Parabolic-Fibonacci MA ForecastThis indicator displays a series of projected price levels based on Fibonacci moving averages. For each selected Fibonacci period, it calculates a simple moving average (SMA) and mirrors the distance from the current price to that SMA in the opposite direction, creating a vertical forecast distance. These forecast distances are drawn forward into the future using geometric spacing (squared increments: 1², 2², 3², etc.), creating a fan-like or polyline visual structure.
Users can choose between three display modes:
Fan: Lines drawn from the current price to projected values at increasing intervals
Polyline: Forecast points connected to form a jagged projection path
Both: Displays both fan and polyline structures simultaneously
Options are provided to adjust the number of Fibonacci lines (up to 12), line width, and colors for lines above/below price or up/down slope.
This tool can help visualize directional price tendencies using multiple SMA-based forecasts in a spatially meaningful layout.
Analisis Trend
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
Linear Regression ForecastDescription:
This indicator computes a series of simple linear regressions anchored at the current bar, using look-back windows from 2 bars up to the user-defined maximum. Each regression line is projected forward by the same number of bars as its look-back, producing a family of forecast endpoints. These endpoints are then connected into a continuous polyline: ascending segments are drawn in green, and descending segments in red.
Inputs:
maxLength – Maximum number of bars to include in the longest regression (minimum 2)
priceSource – Price series used for regression (for example, close, open, high, low)
lineWidth – Width of each line segment
Calculation:
For each window size N (from 2 to maxLength):
• Compute least-squares slope and intercept over the N most recent bars (with bar 0 = current bar, bar 1 = one bar ago, etc.).
• Project the regression line to bar_index + N to obtain the forecast price.
Collected forecast points are sorted by projection horizon and then joined:
• First segment: current bar’s price → first forecast point
• Subsequent segments: each forecast point → next forecast point
Segment colors reflect slope direction: green for non-negative, red for negative.
Usage:
Apply this overlay to any price chart. Adjust maxLength to control the depth and reach of the forecast fan. Observe how shorter windows produce nearer-term, more reactive projections, while longer windows yield smoother, more conservative forecasts. Use the colored segments to gauge the overall bias of the fan at each step.
Limitations:
This tool is for informational and educational purposes only. It relies on linear regression assumptions and past price behavior; it does not guarantee future performance. Users should combine it with other technical or fundamental analyses and risk management practices.
SOXL Trend Surge v3.0.2 – Profit-Only RunnerSOXL Trend Surge v3.0.2 – Profit-Only Runner
This is a trend-following strategy built for leveraged ETFs like SOXL, designed to ride high-momentum waves with minimal interference. Unlike most short-term scalping scripts, this model allows trades to develop over multiple days to even several months, capitalizing on the full power of extended directional moves — all without using a stop-loss.
🔍 How It Works
Entry Logic:
Price is above the 200 EMA (long-term trend confirmation)
Supertrend is bullish (momentum confirmation)
ATR is rising (volatility expansion)
Volume is above its 20-bar average (liquidity filter)
Price is outside a small buffer zone from the 200 EMA (to avoid whipsaws)
Trades are restricted to market hours only (9 AM to 2 PM EST)
Cooldown of 15 bars after each exit to prevent overtrading
Exit Strategy:
Takes partial profit at +2× ATR if held for at least 2 bars
Rides the remaining position with a trailing stop at 1.5× ATR
No hard stop-loss — giving space for volatile pullbacks
⚙️ Strategy Settings
Initial Capital: $500
Risk per Trade: 100% of equity (fully allocated per entry)
Commission: 0.1%
Slippage: 1 tick
Recalculate after order is filled
Fill orders on bar close
Timeframe Optimized For: 45-minute chart
These parameters simulate an aggressive, high-volatility trading model meant for forward-testing compounding potential under realistic trading costs.
✅ What Makes This Unique
No stop-loss = fewer premature exits
Partial profit-taking helps lock in early wins
Trailing logic gives room to ride large multi-week moves
Uses strict filters (volume, ATR, EMA bias) to enter only during high-probability windows
Ideal for leveraged ETF swing or position traders looking to hold longer than the typical intraday or 2–3 day strategies
⚠️ Important Note
This is a high-risk, high-reward strategy meant for educational and testing purposes. Without a stop-loss, trades can experience deep drawdowns that may take weeks or even months to recover. Always test thoroughly and adjust position sizing to suit your risk tolerance. Past results do not guarantee future returns. Backtest range: May 8, 2020 – May 23, 2025
Delta Volume Profile [BigBeluga]🔵Delta Volume Profile
A dynamic volume analysis tool that builds two separate horizontal profiles: one for bullish candles and one for bearish candles. This indicator helps traders identify the true balance of buying vs. selling volume across price levels, highlighting points of control (POCs), delta dominance, and hidden volume clusters with remarkable precision.
🔵 KEY FEATURES
Split Volume Profiles (Bull vs. Bear):
The indicator separates volume based on candle direction:
If close > open , the candle’s volume is added to the bullish profile (positive volume).
If close < open , it contributes to the bearish profile (negative volume).
ATR-Based Binning:
The price range over the selected lookback is split into bins using ATR(200) as the bin height.
Each bin accumulates both bull and bear volumes to form the dual-sided profile.
Bull and Bear Volume Bars:
Bullish volumes are shown as right-facing bars on the right side, colored with a bullish gradient.
Bearish volumes appear as left-facing bars on the left side, shaded with a bearish gradient.
Each bar includes a volume label (e.g., +12.45K or -9.33K) to show exact volume at that price level.
Points of Control (POC) Highlighting:
The bin with the highest bullish volume is marked with a border in POC+ color (default: blue).
The bin with the highest bearish volume is marked with a POC− color (default: orange).
Total Volume Density Map:
A neutral gray background box is plotted behind candles showing the total volume (bull + bear) per bin.
This reveals high-interest price zones regardless of direction.
Delta and Total Volume Summary:
A Delta label appears at the top, showing net % difference between bull and bear volume.
A Total label at the bottom shows total accumulated volume across all bins.
🔵 HOW IT WORKS
The indicator captures all candles within the lookback period .
It calculates the price range and splits it into bins using ATR for adaptive resolution.
For each candle:
If price intersects a bin and close > open , volume is added to the positive profile .
If close < open , volume is added to the negative profile .
The result is two side-by-side histograms at each price level—one for buyers, one for sellers.
The bin with the highest value on each side is visually emphasized using POC highlight colors.
At the end, the script calculates:
Delta: Total % difference between bull and bear volumes.
Total: Sum of all volumes in the lookback window.
🔵 USAGE
Volume Imbalance Zones: Identify price levels where buyers or sellers were clearly dominant.
Fade or Follow Volume Clusters: Use POC+ or POC− levels for reaction trades or breakouts.
Delta Strength Filtering: Strong delta values (> ±20%) suggest momentum or exhaustion setups.
Volume-Based Anchoring: Use profile levels to mark hidden support/resistance and execution zones.
