VWAP with 4 EMAsVWAP + 4 EMA Indicator
This indicator combines the Volume Weighted Average Price (VWAP) with three customizable Exponential Moving Averages (EMAs) to provide a comprehensive view of market trend, momentum, and institutional price levels.
Features:
VWAP Line: Plots the intraday VWAP, a key indicator used by institutions to gauge fair value.
3 EMAs: Customizable short, medium, and long-term EMAs help identify trend direction and potential entry/exit points.
Flexible Settings: Easily adjust the EMA lengths and styling to suit your trading strategy.
Clean Visual Layout: Designed for clarity without cluttering your chart.
Use Cases:
Trend Confirmation: Use the VWAP as a dynamic support/resistance level, while EMAs confirm the direction and strength of the trend.
Mean Reversion & Breakouts: Identify when price is stretched from VWAP or crosses key EMAs for potential reversal or breakout trades.
Day Trading & Swing Trading: Suitable for both short-term intraday and multi-day analysis.
This tool is ideal for traders who want to blend volume-weighted price levels with moving average trend signals on a single, efficient chart.
Cerca negli script per "swing trading"
Devel Future 2030🚀 Devel Future for Short & Long Signals
📈 Introducing: Devel Future 2030 – Precision Trend Breakout Indicator
🔹 Trend detection powered by custom SuperTrend logic and break of structure
🔹 Volume filter: Signals only when volume spikes 36%–220% above average
🔹 Auto-calculated SL & TP using the wick of the previous candle – not the body
🔹 Visual trade zones with clean entry, stop-loss, and target display
🔹 Built-in alerts for automation or mobile notifications
🔹 High-risk trades automatically filtered out to protect your capital
💼 Suitable for both scalping and swing trading.
🔥 Smart, reliable, and visually intuitive.
Candle Range Trading (CRT) with Alerts
📌 Description:
The Candle Range Trading (CRT) indicator identifies potential reversal or continuation setups based on specific two-candle price action patterns.
It analyzes pairs of candles to detect Bullish or Bearish CRT patterns and provides visual signals (triangles) and alert notifications to support scalp or swing trading strategies.
🔍 How It Works:
🔻 Bearish CRT Pattern:
Candle 1 is bullish
Candle 2 is bearish
Candle 2's high > Candle 1's high
Candle 2 closes within Candle 1’s range
🔺 Red triangle above candle
🔺 Bullish CRT Pattern:
Candle 1 is bearish
Candle 2 is bullish
Candle 2's low < Candle 1's low
Candle 2 closes within Candle 1’s range
🔻 Green triangle below candle
📈 Visual Features:
🔺 Red triangle = Bearish CRT
🔻 Green triangle = Bullish CRT
📏 Optional box showing CRT High and CRT Low
🔔 Built-in Alerts:
Bullish CRT Alert: "Bullish CRT Pattern Detected"
Bearish CRT Alert: "Bearish CRT Pattern Detected"
Set alerts to get notified instantly when a pattern is detected.
⚠️ Note:
Use in conjunction with trend filters, support/resistance, or volume for best results.
Ideal for scalping or short-term trades.
Avoid trading in choppy or low-volume markets.
⚠️ Disclaimer:
This script was generated with the assistance of ChatGPT by OpenAI and is intended for educational and informational purposes only.
All strategies, alerts, and signals derived from this indicator should be thoroughly backtested and validated before using in live trading.
Trading involves substantial risk, and past performance is not indicative of future results. The author and ChatGPT bear no responsibility for any trading losses or financial decisions made using this script.
Users are solely responsible for the risks associated with their trading actions. Always apply proper risk management and perform your own due diligence before making any financial decisions.
Paul_BDT Osc. MACD, ADX, CHOP, RSI & CVD🔧 Overview
Modular multi-oscillator engine designed for actionable and filtered trading signals. It combines the power of MACD, ADX, CHOP, RSI, and CVD, integrates advanced divergence detection, a multi-timeframe dashboard, and a built-in risk management system.
⸻
🚨 Alert System
Alerts are organized by signal type, oscillator used, and timeframe block, with precision controls for filtering and sensitivity.
1. Oscillator Alerts (Osc.)
Triggers ▲ / ▼ triangle markers based on trend momentum shifts detected on the selected oscillator:
• MACD: triggers when histogram crosses 0 with bullish or bearish slope
• ADX: triggers on directional breakout with increasing trend strength
• CHOP: signals trend resumption after choppy market phase
• RSI: breakout from dynamic support/resistance using pivot detection
• CVD: shift in buy/sell pressure based on aggregated volume delta
✅ All signals optionally trigger on bar close only (if enabled)
2. Divergence Alerts (Div.)
Automatic detection of:
• 🔼 Regular Divergences
• Bullish: Lower lows in price, higher lows in oscillator
• Bearish: Higher highs in price, lower highs in oscillator
• 🔁 Hidden Divergences
• Hidden Bullish: Higher lows in price, lower lows in oscillator
• Hidden Bearish: Lower highs in price, higher highs in oscillator
Alert trigger logic:
• Divergences only trigger if confirmed by price action:
→ breakout from wick or close beyond BB/RSI dynamic bands
• Alerts are non-repeating (fires only on signal change)
🔔 divergeUP and divergeDN are fired when divergence AND price condition are met.
3. Reversal Alerts (Rev.)
Strict combo alert:
• reverseUP = divergeUP AND bullish wick breakout
• reverseDN = divergeDN AND bearish wick breakout
🧠 These are high-conviction signals, ideal for swing entries or reversion trades.
📊 Multi-Timeframe Support (4 Blocks)
4 independent blocks:
• Scalp, Intra, Swing, Custom
• Each block accepts 3 sorted timeframes
• You can individually enable:
• Oscillator alerts
• Divergences
• Reversals
Example:
• Scalp: RSI only, no divergence
• Intra: CVD + reversal only
• Swing: MACD + divergence + reversal
Each timeframe is dynamically sorted and shown in a structured dashboard grid (TF01 to TF12), making the multi-timeframe readout seamless.
⸻
⚙️ Additional Features
• Full visual panel with color-coded trend indicators
• Take Profit/Exit Alerts available on a custom timeframe
• Built-in Money Management:
• % or USD risk
• Configurable R/R ratio
• Minimum PnL threshold (filter out low-return setups)
⸻
✅ Best Use Cases
• High-frequency scalping (1s–1min) with real-time oscillator breakouts
• Structured intraday/swing planning using divergence + reversal logic
• Manual backtesting and alert-based discretionary entries
⸻⸻⸻⸻⸻⸻⸻⸻⸻⸻⸻⸻⸻⸻
🧠 Fonctionnalités
• Oscillateurs personnalisables : activez un indicateur à la fois (MACD, ADX, CHOP, RSI, ou CVD) pour une analyse ciblée et lisible.
• Détection des divergences :
• Divergences classiques (bullish/bearish),
• Divergences cachées (hidden bullish/bearish),
• Filtres avancés pour ne détecter que les signaux pertinents (crossover/crossunder + break de mèche).
• Multi-timeframes :
• Jusqu’à 4 blocs configurables (scalp, intra, swing, custom),
• Tri automatique des UT,
• Alertes différenciées par bloc et par type de signal.
• Visualisation modulaire :
• Tableau de synthèse personnalisable, affichant l’état de chaque indicateur par UT,
• Affichage hors graphique ou directement sur le chart,
• Couleurs dynamiques pour les signaux haussiers, baissiers ou neutres.
• Gestion du risque intégrée :
• Paramétrez le risque en % du capital ou en valeur absolue (USD),
• Ratio risk/reward configurable pour filtrer les signaux,
• Seuil de profit minimum (PnL) configurable pour filtrer les signaux.
• Support de volumes agrégés multi-exchange pour CVD : compatible avec les plateformes crypto (BITGET, BINANCE, etc).
⸻
⚙️ Personnalisation
• Choix du type de moyenne mobile (EMA, RMA, VWAP, etc.).
• Activation sélective des signaux (Oscillateur, Divergence, Renversement) pour chaque bloc de timeframes.
⸻
📈 Alertes intégrées
• Compatibles avec les alertes automatiques de TradingView,
• Détection de signaux d’entrée (achat/vente), divergences, renversements,
• Configuration des alertes par type de signal et par timeframe (scalp/intra/swing/custom).
⸻
🔍 Utilisations recommandées
• Scalping haute fréquence (1s à 1min),
• Intraday en multi-UT (5 à 30min),
• Swing trading (1H à 1D),
• Analyse technique avancée sur crypto, indices, forex ou actions.
⸻
📌 Conclusion
Ce script combine précision algorithmique et flexibilité de personnalisation.
