Never risk more than you can afford to lose. Consider consulting a qualified financial advisor before making trading decisions.
VERSION HISTORY
v1.0 - Initial Release
- Five-factor confluence scoring system
- Regime detection and automatic adaptation
- Liquidity sweep and reclaim detection
- Volatility squeeze state machine
- Multi-factor gate with bonus system
- Adaptive risk management
- Comprehensive alert system
- Three dashboard display panels
- Session filter with multipliers
- Multiple trading style presets
- Theme customization options
Developed by BullByte
Pine Script v6
2025
Journal Diario Manual [KEKG]📊 Daily Trading Journal – Manual Profit & Risk Tracker
This indicator is a clean, fully customizable daily trading journal designed to help traders manually track their performance directly on the chart.
✅ Features:
• Manual input for:
• Take Profits (TP)
• Stop Losses (SL)
• Total TP Pips
• Total SL Pips
• Automatic Profit (Pips) calculation:
• Shows + in green for positive results
• Shows − in red for negative results
• Customizable reset system:
• Reset by Day
• Reset by Week
• Manual reset
• Optional reset at a specific time (AM/PM)
• Each reset method can be turned ON or OFF
• Fully adjustable colors:
• Default TP color: #66BB6A
• Default SL color: #F23645
• Editable profit colors and panel background
• Movable panel position (any screen corner)
• Transparent background by default
• Clean, left-aligned professional layout
🎯 Purpose:
This tool is built for discipline, consistency, and performance tracking, helping traders stay aware of:
• Daily results
• Total risk
• Overall profitability
Perfect for Forex, Indices, Commodities, and Crypto traders who want a simple but powerful on-chart journal without automation or broker connection.
200 Week MA Extensions (Crypto Currently Strategy)Bitcoin 200 Week MA Extensions
The 200-week moving average has never been breached in Bitcoin's history, making it one of the most reliable indicators for identifying absolute market bottoms. This indicator plots the 200 Week MA along with percentage extensions above it to help identify potential cycle tops and key resistance levels during bull markets.
What is the 200 Week MA?
The 200-week simple moving average is the average closing price of Bitcoin over the past 200 weeks (approximately 3.8 years). It's a ultra-long-term trend indicator that:
Has never been broken to the downside in Bitcoin's entire history
Acts as the ultimate floor for Bitcoin price during bear markets
Rises steadily over time, reflecting Bitcoin's long-term growth trajectory
Moves slowly, making it a stable reference point for market cycles
Key Components:
200 Week MA - Blue Line (Base Level)
The foundation line that has historically marked absolute bottoms
Currently around $62,000 (and rising ~$500-800 per week)
Touching this level has historically represented generational buying opportunities
Last tested during the COVID crash (March 2020) and 2022 bear market
+50% Extension - Green Line (1.5x the 200 Week MA)
First major resistance zone above the base
Often acts as support during healthy bull market corrections
Historically a comfortable zone for accumulation in early bull markets
+100% Extension - Yellow Line (2.0x the 200 Week MA)
Double the 200 Week MA value
Represents a well-developed bull market
Often tested multiple times during mid-cycle consolidations
Can act as strong resistance when first approached
+150% Extension - Orange Line (2.5x the 200 Week MA)
Advanced bull market territory
Historically marks the acceleration phase of bull runs
Breaking above this level often signals euphoric market conditions approaching
+200% Extension - Red Line (3.0x the 200 Week MA)
Triple the 200 Week MA value
Extreme overextension zone
Historically near or beyond previous cycle tops
Suggests extreme caution and profit-taking considerations
Historical Context:
2020-2021 Bull Market:
March 2020: Price touched the 200 Week MA (~$5,000) - absolute bottom
Throughout 2020: Price traded between +50% and +100% extensions
Late 2020 - Early 2021: Price broke above +100%, accelerated to +150%
April 2021 & November 2021: Price reached +200% extension area, marking local/cycle tops
2022 Bear Market:
Price fell from +200% extension back toward the 200 Week MA
June 2022: Price came within 10% of the 200 Week MA ($18,000)
Bounce from near the 200 Week MA marked the bear market bottom
2023-2024 Recovery:
Price recovered from near 200 Week MA back through the extension levels
Each extension level acted as resistance, then support as bull market developed
Current position relative to extensions helps gauge cycle maturity
How to Use This Indicator:
For Long-Term Accumulation:
At 200 Week MA: Maximum conviction buying zone - historically has never failed
+0% to +50%: Excellent accumulation zone, low risk relative to reward
+50% to +100%: Good accumulation zone during bull market dips
Above +100%: Consider reducing accumulation, focus on holding or taking profits
For Profit Taking:
Approaching +100%: Consider taking initial profits (10-20% of position)
+100% to +150%: Take incremental profits as price advances
+150% to +200%: Increase profit-taking pace significantly
Above +200%: Maximum caution - historically unsustainable levels
For Risk Management:
Distance from 200 Week MA indicates market risk level
Further above = higher risk, more extended, closer to top
Closer to = lower risk, better value, closer to bottom
Use extensions as profit-taking targets in bull markets
Use extensions as re-entry targets during corrections
For Cycle Timing:
Bear Market: Price converges toward 200 Week MA
Early Bull: Price in +0% to +50% range, building base
Mid Bull: Price in +50% to +100% range, healthy growth
Late Bull: Price in +100% to +150% range, acceleration
Euphoric Top: Price at +150% to +200%+, extreme extension
Key Insights:
The 200 Week MA as Ultimate Support:
Bitcoin has touched or approached this level during every major bear market
It rises consistently (~$30,000 per year currently), creating a rising floor
Breaking below would be unprecedented and signal a fundamental market structure change
Provides enormous psychological and technical support
Extension Levels as Resistance/Support:
Bull markets often stall at each extension level before breaking through
Once broken, extensions often flip from resistance to support
Rejections from higher extensions can signal local or cycle tops
Corrections back to lower extensions offer re-entry opportunities
Diminishing Returns:
Each cycle's top has formed at progressively lower extension multiples
2013: ~10x the then-200WMA
2017: ~5x the then-200WMA
2021: ~3x the then-200WMA
Suggests future tops may not reach +200% extension (market maturation)
Best Practices:
Do:
Use the 200 Week MA as your ultimate risk-off level for long-term holdings
Scale into positions as price approaches the 200 Week MA
Take profits incrementally as price rises through extensions
View corrections back to lower extensions as opportunities
Combine with other on-chain metrics (MVRV, Realized Price) for confirmation
Don't:
Expect the 200 Week MA to provide perfect entry timing (you might be early)
Assume price will reach +200% extension every cycle
Sell all holdings at first extension level during bull markets
Ignore price action and volume when making decisions
Panic if price approaches the 200 Week MA (historically the best time to buy)
Why This Indicator Works:
The 200 Week MA represents nearly 4 years of price data, which:
Encompasses approximately one full Bitcoin halving cycle
Smooths out all short and medium-term volatility
Reflects Bitcoin's true long-term adoption and growth trend
Provides a slow-moving, stable reference that doesn't whipsaw
The extension levels work because:
They create objective profit-taking targets based on historical overextension
They account for the rising base (200 Week MA) over time
They've proven reliable across multiple market cycles
They help remove emotion from buy/sell decisions
Technical Notes:
Calculations performed on weekly timeframe data for consistency
The indicator displays correctly on any chart timeframe (Daily, 4H, etc.)
Uses lookahead_on to prevent repainting and show consistent historical values
All extension levels update automatically as the 200 Week MA rises
Best viewed on logarithmic scale for full historical perspective
Important Reminders:
Past performance does not guarantee future results - while the 200 Week MA has never been breached, future market conditions could differ
Market maturation - as Bitcoin matures, cycle dynamics may change
Black swan events - unexpected macro events could temporarily break historical patterns
Not financial advice - this is an educational tool, always do your own research
Recommended Usage:
Best Timeframes: Daily, Weekly, Monthly charts
Pair With: MVRV Ratio, Realized Price, Stock-to-Flow, Fear & Greed Index
Update Frequency: Weekly (the base 200 Week MA only changes weekly)
Chart Type: Logarithmic scale recommended for full historical view
Strategy Example:
Buy aggressively when price is within 20% of 200 Week MA
Hold and accumulate between 200WMA and +50% extension
Begin scaling out profits at +100% extension (20% of position)
Scale out more at +150% extension (40% of position)
Significant profit-taking at +200% extension (remaining position)
Wait for next cycle and repeat
This indicator provides a simple, objective, and historically reliable framework for navigating Bitcoin's market cycles. By respecting the 200 Week MA as the ultimate floor and using the extensions as profit-taking guides, investors can remove emotion and develop disciplined strategies for long-term success.
Float Rotation TrackerFloat Rotation Tracker - Quick Reference Guide
What is Float Rotation?
Float Rotation = Cumulative Daily Volume ÷ Float
Example:
Float = 5,000,000 shares
Day Volume = 7,500,000 shares
Rotation = 7.5M ÷ 5M = 1.5x (150%)
When rotation hits 1x (100%), every available share has theoretically changed hands at least once during the trading day.
Why It Matters
RotationMeaningImplication0.5x50% of float tradedInterest building1.0x 🔥Full rotationExtreme interest confirmed2.0x 🔥🔥Double rotationVery high volatility3.0x 🔥🔥🔥Triple rotationRare - maximum volatility
Key insight: High rotation on a low-float stock = explosive potential
Float Classification
Float SizeClassificationRotation Impact≤ 2M🔥 MICROExtremely volatile, fast rotation≤ 5M🔥 VERY LOWExcellent momentum potential≤ 10MLOWGood for rotation plays> 10MNORMALNeeds massive volume to rotate
Rule of thumb: Focus on stocks with float under 10M for meaningful rotation signals.
Reading the Indicator
Rotation Line (Yellow)
Shows current rotation level
Rises throughout the day as volume accumulates
Crosses horizontal level lines at milestones
Level Lines
LineColorMeaning0.5Gray dotted50% rotation1.0Orange solidFull rotation2.0Red solidDouble rotation3.0Fuchsia solidTriple rotation
Volume Bars (Bottom)
ColorMeaningGrayBelow average volumeBlueNormal volume (1-2x avg)GreenHigh volume (2-5x avg)LimeExtreme volume (5x+ avg)
Milestone Markers
Circles appear when rotation crosses key levels
Labels show "50%", "1x", "2x", "3x🔥"
Background Color
Changes as rotation increases
Darker = higher rotation level
Info Table Explained
FieldDescriptionFloatShare count + classification (MICRO/LOW/NORMAL)SourceAuto ✓ = TradingView data / Manual = user enteredRotationCurrent rotation with emoji indicatorRotation %Same as rotation × 100Day VolumeCumulative volume todayTo XxVolume needed to reach next milestoneBar RVolCurrent bar's relative volumeMilestonesWhich levels have been hit todayPer RotationShares equal to one full rotationEst. TimeBars until next milestone (at current pace)
Trading with Float Rotation
Entry Signals
Early Entry (Higher Risk, Higher Reward)
Rotation approaching 0.5x
Strong price action (bull flag, breakout)
Rising relative volume bars
Confirmation Entry (Lower Risk)
Rotation at or above 1x
Price holding above VWAP
Continuous green/lime volume bars
Late Entry (Highest Risk)
Rotation above 2x
Only enter on clear pullback pattern
Tight stop required
Exit Signals
Warning Signs:
Rotation very high (2x+) with declining volume bars
Reversal candle after milestone
Price breaking below key support
Volume bars turning gray/blue after being green/lime
Take Profits:
Partial profit at each rotation milestone
Trail stop as rotation increases
Full exit on reversal pattern after 2x+ rotation
Best Setups
Ideal Float Rotation Play
✓ Float under 10M (preferably under 5M)
✓ Stock up 5%+ on the day
✓ News catalyst driving interest
✓ Rotation approaching or exceeding 1x
✓ Price above VWAP
✓ Volume bars green or lime
✓ Clear chart pattern (bull flag, flat top)
Red Flags to Avoid
✗ Float over 50M (hard to rotate meaningfully)
✗ Rotation high but price declining
✗ Volume bars turning gray after spike
✗ No clear catalyst
✗ Price below VWAP with high rotation
✗ Late in day (3pm+) after 2x rotation
Float Data Sources
If auto-detect doesn't work, get float from:
SourceHow to FindFinvizfinviz.com → ticker → "Shs Float"Yahoo FinanceFinance.yahoo.com → Statistics → "Float"MarketWatchMarketwatch.com → ticker → ProfileYour BrokerUsually in stock details/fundamentals
Note: Float can change due to offerings, buybacks, lockup expirations. Check recent data.
Settings Guide
Conservative Settings
Alert Level 1: 0.75 (75%)
Alert Level 2: 1.0 (100%)
Alert Level 3: 2.0 (200%)
Alert Level 4: 3.0 (300%)
High Vol Multiplier: 2.0
Extreme Vol Multiplier: 5.0
Aggressive Settings
Alert Level 1: 0.3 (30%)
Alert Level 2: 0.5 (50%)
Alert Level 3: 1.0 (100%)
Alert Level 4: 2.0 (200%)
High Vol Multiplier: 1.5
Extreme Vol Multiplier: 3.0
Alert Setup
Recommended Alerts
100% Rotation (1x) - Primary signal
Most important milestone
Confirms extreme interest
High Rotation + Extreme Volume
Combined condition
Very high probability signal
How to Set
Right-click chart → Add Alert
Condition: Float Rotation Tracker
Select desired milestone
Set notification (popup/email/phone)
Set expiration
Common Questions
Q: Why is my float showing "Manual (no data)"?
A: TradingView doesn't have float data for this stock. Enter the float manually in settings after looking it up on Finviz or Yahoo Finance.
Q: The rotation seems too high/low - is the float wrong?
A: Possibly. Cross-check float on Finviz. Recent offerings or share structure changes may not be reflected in TradingView's data.
Q: What if float rotates early in the day?
A: Early 1x rotation (within first hour) is very bullish - indicates massive interest. Watch for continuation patterns.
Q: High rotation but price is dropping?
A: This is distribution - large holders are selling into demand. High rotation doesn't guarantee price direction, just volatility.
Q: Can I use this for swing trading?
A: The indicator resets daily, so it's designed for intraday use. You could note multi-day rotation patterns manually.
Quick Decision Matrix
RotationPrice ActionVolumeDecision<0.5xStrong upHighWatch, early stage0.5-1xConsolidatingSteadyPrepare entry1x+Breaking outIncreasingEntry on pattern1x+DroppingHighAvoid - distribution2x+Strong upExtremePartial profit, trail stop2x+Reversal candleDecliningExit or avoid
Workflow Integration
MORNING ROUTINE:
1. Scan for gappers (5%+, high volume)
2. Check float on each candidate
3. Apply Float Rotation Tracker
4. Prioritize lowest float with building rotation
DURING SESSION:
5. Watch rotation levels on active trades
6. Enter on patterns when rotation confirms (0.5-1x)
7. Scale out as rotation increases
8. Exit or trail after 2x rotation
END OF DAY:
9. Note which stocks hit 2x+ rotation
10. Review rotation vs price action
11. Learn patterns for future trades
Combining with Other Indicators
IndicatorHow to Use Together5 PillarsScreen for low-float stocks firstGap & GoCheck rotation on gappersBull FlagEnter bull flags with 1x+ rotationVWAPOnly trade rotation plays above VWAPRSIWatch for divergence at high rotation
Key Takeaways
Float size matters - Lower float = faster rotation = more volatility
1x is the key level - Full rotation confirms extreme interest
Volume quality matters - Green/lime bars better than gray
Combine with price action - Rotation confirms, patterns trigger
Know when you're late - 2x+ rotation is late stage
Check your float data - Wrong float = wrong rotation calculation
Happy Trading! 🔥
RAFA's SMC Killer LITEWhat is the SMC Killer?
The Smart Money Concepts (SMC) Killer is a trading indicator that identifies high-probability entry points using three proven strategies:
Break of Structure (BOS) - Trades when price breaks key support/resistance levels
Fair Value Gap (FVG) - Enters when price fills gaps in the market
Order Blocks (OB) - Entry from institutional order clusters (optional display)
This indicator automatically:
✅ Calculates correct entry, take-profit, and stop-loss levels for your asset
✅ Tracks win/loss statistics in real-time
✅ Works on 30+ different futures contracts
✅ Adapts tick size and point value automatically
Asset Selection
Supported Assets
The indicator supports all major futures contracts:
Equity Futures:
ES (E-mini S&P 500)
NQ (E-mini NASDAQ 100)
YM (Mini Dow Jones)
NKD (Nikkei 225)
EMD (E-mini Midcap 400)
RTY (Russell 2000)
Currency Futures:
6A (Australian Dollar)
6B (British Pound)
6C (Canadian Dollar)
6E (Euro FX)
6J (Japanese Yen)
6S (Swiss Franc)
6N (New Zealand Dollar)
Agricultural Futures:
HE (Lean Hogs)
LE (Live Cattle)
GF (Feeder Cattle)
ZC (Corn)
ZW (Wheat)
ZS (Soybeans)
ZM (Soybean Meal)
ZL (Soybean Oil)
Energy Futures:
CL (Crude Oil)
QM (Mini Crude Oil)
NG (Natural Gas)
QG (E-mini Natural Gas)
HO (Heating Oil)
RB (RBOB Gasoline)
Metal Futures:
GC (Gold)
SI (Silver)
HG (Copper)
PL (Platinum)
PA (Palladium)
QI (E-mini Silver)
QO (E-mini Gold)
Micro Futures:
MES (Micro E-mini S&P 500)
MYM (Micro E-mini Dow Jones)
MNQ (Micro E-mini NASDAQ)
M2K (Micro Russell 2000)
MGC (E-Micro Gold)
M6A (E-Micro AUD/USD)
M6E (E-Micro EUR/USD)
MCL (Micro Crude Oil)
How to Select Your Asset
Open the indicator settings (click ⚙️)
Go to ASSET SELECT section
Select Asset Category (e.g., "Metal Futures")
Enter Select Asset Symbol (e.g., "GC" for Gold)
Click OK
The indicator will automatically load the correct:
✅ Tick size
✅ Point value
✅ Risk/reward calculations
Settings Configuration
ASSET SELECT Group
Asset Category: Choose from 6 categories
Select Asset Symbol: Enter symbol (ES, GC, CL, etc.)
STRUCTURE Group
Show Swing Structure: Display swing highs/lows
Swing Length: Bars used for pivot detection (default: 5)
Build Sweep: Show sweep formations (default: ON)
What it does: Identifies the market trend and key turning points
Teal/Green bars = Uptrend
Orange/Red bars = Downtrend
FVG Group
Enable FVG Entry: Use Fair Value Gap strategy
FVG Threshold: Sensitivity filter (default: 0)
What it does: Detects gaps in price action that indicate imbalance
Lower threshold = More signals
Higher threshold = Fewer, high-quality signals
RISK Group
Show Bracket: Display entry/TP/SL lines
Units/Contracts: Number of contracts to trade (default: 6)
Stop Loss ($): Risk amount per trade (default: $250)
Target ($): Profit target per trade (default: $1,000)
Example: If you select ES with $250 stop loss:
The indicator calculates: 250 ÷ (6 contracts × $50 per point) = 0.83 points
Your stop loss line appears 0.83 points below entry
TABLE Group
Show Statistics: Display results table
Position: Table location (default: top_right)
Year: Start tracking from this year
Month: Start tracking from this month
Day: Start tracking from this day
Trading Signals
BUY Signal 🟢
When you see a green "BUY" label below a candle:
Price is breaking higher (Break of Structure)
OR price is filling a gap (Fair Value Gap)
The indicator plots three lines:
Green line = Entry price
Lime/bright green line = Take Profit level
Red line = Stop Loss level
Action: Consider entering a LONG position at market or entry price
SELL Signal 🔴
When you see a red "SELL" label above a candle:
Price is breaking lower (Break of Structure)
OR price is filling a gap (Fair Value Gap)
The indicator plots three lines:
Red line = Entry price
Magenta/pink line = Take Profit level
Orange line = Stop Loss level
Action: Consider entering a SHORT position at market or entry price
Signal Confirmation
✅ Wait for confirmation - Only trade signals on confirmed (closed) bars
✅ Check the trend - Look at candle colors (green uptrend, orange downtrend)
✅ Risk/reward ratio - TP should be at least 2x your SL risk
Risk Management
Position Sizing Example
Trading Gold (GC) with ES Settings:
Units: 6 contracts
Stop Loss: $250
Target: $1,000
Tick Size: 0.1 (automatic for GC)
Point Value: $100 per point (automatic for GC)
Risk per trade: $250
Reward per trade: $1,000
Risk/Reward Ratio: 1:4 (Excellent!)
Stop Loss Strategy
Always place your stop loss below/above the entry lines
The red/orange line shows exactly where to place SL
Never move your stop loss against the trade (unless scaling)
Use hard stops - set them immediately upon entry
Take Profit Strategy
Take profits at the lime/magenta line (TP level)
Consider taking partial profits at 50% of target
Let remaining 50% run to full target
Use trailing stops if price moves in your favor
Risk Per Trade
Formula: (Stop Loss $) ÷ (Units × Point Value)
Example for ES:
Stop Loss: $250
Units: 6
Point Value: $50
Risk per point: 250 ÷ (6 × 50) = 0.83 points
Reading the Chart
Visual Elements
Candle Colors:
🟩 Green/Teal = Uptrend (higher highs and higher lows)
🟥 Orange/Red = Downtrend (lower highs and lower lows)
Signal Labels:
BUY (Green) = Long entry opportunity
SELL (Red) = Short entry opportunity
Bracket Lines:
Entry Line (Solid) = Your entry price
TP Line (Bright color) = Take profit target
SL Line (Red/Orange) = Stop loss level
Success Markers:
✓ (Green checkmark) = Trade hit TP (WIN)
✗ (Red X) = Trade hit SL (LOSS)
Statistics Table
What Each Column Means
📊 ← Current asset being traded
├── Total: Total signals generated (buys + sells)
├── Buy: Number of buy signals
├── Sell: Number of sell signals
├── Win ✓: Trades that hit take profit
├── Loss ✗: Trades that hit stop loss
├── W%: Win rate percentage (wins ÷ total trades)
└── Asset Info: Tick size and point value
Example Reading
📊 ES
Total: 15
Buy: 8
Sell: 7
Win ✓: 10
Loss ✗: 5
W%: 66.7%
Asset Info: Tick: 0.25 | PV: $50
This means:
15 total signals since tracking started
10 wins, 5 losses
66.7% win rate (Professional level!)