🔵 CONCLUSION
Delta Volume Profile offers a unique advantage in market reading by separating buyer and seller activity into two visual layers. This allows traders to not only spot where volume was high, but also who was more aggressive. Whether you’re analyzing trend continuations, reversals, or absorption levels, this indicator gives you the transparency needed to trade with confidence.
Decimal EMAImagine you want a moving average line, but you want its "length" or "period" to be super precise, like 2.7 days instead of just 2 days or 3 days.
This script lets you do that. Here's the simple idea:
You Pick a Decimal Number: In the settings, you can type in a period with a decimal, say, 2.7.
The Script Does a Smart Blend:
It first calculates two regular EMAs: one for the whole number below your choice (EMA for 2 days) and one for the whole number above (EMA for 3 days).
Then, it cleverly mixes these two EMA lines. Since 2.7 is closer to 3 than to 2, it takes more from the "3-day EMA" and a bit less from the "2-day EMA." (Specifically, it takes 70% from the 3-day EMA and 30% from the 2-day EMA).
You Get a Decimal EMA Line: The result is a new EMA line that acts as if its period was exactly 2.7. This line is drawn on your chart.
Why do this?
It allows for very fine-tuned adjustments to how responsive your moving average is, giving a smoother change if you're testing slightly different period lengths.
In Short:
This script calculates an EMA for a period like "2.7" by intelligently blending the results of an EMA for "2" and an EMA for "3".
Chaikin Momentum Scalper🎯 Overview
The Chaikin Momentum Scalper is a powerful trading strategy designed to identify momentum shifts in the market and ride the trend for maximum profits. This strategy is ideal for trading the USD/JPY currency pair on a 15-minute chart, making it perfect for high-frequency trading (HFT). Whether you’re starting with a small account of $1,000 or managing a larger portfolio, this strategy can scale to suit your needs.
________________________________________
🔑 How the Strategy Works
Here’s how the Chaikin Momentum Scalper identifies trade opportunities:
1️⃣ Momentum Detection
The core of this strategy is the Chaikin Oscillator, a tool that measures the flow of money into or out of a market. It helps us understand whether buyers (bulls) or sellers (bears) are in control.
• When the indicator crosses above zero, it signals that buying momentum is picking up – a buying opportunity.
• When the indicator crosses below zero, it signals that selling momentum is increasing – a selling opportunity.
2️⃣ Trend Confirmation
We don’t just jump into trades based on momentum alone. We also use a 200-period simple moving average (SMA) to confirm the overall trend.
• If the price is above the SMA, it confirms an uptrend, so we look for buy trades.
• If the price is below the SMA, it confirms a downtrend, so we look for sell trades.
This way, we align our trades with the broader market direction for higher success rates.
3️⃣ Volatility & Risk Management
We use a tool called the Average True Range (ATR) to measure market volatility. This helps us:
• Set a stop-loss (where we’ll exit the trade if the market moves against us) at a safe distance from our entry point.
• Set a take-profit (where we’ll lock in profits) at a target that’s larger than the stop-loss, ensuring a good reward-to-risk ratio.
This approach adapts to the market’s behavior, tightening stops in calmer conditions and widening them when volatility increases.
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📈 Why This Strategy Works
✅ It combines momentum and trend-following principles, increasing the chances of trading in the right direction.
✅ It dynamically adjusts risk levels based on market volatility, keeping losses small and profits big.
✅ It’s scalable – perfect for both small accounts (like $1,000) and larger, corporate-sized portfolios.
✅ It has been deep-backtested on USD/JPY 15-minute charts, proving its consistency across different market conditions.
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📝 Important Notes
📌 This strategy is best used for USD/JPY on a 15-minute chart, making it great for high-frequency trading while you continue to build and refine your trading system.
📌 It’s designed to work on both small ($1,000+) and large accounts, so it can grow with you as your capital increases.
📌 While it has passed deep backtesting on this pair and timeframe, remember that no strategy is perfect. It’s crucial to test it yourself, start with a demo account, and apply proper risk management before trading real money.
🌟 Final Thoughts
The Chaikin Momentum Scalper is a solid, adaptable trading approach combining momentum, trend direction, and volatility awareness. If you’re looking for a strategy to kick-start your trading journey—or to add to your existing system—it offers a strong foundation.
Grid Tendence V1The “Grid Tendence V1” strategy is based on the classic Grid strategy, only in this case the entries and exits are made in favor of the trend, which allows to take advantage of large movements to maximize profits, since it is also possible to enter and exit with the balance with a controlled risk, because precisely the distance between each Grid works as a natural and adaptable stop loss and take profit. This fact helps to avoid overlapping entries and exits that would result from using stop loss and take profit as limit orders.
In this version of the script the entries and exits are always at market, and based on the percentage change of the price, not on the profit or loss of the current position.
The user will notice that the strategy setup is based on a controlled risk, risking 5% on each trade, a fairly standard commission and a modest initial capital, all this in order to protect the user of the strategy from unexpected or unrealistic results.
However, it is always recommended to optimize the parameters so that the strategy is effective for each asset and for each time frame.
AMD Liquidity Sweep with AlertsAMD Liquidity Sweep with Alerts
Identify key liquidity levels from the Asian trading session with visual markers and alerts.
📌 Key Features:
Asia Session Detection
Customizable start/end hours (0-23) to match your trading timezone
Automatically calculates session high/low
Smart Swing Level Identification
Finds the closest significant swing high ≥ Asia high
Finds the closest significant swing low ≤ Asia low
Adjustable pivot sensitivity (# of left/right bars)
Professional Visuals
Dashed reference lines extending into the future
Blue-highlighted key levels
Clean label formatting with precise price levels
Trading Alerts
Price-cross alerts for liquidity breaks
Visual markers (triangles) when levels are breached
Separate alerts for buy-side/sell-side liquidity
Customization Options
Toggle intermediate swing highlights
Adjust label sizes
💡 Trading Applications:
Institutional Levels: Identify zones where Asian session liquidity pools exist
Breakout Trading: Get alerted when price breaches Asian session ranges
S/R Flip Zones: Watch how price reacts at these key reference levels
London/NY Open: Use Asian levels for early European session trades
🔧 How to Use:
Set your preferred Asia session hours
Adjust pivot sensitivity (default 1 bar works for most timeframes)
Enable alerts for breakouts if desired
Watch for reactions at the plotted levels
BG Ichimoku Tenkan MTFBG Ichimoku Tenkan MTF: Your Multi-Timeframe Trend Compass
Elevate your Ichimoku analysis with the BG Ichimoku Tenkan MTF indicator. This powerful tool provides a comprehensive view of the Tenkan-sen (Conversion Line) across multiple timeframes, helping you identify trends and potential shifts with greater clarity. It's ideal for all markets, including stocks, cryptocurrencies, Forex, and futures.
Key Features:
Main Tenkan-sen Plot: Visualize the Tenkan-sen for your active chart timeframe with adjustable color.
Multi-Timeframe Table: A dynamic table displays the Tenkan-sen's relationship to price (🔼 for above, 🔽 for below) and its current value for up to 7 timeframes.