Time Based Range# Time Based Range
**A fully customizable session-based range indicator for intraday and daily trading analysis**
## Overview
The Time Based Range indicator identifies and visualizes key price levels from any user-defined time session. Whether you're trading the London open, New York session, or any custom timeframe, this indicator helps you identify crucial support and resistance levels formed during specific trading periods.
## Key Features
### 🕒 **Flexible Session Configuration**
- Customize any time range (e.g., 05:00-13:00, 20:00-02:00)
- Select specific days of the week (Sunday=1 through Saturday=7)
- Works on any timeframe from 1-minute to daily charts
### 📊 **Three Display Modes**
**OHLC Mode:**
- Shows Open, High, Low, Close, and Midpoint lines
- Fully customizable line colors, styles, and widths
- Optional labels with custom text
- Toggle individual lines on/off
**Range Mode:**
- Displays High, Low, and Midpoint lines extending into the future
- Session background box for visual clarity
- Configurable extension length in hours
- Clean range-based analysis
**Mitigate Mode:**
- Horizontal pivot lines that extend until price "mitigates" (touches) them
- Session background box
- Lines automatically stop extending when price reaches the level
- Perfect for ICT-style analysis
### 🚨 **Advanced Alert System**
**Breakout Alerts:**
- Notifies when price breaks above session high or below session low
- Real-time notifications for range expansion
**Liquidity Sweep Alerts:**
- Detects when price briefly breaks a level but closes back inside the range
- Configurable lookback period for sweep detection
- Helps identify false breakouts and liquidity grabs
**Equilibrium Rejection Alerts:**
- Monitors price reaction at the session midpoint
- Detects strong rejections with wick formations
- Configurable sensitivity threshold
### 🎨 **Full Customization**
- Individual color settings for all lines and boxes
- Multiple line style options (Solid, Dashed, Dotted)
- Adjustable line widths and transparency
- Custom label text and positioning
- Session limit control (1-10 sessions displayed)
## Use Cases
### Day Trading
- Mark key levels from overnight sessions
- Identify London/New York opening ranges
- Track Asian session highs and lows
### Swing Trading
- Daily range analysis
- Multi-day level identification
- Key support/resistance from specific periods
### ICT/SMC Trading
- Liquidity pool identification
- Fair value gap analysis
- Market structure understanding
## Technical Specifications
- **Maximum Sessions:** 1-10 (user configurable)
- **Time Format:** 24-hour (HHMM-HHMM)
- **Day Selection:** Individual day toggles (1=Sunday through 7=Saturday)
- **Alert Types:** 4 different alert conditions
- **Drawing Objects:** Optimized with automatic cleanup
- **Performance:** Efficient array management prevents chart lag
## Best Practices
1. **Start Simple:** Begin with OHLC mode to understand session dynamics
2. **Use Alerts:** Enable notifications for key level interactions
3. **Combine Modes:** Switch between modes based on market conditions
4. **Optimize Settings:** Adjust colors and styles for your chart theme
5. **Multiple Timeframes:** Use different sessions for various trading strategies
## Compatibility
- Works on all TradingView chart types
- Compatible with all asset classes (Forex, Stocks, Crypto, Futures)
- Optimized for both light and dark themes
- Mobile-friendly display
---
*This indicator helps traders identify high-probability trading zones based on time-specific price action. Always combine with proper risk management and additional analysis methods.*
Hull Moving Average RibbonGradient Wave HMA - Multi-Ribbon Hull Moving Average System
Overview
The Gradient Wave HMA is an advanced technical indicator that transforms Alan Hull's Hull Moving Average (HMA) into a dynamic multi-layered ribbon system. Unlike traditional moving average ribbons that use simple or exponential calculations, this indicator applies Hull's innovative lag-reduction formula across 12 different timeframes simultaneously, creating a visually striking gradient effect that flows with market momentum.
Technical Foundation
This indicator is built upon the Hull Moving Average, developed by Alan Hull in 2005. The HMA uses a weighted moving average calculation designed to almost eliminate lag while maintaining curve smoothness:
HMA = WMA(2*WMA(n/2) − WMA(n), sqrt(n))
Credit: Alan Hull (www.alanhull.com)
Key Features
Multi-Period Ribbon Structure
12 individual HMA lines with customizable periods
Preset configurations for different trading styles:
Fast: 3-30 period range (scalping/intraday)
Swing: 8-55 period range (swing trading)
Position: 20-100 period range (position trading)
Custom: User-defined periods
2. Neon Gradient Visualization
Bullish Gradient: Transitions from blue-purple to hot purple
Bearish Gradient: Flows from hot pink to purple-pink
Each line has a unique color in the spectrum
Gradient fills between lines create depth and visual flow
3. Advanced Alert System
Trend Reversal Alerts: Notifies when ribbon changes direction
Price Breakout Alerts: Triggers when price crosses the ribbon
Compression Alerts: Signals potential breakouts during consolidation
Expansion Alerts: Confirms strong trending conditions
Momentum Surge Alerts: Catches explosive moves early
How It Works
The indicator calculates 12 Hull Moving Averages, each with a different period length. The trend direction is determined by the middle HMA (6th line), which triggers the color change across the entire ribbon. When trending up, the ribbon displays a purple gradient; when trending down, it shifts to a pink gradient.
Trading Applications
1. Trend Identification
Ribbon color indicates overall trend direction
All lines moving in sync confirms strong trend
Mixed signals suggest choppy or transitioning markets
2. Dynamic Support/Resistance
In uptrends, the ribbon acts as moving support
In downtrends, it provides resistance levels
Multiple layers offer various strength levels
3. Momentum Analysis
Expanding ribbon = Increasing momentum
Contracting ribbon = Decreasing momentum/consolidation
Ribbon angle indicates trend strength
4. Trading Example
Advantages Over Traditional MAs
Reduced Lag: Hull's formula provides faster response than SMA/EMA ribbons
Visual Clarity: Gradient effect makes trend changes immediately visible
Multiple Timeframes: 12 periods provide comprehensive market view
Flexibility: Presets adapt to different trading styles
Best Practices
Use higher timeframes (4H, Daily) for position trading
Combine with volume indicators for confirmation
Watch for ribbon compression before major moves
Consider overall market conditions when interpreting signals
Customization Options
Adjust individual HMA periods
Fine-tune transparency for different backgrounds
Choose between WMA and EMA base calculations
The Gradient Wave HMA combines Alan Hull's breakthrough moving average formula with modern visualization techniques to create a powerful trend-following tool that's both technically sophisticated and visually intuitive.
ZigZag ProZigZag Pro is a precise market structure indicator that automatically detects two independent ZigZag patterns and highlights breakouts whenever significant highs or lows are breached.
The indicator calculates two separate ZigZag structures in real time. ZigZag1 captures the broader market swings and is ideal for trend or swing trading. ZigZag2 is optional and reacts more quickly – perfect for intraday or scalping setups. Both layers are fully customizable in terms of depth, color, and line width.
What makes this tool especially useful: whenever a previous swing high (for long trades) or swing low (for short trades) is broken, the indicator draws a horizontal breakout line on the chart. This makes it easy to spot structural breakouts and take advantage of potential momentum moves.
ZigZag Pro is designed for traders who rely on clean, rule-based market structure — whether you're trading classic breakouts, smart money concepts, or simply want a clearer view of trend shifts. The visuals are minimal, responsive, and suitable for any timeframe.
CryptoNeo - Crypto Stablecoin MatrixThe CryptoNeo – Crypto Stablecoin Matrix is a forward-looking indicator that decodes broad crypto market sentiment by analyzing how stablecoins behave across spot and futures markets.
Stablecoins are the lifeblood of the crypto ecosystem, and how they move can offer early insight into future market direction. This tool leverages that behavior to forecast potential price action across major cryptocurrencies like BTC, ETH, SOL, DOGE, and other large-cap coins that tend to move in sync with the broader market.
Originally derived from a suite of alpha signals developed for a systematic crypto trading algorithm, this indicator compresses advanced stablecoin flow analytics into a clear and intuitive visual format — designed specifically for discretionary traders.
It is optimized for trading on the 30-minute to 4-hour timeframes, where the nuances of capital flow are most actionable. Whether you’re swing trading majors or scouting key pivot points, this tool provides a fresh edge rooted in stablecoin dynamics.
The Matrix is composed of four core components that signal changes in sentiment, capital flow, and market positioning:
1. Stablecoin Futures Flow (Bullish/Bearish)
Detects shifts in leveraged positioning in the futures market based on proprietary flow dynamics.