Trading ES with 0.25 tick and $50 point value
Trading Examples
Example 1: Gold (GC) Long Trade
Setup:
Asset: Metal Futures → GC
Stop Loss: $150
Target: $600
Units: 2 contracts
What happens:
You see a BUY label on a green candle
Entry line at 2050.0
TP line at 2050.6 (0.6 points higher = $600 profit)
SL line at 2049.85 (0.15 points lower = $150 loss)
Risk/Reward: 1:4 ✅
Trade Result:
Price moves to 2050.6 → Label shows ✓ = WIN
Table updates: Wins increases by 1, Win% increases
Example 2: Crude Oil (CL) Short Trade
Setup:
Asset: Energy Futures → CL
Stop Loss: $500
Target: $2,000
Units: 1 contract
What happens:
You see a SELL label on a red candle
Entry line at 78.50
TP line at 77.50 (1.00 lower = $1,000 profit)
SL line at 79.00 (0.50 higher = $500 loss)
Risk/Reward: 1:2 ✅
Trade Result:
Price drops to 77.50 → Label shows ✓ = WIN
Table updates: Wins increases by 1, Win% increases
Example 3: E-mini S&P (ES) Day Trading
Setup:
Asset: Equity Futures → ES
Stop Loss: $250
Target: $1,000
Units: 6 contracts
Swap Length: 5 (default)
Enable FVG: ON
Morning Session:
See BUY at 5860.25 (swing break)
Hit TP at 5861.08 = WIN ✓
Table shows: Total 1, Buy 1, Win 1, W% 100%
See SELL at 5861.50 (FVG entry)
Hit SL at 5860.67 = LOSS ✗
Table shows: Total 2, Sell 1, Win 1, L% 50%
By end of day: 4 wins, 1 loss, 80% win rate
Troubleshooting
Issue 1: No signals appearing
Solution:
Check if both Show Bracket is ON
Check if Enable FVG Entry is ON
Try changing Swing Length (lower = more signals)
Ensure you're on a 1-hour or higher timeframe
Check chart has enough data (scroll left to see history)
Issue 2: Signals appear but no entry lines
Solution:
Confirm Show Bracket is toggled ON
Check Stop Loss ()andTarget() and Target (
)andTarget() are reasonable amounts
Ensure your Units value is not 0
Try refreshing the chart
Issue 3: Asset not recognized
Solution:
Check spelling of symbol (ES, not E-S)
Verify asset is in the supported list
Check you're in the correct category
Try closing and reopening the chart
Issue 4: Wrong stop loss/target levels
Solution:
Verify correct asset is selected
Check Units setting matches your position size
Verify Stop Loss ($) and Target ($) amounts
Look at Asset Info in table to confirm tick size
Manually calculate: SL $ ÷ (Units × Point Value) = Points
Issue 5: Statistics table not showing
Solution:
Toggle Show Statistics OFF then back ON
Try changing Table Position
Refresh the chart
Check that Show Table is enabled in settings
Issue 6: Indicator acting "heavy" or laggy
Solution:
Turn off Show Swing Structure if not needed
Turn off Show Bracket if reviewing historical trades
Reduce chart's data window (don't load entire years)
Refresh the chart
Pro Tips 🚀
Tip 1: Start with Micro Futures
Micro contracts (MES, MNQ, MCL) have lower cost
Perfect for learning the strategy
Same quality signals, smaller risk
Tip 2: Trade During Peak Hours
Equity Futures: 9:30-16:00 ET (Regular session)
Energy: 18:00-16:00 CT (After hours active)
Metals: 18:00-17:00 CT (Most liquid)
Currencies: 5:00 PM - 4:00 PM ET (24-5 market)
Tip 3: Combine Timeframes
Look for entry on 1-hour chart
Confirm on 15-minute chart
Execute on 5-minute breakout
More confluence = higher probability
Tip 4: Track Your Trades
Keep notes on WIN/LOSS trades
Identify patterns in your losses
Adjust settings based on performance
Use Win% table to monitor improvement
Tip 5: Risk Management First
Never risk more than 2% of account per trade
Respect your stop loss (don't move it)
Take profits when levels are hit
Be patient for high-probability setups
Tip 6: Adjust for Market Conditions
Trending markets: Increase Swing Length (6-8)
Choppy markets: Decrease Swing Length (2-4)
Low volatility: Reduce Stop Loss $
High volatility: Increase Target $
Quick Reference Card
────────────────────────────────────────────────────
SMC KILLER QUICK START ─────────────────────────────────────────────────────
│ 1. Select Asset Category & Symbol
│ 2. Set Units (contracts)
│ 3. Set Stop Loss ($) - your max risk
│ 4. Set Target ($) - your profit goal
│ 5. Wait for BUY (green) or SELL (red) signal
│ 6. Place entry at the entry line
│ 7. Place stop at the red/orange line
│ 8. Place take-profit at the lime/magenta line
│ 9. Close trade when line closes (✓ or ✗)
│ 10. Review statistics and adjust next trade
└─────────────────────────────────────────────────────
BUY Signal = Break Higher OR Fill Gap = LONG
SELL Signal = Break Lower OR Fill Gap = SHORT
Green candles = Uptrend
Orange candles = Downtrend
✓ = Win (took profit)
✗ = Loss (hit stop)
Support & Updates
Check settings are correct for your asset
Ensure adequate chart data is loaded
Test on demo account first
Start with smallest position size
Track performance over 20+ trades
Bifurcation Zone - CAEBifurcation Zone — Cognitive Adversarial Engine (BZ-CAE)
Bifurcation Zone — CAE (BZ-CAE) is a next-generation divergence detection system enhanced by a Cognitive Adversarial Engine that evaluates both sides of every potential trade before presenting signals. Unlike traditional divergence indicators that show every price-oscillator disagreement regardless of context, BZ-CAE applies comprehensive market-state intelligence to identify only the divergences that occur in favorable conditions with genuine probability edges.
The system identifies structural bifurcation points — critical junctures where price and momentum disagree, signaling potential reversals or continuations — then validates these opportunities through five interconnected intelligence layers: Trend Conviction Scoring , Directional Momentum Alignment , Multi-Factor Exhaustion Modeling , Adversarial Validation , and Confidence Scoring . The result is a selective, context-aware signal system that filters noise and highlights high-probability setups.
This is not a "buy the arrow" indicator. It's a decision support framework that teaches you how to read market state, evaluate divergence quality, and make informed trading decisions based on quantified intelligence rather than hope.
What Sets BZ-CAE Apart: Technical Architecture
The Problem With Traditional Divergence Indicators
Most divergence indicators operate on a simple rule: if price makes a higher high and RSI makes a lower high, show a bearish signal. If price makes a lower low and RSI makes a higher low, show a bullish signal. This creates several critical problems:
Context Blindness : They show counter-trend signals in powerful trends that rarely reverse, leading to repeated losses as you fade momentum.
Signal Spam : Every minor price-oscillator disagreement generates an alert, overwhelming you with low-quality setups and creating analysis paralysis.
No Quality Ranking : All signals are treated identically. A marginal divergence in choppy conditions receives the same visual treatment as a high-conviction setup at a major exhaustion point.
Single-Sided Evaluation : They ask "Is this a good long?" without checking if the short case is overwhelmingly stronger, leading you into obvious bad trades.
Static Configuration : You manually choose RSI 14 or Stochastic 14 and hope it works, with no systematic way to validate if that's optimal for your instrument.
BZ-CAE's Solution: Cognitive Adversarial Intelligence
BZ-CAE solves these problems through an integrated five-layer intelligence architecture:
1. Trend Conviction Score (TCS) — 0 to 1 Scale
Most indicators check if ADX is above 25 to determine "trending" conditions. This binary approach misses nuance. TCS is a weighted composite metric:
Formula : 0.35 × normalize(ADX, 10, 35) + 0.35 × structural_strength + 0.30 × htf_alignment
Structural Strength : 10-bar SMA of consecutive directional bars. Captures persistence — are bulls or bears consistently winning?
HTF Alignment : Multi-timeframe EMA stacking (20/50/100/200). When all EMAs align in the same direction, you're in institutional trend territory.
Purpose : Quantifies how "locked in" the trend is. When TCS exceeds your threshold (default 0.80), the system knows to avoid counter-trend trades unless other factors override.
Interpretation :
TCS > 0.85: Very strong trend — counter-trading is extremely high risk
TCS 0.70-0.85: Strong trend — favor continuation, require exhaustion for reversals
TCS 0.50-0.70: Moderate trend — context matters, both directions viable
TCS < 0.50: Weak/choppy — reversals more viable, range-bound conditions
2. Directional Momentum Alignment (DMA) — ATR-Normalized
Formula : (EMA21 - EMA55) / ATR14
This isn't just "price above EMA" — it's a regime-aware momentum gauge. The same $100 price movement reads completely differently in high-volatility crypto versus low-volatility forex. By normalizing with ATR, DMA adapts its interpretation to current market conditions.
Purpose : Quantifies the directional "force" behind current price action. Positive = bullish push, negative = bearish push. Magnitude = strength.
Interpretation :
DMA > 0.7: Strong bullish momentum — bearish divergences risky
DMA 0.3 to 0.7: Moderate bullish bias
DMA -0.3 to 0.3: Balanced/choppy conditions
DMA -0.7 to -0.3: Moderate bearish bias
DMA < -0.7: Strong bearish momentum — bullish divergences risky
3. Multi-Factor Exhaustion Modeling — 0 to 1 Probability
Single-metric exhaustion detection (like "RSI > 80") misses complex market states. BZ-CAE aggregates five independent exhaustion signals:
Volume Spikes : Current volume versus 50-bar average
2.5x average: 0.25 weight
2.0x average: 0.15 weight
1.5x average: 0.10 weight
Divergence Present : The fact that a divergence exists contributes 0.30 weight — structural momentum disagreement is itself an exhaustion signal.
RSI Extremes : Captures oscillator climax zones
RSI > 80 or < 20: 0.25 weight
RSI > 75 or < 25: 0.15 weight
Pin Bar Detection : Identifies rejection candles (2:1 wick-to-body ratio, indicating failed breakout attempts): 0.15 weight
Extended Runs : Consecutive bars above/below EMA20 without pullback
30+ bars: 0.15 weight (market hasn't paused to consolidate)
Total exhaustion score is the sum of all applicable weights, capped at 1.0.
Purpose : Detects when strong trends become vulnerable to reversal. High exhaustion can override trend filters, allowing counter-trend trades at genuine turning points that basic indicators would miss.
Interpretation :
Exhaustion > 0.75: High probability of climax — yellow background shading alerts you visually
Exhaustion 0.50-0.75: Moderate overextension — watch for confirmation
Exhaustion < 0.50: Fresh move — trend can continue, counter-trend trades higher risk
4. Adversarial Validation — Game Theory Applied to Trading
This is BZ-CAE's signature innovation. Before approving any signal, the engine quantifies BOTH sides of the trade simultaneously:
For Bullish Divergences , it calculates:
Bull Case Score (0-1+) :
Distance below EMA20 (pullback quality): up to 0.25
Bullish EMA alignment (close > EMA20 > EMA50): 0.25
Oversold RSI (< 40): 0.25
Volume confirmation (> 1.2x average): 0.25
Bear Case Score (0-1+) :
Price below EMA50 (structural weakness): 0.30
Very oversold RSI (< 30, indicating knife-catching): 0.20
Differential = Bull Case - Bear Case
If differential < -0.10 (default threshold), the bear case is dominating — signal is BLOCKED or ANNOTATED.
For Bearish Divergences , the logic inverts (Bear Case vs Bull Case).
Purpose : Prevents trades where you're fighting obvious strength in the opposite direction. This is institutional-grade risk management — don't just evaluate your trade, evaluate the counter-trade simultaneously.
Why This Matters : You might see a bullish divergence at a local low, but if price is deeply below major support EMAs with strong bearish momentum, you're catching a falling knife. The adversarial check catches this and blocks the signal.
5. Confidence Scoring — 0 to 1 Quality Assessment
Every signal that passes initial filters receives a comprehensive quality score:
Formula :
0.30 × normalize(TCS) // Trend context
+ 0.25 × normalize(|DMA|) // Momentum magnitude
+ 0.20 × pullback_quality // Entry distance from EMA20
+ 0.15 × state_quality // ADX + alignment + structure
+ 0.10 × divergence_strength // Slope separation magnitude
+ adversarial_bonus (0-0.30) // Your side's advantage
Purpose : Ranks setup quality for filtering and position sizing decisions. You can set a minimum confidence threshold (default 0.35) to ensure only quality setups reach your chart.
Interpretation :
Confidence > 0.70: Premium setup — consider increased position size
Confidence 0.50-0.70: Good quality — standard size
Confidence 0.35-0.50: Acceptable — reduced size or skip if conservative
Confidence < 0.35: Marginal — blocked in Filtering mode, annotated in Advisory mode
CAE Operating Modes: Learning vs Enforcement
Off : Disables all CAE logic. Raw divergence pipeline only. Use for baseline comparison.
Advisory : Shows ALL signals regardless of CAE evaluation, but annotates signals that WOULD be blocked with specific warnings (e.g., "Bull: strong downtrend (TCS=0.87)" or "Adversarial bearish"). This is your learning mode — see CAE's decision logic in action without missing educational opportunities.
Filtering : Actively blocks low-quality signals. Only setups that pass all enabled gates (Trend Filter, Adversarial Validation, Confidence Gating) reach your chart. This is your live trading mode — trust the system to enforce discipline.
CAE Filter Gates: Three-Layer Protection
When CAE is enabled, signals must pass through three independent gates (each can be toggled on/off):
Gate 1: Strong Trend Filter
If TCS ≥ tcs_threshold (default 0.80)
And signal is counter-trend (bullish in downtrend or bearish in uptrend)
And exhaustion < exhaustion_required (default 0.50)
Then: BLOCK signal
Logic: Don't fade strong trends unless the move is clearly overextended
Gate 2: Adversarial Validation
Calculate both bull case and bear case scores
If opposing case dominates by more than adv_threshold (default 0.10)
Then: BLOCK signal
Logic: Avoid trades where you're fighting obvious strength in the opposite direction
Gate 3: Confidence Gating
Calculate composite confidence score (0-1)
If confidence < min_confidence (default 0.35)
Then: In Filtering mode, BLOCK signal; in Advisory mode, ANNOTATE with warning
Logic: Only take setups with minimum quality threshold
All three gates work together. A signal must pass ALL enabled gates to fire.
Visual Intelligence System
Bifurcation Zones (Supply/Demand Blocks)
When a divergence signal fires, BZ-CAE draws a semi-transparent box extending 15 bars forward from the signal pivot:
Demand Zones (Bullish) : Theme-colored box (cyan in Cyberpunk, blue in Professional, etc.) labeled "Demand" — marks where smart money likely placed buy orders as price diverged at the low.
Supply Zones (Bearish) : Theme-colored box (magenta in Cyberpunk, orange in Professional) labeled "Supply" — marks where smart money likely placed sell orders as price diverged at the high.
Theory : Divergences represent institutional disagreement with the crowd. The crowd pushed price to an extreme (new high or low), but momentum (oscillator) is waning, indicating smart money is taking the opposite side. These zones mark order placement areas that become future support/resistance.
Use Cases :
Exit targets: Take profit when price returns to opposite-side zone
Re-entry levels: If price returns to your entry zone, consider adding
Stop placement: Place stops just beyond your zone (below demand, above supply)
Auto-Cleanup : System keeps the last 20 zones to prevent chart clutter.
Adversarial Bar Coloring — Real-Time Market Debate Heatmap
Each bar is colored based on the Bull Case vs Bear Case differential:
Strong Bull Advantage (diff > 0.3): Full theme bull color (e.g., cyan)
Moderate Bull Advantage (diff > 0.1): 50% transparency bull
Neutral (diff -0.1 to 0.1): Gray/neutral theme
Moderate Bear Advantage (diff < -0.1): 50% transparency bear
Strong Bear Advantage (diff < -0.3): Full theme bear color (e.g., magenta)
This creates a real-time visual heatmap showing which side is "winning" the market debate. When bars flip from cyan to magenta (or vice versa), you're witnessing a shift in adversarial advantage — a leading indicator of potential momentum changes.
Exhaustion Shading
When exhaustion score exceeds 0.75, the chart background displays a semi-transparent yellow highlight. This immediate visual warning alerts you that the current move is at high risk of reversal, even if trend indicators remain strong.
Visual Themes — Six Aesthetic Options
Cyberpunk : Cyan/Magenta/Yellow — High contrast, neon aesthetic, excellent for dark-themed trading environments
Professional : Blue/Orange/Green — Corporate color palette, suitable for presentations and professional documentation
Ocean : Teal/Red/Cyan — Aquatic palette, calming for extended monitoring sessions
Fire : Orange/Red/Coral — Warm aggressive colors, high energy
Matrix : Green/Red/Lime — Code aesthetic, homage to classic hacker visuals
Monochrome : White/Gray — Minimal distraction, maximum focus on price action
All visual elements (signal markers, zones, bar colors, dashboard) adapt to your selected theme.
Divergence Engine — Core Detection System
What Are Divergences?
Divergences occur when price action and momentum indicators disagree, creating structural tension that often resolves in a change of direction:
Regular Divergence (Reversal Signal) :
Bearish Regular : Price makes higher high, oscillator makes lower high → Potential trend reversal down
Bullish Regular : Price makes lower low, oscillator makes higher low → Potential trend reversal up
Hidden Divergence (Continuation Signal) :
Bearish Hidden : Price makes lower high, oscillator makes higher high → Downtrend continuation
Bullish Hidden : Price makes higher low, oscillator makes lower low → Uptrend continuation
Both types can be enabled/disabled independently in settings.
Pivot Detection Methods
BZ-CAE uses symmetric pivot detection with separate lookback and lookforward periods (default 5/5):
Pivot High : Bar where high > all highs within lookback range AND high > all highs within lookforward range
Pivot Low : Bar where low < all lows within lookback range AND low < all lows within lookforward range
This ensures structural validity — the pivot must be a clear local extreme, not just a minor wiggle.
Divergence Validation Requirements
For a divergence to be confirmed, it must satisfy:
Slope Disagreement : Price slope and oscillator slope must move in opposite directions (for regular divs) or same direction with inverted highs/lows (for hidden divs)
Minimum Slope Change : |osc_slope| > min_slope_change / 100 (default 1.0) — filters weak, marginal divergences
Maximum Lookback Range : Pivots must be within max_lookback bars (default 60) — prevents ancient, irrelevant divergences
ATR-Normalized Strength : Divergence strength = min(|price_slope| × |osc_slope| × 10, 1.0) — quantifies the magnitude of disagreement in volatility context
Regular divergences receive 1.0× weight; hidden divergences receive 0.8× weight (slightly less reliable historically).
Oscillator Options — Five Professional Indicators
RSI (Relative Strength Index) : Classic overbought/oversold momentum indicator. Best for: General purpose divergence detection across all instruments.
Stochastic : Range-bound %K momentum comparing close to high-low range. Best for: Mean reversion strategies and range-bound markets.
CCI (Commodity Channel Index) : Measures deviation from statistical mean, auto-normalized to 0-100 scale. Best for: Cyclical instruments and commodities.
MFI (Money Flow Index) : Volume-weighted RSI incorporating money flow. Best for: Volume-driven markets like stocks and crypto.
Williams %R : Inverse stochastic looking back over period, auto-adjusted to 0-100. Best for: Reversal detection at extremes.
Each oscillator has adjustable length (2-200, default 14) and smoothing (1-20, default 1). You also set overbought (50-100, default 70) and oversold (0-50, default 30) thresholds.
Signal Timing Modes — Understanding Repainting
BZ-CAE offers two timing policies with complete transparency about repainting behavior:
Realtime (1-bar, peak-anchored)
How It Works :
Detects peaks 1 bar ago using pattern: high > high AND high > high
Signal prints on the NEXT bar after peak detection (bar_index)
Visual marker anchors to the actual PEAK bar (bar_index - 1, offset -1)
Signal locks in when bar CONFIRMS (closes)
Repainting Behavior :
On the FORMING bar (before close), the peak condition may change as new prices arrive
Once bar CLOSES (barstate.isconfirmed), signal is locked permanently
This is preview/early warning behavior by design
Best For :
Active monitoring and immediate alerts
Learning the system (seeing signals develop in real-time)
Responsive entry if you're watching the chart live
Confirmed (lookforward)
How It Works :
Uses Pine Script's built-in ta.pivothigh() and ta.pivotlow() functions
Requires full pivot validation period (lookback + lookforward bars)
Signal prints pivot_lookforward bars after the actual peak (default 5-bar delay)
Visual marker anchors to the actual peak bar (offset -pivot_lookforward)
No Repainting Behavior
Best For :
Backtesting and historical analysis
Conservative entries requiring full confirmation
Automated trading systems
Swing trading with larger timeframes
Tradeoff :
Delayed entry by pivot_lookforward bars (typically 5 bars)
On a 5-minute chart, this is a 25-minute delay
On a 4-hour chart, this is a 20-hour delay
Recommendation : Use Confirmed for backtesting to verify system performance honestly. Use Realtime for live monitoring only if you're actively watching the chart and understand pre-confirmation repainting behavior.
