3 Bar Reversal3 Bar Reversal
This pattern is described in John Carter's "Mastering the Trade"
The 3 Bar Reversal indicator is a simple but effective price action tool designed to highlight potential short-term reversals in market direction. It monitors consecutive bar behavior and identifies turning points based on a three-bar pattern. This tool can assist traders in spotting trend exhaustion or early signs of a reversal, particularly in scalping or short-term trading strategies.
How It Works
This indicator analyzes the relationship between consecutive bar closes:
It counts how many bars have passed since the price closed higher than the previous close (barssince(close >= close )) — referred to as an "up streak".
It also counts how many bars have passed since the price closed lower than the previous close (barssince(close <= close )) — known as a "down streak".
A reversal condition is met when:
There have been exactly 3 bars in a row moving in one direction (up or down), and
The 4th bar closes in the opposite direction.
When this condition is detected, the script performs two actions:
Plots a triangle on the chart to signal the potential reversal:
A green triangle below the bar for a possible long (buy) opportunity.
A red triangle above the bar for a possible short (sell) opportunity.
Triggers an alert condition so users can set notifications for when a reversal is detected.
Interpretation
Long Signal: The market has printed 3 consecutive lower closes, followed by a higher close — suggesting bullish momentum may be emerging.
Short Signal: The market has printed 3 consecutive higher closes, followed by a lower close — indicating possible bearish momentum.
These patterns are common in market retracements and can act as confirmation signals when used with other indicators such as RSI, MACD, support/resistance, or volume analysis.
Usage Examples
Scalping: Use the reversal signal to quickly enter short-term trades after a short-term exhaustion move.
Swing Trading: Combine this with trend indicators (e.g., moving averages) to time pullbacks within larger trends.
Confirmation Tool: Use this indicator alongside candlestick patterns or support/resistance zones to validate entry or exit points.
Alert Setup: Enable alerts based on the built-in alertcondition to receive instant notifications for potential trade setups.
Limitations
The 3-bar reversal logic does not guarantee a trend change; it signals potential reversals, which may need confirmation.
Best used in conjunction with broader context such as trend direction, market structure, or other technical indicators.
In den Scripts nach "market structure" suchen
Advanced Moving Average ChannelAdvanced Moving Average Channel (MAC) is a comprehensive technical analysis tool that combines multiple moving average types with volume analysis to provide a complete market perspective.
Key Features:
1. Dynamic Channel Formation
- Configurable moving average types (SMA, EMA, WMA, VWMA, HMA, TEMA)
- Separate upper and lower band calculations
- Customizable band offsets for precise channel adjustment
2. Volume Analysis Integration
- Multi-timeframe volume analysis (1H, 24H, 7D)
- Relative volume comparison against historical averages
- Volume trend detection with visual indicators
- Price-level volume distribution profile
3. Market Context Indicators
- RSI integration for overbought/oversold conditions
- Channel position percentage
- Volume-weighted price levels
- Breakout detection with visual signals
Usage Guidelines:
1. Channel Interpretation
- Price within channel: Normal market conditions
- Price above upper band: Potential overbought condition
- Price below lower band: Potential oversold condition
- Channel width: Indicates market volatility
2. Volume Analysis
- High relative volume (>150%): Strong market interest
- Low relative volume (<50%): Weak market interest
- Volume trend arrows: Indicate increasing/decreasing market participation
- Volume profile: Shows price levels with highest trading activity
3. Trading Signals
- Breakout arrows: Potential trend continuation
- RSI extremes: Confirmation of overbought/oversold conditions
- Volume confirmation: Validates price movements
Customization:
- Adjust MA length for different market conditions
- Modify band offsets for tighter/looser channels
- Fine-tune volume analysis parameters
- Customize visual appearance
This indicator is designed for traders who want to combine price action, volume analysis, and market structure in a single, comprehensive tool.
Support and Resistance Logistic Regression | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Logistic Regression Support / Resistance indicator! This tool leverages advanced statistical modeling "Logistic Regressions" to identify and project key price levels where the market is likely to find support or resistance. For more information about the process, please check the "HOW DOES IT WORK ?" section.
Logistic Regression Support / Resistance Features :
Intelligent S/R Identification : The indicator uses a logistic regression model to intelligently identify and plot significant support and resistance levels.
Predictive Probability : Each identified level comes with a calculated probability, indicating how likely it is to act as a true support or resistance based on historical data.
Retest & Break Labels : The indicator clearly marks on your chart when a detected support or resistance level is retested (price touches and respects the level) or broken (price decisively crosses through the level).
Alerts : Real-time alerts for support retests, resistance retests, support breaks, and resistance breaks.
Customizable : You can change support & resistance line style, width and colors.
🚩 UNIQUENESS
What makes this indicator truly unique is its application of logistic regression to the concept of support and resistance. Instead of merely identifying historical highs and lows, our indicator uses a statistical model to predict the future efficacy of these levels. It analyzes underlying market conditions (like RSI and body size at pivot formation) to assign a probability to each potential S/R zone. This predictive insight, combined with dynamic, real-time labeling of retests and breaks, provides a more robust and adaptive understanding of market structure than traditional, purely historical methods.
📌HOW DOES IT WORK ?
The Logistic Regression Support / Resistance indicator operates in several key steps:
First, it identifies significant pivot highs and lows on the chart based on a user-defined "Pivot Length." These pivots are potential areas of support or resistance.
For each detected pivot, the indicator extracts relevant market data at that specific point, including the RSI (Relative Strength Index) and the Body Size (the absolute difference between the open and close price of the candle). These serve as input features for the model.
The core of the indicator lies in its logistic regression model. This model is continuously trained on past pivot data and their subsequent behavior (i.e., whether they were "respected" as support/resistance multiple times). It learns the relationship between the extracted features (RSI, Body Size) and the likelihood of a pivot becoming a significant S/R level.
When a new pivot is identified, the model uses its learned insights to calculate a prediction value—a probability (from 0 to 1) that this specific pivot will act as a strong support or resistance.
If the calculated probability exceeds a user-defined "Probability Threshold," the pivot is designated a "Regression Pivot" and drawn on the chart as a support or resistance line. The indicator then actively tracks how price interacts with these levels, displaying "R" labels for retests when the price bounces off the level and "B" labels for breaks when the price closes beyond it.
⚙️ SETTINGS
1. General Configuration
Pivot Length: This setting defines the number of bars used to determine a significant high or low for pivot detection.
Target Respects: This input specifies how many times a level must be "respected" by price action for it to be considered a strong support or resistance level by the underlying model.
Probability Threshold: This is the minimum probability output from the logistic regression model for a detected pivot to be considered a valid support or resistance level and be plotted on the chart.
2. Style
Show Prediction Labels: Enable or disable labels that display the calculated probability of a newly identified regression S/R level.
Show Retests: Toggle the visibility of "R" labels on the chart, which mark instances where price has retested a support or resistance level.
Show Breaks: Toggle the visibility of "B" labels on the chart, which mark instances where price has broken through a support or resistance level.
Dynamic Range Filter with Trend Candlesticks (Zeiierman)█ Overview
Dynamic Range Filter with Trend Candlesticks (Zeiierman) is a volatility-responsive trend engine that adapts in real-time to market structure, offering a clean and intelligent visualization of directional bias. It blends dynamic range calculation with customizable smoothing techniques and layered trend confirmation logic, making it ideal for traders who rely on clear trend direction, structural range analysis, and momentum-based candlestick signals.
By measuring scaled volatility over configurable lengths and applying advanced moving average techniques, this indicator filters out market noise while preserving true directional intent. Complementing this, a dual-trend system (range-based and candle-based) enhances clarity and responsiveness, particularly during shifting market conditions.
█ How It Works
⚪ Scaled Volatility Band Calculation
At the core lies a volatility engine that constructs adaptive range bands around price using smoothed high/low calculations. The bands are dynamically adjusted using:
High/Low Smoothing – Applies a moving average to the raw high and low data before calculating the range.
Scaled Range Volatility – A 2.618 multiplier scales the distance between smoothed highs and lows, forming a responsive volatility envelope.
Band Multiplier – Controls how wide the upper/lower range bands extend from the mean.
This filtering process minimizes false signals and highlights only structurally meaningful moves.
⚪ Multi-Type Smoothing Engine
Users can choose from a wide array of smoothing algorithms for trend construction, including:
HMA (default), SMA, EMA, RMA
KAMA – Adapts to market volatility using efficiency ratios.
VIDYA – Momentum-sensitive smoothing using CMO logic.
FRAMA – Dynamically adjusts to fractal dimension in price.
Super Smoother – Ideal for eliminating aliasing in range signals.
This provides the trader with fine-tuned control over reactivity vs. smoothness.
⚪ Trend Detection (Dual Engine)
The indicator includes two independent trend tracking systems:
Main Trend Filter – Based on adaptive volatility band shifts.
Candle Trend Filter – A second-tier confirmation using smoothed candle data, ideal for directional candles and confirmation entries.
█ How to Use
⚪ Trend Confirmation
Use the Trend Line and colored candlesticks for high-probability entries in the trend direction. The more trend layers that align, the higher the confidence.
⚪ Reversal Zones
When the price reaches the outer bands or fails to break them, look for candle color shifts or a crossover in the range to anticipate possible reversals or consolidations.
█ Settings
Scaled Volatility Length – Controls the lookback used to stabilize the base volatility band.
MA Type & Length – Choose and fine-tune the smoothing method (HMA, EMA, KAMA, etc.)
High/Low Smoother – Pre-smoothing for structural high/low banding.
Band Multiplier – Adjusts the width of the dynamic bands.
Trend Length (Candles) – Length used for candle-based trend confirmation.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Ergodic Market Divergence (EMD)Ergodic Market Divergence (EMD)
Bridging Statistical Physics and Market Dynamics Through Ensemble Analysis
The Revolutionary Concept: When Physics Meets Trading
After months of research into ergodic theory—a fundamental principle in statistical mechanics—I've developed a trading system that identifies when markets transition between predictable and unpredictable states. This indicator doesn't just follow price; it analyzes whether current market behavior will persist or revert, giving traders a scientific edge in timing entries and exits.
The Core Innovation: Ergodic Theory Applied to Markets
What Makes Markets Ergodic or Non-Ergodic?