🟩 Green squares = bullish futures flow (long bias)
🟥 Red squares = bearish futures flow (short bias)
Helps identify directional sentiment through futures-driven stablecoin movement.
2. Stablecoin Spot Flow (Bullish/Bearish)
Analyzes momentum in spot market stablecoin activity to reveal potential accumulation or distribution.
🟢 Green circles = bullish spot flow (buying pressure)
🔴 Red circles = bearish spot flow (selling pressure)
Offers early signals of demand or profit-taking pressure.
3. Futures Oversold/Overbought Level 1
Identifies early signs of exhaustion or trend slowing based on leveraged market conditions.
🟢 Green diamonds = early oversold signal
🔴 Red diamonds = early overbought signal
Useful for catching subtle turning points or slowing momentum.
4. Futures Oversold/Overbought Level 2
Flags rare and extreme positioning events that may precede major reversals.
🟢 Large green diamonds = deep oversold condition
🔴 Large red diamonds = deep overbought condition
Highlights moments of extreme imbalance or sentiment peaks.
Customization & Flexibility
Adjustable sensitivity settings allow you to fine-tune:
Bullish and bearish Spot and Futures Flow
Thresholds for Level 1 and Level 2 Overbought/Oversold signals
This ensures traders can align signal responsiveness with their trading style and market conditions.
Best Used For:
Swing trading crypto majors (BTC, ETH, SOL, DOGE, etc.)
Timeframes between 30 minutes and 4 hours
Identifying trend reversals and accumulation zones
Tracking macro market sentiment using stablecoin behavior
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
Lorentzian Classification - Advanced Trading DashboardLorentzian Classification - Relativistic Market Analysis
A Journey from Theory to Trading Reality
What began as fascination with Einstein's relativity and Lorentzian geometry has evolved into a practical trading tool that bridges theoretical physics and market dynamics. This indicator represents months of wrestling with complex mathematical concepts, debugging intricate algorithms, and transforming abstract theory into actionable trading signals.
The Theoretical Foundation
Lorentzian Distance in Market Space
Traditional Euclidean distance treats all feature differences equally, but markets don't behave uniformly. Lorentzian distance, borrowed from spacetime geometry, provides a more nuanced similarity measure:
d(x,y) = Σ ln(1 + |xi - yi|)
This logarithmic formulation naturally handles:
Scale invariance: Large price moves don't overwhelm small but significant patterns
Outlier robustness: Extreme values are dampened rather than dominating
Non-linear relationships: Captures market behavior better than linear metrics
K-Nearest Neighbors with Relativistic Weighting
The algorithm searches historical market states for patterns similar to current conditions. Each neighbor receives weight inversely proportional to its Lorentzian distance:
w = 1 / (1 + distance)
This creates a "gravitational" effect where closer patterns have stronger influence on predictions.
The Implementation Challenge
Creating meaningful market features required extensive experimentation:
Price Features: Multi-timeframe momentum (1, 2, 3, 5, 8 bar lookbacks) Volume Features: Relative volume analysis against 20-period average
Volatility Features: ATR and Bollinger Band width normalization Momentum Features: RSI deviation from neutral and MACD/price ratio
Each feature undergoes min-max normalization to ensure equal weighting in distance calculations.
The Prediction Mechanism
For each current market state:
Feature Vector Construction: 12-dimensional representation of market conditions
Historical Search: Scan lookback period for similar patterns using Lorentzian distance
Neighbor Selection: Identify K nearest historical matches
Outcome Analysis: Examine what happened N bars after each match
Weighted Prediction: Combine outcomes using distance-based weights
Confidence Calculation: Measure agreement between neighbors
Technical Hurdles Overcome
Array Management: Complex indexing to prevent look-ahead bias
Distance Calculations: Optimizing nested loops for performance
Memory Constraints: Balancing lookback depth with computational limits
Signal Filtering: Preventing clustering of identical signals
Advanced Dashboard System
Main Control Panel
The primary dashboard provides real-time market intelligence:
Signal Status: Current prediction with confidence percentage
Neighbor Analysis: How many historical patterns match current conditions
Market Regime: Trend strength, volatility, and volume analysis
Temporal Context: Real-time updates with timestamp
Performance Analytics
Comprehensive tracking system monitors:
Win Rate: Percentage of successful predictions
Signal Count: Total predictions generated
Streak Analysis: Current winning/losing sequence
Drawdown Monitoring: Maximum equity decline
Sharpe Approximation: Risk-adjusted performance estimate
Risk Assessment Panel
Multi-dimensional risk analysis:
RSI Positioning: Overbought/oversold conditions
ATR Percentage: Current volatility relative to price
Bollinger Position: Price location within volatility bands
MACD Alignment: Momentum confirmation
Confidence Heatmap
Visual representation of prediction reliability:
Historical Confidence: Last 10 periods of prediction certainty
Strength Analysis: Magnitude of prediction values over time
Pattern Recognition: Color-coded confidence levels for quick assessment
Input Parameters Deep Dive
Core Algorithm Settings
K Nearest Neighbors (1-20): More neighbors create smoother but less responsive signals. Optimal range 5-8 for most markets.
Historical Lookback (50-500): Deeper history improves pattern recognition but reduces adaptability. 100-200 bars optimal for most timeframes.
Feature Window (5-30): Longer windows capture more context but reduce sensitivity. Match to your trading timeframe.
Feature Selection
Price Changes: Essential for momentum and reversal detection Volume Profile: Critical for institutional activity recognition Volatility Measures: Key for regime change detection Momentum Indicators: Vital for trend confirmation
Signal Generation
Prediction Horizon (1-20): How far ahead to predict. Shorter horizons for scalping, longer for swing trading.
Signal Threshold (0.5-0.9): Confidence required for signal generation. Higher values reduce false signals but may miss opportunities.
Smoothing (1-10): EMA applied to raw predictions. More smoothing reduces noise but increases lag.
Visual Design Philosophy
Color Themes
Professional: Corporate blue/red for institutional environments Neon: Cyberpunk cyan/magenta for modern aesthetics
Matrix: Green/red hacker-inspired palette Classic: Traditional trading colors
Information Hierarchy
The dashboard system prioritizes information by importance:
Primary Signals: Largest, most prominent display
Confidence Metrics: Secondary but clearly visible
Supporting Data: Detailed but unobtrusive
Historical Context: Available but not distracting
Trading Applications
Signal Interpretation
Long Signals: Prediction > threshold with high confidence
Look for volume confirmation
- Check trend alignment
- Verify support levels
Short Signals: Prediction < -threshold with high confidence
Confirm with resistance levels
- Check for distribution patterns
- Verify momentum divergence
- Market Regime Adaptation
Trending Markets: Higher confidence in directional signals
Ranging Markets: Focus on reversal signals at extremes
Volatile Markets: Require higher confidence thresholds
Low Volume: Reduce position sizes, increase caution
Risk Management Integration
Confidence-Based Sizing: Larger positions for higher confidence signals
Regime-Aware Stops: Wider stops in volatile regimes
Multi-Timeframe Confirmation: Align signals across timeframes
Volume Confirmation: Require volume support for major signals
Originality and Innovation
This indicator represents genuine innovation in several areas:
Mathematical Approach
First application of Lorentzian geometry to market pattern recognition. Unlike Euclidean-based systems, this naturally handles market non-linearities.
Feature Engineering
Sophisticated multi-dimensional feature space combining price, volume, volatility, and momentum in normalized form.
Visualization System
Professional-grade dashboard system providing comprehensive market intelligence in intuitive format.
Performance Tracking
Real-time performance analytics typically found only in institutional trading systems.
Development Journey
Creating this indicator involved overcoming numerous technical challenges:
Mathematical Complexity: Translating theoretical concepts into practical code
Performance Optimization: Balancing accuracy with computational efficiency
User Interface Design: Making complex data accessible and actionable
Signal Quality: Filtering noise while maintaining responsiveness
The result is a tool that brings institutional-grade analytics to individual traders while maintaining the theoretical rigor of its mathematical foundation.
Best Practices
- Parameter Optimization
- Start with default settings and adjust based on:
Market Characteristics: Volatile vs. stable
Trading Timeframe: Scalping vs. swing trading
Risk Tolerance: Conservative vs. aggressive
Signal Confirmation
Never trade on Lorentzian signals alone:
Price Action: Confirm with support/resistance
Volume: Verify with volume analysis
Multiple Timeframes: Check higher timeframe alignment
Market Context: Consider overall market conditions
Risk Management
Position Sizing: Scale with confidence levels
Stop Losses: Adapt to market volatility
Profit Targets: Based on historical performance
Maximum Risk: Never exceed 2-3% per trade
Disclaimer
This indicator is for educational and research purposes only. It does not constitute financial advice or guarantee profitable trading results. The Lorentzian classification system reveals market patterns but cannot predict future price movements with certainty. Always use proper risk management, conduct your own analysis, and never risk more than you can afford to lose.