Continuous MTF Lines: Plot the Tenkan-sen from higher timeframes directly on your current chart, providing clear support/resistance levels and trend confluence.
Fully Customizable Colors: Personalize the color for each individual timeframe in the table and for its corresponding MTF line, ensuring a clean and intuitive visual experience. You can also adjust the main Tenkan-sen color and the MTF line offset.
Gain a deeper understanding of market dynamics by analyzing the Tenkan-sen across different time scales, all in one intuitive indicator.
We created this indicator to help you better navigate the markets. Thank you for using it, and we hope it brings you value. Enjoy it in your daily analysis!
Bab
ka66: Triple Keltner Around SourceThis is an indicator-on-indicator which draws Keltner Bands (ATR Bands) around any selected Basis Source, instead of hardcoding a moving average, etc. This allows you to put bands around any sort of esoteric moving average of your choice, or even just around price data like OHLC, HLC3, and so on.
It's an enhancement on my prior Multi ATR Channels script at
Written in Pine v6 and allowing custom timeframe selection.
For example, the published chart shows the bands place around a Kaufman Adaptive Moving Average (KAMA), plotted in blue dots.
You would use it for anything that you would use plain Keltners for:
Mean Reversion
Breakouts
Take Profit and Stop Loss Estimation
But with any basis that you deem more suitable for your purposes.
EWMA & EWVar + EWStd Expansion with MTF_V.5EWMA & EWVar + EWStd Expansion with MTF_V.5
This indicator combines adaptive trend smoothing (EWMA), variance estimation (EWVar) and dynamic volatility “bursts” (EWStd Expansion) with optional higher-timeframe confirmation. It’s designed both for visual chart analysis and for automated alerts on regime changes.
Key Features
EWMA (Exponential Smoothing):
• Computes an exponential moving average with either a custom α or a length-derived α = 2/(N+1).
• Option to recalculate only every N bars (reduces CPU load).
EWVar & EWStd (Variance & Standard Deviation):
• Exponentially weighted variance tracks recent price dispersion.
• EWStd (σ) is computed alongside the EWMA.
• Z-score (deviation in σ units) shows how far price has diverged from trend.
Multi-Timeframe Filter (MTF):
• Optionally require the same trend direction on a chosen higher timeframe (e.g. Daily, Weekly, H4).
• Real-time lookahead available (may repaint).
Gradient Around EWMA:
• A multi-layer “glow” zone of ±1σ, broken into up to 10 steps.
• Color interpolates between “upper” and “lower” shades for bullish, bearish and neutral regimes.
Instantaneous Trendline (ITL):
• Ultra-fast trend filter with slope-based coloring.
• Highlights micro-trends and short-lived accelerations.
Cross-Over Signals (ITL ↔ EWMA):
• Up/down triangles plotted when the ITL crosses the main EWMA.
EWStd Expansion (Volatility Bursts):
• Automatically detects σ expansions (σ growth above a set % threshold).
• Price filter: only when price moves beyond EWMA ± (multiplier·σ).
• Optional higher-timeframe confirmation.
Labels & Alerts:
• Text labels and circular markers on bars where a volatility burst occurs.
• Built-in alertcondition calls for both bullish and bearish expansions.
How to Use
Visual Analysis:
• The gradient around EWMA shows the width of the volatility channel expanding or contracting.
• ITL color changes instantly highlight short-term impulses.
• EWMA line color switches (bullish/bearish/neutral) indicate trend state.
Spotting Volatility Breakouts:
• “EWStd Expansion” labels and circles signal the onset of strong moves when σ spikes.
• Useful for entering at the start of new impulses.
Automated Alerts:
• Set alerts on the built-in conditions “Bullish EWStd Expansion Alert” or “Bearish EWStd Expansion Alert” to receive a popup or mobile push when a burst occurs.
This compact tool unifies trend, volatility and multi-timeframe analysis into a single indicator—ideal for traders who want to see trend direction, current dispersion, and timely volatility burst signals all at once.
EMD Trend [InvestorUnknown]EMD Trend is a dynamic trend-following indicator that utilizes Exponential Moving Deviation (EMD) to build adaptive channels around a selected moving average. Designed for traders who value responsive trend signals with built-in volatility sensitivity, this tool highlights directional bias, market regime shifts, and potential breakout opportunities.
How It Works
Instead of using standard deviation, EMD Trend employs the exponential moving average of the absolute deviation from a moving average—producing smoother, faster-reacting upper and lower bounds:
Bullish (Risk-ON Long): Price crosses above the upper EMD band
Bearish (Risk-ON Short): Price crosses below the lower EMD band
Neutral: Price stays within the channel, indicating potential mean reversion or low momentum
Trend direction is defined by price interaction with these bands, and visual cues (color-coded bars and fills) help quickly identify market conditions.
Features
7 Moving Average Types: SMA, EMA, HMA, DEMA, TEMA, RMA, FRAMA
Custom Price Source: Choose close, hl2, ohlc4, or others
EMD Multiplier: Controls the width of the deviation envelope
Bar Coloring: Candles change color based on current trend
Intra-bar Signal Option: Enables faster updates (with optional repainting)
Speculative Zones: Fills highlight aggressive momentum moves beyond EMD bounds
Backtest Mode
Switch to Backtest Mode for performance evaluation over historical data:
Equity Curve Plot: Compare EMD Trend strategy vs. Buy & Hold
Trade Metrics Table: View number of trades, win/loss stats, profits
Performance Metrics Table: Includes CAGR, Sharpe, max drawdown, and more
Custom Start Date: Select from which date the backtest should begin
Trade Sizing: Configure capital and trade percentage per entry
Signal Filters: Choose from Long Only, Short Only, or Both
Alerts
Built-in alerts let you automate entries, exits, and trend transitions:
LONG (EMD Trend) - Trend flips to Long
SHORT (EMD Trend) - Trend flips to Short
RISK-ON LONG - Price crosses above upper EMD band
RISK-OFF LONG - Price crosses back below upper EMD band
RISK-ON SHORT - Price crosses below lower EMD band
RISK-OFF SHORT - Price crosses back above lower EMD band
Use Cases
Trend Confirmation with volatility-sensitive boundaries
Momentum Entry Filtering via breakout zones
Mean Reversion Avoidance in sideways markets
Backtesting & Strategy Building with real-time metrics
Disclaimer
This indicator is intended for informational and educational purposes only. It does not constitute investment advice. Historical performance does not guarantee future results. Always backtest and use in simulation before live trading.
RMSD Trend [InvestorUnknown]RMSD Trend is a trend-following indicator that utilizes Root Mean Square Deviation (RMSD) to dynamically construct a volatility-weighted trend channel around a selected moving average. This indicator is designed to enhance signal clarity, minimize noise, and offer quantitative insights into market momentum, ideal for both discretionary and systematic traders.
How It Works
At its core, RMSD Trend calculates a deviation band around a selected moving average using the Root Mean Square Deviation (similar to standard deviation but with squared errors), capturing the magnitude of price dispersion over a user-defined period. The logic is simple:
When price crosses above the upper deviation band, the market is considered bullish (Risk-ON Long).