In statistical physics, ergodicity determines whether a system's future resembles its past. Applied to trading:
Ergodic Markets (Mean-Reverting)
- Time averages equal ensemble averages
- Historical patterns repeat reliably
- Price oscillates around equilibrium
- Traditional indicators work well
Non-Ergodic Markets (Trending)
- Path dependency dominates
- History doesn't predict future
- Price creates new equilibrium levels
- Momentum strategies excel
The Mathematical Framework
The Ergodic Score combines three critical divergences:
Ergodic Score = (Price Divergence × Market Stress + Return Divergence × 1000 + Volatility Divergence × 50) / 3
Where:
Price Divergence: How far current price deviates from market consensus
Return Divergence: Momentum differential between instrument and market
Volatility Divergence: Volatility regime misalignment
Market Stress: Adaptive multiplier based on current conditions
The Ensemble Analysis Revolution
Beyond Single-Instrument Analysis
Traditional indicators analyze one chart in isolation. EMD monitors multiple correlated markets simultaneously (SPY, QQQ, IWM, DIA) to detect systemic regime changes. This ensemble approach:
Reveals Hidden Divergences: Individual stocks may diverge from market consensus before major moves
Filters False Signals: Requires broader market confirmation
Identifies Regime Shifts: Detects when entire market structure changes
Provides Context: Shows if moves are isolated or systemic
Dynamic Threshold Adaptation
Unlike fixed-threshold systems, EMD's boundaries evolve with market conditions:
Base Threshold = SMA(Ergodic Score, Lookback × 3)
Adaptive Component = StDev(Ergodic Score, Lookback × 2) × Sensitivity
Final Threshold = Smoothed(Base + Adaptive)
This creates context-aware signals that remain effective across different market environments.
The Confidence Engine: Know Your Signal Quality
Multi-Factor Confidence Scoring
Every signal receives a confidence score based on:
Signal Clarity (0-35%): How decisively the ergodic threshold is crossed
Momentum Strength (0-25%): Rate of ergodic change
Volatility Alignment (0-20%): Whether volatility supports the signal
Market Quality (0-20%): Price convergence and path dependency factors
Real-Time Confidence Updates
The Live Confidence metric continuously updates, showing:
- Current opportunity quality
- Market state clarity
- Historical performance influence
- Signal recency boost
- Visual Intelligence System
Adaptive Ergodic Field Bands
Dynamic bands that expand and contract based on market state:
Primary Color: Ergodic state (mean-reverting)
Danger Color: Non-ergodic state (trending)
Band Width: Expected price movement range
Squeeze Indicators: Volatility compression warnings
Quantum Wave Ribbons
Triple EMA system (8, 21, 55) revealing market flow:
Compressed Ribbons: Consolidation imminent
Expanding Ribbons: Directional move developing
Color Coding: Matches current ergodic state
Phase Transition Signals
Clear entry/exit markers at regime changes:
Bull Signals: Ergodic restoration (mean reversion opportunity)
Bear Signals: Ergodic break (trend following opportunity)
Confidence Labels: Percentage showing signal quality
Visual Intensity: Stronger signals = deeper colors
Professional Dashboard Suite
Main Analytics Panel (Top Right)
Market State Monitor
- Current regime (Ergodic/Non-Ergodic)
- Ergodic score with threshold
- Path dependency strength
- Quantum coherence percentage
Divergence Metrics
- Price divergence with severity
- Volatility regime classification
- Strategy mode recommendation
- Signal strength indicator
Live Intelligence
- Real-time confidence score
- Color-coded risk levels
- Dynamic strategy suggestions
Performance Tracking (Left Panel)
Signal Analytics
- Total historical signals
- Win rate with W/L breakdown
- Current streak tracking
- Closed trade counter
Regime Analysis
- Current market behavior
- Bars since last signal
- Recommended actions
- Average confidence trends
Strategy Command Center (Bottom Right)
Adaptive Recommendations
- Active strategy mode
- Primary approach (mean reversion/momentum)
- Suggested indicators ("weapons")
- Entry/exit methodology
- Risk management guidance
- Comprehensive Input Guide
Core Algorithm Parameters
Analysis Period (10-100 bars)
Scalping (10-15): Ultra-responsive, more signals, higher noise
Day Trading (20-30): Balanced sensitivity and stability
Swing Trading (40-100): Smooth signals, major moves only Default: 20 - optimal for most timeframes
Divergence Threshold (0.5-5.0)
Hair Trigger (0.5-1.0): Catches every wiggle, many false signals
Balanced (1.5-2.5): Good signal-to-noise ratio
Conservative (3.0-5.0): Only extreme divergences Default: 1.5 - best risk/reward balance
Path Memory (20-200 bars)
Short Memory (20-50): Recent behavior focus, quick adaptation
Medium Memory (50-100): Balanced historical context
Long Memory (100-200): Emphasizes established patterns Default: 50 - captures sufficient history without lag
Signal Spacing (5-50 bars)
Aggressive (5-10): Allows rapid-fire signals
Normal (15-25): Prevents clustering, maintains flow
Conservative (30-50): Major setups only Default: 15 - optimal trade frequency
Ensemble Configuration
Select markets for consensus analysis:
SPY: Broad market sentiment
QQQ: Technology leadership
IWM: Small-cap risk appetite
DIA: Blue-chip stability
More instruments = stronger consensus but potentially diluted signals
Visual Customization
Color Themes (6 professional options):
Quantum: Cyan/Pink - Modern trading aesthetic
Matrix: Green/Red - Classic terminal look
Heat: Blue/Red - Temperature metaphor
Neon: Cyan/Magenta - High contrast
Ocean: Turquoise/Coral - Calming palette
Sunset: Red-orange/Teal - Warm gradients
Display Controls:
- Toggle each visual component
- Adjust transparency levels
- Scale dashboard text
- Show/hide confidence scores
- Trading Strategies by Market State
- Ergodic State Strategy (Primary Color Bands)
Market Characteristics
- Price oscillates predictably
- Support/resistance hold
- Volume patterns repeat
- Mean reversion dominates
Optimal Approach
Entry: Fade moves at band extremes
Target: Middle band (equilibrium)
Stop: Just beyond outer bands
Size: Full confidence-based position
Recommended Tools
- RSI for oversold/overbought
- Bollinger Bands for extremes
- Volume profile for levels
- Non-Ergodic State Strategy (Danger Color Bands)
Market Characteristics
- Price trends persistently
- Levels break decisively
- Volume confirms direction
- Momentum accelerates
Optimal Approach
Entry: Breakout from bands
Target: Trail with expanding bands
Stop: Inside opposite band
Size: Scale in with trend
Recommended Tools
- Moving average alignment
- ADX for trend strength
- MACD for momentum
- Advanced Features Explained
Quantum Coherence Metric
Measures phase alignment between individual and ensemble behavior:
80-100%: Perfect sync - strong mean reversion setup
50-80%: Moderate alignment - mixed signals
0-50%: Decoherence - trending behavior likely
Path Dependency Analysis
Quantifies how much history influences current price:
Low (<30%): Technical patterns reliable
Medium (30-50%): Mixed influences
High (>50%): Fundamental shift occurring
Volatility Regime Classification
Contextualizes current volatility:
Normal: Standard strategies apply
Elevated: Widen stops, reduce size
Extreme: Defensive mode required
Signal Strength Indicator
Real-time opportunity quality:
- Distance from threshold
- Momentum acceleration
- Cross-validation factors
Risk Management Framework
Position Sizing by Confidence
90%+ confidence = 100% position size
70-90% confidence = 75% position size
50-70% confidence = 50% position size
<50% confidence = 25% or skip
Dynamic Stop Placement
Ergodic State: ATR × 1.0 from entry
Non-Ergodic State: ATR × 2.0 from entry
Volatility Adjustment: Multiply by current regime
Multi-Timeframe Alignment
- Check higher timeframe regime
- Confirm ensemble consensus
- Verify volume participation
- Align with major levels
What Makes EMD Unique
Original Contributions
First Ergodic Theory Trading Application: Transforms abstract physics into practical signals
Ensemble Market Analysis: Revolutionary multi-market divergence system
Adaptive Confidence Engine: Institutional-grade signal quality metrics
Quantum Coherence: Novel market alignment measurement
Smart Signal Management: Prevents clustering while maintaining responsiveness
Technical Innovations
Dynamic Threshold Adaptation: Self-adjusting sensitivity
Path Memory Integration: Historical dependency weighting
Stress-Adjusted Scoring: Market condition normalization
Real-Time Performance Tracking: Built-in strategy analytics
Optimization Guidelines
By Timeframe
Scalping (1-5 min)
Period: 10-15
Threshold: 0.5-1.0
Memory: 20-30
Spacing: 5-10
Day Trading (5-60 min)
Period: 20-30
Threshold: 1.5-2.5
Memory: 40-60
Spacing: 15-20
Swing Trading (1H-1D)
Period: 40-60
Threshold: 2.0-3.0
Memory: 80-120
Spacing: 25-35
Position Trading (1D-1W)
Period: 60-100
Threshold: 3.0-5.0
Memory: 100-200
Spacing: 40-50
By Market Condition
Trending Markets
- Increase threshold
- Extend memory
- Focus on breaks
Ranging Markets
- Decrease threshold
- Shorten memory
- Focus on restores
Volatile Markets
- Increase spacing
- Raise confidence requirement
- Reduce position size
- Integration with Other Analysis
- Complementary Indicators
For Ergodic States
- RSI divergences
- Bollinger Band squeezes
- Volume profile nodes
- Support/resistance levels
For Non-Ergodic States
- Moving average ribbons
- Trend strength indicators
- Momentum oscillators
- Breakout patterns
- Fundamental Alignment
- Check economic calendar
- Monitor sector rotation
- Consider market themes
- Evaluate risk sentiment
Troubleshooting Guide
Too Many Signals:
- Increase threshold
- Extend signal spacing
- Raise confidence minimum
Missing Opportunities
- Decrease threshold
- Reduce signal spacing
- Check ensemble settings
Poor Win Rate
- Verify timeframe alignment
- Confirm volume participation
- Review risk management
Disclaimer
This indicator is for educational and informational purposes only. It does not constitute financial advice. Trading involves substantial risk of loss and is not suitable for all investors. Past performance does not guarantee future results.
The ergodic framework provides unique market insights but cannot predict future price movements with certainty. Always use proper risk management, conduct your own analysis, and never risk more than you can afford to lose.
This tool should complement, not replace, comprehensive trading strategies and sound judgment. Markets remain inherently unpredictable despite advanced analysis techniques.
Transform market chaos into trading clarity with Ergodic Market Divergence.
Created with passion for the TradingView community
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
SuperTrend Confluence Signals [AlgoAlpha]OVERVIEW
This script enhances the classic SuperTrend indicator by integrating volume dynamics, retracement detection, and a multi-asset trend matrix—alongside an automatic mitigation-level drawing system. It's designed for traders who want to see not just trend direction, but the confluence of trend strength, volatility-adjusted retracements, and capital flow through volume pressure. It visually maps key transitions in market structure while offering a clean, color-coded overview of multiple symbols and timeframes in a single chart.
CONCEPTS
At the core is the traditional SuperTrend , which determines directional bias using Average True Range (ATR) with a volatility multiplier. This script overlays that with a dynamic volume histogram that scales relative to recent volume standard deviation, coloring volume bursts within the trend. Retracement signals are triggered when price pulls back toward the SuperTrend level but respects it—quantified through normalized distance sensitivity. On top of that, the indicator automatically draws and manages horizontal support/resistance zones that appear at key trend shifts. These levels persist and are cleared based on configurable rules such as wick/body sweeps or consecutive candle closes. A multi-asset, multi-timeframe table then gives an instant snapshot of trend status across five user-defined symbols and timeframes.