Market dynamics are inherently uncertain, and past performance does not guarantee future results. This tool should be used as part of a comprehensive trading strategy, not as a standalone solution.
Bringing the elegance of relativistic geometry to market analysis through sophisticated pattern recognition and intuitive visualization.
Thank you for sharing the idea. You're more than a follower, you're a leader!
@vasanthgautham1221
Trade with precision. Trade with insight.
— Dskyz , for DAFE Trading Systems
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
Malama's Heikin CountMalama's Heikin Count is a Pine Script indicator designed to enhance price action analysis by combining Heikin Ashi candlestick calculations with a normalized measurement of upper and lower shadow sizes. The indicator overlays Heikin Ashi candles on the chart and displays the relative sizes of upper and lower shadows as numerical labels (scaled from 1 to 10) for candles within the last two days, starting from 9:00 AM each day. This tool aims to help traders identify the strength of price movements and potential reversals by quantifying the significance of candlestick shadows in the context of Heikin Ashi’s smoothed price data. It is particularly useful for day traders and swing traders who rely on candlestick patterns to gauge market sentiment and momentum.
The indicator solves the problem of interpreting raw candlestick data by providing a smoothed visualization through Heikin Ashi candles and a simplified, numerical representation of shadow sizes. This allows traders to quickly assess whether a candle’s upper or lower shadow indicates strong buying or selling pressure, aiding in decision-making for entries, exits, or reversals.
Originality and Usefulness
Originality: While Heikin Ashi candles are a well-known technique for smoothing price data and reducing noise, Malama's Heikin Count introduces a novel feature by calculating and normalizing the sizes of upper and lower shadows relative to the total candle height. Unlike standard Heikin Ashi implementations, which focus solely on candle body trends, this indicator quantifies shadow proportions and presents them on a standardized 1–10 scale. This normalization makes it easier for traders to compare shadow significance across different timeframes and assets without needing to manually interpret raw measurements. The restriction of shadow size labels to the last two days from 9:00 AM ensures relevance for active trading sessions, avoiding clutter from older data.
Usefulness: The indicator is particularly valuable for traders who combine candlestick pattern analysis with trend-following strategies. By integrating Heikin Ashi’s trend-smoothing capabilities with shadow size metrics, it provides a unique perspective on market dynamics. For example, large upper shadows (high normalized values) may indicate rejection at resistance levels, while large lower shadows may suggest support or buying pressure. Unlike other open-source Heikin Ashi indicators, which typically focus only on candle plotting, this script’s shadow size normalization and time-based filtering offer a distinctive tool for intraday and short-term trading strategies.
Detailed Methodology ("How It Works")
The core logic of Malama's Heikin Count revolves around three main components: Heikin Ashi candle calculations, shadow size analysis, and time-based filtering for label display. Below is a breakdown of how these components work together:
Heikin Ashi Candle Calculations:
The script calculates Heikin Ashi candles to smooth price data and reduce market noise, making trends easier to identify.
Formulas:
haClose = (open + high + low + close) / 4: The Heikin Ashi close is the average of the current bar’s open, high, low, and close prices.
haOpen = na(haOpen ) ? (open + close) / 2 : (haOpen + haClose ) / 2: The Heikin Ashi open is either the average of the current bar’s open and close (for the first bar) or the average of the previous Heikin Ashi open and close.
haHigh = max(high, max(haOpen, haClose)): The Heikin Ashi high is the maximum of the current bar’s high, Heikin Ashi open, and Heikin Ashi close.
haLow = min(low, min(haOpen, haClose)): The Heikin Ashi low is the minimum of the current bar’s low, Heikin Ashi open, and Heikin Ashi close.
These calculations produce smoothed candles that emphasize trend direction and reduce the impact of short-term price fluctuations.
Shadow Size Analysis:
The script calculates the upper and lower shadows of each Heikin Ashi candle to assess market sentiment.
Formulas:
upperShadow = haHigh - max(haClose, haOpen): Measures the length of the upper shadow (distance from the top of the candle body to the high).
lowerShadow = min(haClose, haOpen) - haLow: Measures the length of the lower shadow (distance from the bottom of the candle body to the low).
totalHeight = haHigh - haLow: Calculates the total height of the candle (from high to low).
upperShadowPercentage = (upperShadow / totalHeight) * 100: Converts the upper shadow length to a percentage of the total candle height.
lowerShadowPercentage = (lowerShadow / totalHeight) * 100: Converts the lower shadow length to a percentage of the total candle height.
Normalization: The normalizeShadowSize function scales the shadow percentages to a 1–10 range using math.round(value / 10). This ensures that shadow sizes are presented in an easily interpretable format, where 1 represents a very small shadow (less than 10% of the candle height) and 10 represents a very large shadow (90–100% of the candle height). The normalization caps values between 1 and 10 for consistency.
Time-Based Filtering:
The script only displays shadow size labels for candles within the last two days, starting from 9:00 AM each day. This is achieved by calculating a start timestamp using timestamp(year(timenow), month(timenow), dayofmonth(timenow) - daysBack, startHour, startMinute), where daysBack = 2, startHour = 9, and startMinute = 0.
The condition time >= startTime ensures that labels are only plotted for candles within this time window, keeping the chart relevant for recent trading activity and avoiding clutter from older data.
Signal Generation:
The script does not generate explicit buy or sell signals but provides visual cues through shadow size labels. Large upper shadow sizes (e.g., 8–10) may indicate selling pressure or resistance, while large lower shadow sizes may suggest buying pressure or support. Traders can use these metrics in conjunction with the Heikin Ashi candle colors (green for bullish, red for bearish) to make trading decisions.
Strategy Results and Risk Management
Backtesting: The script is an indicator and does not include built-in backtesting or strategy logic for generating buy/sell signals. As such, it does not assume specific commission, slippage, or account sizing parameters. Traders using this indicator should incorporate it into their existing strategies, applying their own risk management rules.
Risk Management Guidance:
Traders can use the shadow size labels to inform risk management decisions. For example, a large upper shadow (e.g., 8–10) at a resistance level may prompt a trader to set a tighter stop-loss above the candle’s high, anticipating a potential reversal. Conversely, a large lower shadow at a support level may suggest a wider stop-loss below the low to account for volatility.
Default settings (e.g., 2-day lookback, 9:00 AM start) are designed to focus on recent price action, which is suitable for intraday and short-term swing trading. Traders should combine the indicator with other tools (e.g., support/resistance levels, trendlines) to define risk limits, such as risking 5–10% of equity per trade.
The indicator does not enforce specific risk management settings, allowing traders to customize their approach based on their risk tolerance and trading style.
User Settings and Customization
The script includes the following user-customizable inputs:
Days Back (daysBack = 2):
Description: Controls the lookback period for displaying shadow size labels. The default value of 2 means labels are shown for candles within the last two days.
Impact: Increasing daysBack extends the time window for label display, which may be useful for longer-term analysis but could clutter the chart. Decreasing it focuses on more recent data, ideal for intraday trading.
Start Hour (startHour = 9) and Start Minute (startMinute = 0):
Description: Defines the start time of the trading day (default is 9:00 AM). Labels are only shown for candles after this time each day within the lookback period.
Impact: Traders can adjust these settings to align with their preferred trading session (e.g., 9:30 AM for U.S. market open). Changing the start time shifts the time window for label display, affecting which candles are analyzed.
These settings allow traders to tailor the indicator to their trading timeframe and session preferences, ensuring that the shadow size labels remain relevant to their analysis.
Visualizations and Chart Setup
The indicator plots the following elements on the chart:
Heikin Ashi Candles:
Plotted using plotcandle(haOpen, haClose, haHigh, haLow), these candles overlay the standard price chart.
Color Coding: Green candles indicate bullish momentum (Heikin Ashi close ≥ open), while red candles indicate bearish momentum (Heikin Ashi close < open).
These candles provide a smoothed view of price trends, making it easier to identify trend direction and continuations.
Shadow Size Labels:
Upper Shadow Labels: Displayed above each candle at the Heikin Ashi high, showing the normalized upper shadow size (1–10). These labels are green with white text and use the label.style_label_down style for clear visibility.
Lower Shadow Labels: Displayed below each candle at the Heikin Ashi low, showing the normalized lower shadow size (1–10). These labels are red with white text and use the label.style_label_up style.
Labels are only shown for candles within the last two days from 9:00 AM, ensuring that only recent and relevant data is visualized.