Signal Spacing System — Anti-Spam Architecture
Even after CAE filtering, raw divergences can cluster. The spacing system enforces separation:
Three Independent Filters
1. Min Bars Between ANY Signals (default 12):
Prevents rapid-fire clustering across both directions
If last signal (bull or bear) was within N bars, block new signal
Ensures breathing room between all setups
2. Min Bars Between SAME-SIDE Signals (default 24, optional enforcement):
Prevents bull-bull or bear-bear spam
Separate tracking for bullish and bearish signal timelines
Toggle enforcement on/off
3. Min ATR Distance From Last Signal (default 0, optional):
Requires price to move N × ATR from last signal location
Ensures meaningful price movement between setups
0 = disabled, 0.5-2.0 = typical range for enabled
All three filters work independently. A signal must pass ALL enabled filters to proceed.
Practical Guidance :
Scalping (1-5m) : Any 6-10, Same-side 12-20, ATR 0-0.5
Day Trading (15m-1H) : Any 12, Same-side 24, ATR 0-1.0
Swing Trading (4H-D) : Any 20-30, Same-side 40-60, ATR 1.0-2.0
Dashboard — Real-Time Control Center
The dashboard (toggleable, four corner positions, three sizes) provides comprehensive system intelligence:
Oscillator Section
Current oscillator type and value
State: OVERBOUGHT / OVERSOLD / NEUTRAL (color-coded)
Length parameter
Cognitive Engine Section
TCS (Trend Conviction Score) :
Current value with emoji state indicator
🔥 = Strong trend (>0.75)
📊 = Moderate trend (0.50-0.75)
〰️ = Weak/choppy (<0.50)
Color: Red if above threshold (trend filter active), yellow if moderate, green if weak
DMA (Directional Momentum Alignment) :
Current value with emoji direction indicator
🐂 = Bullish momentum (>0.5)
⚖️ = Balanced (-0.5 to 0.5)
🐻 = Bearish momentum (<-0.5)
Color: Green if bullish, red if bearish
Exhaustion :
Current value with emoji warning indicator
⚠️ = High exhaustion (>0.75)
🟡 = Moderate (0.50-0.75)
✓ = Low (<0.50)
Color: Red if high, yellow if moderate, green if low
Pullback :
Quality of current distance from EMA20
Values >0.6 are ideal entry zones (not too close, not too far)
Bull Case / Bear Case (if Adversarial enabled):
Current scores for both sides of the market debate
Differential with emoji indicator:
📈 = Bull advantage (>0.2)
➡️ = Balanced (-0.2 to 0.2)
📉 = Bear advantage (<-0.2)
Last Signal Metrics Section (New Feature)
When a signal fires, this section captures and displays:
Signal type (BULL or BEAR)
Bars elapsed since signal
Confidence % at time of signal
TCS value at signal time
DMA value at signal time
Purpose : Provides a historical reference for learning. You can see what the market state looked like when the last signal fired, helping you correlate outcomes with conditions.
Statistics Section
Total Signals : Lifetime count across session
Blocked Signals : Count and percentage (filter effectiveness metric)
Bull Signals : Total bullish divergences
Bear Signals : Total bearish divergences
Purpose : System health monitoring. If blocked % is very high (>60%), filters may be too strict. If very low (<10%), filters may be too loose.
Advisory Annotations
When CAE Mode = Advisory, this section displays warnings for signals that would be blocked in Filtering mode:
Examples:
"Bull spacing: wait 8 bars"
"Bear: strong uptrend (TCS=0.87)"
"Adversarial bearish"
"Low confidence 32%"
Multiple warnings can stack, separated by " | ". This teaches you CAE's decision logic transparently.
How to Use BZ-CAE — Complete Workflow
Phase 1: Initial Setup (First Session)
Apply BZ-CAE to your chart
Select your preferred Visual Theme (Cyberpunk recommended for visibility)
Set Signal Timing to "Confirmed (lookforward)" for learning
Choose your Oscillator Type (RSI recommended for general use, length 14)
Set Overbought/Oversold to 70/30 (standard)
Enable both Regular Divergence and Hidden Divergence
Set Pivot Lookback/Lookforward to 5/5 (balanced structure)
Enable CAE Intelligence
Set CAE Mode to "Advisory" (learning mode)
Enable all three CAE filters: Strong Trend Filter , Adversarial Validation , Confidence Gating
Enable Show Dashboard , position Top Right, size Normal
Enable Draw Bifurcation Zones and Adversarial Bar Coloring
Phase 2: Learning Period (Weeks 1-2)
Goal : Understand how CAE evaluates market state and filters signals.
Activities :
Watch the dashboard during signals :
Note TCS values when counter-trend signals fail — this teaches you the trend strength threshold for your instrument
Observe exhaustion patterns at actual turning points — learn when overextension truly matters
Study adversarial differential at signal times — see when opposing cases dominate
Review blocked signals (orange X-crosses):
In Advisory mode, you see everything — signals that would pass AND signals that would be blocked
Check the advisory annotations to understand why CAE would block
Track outcomes: Were the blocks correct? Did those signals fail?
Use Last Signal Metrics :
After each signal, check the dashboard capture of confidence, TCS, and DMA
Journal these values alongside trade outcomes
Identify patterns: Do confidence >0.70 signals work better? Does your instrument respect TCS >0.85?
Understand your instrument's "personality" :
Trending instruments (indices, major forex) may need TCS threshold 0.85-0.90
Choppy instruments (low-cap stocks, exotic pairs) may work best with TCS 0.70-0.75
High-volatility instruments (crypto) may need wider spacing
Low-volatility instruments may need tighter spacing
Phase 3: Calibration (Weeks 3-4)
Goal : Optimize settings for your specific instrument, timeframe, and style.
Calibration Checklist :
Min Confidence Threshold :
Review confidence distribution in your signal journal
Identify the confidence level below which signals consistently fail
Set min_confidence slightly above that level
Day trading : 0.35-0.45
Swing trading : 0.40-0.55
Scalping : 0.30-0.40
TCS Threshold :
Find the TCS level where counter-trend signals consistently get stopped out
Set tcs_threshold at or slightly below that level
Trending instruments : 0.85-0.90
Mixed instruments : 0.80-0.85
Choppy instruments : 0.75-0.80
Exhaustion Override Level :
Identify exhaustion readings that marked genuine reversals
Set exhaustion_required just below the average
Typical range : 0.45-0.55
Adversarial Threshold :
Default 0.10 works for most instruments
If you find CAE is too conservative (blocking good trades), raise to 0.15-0.20
If signals are still getting caught in opposing momentum, lower to 0.07-0.09
Spacing Parameters :
Count bars between quality signals in your journal
Set min bars ANY to ~60% of that average
Set min bars SAME-SIDE to ~120% of that average
Scalping : Any 6-10, Same 12-20
Day trading : Any 12, Same 24
Swing : Any 20-30, Same 40-60
Oscillator Selection :
Try different oscillators for 1-2 weeks each
Track win rate and average winner/loser by oscillator type
RSI : Best for general use, clear OB/OS
Stochastic : Best for range-bound, mean reversion
MFI : Best for volume-driven markets
CCI : Best for cyclical instruments
Williams %R : Best for reversal detection
Phase 4: Live Deployment
Goal : Disciplined execution with proven, calibrated system.
Settings Changes :
Switch CAE Mode from Advisory to Filtering
System now actively blocks low-quality signals
Only setups passing all gates reach your chart
Keep Signal Timing on Confirmed for conservative entries
OR switch to Realtime if you're actively monitoring and want faster entries (accept pre-confirmation repaint risk)
Use your calibrated thresholds from Phase 3
Enable high-confidence alerts: "⭐ High Confidence Bullish/Bearish" (>0.70)
Trading Discipline Rules :
Respect Blocked Signals :
If CAE blocks a trade you wanted to take, TRUST THE SYSTEM
Don't manually override — if you consistently disagree, return to Phase 2/3 calibration
The block exists because market state failed intelligence checks
Confidence-Based Position Sizing :
Confidence >0.70: Standard or increased size (e.g., 1.5-2.0% risk)
Confidence 0.50-0.70: Standard size (e.g., 1.0% risk)
Confidence 0.35-0.50: Reduced size (e.g., 0.5% risk) or skip if conservative
TCS-Based Management :
High TCS + counter-trend signal: Use tight stops, quick exits (you're fading momentum)
Low TCS + reversal signal: Use wider stops, trail aggressively (genuine reversal potential)
Exhaustion Awareness :
Exhaustion >0.75 (yellow shading): Market is overextended, reversal risk is elevated — consider early exit or tighter trailing stops even on winning trades
Exhaustion <0.30: Continuation bias — hold for larger move, wide trailing stops
Adversarial Context :
Strong differential against you (e.g., bullish signal with bear diff <-0.2): Use very tight stops, consider skipping
Strong differential with you (e.g., bullish signal with bull diff >0.2): Trail aggressively, this is your tailwind
Practical Settings by Timeframe & Style
Scalping (1-5 Minute Charts)
Objective : High frequency, tight stops, quick reversals in fast-moving markets.
Oscillator :
Type: RSI or Stochastic (fast response to quick moves)
Length: 9-11 (more responsive than standard 14)
Smoothing: 1 (no lag)
OB/OS: 65/35 (looser thresholds ensure frequent crossings in fast conditions)
Divergence :
Pivot Lookback/Lookforward: 3/3 (tight structure, catch small swings)
Max Lookback: 40-50 bars (recent structure only)
Min Slope Change: 0.8-1.0 (don't be overly strict)
CAE :
Mode: Advisory first (learn), then Filtering
Min Confidence: 0.30-0.35 (lower bar for speed, accept more signals)
TCS Threshold: 0.70-0.75 (allow more counter-trend opportunities)
Exhaustion Required: 0.45-0.50 (moderate override)
Strong Trend Filter: ON (still respect major intraday trends)
Adversarial: ON (critical for scalping protection — catches bad entries quickly)
Spacing :
Min Bars ANY: 6-10 (fast pace, many setups)
Min Bars SAME-SIDE: 12-20 (prevent clustering)
Min ATR Distance: 0 or 0.5 (loose)
Timing : Realtime (speed over precision, but understand repaint risk)
Visuals :
Signal Size: Tiny (chart clarity in busy conditions)
Show Zones: Optional (can clutter on low timeframes)
Bar Coloring: ON (helps read momentum shifts quickly)
Dashboard: Small size (corner reference, not main focus)
Key Consideration : Scalping generates noise. Even with CAE, expect lower win rate (45-55%) but aim for favorable R:R (2:1 or better). Size conservatively.
Day Trading (15-Minute to 1-Hour Charts)
Objective : Balance quality and frequency. Standard divergence trading approach.
Oscillator :
Type: RSI or MFI (proven reliability, volume confirmation with MFI)
Length: 14 (industry standard, well-studied)
Smoothing: 1-2
OB/OS: 70/30 (classic levels)
Divergence :
Pivot Lookback/Lookforward: 5/5 (balanced structure)
Max Lookback: 60 bars
Min Slope Change: 1.0 (standard strictness)
CAE :
Mode: Filtering (enforce discipline from the start after brief Advisory learning)
Min Confidence: 0.35-0.45 (quality filter without being too restrictive)
TCS Threshold: 0.80-0.85 (respect strong trends)
Exhaustion Required: 0.50 (balanced override threshold)
Strong Trend Filter: ON
Adversarial: ON
Confidence Gating: ON (all three filters active)
Spacing :
Min Bars ANY: 12 (breathing room between all setups)
Min Bars SAME-SIDE: 24 (prevent bull/bear clusters)
Min ATR Distance: 0-1.0 (optional refinement, typically 0.5-1.0)
Timing : Confirmed (1-bar delay for reliability, no repainting)
Visuals :
Signal Size: Tiny or Small
Show Zones: ON (useful reference for exits/re-entries)
Bar Coloring: ON (context awareness)
Dashboard: Normal size (full visibility)
Key Consideration : This is the "sweet spot" timeframe for BZ-CAE. Market structure is clear, CAE has sufficient data, and signal frequency is manageable. Expect 55-65% win rate with proper execution.
Swing Trading (4-Hour to Daily Charts)
Objective : Quality over quantity. High conviction only. Larger stops and targets.
Oscillator :
Type: RSI or CCI (robust on higher timeframes, smooth longer waves)
Length: 14-21 (capture larger momentum swings)
Smoothing: 1-3
OB/OS: 70/30 or 75/25 (strict extremes)
Divergence :
Pivot Lookback/Lookforward: 5/5 or 7/7 (structural purity, major swings only)
Max Lookback: 80-100 bars (broader historical context)
Min Slope Change: 1.2-1.5 (require strong, undeniable divergence)
CAE :
Mode: Filtering (strict enforcement, premium setups only)
Min Confidence: 0.40-0.55 (high bar for entry)
TCS Threshold: 0.85-0.95 (very strong trend protection — don't fade established HTF trends)
Exhaustion Required: 0.50-0.60 (higher bar for override — only extreme exhaustion justifies counter-trend)
Strong Trend Filter: ON (critical on HTF)
Adversarial: ON (avoid obvious bad trades)
Confidence Gating: ON (quality gate essential)
Spacing :
Min Bars ANY: 20-30 (substantial separation)
Min Bars SAME-SIDE: 40-60 (significant breathing room)
Min ATR Distance: 1.0-2.0 (require meaningful price movement)
Timing : Confirmed (purity over speed, zero repaint for swing accuracy)
Visuals :
Signal Size: Small or Normal (clear markers on zoomed-out view)
Show Zones: ON (important HTF levels)
Bar Coloring: ON (long-term trend awareness)
Dashboard: Normal or Large (comprehensive analysis)
Key Consideration : Swing signals are rare but powerful. Expect 2-5 signals per month per instrument. Win rate should be 60-70%+ due to stringent filtering. Position size can be larger given confidence.
Dashboard Interpretation Reference
TCS (Trend Conviction Score) States
0.00-0.50: Weak/Choppy
Emoji: 〰️
Color: Green/cyan
Meaning: No established trend. Range-bound or consolidating. Both reversal and continuation signals viable.
Action: Reversals (regular divs) are safer. Use wider profit targets (market has room to move). Consider mean reversion strategies.
0.50-0.75: Moderate Trend
Emoji: 📊
Color: Yellow/neutral
Meaning: Developing trend but not locked in. Context matters significantly.
Action: Check DMA and exhaustion. If DMA confirms trend and exhaustion is low, favor continuation (hidden divs). If exhaustion is high, reversals are viable.
0.75-0.85: Strong Trend
Emoji: 🔥
Color: Orange/warning
Meaning: Well-established trend with persistence. Counter-trend is high risk.
Action: Require exhaustion >0.50 for counter-trend entries. Favor continuation signals. Use tight stops on counter-trend attempts.
0.85-1.00: Very Strong Trend
Emoji: 🔥🔥
Color: Red/danger (if counter-trading)
Meaning: Locked-in institutional trend. Extremely high risk to fade.
Action: Avoid counter-trend unless exhaustion >0.75 (yellow shading). Focus exclusively on continuation opportunities. Momentum is king here.
DMA (Directional Momentum Alignment) Zones
-2.0 to -1.0: Strong Bearish Momentum
Emoji: 🐻🐻
Color: Dark red
Meaning: Powerful downside force. Sellers are in control.
Action: Bullish divergences are counter-momentum (high risk). Bearish divergences are with-momentum (lower risk). Size down on longs.
-0.5 to 0.5: Neutral/Balanced
Emoji: ⚖️
Color: Gray/neutral
Meaning: No strong directional bias. Choppy or consolidating.
Action: Both directions have similar probability. Focus on confidence score and adversarial differential for edge.
1.0 to 2.0: Strong Bullish Momentum
Emoji: 🐂🐂
Color: Bright green/cyan
Meaning: Powerful upside force. Buyers are in control.
Action: Bearish divergences are counter-momentum (high risk). Bullish divergences are with-momentum (lower risk). Size down on shorts.
Exhaustion States
0.00-0.50: Fresh Move
Emoji: ✓
Color: Green
Meaning: Trend is healthy, not overextended. Room to run.
Action: Counter-trend trades are premature. Favor continuation. Hold winners for larger moves. Avoid early exits.
0.50-0.75: Mature Move
Emoji: 🟡
Color: Yellow
Meaning: Move is aging. Watch for signs of climax.
Action: Tighten trailing stops on winning trades. Be ready for reversals. Don't add to positions aggressively.
0.75-0.85: High Exhaustion
Emoji: ⚠️
Color: Orange
Background: Yellow shading appears
Meaning: Move is overextended. Reversal risk elevated significantly.
Action: Counter-trend reversals are higher probability. Consider early exits on with-trend positions. Size up on reversal divergences (if CAE allows).
0.85-1.00: Critical Exhaustion
Emoji: ⚠️⚠️
Color: Red
Background: Yellow shading intensifies
Meaning: Climax conditions. Reversal imminent or underway.
Action: Aggressive reversal trades justified. Exit all with-trend positions. This is where major turns occur.
Confidence Score Tiers
0.00-0.30: Low Quality
Color: Red
Status: Blocked in Filtering mode
Action: Skip entirely. Setup lacks fundamental quality across multiple factors.
0.30-0.50: Moderate Quality
Color: Yellow/orange
Status: Marginal — passes in Filtering only if >min_confidence
Action: Reduced position size (0.5-0.75% risk). Tight stops. Conservative profit targets. Skip if you're selective.
0.50-0.70: High Quality
Color: Green/cyan
Status: Good setup across most quality factors
Action: Standard position size (1.0-1.5% risk). Normal stops and targets. This is your bread-and-butter trade.
0.70-1.00: Premium Quality
Color: Bright green/gold
Status: Exceptional setup — all factors aligned
Visual: Double confidence ring appears
Action: Consider increased position size (1.5-2.0% risk, maximum). Wider stops. Larger targets. High probability of success. These are rare — capitalize when they appear.
Adversarial Differential Interpretation
Bull Differential > 0.3 :
Visual: Strong cyan/green bar colors
Meaning: Bull case strongly dominates. Buyers have clear advantage.
Action: Bullish divergences favored (with-advantage). Bearish divergences face headwind (reduce size or skip). Momentum is bullish.
Bull Differential 0.1 to 0.3 :
Visual: Moderate cyan/green transparency
Meaning: Moderate bull advantage. Buyers have edge but not overwhelming.
Action: Both directions viable. Slight bias toward longs.
Differential -0.1 to 0.1 :
Visual: Gray/neutral bars
Meaning: Balanced debate. No clear advantage either side.
Action: Rely on other factors (confidence, TCS, exhaustion) for direction. Adversarial is neutral.
Bear Differential -0.3 to -0.1 :
Visual: Moderate red/magenta transparency
Meaning: Moderate bear advantage. Sellers have edge but not overwhelming.
Action: Both directions viable. Slight bias toward shorts.
Bear Differential < -0.3 :
Visual: Strong red/magenta bar colors
Meaning: Bear case strongly dominates. Sellers have clear advantage.
Action: Bearish divergences favored (with-advantage). Bullish divergences face headwind (reduce size or skip). Momentum is bearish.
Last Signal Metrics — Post-Trade Analysis
After a signal fires, dashboard captures:
Type : BULL or BEAR
Bars Ago : How long since signal (updates every bar)
Confidence : What was the quality score at signal time
TCS : What was trend conviction at signal time
DMA : What was momentum alignment at signal time
Use Case : Post-trade journaling and learning.
Example: "BULL signal 12 bars ago. Confidence: 68%, TCS: 0.42, DMA: -0.85"
Analysis : This was a bullish reversal (regular div) with good confidence, weak trend (TCS), but strong bearish momentum (DMA). The bet was that momentum would reverse — a counter-momentum play requiring exhaustion confirmation. Check if exhaustion was high at that time to justify the entry.
Track patterns:
Do your best trades have confidence >0.65?
Do low-TCS signals (<0.50) work better for you?
Are you more successful with-momentum (DMA aligned with signal) or counter-momentum?
Troubleshooting Guide
Problem: No Signals Appearing
Symptoms : Chart loads, dashboard shows metrics, but no divergence signals fire.
Diagnosis Checklist :
Check dashboard oscillator value : Is it crossing OB/OS levels (70/30)? If oscillator stays in 40-60 range constantly, it can't reach extremes needed for divergence detection.
Are pivots forming? : Look for local swing highs/lows on your chart. If price is in tight consolidation, pivots may not meet lookback/lookforward requirements.
Is spacing too tight? : Check "Last Signal" metrics — how many bars since last signal? If <12 and your min_bars_ANY is 12, spacing filter is blocking.
Is CAE blocking everything? : Check dashboard Statistics section — what's the blocked signal count? High blocks indicate overly strict filters.
Solutions :
Loosen OB/OS Temporarily :
Try 65/35 to verify divergence detection works
If signals appear, the issue was threshold strictness
Gradually tighten back to 67/33, then 70/30 as appropriate
Lower Min Confidence :
Try 0.25-0.30 (diagnostic level)
If signals appear, filter was too strict
Raise gradually to find sweet spot (0.35-0.45 typical)
Disable Strong Trend Filter Temporarily :
Turn off in CAE settings
If signals appear, TCS threshold was blocking everything
Re-enable and lower TCS_threshold to 0.70-0.75
Reduce Min Slope Change :
Try 0.7-0.8 (from default 1.0)
Allows weaker divergences through
Helpful on low-volatility instruments
Widen Spacing :
Set min_bars_ANY to 6-8
Set min_bars_SAME_SIDE to 12-16
Reduces time between allowed signals
Check Timing Mode :
If using Confirmed, remember there's a pivot_lookforward delay (5+ bars)
Switch to Realtime temporarily to verify system is working
Realtime has no delay but repaints
Verify Oscillator Settings :
Length 14 is standard but might not fit all instruments
Try length 9-11 for faster response
Try length 18-21 for slower, smoother response
Problem: Too Many Signals (Signal Spam)
Symptoms : Dashboard shows 50+ signals in Statistics, confidence scores mostly <0.40, signals clustering close together.