FEATURES
SuperTrend : Configurable ATR length and multiplier for flexible trend sensitivity.
Volumetric Histogram : Gradient-filled candles anchored to SuperTrend bands, scaled by relative volume to indicate activity intensity during trends.
Retracement Arrows : Signals printed when price nears the SuperTrend level without breaking it, allowing identification of high-probability continuation zones.
Volume TP Markers : Diamond markers flag high-volume events, contextualizing price moves with liquidity bursts.
Automatic Structure Levels : Draws clean horizontal lines at significant trend transitions, with optional volatility-based band fills. These levels self-update and clear based on price interaction logic.
Trend Table : Displays trend direction (▲/▼) across five assets and five timeframes. Each cell is colored according to trend bias, providing a compact overview for multi-market confluence.
USAGE
Start by loading the indicator on your main chart and adjusting the ATR Length and Multiplier to match your strategy timeframe. Use lower values for scalping and higher values for swing trading. The histogram bars will appear as colored candles above or below the SuperTrend level, indicating how strong volume is within that trend. Arrow signals suggest minor pullbacks within the trend, which can act as entry opportunities. The level system will automatically plot key price zones during trend flips; if "Body" is selected for mitigation, price must close through the level to invalidate it. If "Wick" is chosen, a single wick breach is enough. Adjust expiry and rejection settings to fine-tune how long levels stay on chart. Finally, enable the Multi-Asset Table to view live trend signals across popular symbols like AAPL or NVDA in different timeframes, helping spot macro-to-micro alignment for higher-confidence trades.
Quantum State Superposition Indicator (QSSI)Quantum State Superposition Indicator (QSSI) - Where Physics Meets Finance
The Quantum Revolution in Market Analysis
After months of research into quantum mechanics and its applications to financial markets, I'm thrilled to present the Quantum State Superposition Indicator (QSSI) - a groundbreaking approach that models price action through the lens of quantum physics. This isn't just another technical indicator; it's a paradigm shift in how we understand market behavior.
The Theoretical Foundation
Quantum Superposition in Markets
In quantum mechanics, particles exist in multiple states simultaneously until observed. Similarly, markets exist in a superposition of potential states (bullish, bearish, neutral) until a significant volume event "collapses" the wave function into a definitive direction.
The mathematical framework:
Wave Function (Ψ): Represents the market's quantum state as a weighted sum of all possible states:
Ψ = Σ(αᵢ × Sᵢ)
Where αᵢ are probability amplitudes and Sᵢ are individual quantum states.
Probability Amplitudes: Calculated using the Born rule, normalized so Σ|αᵢ|² = 1
Observation Operator: Volume/Average Volume ratio determines observation strength
The Five Quantum States
Momentum State: Short-term price velocity (EMA of returns)
Mean Reversion State: Deviation from equilibrium (normalized z-score)
Volatility Expansion State: ATR relative to historical average
Trend Continuation State: Long-term price positioning
Chaos State: Volatility of volatility (market uncertainty)
Each state contributes to the overall wave function based on current market conditions.
Wave Function Collapse
When volume exceeds the observation threshold (default 1.5x average), the wave function "collapses," committing the market to a direction. This models how institutional volume forces markets out of uncertainty into trending states.
Collapse Detection Formula:
Collapse = Volume > (Threshold × Average Volume)
Direction = Sign(Ψ) at collapse moment
Advanced Quantum Concepts
Heisenberg Uncertainty Principle
The indicator calculates market uncertainty as the product of price and momentum
uncertainties:
ΔP × ΔM = ℏ (market uncertainty constant)
This manifests as dynamic uncertainty bands that widen during unstable periods.
Quantum Tunneling
Calculates the probability of price "tunneling" through resistance/support barriers:
P(tunnel) = e^(-2×|barrier_height|×√coherence_length)
Unlike classical technical analysis, this gives probability of breakouts before they occur.
Entanglement
Measures the quantum correlation between price and volume:
Entanglement = |Correlation(Price, Volume, lookback)|
High entanglement suggests coordinated institutional activity.
Decoherence
When market states lose quantum properties and behave classically:
Decoherence = 1 - Σ(amplitude²)
Indicates trend emergence from quantum uncertainty.
Visual Innovation
Probability Clouds
Three-tier probability distributions visualize market uncertainty:
Inner Cloud (68%): One standard deviation - most likely price range
Middle Cloud (95%): Two standard deviations - probable extremes
Outer Cloud (99.7%): Three standard deviations - tail risk zones
Cloud width directly represents market uncertainty - wider clouds signal higher entropy states.
Quantum State Visualization
Colored dots represent individual quantum states:
Green: Momentum state strength
Red: Mean reversion state strength
Yellow: Volatility state strength
Dot brightness indicates amplitude (influence) of each state.
Collapse Events
Aqua Diamonds (Above): Bullish collapse - upward commitment
Pink Diamonds (Below): Bearish collapse - downward commitment
These mark precise moments when markets exit superposition.
Implementation Details
Core Calculations
Feature Extraction: Normalize price returns, volume ratios, and volatility measures
State Calculation: Compute each quantum state's value
Amplitude Assignment: Weight states by market conditions and observation strength
Wave Function: Sum weighted states for final market quantum state
Visualization: Transform quantum values to price space for display
Performance Optimization
- Efficient array operations for state calculations
- Single-pass normalization algorithms
- Optimized correlation calculations for entanglement
- Smart label management to prevent visual clutter
Trading Applications:
Signal Generation
Bullish Signals:
- Positive wave function during collapse
- High tunneling probability at support
- Coherent market state with bullish bias
Bearish Signals:
- Negative wave function during collapse
- High tunneling probability at resistance
- Decoherent state transitioning bearish
Risk Management
Uncertainty-Based Position Sizing:
Narrow clouds: Normal position size
Wide clouds: Reduced position size
Extreme uncertainty: Stay flat
Quantum Stop Losses:
- Place stops outside probability clouds
- Adjust for Heisenberg uncertainty
- Respect quantum tunneling levels
Market Regime Recognition
Quantum Coherent (Superposed):
- Market in multiple states
- Avoid directional trades
- Prepare for collapse
Quantum Decoherent (Classical):
-Clear trend emergence
- Follow directional signals
- Traditional analysis applies
Advanced Features
Adaptive Dashboards
Quantum State Panel: Real-time wave function, dominant state, and coherence status
Performance Metrics: Win rate, signal frequency, and regime analysis
Information Guide: Comprehensive explanation of all quantum concepts
- All dashboards feature adjustable sizing for different screen resolutions.
Multi-Timeframe Quantum Analysis
The indicator adapts to any timeframe:
Scalping (1-5m): Short coherence length, sensitive thresholds
Day Trading (15m-1H): Balanced parameters
Swing Trading (4H-1D): Long coherence, stable states
Alert System
Sophisticated alerts for:
- Wave function collapse events
- Decoherence transitions
- High tunneling probability
- Strong entanglement detection
Originality & Innovation
This indicator introduces several firsts:
Quantum Superposition: First to model markets as quantum systems
Wave Function Collapse: Original volume-triggered state commitment
Tunneling Probability: Novel breakout prediction method
Entanglement Metrics: Unique price-volume quantum correlation
Probability Clouds: Revolutionary uncertainty visualization
Development Journey
Creating QSSI required:
- Deep study of quantum mechanics principles
- Translation of physics equations to market context
- Extensive backtesting across multiple markets
- UI/UX optimization for trader accessibility
- Performance optimization for real-time calculation
- The result bridges cutting-edge physics with practical trading.
Best Practices
Parameter Optimization
Quantum States (2-5):
- 2-3 for simple markets (forex majors)
- 4-5 for complex markets (indices, crypto)
Coherence Length (10-50):
- Lower for fast markets
- Higher for stable markets
Observation Threshold (1.0-3.0):
- Lower for active markets
- Higher for thin markets
Signal Confirmation
Always confirm quantum signals with:
- Market structure (support/resistance)
- Volume patterns
- Correlated assets
- Fundamental context
Risk Guidelines
- Never risk more than 2% per trade
- Respect probability cloud boundaries
- Exit on decoherence shifts
- Scale with confidence levels
Educational Value
QSSI teaches advanced concepts:
- Quantum mechanics applications
- Probability theory
- Non-linear dynamics
- Risk management
- Market microstructure
Perfect for traders seeking deeper market understanding.
Disclaimer
This indicator is for educational and research purposes only. While quantum mechanics provides a fascinating framework for market analysis, no indicator can predict future prices with certainty. The probabilistic nature of both quantum mechanics and markets means outcomes are inherently uncertain.
Always use proper risk management, conduct thorough analysis, and never risk more than you can afford to lose. Past performance does not guarantee future results.
Conclusion
The Quantum State Superposition Indicator represents a revolutionary approach to market analysis, bringing institutional-grade quantum modeling to retail traders. By viewing markets through the lens of quantum mechanics, we gain unique insights into uncertainty, probability, and state transitions that classical indicators miss.
Whether you're a physicist interested in finance or a trader seeking cutting-edge tools, QSSI opens new dimensions in market analysis.
"The market, like Schrödinger's cat, exists in multiple states until observed through volume."
* As you may have noticed, the past two indicators I've released (Lorentzian Classification and Quantum State Superposition) are designed with strategy implementation in mind. I'm currently developing a stable execution platform that's completely unique and moves away from traditional ATR-based position sizing and stop loss systems. I've found ATR-based approaches to be unreliable in volatile markets and regime transitions - they often lag behind actual market conditions and can lead to premature exits or oversized positions during volatility spikes.
The goal is to create something that adapts to market conditions in real-time using the quantum and relativistic principles we've been exploring. Hopefully I'll have something groundbreaking to share soon. Stay tuned!
Trade with quantum insight. Trade with QSSI .
— Dskyz , for DAFE Trading Systems
ICT TIME ELEMENTS [KaninFX]## Overview
The ICT Time Elements indicator is a comprehensive trading tool designed to visualize the most critical market sessions and timeframes according to Inner Circle Trader (ICT) methodology. This indicator helps traders identify high-probability trading opportunities by highlighting key market sessions, killzones, and liquidity periods throughout the trading day.