Debugging Labels (Optional):
A blue label at the bottom of the chart displays the text "Upper: Lower: " for each candle, showing both shadow sizes for debugging purposes. This can be removed or commented out if not needed, as it is primarily for development use.
The visualizations are designed to be minimal and focused, ensuring that traders can quickly interpret the Heikin Ashi trend and shadow size metrics without unnecessary clutter. The use of color-coded candles and labels enhances readability, while the time-based filtering keeps the chart clean and relevant.
Information Asymmetry Gradient (IAG) What is the Information Asymmetry Gradient (IAG)?
The Information Asymmetry Gradient (IAG) is a unique market regime and imbalance detector that quantifies the subtle, directional “information flow” in price and volume. Inspired by information theory and market microstructure, IAG is designed to help traders spot the early buildup of conviction or surprise—the kind of hidden imbalance that often precedes major price moves.
Unlike traditional volume or momentum indicators, IAG focuses on the efficiency and directionality of information transfer: how much “informational energy” is being revealed by up-moves versus down-moves, normalized by price movement. It’s not just about net flow, but about the quality and asymmetry of that flow.
Theoretical Foundation
Information Asymmetry: Markets move when new information is revealed. If one side (buyers or sellers) is consistently more “informationally efficient” per unit of price change, an imbalance is building—even if price hasn’t moved much yet.
Gradient: By tracking the rate of change (gradient) between fast and slow information flows, IAG highlights when a subtle imbalance is accelerating.
Volatility of Asymmetry: Sudden spikes in the volatility of information asymmetry often signal regime uncertainty or the approach of a “surprise” move.
How IAG Works
Directional Information Content: For each bar, IAG estimates the “information per unit of price change” for both up-moves and down-moves, using volume and price action.
Asymmetry Calculation: Computes the difference (or ratio) between up and down information content, revealing directional bias.
Gradient Detection: Calculates both a fast and slow EMA of the asymmetry, then measures their difference (the “gradient”), normalized as a Z-score.
Volatility of Asymmetry: Tracks the standard deviation of asymmetry over a rolling window, with Z-score normalization to spot “information shocks.”
Flow Strength: Quantifies the conviction of the current information flow on a 0–100 scale.
Regime Detection: Flags “extreme” asymmetry, “building” flow, and “high volatility” states.
Inputs:
🌌 Core Asymmetry Parameters
Fast Information Period (short_len, default 8): EMA period for detecting immediate information flow changes.
5–8: Scalping (1–5min)
8–12: Day trading (15min–1hr)
12–20: Swing trading (4hr+)
Slow Information Period (long_len, default 34): EMA period for baseline information context. Should be 3–5x fast period.
Default (34): Fibonacci number, stable for most assets.
Gradient Smoothing (gradient_smooth, default 3): Smooths the gradient calculation.
1–2: Raw, responsive
3–5: Balanced
6–10: Very smooth
📊 Asymmetry Method
Calculation Mode (calc_mode, default "Weighted"):
“Simple”: Basic volume split by direction
“Weighted”: Volume × price movement (default, most robust)
“Logarithmic”: Log-scaled for large moves
Use Ratio (show_ratio, default false):
“Difference”: UpInfo – DownInfo (additive)
“Ratio”: UpInfo / DownInfo (multiplicative, better for comparing volatility regimes)
🌊 Volatility Analysis
Volatility Window (stdev_len, default 21): Lookback for measuring asymmetry volatility.
Volatility Alert Level (vol_threshold, default 1.5): Z-score threshold for volatility alerts.
🎨 Visual Settings
Color Theme (color_theme, default "Starry Night"):
Van Gogh-inspired palettes:
“Starry Night”: Deep blues and yellows
“Sunflowers”: Warm yellows and browns
“Café Terrace”: Night blues and warm lights
“Wheat Field”: Golden and sky blue
Show Swirl Effects (show_swirls, default true): Adds swirling background to visualize information turbulence.
Show Signal Stars (show_stars, default true): Star markers at significant asymmetry points.
Show Info Dashboard (show_dashboard, default true): Top-right panel with current metrics and market state.
Show Flow Visualization (show_flow, default true): Main gradient line with artistic effects.
Color Schemes
Dynamic color gradients adapt to both the direction and intensity of the information gradient, using Van Gogh-inspired palettes for visual clarity and artistic flair.
Glow and aura effects: The main line is layered with glows for depth and to highlight strong signals.
Swirl background: Visualizes the “turbulence” of information flow, darker and more intense as flow strength and volatility rise.
Visual Logic
Main Gradient Line: Plots the normalized information gradient (Z-score), color-coded by direction and intensity.
Glow/Aura: Multiple layers for visual depth and to highlight strong signals.
Threshold Zones: Dotted lines and filled areas mark “Building” and “Extreme” asymmetry zones.
Volatility Ribbon: Area plot of volatility Z-score, highlighting information shocks.
Signal Stars: Circular markers at each “Extreme” event, color-coded for bullish/bearish; cross markers for volatility spikes.
Dashboard: Top-right panel shows current status (Extreme, Building, High Volatility, Balanced), gradient value, flow strength, information balance, and volatility status.
Trading Guide: Bottom-left panel explains all states and how to interpret them.
How to Use IAG
🌟 EXTREME: Major information imbalance—potential for explosive move or reversal.
🌙 BUILDING: Asymmetry is forming—watch for a breakout or trend acceleration.
🌪️ HIGH VOLATILITY: Information flow is unstable—expect regime uncertainty or “surprise” moves.
☁️ BALANCED: No clear bias—market is in equilibrium.
Positive Gradient: Bullish information flow (buyers have the edge).
Negative Gradient: Bearish information flow (sellers have the edge).
Flow >66%: Strong conviction—crowd is acting in unison.
Volatility Spike: Regime uncertainty—be alert for sudden moves.
Tips:
- Use lower periods for scalping, higher for swing trading.
- “Weighted” mode is most robust for most assets.
- Combine with price action or your own system for confirmation.
- Works on all assets and timeframes—tune to your style.
Alerts
IAG Extreme Asymmetry: Extreme information asymmetry detected.
IAG Building Flow: Information flow building.
IAG High Volatility: Information volatility spike.
IAG Bullish/Bearish Extreme: Directional extreme detected.
Originality & Usefulness
IAG is not a mashup of existing indicators. It is a novel approach to quantifying the “surprise” or “conviction” element in market moves, focusing on the efficiency and directionality of information transfer per unit of price change. The multi-layered color logic, artistic visual effects, and regime dashboard are unique to this script. IAG is designed for anticipation, not confirmation—helping you see subtle imbalances before they become obvious in price.
Chart Info
Script Name: Information Asymmetry Gradient (IAG) – Starry Night
Recommended Use: Any asset, any timeframe. Tune parameters to your style.
Disclaimer
This script is for research and educational purposes only. It does not provide financial advice or direct buy/sell signals. Always use proper risk management and combine with your own strategy. Past performance is not indicative of future results.
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
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
Math by Thomas Swing RangeMath by Thomas Swing Range is a simple yet powerful tool designed to visually highlight key swing levels in the market based on a user-defined lookback period. It identifies the highest high, lowest low, and calculates the midpoint between them — creating a clear range for swing trading strategies.
These levels can help traders:
Spot potential support and resistance zones
Analyze price rejection near range boundaries
Frame mean-reversion or breakout setups
The indicator continuously updates and extends these lines into the future, making it easier to plan and manage trades with visual clarity.
🛠️ How to Use
Add to Chart:
Apply the indicator on any timeframe and asset (works best on higher timeframes like 1H, 4H, or Daily).
Configure Parameters:
Lookback Period: Number of candles used to detect the highest high and lowest low. Default is 20.
Extend Lines by N Bars: Number of future bars the levels should be projected to the right.
Interpret Lines:
🔴 Red Line: Swing High (Resistance)
🟢 Green Line: Swing Low (Support)
🔵 Blue Line: Midpoint (Mean level — useful for equilibrium-based strategies)
Trade Ideas:
Bounce trades from swing high/low zones.
Breakout confirmation if price closes strongly outside the range.
Reversion trades if price moves toward the midpoint after extreme moves.
Realtime ATR-Based Stop Loss Numerical OverlayRealtime ATR-Based Stop Loss Numerical Overlay
A simple, effective tool for dynamic risk management based on ATR (Average True Range) without adding cluttered and distracting lines all over your chart.
📌 Description
This script plots a real-time stop loss level using the Average True Range (ATR) on your chart, helping you set consistent, volatility-based stops. It supports both:
✅ Current chart timeframe
✅ Custom fixed timeframe inputs (1m, 5m, 15m, 1h, etc.)