Solutions :
Raise Min Confidence :
Try 0.40-0.50 (quality filter)
Blocks bottom-tier setups
Targets top 50-60% of divergences only
Tighten OB/OS :
Use 70/30 or 75/25
Requires more extreme oscillator readings
Reduces false divergences in mid-range
Increase Min Slope Change :
Try 1.2-1.5 (from default 1.0)
Requires stronger, more obvious divergences
Filters marginal slope disagreements
Raise TCS Threshold :
Try 0.85-0.90 (from default 0.80)
Stricter trend filter blocks more counter-trend attempts
Favors only strongest trend alignment
Enable ALL CAE Gates :
Turn on Trend Filter + Adversarial + Confidence
Triple-layer protection
Blocks aggressively — expect 20-40% reduction in signals
Widen Spacing :
min_bars_ANY: 15-20 (from 12)
min_bars_SAME_SIDE: 30-40 (from 24)
Creates substantial breathing room
Switch to Confirmed Timing :
Removes realtime preview noise
Ensures full pivot validation
5-bar delay filters many false starts
Problem: Signals in Strong Trends Get Stopped Out
Symptoms : You take a bullish divergence in a downtrend (or bearish in uptrend), and it immediately fails. Dashboard showed high TCS at the time.
Analysis : This is INTENDED behavior — CAE is protecting you from low-probability counter-trend trades.
Understanding :
Check Last Signal Metrics in dashboard — what was TCS when signal fired?
If TCS was >0.85 and signal was counter-trend, CAE correctly identified it as high risk
Strong trends rarely reverse cleanly without major exhaustion
Your losses here are the system working as designed (blocking bad odds)
If You Want to Override (Not Recommended) :
Lower TCS_threshold to 0.70-0.75 (allows more counter-trend)
Lower exhaustion_required to 0.40 (easier override)
Disable Strong Trend Filter entirely (very risky)
Better Approach :
TRUST THE FILTER — it's preventing costly mistakes
Wait for exhaustion >0.75 (yellow shading) before counter-trending strong TCS
Focus on continuation signals (hidden divs) in high-TCS environments
Use Advisory mode to see what CAE is blocking and learn from outcomes
Problem: Adversarial Blocking Seems Wrong
Symptoms : You see a divergence that "looks good" visually, but CAE blocks with "Adversarial bearish/bullish" warning.
Diagnosis :
Check dashboard Bull Case and Bear Case scores at that moment
Look at Differential value
Check adversarial bar colors — was there strong coloring against your intended direction?
Understanding :
Adversarial catches "obvious" opposing momentum that's easy to miss
Example: Bullish divergence at a local low, BUT price is deeply below EMA50, bearish momentum is strong, and RSI shows knife-catching conditions
Bull Case might be 0.20 while Bear Case is 0.55
Differential = -0.35, far beyond threshold
Block is CORRECT — you'd be fighting overwhelming opposing flow
If You Disagree Consistently
Review blocked signals on chart — scroll back and check outcomes
Did those blocked signals actually work, or did they fail as adversarial predicted?
Raise adv_threshold to 0.15-0.20 (more permissive, allows closer battles)
Disable Adversarial Validation temporarily (diagnostic) to isolate its effect
Use Advisory mode to learn adversarial patterns over 50-100 signals
Remember : Adversarial is conservative BY DESIGN. It prevents "obvious" bad trades where you're fighting strong strength the other way.
Problem: Dashboard Not Showing or Incomplete
Solutions :
Toggle "Show Dashboard" to ON in settings
Try different dashboard sizes (Small/Normal/Large)
Try different positions (Top Left/Right, Bottom Left/Right) — might be off-screen
Some sections require CAE Enable = ON (Cognitive Engine section won't appear if CAE is disabled)
Statistics section requires at least 1 lifetime signal to populate
Check that visual theme is set (dashboard colors adapt to theme)
Problem: Performance Lag, Chart Freezing
Symptoms : Chart loading is slow, indicator calculations cause delays, pinch-to-zoom lags.
Diagnosis : Visual features are computationally expensive, especially adversarial bar coloring (recalculates every bar).
Solutions (In Order of Impact) :
Disable Adversarial Bar Coloring (MOST EXPENSIVE):
Turn OFF "Adversarial Bar Coloring" in settings
This is the single biggest performance drain
Immediate improvement
Reduce Vertical Lines :
Lower "Keep last N vertical lines" to 20-30
Or set to 0 to disable entirely
Moderate improvement
Disable Bifurcation Zones :
Turn OFF "Draw Bifurcation Zones"
Reduces box drawing calculations
Moderate improvement
Set Dashboard Size to Small :
Smaller dashboard = fewer cells = less rendering
Minor improvement
Use Shorter Max Lookback :
Reduce max_lookback to 40-50 (from 60+)
Fewer bars to scan for divergences
Minor improvement
Disable Exhaustion Shading :
Turn OFF "Show Market State"
Removes background coloring calculations
Minor improvement
Extreme Performance Mode :
Disable ALL visual enhancements
Keep only triangle markers
Dashboard Small or OFF
Use Minimal theme if available
Problem: Realtime Signals Repainting
Symptoms : You see a signal appear, but on next bar it disappears or moves.
Explanation :
Realtime mode detects peaks 1 bar ago: high > high AND high > high
On the FORMING bar (before close), this condition can change as new prices arrive
Example: At 10:05, high (10:04 bar) was 100, current high is 99 → peak detected
At 10:05:30, new high of 101 arrives → peak condition breaks → signal disappears
At 10:06 (bar close), final high is 101 → no peak at 10:04 anymore → signal gone permanently
This is expected behavior for realtime responsiveness. You get preview/early warning, but it's not locked until bar confirms.
Solutions :
Use Confirmed Timing :
Switch to "Confirmed (lookforward)" mode
ZERO repainting — pivot must be fully validated
5-bar delay (pivot_lookforward)
What you see in history is exactly what would have appeared live
Accept Realtime Repaint as Tradeoff :
Keep Realtime mode for speed and alerts
Understand that pre-confirmation signals may vanish
Only trade signals that CONFIRM at bar close (check barstate.isconfirmed)
Use for live monitoring, NOT for backtesting
Trade Only After Confirmation :
In Realtime mode, wait 1 full bar after signal appears before entering
If signal survives that bar close, it's locked
This adds 1-bar delay but removes repaint risk
Recommendation : Use Confirmed for backtesting and conservative trading. Use Realtime only for active monitoring with full understanding of preview behavior.
Risk Management Integration
BZ-CAE is a signal generation system, not a complete trading strategy. You must integrate proper risk management:
Position Sizing by Confidence
Confidence 0.70-1.00 (Premium) :
Risk: 1.5-2.0% of account (MAXIMUM)
Reasoning: High-quality setup across all factors
Still cap at 2% — even premium setups can fail
Confidence 0.50-0.70 (High Quality) :
Risk: 1.0-1.5% of account
Reasoning: Standard good setup
Your bread-and-butter risk level
Confidence 0.35-0.50 (Moderate Quality) :
Risk: 0.5-1.0% of account
Reasoning: Marginal setup, passes minimum threshold
Reduce size or skip if you're selective
Confidence <0.35 (Low Quality) :
Risk: 0% (blocked in Filtering mode)
Reasoning: Insufficient quality factors
System protects you by not showing these
Stop Placement Strategies
For Reversal Signals (Regular Divergences) :
Place stop beyond the divergence pivot plus buffer
Bullish : Stop below the divergence low - 1.0-1.5 × ATR
Bearish : Stop above the divergence high + 1.0-1.5 × ATR
Reasoning: If price breaks the pivot, divergence structure is invalidated
For Continuation Signals (Hidden Divergences) :
Place stop beyond recent swing in opposite direction
Bullish continuation : Stop below recent swing low (not the divergence pivot itself)
Bearish continuation : Stop above recent swing high
Reasoning: You're trading with trend, allow more breathing room
ATR-Based Stops :
1.5-2.0 × ATR is standard
Scale by timeframe:
Scalping (1-5m): 1.0-1.5 × ATR (tight)
Day trading (15m-1H): 1.5-2.0 × ATR (balanced)
Swing (4H-D): 2.0-3.0 × ATR (wide)
Never Use Fixed Dollar/Pip Stops :
Markets have different volatility
50-pip stop on EUR/USD ≠ 50-pip stop on GBP/JPY
Always normalize by ATR or pivot structure
Profit Targets and Scaling
Primary Target :
2-3 × ATR from entry (minimum 2:1 reward-risk)
Example : Entry at 100, ATR = 2, stop at 97 (1.5 × ATR) → target at 106 (3 × ATR) = 2:1 R:R
Scaling Out Strategy :
Take 50% off at 1.5 × ATR (secure partial profit)
Move stop to breakeven
Trail remaining 50% with 1.0 × ATR trailing stop
Let winners run if trend persists
Targets by Confidence :
High Confidence (>0.70) : Aggressive targets (3-4 × ATR), trail wider (1.5 × ATR)
Standard Confidence (0.50-0.70) : Normal targets (2-3 × ATR), standard trail (1.0 × ATR)
Low Confidence (0.35-0.50) : Conservative targets (1.5-2 × ATR), tight trail (0.75 × ATR)
Use Bifurcation Zones :
If opposite-side zone is visible on chart (from previous signal), use it as target
Example : Bullish signal at 100, prior supply zone at 110 → use 110 as target
Zones mark institutional resistance/support
Exhaustion-Based Exits :
If you're in a trade and exhaustion >0.75 develops (yellow shading), consider early exit
Market is overextended — reversal risk is high
Take profit even if target not reached
Trade Management by TCS
High TCS + Counter-Trend Trade (Risky) :
Use very tight stops (1.0-1.5 × ATR)
Conservative targets (1.5-2 × ATR)
Quick exit if trade doesn't work immediately
You're fading momentum — respect it
Low TCS + Reversal Trade (Safer) :
Use wider stops (2.0-2.5 × ATR)
Aggressive targets (3-4 × ATR)
Trail with patience
Genuine reversal potential in weak trend
High TCS + Continuation Trade (Safest) :
Standard stops (1.5-2.0 × ATR)
Very aggressive targets (4-5 × ATR)
Trail wide (1.5-2.0 × ATR)
You're with institutional momentum — let it run
Educational Value — Learning Machine Intelligence
BZ-CAE is designed as a learning platform, not just a tool:
Advisory Mode as Teacher
Most indicators are binary: signal or no signal. You don't learn WHY certain setups are better.
BZ-CAE's Advisory mode shows you EVERY potential divergence, then annotates the ones that would be blocked in Filtering mode with specific reasons:
"Bull: strong downtrend (TCS=0.87)" teaches you that TCS >0.85 makes counter-trend very risky
"Adversarial bearish" teaches you that the opposing case was dominating
"Low confidence 32%" teaches you that the setup lacked quality across multiple factors
"Bull spacing: wait 8 bars" teaches you that signals need breathing room
After 50-100 signals in Advisory mode, you internalize the CAE's decision logic. You start seeing these factors yourself BEFORE the indicator does.
Dashboard Transparency
Most "intelligent" indicators are black boxes — you don't know how they make decisions.
BZ-CAE shows you ALL metrics in real-time:
TCS tells you trend strength
DMA tells you momentum alignment
Exhaustion tells you overextension
Adversarial shows both sides of the debate
Confidence shows composite quality
You learn to interpret market state holistically, a skill applicable to ANY trading system beyond this indicator.
Divergence Quality Education
Not all divergences are equal. BZ-CAE teaches you which conditions produce high-probability setups:
Quality divergence : Regular bullish div at a low, TCS <0.50 (weak trend), exhaustion >0.75 (overextended), positive adversarial differential, confidence >0.70
Low-quality divergence : Regular bearish div at a high, TCS >0.85 (strong uptrend), exhaustion <0.30 (not overextended), negative adversarial differential, confidence <0.40
After using the system, you can evaluate divergences manually with similar intelligence.
Risk Management Discipline
Confidence-based position sizing teaches you to adjust risk based on setup quality, not emotions:
Beginners often size all trades identically
Or worse, size UP on marginal setups to "make up" for losses
BZ-CAE forces systematic sizing: premium setups get larger size, marginal setups get smaller size
This creates a probabilistic approach where your edge compounds over time.
What This Indicator Is NOT
Complete transparency about limitations and positioning:
Not a Prediction System
BZ-CAE does not predict future prices. It identifies structural divergences (price-momentum disagreements) and assesses current market state (trend, exhaustion, adversarial conditions). It tells you WHEN conditions favor a potential reversal or continuation, not WHAT WILL HAPPEN.
Markets are probabilistic. Even premium-confidence setups fail ~30-40% of the time. The system improves your probability distribution over many trades — it doesn't eliminate risk.
Not Fully Automated
This is a decision support tool, not a trading robot. You must:
Execute trades manually based on signals
Manage positions (stops, targets, trailing)
Apply discretionary judgment (news events, liquidity, context)
Integrate with your broader strategy and risk rules
The confidence scores guide position sizing, but YOU determine final risk allocation based on your account size, risk tolerance, and portfolio context.
Not Beginner-Friendly
BZ-CAE requires understanding of:
Divergence trading concepts (regular vs hidden, reversal vs continuation)
Market state interpretation (trend vs range, momentum, exhaustion)
Basic technical analysis (pivots, support/resistance, EMAs)
Risk management fundamentals (position sizing, stops, R:R)
This is designed for intermediate to advanced traders willing to invest time learning the system. If you want "buy the arrow" simplicity, this isn't the tool.
Not a Holy Grail
There is no perfect indicator. BZ-CAE filters noise and improves signal quality significantly, but:
Losing trades are inevitable (even at 70% win rate, 30% still fail)
Market conditions change rapidly (yesterday's strong trend becomes today's chop)
Black swan events occur (fundamentals override technicals)
Execution matters (slippage, fees, emotional discipline)
The system provides an EDGE, not a guarantee. Your job is to execute that edge consistently with proper risk management over hundreds of trades.
Not Financial Advice
BZ-CAE is an educational and analytical tool. All trading decisions are your responsibility. Past performance (backtested or live) does not guarantee future results. Only risk capital you can afford to lose. Consult a licensed financial advisor for investment advice specific to your situation.
Ideal Market Conditions
Best Performance Characteristics
Liquid Instruments :
Major forex pairs (EUR/USD, GBP/USD, USD/JPY)
Large-cap stocks and index ETFs (SPY, QQQ, AAPL, MSFT)
High-volume crypto (BTC, ETH)
Major commodities (Gold, Oil, Natural Gas)
Reasoning: Clean price structure, clear pivots, meaningful oscillator behavior
Trending with Consolidations :
Markets that trend for 20-40 bars, then consolidate 10-20 bars, repeat
Creates divergences at consolidation boundaries (reversals) and within trends (continuations)
Both regular and hidden divs find opportunities
5-Minute to Daily Timeframes :
Below 5m: too much noise, false pivots, CAE metrics unstable
Above daily: too few signals, edge diminishes (fundamentals dominate)
Sweet spot: 15m to 4H for most traders
Consistent Volume and Participation :
Regular trading sessions (not holidays or thin markets)
Predictable volatility patterns
Avoid instruments with sudden gaps or circuit breakers
Challenging Conditions
Extremely Low Liquidity :
Penny stocks, exotic forex pairs, low-volume crypto
Erratic pivots, unreliable oscillator readings
CAE metrics can't assess market state properly
Very Low Timeframes (1-Minute or Below) :
Dominated by market microstructure noise
Divergences are everywhere but meaningless
CAE filtering helps but still unreliable
Extended Sideways Consolidation :
100+ bars of tight range with no clear pivots
Oscillator hugs midpoint (45-55 range)
No divergences to detect
Fundamentally-Driven Gap Markets :
Earnings releases, economic data, geopolitical events
Price gaps over stops and targets
Technical structure breaks down
Recommendation: Disable trading around known events
Calculation Methodology — Technical Depth
For users who want to understand the math:
Oscillator Computation
Each oscillator type calculates differently, but all normalize to 0-100:
RSI : ta.rsi(close, length) — Standard Relative Strength Index
Stochastic : ta.stoch(high, low, close, length) — %K calculation
CCI : (ta.cci(hlc3, length) + 100) / 2 — Normalized from -100/+100 to 0-100
MFI : ta.mfi(hlc3, length) — Volume-weighted RSI equivalent
Williams %R : ta.wpr(length) + 100 — Inverted stochastic adjusted to 0-100
Smoothing: If smoothing > 1, apply ta.sma(oscillator, smoothing)
Divergence Detection Algorithm
Identify Pivots :
Price high pivot: ta.pivothigh(high, lookback, lookforward)
Price low pivot: ta.pivotlow(low, lookback, lookforward)
Oscillator high pivot: ta.pivothigh(osc, lookback, lookforward)
Oscillator low pivot: ta.pivotlow(osc, lookback, lookforward)
Store Recent Pivots :
Maintain arrays of last 10 pivots with bar indices
When new pivot confirmed, unshift to array, pop oldest if >10
Scan for Slope Disagreements :
Loop through last 5 pivots
For each pair (current pivot, historical pivot):
Check if within max_lookback bars
Calculate slopes: (current - historical) / bars_between
Regular bearish: price_slope > 0, osc_slope < 0, |osc_slope| > min_threshold
Regular bullish: price_slope < 0, osc_slope > 0, |osc_slope| > min_threshold
Hidden bearish: price_slope < 0, osc_slope > 0, osc_slope > min_threshold
Hidden bullish: price_slope > 0, osc_slope < 0, |osc_slope| > min_threshold
Important Disclaimers and Terms
Performance Disclosure
Past performance, whether backtested or live-traded, does not guarantee future results. Markets change. What works today may not work tomorrow. Hypothetical or simulated performance results have inherent limitations and do not represent actual trading.
Risk of Loss
Trading involves substantial risk of loss. Only trade with risk capital you can afford to lose entirely. The high degree of leverage often available in trading can work against you as well as for you. Leveraged trading may result in losses exceeding your initial deposit.
Not Financial Advice
BZ-CAE is an educational and analytical tool for technical analysis. It is not financial advice, investment advice, or a recommendation to buy or sell any security or instrument. All trading decisions are your sole responsibility. Consult a licensed financial advisor for advice specific to your circumstances.
Technical Indicator Limitations
BZ-CAE is a technical analysis tool based on price and volume data. It does not account for:
Fundamental analysis (earnings, economic data, financial health)
Market sentiment and positioning
Geopolitical events and news
Liquidity conditions and market microstructure changes
Regulatory changes or exchange rules
Integrate with broader analysis and strategy. Do not rely solely on technical indicators for trading decisions.
Repainting Acknowledgment
As disclosed throughout this documentation:
Realtime mode may repaint on forming bars before confirmation (by design for preview functionality)
Confirmed mode has zero repainting (fully validated pivots only)
Choose timing mode appropriate for your use case. Understand the tradeoffs.
Testing Recommendation
ALWAYS test on demo/paper accounts before committing real capital. Validate the indicator's behavior on your specific instruments and timeframes. Learn the system thoroughly in Advisory mode before using Filtering mode.
Learning Resources :
In-indicator tooltips (hover over setting names for detailed explanations)
This comprehensive publishing statement (save for reference)
User guide in script comments (top of code)
Final Word — Philosophy of BZ-CAE
BZ-CAE is not designed to replace your judgment — it's designed to enhance it.
The indicator identifies structural inflection points (bifurcations) where price and momentum disagree. The Cognitive Engine evaluates market state to determine if this disagreement is meaningful or noise. The Adversarial model debates both sides of the trade to catch obvious bad setups. The Confidence system ranks quality so you can choose your risk appetite.
But YOU still execute. YOU still manage risk. YOU still learn from outcomes.
This is intelligence amplification, not intelligence replacement.
Use Advisory mode to learn how expert traders evaluate market state. Use Filtering mode to enforce discipline when emotions run high. Use the dashboard to develop a systematic approach to reading markets. Use confidence scores to size positions probabilistically.
The system provides an edge. Your job is to execute that edge with discipline, patience, and proper risk management over hundreds of trades.
Markets are probabilistic. No system wins every trade. But a systematic edge + disciplined execution + proper risk management compounds over time. That's the path to consistent profitability. BZ-CAE gives you the edge. The discipline and risk management are on you.
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
WR 3TF (5m+15m+1h)Who Should Use This:
✅ Perfect For:
Day traders who can monitor charts
Swing traders (hold 1-3 days)
People who want clear signals
Traders who struggle with emotions
Anyone wanting 60%+ win rate
❌ NOT For:
Complete beginners (learn basics first)
Long-term investors (too active)
People who can't watch charts daily
Those trading without stop losses
Trading Rules (IMPORTANT!):
Risk Management:
1. Risk only 1-2% per trade
2. ALWAYS use stop loss (2% below entry)
3. Take profit at 4-6% or opposite signal
4. Never trade more than you can afford to lose
5. Don't overtrade - follow signals only
Best Practices:
✅ Trade during high liquidity hours
✅ Wait for full signal confirmation
✅ Don't enter during major news events
✅ Keep a trading journal
✅ Review your trades weekly
Pro Tips:
Set Alerts: So you don't miss signals
Trade Multiple Assets: Don't put all in one coin
Compound Profits: Reinvest winnings
Stay Patient: Wait for signals, don't force trades
Keep Learning: Market conditions change
⚠️ Important Warnings:
❌ This is NOT:
A get-rich-quick scheme
100% guaranteed profits
A replacement for learning
Risk-free trading
✅ This IS:
A tested strategy (65% win rate)
A tool to improve your odds
A systematic approach
Still requires discipline
Chronos Reversal Labs - SPChronos Reversal Labs - Shadow Portfolio
Chronos Reversal Labs - Shadow Portfolio: combines reinforcement learning optimization with adaptive confluence detection through a shadow portfolio system. Unlike traditional indicator mashups that force traders to manually interpret conflicting signals, this system deploys 4 multi-armed bandit algorithms to automatically discover which of 5 specialized confluence strategies performs best in current market conditions, then validates those discoveries through parallel shadow portfolios that track virtual P&L for each strategy independently.
Core Innovation: Rather than relying on static indicator combinations, this system implements Thompson Sampling (Bayesian multi-armed bandits), contextual bandits (regime-specific learning), advanced chop zone detection (geometric pattern analysis), and historical pre-training to build a self-improving confluence detection engine. The shadow portfolio system runs 5 parallel virtual trading accounts—one per strategy—allowing the system to learn which confluence approach works best through actual position tracking with realistic exits.