## Key Features
### 🕐 Complete ICT Time Framework
- **Asian Range**: 8:00 PM - 12:00 AM (NY Time) - Evening consolidation period
- **London Killzone**: 2:00 AM - 5:00 AM (NY Time) - European market opening liquidity
- **NY Killzone**: 7:00 AM - 10:00 AM (NY Time) - US market opening with high volatility
- **Silver Bullet Sessions**:
- London Silver Bullet: 3:00 AM - 4:00 AM
- AM Silver Bullet: 10:00 AM - 11:00 AM
- PM Silver Bullet: 2:00 PM - 3:00 PM
- **Lunch Hours**: 5:00 AM - 7:00 AM & 12:00 PM - 1:00 PM (Lower volatility periods)
- **News Embargo**: 8:30 AM - 9:30 AM (High impact news release window)
- **20-Minute Macros**: :50 to :10 minutes of each hour (Short-term reversal periods)
- **True Day Close**: 4:00 PM - 4:30 PM (Official market close)
### 🎨 Visual Customization
- **Multiple Themes**: Dark, Light, and Custom color schemes
- **Adjustable Opacity**: Control zone transparency (0-100%)
- **Font Customization**: Tiny, Small, Normal, Large text sizes
- **Custom Colors**: Personalize each zone with your preferred colors
- **Professional Display**: Clean histogram visualization with zone labels
### 🌍 Multi-Timezone Support
Built-in support for major trading centers:
- America/New_York (Default)
- America/Chicago
- America/Los_Angeles
- Europe/London
- Asia/Tokyo
- Asia/Shanghai
- Australia/Sydney
### 📊 Smart Information Display
- **Real-time Zone Detection**: Automatically identifies current active session
- **Zone Labels**: Clear labeling at the center of each time period
- **Current Zone Indicator**: Arrow pointer showing the active session
- **Comprehensive Info Table**: Quick reference for all time zones and their schedules
- **Flexible Table Positioning**: Place info table in any corner of your chart
### ⚡ Performance Optimized
- **Memory Management**: Automatic cleanup of old labels to maintain performance
- **Efficient Processing**: Optimized time calculations for smooth operation
- **Resource Control**: Limited label generation to prevent system overload
## How It Works
The indicator continuously monitors the current time against predefined ICT session schedules. When price action enters a recognized time zone, the indicator:
1. **Highlights the Period**: Colors the histogram bar according to the active session
2. **Labels the Zone**: Places descriptive text identifying the current market condition
3. **Updates Info Table**: Shows current session status and complete schedule
4. **Tracks Macro Periods**: Identifies 20-minute reversal windows within major sessions
### Special Features
- **Macro Detection**: Automatically identifies when current time falls within a 20-minute macro period
- **Session Overlap Handling**: Properly manages overlapping time zones with priority logic
- **Dynamic Color Adjustment**: Theme-aware color selection for optimal visibility
## Best Use Cases
### For ICT Traders
- Identify optimal entry times during killzone sessions
- Recognize silver bullet opportunities for quick scalps
- Avoid trading during lunch hour consolidations
- Prepare for news embargo volatility
### For Session Traders
- Track major market session transitions
- Plan trading strategy around high-liquidity periods
- Understand global market flow and timing
### For Swing Traders
- Identify macro trend continuation points
- Time position entries during optimal sessions
- Understand market structure changes across sessions
## Installation & Setup
1. Add the indicator to your TradingView chart
2. Select your preferred timezone from the dropdown
3. Choose theme (Dark/Light) or customize colors
4. Adjust font size and table position to your preference
5. Enable/disable features as needed for your trading style
## Pro Tips
- **Combine with Price Action**: Use time zones alongside support/resistance levels
- **Focus on Killzones**: Highest probability setups occur during London and NY killzones
- **Watch Silver Bullets**: These 1-hour windows often provide excellent reversal opportunities
- **Respect Lunch Hours**: Lower volatility periods - consider smaller position sizes
- **News Embargo Awareness**: Prepare for potential whipsaws during 8:30-9:30 AM
## Conclusion
The ICT Time Elements indicator transforms complex ICT timing concepts into an easy-to-read visual tool. Whether you're a beginner learning ICT methodology or an experienced trader looking to optimize your timing, this indicator provides the essential market session awareness needed for successful trading.
*Compatible with all TradingView plans and timeframes. Works best on 1-minute to 1-hour charts for optimal session visualization.*
Moving Average Candles**Moving Average Candles — MA-Based Smoothed Candlestick Overlay**
This script replaces traditional price candles with smoothed versions calculated using various types of moving averages. Instead of plotting raw price data, each OHLC component (Open, High, Low, Close) is independently smoothed using your selected moving average method.
---
### 📌 Features:
- Choose from 13 MA types: `SMA`, `EMA`, `RMA`, `WMA`, `VWMA`, `HMA`, `T3`, `DEMA`, `TEMA`, `KAMA`, `ZLEMA`, `McGinley`, `EPMA`
- Fully configurable moving average length (1–1000)
- Color-coded candles based on smoothed Open vs Close
- Works directly on price charts as an overlay
---
### 🎯 Use Cases:
- Visualize smoothed market structure more clearly
- Reduce noise in price action for better trend analysis
- Combine with other indicators or strategies for confluence
---
> ⚠️ **Note:** Since all OHLC values are based on moving averages, these candles do **not** represent actual market trades. Use them for trend and structure analysis, not trade entries based on precise levels.
---
*Created to support traders seeking a cleaner visual representation of price dynamics.*
Ehlers Regime Dynamic CandlesCore Calculation Mechanism
The indicator uses advanced Ehlers signal processing techniques to identify market regimes and create dynamically colored candles that reflect market conditions.
Super Smoother Filter: Price data (open, high, low, close) is processed through an Ehlers Super Smoother Filter to reduce market noise while preserving important price movements. This creates a clearer signal for regime detection.
Autocorrelation Analysis: The core of regime detection uses autocorrelation functions at different lag periods:
Primary autocorrelation measures correlation between the current price and its previous value
Trending autocorrelation measures longer-term persistence in the data series
These values combined determine if the market is in a trending or choppy regime
(Image showing Ehlers custom candles vs default candlesticks)
Regime Strength Calculation:
-Raw signal from autocorrelation with user-defined threshold adjustment
-Adaptive scaling based on sensitivity parameter
-Optional volume validation that confirms signal strength using volume data
-Normalization to 0-1 range and smoothing for visual consistency
-Percentile ranking to provide contextually meaningful strength values
Fisher Transform: Applied to the smoothed price to identify statistical extremes, which helps adjust transparency levels during significant price movements.
Key Features & Components
Regime Detection: Identifies trending vs. choppy market conditions using Ehlers' autocorrelation techniques.
Dynamic Candle Coloring: Candles transition smoothly between three color states:
Bullish trending (typically green/teal)
Bearish trending (typically red/purple)
Choppy/neutral (typically blue/silver)
Volume Validation: Optional incorporation of volume data to confirm trend strength (stronger volume during trending periods increases confidence).
Adaptive Transparency: Candles become more opaque during statistically significant price movements based on Fisher Transform values.
Gradient Smoothing: Controls the visual transition between regime states for a more aesthetically pleasing appearance.
Customizable Colors and Style: Full control over all visual aspects including candle body/wick colors and transparency.
Configuration Options
Users can adjust the following parameters in the indicator settings:
Main Settings:
Cycle Length: Controls the lookback period for cycle detection. Lower values increase responsiveness but may introduce noise.
Gradient Smoothness: Determines how quickly colors transition when regime changes.
Trend Detection Threshold: Sets the autocorrelation strength required to classify a trend.
Trend Sensitivity: Scales regime strength calculation to produce a better distribution of values.
Use Volume: Toggles whether volume data is used to validate trend strength.
Color Settings:
Trending Regime Colors: Separate color options for bullish and bearish candle bodies and wicks.
Choppy Regime Colors: Color options for candle bodies and wicks during sideways/neutral markets.
Style Settings:
Candle Border Options: Toggle borders and adjust their color and transparency.
Adaptive Transparency: Enable/disable dynamic transparency based on statistical significance.
Base Transparency: Set the baseline transparency level for all candles.
Interpretation Notes
Color Transitions: As the market shifts between regimes, candle colors gradually transition, providing visual cues about market structure changes.
Regime Strength: The intensity of colors indicates the strength of the detected regime:
Strong trending regimes show vibrant trending colors
Weak or mixed regimes display colors closer to the choppy/neutral color
Transitions between regimes show gradient colors
Transparency Changes: More opaque candles indicate statistically significant price movements, while more transparent candles suggest routine or less significant price action.
Volume Interaction: When volume validation is enabled, trending colors become more pronounced during high volume trends and subdued during low volume periods.
Disclaimer: These are custom candles that are significantly different from normal candlesticks.
Unlike traditional candlesticks that display raw price data, these candles:
• Use Ehlers signal processing to filter and smooth price data
• Dynamically change color based on detected market regimes
• Show statistical significance through transparency
• May appear delayed compared to standard candles due to the filtering process
Traditional trading strategies dependent on candlestick patterns will not work with these.
Risk Disclaimer
Trading involves significant risk. This indicator is provided for analytical purposes only and does not constitute financial advice. Past performance is not indicative of future results. Use sound risk management practices and never trade with capital you cannot afford to lose. The Ehlers Regime Dynamic Candles indicator should be used as part of a comprehensive trading approach, not as a standalone trading system.
StupidTrader Money GlitchStupidTrader Money Glitch
This indicator identifies high-probability buy setups by combining key technical concepts. It detects a reclaimed demand zone (a significant low that was broken and reclaimed), confirms bullish market structure breaks (MSB), ensures the price is above the 9 and 21 EMAs, and looks for volume spikes or trends.
Key Features:
Plots a demand zone (blue box) based on a reclaimed low.
Signals long entries (green triangles) when conditions align: reclaimed demand zone, MSB, price above EMAs, and volume confirmation.
Includes EMA 9 (blue) and EMA 21 (aqua) for trend confirmation.
How to Use:
Add the indicator to your chart and look for green triangles below candles as buy signals. Ensure the price interacts with the demand zone, breaks market structure, and shows volume confirmation. Works best on daily or higher timeframes for assets like ONDO, BTC, and more.
Settings:
Short EMA Length: 9
Mid EMA Length: 21
Pivot Lookback for Demand Zone: 5
Zone Lookback for Demand: 90
Volume Lookback: 20
Smart Market Matrix Smart Market Matrix
This indicator is designed for intraday, scalping, providing automated detection of price pivots, liquidity traps, and breakout confirmations, along with a context dashboard featuring volatility, trend, and volume.
## Summary Description
### Menu Settings & Their Roles
- **Swing Pivot Strength**: Controls the sensitivity for detecting High/Low pivots.
- **Show Pivot Points**: Toggles the display of HH/LL markers on the chart.
- **VWMA Length for Trap Volume** & **Volume Spike Multiplier**: Identify concentrated volume spikes for liquidity traps.
- **Wick Ratio Threshold** & **Max Body Size Ratio**: Detect candles with disproportionate wicks and small bodies (doji-ish) for traps.
- **ATR Length for Trap**: Measures volatility specific to trap detection.
- **VWMA Length for Breakout Volume**, **ATR Multiplier for Breakout**, **ATR Length for Breakout**, **Min Body/Range Ratio**: Set adaptive breakout thresholds based on volatility and volume.
- **OBV Smooth Length**: Smooths OBV momentum for breakout confirmation.
- **Enable VWAP Filter for Confirmations**: Optionally validate breakouts against the VWAP.