The stop level is calculated as:
Stop = ATR × Multiplier
and updates in real-time. An overlay table displays on the bottom-right of your chart with the calculated stop value in a clean, simple way.
⚙️ Settings
ATR Timeframe Source:
Choose between using the current chart's timeframe or a fixed one (e.g. 5, 15, 60, D, etc).
ATR Length:
Period used to calculate the ATR (default is 14).
Stop Loss Multiplier:
Multiplies the ATR value to define your stop (e.g., 1.5 × ATR).
Wait for Timeframe Closes:
If enabled, the ATR value waits for the selected timeframe’s candle to close before updating. If unselected, it will update in real time.
🛠️ How to Use
Add this script to your chart from your indicators list.
Configure your desired timeframe, ATR length, and multiplier in the settings panel.
Use the value shown in the table overlay as your suggested stop loss distance from entry.
Adjust your position sizing accordingly to fit your risk tolerance.
This tool is especially useful for traders looking for adaptive risk management that evolves with market volatility — whether scalping intraday or swing trading.
💡 Pro Tip
The ATR stop can also be used to dynamically trail your stop behind price movement.
Dual Stochastic Enhanced (with Presets giua64)Script Title: Dual Stochastic Enhanced (with Presets giua64)
Overview:
This indicator enhances the traditional Dual Stochastic strategy, aiming to provide more filtered and potentially reliable trading signals. By integrating dynamic overbought/oversold levels via Bollinger Bands on the slow stochastic, a trend filter based on a moving average, momentum confirmation via RSI, and user-friendly selectable presets, "Dual Stochastic Enhanced" seeks to offer a more robust approach to identifying potential entry points.
Key Features:
Dual Stochastics: Utilizes a slow stochastic (configurable, e.g., 14 periods) as a context filter and a fast stochastic (configurable, e.g., 5 periods) as a signal trigger.
Bollinger Bands on Slow Stochastic: Instead of fixed overbought/oversold levels (80/20), Bollinger Bands are applied to the %K line of the slow stochastic. This creates dynamic zones that adapt to the stochastic's own volatility.
Trend Filter: A moving average (configurable type and length, e.g., EMA 100 as seen in the example chart for general context) on the price helps filter signals, allowing only trades aligned with the prevailing trend.
RSI Confirmation: An RSI oscillator (configurable length, e.g., 14 periods) is used to confirm momentum. Signals require the RSI to cross certain thresholds to validate the strength of the move.
User Presets: Includes presets for "Scalping," "Intraday," and "Swing trading," which quickly set all key parameters to suit different styles and timeframes. A "Custom" option is also available for full manual configuration.
Clear Visual Signals: Long (green) and Short (red) arrows appear on the chart when all entry conditions are met.
Active Zone Highlighting: The background of the indicator panel changes color (green or red) when "active zone" conditions (a combination of stochastics, trend, and RSI) are favorable.
Information Panel: A table in the top-right corner of the indicator panel displays the current status of the selected preset, trend filter, RSI value, and stochastic levels.
Signal Logic:
A LONG signal is generated when:
The fast stochastic %K crosses above its %D line.
The slow stochastic %K line is below its lower Bollinger Band (dynamic oversold condition).
The fast stochastic %K line is also in a low area (e.g., <25) to confirm the trigger is not premature.
The closing price is above the trend moving average (uptrend).
The RSI is above its long confirmation level (e.g., >40), indicating sufficient bullish momentum.
A SHORT signal is generated when:
The fast stochastic %K crosses below its %D line.
The slow stochastic %K line is above its upper Bollinger Band (dynamic overbought condition).
The fast stochastic %K line is also in a high area (e.g., >75).
The closing price is below the trend moving average (downtrend).
The RSI is below its short confirmation level (e.g., <60), indicating sufficient bearish momentum.
How to Use:
Select a Preset suitable for your trading style and the timeframe you are analyzing (e.g., Scalping for M1-M15, Intraday for M5-H1, Swing for H4-D1).
Alternatively, choose "Custom" and manually adjust all parameters (stochastic lengths, smoothing, Bollinger Bands, Moving Average, RSI, confirmation thresholds).
Observe the Information Panel for a quick understanding of the current conditions.
Evaluate the arrow signals, always considering the broader market context, price action, and any other confluences (supports/resistances, chart patterns).
The background highlighting can help quickly identify periods where conditions are aligned for potential trades.
Disclaimer:
This script is provided for educational and informational purposes only. Trading involves significant risk, and past performance is not indicative of future results. Always thoroughly test any strategy or indicator on historical data and on a demo account before risking real capital. The author assumes no responsibility for any losses incurred from the use of this script.
Author: giua64
EMA with ColoringDescription:
The "EMA with Coloring" indicator plots a customizable Exponential Moving Average (EMA) on the price chart, with its color dynamically changing based on the Ichimoku Cloud's trend signals. This tool helps traders identify trend direction and potential trading opportunities by combining the simplicity of an EMA with the robust trend analysis of the Ichimoku system. The EMA changes color to reflect bullish (uptrend), bearish (downtrend), or neutral (in-cloud) market conditions, making it easier to spot trend shifts and trade setups.
How It Works:
EMA Calculation: The indicator calculates an EMA based on the user-defined period (default: 9). The EMA is plotted directly on the price chart, overlaying candlesticks or bars.
Ichimoku Coloring Logic: The EMA’s color is determined by an underlying Ichimoku Cloud system:
Green (Uptrend): When the price is above the Ichimoku Cloud and bullish conditions are confirmed (e.g., Conversion Line above Base Line and rising momentum).
Red (Downtrend): When the price is below the Ichimoku Cloud and bearish conditions are confirmed (e.g., Conversion Line below Base Line and falling momentum).
ATR Whipsaw Protection: The indicator uses an Average True Range (ATR) filter to reduce false signals during choppy markets, ensuring more reliable trend identification.
Customizable Settings:
EMA Length: Adjust the period of the EMA (default: 9) to make it more or less sensitive to price changes.
Uptrend/Downtrend Colors: Choose from Green, Red, or Blue for the EMA’s color in bullish or bearish conditions.
Transparency: Set the EMA’s opacity (default: 0, fully opaque) for better visibility on the chart.
How to Trade It:
Trend Identification:
Bullish (Green EMA): Indicates a strong uptrend. Look for buying opportunities when the EMA turns green, especially if the price is above the cloud and the EMA is sloping upward.
Bearish (Red EMA): Indicates a strong downtrend. Consider selling or shorting when the EMA turns red, particularly if the price is below the cloud and the EMA is sloping downward.
Neutral (Gray EMA): Signals a range-bound market. Avoid trend-based trades and consider range trading or waiting for a breakout.
Entry Signals:
Long Entry: Enter a buy trade when the EMA changes from gray or red to green, and the price breaks above a recent high or key resistance, confirming bullish momentum.
Short Entry: Enter a sell/short trade when the EMA changes from gray or green to red, and the price breaks below a recent low or key support, confirming bearish momentum.
Exit Signals:
Exit long trades when the EMA turns gray or red, indicating a potential trend reversal or consolidation.
Exit short trades when the EMA turns gray or green, suggesting the downtrend may be weakening.
Risk Management:
Use stop-losses below recent swing lows (for longs) or above swing highs (for shorts) to protect against unexpected reversals.
Combine with support/resistance levels, candlestick patterns, or other indicators (e.g., RSI, MACD) for confirmation.
Tips:
Adjust the EMA length to suit your trading style: shorter periods (e.g., 5–10) for scalping/day trading, longer periods (e.g., 20–50) for swing trading.
Test the indicator on your preferred timeframe and asset to optimize settings.
Settings:
EMA Settings:
EMA Length: Default is 9. Increase for smoother trends, decrease for more sensitivity.
EMA Color Settings:
Uptrend EMA Color: Choose Green, Red, or Blue (default: Green) for bullish conditions.
Downtrend EMA Color: Choose Green, Red, or Blue (default: Red) for bearish conditions.
EMA Color Transparency: Default is 0 (fully opaque). Adjust to 10–100 for partial transparency if needed.
Notes:
Best used on timeframes where trends are clear (e.g., 1H, 4H, Daily).
The Ichimoku logic runs in the background with fixed parameters optimized for reliability, so only the EMA and color settings are adjustable.
Always backtest and practice on a demo account before using in live trading.