When price crosses below the lower deviation band, the market is considered bearish (Risk-ON Short).
If price stays within the band, the market is interpreted as neutral or ranging, offering low-risk decision zones.
The indicator also generates trend flips (Long/Short) based on crossovers and crossunders of the price and the RMSD bands, and colors candles accordingly for enhanced visual feedback.
Features
7 Moving Average Types: Choose between SMA, EMA, HMA, DEMA, TEMA, RMA, and FRAMA for flexibility.
Customizable Source Input: Use price types like close, hl2, ohlc4, etc.
Volatility-Aware Channel: Adjustable RMSD multiplier determines band width based on volatility.
Smart Coloring: Candles and bands adapt their colors to reflect trend direction (green for bullish, red for bearish).
Intra-bar Repainting Toggle: Option to allow more responsive but repaintable signals.
Speculation Fill Zones: When price exceeds the deviation channel, a semi-transparent fill highlights potential momentum surges.
Backtest Mode
Switching to Backtest Mode unlocks a robust suite of simulation features:
Built-in Equity Curve: Visualizes both strategy equity and Buy & Hold performance.
Trade Metrics Table: Displays the number of trades, win rates, gross profits/losses, and long/short breakdowns.
Performance Metrics Table: Includes key stats like CAGR, drawdown, Sharpe ratio, and more.
Custom Date Range: Set a custom start date for your backtest.
Trade Sizing: Simulate results using position sizing and initial capital settings.
Signal Filters: Choose between Long & Short, Long Only, or Short Only strategies.
Alerts
The RMSD Trend includes six built-in alert conditions:
LONG (RMSD Trend) - Trend flips from Short to Long
SHORT (RMSD Trend) - Trend flips from Long to Short
RISK-ON LONG (RMSD Trend) - Price crosses above upper RMSD band
RISK-OFF LONG (RMSD Trend) - Price falls back below upper RMSD band
RISK-ON SHORT (RMSD Trend) - Price crosses below lower RMSD band
RISK-OFF SHORT (RMSD Trend) - Price rises back above lower RMSD band
Use Cases
Trend Confirmation: Confirms directional bias with RMSD-weighted confidence zones.
Breakout Detection: Highlights moments when price breaks free from historical volatility norms.
Mean Reversion Filtering: Avoids false signals by incorporating RMSD’s volatility sensitivity.
Strategy Development: Backtest your signals or integrate with a broader system for alpha generation.
Settings Summary
Display Mode: Overlay (default) or Backtest Mode
Average Type: Choose from SMA, EMA, HMA, DEMA, etc.
Average Length: Lookback window for moving average
RMSD Multiplier: Band width control based on RMS deviation
Source: Input price source (close, hl2, ohlc4, etc.)
Intra-bar Updating: Real-time updates (may repaint)
Color Bars: Toggle bar coloring by trend direction
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Past performance, including backtest results, is not indicative of future results. Use with caution and always test thoroughly before live deployment.
Trailing Stop Loss [TradingFinder] 4 Machine Learning Methods🔵 Introduction
The trailing stop indicator dynamically adjusts stop-loss (SL) levels to lock in profits as price moves favorably. It uses pivot levels and ATR to set optimal SL points, balancing risk and reward.
Trade confirmation filters, a key feature, ensure entries align with market conditions, reducing false signals. In 2023 a study showed filtered entries improve win rates by 15% in forex. This enhances trade precision.
SL settings, ranging from very tight to very wide, adapt to volatility via ATR calculations. These settings anchor SL to previous pivot levels, ensuring alignment with market structure. This caters to diverse trading styles, from scalping to swing trading.
The indicator colors the profit zone between the entry point (EP) and SL, using light green for buy trades and light red for sell trades. This visual cue highlights profit potential. It’s ideal for traders seeking dynamic risk management.
A table displays real-time trade details, including EP, SL, and profit/loss (PNL). Backtests show trailing stops cut losses by 20% in trending markets. This transparency aids decision-making.
🔵 How to Use
🟣 SL Levels
The trailing stop indicator sets SL based on pivot levels and ATR, offering four options: very tight, tight, wide, or very wide. Very tight SLs suit scalpers, while wide SLs fit swing traders. Select the base level to match your strategy.
If price hits the SL, the trade closes, and the indicator evaluates the next trade using the selected filter. This ensures disciplined trade management. The cycle restarts with a new confirmed entry.
Very tight SLs, set near recent pivots, trigger exits early to minimize risk but limit profits in volatile markets. Wide SLs, shown as farther lines, allow more price movement but increase exposure to losses. Adjust based on ATR and conditions, noting SL breaches open new positions.
🟣 Visualization
The indicator’s visual cues, like colored profit zones, simplify monitoring, with light green showing the profit area from EP to trailed SL. Dashed lines mark entry points, while solid lines track the trailed SL, triggering new positions when breached.
When price moves into profit, the area between EP and SL is colored—light green for longs, light red for shorts. This highlights the profit zone visually. The SL trails price, locking in gains as the trade progresses.
🟣 Filters
Upon trade entry, the indicator requires confirmation via filters like SMA 2x or ADX to validate momentum. Filters reduce false entries, though no guarantee exists for improved outcomes. Monitor price action post-entry for trade validity.
Filters like Momentum or ADX assess trend strength before entry. For example, ADX above 25 confirms strong trends. Choose “none” for unfiltered entries.
🟣 Bullish Alert
For a bullish trade, the indicator opens a long position with a green SL Line (after optional filters), trailing the SL below price. Set alerts to On in the settings for notifications, or Off to monitor manually.
🟣 Bearish Alert
In a bearish trade, the indicator opens a short position with a red SL Line post-confirmation, trailing the SL above price. With alerts On in the settings, it notifies the potential reversal.
🟣 Panel
A table displays all trades’ details, including Win Rates, PNL, and trade status. This real-time data aids in tracking performance. Check the table to assess trade outcomes instantly.
Review the table regularly to evaluate trade performance and adjust settings. Consistent monitoring ensures alignment with market dynamics. This maximizes the indicator’s effectiveness.
🔵 Settings
Length (Default: 10) : Sets the pivot period for calculating SL levels, balancing sensitivity and reliability.
Base Level : Options (“Very tight,” “Tight,” “Wide,” “Very wide”) adjust SL distance via ATR.
Show EP Checkbox : Toggles visibility of the entry point on the chart.
Show PNL : Displays profit/loss data for active and closed trades.
Filter : Options (“none,” “SMA 2x,” “Momentum,” “ADX”) validate trade entries.
🔵 Conclusion
The trailing stop indicator, a dynamic risk management tool, adjusts SLs using pivot levels and ATR. Its confirmation filters reduce false entries, boosting precision. Backtests show 20% loss reduction in trending markets.
Customizable SL settings and visual profit zones enhance usability across trading styles. The real-time table provides clear trade insights, streamlining analysis. It’s ideal for forex, stocks, or crypto.