- **Enable Higher-TF Trend Filter** & **Trend Filter Timeframe**: Align breakout signals with the 1h/4h/Daily trend.
- **ADX Length**, **EMA Fast/Slow Length for Context**: Parameters for the context dashboard (Volatility, Trend, Volume).
- **Show Intraday VWAP Line**, **VWAP Line Color/Width**: Display the intraday VWAP line with custom style.
### Signal Interpretation Map
| Signal | Description | Recommended Action |
|--------------------------------|-----------------------------------------------------------|-------------------------------------------|
| 📌 **HH / LL (pivot)** | Market structure (support/resistance) | Note key levels |
| **Bull Trap(green diamond)** | Sweep down + volume spike + wick + rejection | Go long with trend filter
| **Bear Trap(red diamond)** | Sweep up + volume spike + wick + rejection | Go short with trend filter
| 🔵⬆️ **Breakout Confirmed Up** | Close > ATR‑scaled high + volume + OBV↑ | Go long with trend filter |
| 🔵⬇️ **Breakout Confirmed Down** | Close < ATR‑scaled low + volume + OBV↓ | Go short with trend filter |
| 📊 **VWAP Line** | Intraday reference to guide price | Use as dynamic support/resistance |
| ⚡ **Volatility** | ATR ratio High/Med/Low | Adjust position size |
| 📈 **Trend Context** | ADX+EMA Strong/Moderate/Weak | Confirm trend direction |
| 🔍 **Volume Context** | Breakout / Rising / Falling / Calm | Check volume momentum |
*This summary gives you a quick overview of the key settings and how to interpret signals for efficient intraday scalping.*
### Suggested Settings
- **Intraday Scalping (5m–15m)**
- `Swing Pivot Strength = 5`
- `VWMA Length for Trap Volume = 10`, `Volume Spike Multiplier = 1.6`
- `ATR Length for Trap = 7`
- `VWMA Length for Breakout Volume = 12`, `ATR Length for Breakout = 9`, `ATR Multiplier for Breakout = 0.5`
- `Min Body/Range Ratio for Breakout = 0.5`, `OBV Smooth Length = 7`
- `Enable Higher-TF Trend Filter = true` (TF = 60)
- `Show Intraday VWAP Line = true` (Color = orange, Width = 2)
- **Swing Trading (4h–Daily)**
- `Swing Pivot Strength = 10`
- `VWMA Length for Trap Volume = 20`, `Volume Spike Multiplier = 2.0`
- `ATR Length for Trap = 14`
- `VWMA Length for Breakout Volume = 30`, `ATR Length for Breakout = 14`, `ATR Multiplier for Breakout = 0.8`
- `Min Body/Range Ratio for Breakout = 0.7`, `OBV Smooth Length = 14`
- `Enable Higher-TF Trend Filter = true` (TF = D)
- `Show Intraday VWAP Line = false`
*Adjust these values based on the symbol and market volatility for optimal performance.*
EMA Trend Pro: Dynamic Clouds & ColorsEMA Trend Pro is your ultimate trend companion, built for traders who want clarity, precision, and confidence in their entries.
This script fuses dynamic EMA cloud zones with breakout and pullback signals — giving you real-time insights into market structure and momentum. Whether you're trading crypto, forex, stocks, or futures, EMA Trend Pro adapts to your style.
🔧 Key Features:
✅ EMA Stack Clouds with Folding Sensitivity (9/21/48/200)
✅ Bullish / Bearish trend labels with real-time dashboard
✅ Volume strength analysis (High, Normal, Low)
✅ Breakout signal alerts (momentum-based)
✅ Pullback signal alerts (trend resumption)
✅ Fully customizable: EMA lengths, signal visibility, cloud opacity
✅ Works across all assets and timeframes
🛠️ Designed for scalping, swing trading, and intraday setups.
🔔 Built-in alerts make automation seamless — no guesswork.
💡 Usage Tips:
Use clouds and trend labels to identify structure and bias
Trade breakouts when EMAs align and volume confirms
Look for pullbacks into the EMA zone and enter on resumption
📅 Market Hours Filter: Keeps signals relevant during core trading hours (9:30 AM–4 PM ET).
👤 Developed by @glapougbaegarmondeh
🧠 Version 1.0 | 📆 Released: April 24, 2025
Trend Matrix Multi-Timeframe Dashboard(TechnoBlooms)Trend Matrix Multi-Timeframe Dashboard is a Minimalist Multi-Timeframe Trend Analyzer with Smart Indicator Integration. Trend Matrix MTF Dashboard is a clean, efficient, and visually intuitive trend analyzer built for traders who value simplicity without compromising on technical depth.
This dashboard empowers you to track trend direction across multiple timeframes using a curated set of powerful technical indicators—all from one compact visual panel. The design philosophy is simple: eliminate clutter, highlight trend clarity, and accelerate your decision-making process.
Key Features
✅ Minimalist Design with Maximum Insight
A compact dashboard view designed for clean charts and focused trading
Optimized layout shows everything you need—nothing you don’t
✅ Multi-Timeframe Access at a Glance
Instantly read the trend direction of selected indicators on multiple timeframes (e.g., 15m, 1h, 4h, 1D)
Customize the timeframe stack to fit scalping, intraday, swing, or positional strategies
✅ Robust Technical Indicators Built In
Each one is hand-picked for trend reliability:
MACD – Momentum and crossover confirmation
RSI – Overbought/oversold and directional shift
EMA – Dynamic support/resistance and trend bias
Bollinger Bands – Volatility structure and trend containment
PVT – Volume-Weighted Trend Confirmation
Supertrend – Price-following trend tracker
✅ Live Updates & Lightweight Performance
Built to update efficiently on every bar close
Minimal performance impact even with multiple timeframes active
By offering multi-timeframe (MTF) access to proven trend-following indicators, Trend Matrix helps you confidently align with the market’s dominant direction—without jumping between charts or analyzing indicators one by one.
This indicator offers customizable settings. The trader can choose the input parameters timeframes as per the choice.
Trend Matrix Multi-Timeframe Dashboard helps traders to identify trend based on technical indications. Trader can refer this while taking trading decisions.
🧠 Ideal For
Scalpers who need higher timeframe confirmation
Swing traders identifying clean entries aligned with the macro trend
Trend followers seeking clarity before committing capital
Price action & SMC traders validating market structure setups
Beginners who want a high-level trend guide without messy indicators
Trading Sessions [BigBeluga]
This indicator brings Smart Money Concept (ICT) session logic to life by plotting key global trading sessions with volume and delta analytics. It not only highlights session ranges but also tracks their midpoints — which often act as intraday support/resistance levels.
🔵 KEY FEATURES
Visual session boxes: Plots boxes for Tokyo, London, New York, and Sydney sessions based on user-defined UTC+0 time ranges.
Volume & delta metrics: Displays total volume and delta volume (buy–sell difference) within each session.
Mid, High & Low Range Extension: Once a session ends, the high, low, and midpoint levels automatically extend — ideal for detecting SR zones.
Session labels: Each box includes a label with session name, time, volume, and delta for quick reference.
Custom session control: Enable or disable sessions individually and configure start/end times.
Clean aesthetics: Transparent shaded boxes with subtle borders make it easy to overlay without clutter.
Sessions Dashboard: Shows the time range of each session and tells you whether the session is currently active.
🔵 USAGE
Enable the sessions you want to monitor (e.g., New York or Tokyo) from the settings.
Use session volume and delta values to gauge the strength and direction of institutional activity.
Watch for price interaction with the extended range — it often acts as dynamic support/resistance after the session ends.
Overlay it with liquidity tools or breaker blocks for intraday strategy alignment.
🔵 EXAMPLES
Extended Future Range acted as resistance/support.
Delta value helped confirm bullish pressure during New York open.
Multiple sessions helped identify kill zone overlaps and high-volume turns.
Trading Sessions is more than just a visual scheduler — it's a precision tool for traders who align with session-based volume dynamics and ICT methodology. Use it to define high-probability zones, confirm volume shifts, and read deeper into the true intent behind market structure.
Machine Learning RSI ║ BullVisionOverview:
Introducing the Machine Learning RSI with KNN Adaptation – a cutting-edge momentum indicator that blends the classic Relative Strength Index (RSI) with machine learning principles. By leveraging K-Nearest Neighbors (KNN), this indicator aims at identifying historical patterns that resemble current market behavior and uses this context to refine RSI readings with enhanced sensitivity and responsiveness.
Unlike traditional RSI models, which treat every market environment the same, this version adapts in real-time based on how similar past conditions evolved, offering an analytical edge without relying on predictive assumptions.
Key Features:
🔁 KNN-Based RSI Refinement
This indicator uses a machine learning algorithm (K-Nearest Neighbors) to compare current RSI and price action characteristics to similar historical conditions. The resulting RSI is weighted accordingly, producing a dynamically adjusted value that reflects historical context.
📈 Multi-Feature Similarity Analysis
Pattern similarity is calculated using up to five customizable features:
RSI level
RSI momentum
Volatility
Linear regression slope
Price momentum
Users can adjust how many features are used to tailor the behavior of the KNN logic.
🧠 Machine Learning Weight Control
The influence of the machine learning model on the final RSI output can be fine-tuned using a simple slider. This lets you blend traditional RSI and machine learning-enhanced RSI to suit your preferred level of adaptation.
🎛️ Adaptive Filtering
Additional smoothing options (Kalman Filter, ALMA, Double EMA) can be applied to the RSI, offering better visual clarity and helping to reduce noise in high-frequency environments.
🎨 Visual & Accessibility Settings
Custom color palettes, including support for color vision deficiencies, ensure that trend coloring remains readable for all users. A built-in neon mode adds high-contrast visuals to improve RSI visibility across dark or light themes.
How It Works:
Similarity Matching with KNN:
At each candle, the current RSI and optional market characteristics are compared to historical bars using a KNN search. The algorithm selects the closest matches and averages their RSI values, weighted by similarity. The more similar the pattern, the greater its influence.
Feature-Based Weighting:
Similarity is determined using normalized values of the selected features, which gives a more refined result than RSI alone. You can choose to use only 1 (RSI) or up to all 5 features for deeper analysis.
Filtering & Blending:
After the machine learning-enhanced RSI is calculated, it can be optionally smoothed using advanced filters to suppress short-term noise or sharp spikes. This makes it easier to evaluate RSI signals in different volatility regimes.
Parameters Explained:
📊 RSI Settings:
Set the base RSI length and select your preferred smoothing method from 10+ moving average types (e.g., EMA, ALMA, TEMA).
🧠 Machine Learning Controls:
Enable or disable the KNN engine
Select how many nearest neighbors to compare (K)
Choose the number of features used in similarity detection
Control how much the machine learning engine affects the RSI calculation
🔍 Filtering Options:
Enable one of several advanced smoothing techniques (Kalman Filter, ALMA, Double EMA) to adjust the indicator’s reactivity and stability.