Target Users: Intermediate to advanced traders seeking systematic reversal signals with mathematical rigor. Suitable for swing trading and day trading across stocks, forex, crypto, and futures on liquid instruments. Requires understanding of basic technical analysis and willingness to allow 50-100 bars for initial learning.
Why These Components Are Combined
The Fundamental Problem
No single confluence method works consistently across all market regimes. Kernel-based methods (entropy, DFA) excel during predictable phases but fail in chaos. Structure-based methods (harmonics, BOS) work during clear swings but fail in ranging conditions. Technical methods (RSI, MACD, divergence) provide reliable signals in trends but generate false signals during consolidation.
Traditional solutions force traders to either manually switch between methods (slow, error-prone) or interpret all signals simultaneously (cognitive overload). Both fail because they assume the trader knows which regime the market is in and which method works best.
The Solution: Meta-Learning Through Reinforcement Learning
This system solves the problem through automated strategy selection : Deploy 5 specialized confluence strategies designed for different market conditions, track their real-world performance through shadow portfolios, then use multi-armed bandit algorithms to automatically select the optimal strategy for the next trade.
Why Shadow Portfolios? Traditional bandit implementations use abstract "rewards." Shadow portfolios provide realistic performance measurement : Each strategy gets a virtual trading account with actual position tracking, stop-loss management, take-profit targets, and maximum holding periods. This creates risk-adjusted learning where strategies are evaluated on P&L, win rate, and drawdown—not arbitrary scores.
The Five Confluence Strategies
The system deploys 5 orthogonal strategies with different weighting schemes optimized for specific market conditions:
Strategy 1: Kernel-Dominant (Entropy/DFA focused, optimal in predictable markets)
Shannon Entropy weight × 2.5, DFA weight × 2.5
Detects low-entropy predictable patterns and DFA persistence/mean-reversion signals
Failure mode: High-entropy chaos (hedged by Technical-Dominant)
Strategy 2: Structure-Dominant (Harmonic/BOS focused, optimal in clear swing structures)
Harmonics weight × 2.5, Liquidity (S/R) weight × 2.0
Uses swing detection, break-of-structure, and support/resistance clustering
Failure mode: Range-bound markets (hedged by Balanced)
Strategy 3: Technical-Dominant (RSI/MACD/Divergence focused, optimal in established trends)
RSI weight × 2.0, MACD weight × 2.0, Trend weight × 2.0
Zero-lag RSI suite with 4 calculation methods, MACD analysis, divergence detection
Failure mode: Choppy/ranging markets (hedged by chop filter)
Strategy 4: Balanced (Equal weighting, optimal in unknown/transitional regimes)
All components weighted 1.2×
Baseline performance during regime uncertainty
Strategy 5: Regime-Adaptive (Dynamic weighting by detected market state)
Chop zones: Kernel × 2.0, Technical × 0.3
Bull/Bear trends: Trend × 1.5, DFA × 2.0
Ranging: Mean reversion × 1.5
Adapts explicitly to detected regime
Multi-Armed Bandit System: 4 Core Algorithms
What Is a Multi-Armed Bandit Problem?
Formal Definition: K arms (strategies), each with unknown reward distribution. Goal: Maximize cumulative reward while learning which arms are best. Challenge: Balance exploration (trying uncertain strategies) vs. exploitation (using known-best strategy).
Trading Application: Each confluence strategy is an "arm." After each trade, receive reward (P&L percentage). Bandits decide which strategy to trust for next signal.
The 4 Implemented Algorithms
1. Thompson Sampling (DEFAULT)
Category: Bayesian approach with probability distributions
How It Works: Model each strategy as Beta(α, β) where α = wins, β = losses. Sample from distributions, select highest sample.
Properties: Optimal regret O(K log T), automatic exploration-exploitation balance
When To Use: Best all-around choice, adaptive markets, long-term optimization
2. UCB1 (Upper Confidence Bound)
Category: Frequentist approach with confidence intervals
Formula: UCB_i = reward_mean_i + sqrt(2 × ln(total_pulls) / pulls_i)
Properties: Deterministic, interpretable, same optimal regret as Thompson
When To Use: Prefer deterministic behavior, stable markets
3. Epsilon-Greedy
Category: Simple baseline with random exploration
How It Works: With probability ε (0.15): random strategy. Else: best average reward.
Properties: Simple, fast initial learning
When To Use: Baseline comparison, short-term testing
4. Contextual Bandit
Category: Context-aware Thompson Sampling
Enhancement: Maintains separate alpha/beta for Bull/Bear/Ranging regimes
Learning: "Strategy 2: 60% win rate in Bull, 40% in Bear"
When To Use: After 100+ bars, clear regime shifts
Shadow Portfolio System
Why Shadow Portfolios?
Traditional bandits use abstract scores. Shadow portfolios provide realistic performance measurement through actual position simulation.
How It Works
Position Opening:
When strategy generates validated signal:
Opens virtual position for selected strategy
Records: entry price, direction, entry bar, RSI method
Optional: Open positions for ALL strategies simultaneously (faster learning)
Position Management (Every Bar):
Current P&L: pnl_pct = (close - entry) / entry × direction × 100
Exit if: pnl_pct <= -2.0% (stop-loss) OR pnl_pct >= +4.0% (take-profit) OR held ≥ 100 bars (time)
Position Closing:
Calculate final P&L percentage
Update strategy equity, track win rate, gross profit/loss, max drawdown
Calculate risk-adjusted reward:
text
base_reward = pnl_pct / 10.0
win_rate_bonus = (win_rate - 0.5) × 0.3
drawdown_penalty = -max_drawdown × 0.05
total_reward = sigmoid(base + bonus + penalty)
Update bandit algorithms with reward
Update RSI method bandit
Statistics Tracked Per Strategy:
Equity curve (starts at $10,000)
Win rate percentage
Max drawdown
Gross profit/loss
Current open position
This creates closed-loop learning : Strategies compete → Best performers selected → Bandits learn quality → System adapts automatically.
Historical Pre-Training System
The Problem with Live-Only Learning
Standard bandits start with zero knowledge and need 50-100 signals to stabilize. For weekly timeframe traders, this could take years.
The Solution: Historical Training
During Chart Load: System processes last 300-1000 bars (configurable) in "training mode":
Detect signals using Balanced strategy (consistent baseline)
For each signal, open virtual training positions for all 5 strategies
Track positions through historical bars using same exit logic (SL/TP/time)
Update bandit algorithms with historical outcomes
CRITICAL TRANSPARENCY: Signal detection does NOT look ahead—signals use only data available at entry bar. Exit tracking DOES look ahead (uses future bars for SL/TP), which is acceptable because:
✅ Entry decisions remain valid (no forward bias)
✅ Learning phase only (not affecting shown signals)
✅ Real-time mirrors training (identical exit logic)
Training Completion: Once chart reaches current bar, system transitions to live mode. Dashboard displays training vs. live statistics for comparison.
Benefit: System begins live trading with 100-500 historical trades worth of learning, enabling immediate intelligent strategy selection.
Advanced Chop Zone Detection Engine
The Innovation: Multi-Layer Geometric Chop Analysis
Traditional chop filters use simple volatility metrics (ATR thresholds) that can't distinguish between trending volatility (good for signals) and choppy volatility (bad for signals). This system implements three-layer geometric pattern analysis to precisely identify consolidation zones where reversal signals fail.
Layer 1: Micro-Structure Chop Detection
Method: Analyzes micro pivot points (5-bar left, 2-bar right) to detect geometric compression patterns.
Slope Analysis:
Calculates slope of pivot high trendline and pivot low trendline
Compression ratio: compression = slope_high - slope_low
Pattern Classification:
Converging slopes (compression < -0.05) → "Rising Wedge" or "Falling Wedge"
Flat slopes (|slope| < 0.05) → "Rectangle"
Parallel slopes (|compression| < 0.1) → "Channel"
Expanding slopes → "Expanding Range"
Chop Scoring:
Rectangle pattern: +15 points (highest chop)
Low average slope (<0.05): +15 points
Wedge patterns: +12 points
Flat structures: +10 points
Why This Works: Geometric patterns reveal market indecision. Rectangles and wedges create false breakouts that trap technical traders. By quantifying geometric compression, system detects these zones before signals fire.
Layer 2: Macro-Structure Chop Detection
Method: Tracks major swing highs/lows using ATR-based deviation threshold (default 2.0× ATR), projects channel boundaries forward.
Channel Position Calculation:
proj_high = last_swing_high + (swing_high_slope × bars_since)
proj_low = last_swing_low + (swing_low_slope × bars_since)
channel_width = proj_high - proj_low
position = (close - proj_low) / channel_width
Dead Zone Detection:
Middle 50% of channel (position 0.25-0.75) = low-conviction zone
Score increases as price approaches center (0.5)
Chop Scoring:
Price in dead zone: +15 points (scaled by centrality)
Narrow channel width (<3× ATR): +15 points
Channel width 3-5× ATR: +10 points
Why This Works: Price in middle of range has equal probability of moving either direction. Institutional traders avoid mid-range entries. By detecting "dead zones," system avoids low-probability setups.
Layer 3: Volume Chop Scoring
Method: Low volume indicates weak conviction—precursor to ranging behavior.
Scoring:
Volume < 0.5× average: +20 points
Volume 0.5-0.8× average: +15 points
Volume 0.8-1.0× average: +10 points
Overall Chop Intensity & Signal Filtering
Total Chop Calculation:
chop_intensity = micro_score + macro_score + (volume_score × volume_weight)
is_chop = chop_intensity >= 40
Signal Filtering (Three-Tier Approach):
1. Signal Blocking (Intensity > 70):
Extreme chop detected (e.g., tight rectangle + dead zone + low volume)
ALL signals blocked regardless of confluence
Chart displays red/orange background shading
2. Threshold Adjustment (Intensity 40-70):
Moderate chop detected
Confluence threshold increased: threshold += (chop_intensity / 50)
Only highest-quality signals pass
3. Strategy Weight Adjustment:
During Chop: Kernel-Dominant weight × 2.0 (entropy detects breakout precursors), Technical-Dominant weight × 0.3 (reduces false signals)
After Chop Exit: Weights revert to normal
Why This Three-Tier Approach Is Original: Most chop filters simply block all signals (loses breakout entries). This system adapts strategy selection during chop—allowing Kernel-Dominant (which excels at detecting low-entropy breakout precursors) to operate while suppressing Technical-Dominant (which generates false signals in consolidation). Result: System remains functional across full market regime spectrum.
Zero-Lag Filter Suite with Dynamic Volatility Scaling
Zero-Lag ADX (Trend Regime Detection)
Implementation: Applies ZLEMA to ADX components:
lag = (length - 1) / 2
zl_source = source + (source - source ) × strength
Dynamic Volatility Scaling (DVS):
Calculates volatility ratio: current_ATR / ATR_100period_avg
Adjusts ADX length dynamically: High vol → shorter length (faster), Low vol → longer length (smoother)
Regime Classification:
ADX > 25 with +DI > -DI = Bull Trend
ADX > 25 with -DI > +DI = Bear Trend
ADX < 25 = Ranging
Zero-Lag RSI Suite (4 Methods with Bandit Selection)
Method 1: Standard RSI - Traditional Wilder's RSI
Method 2: Ehlers Zero-Lag RSI
ema1 = ema(close, length)
ema2 = ema(ema1, length)
zl_close = close + (ema1 - ema2)
Method 3: ZLEMA RSI
lag = (length - 1) / 2
zl_close = close + (close - close )
Method 4: Kalman-Filtered RSI - Adaptive smoothing with process/measurement noise
RSI Method Bandit: Separate 4-arm bandit learns which calculation method produces best results. Updates independently after each trade.
Kalman Adaptive Filters
Fast Kalman: Low process noise → Responsive to genuine moves
Slow Kalman: Higher measurement noise → Filters noise
Application: Crossover logic for trend detection, acceleration analysis for momentum inflection
What Makes This Original
Innovation 1: Shadow Portfolio Validation
First TradingView script to implement parallel virtual portfolios for multi-armed bandit reward calculation. Instead of abstract scoring metrics, each strategy's performance is measured through realistic position tracking with stop-loss, take-profit, time-based exits, and risk-adjusted reward functions (P&L + win rate + drawdown). This provides orders-of-magnitude better reward signal quality for bandit learning than traditional score-based approaches.
Innovation 2: Three-Layer Geometric Chop Detection
Novel multi-scale geometric pattern analysis combining: (1) Micro-structure slope analysis with pattern classification (wedges, rectangles, channels), (2) Macro-structure channel projection with dead zone detection, (3) Volume confirmation. Unlike simple volatility filters, this system adapts strategy weights during chop —boosting Kernel-Dominant (breakout detection) while suppressing Technical-Dominant (false signal reduction)—allowing operation across full market regime spectrum without blind signal blocking.
Innovation 3: Historical Pre-Training System
Implements two-phase learning : Training phase (processes 300-1000 historical bars on chart load with proper state isolation) followed by live phase (real-time learning). Training positions tracked separately from live positions. System begins live trading with 100-500 trades worth of learned experience. Dashboard displays training vs. live performance for transparency.
Innovation 4: Contextual Multi-Armed Bandits with Regime-Specific Learning
Beyond standard bandits (global strategy quality), implements regime-specific alpha/beta parameters for Bull/Bear/Ranging contexts. System learns: "Strategy 2: 60% win rate in ranging markets, 45% in bull trends." Uses current regime's learned parameters for strategy selection, enabling regime-aware optimization.
Innovation 5: RSI Method Meta-Learning
Deploys 4 different RSI calculation methods (Standard, Ehlers ZL, ZLEMA, Kalman) with separate 4-arm bandit that learns which calculation works best. Updates RSI method bandit independently based on trade outcomes, allowing automatic adaptation to instrument characteristics.
Innovation 6: Dynamic Volatility Scaling (DVS)
Adjusts ALL lookback periods based on current ATR ratio vs. 100-period average. High volatility → shorter lengths (faster response). Low volatility → longer lengths (smoother signals). Applied system-wide to entropy, DFA, RSI, ADX, and Kalman filters for adaptive responsiveness.
How to Use: Practical Guide
Initial Setup (5 Minutes)
Theory Mode: Start with "BALANCED" (APEX for aggressive, CONSERVATIVE for defensive)
Enable RL: Toggle "Enable RL Auto-Optimization" to TRUE, select "Thompson Sampling"
Enable Confluence Modules: Divergence, Volume Analysis, Liquidity Mapping, RSI OB/OS, Trend Analysis, MACD (all recommended)
Enable Chop Filter: Toggle "Enable Chop Filter" to TRUE, sensitivity 1.0 (default)
Historical Training: Enable "Enable Historical Pre-Training", set 300-500 bars
Dashboard: Enable "Show Dashboard", position Top Right, size Large
Learning Phase (First 50-100 Bars)
Monitor Thompson Sampling Section:
Alpha/beta values should diverge from initial 1.0 after 20-30 trades
Expected win% should stabilize around 55-60% (excellent), >50% (acceptable)
"Pulls" column should show balanced exploration (not 100% one strategy)
Monitor Shadow Portfolios:
Equity curves should diverge (different strategies performing differently)
Win rate > 55% is strong
Max drawdown < 15% is healthy
Monitor Training vs Live (if enabled):
Delta difference < 10% indicates good generalization
Large negative delta suggests overfitting
Large positive delta suggests system adapting well
Optimization:
Too few signals: Lower "Base Confluence Threshold" to 2.5-3.0
Too many signals: Raise threshold to 4.0-4.5
One strategy dominates (>80%): Increase "Exploration Rate" to 0.20-0.25
Excessive chop blocking: Lower "Chop Sensitivity" to 0.7-0.8
Signal Interpretation
Dashboard Indicators:
"WAITING FOR SIGNAL": No confluence
"LONG ACTIVE ": Validated long entry
"SHORT ACTIVE ": Validated short entry
Chart Visuals:
Triangle markers: Entry signal (green = long, red = short)
Orange/red background: Chop zone
Lines: Support/resistance if enabled
Position Management
Entry: Enter on triangle marker, confirm direction matches dashboard, check confidence >60%
Stop-Loss: Entry ± 1.5× ATR or at structural swing point
Take-Profit:
TP1: Entry + 1.5R (take 50%, move SL to breakeven)
TP2: Entry + 3.0R (runner) or trail
Position Sizing:
Risk per trade = 1-2% of capital
Position size = (Account × Risk%) / (Entry - SL)
Recommended Settings by Instrument
Stocks (Large Cap): Balanced mode, Threshold 3.5, Thompson Sampling, Chop 1.0, 15min-1H, Training 300-500 bars
Forex Majors: Conservative-Balanced mode, Threshold 3.5-4.0, Thompson Sampling, Chop 0.8-1.0, 5min-30min, Training 400-600 bars
Cryptocurrency: Balanced-APEX mode, Threshold 3.0-3.5, Thompson Sampling, Chop 1.2-1.5, 15min-4H, Training 300-500 bars
Futures: Balanced mode, Threshold 3.5, UCB1 or Thompson, Chop 1.0, 5min-30min, Training 400-600 bars
Technical Approximations & Limitations
1. Thompson Sampling: Pseudo-Random Beta Distribution
Standard: Cryptographic RNG with true beta sampling
This Implementation: Box-Muller transform using market data as entropy source
Impact: Not cryptographically random but maintains exploration-exploitation balance. Sufficient for strategy selection.
2. Shadow Portfolio: Simplified Execution Model
Standard: Order book simulation with slippage, partial fills
This Implementation: Perfect fills at close price, no fees modeled
Impact: Real-world performance ~0.1-0.3% worse per trade due to execution costs.
3. Historical Training: Forward-Looking for Exits Only
Entry signals: Use only past data (causal, no bias)
Exit tracking: Uses future bars to determine SL/TP (forward-looking)
Impact: Acceptable because: (1) Entry logic remains valid, (2) Live trading mirrors training, (3) Improves learning quality. Training win rates reflect 8-bar evaluation window—live performance may differ if positions held longer.
4. Shannon Entropy & DFA: Simplified Calculations
Impact: 10-15% precision loss vs. academic implementations. Still captures predictability and persistence signals effectively.
General Limitations
No Predictive Guarantee: Past performance ≠ future results
Learning Period Required: Minimum 50-100 bars for stable statistics
Overfitting Risk: May not generalize to unprecedented conditions
Single-Instrument: No multi-asset correlation or sector context
Execution Assumptions: Degrades in illiquid markets (<100k volume), major news events, flash crashes
Risk Warnings & Disclaimers
No Guarantee of Profit: All trading involves substantial risk of loss. This indicator is a tool, not a guaranteed profit system.
System Failures: Software bugs possible despite testing. Use appropriate position sizing.
Market Regime Changes: Performance may degrade during extreme volatility (VIX >40), low liquidity periods, or fundamental regime shifts.
Broker-Specific Issues: Real-world execution includes slippage (0.1-0.5%), commissions, overnight financing costs, partial fills.
Forward-Looking Bias in Training: Historical training uses 8-bar forward window for exit evaluation. Dashboard "Training Win%" reflects this method. Real-time performance may differ.
Appropriate Use
This Indicator IS:
✅ Entry trigger system with confluence validation
✅ Risk management framework (automated SL/TP)
✅ Adaptive strategy selection engine
✅ Learning system that improves over time
This Indicator IS NOT:
❌ Complete trading strategy (requires position sizing, portfolio management)
❌ Replacement for due diligence
❌ Guaranteed profit generator
❌ Suitable for complete beginners
Recommended Complementary Analysis: Market context, volume profile, fundamental catalysts, higher timeframe alignment, support/resistance from other sources.
Conclusion
Chronos Reversal Labs V2.0 - Elite Edition synthesizes research from multi-armed bandit theory (Thompson Sampling, UCB, contextual bandits), market microstructure (geometric chop detection, zero-lag filters), and machine learning (shadow portfolio validation, historical pre-training, RSI method meta-learning).
Unlike typical indicator mashups, this system implements mathematically rigorous bandit algorithms with realistic performance validation, three-layer chop detection with adaptive strategy weighting, regime-specific learning, and full transparency on approximations and limitations.
The system is designed for intermediate to advanced traders who understand that no indicator is perfect, but through proper machine learning and realistic validation, we can build systems that improve over time and adapt to changing markets without manual intervention.
Use responsibly. Understand the limitations. Risk disclosure applies. Past performance does not guarantee future results.
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
NeuraEdge Pro v1- Auto-OptimizedNeuraEdge Pro is an advanced, self-optimizing trading system that combines Smart Money Concepts (SMC), ICT principles, and adaptive neural networks to identify high-probability trade setups. The indicator automatically learns from its signal history and optimizes parameters in real-time to maintain your target win rate.
Key Features:
✅ Auto-optimization based on historical performance
✅ Neural adaptive system that learns market conditions
✅ ICT session filtering (London, New York, Asian)
✅ Smart Money Concepts integration
✅ Multi-timeframe support (Scalping to Swing trading)
✅ Built-in risk management system
📊 How It Works
NeuraEdge Pro identifies institutional order blocks, fair value gaps, and liquidity zones using advanced price action analysis. The system then filters these setups through multiple confluence factors including:
Market structure alignment
Volume confirmation
Neural network prediction
Session timing (ICT concepts)
Momentum indicators
RSI divergences
The higher you set the confluence number to (max 5) the more accurate but less signal quantity preferred on higher time frame from 1 HR and above.
The unique auto-optimization engine tracks signal performance and automatically adjusts internal parameters to improve accuracy over time.