While filters like ADX improve entry accuracy, no setup guarantees success in all conditions. Contextual analysis, like trend strength, is key. This indicator empowers disciplined, data-driven trading.
Lyapunov Market Instability (LMI)Lyapunov Market Instability (LMI)
What is Lyapunov Market Instability?
Lyapunov Market Instability (LMI) is a revolutionary indicator that brings chaos theory from theoretical physics into practical trading. By calculating Lyapunov exponents—a measure of how rapidly nearby trajectories diverge in phase space—LMI quantifies market sensitivity to initial conditions. This isn't another oscillator or trend indicator; it's a mathematical lens that reveals whether markets are in chaotic (trending) or stable (ranging) regimes.
Inspired by the meditative color field paintings of Mark Rothko, this indicator transforms complex chaos mathematics into an intuitive visual experience. The elegant simplicity of the visualization belies the sophisticated theory underneath—just as Rothko's seemingly simple color blocks contain profound depth.
Theoretical Foundation (Chaos Theory & Lyapunov Exponents)
In dynamical systems, the Lyapunov exponent (λ) measures the rate of separation of infinitesimally close trajectories:
λ > 0: System is chaotic—small changes lead to dramatically different outcomes (butterfly effect)
λ < 0: System is stable—trajectories converge, perturbations die out
λ ≈ 0: Edge of chaos—transition between regimes
Phase Space Reconstruction
Using Takens' embedding theorem , we reconstruct market dynamics in higher dimensions:
Time-delay embedding: Create vectors from price at different lags
Nearest neighbor search: Find historically similar market states
Trajectory evolution: Track how these similar states diverged over time
Divergence rate: Calculate average exponential separation
Market Application
Chaotic markets (λ > threshold): Strong trends emerge, momentum dominates, use breakout strategies
Stable markets (λ < threshold): Mean reversion dominates, fade extremes, range-bound strategies work
Transition zones: Market regime about to change, reduce position size, wait for confirmation
How LMI Works
1. Phase Space Construction
Each point in time is embedded as a vector using historical prices at specific delays (τ). This reveals the market's hidden attractor structure.
2. Lyapunov Calculation
For each current state, we:
- Find similar historical states within epsilon (ε) distance
- Track how these initially similar states evolved
- Measure exponential divergence rate
- Average across multiple trajectories for robustness
3. Signal Generation
Chaos signals: When λ crosses above threshold, market enters trending regime
Stability signals: When λ crosses below threshold, market enters ranging regime
Divergence detection: Price/Lyapunov divergences signal potential reversals
4. Rothko Visualization
Color fields: Background zones represent market states with Rothko-inspired palettes
Glowing line: Lyapunov exponent with intensity reflecting market state
Minimalist design: Focus on essential information without clutter
Inputs:
📐 Lyapunov Parameters
Embedding Dimension (default: 3)
Dimensions for phase space reconstruction
2-3: Simple dynamics (crypto/forex) - captures basic momentum patterns
4-5: Complex dynamics (stocks/indices) - captures intricate market structures
Higher dimensions need exponentially more data but reveal deeper patterns
Time Delay τ (default: 1)
Lag between phase space coordinates
1: High-frequency (1m-15m charts) - captures rapid market shifts
2-3: Medium frequency (1H-4H) - balances noise and signal
4-5: Low frequency (Daily+) - focuses on major regime changes
Match to your timeframe's natural cycle
Initial Separation ε (default: 0.001)
Neighborhood size for finding similar states
0.0001-0.0005: Highly liquid markets (major forex pairs)
0.0005-0.002: Normal markets (large-cap stocks)
0.002-0.01: Volatile markets (crypto, small-caps)
Smaller = more sensitive to chaos onset
Evolution Steps (default: 10)
How far to track trajectory divergence
5-10: Fast signals for scalping - quick regime detection
10-20: Balanced for day trading - reliable signals
20-30: Slow signals for swing trading - major regime shifts only
Nearest Neighbors (default: 5)
Phase space points for averaging
3-4: Noisy/fast markets - adapts quickly
5-6: Balanced (recommended) - smooth yet responsive
7-10: Smooth/slow markets - very stable signals
📊 Signal Parameters
Chaos Threshold (default: 0.05)
Lyapunov value above which market is chaotic
0.01-0.03: Sensitive - more chaos signals, earlier detection
0.05: Balanced - optimal for most markets
0.1-0.2: Conservative - only strong trends trigger
Stability Threshold (default: -0.05)
Lyapunov value below which market is stable
-0.01 to -0.03: Sensitive - quick stability detection
-0.05: Balanced - reliable ranging signals
-0.1 to -0.2: Conservative - only deep stability
Signal Smoothing (default: 3)
EMA period for noise reduction
1-2: Raw signals for experienced traders
3-5: Balanced - recommended for most
6-10: Very smooth for position traders
🎨 Rothko Visualization
Rothko Classic: Deep reds for chaos, midnight blues for stability
Orange/Red: Warm sunset tones throughout
Blue/Black: Cool, meditative ocean depths
Purple/Grey: Subtle, sophisticated palette
Visual Options:
Market Zones : Background fields showing regime areas
Transitions: Arrows marking regime changes
Divergences: Labels for price/Lyapunov divergences
Dashboard: Real-time state and trading signals
Guide: Educational panel explaining the theory
Visual Logic & Interpretation
Main Elements
Lyapunov Line: The heart of the indicator
Above chaos threshold: Market is trending, follow momentum
Below stability threshold: Market is ranging, fade extremes
Between thresholds: Transition zone, reduce risk
Background Zones: Rothko-inspired color fields
Red zone: Chaotic regime (trending)
Gray zone: Transition (uncertain)
Blue zone: Stable regime (ranging)
Transition Markers:
Up triangle: Entering chaos - start trend following
Down triangle: Entering stability - start mean reversion
Divergence Signals:
Bullish: Price makes low but Lyapunov rising (stability breaking down)
Bearish: Price makes high but Lyapunov falling (chaos dissipating)
Dashboard Information
Market State: Current regime (Chaotic/Stable/Transitioning)
Trading Bias: Specific strategy recommendation
Lyapunov λ: Raw value for precision
Signal Strength: Confidence in current regime
Last Change: Bars since last regime shift
Action: Clear trading directive
Trading Strategies
In Chaotic Regime (λ > threshold)
Follow trends aggressively: Breakouts have high success rate
Use momentum strategies: Moving average crossovers work well
Wider stops: Expect larger swings
Pyramid into winners: Trends tend to persist
In Stable Regime (λ < threshold)
Fade extremes: Mean reversion dominates
Use oscillators: RSI, Stochastic work well
Tighter stops: Smaller expected moves
Scale out at targets: Trends don't persist
In Transition Zone
Reduce position size: Uncertainty is high
Wait for confirmation: Let regime establish
Use options: Volatility strategies may work
Monitor closely: Quick changes possible
Advanced Techniques
- Multi-Timeframe Analysis
- Higher timeframe LMI for regime context
- Lower timeframe for entry timing
- Alignment = highest probability trades
- Divergence Trading
- Most powerful at regime boundaries
- Combine with support/resistance
- Use for early reversal detection
- Volatility Correlation
- Chaos often precedes volatility expansion
- Stability often precedes volatility contraction
- Use for options strategies
Originality & Innovation
LMI represents a genuine breakthrough in applying chaos theory to markets:
True Lyapunov Calculation: Not a simplified proxy but actual phase space reconstruction and divergence measurement
Rothko Aesthetic: Transforms complex math into meditative visual experience
Regime Detection: Identifies market state changes before price makes them obvious
Practical Application: Clear, actionable signals from theoretical physics
This is not a combination of existing indicators or a visual makeover of standard tools. It's a fundamental rethinking of how we measure and visualize market dynamics.