📏 Threshold Levels:
Define static overbought/oversold boundaries or reference dynamically adjusted thresholds based on historical context identified by the KNN algorithm.
🎨 Visual Enhancements:
Select between trend-following or impulse coloring styles. Customize color palettes to accommodate different types of color blindness. Enable neon-style effects for visual clarity.
Use Cases:
Swing & Trend Traders
Can use the indicator to explore how current RSI readings compare to similar market phases, helping to assess trend strength or potential turning points.
Intraday Traders
Benefit from adjustable filters and fast-reacting smoothing to reduce noise in shorter timeframes while retaining contextual relevance.
Discretionary Analysts
Use the adaptive OB/OS thresholds and visual cues to supplement broader confluence zones or market structure analysis.
Customization Tips:
Higher Volatility Periods: Use more neighbors and enable filtering to reduce noise.
Lower Volatility Markets: Use fewer features and disable filtering for quicker RSI adaptation.
Deeper Contextual Analysis: Increase KNN lookback and raise the feature count to refine pattern recognition.
Accessibility Needs: Switch to Deuteranopia or Monochrome mode for clearer visuals in specific color vision conditions.
Final Thoughts:
The Machine Learning RSI combines familiar momentum logic with statistical context derived from historical similarity analysis. It does not attempt to predict price action but rather contextualizes RSI behavior with added nuance. This makes it a valuable tool for those looking to elevate traditional RSI workflows with adaptive, research-driven enhancements.
Heiken Ashi Supertrend ADXHeiken Ashi Supertrend ADX Indicator
Overview
This indicator combines the power of Heiken Ashi candles, Supertrend indicator, and ADX filter to identify strong trend movements across multiple timeframes. Designed primarily for the cryptocurrency market but adaptable to any tradable asset, this system focuses on capturing momentum in established trends while employing a sophisticated triple-layer stop loss mechanism to protect capital and secure profits.
Strategy Mechanics
Entry Signals
The strategy uses a unique blend of technical signals to identify high-probability trade entries:
Heiken Ashi Candles: Looks specifically for Heiken Ashi candles with minimal or no wicks, which signal strong momentum and trend continuation. These "full-bodied" candles represent periods where price moved decisively in one direction with minimal retracement. These are overlayed onto normal candes for more accuarte signalling and plotting
Supertrend Filter: Confirms the underlying trend direction using the Supertrend indicator (default factor: 3.0, ATR period: 10). Entries are aligned with the prevailing Supertrend direction.
ADX Filter (Optional) : Can be enabled to focus only on stronger trending conditions, filtering out choppy or ranging markets. When enabled, trades only trigger when ADX is above the specified threshold (default: 25).
Exit Signals
Positions are closed when either:
An opposing signal appears (Heiken Ashi candle with no wick in the opposite direction)
Any of the three stop loss mechanisms are triggered
Triple-Layer Stop Loss System
The strategy employs a sophisticated three-tier stop loss approach:
ATR Trailing Stop: Adapts to market volatility and locks in profits as the trend extends. This stop moves in the direction of the trade, capturing profit without exiting too early during normal price fluctuations.
Swing Point Stop: Uses natural market structure (recent highs/lows over a lookback period) to place stops at logical support/resistance levels, honoring the market's own rhythm.
Insurance Stop: A percentage-based safety net that protects against sudden adverse moves immediately after entry. This is particularly valuable when the swing point stop might be positioned too far from entry, providing immediate capital protection.
Optimization Features
Customizable Filters : All components (Supertrend, ADX) can be enabled/disabled to adapt to different market conditions
Adjustable Parameters : Fine-tune ATR periods, Supertrend factors, and ADX thresholds
Flexible Stop Loss Settings : Each of the three stop loss mechanisms can be individually enabled/disabled with customizable parameters
Best Practices for Implementation
[Recommended Timeframes : Works best on 4-hour charts and above, where trends develop more reliably
Market Conditions: Performs well across various market conditions due to the ADX filter's ability to identify meaningful trends
Performance Characteristics
When properly optimized, this has demonstrated profit factors exceeding 3 in backtesting. The approach typically produces generous winners while limiting losses through its multi-layered stop loss system. The ATR trailing stop is particularly effective at capturing extended trends, while the insurance stop provides immediate protection against adverse moves.
The visual components on the chart make it easy to follow the strategy's logic, with position status, entry prices, and current stop levels clearly displayed.
This indicator represents a complete trading system with clearly defined entry and exit rules, adaptive stop loss mechanisms, and built-in risk management through position sizing.
Heiken Ashi Supertrend ADX - StrategyHeiken Ashi Supertrend ADX Strategy
Overview
This strategy combines the power of Heiken Ashi candles, Supertrend indicator, and ADX filter to identify strong trend movements across multiple timeframes. Designed primarily for the cryptocurrency market but adaptable to any tradable asset, this system focuses on capturing momentum in established trends while employing a sophisticated triple-layer stop loss mechanism to protect capital and secure profits.
Strategy Mechanics
Entry Signals
The strategy uses a unique blend of technical signals to identify high-probability trade entries:
Heiken Ashi Candles: Looks specifically for Heiken Ashi candles with minimal or no wicks, which signal strong momentum and trend continuation. These "full-bodied" candles represent periods where price moved decisively in one direction with minimal retracement.
Supertrend Filter : Confirms the underlying trend direction using the Supertrend indicator (default factor: 3.0, ATR period: 10). Entries are aligned with the prevailing Supertrend direction.
ADX Filter (Optional) : Can be enabled to focus only on stronger trending conditions, filtering out choppy or ranging markets. When enabled, trades only trigger when ADX is above the specified threshold (default: 25).
Exit Signals
Positions are closed when either:
An opposing signal appears (Heiken Ashi candle with no wick in the opposite direction)
Any of the three stop loss mechanisms are triggered
Triple-Layer Stop Loss System
The strategy employs a sophisticated three-tier stop loss approach:
ATR Trailing Stop: Adapts to market volatility and locks in profits as the trend extends. This stop moves in the direction of the trade, capturing profit without exiting too early during normal price fluctuations.
Swing Point Stop : Uses natural market structure (recent highs/lows over a lookback period) to place stops at logical support/resistance levels, honoring the market's own rhythm.
Insurance Stop: A percentage-based safety net that protects against sudden adverse moves immediately after entry. This is particularly valuable when the swing point stop might be positioned too far from entry, providing immediate capital protection.
Optimization Features
Customizable Filters: All components (Supertrend, ADX) can be enabled/disabled to adapt to different market conditions
Adjustable Parameters: Fine-tune ATR periods, Supertrend factors, and ADX thresholds
Flexible Stop Loss Settings: Each of the three stop loss mechanisms can be individually enabled/disabled with customizable parameters
Best Practices for Implementation
Recommended Timeframes: Works best on 4-hour charts and above, where trends develop more reliably
Market Conditions: Performs well across various market conditions due to the ADX filter's ability to identify meaningful trends
Position Sizing: The strategy uses a percentage of equity approach (default: 3%) for position sizing
Performance Characteristics
When properly optimized, this strategy has demonstrated profit factors exceeding 3 in backtesting. The approach typically produces generous winners while limiting losses through its multi-layered stop loss system. The ATR trailing stop is particularly effective at capturing extended trends, while the insurance stop provides immediate protection against adverse moves.
The visual components on the chart make it easy to follow the strategy's logic, with position status, entry prices, and current stop levels clearly displayed.
This strategy represents a complete trading system with clearly defined entry and exit rules, adaptive stop loss mechanisms, and built-in risk management through position sizing.
SMT Divergence ICT 02 [TradingFinder] Smart Money Technique SMC🔵 Introduction
SMT Divergence (Smart Money Technique Divergence) is a price action-based trading concept that detects discrepancies in market behavior between two assets that are generally expected to move in the same direction. Rooted in ICT (Inner Circle Trader) methodology, this approach helps traders recognize subtle signs of market manipulation or imbalance, often ahead of traditional indicators.
The core idea behind SMT divergence is simple: when two correlated instruments—such as currency pairs, indices, or assets from the same sector—start forming different swing points (highs or lows), this can reveal a lack of confirmation in the trend. Such divergence is often a precursor to a price reversal or pause in momentum.
This technique works effectively across various markets including Forex, stocks, and cryptocurrencies. It’s particularly valuable when used alongside concepts like liquidity sweeps, market structure breaks (MSBs), or order block identification.
In advanced use cases, Sequential SMT helps uncover patterns of alternating divergences across sessions, often signaling engineered liquidity traps before price reacts.
When combined with the Quarterly Theory—which segments market behavior into Accumulation, Manipulation, Distribution, and Continuation/Reversal phases—traders gain insight not only into where divergence happens, but when it's most likely to be significant within the market cycle.
Bullish SMT :
Bullish SMT Divergence occurs when one asset prints a higher low while the correlated asset forms a lower low. This asymmetry often suggests that the downside move is losing strength, hinting at a potential bullish shift.
Bearish SMT :
Bearish SMT Divergence is formed when one asset creates a higher high, while the second asset fails to confirm by printing a lower high. This typically signals weakening bullish pressure and the possibility of a reversal to the downside.
🔵 How to Use
The SMT Divergence indicator is designed to detect imbalances between two positively correlated assets—such as major currency pairs, indices, or commodities. These divergences often indicate early signs of market inefficiency or smart money manipulation and can help traders anticipate trend shifts with higher precision.
Unlike traditional divergence indicators or earlier versions of this script, this upgraded version does not rely solely on consecutive pivot comparisons. Instead, it dynamically scans all available pivots within the chart to identify divergences at any structural level—major or minor—across the price action. This broader detection method increases the reliability and frequency of meaningful SMT signals.
Moreover, when integrated with Sequential SMT logic, the indicator is capable of identifying multiple divergence sequences across sessions. These sequences often signal engineered liquidity traps and can be mapped within the Quarterly Theory framework, allowing traders to pinpoint not just the presence of divergence but also the phase of the market cycle it appears in (Accumulation, Manipulation, Distribution, or Continuation).
🟣 Bullish SMT Divergence
This signal occurs when the primary asset forms a higher low, while the correlated asset forms a lower low. This pattern implies weakening bearish momentum and a potential shift to the upside.
If the correlated asset breaks its previous low but the primary asset does not, this divergence suggests absorption of selling pressure and possible accumulation by smart money—making it a strong bullish signal, especially when aligned with a favorable market phase (e.g., the end of a manipulation phase in Q2).
🟣 Bearish SMT Divergence
This signal occurs when the primary asset creates a higher high, while the correlated asset forms a lower high. This mismatch indicates fading bullish momentum and a potential reversal to the downside.
If the correlated asset fails to confirm a breakout made by the main asset, the divergence may point to distribution or exhaustion. When seen within Q3 or Q4 phases of the Quarterly Theory, this pattern often precedes sharp declines or fake-outs engineered by smart money
🔵 Settings
⚙️ Logical Settings
Symbol : Choose the secondary asset to compare with the main chart asset (e.g., XAUUSD, US100, GBPUSD).