⚙️ Recommended Settings by Trading Style
🔥 Scalping (1m - 5m charts)
Trading Mode:
✅ Scalp Mode
❌ Intraday Mode
❌ Swing Mode
✅ ICT Concepts
✅ Neural Adaptive
Risk Management:
Risk % per Trade: 0.5-1.0%
Risk:Reward Ratio: 2:1
ATR-Based Stop Loss: ON
ATR Multiplier: 1.3
Min SL Points: 15-20
Advanced Settings:
Analysis Lookback: 40
Order Block Strength: 4-5
Base FVG Size: 0.8-1.0
Base Volume Threshold: 1.8
Base Confluence Score: 4
📈 Intraday (15m - 1h charts)
Trading Mode:
❌ Scalp Mode
✅ Intraday Mode
❌ Swing Mode
✅ ICT Concepts
✅ Neural Adaptive
Risk Management:
Risk % per Trade: 1.0-1.5%
Risk:Reward Ratio: 2.5:1
ATR-Based Stop Loss: ON
ATR Multiplier: 1.5
Min SL Points: 25-30
Advanced Settings:
Analysis Lookback: 50
Order Block Strength: 4
Base FVG Size: 0.9
Base Volume Threshold: 1.6
Base Confluence Score: 4
📊 Swing Trading (4h - Daily charts)
Trading Mode:
❌ Scalp Mode
❌ Intraday Mode
✅ Swing Mode
✅ ICT Concepts
✅ Neural Adaptive
Risk Management:
Risk % per Trade: 1.5-2.0%
Risk:Reward Ratio: 3:1
ATR-Based Stop Loss: ON
ATR Multiplier: 1.8
Min SL Points: 40-50
Advanced Settings:
Analysis Lookback: 75
Order Block Strength: 3-4
Base FVG Size: 1.0-1.2
Base Volume Threshold: 1.5
Base Confluence Score: 3-4
🤖 Auto-Optimization Settings
Recommended for all timeframes:
Enable Auto-Optimization: ON
Optimization Lookback: 100 trades
Target Win Rate: 60%
💡 The system needs at least 10-15 signals to begin optimization. Initial signals use base settings, then the system adapts automatically.
🔮 Predictive Analysis
Keep these balanced for optimal results:
Enable Predictive Mode: ON
Price Action Weight: 0.4
Volume Weight: 0.3
Momentum Weight: 0.3
These weights determine how much each factor influences setup scoring.
📱 Signal Interpretation
BUY Signals (Green Labels)
Price has reached a bullish order block or FVG
Multiple confluence factors aligned
Neural network confirms bullish bias
Entry price shown on label
Green dashed line = Take Profit target
Red dashed line = Stop Loss
SELL Signals (Red Labels)
Price has reached a bearish order block or FVG
Multiple confluence factors aligned
Neural network confirms bearish bias
Entry price shown on label
Green dashed line = Take Profit target
Red dashed line = Stop Loss
📊 Dashboard Explained
Top Section:
Mode - Active trading mode and timeframe
Trend - Current market structure (Bullish/Bearish/Range)
Vol - Volume ratio (higher = stronger moves)
ATR - Current volatility measurement
Auto-Optimize Section:
Win Rate - Historical performance (updates after signals)
FVG/Vol/Conf - Current optimized parameters with arrows:
↑ = System increased selectivity (fewer signals)
↓ = System decreased selectivity (more signals)
= = No change from base settings
Ready OBs - Number of high-probability setups currently available
⚠️ Important Trading Rules
Wait for signal labels - Don't trade order blocks/FVGs without confirmation
Respect the stop loss - Always displayed as red dashed line
Use proper position sizing - Based on your Risk % setting
Trade during recommended sessions - When ICT Concepts enabled
Let auto-optimization work - Give it 15-20 signals before judging
One signal at a time - System prevents new signals for 5 bars after entry
🎯 Best Practices
✅ DO:
Use on liquid, trending markets (Forex majors, indices, crypto majors)
Enable only ONE trading mode matching your timeframe
Keep ICT Concepts enabled for session filtering
Trust the auto-optimization after 15+ signals
Set alerts for BUY/SELL signals
❌ DON'T:
Enable multiple trading modes simultaneously
Override stop losses manually
Trade during low liquidity hours without ICT filtering
Expect perfection - manage risk appropriately
Judge performance before 20+ signals
🔔 Alert Setup
The indicator includes 4 alert types:
Buy Signal - Long entry opportunity
Sell Signal - Short entry opportunity
Sell-Side Sweep - Liquidity grabbed above
Buy-Side Sweep - Liquidity grabbed below
Set up alerts via TradingView's alert menu for real-time notifications.
📈 Performance Tracking
The dashboard shows real-time performance metrics:
Win Rate % - Percentage of profitable signals
Parameter adjustments - How the system is adapting
Neural Score - AI confidence (0-1 scale)
ICT Session Status - Whether optimal trading hours are active
💡 Pro Tips
Start conservative - Use recommended settings for your timeframe
Give it time - Auto-optimization needs 20-30 signals for best results
Higher timeframes = higher quality - Fewer but better signals
Volume matters - Strongest signals occur on volume spikes
Structure alignment - Best trades align with overall trend
⚙️ Technical Requirements
Minimum Timeframe: 1 minute
Maximum Timeframe: Monthly
Best Timeframes: 5m, 15m, 1h, 4h
Asset Classes: Forex, Crypto, Indices, Stocks
Account Type: Any (works with all TradingView plans)
📞 Support & Updates
This indicator is actively maintained and updated based on user feedback. Future updates will include additional features and optimizations.
Disclaimer: Trading involves substantial risk. This indicator is a tool to assist analysis, not a guarantee of profits. Always use proper risk management and never risk more than you can afford to lose. Past performance does not guarantee future results.
RED-E Market Structure (Pro V2)RED-E Market Structure - Comprehensive Technical Analysis System
⚠️ EDUCATIONAL TOOL - NO GUARANTEES
This indicator is designed for educational purposes to help traders learn technical analysis concepts. It does not predict future price movements or guarantee profitable trades. Trading involves substantial risk of loss.
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📊 WHAT THIS INDICATOR DOES
This indicator combines multiple standard technical analysis methods into a unified system for analyzing market structure, momentum, volume dynamics, and key price levels. Rather than adding 10 separate indicators to your chart, this consolidates related information into one cohesive interface where each component informs the others.
═══════════════════════════════════════════════════════════════
🔧 TECHNICAL METHODOLOGY - HOW IT WORKS
1️⃣ MOMENTUM CANDLE COLORING (6 Levels)
Calculation Method:
- Compares close vs EMA(9) and EMA(21)
- Applies RSI(14) thresholds for strength
- Color codes: Royal Blue (strongest bull) → Cyan → Green → Yellow → Orange → Red (strongest bear) → White (neutral)
Formula Logic:
IF close > EMA(9) AND close > EMA(21) AND close > open:
RSI > 70 = Level 3 Bull (Royal Blue)
RSI 60-70 = Level 2 Bull (Cyan)
RSI < 60 = Level 1 Bull (Green)
Purpose: Visualizes momentum strength by combining trend (EMAs), candle direction, and overbought/oversold conditions (RSI).
2️⃣ ENTRY SIGNAL LABELS
Calculation Method:
- Uses EMA alignment: EMA(9) > EMA(21) > EMA(50) for bullish
- Filters RSI to avoid extremes
- Requires confirming candle
BUY Signal Logic:
IF close > EMA(9) AND RSI between 40-70 AND EMA(9) > EMA(21) > EMA(50) AND close > open
THEN: Display "BUY" label
Purpose: Identifies potential entries when multiple trend and momentum conditions align. This is standard multi-confirmation technical analysis.
3️⃣ VOLUME DELTA PERCENTAGE
Calculation Method:
FOR each bar in lookback period (default 20):
IF close > open: add volume to bullish_volume
IF close < open: add volume to bearish_volume
bullish_percent = (bullish_volume / total_volume) × 100
Purpose: Quantifies buying vs selling pressure as percentages. Shows if volume supports the current trend.
Display: "🟢65.3% | 🔴34.7%" in dashboard
4️⃣ PRE-MARKET HIGH/LOW TRACKING
Calculation Method:
1. Detect pre-market session (4:00-9:30 AM ET)
2. Track highest high during pre-market
3. Track lowest low during pre-market
4. Draw horizontal lines when market opens
Purpose: Pre-market levels often act as support/resistance during regular hours. This automates their tracking and visualization.
5️⃣ OPENING RANGE BREAKOUT (ORB)
Calculation Method:
1. User sets start time (default 9:30 AM) and duration (default 15 min)
2. Track highest high and lowest low during this period
3. Draw box and extend lines
Purpose: The opening range breakout is a well-documented day trading strategy. First X minutes establish a range, and breakouts often signal directional moves.
6️⃣ SUPPORT/RESISTANCE TRENDLINES
Calculation Method:
1. Identify pivot highs: ta.pivothigh(high, 5, 5)
2. Identify pivot lows: ta.pivotlow(low, 5, 5)
3. Connect last two pivot highs = Resistance (red)
4. Connect last two pivot lows = Support (blue)
Purpose: Automatically connects significant pivot points. Based on standard pivot analysis where price respects these levels.
7️⃣ GAMMA ZONE DETECTION
Calculation Method:
1. Calculate 30-min range: (high - low)
2. Calculate 10-period SMA of range
3. Calculate ratio: current_range / average_range
IF ratio < (1.0 / sensitivity): HIGH GAMMA = Low volatility
IF ratio > (1.0 × sensitivity): LOW GAMMA = High volatility
Purpose: Approximates options gamma effects. High gamma = dealers hedge more = suppressed volatility. Low gamma = less hedging = potential explosive moves.
8️⃣ TAKE PROFIT LEVELS (5 Levels + ATR Stop Loss)
Calculation Method:
LONG: TP = entry_price × (1 + percentage/100)
SHORT: TP = entry_price × (1 - percentage/100)
Stop Loss (ATR): entry ± (ATR(14) × multiplier)
Purpose: Automatically calculates percentage-based targets and volatility-adjusted stops. ATR adapts stop to current market conditions.
9️⃣ THE STRAT PATTERN RECOGNITION
Calculation Method:
Compare current bar to previous:
- Strat 3 (outside bar): high > high AND low < low
- Strat 1 (inside bar): high ≤ high AND low ≥ low
- Strat 2 (directional): All others
Purpose: The Strat is a price action system categorizing bars by relationship to previous bars. This automates classification.
🔟 FIBONACCI RETRACEMENTS
Calculation Method:
1. Find highest high in lookback (default 30 bars)
2. Find lowest low in lookback
3. Calculate: 0.0, 0.382, 0.5, 0.618, 1.0 levels
Purpose: Standard Fibonacci tool. These ratios are commonly used support/resistance in technical analysis.
1️⃣1️⃣ MULTI-TIMEFRAME ANALYSIS
Calculation Method:
FOR each timeframe (default 15m, 1H, 4H):
Check if close > EMA(9) on that timeframe
IF true: "BULLISH", else: "BEARISH"
Purpose: Shows trend alignment across timeframes using Pine's request.security(). Common confirmation technique.
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💡 WHY THESE COMPONENTS WORK TOGETHER
This indicator's originality lies in its unified system approach:
1. TREND IDENTIFICATION (EMAs, MTF) - Shows direction
2. MOMENTUM MEASUREMENT (RSI, candles) - Shows strength
3. VOLUME CONFIRMATION (Volume Delta) - Shows conviction
4. KEY LEVELS (PM, ORB, Fib, S/R) - Shows decision points
5. RISK MANAGEMENT (TP levels, ATR stops) - Shows exits
VALUE OF INTEGRATION:
Rather than 10 separate indicators creating chart clutter, this consolidates related concepts where each component provides different information that, when viewed together, gives a more complete market picture.
Example Integration:
- Entry signal appears (EMA + RSI aligned)
- Volume Delta confirms (more buying than selling)
- MTF shows higher timeframes agree
- TP levels auto-calculate with good risk:reward
- Support trendline nearby provides stop reference
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⚙️ CUSTOMIZATION OPTIONS
All features independently toggleable:
- EMAs: Adjust lengths (9, 21, 50, 200), colors, widths
- RSI: Change overbought/oversold levels (70/30)
- Volume Delta: Adjust lookback period (20)
- ORB: Set custom start time, duration, timezone
- Gamma: Adjust sensitivity (1-10)
- TP Levels: Customize all 5 percentages
- Dashboard: Reposition, resize, recolor
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📖 HOW TO USE
Step 1 - Assess Context:
- Check MTF Dashboard for alignment
- Check EMA indicator for trend
- Check Gamma Zone for volatility expectation
Step 2 - Identify Setups:
- Wait for BUY/SELL signal
- Check Volume Delta matches direction
- Verify RSI not extreme (30-70)
- Look for support/resistance confluence
Step 3 - Evaluate Risk:Reward:
- Review TP3 R:R ratio (target 2:1+)
- Check stop loss placement
- Ensure risk acceptable
Step 4 - Monitor:
- Track P&L % in real-time
- Use TP levels as potential exits
- Adjust stops based on S/R
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⚠️ LIMITATIONS & REALISTIC EXPECTATIONS
This indicator does NOT:
- Predict future price movements
- Guarantee profitable trades
- Work in all market conditions
- Replace proper education and practice
This indicator CAN:
- Display standard technical indicators in organized way
- Automate common calculations
- Visualize multiple analysis methods simultaneously
- Help learn how different indicators relate
Key Understanding:
All technical indicators use historical data. They help identify patterns and conditions but cannot predict the future. Successful trading requires risk management, psychology, and experience—not just indicators.
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📚 EDUCATIONAL CONCEPTS TAUGHT
- How EMAs show trend direction and alignment
- How RSI identifies momentum extremes
- How volume confirms or diverges from price
- How support/resistance levels form
- How multiple timeframes provide context
- How ATR adapts stops to volatility
- How risk:reward ratios work
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📊 BEST SUITED FOR
- Scalping: 1m-5m charts with quick entries/exits
- Day Trading: 15m-1H focusing on ORB and PM levels
- Swing Trading: 4H-D following major trends
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⚠️ RISK DISCLAIMER
Trading involves substantial risk of loss. This educational tool:
- Does NOT guarantee profits
- Cannot predict future performance
- Requires proper risk management
- Should be practiced on demo accounts first
Always use stop losses, risk only 1-2% per trade, and consult licensed financial professionals before trading with real capital.
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Educational tool for learning technical analysis. Not financial advice. Past results do not indicate future performance.
Algorithm Predator - ProAlgorithm Predator - Pro: Advanced Multi-Agent Reinforcement Learning Trading System
Algorithm Predator - Pro combines four specialized market microstructure agents with a state-of-the-art reinforcement learning framework . Unlike traditional indicator mashups, this system implements genuine machine learning to automatically discover which detection strategies work best in current market conditions and adapts continuously without manual intervention.
Core Innovation: Rather than forcing traders to interpret conflicting signals, this system uses 15 different multi-armed bandit algorithms and a full reinforcement learning stack (Q-Learning, TD(λ) with eligibility traces, and Policy Gradient with REINFORCE) to learn optimal agent selection policies. The result is a self-improving system that gets smarter with every trade.
Target Users: Swing traders, day traders, and algorithmic traders seeking systematic signal generation with mathematical rigor. Suitable for stocks, forex, crypto, and futures on liquid instruments (>100k daily volume).
Why These Components Are Combined
The Fundamental Problem
No single indicator works consistently across all market regimes. What works in trending markets fails in ranging conditions. Traditional solutions force traders to manually switch indicators (slow, error-prone) or interpret all signals simultaneously (cognitive overload).
This system solves the problem through automated meta-learning: Deploy multiple specialized agents designed for specific market microstructure conditions, then use reinforcement learning to discover which agent (or combination) performs best in real-time.
Why These Specific Four Agents?
The four agents provide orthogonal failure mode coverage —each agent's weakness is another's strength:
Spoofing Detector - Optimal in consolidation/manipulation; fails in trending markets (hedged by Exhaustion Detector)
Exhaustion Detector - Optimal at trend climax; fails in range-bound markets (hedged by Liquidity Void)
Liquidity Void - Optimal pre-breakout compression; fails in established trends (hedged by Mean Reversion)
Mean Reversion - Optimal in low volatility; fails in strong trends (hedged by Spoofing Detector)
This creates complete market state coverage where at least one agent should perform well in any condition. The bandit system identifies which one without human intervention.
Why Reinforcement Learning vs. Simple Voting?
Traditional consensus systems have fatal flaws: equal weighting assumes all agents are equally reliable (false), static thresholds don't adapt, and no learning means past mistakes repeat indefinitely.
Reinforcement learning solves this through the exploration-exploitation tradeoff: Continuously test underused agents (exploration) while primarily relying on proven winners (exploitation). Over time, the system builds a probability distribution over agent quality reflecting actual market performance.
Mathematical Foundation: Multi-armed bandit problem from probability theory, where each agent is an "arm" with unknown reward distribution. The goal is to maximize cumulative reward while efficiently learning each arm's true quality.
The Four Trading Agents: Technical Explanation
Agent 1: 🎭 Spoofing Detector (Institutional Manipulation Detection)
Theoretical Basis: Market microstructure theory on order flow toxicity and information asymmetry. Based on research by Easley, López de Prado, and O'Hara on high-frequency trading manipulation.
What It Detects:
1. Iceberg Orders (Hidden Liquidity Absorption)
Method: Monitors volume spikes (>2.5× 20-period average) with minimal price movement (<0.3× ATR)
Formula: score += (close > open ? -2.5 : 2.5) when volume > vol_avg × 2.5 AND abs(close - open) / ATR < 0.3
Interpretation: Large volume without price movement indicates institutional absorption (buying) or distribution (selling) using hidden orders
Signal Logic: Contrarian—fade false breakouts caused by institutional manipulation
2. Spoofing Patterns (Fake Liquidity via Layering)
Method: Analyzes candlestick wick-to-body ratios during volume spikes
Formula: if upper_wick > body × 2 AND volume_spike: score += 2.0
Mechanism: Spoofing creates large wicks (orders pulled before execution) with volume evidence
Signal Logic: Wick direction indicates trapped participants; trade against the failed move
3. Post-Manipulation Reversals
Method: Tracks volume decay after manipulation events
Formula: if volume > vol_avg × 3 AND volume / volume < 0.3: score += (close > open ? -1.5 : 1.5)
Interpretation: Sharp volume drop after manipulation indicates exhaustion of manipulative orders
Why It Works: Institutional manipulation creates detectable microstructure anomalies. While retail traders see "mysterious reversals," this agent quantifies the order flow patterns causing them.
Parameter: i_spoof (sensitivity 0.5-2.0) - Controls detection threshold
Best Markets: Consolidations before breakouts, London/NY overlap windows, stocks with institutional ownership >70%
Agent 2: ⚡ Exhaustion Detector (Momentum Failure Analysis)
Theoretical Basis: Technical analysis divergence theory combined with VPIN reversals from market microstructure literature.
What It Detects:
1. Price-RSI Divergence (Momentum Deceleration)
Method: Compares 5-bar price ROC against RSI change
Formula: if price_roc > 5% AND rsi_current < rsi : score += 1.8
Mathematics: Second derivative detecting inflection points
Signal Logic: When price makes higher highs but momentum makes lower highs, expect mean reversion
2. Volume Exhaustion (Buying/Selling Climax)
Method: Identifies strong price moves (>5% ROC) with declining volume (<-20% volume ROC)
Formula: if price_roc > 5 AND vol_roc < -20: score += 2.5
Interpretation: Price extension without volume support indicates retail chasing while institutions exit
3. Momentum Deceleration (Acceleration Analysis)
Method: Compares recent 3-bar momentum to prior 3-bar momentum
Formula: deceleration = abs(mom1) < abs(mom2) × 0.5 where momentum significant (> ATR)
Signal Logic: When rate of price change decelerates significantly, anticipate directional shift
Why It Works: Momentum is lagging, but momentum divergence is leading. By comparing momentum's rate of change to price, this agent detects "weakening conviction" before reversals become obvious.
Parameter: i_momentum (sensitivity 0.5-2.0)
Best Markets: Strong trends reaching climax, parabolic moves, instruments with high retail participation
Agent 3: 💧 Liquidity Void Detector (Breakout Anticipation)
Theoretical Basis: Market liquidity theory and order book dynamics. Based on research into "liquidity holes" and volatility compression preceding expansion.
What It Detects:
1. Bollinger Band Squeeze (Volatility Compression)
Method: Monitors Bollinger Band width relative to 50-period average
Formula: bb_width = (upper_band - lower_band) / middle_band; triggers when < 0.6× average
Mathematical Foundation: Regression to the mean—low volatility precedes high volatility
Signal Logic: When volatility compresses AND cumulative delta shows directional bias, anticipate breakout
2. Volume Profile Gaps (Thin Liquidity Zones)
Method: Identifies sharp volume transitions indicating few limit orders
Formula: if volume < vol_avg × 0.5 AND volume < vol_avg × 0.5 AND volume > vol_avg × 1.5
Interpretation: Sudden volume drop after spike indicates price moved through order book to low-opposition area
Signal Logic: Price accelerates through low-liquidity zones
3. Stop Hunts (Liquidity Grabs Before Reversals)
Method: Detects new 20-bar highs/lows with immediate reversal and rejection wick
Formula: if new_high AND close < high - (high - low) × 0.6: score += 3.0
Mechanism: Market makers push price to trigger stop-loss clusters, then reverse
Signal Logic: Enter reversal after stop-hunt completes
Why It Works: Order book theory shows price moves fastest through zones with minimal liquidity. By identifying these zones before major moves, this agent provides early entry for high-reward breakouts.
Parameter: i_liquidity (sensitivity 0.5-2.0)
Best Markets: Range-bound pre-breakout setups, volatility compression zones, instruments prone to gap moves
Agent 4: 📊 Mean Reversion (Statistical Arbitrage Engine)
Theoretical Basis: Statistical arbitrage theory, Ornstein-Uhlenbeck mean-reverting processes, and pairs trading methodology applied to single instruments.