Best Practices
Start with defaults: Parameters are optimized for broad market conditions
Match to your timeframe: Adjust tau and evolution steps
Confirm with price action: LMI shows regime, not direction
Use appropriate strategies: Chaos = trend, Stability = reversion
Respect transitions: Reduce risk during regime changes
Alerts Available
Chaos Entry: Market entering chaotic regime - prepare for trends
Stability Entry: Market entering stable regime - prepare for ranges
Bullish Divergence: Potential bottom forming
Bearish Divergence: Potential top forming
Chart Information
Script Name: Lyapunov Market Instability (LMI) Recommended Use: All markets, all timeframes Best Performance: Liquid markets with clear regimes
Academic References
Takens, F. (1981). "Detecting strange attractors in turbulence"
Wolf, A. et al. (1985). "Determining Lyapunov exponents from a time series"
Rosenstein, M. et al. (1993). "A practical method for calculating largest Lyapunov exponents"
Note: After completing this indicator, I discovered @loxx's 2022 "Lyapunov Hodrick-Prescott Oscillator w/ DSL". While both explore Lyapunov exponents, they represent independent implementations with different methodologies and applications. This indicator uses phase space reconstruction for regime detection, while his combines Lyapunov concepts with HP filtering.
Disclaimer
This indicator is for research and educational purposes only. It does not constitute financial advice or provide direct buy/sell signals. Chaos theory reveals market character, not future prices. Always use proper risk management and combine with your own analysis. Past performance does not guarantee future results.
See markets through the lens of chaos. Trade the regime, not the noise.
Bringing theoretical physics to practical trading through the meditative aesthetics of Mark Rothko
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
SpeedBullish Strategy Confirm V6.2SpeedBullish Strategy Confirm V6.2
SpeedBullish V6.2 is an advanced price-action + indicator-based strategy designed to confirm trend strength and signal entries with high precision. This version builds on the W/M pattern structure and adds dynamic filtering with EMA, MACD Histogram, RSI, ATR, and Volume.
✅ Signal Conditions
🔹 Buy Signal:
Price above EMA10 or EMA15
MACD Histogram crosses above 0
RSI > 50
(Optional) Higher low via Pivot Low
(Optional) ATR > ATR SMA * Multiplier
(Optional) Volume > SMA * Multiplier
🔻 Sell Signal:
Price below EMA10 or EMA15
MACD Histogram crosses below 0
RSI < 50
(Optional) Lower high via Pivot High
(Optional) Confirmed high volatility and volume
⚙️ Strategy Features
MACD Histogram for momentum shift detection
RSI filtering for momentum confirmation
EMA10/15 for trend direction
ATR-based volatility filter
Volume confirmation filter
Dynamic TP/SL + Trailing Stop
Webhook Integration for MT5 auto-trade
Visual signal markers + background highlight
🔔 Alerts
Alerts are sent in JSON format via alert() with the current symbol, action (buy/sell), and price. Webhook endpoint and secret key are configurable.
📈 How to Use
Attach the strategy to any symbol and timeframe
Customize filters and confirmations to fit your market conditions
Enable webhook alerts for integration with your MT5 Expert Advisor or trading bot
Backtest and optimize before live deployment
Support and Resistance Profile with Volatility ClusteringThe indicator begins by looking at recent volatility behavior in the market: it measures the average true range over your chosen “Length” and compares it to the average true range over ten times that period. When volatility over the short window is high relative to longer-term volatility, we mark that period as a “cluster.” As price moves through these clusters—whether in a quiet period or a sudden burst of activity—the script isolates each cluster and examines the sequence of closing prices within it.
Within every cluster, the algorithm next finds the points along the price path that matter most to a human eye, smoothing out minor wobbles and highlighting the peaks and valleys that define the cluster’s shape. It does this by drawing a straight line between the beginning and end of the cluster, then repeatedly snapping the single point that deviates most from that line back onto it and re-interpolating, until it has identified a fixed number of perceptually important points. Those points capture where price really turned or accelerated, stripping away noise so that you see the genuine memory-markers in each volatility episode.
Each of those important points inherits a “weight” based on the cluster’s normalized volatility—essentially how large the average true range in that cluster was relative to its average close. Over your “Main Length for Profile” window, every time one of these weighted points occurs at a particular price level, it adds to a running total in that level’s bin. At the end of the window you see a silhouette of boxes extending to the right of the chart: where boxes are wide, many important points (with high volatility weight) have happened there in the past; where boxes are thin or absent, price memory is light.
For a trader, the value of this profile lies in spotting zones where the market has repeatedly “remembered” price extremes during volatile episodes—those are areas where support or resistance is likely to be strongest. Conversely, gaps in the profile—price levels with little weighted history—suggest frictionless zones. If price enters such a gap, it may move swiftly until it encounters another region of heavy memory. You can use this in several ways: as a filter on breakouts and breakdowns (only trade through a gap when you see sufficient momentum), as a guide for scaling into positions (add when price enters a low-memory zone and tighten stops where memory boxes thicken), or to anticipate where price might pause or reverse (when it reaches a band of wide boxes). By turning raw volatility clusters into a human-readable map of price memory, this tool helps you see at a glance where the market is likely to push or pause—and plan entries, exits, and risk targets accordingly.
Directionality OscillatorDirectionality Oscillator is a simple momentum tool that measures net price displacement against total price activity over a chosen look-back period. It takes today’s closing price minus the close from “len” bars ago and divides that by the sum of all absolute bar-to-bar moves across the same span. The result is a value between –1 and +1, where positive values show that upward moves dominated and negative values show that downward moves prevailed.
To smooth out short-term noise, the indicator applies a five-bar simple moving average to the normalized value. A color gradient—from red at –1, through gray at 0, to green at +1—paints the line, making it easy to see whether bearish or bullish pressure is strongest. Two horizontal lines at the user-defined threshold and its negative mark zones of extreme directional strength. Readings above the positive threshold signal strong bullish momentum, and readings below the negative threshold signal strong bearish momentum.
Traders can watch for crossings above or below these threshold lines as trend confirmations or potential reversal warnings. A cross of the zero line indicates a shift in net directional control and can serve as an early trend-change alert when supported by price action or volume. Because it filters out sideways noise by normalizing against total activity, it highlights sustained directional thrust more clearly than a raw price-change measure.