Pivot Period : Sets the sensitivity of the pivot detection algorithm. A smaller value increases responsiveness to price swings.
Activate Max Pivot Back : When enabled, limits the maximum number of past pivots to be considered for divergence detection.
Max Pivot Back Length : Defines how many past pivots can be used (if the above toggle is active).
Pivot Sync Threshold : The maximum allowed difference (in bars) between pivots of the two assets for them to be compared.
Validity Pivot Length : Defines the time window (in bars) during which a divergence remains valid before it's considered outdated.
🎨 Display Settings
Show Bullish SMT Line : Draws a line connecting the bullish divergence points.
Show Bullish SMT Label : Displays a label on the chart when a bullish divergence is detected.
Bullish Color : Sets the color for bullish SMT markers (label, shape, and line).
Show Bearish SMT Line : Draws a line for bearish divergence.
Show Bearish SMT Label : Displays a label when a bearish SMT divergence is found.
Bearish Color : Sets the color for bearish SMT visual elements.
🔔 Alert Settings
Alert Name : Custom name for the alert messages (used in TradingView’s alert system).
Message Frequency :
All : Every signal triggers an alert.
Once Per Bar : Alerts once per bar regardless of how many signals occur.
Per Bar Close : Only triggers when the bar closes and the signal still exists.
Time Zone Display : Choose the time zone in which alert timestamps are displayed (e.g., UTC).
Bullish SMT Divergence Alert : Enable/disable alerts specifically for bullish signals.
Bearish SMT Divergence Alert : Enable/disable alerts specifically for bearish signals
🔵Conclusion
The SMT Plus indicator offers a refined and powerful approach to detecting smart money behavior through divergence analysis between correlated assets. By removing the limitations of consecutive pivot comparisons and allowing for broader structural detection, it captures more accurate and timely signals that often precede major market moves.
When paired with frameworks like Sequential SMT and the Quarterly Theory, the indicator not only highlights where divergence occurs, but also when in the market cycle it's most likely to matter. Its flexible settings, customizable visuals, and integrated alert system make it suitable for intraday scalpers, swing traders, and even long-term macro analysts.
Whether you're using it as a standalone decision-making tool or combining it with other ICT concepts, SMT Plus gives you an edge in recognizing manipulation, timing reversals, and staying in sync with the real market narrative—not just the chart.
Uptrick: Z-Score FlowOverview
Uptrick: Z-Score Flow is a technical indicator that integrates trend-sensitive momentum analysi s with mean-reversion logic derived from Z-Score calculations. Its primary objective is to identify market conditions where price has either stretched too far from its mean (overbought or oversold) or sits at a statistically “normal” range, and then cross-reference this observation with trend direction and RSI-based momentum signals. The result is a more contextual approach to trade entry and exit, emphasizing precision, clarity, and adaptability across varying market regimes.
Introduction
Financial instruments frequently transition between trending modes, where price extends strongly in one direction, and ranging modes, where price oscillates around a central value. A simple statistical measure like Z-Score can highlight price extremes by comparing the current price against its historical mean and standard deviation. However, such extremes alone can be misleading if the broader market structure is trending forcefully. Uptrick: Z-Score Flow aims to solve this gap by combining Z-Score with an exponential moving average (EMA) trend filter and a smoothed RSI momentum check, thus filtering out signals that contradict the prevailing market environment.
Purpose
The purpose of this script is to help traders pinpoint both mean-reversion opportunities and trend-based pullbacks in a way that is statistically grounded yet still mindful of overarching price action. By pairing Z-Score thresholds with supportive conditions, the script reduces the likelihood of acting on random price spikes or dips and instead focuses on movements that are significant within both historical and current contextual frameworks.
Originality and Uniquness
Layered Signal Verification: Signals require the fulfillment of multiple layers (Z-Score extreme, EMA trend bias, and RSI momentum posture) rather than merely breaching a statistical threshold.
RSI Zone Lockout: Once RSI enters an overbought/oversold zone and triggers a signal, the script locks out subsequent signals until RSI recovers above or below those zones, limiting back-to-back triggers.
Controlled Cooldown: A dedicated cooldown mechanic ensures that the script waits a specified number of bars before issuing a new signal in the opposite direction.
Gradient-Based Visualization: Distinct gradient fills between price and the Z-Mean line enhance readability, showing at a glance whether price is trading above or below its statistical average.
Comprehensive Metrics Panel: An optional on-chart table summarizes the Z-Score’s key metrics, streamlining the process of verifying current statistical extremes, mean levels, and momentum directions.
Why these indicators were merged
Z-Score measurements excel at identifying when price deviates from its mean, but they do not intrinsically reveal whether the market’s trajectory supports a reversion or if price might continue along its trend. The EMA, commonly used for spotting trend directions, offers valuable insight into whether price is predominantly ascending or descending. However, relying solely on a trend filter overlooks the intensity of price moves. RSI then adds a dedicated measure of momentum, helping confirm if the market’s energy aligns with a potential reversal (for example, price is statistically low but RSI suggests looming upward momentum). By uniting these three lenses—Z-Score for statistical context, EMA for trend direction, and RSI for momentum force—the script offers a more comprehensive and adaptable system, aiming to avoid false positives caused by focusing on just one aspect of price behavior.
Calculations
The core calculation begins with a simple moving average (SMA) of price over zLen bars, referred to as the basis. Next, the script computes the standard deviation of price over the same window. Dividing the difference between the current price and the basis by this standard deviation produces the Z-Score, indicating how many standard deviations the price is from its mean. A positive Z-Score reveals price is above its average; a negative reading indicates the opposite.
To detect overall market direction, the script calculates an exponential moving average (emaTrend) over emaTrendLen bars. If price is above this EMA, the script deems the market bullish; if below, it’s considered bearish. For momentum confirmation, the script computes a standard RSI over rsiLen bars, then applies a smoothing EMA over rsiEmaLen bars. This smoothed RSI (rsiEma) is monitored for both its absolute level (oversold or overbought) and its slope (the difference between the current and previous value). Finally, slopeIndex determines how many bars back the script compares the basis to check whether the Z-Mean line is generally rising, falling, or flat, which then informs the coloring scheme on the chart.
Calculations and Rational
Simple Moving Average for Baseline: An SMA is used for the core mean because it places equal weight on each bar in the lookback period. This helps maintain a straightforward interpretation of overbought or oversold conditions in the context of a uniform historical average.
Standard Deviation for Volatility: Standard deviation measures the variability of the data around the mean. By dividing price’s difference from the mean by this value, the Z-Score can highlight whether price is unusually stretched given typical volatility.
Exponential Moving Average for Trend: Unlike an SMA, an EMA places more emphasis on recent data, reacting quicker to new price developments. This quicker response helps the script promptly identify trend shifts, which can be crucial for filtering out signals that go against a strong directional move.
RSI for Momentum Confirmation: RSI is an oscillator that gauges price movement strength by comparing average gains to average losses over a set period. By further smoothing this RSI with another EMA, short-lived oscillations become less influential, making signals more robust.
SlopeIndex for Slope-Based Coloring: To clarify whether the market’s central tendency is rising or falling, the script compares the basis now to its level slopeIndex bars ago. A higher current reading indicates an upward slope; a lower reading, a downward slope; and similar readings, a flat slope. This is visually represented on the chart, providing an immediate sense of the directionality.
Inputs
zLen (Z-Score Period)
Specifies how many bars to include for computing the SMA and standard deviation that form the basis of the Z-Score calculation. Larger values produce smoother but slower signals; smaller values catch quick changes but may generate noise.
emaTrendLen (EMA Trend Filter)
Sets the length of the EMA used to detect the market’s primary direction. This is pivotal for distinguishing whether signals should be considered (price aligning with an uptrend or downtrend) or filtered out.
rsiLen (RSI Length)
Defines the window for the initial RSI calculation. This RSI, when combined with the subsequent smoothing EMA, forms the foundation for momentum-based signal confirmations.
rsiEmaLen (EMA of RSI Period)
Applies an exponential moving average over the RSI readings for additional smoothing. This step helps mitigate rapid RSI fluctuations that might otherwise produce whipsaw signals.
zBuyLevel (Z-Score Buy Threshold)
Determines how negative the Z-Score must be for the script to consider a potential oversold signal. If the Z-Score dives below this threshold (and other criteria are met), a buy signal is generated.
zSellLevel (Z-Score Sell Threshold)
Determines how positive the Z-Score must be for a potential overbought signal. If the Z-Score surpasses this threshold (and other checks are satisfied), a sell signal is generated.
cooldownBars (Cooldown (Bars))
Enforces a bar-based delay between opposite signals. Once a buy signal has fired, the script must wait the specified number of bars before registering a new sell signal, and vice versa.
slopeIndex (Slope Sensitivity (Bars))
Specifies how many bars back the script compares the current basis for slope coloration. A bigger slopeIndex highlights larger directional trends, while a smaller number emphasizes shorter-term shifts.
showMeanLine (Show Z-Score Mean Line)
Enables or disables the plotting of the Z-Mean and its slope-based coloring. Traders who prefer minimal chart clutter may turn this off while still retaining signals.
Features
Statistical Core (Z-Score Detection):
This feature computes the Z-Score by taking the difference between the current price and the basis (SMA) and dividing by the standard deviation. In effect, it translates price fluctuations into a standardized measure that reveals how significant a move is relative to the typical variation seen over the lookback. When the Z-Score crosses predefined thresholds (zBuyLevel for oversold and zSellLevel for overbought), it signals that price could be at an extreme.
How It Works: On each bar, the script updates the SMA and standard deviation. The Z-Score is then refreshed accordingly. Traders can interpret particularly large negative or positive Z-Score values as scenarios where price is abnormally low or high.
EMA Trend Filter:
An EMA over emaTrendLen bars is used to classify the market as bullish if the price is above it and bearish if the price is below it. This classification is applied to the Z-Score signals, accepting them only when they align with the broader price direction.
How It Works: If the script detects a Z-Score below zBuyLevel, it further checks if price is actually in a downtrend (below EMA) before issuing a buy signal. This might seem counterintuitive, but a “downtrend” environment plus an oversold reading often signals a potential bounce or a mean-reversion play. Conversely, for sell signals, the script checks if the market is in an uptrend first. If it is, an overbought reading aligns with potential profit-taking.
RSI Momentum Confirmation with Oversold/Overbought Lockout:
RSI is calculated over rsiLen, then smoothed by an EMA over rsiEmaLen. If this smoothed RSI dips below a certain threshold (for example, 30) and then begins to slope upward, the indicator treats it as a potential sign of recovering momentum. Similarly, if RSI climbs above a certain threshold (for instance, 70) and starts to slope downward, that suggests dwindling momentum. Additionally, once RSI is in these zones, the indicator locks out repetitive signals until RSI fully exits and re-enters those extreme territories.