What It Detects:
1. Z-Score Extremes (Standard Deviation Analysis)
Method: Calculates price distance from 20-period and 50-period SMAs in standard deviation units
Formula: zscore_20 = (close - SMA20) / StdDev(50)
Statistical Interpretation: Z-score >2.0 means price is 2 standard deviations above mean (97.5th percentile)
Trigger Logic: if abs(zscore_20) > 2.0: score += zscore_20 > 0 ? -1.5 : 1.5 (fade extremes)
2. Ornstein-Uhlenbeck Process (Mean-Reverting Stochastic Model)
Method: Models price as mean-reverting stochastic process: dx = θ(μ - x)dt + σdW
Implementation: Calculates spread = close - SMA20, then z-score of spread vs. spread distribution
Formula: ou_signal = (spread - spread_mean) / spread_std
Interpretation: Measures "tension" pulling price back to equilibrium
3. Correlation Breakdown (Regime Change Detection)
Method: Compares 50-period price-volume correlation to 10-period correlation
Formula: corr_breakdown = abs(typical_corr - recent_corr) > 0.5
Enhancement: if corr_breakdown AND abs(zscore_20) > 1.0: score += zscore_20 > 0 ? -1.2 : 1.2
Why It Works: Mean reversion is the oldest quantitative strategy (1970s pairs trading at Morgan Stanley). While simple, it remains effective because markets exhibit periodic equilibrium-seeking behavior. This agent applies rigorous statistical testing to identify when mean reversion probability is highest.
Parameter: i_statarb (sensitivity 0.5-2.0)
Best Markets: Range-bound instruments, low-volatility periods (VIX <15), algo-dominated markets (forex majors, index futures)
Multi-Armed Bandit System: 15 Algorithms Explained
What Is a Multi-Armed Bandit Problem?
Origin: Named after slot machines ("one-armed bandits"). Imagine facing multiple slot machines, each with unknown payout rates. How do you maximize winnings?
Formal Definition: K arms (agents), each with unknown reward distribution with mean μᵢ. Goal: Maximize cumulative reward over T trials. Challenge: Balance exploration (trying uncertain arms to learn quality) vs. exploitation (using known-best arm for immediate reward).
Trading Application: Each agent is an "arm." After each trade, receive reward (P&L). Must decide which agent to trust for next signal.
Algorithm Categories
Bayesian Approaches (probabilistic, optimal for stationary environments):
Thompson Sampling
Bootstrapped Thompson Sampling
Discounted Thompson Sampling
Frequentist Approaches (confidence intervals, deterministic):
UCB1
UCB1-Tuned
KL-UCB
SW-UCB (Sliding Window)
D-UCB (Discounted)
Adversarial Approaches (robust to non-stationary environments):
EXP3-IX
Hedge
FPL-Gumbel
Reinforcement Learning Approaches (leverage learned state-action values):
Q-Values (from Q-Learning)
Policy Network (from Policy Gradient)
Simple Baseline:
Epsilon-Greedy
Softmax
Key Algorithm Details
Thompson Sampling (DEFAULT - RECOMMENDED)
Theoretical Foundation: Bayesian decision theory with conjugate priors. Published by Thompson (1933), rediscovered for bandits by Chapelle & Li (2011).
How It Works:
Model each agent's reward distribution as Beta(α, β) where α = wins, β = losses
Each step, sample from each agent's beta distribution: θᵢ ~ Beta(αᵢ, βᵢ)
Select agent with highest sample: argmaxᵢ θᵢ
Update winner's distribution after observing outcome
Mathematical Properties:
Optimality: Achieves logarithmic regret O(K log T) (proven optimal)
Bayesian: Maintains probability distribution over true arm means
Automatic Balance: High uncertainty → more exploration; high certainty → exploitation
⚠️ CRITICAL APPROXIMATION: This is a pseudo-random approximation of true Thompson Sampling. True implementation requires random number generation from beta distributions, which Pine Script doesn't provide. This version uses Box-Muller transform with market data (price/volume decimal digits) as entropy source. While not mathematically pure, it maintains core exploration-exploitation balance and learns agent preferences effectively.
When To Use: Best all-around choice. Handles non-stationary markets reasonably well, balances exploration naturally, highly sample-efficient.
UCB1 (Upper Confidence Bound)
Formula: UCB_i = reward_mean_i + sqrt(2 × ln(total_pulls) / pulls_i)
Interpretation: First term (exploitation) + second term (exploration bonus for less-tested arms)
Mathematical Properties:
Deterministic : Always selects same arm given same state
Regret Bound: O(K log T) — same optimality as Thompson Sampling
Interpretable: Can visualize confidence intervals
When To Use: Prefer deterministic behavior, want to visualize uncertainty, stable markets
EXP3-IX (Exponential Weights - Adversarial)
Theoretical Foundation: Adversarial bandit algorithm. Assumes environment may be actively hostile (worst-case analysis).
How It Works:
Maintain exponential weights: w_i = exp(η × cumulative_reward_i)
Select agent with probability proportional to weights: p_i = (1-γ)w_i/Σw_j + γ/K
After outcome, update with importance weighting: estimated_reward = observed_reward / p_i
Mathematical Properties:
Adversarial Regret: O(sqrt(TK log K)) even if environment is adversarial
No Assumptions: Doesn't assume stationary or stochastic reward distributions
Robust: Works even when optimal arm changes continuously
When To Use: Extreme non-stationarity, don't trust reward distribution assumptions, want robustness over efficiency
KL-UCB (Kullback-Leibler Upper Confidence Bound)
Theoretical Foundation: Uses KL-divergence instead of Hoeffding bounds. Tighter confidence intervals.
Formula (conceptual): Find largest q such that: n × KL(p||q) ≤ ln(t) + 3×ln(ln(t))
Mathematical Properties:
Tighter Bounds: KL-divergence adapts to reward distribution shape
Asymptotically Optimal: Better constant factors than UCB1
Computationally Intensive: Requires iterative binary search (15 iterations)
When To Use: Maximum sample efficiency needed, willing to pay computational cost, long-term trading (>500 bars)
Q-Values & Policy Network (RL-Based Selection)
Unique Feature: Instead of treating agents as black boxes with scalar rewards, these algorithms leverage the full RL state representation .
Q-Values Selection:
Uses learned Q-values: Q(state, agent_i) from Q-Learning
Selects agent via softmax over Q-values for current market state
Advantage: Selects based on state-conditional quality (which agent works best in THIS market state)
Policy Network Selection:
Uses neural network policy: π(agent | state, θ) from Policy Gradient
Direct policy over agents given market features
Advantage: Can learn non-linear relationships between market features and agent quality
When To Use: After 200+ RL updates (Q-Values) or 500+ updates (Policy Network) when models converged
Machine Learning & Reinforcement Learning Stack
Why Both Bandits AND Reinforcement Learning?
Critical Distinction:
Bandits treat agents as contextless black boxes: "Agent 2 has 60% win rate"
Reinforcement Learning adds state context: "Agent 2 has 60% win rate WHEN trend_score > 2 and RSI < 40"
Power of Combination: Bandits provide fast initial learning with minimal assumptions. RL provides state-dependent policies for superior long-term performance.
Component 1: Q-Learning (Value-Based RL)
Algorithm: Temporal Difference Learning with Bellman equation.
State Space: 54 discrete states formed from:
trend_state = {0: bearish, 1: neutral, 2: bullish} (3 values)
volatility_state = {0: low, 1: normal, 2: high} (3 values)
RSI_state = {0: oversold, 1: neutral, 2: overbought} (3 values)
volume_state = {0: low, 1: high} (2 values)
Total states: 3 × 3 × 3 × 2 = 54 states
Action Space: 5 actions (No trade, Agent 1, Agent 2, Agent 3, Agent 4)
Total state-action pairs: 54 × 5 = 270 Q-values
Bellman Equation:
Q(s,a) ← Q(s,a) + α ×
Parameters:
α (learning rate): 0.01-0.50, default 0.10 - Controls step size for updates
γ (discount factor): 0.80-0.99, default 0.95 - Values future rewards
ε (exploration): 0.01-0.30, default 0.10 - Probability of random action
Update Mechanism:
Position opens with state s, action a (selected agent)
Every bar position is open: Calculate floating P&L → scale to reward
Perform online TD update
When position closes: Perform terminal update with final reward
Gradient Clipping: TD errors clipped to ; Q-values clipped to for stability.
Why It Works: Q-Learning learns "quality" of each agent in each market state through trial and error. Over time, builds complete state-action value function enabling optimal state-dependent agent selection.
Component 2: TD(λ) Learning (Temporal Difference with Eligibility Traces)
Enhancement Over Basic Q-Learning: Credit assignment across multiple time steps.
The Problem TD(λ) Solves:
Position opens at t=0
Market moves favorably at t=3
Position closes at t=8
Question: Which earlier decisions contributed to success?
Basic Q-Learning: Only updates Q(s₈, a₈) ← reward
TD(λ): Updates ALL visited state-action pairs with decayed credit
Eligibility Trace Formula:
e(s,a) ← γ × λ × e(s,a) for all s,a (decay all traces)
e(s_current, a_current) ← 1 (reset current trace)
Q(s,a) ← Q(s,a) + α × TD_error × e(s,a) (update all with trace weight)
Lambda Parameter (λ): 0.5-0.99, default 0.90
λ=0: Pure 1-step TD (only immediate next state)
λ=1: Full Monte Carlo (entire episode)
λ=0.9: Balance (recommended)
Why Superior: Dramatically faster learning for multi-step tasks. Q-Learning requires many episodes to propagate rewards backwards; TD(λ) does it in one.
Component 3: Policy Gradient (REINFORCE with Baseline)
Paradigm Shift: Instead of learning value function Q(s,a), directly learn policy π(a|s).
Policy Network Architecture:
Input: 12 market features
Hidden: None (linear policy)
Output: 5 actions (softmax distribution)
Total parameters: 12 features × 5 actions + 5 biases = 65 parameters
Feature Set (12 Features):
Price Z-score (close - SMA20) / ATR
Volume ratio (volume / vol_avg - 1)
RSI deviation (RSI - 50) / 50
Bollinger width ratio
Trend score / 4 (normalized)
VWAP deviation
5-bar price ROC
5-bar volume ROC
Range/ATR ratio - 1
Price-volume correlation (20-period)
Volatility ratio (ATR / ATR_avg - 1)
EMA50 deviation
REINFORCE Update Rule:
θ ← θ + α × ∇log π(a|s) × advantage
where advantage = reward - baseline (variance reduction)
Why Baseline? Raw rewards have high variance. Subtracting baseline (running average) centers rewards around zero, reducing gradient variance by 50-70%.
Learning Rate: 0.001-0.100, default 0.010 (much lower than Q-Learning because policy gradients have high variance)
Why Policy Gradient?
Handles 12 continuous features directly (Q-Learning requires discretization)
Naturally maintains exploration through probability distribution
Can converge to stochastic optimal policy
Component 4: Ensemble Meta-Learner (Stacking)
Architecture: Level-1 meta-learner combines Level-0 base learners (Q-Learning, TD(λ), Policy Gradient).
Three Meta-Learning Algorithms:
1. Simple Average (Baseline)
Final_prediction = (Q_prediction + TD_prediction + Policy_prediction) / 3
2. Weighted Vote (Reward-Based)
weight_i ← 0.95 × weight_i + 0.05 × (reward_i + 1)
3. Adaptive Weighting (Gradient-Based) — RECOMMENDED
Loss Function: L = (y_true - ŷ_ensemble)²
Gradient: ∂L/∂weight_i = -2 × (y_true - ŷ_ensemble) × agent_contribution_i
Updates weights via gradient descent with clipping and normalization
Why It Works: Unlike simple averaging, meta-learner discovers which base learner is most reliable in current regime. If Policy Gradient excels in trending markets while Q-Learning excels in ranging, meta-learner learns these patterns and weights accordingly.
Feature Importance Tracking
Purpose: Identify which of 12 features contribute most to successful predictions.
Update Rule: importance_i ← 0.95 × importance_i + 0.05 × |feature_i × reward|
Use Cases:
Feature selection: Drop low-importance features
Market regime detection: Importance shifts reveal regime changes
Agent tuning: If VWAP deviation has high importance, consider boosting agents using VWAP
RL Position Tracking System
Critical Innovation: Proper reinforcement learning requires tracking which decisions led to outcomes.
State Tracking (When Signal Validates):
active_rl_state ← current_market_state (0-53)
active_rl_action ← selected_agent (1-4)
active_rl_entry ← entry_price
active_rl_direction ← 1 (long) or -1 (short)
active_rl_bar ← current_bar_index
Online Updates (Every Bar Position Open):
floating_pnl = (close - entry) / entry × direction
reward = floating_pnl × 10 (scale to meaningful range)
reward = clip(reward, -5.0, 5.0)
Update Q-Learning, TD(λ), and Policy Gradient
Terminal Update (Position Close):
Final Q-Learning update (no next Q-value, terminal state)
Update meta-learner with final result
Update agent memory
Clear position tracking
Exit Conditions:
Time-based: ≥3 bars held (minimum hold period)
Stop-loss: 1.5% adverse move
Take-profit: 2.0% favorable move
Market Microstructure Filters
Why Microstructure Matters
Traditional technical analysis assumes fair, efficient markets. Reality: Markets have friction, manipulation, and information asymmetry. Microstructure filters detect when market structure indicates adverse conditions.
Filter 1: VPIN (Volume-Synchronized Probability of Informed Trading)
Theoretical Foundation: Easley, López de Prado, & O'Hara (2012). "Flow Toxicity and Liquidity in a High-Frequency World."
What It Measures: Probability that current order flow is "toxic" (informed traders with private information).
Calculation:
Classify volume as buy or sell (close > close = buy volume)
Calculate imbalance over 20 bars: VPIN = |Σ buy_volume - Σ sell_volume| / Σ total_volume
Compare to moving average: toxic = VPIN > VPIN_MA(20) × sensitivity
Interpretation:
VPIN < 0.3: Normal flow (uninformed retail)
VPIN 0.3-0.4: Elevated (smart money active)
VPIN > 0.4: Toxic flow (informed institutions dominant)
Filter Logic:
Block LONG when: VPIN toxic AND price rising (don't buy into institutional distribution)
Block SHORT when: VPIN toxic AND price falling (don't sell into institutional accumulation)
Adaptive Threshold: If VPIN toxic frequently, relax threshold; if rarely toxic, tighten threshold. Bounded .
Filter 2: Toxicity (Kyle's Lambda Approximation)
Theoretical Foundation: Kyle (1985). "Continuous Auctions and Insider Trading."
What It Measures: Price impact per unit volume — market depth and informed trading.
Calculation:
price_impact = (close - close ) / sqrt(Σ volume over 10 bars)
impact_zscore = (price_impact - impact_mean) / impact_std
toxicity = abs(impact_zscore)
Interpretation:
Low toxicity (<1.0): Deep liquid market, large orders absorbed easily
High toxicity (>2.0): Thin market or informed trading
Filter Logic: Block ALL SIGNALS when toxicity > threshold. Most dangerous when price breaks from VWAP with high toxicity.
Filter 3: Regime Filter (Counter-Trend Protection)
Purpose: Prevent counter-trend trades during strong trends.
Trend Scoring:
trend_score = 0
trend_score += close > EMA8 ? +1 : -1
trend_score += EMA8 > EMA21 ? +1 : -1
trend_score += EMA21 > EMA50 ? +1 : -1
trend_score += close > EMA200 ? +1 : -1
Range:
Regime Classification:
Strong Bull: trend_score ≥ +3 → Block all SHORT signals
Strong Bear: trend_score ≤ -3 → Block all LONG signals
Neutral: -2 ≤ trend_score ≤ +2 → Allow both directions
Filter 4: Liquidity Boost (Signal Enhancer)
Unique: Unlike other filters (which block), this amplifies signals during low liquidity.
Logic: if volume < vol_avg × 0.7: agent_scores × 1.2
Why It Works: Low liquidity often precedes explosive moves (breakouts). By increasing agent sensitivity during compression, system catches pre-breakout signals earlier.
Technical Implementation & Approximations
⚠️ Critical Approximations Required by Pine Script
1. Thompson Sampling: Pseudo-Random Beta Distribution
Academic Standard: True random sampling from beta distributions using cryptographic RNG
This Implementation: Box-Muller transform for normal distribution using market data (price/volume decimal digits) as entropy source, then scale to beta distribution mean/variance
Impact: Not cryptographically random, may have subtle biases in specific price ranges, but maintains correct mean and approximate variance. Sufficient for bandit agent selection.
2. VPIN: Simplified Volume Classification
Academic Standard: Lee-Ready algorithm or exchange-provided aggressor flags with tick-by-tick data
This Implementation: Bar-based classification: if close > close : buy_volume += volume
Impact: 10-15% precision loss. Works well in directional markets, misclassifies in choppy conditions. Still captures order flow imbalance signal.
3. Policy Gradient: Simplified Per-Action Updates
Academic Standard: Full softmax gradient updating all actions (selected action UP, others DOWN proportionally)
This Implementation: Only updates selected action's weights
Impact: Valid approximation for small action spaces (5 actions). Slower convergence than full softmax but still learns optimal policy.
4. Kyle's Lambda: Simplified Price Impact
Academic Standard: Regression over multiple time scales with signed order flow
This Implementation: price_impact = Δprice_10 / sqrt(Σvolume_10); z_score calculation
Impact: 15-20% precision loss. No proper signed order flow. Still detects informed trading signals at extremes (>2σ).
5. Other Simplifications:
Hawkes Process: Fixed exponential decay (0.9) not MLE-optimized
Entropy: Ratio approximation not true Shannon entropy H(X) = -Σ p(x)·log₂(p(x))
Feature Engineering: 12 features vs. potential 100+ with polynomial interactions
RL Hybrid Updates: Both online and terminal (non-standard but empirically effective)
Overall Precision Loss Estimate: 10-15% compared to academic implementations with institutional data feeds.
Practical Trade-off: For retail trading with OHLCV data, these approximations provide 90%+ of the edge while maintaining full transparency, zero latency, no external dependencies, and runs on any TradingView plan.
How to Use: Practical Guide
Initial Setup (5 Minutes)
Select Trading Mode: Start with "Balanced" for most users
Enable ML/RL System: Toggle to TRUE, select "Full Stack" ML Mode
Bandit Configuration: Algorithm: "Thompson Sampling", Mode: "Switch" or "Blend"
Microstructure Filters: Enable all four filters, enable "Adaptive Microstructure Thresholds"
Visual Settings: Enable dashboard (Top Right), enable all chart visuals
Learning Phase (First 50-100 Signals)
What To Monitor:
Agent Performance Table: Watch win rates develop (target >55%)
Bandit Weights: Should diverge from uniform (0.25 each) after 20-30 signals
RL Core Metrics: "RL Updates" should increase when position open
Filter Status: "Blocked" count indicates filter activity
Optimization Tips:
Too few signals: Lower min_confidence to 0.25, increase agent sensitivities to 1.1-1.2
Too many signals: Raise min_confidence to 0.35-0.40, decrease agent sensitivities to 0.8-0.9
One agent dominates (>70%): Consider "Lock Agent" feature
Signal Interpretation
Dashboard Signal Status:
⚪ WAITING FOR SIGNAL: No agent signaling
⏳ ANALYZING...: Agent signaling but not confirmed
🟡 CONFIRMING 2/3: Building confirmation (2 of 3 bars)
🟢 LONG ACTIVE : Validated long entry
🔴 SHORT ACTIVE : Validated short entry
Kill Zone Boxes: Entry price (triangle marker), Take Profit (Entry + 2.5× ATR), Stop Loss (Entry - 1.5× ATR). Risk:Reward = 1:1.67
Risk Management
Position Sizing:
Risk per trade = 1-2% of capital
Position size = (Capital × Risk%) / (Entry - StopLoss)
Stop-Loss Placement:
Initial: Entry ± 1.5× ATR (shown in kill zone)
Trailing: After 1:1 R:R achieved, move stop to breakeven
Take-Profit Strategy:
TP1 (2.5× ATR): Take 50% off
TP2 (Runner): Trail stop at 1× ATR or use opposite signal as exit
Memory Persistence
Why Save Memory: Every chart reload resets the system. Saving learned parameters preserves weeks of learning.
When To Save: After 200+ signals when agent weights stabilize
What To Save: From Memory Export panel, copy all alpha/beta/weight values and adaptive thresholds
How To Restore: Enable "Restore From Saved State", input all values into corresponding fields
What Makes This Original
Innovation 1: Genuine Multi-Armed Bandit Framework
This implements 15 mathematically rigorous bandit algorithms from academic literature (Thompson Sampling from Chapelle & Li 2011, UCB family from Auer et al. 2002, EXP3 from Auer et al. 2002, KL-UCB from Garivier & Cappé 2011). Each algorithm maintains proper state, updates according to proven theory, and converges to optimal behavior. This is real learning, not superficial parameter changes.
Innovation 2: Full Reinforcement Learning Stack
Beyond bandits learning which agent works best globally, RL learns which agent works best in each market state. After 500+ positions, system builds 54-state × 5-action value function (270 learned parameters) capturing context-dependent agent quality.
Innovation 3: Market Microstructure Integration
Combines retail technical analysis with institutional-grade microstructure metrics: VPIN from Easley, López de Prado, O'Hara (2012), Kyle's Lambda from Kyle (1985), Hawkes Processes from Hawkes (1971). These detect informed trading, manipulation, and liquidity dynamics invisible to technical analysis.
Innovation 4: Adaptive Threshold System
Dynamic quantile-based thresholds: Maintains histogram of each agent's score distribution (24 bins, exponentially decayed), calculates 80th percentile threshold from histogram. Agent triggers only when score exceeds its own learned quantile. Proper non-parametric density estimation automatically adapts to instrument volatility, agent behavior shifts, and market regime changes.
Innovation 5: Episodic Memory with Transfer Learning
Dual-layer architecture: Short-term memory (last 20 trades, fast adaptation) + Long-term memory (condensed episodes, historical patterns). Transfer mechanism consolidates knowledge when STM reaches threshold. Mimics hippocampus → neocortex consolidation in human memory.
Limitations & Disclaimers
General Limitations
No Predictive Guarantee: Pattern recognition ≠ prediction. Past performance ≠ future results.
Learning Period Required: Minimum 50-100 bars for reliable statistics. Initial performance may be suboptimal.
Overfitting Risk: System learns patterns in historical data. May not generalize to unprecedented conditions.
Approximation Limitations: See technical implementation section (10-15% precision loss vs. academic standards)
Single-Instrument Limitation: No multi-asset correlation, sector context, or VIX integration.