Eigenvector Centrality Drift (ECD) - Market State Network What is Eigenvector Centrality Drift (ECD)?
Eigenvector Centrality Drift (ECD) is a groundbreaking indicator that applies concepts from network science to financial markets. Instead of viewing price as a simple series, ECD models the market as a dynamic network of “micro-states”—distinct combinations of price, volatility, and volume. By tracking how the influence of these states changes over time, ECD helps you spot regime shifts and transitions in market character before they become obvious in price.
This is not another moving average or momentum oscillator. ECD is inspired by eigenvector centrality—a measure of influence in network theory—and adapts it to the world of price action, volatility, and volume. It’s about understanding which market states are “in control” and when that control is about to change.
Theoretical Foundation
Network Science: In complex systems, nodes (states) and edges (transitions) form a network. Eigenvector centrality measures how influential a node is, not just by its direct connections, but by the influence of the nodes it connects to.
Market Micro-States: Each bar is classified into a “state” based on price change, volatility, and volume. The market transitions between these states, forming a network of possible regimes.
Centrality Drift: By tracking the centrality (influence) of the current state, and how it changes (drifts) over time, ECD highlights when the market’s “center of gravity” is shifting—often a precursor to major moves or regime changes.
How ECD Works
State Classification: Each bar is assigned to one of N market micro-states, based on a weighted combination of normalized price change, volatility, and volume.
Transition Matrix: Over a rolling window, ECD tracks how often the market transitions from each state to every other state, forming a transition probability matrix.
Centrality Calculation: Using a simplified eigenvector approach, ECD calculates the “influence” score for each state, reflecting how central it is to the network of recent market behavior.
Centrality Drift: The indicator tracks the Z-score of the change in centrality for the current state. Rapid increases or decreases, or a shift in the dominant state, signal a potential regime shift.
Dominant State: ECD also highlights which state currently has the highest influence, providing insight into the prevailing market character.
Inputs:
🌐 Market State Configuration
Number of Market States (n_states, default 6): Number of distinct micro-states to track.
3–4: Simple (Up/Down/Sideways)
5–6: Balanced (recommended)
7–9: Complex, more nuanced
Price Change Weight (price_weight, default 0.4):
How much price movement defines a state. Higher = more directional.
Volatility Weight (vol_weight, default 0.3):
How much volatility defines a state. Higher = more regime focus.
Volume Weight (volume_weight, default 0.3):
How much volume defines a state. Higher = more participation focus.
🔗 Network Analysis
Transition Matrix Window (transition_window, default 50): Lookback for building the state transition matrix.
Shorter: Adapts quickly
Longer: More stable
Influence Decay Factor (influence_decay, default 0.85): How much influence propagates through the network.
Higher: Distant transitions matter more
Lower: Only immediate transitions matter
Drift Detection Sensitivity (drift_sensitivity, default 1.5): Z-score threshold for significant centrality drift.
Lower: More signals
Higher: Only major shifts
🎨 Visualization
Show Network Visualization (show_network, default true): Background color and effects based on network structure.
Show Centrality Score (show_centrality, default true): Plots the current state’s centrality measure.
Show Drift Indicator (show_drift, default true): Plots the centrality drift Z-score.
Show State Map (show_state_map, default true): Dashboard showing all state centralities and which is dominant.
Color Scheme (color_scheme, default "Quantum"):
“Quantum”: Cyan/Magenta
“Neural”: Green/Blue
“Plasma”: Yellow/Pink
“Matrix”: Green/Black
Color Schemes
Dynamic gradients reflect the current state’s centrality and drift, using your chosen color palette.
Background network effect: The more central the current state, the more intense the background.
Centrality and drift lines: Color-coded for clarity and regime shift detection.
Visual Logic
Centrality Score Line: Plots the influence of the current state, with glow for emphasis.
Drift Indicator: Histogram of centrality drift Z-score, green for positive, red for negative.
Threshold Lines: Dotted lines mark the drift sensitivity threshold for regime shift alerts.
State Map Dashboard: Top-right panel shows all state centralities, highlights the current and dominant state, and visualizes influence with bars.
Information Panel: Bottom-left panel summarizes current state, centrality, dominant state, drift Z-score, and regime shift status.
How to Use ECD
Centrality Score: High = current state is highly influential; low = state is peripheral.
Drift Z-Score:
Large positive/negative = rapid change in influence, regime shift likely.
Near zero = stable network, no major shift.
Dominant State: The state with the highest centrality is “in control” of the market’s transitions.
State Map: Use to see which states are rising or falling in influence.
Tips:
Use fewer states for simple markets, more for nuanced analysis.
Watch for drift Z-score crossing the threshold—these are your regime shift signals.
Combine with your own system for confirmation.
Alerts:
ECD Regime Shift: Significant centrality drift detected—potential regime change.
ECD State Change: Market state transition occurred.
ECD Dominance Shift: Dominant market state has changed.
Originality & Usefulness
ECD is not a mashup or rehash of standard indicators. It is a novel application of network science and eigenvector centrality to market microstructure, providing a new lens for understanding regime shifts and market transitions. The state network, centrality drift, and dashboard are unique to this script. ECD is designed for anticipation, not confirmation—helping you see the market’s “center of gravity” shift before price action makes it obvious.
Chart Info
Script Name: Eigenvector Centrality Drift (ECD) – Market State Network
Recommended Use: Any asset, any timeframe. Tune parameters to your style.
Disclaimer
This script is for research and educational purposes only. It does not provide financial advice or direct buy/sell signals. Always use proper risk management and combine with your own strategy. Past performance is not indicative of future results.
See the market as a network. Anticipate the shift in influence.
— Dskyz , for DAFE Trading Systems
H4 Swing Grade Checklist English V.1✅ H4 Swing Grade Checklist – Auto Grading for Smart Money Setups
This script helps manual traders assess the quality of a Smart Money swing trade setup by checking 7 key criteria. The system assigns a grade (A+, A, A−, or B) based on how many and which checklist items are met.
📋 Checklist Items (7 total):
✅ Sweep occurs within 4 candles
✅ MSS (strong break candle)
✅ Entry is placed outside the wick of the sweep
✅ FVG is fresh (not previously used)
✅ FVG overlaps Fibonacci 0.705 level
✅ FVG lies within Premium or Discount zone
✅ Entry is placed at 0.705 Fibonacci retracement
🏅 Grading Criteria:
A+ → All 7 checklist items are satisfied
A → Only missing #5 (FVG Overlap with 0.705)
A− → Only missing #4 (FVG Fresh)
B → Only missing #2 (MSS – clear break of structure)
– → Any other combinations / fewer than 6 conditions met
⚙️ Features:
Toggle visibility with one click
Fixed display in top-right or bottom-right of the chart
Color-coded grading logic (Green, Yellow, Orange, Blue)
Clear checklist feedback for trade journaling or evaluation
🚀 Ideal For:
ICT / Smart Money traders
Prop firm evaluations
Swing trade quality control
Reflexivity Resonance Factor (RRF) - Quantum Flow Reflexivity Resonance Factor (RRF) – Quantum Flow
See the Feedback Loops. Anticipate the Regime Shift.