Stochastic RSI with Alerts# Stochastic RSI with Alerts - User Manual
## 1. Overview
This enhanced Stochastic RSI indicator identifies overbought/oversold conditions with visual signals and customizable alerts. It features:
- Dual-line Stoch RSI (K & D)
- Threshold-based buy/sell signals
- Configurable alert system
- Customizable parameters
## 2. Installation
1. Open TradingView chart
2. Open Pine Editor (📈 icon at bottom)
3. Copy/paste the full code
4. Click "Add to Chart"
## 3. Input Parameters
### 3.1 Core Settings
| Parameter | Default | Description |
|-----------|---------|-------------|
| K | 3 | Smoothing period for %K line |
| D | 3 | Smoothing period for %D line |
| RSI Length | 14 | RSI calculation period |
| Stochastic Length | 14 | Lookback period for Stoch calculation |
| RSI Source | Close | Price source for RSI calculation |
### 3.2 Signal Thresholds
| Parameter | Default | Description |
|-----------|---------|-------------|
| Upper Limit | 80 | Sell signal threshold (overbought) |
| Lower Limit | 20 | Buy signal threshold (oversold) |
### 3.3 Alert Settings
| Parameter | Default | Description |
|-----------|---------|-------------|
| Enable Buy Alerts | True | Toggle buy notifications |
| Enable Sell Alerts | True | Toggle sell notifications |
| Custom Alert Message | Empty | Additional text for alerts |
## 4. Signal Logic
### 4.1 Buy Signal (Green ▲)
Triggers when:
\text{%K crossover %D} \quad AND \quad (\text{%K ≤ Lower Limit} \quad OR \quad \text{%D ≤ Lower Limit})
### 4.2 Sell Signal (Red ▼)
Triggers when:
\text{%K crossunder %D} \quad AND \quad (\text{%K ≥ Upper Limit} \quad OR \quad \text{%D ≥ Upper Limit})
## 5. Alert System
### 5.1 Auto-Generated Alerts
The script automatically creates these alert conditions:
- **Buy Signal Alert**: Triggers on valid buy signals
- **Sell Signal Alert**: Triggers on valid sell signals
Alert messages include:
- Signal type (Buy/Sell)
- Current %K and %D values
- Custom message (if configured)
### 5.2 Alert Configuration
**Method 1: Script-Generated Alerts**
1. Hover over any signal marker
2. Click the 🔔 icon
3. Select trigger conditions:
- "Buy Signal Alert"
- "Sell Signal Alert"
**Method 2: Manual Setup**
1. Open Alert creation window
2. Condition: Select "Stoch RSI Alerts"
3. Choose:
- "Buy Signal Alert" for long entries
- "Sell Signal Alert" for exits/shorts
## 6. Customization Tips
### 6.1 Threshold Adjustment
// For day trading (tighter ranges)
upperLimit = 75
lowerLimit = 25
// For swing trading (wider ranges)
upperLimit = 85
lowerLimit = 15
### 6.2 Visual Modifications
Change signal markers via:
- `style=` : Try `shape.labelup`, `shape.flag`, etc.
- `color=` : Use hex codes (#FF00FF) or named colors
- `size=` : `size.tiny` to `size.huge`
## 7. Recommended Use Cases
1. **Mean Reversion Strategies**: Pair with support/resistance levels
2. **Trend Confirmation**: Filter with 200EMA direction
3. **Divergence Trading**: Compare with price action
## 8. Limitations
- Works best in ranging markets
- Combine with volume analysis for confirmation
- Not recommended as standalone strategy
---
This documentation follows technical writing best practices with:
- Clear parameter tables
- Mathematical signal logic
- Visual hierarchy
- Practical examples
- Usage recommendations
Levels & Flow📌 Overview
Levels & Flow is a visual trading tool that combines daily pivot levels with a dynamic EMA ribbon to help traders identify structure, momentum, and key decision zones in the market.
This script is designed for discretionary traders who rely on clean visual cues for intraday and swing trading strategies.
⚙️ Key Features
Daily Pivot, Support, and Resistance Lines
Automatically plots the daily pivot level based on the previous day’s OHLC data, along with calculated support and resistance levels.
Fibonacci Retracement Levels
Two dashed lines above and below the pivot represent the retracement of the pivot-resistance and pivot-support range, forming the boundaries of the “no-trade zone.”
No-Trade Zone (Shaded Box)
A gray shaded box between the two Fibonacci levels to visually mark a high-chop/low-conviction zone.
Trend-Based Candle Coloring (Current Day Only)
Candles are colored green if the close is above the pivot, red if below (only on the current trading day).
Bullish/Bearish Trend Label
A small table in the bottom-right corner displays “Bullish” or “Bearish” depending on whether price is above or below the pivot.
20-EMA Gradient Ribbon
A stack of 20 EMAs, each smoothed and color-coded from blue to green to reflect short- to long-term trend alignment.
Cumulative EMA with Adaptive Weighting
An intelligent moving average line that adjusts weight distribution among the 20 EMAs based on recent predictive accuracy using a learning rate and lookback period.
🧠 How It Works
📍 Levels
The script calculates daily pivot, resistance, and support levels using standard formulas:
Pivot = (High + Low + Close) / 3
Resistance = (2 × Pivot) – Low
Support = (2 × Pivot) – High
These levels update each day and extend 143 bars to the right.
📏 Fib Lines
Fib Up = Pivot + (Resistance – Pivot) × 0.382
Fib Down = Pivot – (Pivot – Support) × 0.382
These lines form the “no-trade zone” box.
📈 EMA Ribbon
20 EMAs starting from the user-defined Base Length, each incremented by 1
Each EMA is smoothed using the Smoothing Period
Color-coded from blue to green for intuitive visual flow
Filled between EMAs to visualize trend strength and alignment
🧠 Cumulative EMA Learning
Each EMA’s historical error is calculated over a Lookback Period
Lower-error EMAs receive higher weight; weights are normalized to sum to 1
The result is a cumulative EMA that adapts based on historical predictive power
🔧 User Inputs
Input
Base EMA Length: Sets the period for the shortest EMA (default: 20)
Smoothing Period: Smooths all EMAs and the cumulative EMA
Lookback for Learning: Number of bars to evaluate EMA prediction accuracy
Learning Rate: Adjusts how quickly weights shift in favor of more accurate EMAs
✅ How to Use It
Use the pivot level to define directional bias.
Watch for price breakouts above resistance or breakdowns below support to consider entry.
Avoid trading inside the shaded zone, where direction is less reliable.
Use the EMA ribbon gradient to confirm short/long alignment.
The cumulative EMA helps define trend with noise reduction.
🧪 Best For
Intraday traders who want to blend structure with flow
Swing traders needing clean daily levels with dynamic confirmation
Anyone looking to avoid choppy zones and improve visual clarity
⚠️ Disclaimer
This script is for educational and informational purposes only. It does not constitute financial advice or a trading recommendation. Always test scripts in simulation or on demo accounts before live use. Use at your own risk.
PhenLabs - Market Fluid Dynamics📊 Market Fluid Dynamics -
Version: PineScript™ v6
📌 Description
The Market Fluid Dynamics - Phen indicator is a new thinking regarding market analysis by modeling price action, volume, and volatility using a fluid system. It attempts to offer traders control over more profound market forces, such as momentum (speed), resistance (thickness), and buying/selling pressure. By visualizing such dynamics, the script allows the traders to decide on the prevailing market flow, its power, likely continuations, and zones of calmness and chaos, and thereby allows improved decision-making.
This measure avoids the usual difficulty of reconciling multiple, often contradictory, market indications by including them within a single overarching model. It moves beyond traditional binary indicators by providing a multi-dimensional view of market behavior, employing fluid dynamic analogs to describe complex interactions in an accessible manner.
🚀 Points of Innovation
Integrated Fluid Dynamics Model: Combines velocity, viscosity, pressure, and turbulence into a single indicator.
Normalized Metrics: Uses ATR and other normalization techniques for consistent readings across different assets and timeframes.
Dynamic Flow Visualization: Main flow line changes color and intensity based on direction and strength.
Turbulence Background: Visually represents market stability with a gradient background, from calm to turbulent.
Comprehensive Dashboard: Provides an at-a-glance summary of key fluid dynamic metrics.
Multi-Layer Smoothing: Employs several layers of EMA smoothing for a clearer, more responsive main flow line.
🔧 Core Components
Velocity Component: Measures price momentum (first derivative of price), normalized by ATR. It indicates the speed and direction of price changes.
Viscosity Component: Represents market resistance to price changes, derived from ATR relative to its historical average. Higher viscosity suggests it’s harder for prices to move.
Pressure Component: Quantifies the force created by volume and price range (close - open), normalized by ATR. It reflects buying or selling pressure.
Turbulence Detection: Calculates a Reynolds number equivalent to identify market stability, ranging from laminar (stable) to turbulent (chaotic).