Forward-Looking Bias Disclaimer
CRITICAL TRANSPARENCY: The RL system uses an 8-bar forward-looking window for reward calculation.
What This Means: System learns from rewards incorporating future price information (bars 101-108 relative to entry at bar 100).
Why Acceptable:
✅ Signals do NOT look ahead: Entry decisions use only data ≤ entry bar
✅ Learning only: Forward data used for optimization, not signal generation
✅ Real-time mirrors backtest: In live trading, system learns identically
⚠️ Implication: Dashboard "Agent Win%" reflects this 8-bar evaluation. Real-time performance may differ slightly if positions held longer, slippage/fees not captured, or market microstructure changes.
Risk Warnings
No Guarantee of Profit: All trading involves risk of loss
System Failures: Bugs possible despite extensive testing
Market Conditions: Optimized for liquid markets (>100k daily volume). Performance degrades in illiquid instruments, major news events, flash crashes
Broker-Specific Issues: Execution slippage, commission/fees, overnight financing costs
Appropriate Use
This Indicator Is:
✅ Entry trigger system
✅ Risk management framework (stop/target)
✅ Adaptive agent selection engine
✅ Learning system that improves over time
This Indicator Is NOT:
❌ Complete trading strategy (requires position sizing, portfolio management)
❌ Replacement for fundamental analysis
❌ Guaranteed profit generator
❌ Suitable for complete beginners without training
Recommended Complementary Analysis: Market context (support/resistance), volume profile, fundamental catalysts, correlation with related instruments, broader market regime
Recommended Settings by Instrument
Stocks (Large Cap, >$1B):
Mode: Balanced | ML/RL: Enabled, Full Stack | Bandit: Thompson Sampling, Switch
Agent Sensitivity: Spoofing 1.0-1.2, Exhaustion 0.9-1.1, Liquidity 0.8-1.0, StatArb 1.1-1.3
Microstructure: All enabled, VPIN 1.2, Toxicity 1.5 | Timeframe: 15min-1H
Forex Majors (EURUSD, GBPUSD):
Mode: Balanced to Conservative | ML/RL: Enabled, Full Stack | Bandit: Thompson Sampling, Blend
Agent Sensitivity: Spoofing 0.8-1.0, Exhaustion 0.9-1.1, Liquidity 0.7-0.9, StatArb 1.2-1.5
Microstructure: All enabled, VPIN 1.0-1.1, Toxicity 1.3-1.5 | Timeframe: 5min-30min
Crypto (BTC, ETH):
Mode: Aggressive to Balanced | ML/RL: Enabled, Full Stack | Bandit: Thompson Sampling OR EXP3-IX
Agent Sensitivity: Spoofing 1.2-1.5, Exhaustion 1.1-1.3, Liquidity 1.2-1.5, StatArb 0.7-0.9
Microstructure: All enabled, VPIN 1.4-1.6, Toxicity 1.8-2.2 | Timeframe: 15min-4H
Futures (ES, NQ, CL):
Mode: Balanced | ML/RL: Enabled, Full Stack | Bandit: UCB1 or Thompson Sampling
Agent Sensitivity: All 1.0-1.2 (balanced)
Microstructure: All enabled, VPIN 1.1-1.3, Toxicity 1.4-1.6 | Timeframe: 5min-30min
Conclusion
Algorithm Predator - Pro synthesizes academic research from market microstructure theory, reinforcement learning, and multi-armed bandit algorithms. Unlike typical indicator mashups, this system implements 15 mathematically rigorous bandit algorithms, deploys a complete RL stack (Q-Learning, TD(λ), Policy Gradient), integrates institutional microstructure metrics (VPIN, Kyle's Lambda), adapts continuously through dual-layer memory and meta-learning, and provides full transparency on approximations and limitations.
The system is designed for serious algorithmic traders who understand that no indicator is perfect, but through proper machine learning, we can build systems that improve over time and adapt to changing markets without manual intervention.
Use responsibly. Risk disclosure applies. Past performance ≠ future results.
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Buy/Sell Volume Tracker [wjdtks255]Indicator Description
Function: Separates buy and sell volume based on candle direction (close ≥ open) and displays the buy−sell difference (hist_val) as a histogram.
Visuals: Buy/sell bars are distinguished by user-selectable colors and opacity; two moving averages (MA1 and MA2) are shown to smooth the flow.
Meaning: A positive histogram indicates buy dominance; a negative histogram indicates sell dominance.
Limitation: The current separation is estimated from candle direction and may differ from execution-side (tick/trade-side) based data.
Trading Rules (Summary)
Conservative trend-following long
Entry: Enter long when hist_val turns above 0 and MA1 crosses MA2 from below.
Stop-loss: Exit if hist_val falls back below 0 or MA1 drops below MA2.
Take-profit: Use a risk:reward of 1:1.5 or set targets based on ATR.
Short-term rebound long
Entry: Enter a short-term long when a large negative histogram region begins to narrow and shows a recovery sign.
Stop-loss: Exit if hist_val drops below the previous low or bearish candles continue.
Take-profit: Prefer quick partial profit-taking.
Short (sell) strategy
Entry: Enter short when hist_val falls below 0 and MA1 crosses MA2 from above.
Stop-loss / Take-profit: Apply the inverse rules of the long strategy.
Filters and risk management
Volume filter: Only accept signals when volume exceeds a fraction of average volume to reduce noise.
Entry strength: Require |hist_val| to exceed a historical average threshold (e.g., avg(|hist_val|, N) × factor) to strengthen signals.
Position sizing: Size positions so that account risk per trade is within limits (e.g., 1–2% of account equity).
Timeframe: Use short timeframes for scalping and 1h+ for swing trading.
Atif's Liquidity Toolkit💎 GENERAL OVERVIEW:
Atif’s Liquidity Toolkit is a price-action-based indicator used to identify Buyside & Sellside Liquidity Levels, Liquidity Sweeps, FVG Sweeps, and Buy/Sell signals, following specific rules from Atif Hussain.
This indicator was developed by Flux Charts in collaboration with Atif Hussain.
🔹Purpose of this indicator:
The purpose of Atif’s Liquidity Toolkit is to help traders understand where liquidity is forming, when it’s being taken, and how momentum shifts immediately afterward. It automates the entire process of identifying buyside & sellside liquidity, detecting liquidity sweeps, and confirming whether displacement followed through a Fair Value Gap. The goal is to give traders a consistent, rule-based framework to interpret market structure.
🎯ATIF’S LIQUIDITY TOOLKIT FEATURES:
Atif’s Liquidity Toolkit indicator includes 6 main features:
Fair Value Gaps
Multi-Timeframe Liquidity Levels
Liquidity Sweeps
Fair Value Gap Sweeps
Buy & Sell Signals with Take-Profit & Stop-Loss Levels
Alerts
1️⃣Fair Value Gaps
🔹What is a Fair Value Gap?:
A Fair Value Gap (FVG) is an area where the market’s perception of fair value suddenly changes. On your chart, it appears as a three-candle pattern: a large candle in the middle, with smaller candles on each side that don’t fully overlap it. A bullish FVG forms when a bullish candle is between two smaller bullish/bearish candles, where the first and third candles’ wicks don’t overlap each other at all. A bearish FVG forms when a bearish candle is between two smaller bullish/bearish candles, where the first and third candles’ wicks don’t overlap each other at all.
Bullish & Bearish FVGs:
In the settings, you can toggle on/off FVGs, choose the invalidation method, adjust the sensitivity, and toggle on FVG Midline & Labels.
🔹Invalidation Method:
The Invalidation Method setting allows traders to choose how an FVG is invalidated. You can choose between Close and Wick.
Close: A candle must close below a bullish FVG or above a bearish FVG to invalidate it.
Wick: A candle’s wick must go below a bullish FVG or above a bearish FVG to invalidate it.
🔹Sensitivity:
The sensitivity setting determines the minimum gap size required for an FVG detection. A higher sensitivity will filter out smaller gaps, while a lower sensitivity will detect more frequent, smaller gaps. Setting the sensitivity to 0 will display all gaps, regardless of their size.
On the left, the sensitivity is 5. On the right, the sensitivity is 0.
🔹Midline:
When enabled, a dashed line is drawn at the center of the FVG.
🔹Labels:
When enabled, a text label will be plotted with the gap, clearly identifying the zone as a FVG.
2️⃣ Multi-Timeframe Liquidity Levels
The indicator automatically detects and plots Buyside Liquidity (BSL) & Sellside Liquidity (SSL) Levels across up to three timeframes simultaneously.
🔹What is Buyside Liquidity?
Buyside Liquidity (BSL) represents price levels where many buy stop orders are sitting, usually from traders holding short positions. When price moves into these areas, those stop-loss orders get triggered and short sellers are forced to buy back their positions. These zones often form above key highs such as the previous day, week, or month. Understanding BSL is important because when price reaches these levels, the sudden wave of buy orders can create sharp reactions or reversals as liquidity is taken from the market.
🔹What is Sellside Liquidity?
Sellside Liquidity (SSL) represents price levels where many sell stop orders are waiting, usually from traders holding long positions. When price drops into these areas, those stop-loss orders are triggered and long traders are forced to sell their positions. These zones often form below key lows such as the previous day, week, or month. Understanding SSL is important because when price reaches these levels, the surge of sell orders can cause sharp reactions or reversals as liquidity is taken from the market.
Atif’s Liquidity Toolkit indicator automatically plots Buyside & Sellside Liquidity levels using the following levels:
Previous Day High (PDH) & Previous Day Low (PDL)
Previous Week High (PWH) & Previous Week Low (PWL)
Previous Month High (PMH) & Previous Month Low (PML)
Asia Session Highs/Lows
London Session Highs/Lows
New York Session Highs/Lows
The session start and end times are not customizable. The following times in EST are used for each session:
Asia Session: 20:00-00:00
London Session: 02:00-05:00
New York Sessions:
NY AM: 09:30-11:00
NY Lunch: 12:00-13:00
NY PM: 14:00-16:00
Users can also plot swing highs/lows using a lookback period and choosing the higher timeframe. Users can choose two custom higher timeframes and also enable swing highs/lows from the current chart’s timeframe.
There are three settings to customize for the current chart’s timeframe and higher timeframes:
Current TF - when toggled on, swing highs/lows will be plotted from the chart’s timeframe using the pivot length input
HTF 1 - when toggled on, swing highs/lows will be plotted from the user-inputted timeframe using the pivot length input
HTF 2 - when toggled on, swing highs/lows will be plotted from the user-inputted timeframe using the pivot length input
The Pivot Length controls how far back the indicator checks to confirm whether a candle’s high or low is a true swing point (also called a “pivot”). When detecting a swing high, the indicator checks if that candle’s high is higher than the highs of the previous X candles and the next X candles. For a swing low, it checks if the candle’s low is lower than the lows of the previous X candles and the next X candles. The number X comes from your Pivot Length setting.
A lower Pivot Length input (for example, 3 or 4) means the indicator only looks at a few candles on each side, so it will detect more swing points, including smaller, less significant ones. A higher Pivot Length input (for example, 20 or 25) makes the indicator look at more candles on each side, so it only marks major turning points that stand out clearly on the chart.
In short:
Low Pivot Length = more frequent, smaller levels (short-term focus)
High Pivot Length = fewer, stronger levels (major swing focus)
The Pivot Length input for each setting (Current TF, HTF 1, and HTF 2) are displayed below in the red boxes:
Each liquidity level is plotted with a text label, making it easy to identify where a level came from. You can turn off the ‘Show Levels’ setting if you don’t want to see the levels on your chart.
Please note: Liquidity Levels play a key role in finding liquidity sweeps, FVG Sweeps, and Buy/Sell signals. Keeping the levels turned off will not stop the indicator from using the levels that are enabled from being used for the other features mentioned.
3️⃣Liquidity Sweeps:
The indicator automatically detects bullish and bearish liquidity sweeps using the liquidity levels you have enabled.
🔹What is a Liquidity Sweep?
A liquidity sweep is a market phenomenon where significant players, such as institutional traders, deliberately drive prices through key levels to trigger clusters of pending buy or sell orders. It’s how the market gathers the liquidity needed for larger participants to enter positions.
Traders often place stop-loss orders around obvious highs and lows, such as the previous day’s, week’s, or month’s levels. When price pushes through one of these areas, it triggers the stops placed there and generates a burst of volume. This often creates a short-term fake-out before the market reverses in the opposite direction.
By detecting these sweeps in real time, traders can identify potential reversal areas or “trap” areas where liquidity has been taken.
🔹Bullish Liquidity Sweep
These occur when price dips below a Sellside Liquidity (SSL) level, taking out the stop-loss orders placed by long traders below that low. The indicator marks a zone around the candle that swept the SSL to highlight where liquidity was removed from the market.
When this happens, it shows that the market just cleared out sell-side liquidity, meaning traders who were long had their stops hit. This is often followed by a reversal or strong reaction upward, because the market no longer has pending liquidity to fill below that level.
🔹Bearish Liquidity Sweep
These occur when price dips above a Buyside Liquidity (BSL) level, taking out the stop-loss orders placed by short seller traders above that high. The indicator marks a zone around the candle that swept the BSL to highlight where liquidity was removed from the market.
When this happens, it shows that the market just cleared out buyside liquidity, meaning short traders had their stops hit. This is often followed by a reversal or strong reaction downward, because the market no longer has pending liquidity to fill above that level.
Under the ‘Liquidity Sweeps’ section in the settings, you can toggle on/off Bullish Regular Sweeps and Bearish Regular Sweeps. You can also customize the line style and color of liquidity levels that have been swept.
🔹How to Use Liquidity Sweeps
Liquidity sweeps are not direct trade signals. They are best used as context when forming a directional bias. A sweep shows that the market has removed liquidity from one side, which can hint at where the next move may develop.
For example:
When Buyside Liquidity (BSL) is swept, it often signals that buy stops have been triggered and the market may be preparing to move lower. Traders may then begin looking for short opportunities.
When Sellside Liquidity (SSL) is swept, it often signals that sell stops have been triggered and the market may be preparing to move higher. Traders may then begin looking for long opportunities.
It’s common practice to use liquidity sweeps as the first step in building a trade idea. Many traders will wait for additional confirmation, such as a fair value gap forming after the sweep, before opening a position.
Under the ‘Liquidity Sweeps’ section in the settings, you can toggle on/off:
Bullish Regular Sweeps - when disabled, Bullish Regular Sweeps won’t appear on your chart.
Bearish Regular Sweeps - when disabled, Bearish Regular Sweeps won’t appear on your chart.
4️⃣Fair Value Gap Sweeps:
The indicator automatically detects bullish and bearish Fair Value Gap sweeps (FVG Sweep) using the liquidity levels you have enabled.
🔹What is a FVG Sweep?
A FVG Sweep is a specific type of liquidity sweep that not only clears liquidity above or below a key level, but also forms a Fair Value Gap (FVG) immediately afterward.
The liquidity sweep shows where stop orders were triggered, areas where the market aggressively took out one side’s liquidity. The formation of a Fair Value Gap right after the sweep confirms that displacement followed. This means that the sweep was not just a stop hunt, but a deliberate move backed by momentum.
In simple terms, a regular liquidity sweep only tells you that liquidity was taken. A FVG Sweep tells you that liquidity was taken and a strong directional move started immediately after, leaving an imbalance in price. That imbalance represents where aggressive buyers or sellers entered the market without enough opposite-side orders to keep price balanced. This combination adds a confirmation and intent behind regular liquidity sweeps.
🔹Bullish FVG Sweep
The indicator automatically detects bullish FVG Sweeps when price takes out a Sellside Liquidity (SSL) level and then forms a bullish FVG within the next few candles. This sequence shows that sellers were stopped out and buyers immediately entered the market with momentum.
🔹Bearish FVG Sweep
The indicator automatically detects bearish FVG Sweeps when price takes out a Buyside Liquidity (BSL) level and then forms a bearish FVG shortly after. This shows that short sellers’ stops were triggered, and new selling pressure entered the market right away.
🔹How to Use FVG Sweeps
Unlike regular liquidity sweeps, FVG Sweeps can be used as trade entries because they confirm both liquidity being cleared and immediate momentum. A regular sweep only shows that stop-losses were triggered, but an FVG Sweep proves that price not only cleared liquidity but also moved away with momentum, leaving behind an imbalance (Fair Value Gap). This shift often marks the start of a new short-term trend.
We’ll cover this in more detail in the Buy and Sell Signal section below, but in short, a bullish FVG Sweep can act as confirmation for a potential long entry after price takes out a low, while a bearish FVG Sweep can confirm a short entry after price takes out a high.
The strongest FVG Sweeps come from extremely sharp reversals. On the chart, they look like a “V” shape for bullish setups or an inverted “V” shape for bearish setups. This shape shows how quickly momentum shifted after liquidity was cleared. When price instantly reverses and leaves a Fair Value Gap behind, it’s a clear sign that buyers or sellers stepped in aggressively and absorbed all available liquidity on the opposite side.
In practice, traders often use FVG Sweeps as a trigger to align their bias. For example, after a bullish FVG Sweep, the focus shifts toward looking for long setups within the new imbalance or during a small retracement into the Fair Value Gap. After a bearish FVG Sweep, traders focus on short setups as price retraces back into the gap before continuing lower. The key takeaway is that FVG Sweeps show conviction.
Under the ‘Liquidity Sweeps’ section in the settings, you can toggle on/off:
Bullish FVG Sweeps - when disabled, Bullish FVG Sweeps won’t appear on your chart.
Bearish FVG Sweeps - when disabled, Bearish FVG Sweeps won’t appear on your chart.
Please Note: the settings you choose to use for Fair Value Gaps, under the ‘Fair Value Gaps’ section, will be used for FVG Sweeps. This is important because if you increase the sensitivity value for FVGs, not all FVG Sweeps will appear if the FVG’s size doesn’t meet the sensitivity threshold.
5️⃣Buy & Sell Signals:
This indicator also plots Buy & Sell signals. These signals follow logic based on Atif Hussain’s FVG trading model. The entry requirements for a Long & Short signal are outlined below.
🔹Buy Signal:
In order for a Buy Signal to generate, the following conditions must occur in order:
Bullish FVG Sweep
Price Retraces to the Bullish FVG
🔹Sell Signal:
In order for a Buy Signal to generate, the following conditions must occur in order:
Bearish FVG Sweep
Price Retraces to the FVG
🔹Require Retracement:
Under the ‘Signals’ section in the settings, you can toggle on/off the ‘Require Retracement’ setting. When disabled, a long/short signal will appear immediately after a Bullish or Bearish FVG Sweep, instead of waiting for price to retrace back to the gap.
Please Note: the liquidity levels you enable under the ‘Liquidity Levels’ section will be the levels used for signals. Thus, if you only have the Previous Day Highs/Lows enabled, then only those levels will be used to generate buy/sell signals. Also, long Signals will only appear if Bullish FVG Sweeps are enabled, and Short Signals will only appear if Bearish FVG Sweeps are enabled.
When a Buy Signal or Sell Signal is plotted, three suggested take-profit levels and one suggested stop-loss level are plotted. There are two different Take-Profit methods you can choose from within the indicator settings: Manual or Auto.
🔹Manual Take-Profit:
If you’re using manual take-profit levels, you can customize the Risk-to-Reward (RR) for Take-Profit 1, 2, and 3 by adjusting the “RR 1”, “RR 2”, and “RR 3” settings. Setting RR 1 to 1 means take-profit 1 is a 1:1 risk-to-reward ratio. The stop-loss will always be placed at the recent low for Buy Signals, and at the recent high for Sell Signals.
🔹Auto Take-Profit:
If you select to use Auto Take-Profit instead of Manual, then Take-Profit 1, 2, and 3 will be automatically determined based on nearby liquidity levels. The stop-loss will be placed at the recent low for Buy Signals, and at the recent high for Sell Signals. Take-Profit Levels 1, 2, and 3 will be placed at the three closest opposite liquidity levels. If the take-profit 2 and take-profit 3 levels are too far away, only one take-profit level will be displayed.
🔹Signal Settings:
Long Signals:
When enabled, long signals are shown. When disabled, long signals will not appear.
Short Signals:
When enabled, short signals are shown. When disabled, short signals will not appear.
Require Retracement:
When enabled, price must retrace to a FVG after a FVG Sweep in order for a signal to be generated.
Take-Profit Levels:
When enabled, take-profit levels (TP 1, TP 2, and TP 3) are shown with long/short signals. When disabled, take-profit levels and their price labels are not displayed.
Take-Profit Labels:
When enabled, take-profit labels are displayed when price reaches one of the three take-profit levels. When disabled, labels won’t appear when price reaches take-profit levels.
Stop-Loss Levels:
When enabled, stop-loss levels are shown for long/short signals. When disabled, the stop-loss level and its price label are not displayed.
Stop-Loss Labels:
When enabled, stop-loss levels are shown for long/short signals. When disabled, a label won’t appear when price reaches the stop-loss level.
6️⃣Alerts:
The indicator supports alerts, so you never miss a key market move. You can choose to receive alerts for each of the following conditions:
Bearish Liquidity Sweep
Bullish Liquidity Sweep
Bearish FVG Sweep
Bullish FVG Sweep
Long Signal
Short Signal
TP 1
TP 2
TP 3
Stop-Loss
‼️Important Notes:
TradingView has limitations when running features on multiple timeframes, such as the liquidity levels, which can result in the following error:
🔹Computation Error:
The computation of using MTF features are very intensive on TradingView. This can sometimes cause calculation timeouts. When this occurs, simply force the recalculation by modifying one indicator’s settings or by removing the indicator and adding it to your chart again.
🚩 UNIQUENESS:
This indicator is unique because it identifies a specific type of liquidity event referred to as FVG Sweeps, where price takes liquidity and then immediately forms a Fair Value Gap in the opposite direction. These FVG Sweeps serve as the foundation of the model, and the script uses them as the required condition for generating Buy and Sell signals. Once an FVG Sweep is confirmed, the indicator automatically produces a fully defined trade idea with a stop-loss and up to three take-profit targets, following a consistent rule-based execution approach.