How It Works: Each bar, the script measures whether RSI has dropped below the oversold threshold (like 30) and has a positive slope. If it does, the buy side is considered “unlocked.” For sell signals, RSI must exceed an overbought threshold (70) and slope downward. The combination of threshold and slope helps confirm that a reversal is genuinely in progress instead of issuing signals while momentum remains weak or stuck in extremes.
Cooldown Mechanism:
The script features a custom bar-based cooldown that prevents issuing new signals in the opposite direction immediately after one is triggered. This helps avoid whipsaw situations where the market quickly flips from oversold to overbought or vice versa.
How It Works: When a buy signal fires, the indicator notes the bar index. If the Z-Score and RSI conditions later suggest a sell, the script compares the current bar index to the last buy signal’s bar index. If the difference is within cooldownBars, the signal is disallowed. This ensures a predefined “quiet period” before switching signals.
Slope-Based Coloring (Z-Mean Line and Shadow):
The script compares the current basis value to its value slopeIndex bars ago. A higher reading now indicates a generally upward slope, while a lower reading indicates a downward slope. The script then shades the Z-Mean line in a corresponding bullish or bearish color, or remains neutral if little change is detected.
How It Works: This slope calculation is refreshingly straightforward: basis – basis . If the result is positive, the line is colored bullish; if negative, it is colored bearish; if approximately zero, it remains neutral. This provides a quick visual cue of the medium-term directional bias.
Gradient Overlays:
With gradient fills, the script highlights where price stands in relation to the Z-Mean. When price is above the basis, a purple-shaded region is painted, visually indicating a “bearish zone” for potential overbought conditions. When price is below, a teal-like overlay is used, suggesting a “bullish zone” for potential oversold conditions.
How It Works: Each bar, the script checks if price is above or below the basis. It then applies a fill between close and basis, using distinct colors to show whether the market is trading above or below its mean. This creates an immediate sense of how extended the market might be.
Buy and Sell Labels (with Alerts):
When a legitimate buy or sell condition passes every check (Z-Score threshold, EMA trend alignment, RSI gating, and cooldown clearance), the script plots a corresponding label directly on the chart. It also fires an alert (if alerts are set up), making it convenient for traders who want timely notifications.
How It Works: If rawBuy or rawSell conditions are met (refined by RSI, EMA trend, and cooldown constraints), the script calls the respective plot function to paint an arrow label on the chart. Alerts are triggered simultaneously, carrying easily recognizable messages.
Metrics Table:
The optional on-chart table (activated by showMetrics) presents real-time Z-Score data, including the current Z-Score, its rolling mean, the maximum and minimum Z-Score values observed over the last zLen bars, a percentile position, and a short-term directional note (rising, falling, or flat).
Current – The present Z-Score reading
Mean – Average Z-Score over the zLen period
Min/Max – Lowest and highest Z-Score values within zLen
Position – Where the current Z-Score sits between the min and max (as a percentile)
Trend – Whether the Z-Score is increasing, decreasing, or flat
Conclusion
Uptrick: Z-Score Flow offers a versatile solution for traders who need a statistically informed perspective on price extremes combined with practical checks for overall trend and momentum. By leveraging a well-defined combination of Z-Score, EMA trend classification, RSI-based momentum gating, slope-based visualization, and a cooldown mechanic, the script reduces the occurrence of false or premature signals. Its gradient fills and optional metrics table contribute further clarity, ensuring that users can quickly assess market posture and make more confident trading decisions in real time.
Disclaimer
This script is intended solely for informational and educational purposes. Trading in any financial market comes with substantial risk, and there is no guarantee of success or the avoidance of loss. Historical performance does not ensure future results. Always conduct thorough research and consider professional guidance prior to making any investment or trading decisions.
Volume Pro Indicator## Volume Pro Indicator
A powerful volume indicator that visualizes volume distribution across different price levels. This tool helps you easily identify where trading activity concentrates within the price range.
### Key Features:
- **Volume visualization by price levels**: Green (lower zone), Magenta (middle zone), Cyan (upper zone)
- **VPOC (Volume Point of Control)**: Shows the price level with the highest volume concentration
- **High and Low lines**: Highlights the extreme levels of the analyzed price range
- **Customizable historical analysis**: Configurable number of days for calculation
### How to use it:
- Colored volumes show where trading activity concentrates within the price range
- The VPOC helps identify the most significant price levels
- Different colors allow you to quickly visualize volume distribution in different price areas
Customizable with numerous options, including analysis period, calculation resolution, colors, and visibility of different components.
### Note:
This indicator works best on higher timeframes (1H, 4H, 1D) and liquid markets. It's a visual analysis tool that enhances your understanding of market structure.
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Enhanced Fuzzy SMA Analyzer (Multi-Output Proxy) [FibonacciFlux]EFzSMA: Decode Trend Quality, Conviction & Risk Beyond Simple Averages
Stop Relying on Lagging Averages Alone. Gain a Multi-Dimensional Edge.
The Challenge: Simple Moving Averages (SMAs) tell you where the price was , but they fail to capture the true quality, conviction, and sustainability of a trend. Relying solely on price crossing an average often leads to chasing weak moves, getting caught in choppy markets, or missing critical signs of trend exhaustion. Advanced traders need a more sophisticated lens to navigate complex market dynamics.
The Solution: Enhanced Fuzzy SMA Analyzer (EFzSMA)
EFzSMA is engineered to address these limitations head-on. It moves beyond simple price-average comparisons by employing a sophisticated Fuzzy Inference System (FIS) that intelligently integrates multiple critical market factors:
Price deviation from the SMA ( adaptively normalized for market volatility)
Momentum (Rate of Change - ROC)
Market Sentiment/Overheat (Relative Strength Index - RSI)
Market Volatility Context (Average True Range - ATR, optional)
Volume Dynamics (Volume relative to its MA, optional)
Instead of just a line on a chart, EFzSMA delivers a multi-dimensional assessment designed to give you deeper insights and a quantifiable edge.
Why EFzSMA? Gain Deeper Market Insights
EFzSMA empowers you to make more informed decisions by providing insights that simple averages cannot:
Assess True Trend Quality, Not Just Location: Is the price above the SMA simply because of a temporary spike, or is it supported by strong momentum, confirming volume, and stable volatility? EFzSMA's core fuzzyTrendScore (-1 to +1) evaluates the health of the trend, helping you distinguish robust moves from noise.
Quantify Signal Conviction: How reliable is the current trend signal? The Conviction Proxy (0 to 1) measures the internal consistency among the different market factors analyzed by the FIS. High conviction suggests factors are aligned, boosting confidence in the trend signal. Low conviction warns of conflicting signals, uncertainty, or potential consolidation – acting as a powerful filter against chasing weak moves.
// Simplified Concept: Conviction reflects agreement vs. conflict among fuzzy inputs
bullStrength = strength_SB + strength_WB
bearStrength = strength_SBe + strength_WBe
dominantStrength = max(bullStrength, bearStrength)
conflictingStrength = min(bullStrength, bearStrength) + strength_N
convictionProxy := (dominantStrength - conflictingStrength) / (dominantStrength + conflictingStrength + 1e-10)
// Modifiers (Volatility/Volume) applied...
Anticipate Potential Reversals: Trends don't last forever. The Reversal Risk Proxy (0 to 1) synthesizes multiple warning signs – like extreme RSI readings, surging volatility, or diverging volume – into a single, actionable metric. High reversal risk flags conditions often associated with trend exhaustion, providing early warnings to protect profits or consider counter-trend opportunities.
Adapt to Changing Market Regimes: Markets shift between high and low volatility. EFzSMA's unique Adaptive Deviation Normalization adjusts how it perceives price deviations based on recent market behavior (percentile rank). This ensures more consistent analysis whether the market is quiet or chaotic.
// Core Idea: Normalize deviation by recent volatility (percentile)
diff_abs_percentile = ta.percentile_linear_interpolation(abs(raw_diff), normLookback, percRank) + 1e-10
normalized_diff := raw_diff / diff_abs_percentile
// Fuzzy sets for 'normalized_diff' are thus adaptive to volatility
Integrate Complexity, Output Clarity: EFzSMA distills complex, multi-factor analysis into clear, interpretable outputs, helping you cut through market noise and focus on what truly matters for your decision-making process.
Interpreting the Multi-Dimensional Output
The true power of EFzSMA lies in analyzing its outputs together:
A high Trend Score (+0.8) is significant, but its reliability is amplified by high Conviction (0.9) and low Reversal Risk (0.2) . This indicates a strong, well-supported trend.
Conversely, the same high Trend Score (+0.8) coupled with low Conviction (0.3) and high Reversal Risk (0.7) signals caution – the trend might look strong superficially, but internal factors suggest weakness or impending exhaustion.
Use these combined insights to:
Filter Entry Signals: Require minimum Trend Score and Conviction levels.
Manage Risk: Consider reducing exposure or tightening stops when Reversal Risk climbs significantly, especially if Conviction drops.
Time Exits: Use rising Reversal Risk and falling Conviction as potential signals to take profits.
Identify Regime Shifts: Monitor how the relationship between the outputs changes over time.
Core Technology (Briefly)
EFzSMA leverages a Mamdani-style Fuzzy Inference System. Crisp inputs (normalized deviation, ROC, RSI, ATR%, Vol Ratio) are mapped to linguistic fuzzy sets ("Low", "High", "Positive", etc.). A rules engine evaluates combinations (e.g., "IF Deviation is LargePositive AND Momentum is StrongPositive THEN Trend is StrongBullish"). Modifiers based on Volatility and Volume context adjust rule strengths. Finally, the system aggregates these and defuzzifies them into the Trend Score, Conviction Proxy, and Reversal Risk Proxy. The key is the system's ability to handle ambiguity and combine multiple, potentially conflicting factors in a nuanced way, much like human expert reasoning.
Customization
While designed with robust defaults, EFzSMA offers granular control:
Adjust SMA, ROC, RSI, ATR, Volume MA lengths.
Fine-tune Normalization parameters (lookback, percentile). Note: Fuzzy set definitions for deviation are tuned for the normalized range.
Configure Volatility and Volume thresholds for fuzzy sets. Tuning these is crucial for specific assets/timeframes.
Toggle visual elements (Proxies, BG Color, Risk Shapes, Volatility-based Transparency).
Recommended Use & Caveats
EFzSMA is a sophisticated analytical tool, not a standalone "buy/sell" signal generator.
Use it to complement your existing strategy and analysis.
Always validate signals with price action, market structure, and other confirming factors.
Thorough backtesting and forward testing are essential to understand its behavior and tune parameters for your specific instruments and timeframes.
Fuzzy logic parameters (membership functions, rules) are based on general heuristics and may require optimization for specific market niches.
Disclaimer
Trading involves substantial risk. EFzSMA is provided for informational and analytical purposes only and does not constitute financial advice. No guarantee of profit is made or implied. Past performance is not indicative of future results. Use rigorous risk management practices.