Main Flow Indicator: Combines the above components, applying sensitivity and smoothing, to generate a primary signal of market direction and strength.
🔥 Key Features
Advanced Smoothing Algorithm: Utilizes multiple EMA layers on the raw flow calculation for a fluid and responsive main flow line, reducing noise while maintaining sensitivity.
Gradient Flow Coloring: The main flow line dynamically changes color from light to deep blue for bullish flow and light to deep red for bearish flow, with intensity reflecting flow strength. This provides an immediate visual cue of market sentiment and momentum.
Turbulence Level Background: The chart background changes color based on calculated turbulence (from calm gray to vibrant orange), offering an intuitive understanding of market stability and potential for erratic price action.
Informative Dashboard: A customizable on-screen table displays critical metrics like Flow State, Flow Strength, Market Viscosity, Turbulence, Pressure Force, Flow Acceleration, and Flow Continuity, allowing traders to quickly assess current market conditions.
Configurable Lookback and Sensitivity: Users can adjust the base lookback period for calculations and the sensitivity of the flow to viscosity, tailoring the indicator to different trading styles and market conditions.
Alert Conditions: Pre-defined alerts for flow direction changes (positive/negative crossover of zero line) and detection of high turbulence states.
🎨 Visualization
Main Flow Line: A smoothed line plotted below the main chart, colored blue for bullish flow and red for bearish flow. The intensity of the color (light to dark) indicates the strength of the flow. This line crossing the zero line can signal a change in market direction.
Zero Line: A dotted horizontal line at the zero level, serving as a baseline to gauge whether the market flow is positive (bullish) or negative (bearish).
Turbulence Background: The indicator pane’s background color changes based on the calculated turbulence level. A calm, almost transparent gray indicates low turbulence (laminar flow), while a more vibrant, semi-transparent orange signifies high turbulence. This helps traders visually assess market stability.
Dashboard Table: An optional table displayed on the chart, showing key metrics like ‘Flow State’, ‘Flow Strength’, ‘Market Viscosity’, ‘Turbulence’, ‘Pressure Force’, ‘Flow Acceleration’, and ‘Flow Continuity’ with their current values and qualitative descriptions (e.g., ‘Bullish Flow’, ‘Laminar (Stable)’).
📖 Usage Guidelines
Setting Categories
Show Dashboard - Default: true; Range: true/false; Description: Toggles the visibility of the Market Fluid Dynamics dashboard on the chart. Enable to see key metrics at a glance.
Base Lookback Period - Default: 14; Range: 5 - (no upper limit, practical limits apply); Description: Sets the primary lookback period for core calculations like velocity, ATR, and volume SMA. Shorter periods make the indicator more sensitive to recent price action, while longer periods provide a smoother, slower signal.
Flow Sensitivity - Default: 0.5; Range: 0.1 - 1.0 (step 0.1); Description: Adjusts how much the market viscosity dampens the raw flow. A lower value means viscosity has less impact (flow is more sensitive to raw velocity/pressure), while a higher value means viscosity has a greater dampening effect.
Flow Smoothing - Default: 5; Range: 1 - 20; Description: Controls the length of the EMA smoothing applied to the main flow line. Higher values result in a smoother flow line but with more lag; lower values make it more responsive but potentially noisier.
Dashboard Position - Default: ‘Top Right’; Range: ‘Top Right’, ‘Top Left’, ‘Bottom Right’, ‘Bottom Left’, ‘Middle Right’, ‘Middle Left’; Description: Determines the placement of the dashboard on the chart.
Header Size - Default: ‘Normal’; Range: ‘Tiny’, ‘Small’, ‘Normal’, ‘Large’, ‘Huge’; Description: Sets the text size for the dashboard header.
Values Size - Default: ‘Small’; Range: ‘Tiny’, ‘Small’, ‘Normal’, ‘Large’; Description: Sets the text size for the metric values in the dashboard.
✅ Best Use Cases
Trend Identification: Identifying the dominant market flow (bullish or bearish) and its strength to trade in the direction of the prevailing trend.
Momentum Confirmation: Using the flow strength and acceleration to confirm the conviction behind price movements.
Volatility Assessment: Utilizing the turbulence metric to gauge market stability, helping to adjust position sizing or avoid choppy conditions.
Reversal Spotting: Watching for divergences between price and flow, or crossovers of the main flow line above/below the zero line, as potential reversal signals, especially when combined with changes in pressure or viscosity.
Swing Trading: Leveraging the smoothed flow line to capture medium-term market swings, entering when flow aligns with the desired trade direction and exiting when flow weakens or reverses.
Intraday Scalping: Using shorter lookback periods and higher sensitivity to identify quick shifts in flow and turbulence for short-term trading opportunities, particularly in liquid markets.
⚠️ Limitations
Lagging Nature: Like many indicators based on moving averages and lookback periods, the main flow line can lag behind rapid price changes, potentially leading to delayed signals.
Whipsaws in Ranging Markets: During periods of low volatility or sideways price action (high viscosity, low flow strength), the indicator might produce frequent buy/sell signals (whipsaws) as the flow oscillates around the zero line.
Not a Standalone System: While comprehensive, it should be used in conjunction with other forms of analysis (e.g., price action, support/resistance levels, other indicators) and not as a sole basis for trading decisions.
Subjectivity in Interpretation: While the dashboard provides quantitative values, the interpretation of “strong” flow, “high” turbulence, or “significant” acceleration can still have a subjective element depending on the trader’s strategy and risk tolerance.
💡 What Makes This Unique
Fluid Dynamics Analogy: Its core strength lies in translating complex market interactions into an intuitive fluid dynamics framework, making concepts like momentum, resistance, and pressure easier to visualize and understand.
Market View: Instead of focusing on a single aspect (like just momentum or just volatility), it integrates multiple factors (velocity, viscosity, pressure, turbulence) to provide a more comprehensive picture of market conditions.
Adaptive Visualization: The dynamic coloring of the flow line and the turbulence background provide immediate, adaptive visual feedback that changes with market conditions.
🔬 How It Works
Price Velocity Calculation: The indicator first calculates price velocity by measuring the rate of change of the closing price over a given ‘lookback’ period. The raw velocity is then normalized by the Average True Range (ATR) of the same lookback period. Normalization enables comparison of momentum between assets or timeframes by scaling for volatility. This is the direction and speed of initial price movement.
Viscosity Calculation: Market ‘viscosity’ or resistance to price movement is determined by looking at the current ATR relative to its longer-term average (SMA of ATR over lookback * 2). The further the current ATR is above its average, the lower the viscosity (less resistance to price movement), and vice-versa. The script inverts this relationship and bounds it so that rising viscosity means more resistance.
Pressure Force Measurement: A ‘pressure’ variable is calculated as a function of the ratio of current volume to its simple moving average, multiplied by the price range (close - open) and normalized by ATR. This is designed to measure the force behind price movement created by volume and intraday price thrusts. This pressure is smoothed by an EMA.
Turbulence State Evaluation: A equivalent ‘Reynolds number’ is calculated by dividing the absolute normalized velocity by the viscosity. This is the proclivity of the market to move in a chaotic or orderly fashion. This ‘reynoldsValue’ is smoothed with an EMA to get the ‘turbulenceState’, which indicates if the market is laminar (stable), transitional, or turbulent.
Main Flow Derivation: The ‘rawFlow’ is calculated by taking the normalized velocity, dampening its impact based on the ‘viscosity’ and user-input ‘sensitivity’, and orienting it by the sign of the smoothed ‘pressureSmooth’. The ‘rawFlow’ is then put through multiple layers of exponential moving average (EMA) smoothing (with ‘smoothingLength’ and derived values) to reach the final ‘mainFlow’ line. The extensive smoothing is designed to give a smooth and clear visualization of the overall market direction and magnitude.
Dashboard Metrics Compilation: Additional metrics like flow acceleration (derivative of mainFlow), and flow continuity (correlation between close and volume) are calculated. All primary components (Flow State, Strength, Viscosity, Turbulence, Pressure, Acceleration, Continuity) are then presented in a user-configurable dashboard for ease of monitoring.
💡 Note:
The “Market Fluid Dynamics - Phen” indicator is designed to offer a unique perspective on market behavior by applying principles from fluid dynamics. It’s most effective when used to understand the underlying forces driving price rather than as a direct buy/sell signal generator in isolation. Experiment with the settings, particularly the ‘Base Lookback Period’, ‘Flow Sensitivity’, and ‘Flow Smoothing’, to find what best suits your trading style and the specific asset you are analyzing. Always combine its insights with robust risk management practices.