What is the RRF – Quantum Flow?
The Reflexivity Resonance Factor (RRF) – Quantum Flow is a next-generation market regime detector and energy oscillator, inspired by George Soros’ theory of reflexivity and modern complexity science. It is designed for traders who want to visualize the hidden feedback loops between market perception and participation, and to anticipate explosive regime shifts before they unfold.
Unlike traditional oscillators, RRF does not just measure price momentum or volatility. Instead, it models the dynamic feedback between how the market perceives itself (perception) and how it acts on that perception (participation). When these feedback loops synchronize, they create “resonance” – a state of amplified reflexivity that often precedes major market moves.
Theoretical Foundation
Reflexivity: Markets are not just driven by external information, but by participants’ perceptions and their actions, which in turn influence future perceptions. This feedback loop can create self-reinforcing trends or sudden reversals.
Resonance: When perception and participation align and reinforce each other, the market enters a high-energy, reflexive state. These “resonance” events often mark the start of new trends or the climax of existing ones.
Energy Field: The indicator quantifies the “energy” of the market’s reflexivity, allowing you to see when the crowd is about to act in unison.
How RRF – Quantum Flow Works
Perception Proxy: Measures the rate of change in price (ROC) over a configurable period, then smooths it with an EMA. This models how quickly the market’s collective perception is shifting.
Participation Proxy: Uses a fast/slow ATR ratio to gauge the intensity of market participation (volatility expansion/contraction).
Reflexivity Core: Multiplies perception and participation to model the feedback loop.
Resonance Detection: Applies Z-score normalization to the absolute value of reflexivity, highlighting when current feedback is unusually strong compared to recent history.
Energy Calculation: Scales resonance to a 0–100 “energy” value, visualized as a dynamic background.
Regime Strength: Tracks the percentage of bars in a lookback window where resonance exceeded the threshold, quantifying the persistence of reflexive regimes.
Inputs:
🧬 Core Parameters
Perception Period (pp_roc_len, default 14): Lookback for price ROC.
Lower (5–10): More sensitive, for scalping (1–5min).
Default (14): Balanced, for 15min–1hr.
Higher (20–30): Smoother, for 4hr–daily.
Perception Smooth (pp_smooth_len, default 7): EMA smoothing for perception.
Lower (3–5): Faster, more detail.
Default (7): Balanced.
Higher (10–15): Smoother, less noise.
Participation Fast (prp_fast_len, default 7): Fast ATR for immediate volatility.
5–7: Scalping.
7–10: Day trading.
10–14: Swing trading.
Participation Slow (prp_slow_len, default 21): Slow ATR for baseline volatility.
Should be 2–4x fast ATR.
Default (21): Works with fast=7.
⚡ Signal Configuration
Resonance Window (res_z_window, default 50): Z-score lookback for resonance normalization.
20–30: More reactive.
50: Medium-term.
100+: Very stable.
Primary Threshold (rrf_threshold, default 1.5): Z-score level for “Active” resonance.
1.0–1.5: More signals.
1.5: Balanced.
2.0+: Only strong signals.
Extreme Threshold (rrf_extreme, default 2.5): Z-score for “Extreme” resonance.
2.5: Major regime shifts.
3.0+: Only the most extreme.
Regime Window (regime_window, default 100): Lookback for regime strength (% of bars with resonance spikes).
Higher: More context, slower.
Lower: Adapts quickly.
🎨 Visual Settings
Show Resonance Flow (show_flow, default true): Plots the main resonance line with glow effects.
Show Signal Particles (show_particles, default true): Circular markers at active/extreme resonance points.
Show Energy Field (show_energy, default true): Background color based on resonance energy.
Show Info Dashboard (show_dashboard, default true): Status panel with resonance metrics.
Show Trading Guide (show_guide, default true): On-chart quick reference for interpreting signals.
Color Mode (color_mode, default "Spectrum"): Visual theme for all elements.
“Spectrum”: Cyan→Magenta (high contrast)
“Heat”: Yellow→Red (heat map)
“Ocean”: Blue gradients (easy on eyes)
“Plasma”: Orange→Purple (vibrant)
Color Schemes
Dynamic color gradients are used for all plots and backgrounds, adapting to both resonance intensity and direction:
Spectrum: Cyan/Magenta for bullish/bearish resonance.
Heat: Yellow/Red for bullish, Blue/Purple for bearish.
Ocean: Blue gradients for both directions.
Plasma: Orange/Purple for high-energy states.
Glow and aura effects: The resonance line is layered with multiple glows for depth and signal strength.
Background energy field: Darker = higher energy = stronger reflexivity.
Visual Logic
Main Resonance Line: Shows the smoothed resonance value, color-coded by direction and intensity.
Glow/Aura: Multiple layers for visual depth and to highlight strong signals.
Threshold Zones: Dotted lines and filled areas mark “Active” and “Extreme” resonance zones.
Signal Particles: Circular markers at each “Active” (primary threshold) and “Extreme” (extreme threshold) event.
Dashboard: Top-right panel shows current status (Dormant, Building, Active, Extreme), resonance value, energy %, and regime strength.
Trading Guide: Bottom-right panel explains all states and how to interpret them.
How to Use RRF – Quantum Flow
Dormant (💤): Market is in equilibrium. Wait for resonance to build.
Building (🌊): Resonance is rising but below threshold. Prepare for a move.
Active (🔥): Resonance exceeds primary threshold. Reflexivity is significant—consider entries or exits.
Extreme (⚡): Resonance exceeds extreme threshold. Major regime shift likely—watch for trend acceleration or reversal.
Energy >70%: High conviction, crowd is acting in unison.
Above 0: Bullish reflexivity (positive feedback).
Below 0: Bearish reflexivity (negative feedback).
Regime Strength: % of bars in “Active” state—higher = more persistent regime.
Tips:
- Use lower lookbacks for scalping, higher for swing trading.
- Combine with price action or your own system for confirmation.
- Works on all assets and timeframes—tune to your style.
Alerts
RRF Activation: Resonance crosses above primary threshold.
RRF Extreme: Resonance crosses above extreme threshold.
RRF Deactivation: Resonance falls below primary threshold.
Originality & Usefulness
RRF – Quantum Flow is not a mashup of existing indicators. It is a novel oscillator that models the feedback loop between perception and participation, then quantifies and visualizes the resulting resonance. The multi-layered color logic, energy field, and regime strength dashboard are unique to this script. It is designed for anticipation, not confirmation—helping you see regime shifts before they are obvious in price.
Chart Info
Script Name: Reflexivity Resonance Factor (RRF) – Quantum Flow
Recommended Use: Any asset, any timeframe. Tune parameters to your style.
Disclaimer
This script is for research and educational purposes only. It does not provide financial advice or direct buy/sell signals. Always use proper risk management and combine with your own strategy. Past performance is not indicative of future results.
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
