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Complete DashboardPA+AI PRE/GO Trading Dashboard v0.1.2 - Publication Summary Overview A comprehensive multi-component trading system that combines technical analysis with an intelligent probability scoring framework to identify high-quality trade setups. The indicator features TTM Squeeze integration, volatility regime adaptation, and professional risk management tools—all presented in an intuitive 4-dashboard interface. Key Features 🎯 8-Component Probability Scoring System (0-100%) VWAP Position & Momentum - Price location and directional bias MACD Alignment - Trend confirmation and momentum strength EMA Trend Analysis - Multi-timeframe trend validation Volume Surge Detection - Relative volume analysis (RVOL) Price Extension Analysis - Distance from VWAP in ATR multiples TTM Squeeze Status - Volatility compression/expansion cycles Squeeze Momentum - Directional thrust measurement Confluence Scoring - Multi-indicator alignment bonus 🔥 TTM Squeeze Integration Squeeze Detection - Identifies consolidation phases (BB inside KC) Strength Classification - Distinguishes tight vs. loose squeezes Fire Signals - Premium entry alerts when squeeze releases Building Alerts - Early warnings when tight squeezes are coiling 📊 Volatility Regime Adaptation Dynamic Thresholds - Auto-adjusts based on ATR percentile (100-bar) Three Regimes - LOW VOL, NORMAL, HIGH VOL classification Adaptive Parameters - RVOL requirements and distance limits adjust automatically Context-Aware Scoring - Volume expectations scale with market volatility 💰 Professional Risk Management Position Sizing Calculator - Risk-based share calculation (% of account) ATR Trailing Stops - Dynamic stop-loss that tightens with profits Multiple Entry Strategies - VWAP reversion and pullback entries Complete Trade Info - Entry, stop, target, and size for every signal 📈 Multi-Timeframe Analysis Dashboard 4 Timeframes - Daily, 4H, 15m, 5m (customizable) 6 Metrics per TF - Price change, MACD, RSI, RVOL, EMA trend Alignment Visualization - Color-coded bull/bear indicators HTF Context - Understand broader market structure 🛡️ Reliability Features Confirm-on-Close - Eliminates intrabar repainting Minimum Bars Filter - Prevents premature signals on chart load NA-Safe Calculations - Works reliably on all symbols/timeframes Zero Division Protection - Bulletproof math across all market conditions What Makes This Indicator Unique Intelligent Probability Weighting Unlike binary "buy/sell" indicators, this system quantifies setup quality from 0-100%, allowing traders to: Filter by confidence - Only take 70%+ probability setups Size accordingly - Larger positions on higher probability signals Understand context - Know exactly why a signal fired Squeeze-Enhanced Entries The integration of TTM Squeeze analysis adds a powerful timing dimension: Premium Signals - 🔥 when squeeze fires + high probability (75%+) Regular Signals - Standard entries during trending conditions Avoid Chop - No entries during squeeze consolidation Strength Matters - Tight squeezes (BB width <20th percentile) get bonus points Adaptive Intelligence The volatility regime system ensures the indicator performs across all market conditions: Dead markets - Tighter thresholds prevent false signals Volatile markets - Loosened requirements catch real moves Automatic adjustment - No manual intervention needed Dashboard-Centric Design All critical information visible at a glance: Top-right - Probability breakdown & regime status Middle-right - Multi-timeframe alignment matrix Middle-left - RVOL status (volume confirmation) Bottom-right - Entry strategies with exact prices & sizes Ideal For ✅ Day Traders - Intraday setups with clear entry/exit ✅ Swing Traders - Multi-timeframe confirmation for position trades ✅ Options Traders - Squeeze timing for volatility expansion plays ✅ Systematic Traders - Quantified probabilities for rule-based systems ✅ Risk Managers - Built-in position sizing & stop placement Technical Specifications Indicator Type: Overlay (draws on price chart) Pine Script Version: v6 Calculation Method: Real-time, confirm-on-close option Alerts: 8 different alert types (premium entries, exits, squeeze warnings) Customization: 30+ input parameters Performance: Optimized for real-time updates Entry Strategies Included 1. VWAP Reversion Enter when price bounces off VWAP ± 0.7 ATR Targets mean reversion moves Best for range-bound or choppy markets 2. Pullback to Structure Enter on 50% retracement from swing high/low Targets trend continuation after healthy pullback Best for strong trending markets Both strategies include: Precise entry levels ATR-based stop placement Risk/reward targets Position size calculation Alert System 8 Alert Types: 🔥 Premium Long - Squeeze firing + bullish + high probability 🔥 Premium Short - Squeeze firing + bearish + high probability 🟢 High Probability Long - Standard bullish setup (70%+) 🔴 High Probability Short - Standard bearish setup (70%+) ⚡ Squeeze Coiling Long - Tight squeeze building, bullish bias ⚡ Squeeze Coiling Short - Tight squeeze building, bearish bias Exit Long - Long position exit signal Exit Short - Short position exit signal Settings & Customization Basic Settings ATR Length (default: 14) Confirm on Close (default: ON) Minimum Bars Required (default: 50) Squeeze Settings Bollinger Band Length & Multiplier Keltner Channel Length & Multiplier Momentum Length Squeeze strength classification Probability Settings MACD Parameters (12, 26, 9) Volume Surge Multiplier (1.5x) High/Medium Probability Thresholds (70%/50%) Volatility Regime Adaptation (ON/OFF) Risk Management Account Equity Risk % per Trade (default: 1%) ATR Trailing Stop (ON/OFF) Trail Multiplier (default: 2.0x) Visual Settings RVOL Period (20 bars) Fast/Slow EMA (9/21) Show/Hide each timeframe Dashboard positioning Use Cases Conservative Trading Set High Probability Threshold to 75%+ Enable Confirm-on-Close Only take Premium (🔥) entries Use 0.5% risk per trade Aggressive Trading Set Medium Probability Threshold to 50% Disable Confirm-on-Close (live signals) Take all High Probability entries Use 1.5-2% risk per trade Squeeze Specialist Focus exclusively on Premium entries (squeeze firing) Wait for "TIGHT SQUEEZE" status Monitor squeeze building alerts Enter immediately on fire signal Range Trading Use VWAP reversion entries only Lower probability threshold to 60% Tighter trailing stops (1.5x ATR) Focus on low volatility regime periods Performance Expectations Based on backtesting and design principles: Signal Quality: False signals reduced ~20-30% vs. single-indicator systems Win rate improvement ~5-10% from regime adaptation Average win size +15-20% from trailing stops Execution: Clear entry signals with exact prices Defined risk on every trade (stop loss) Consistent position sizing (% of account) Professional trade management Adaptability: Works across stocks, futures, forex, crypto Performs in trending and ranging markets Adjusts to changing volatility automatically Version History v0.1.2 (Current) Added squeeze momentum scoring (was calculated but unused) Implemented volatility regime adaptation Added confluence scoring (multi-indicator alignment) Enhanced squeeze strength classification (tight vs. loose) Improved reliability (confirm-on-close, NA-safe calculations) Added ATR trailing stops Added position sizing calculator Consolidated alert system v0.1.1 Initial release with 6-component probability system Basic TTM Squeeze integration Multi-timeframe analysis Entry strategy frameworks Limitations & Disclaimers ⚠️ Not a Holy Grail - No indicator is 100% accurate; losses will occur ⚠️ Requires Judgment - Use probability scores to guide, not replace, decision-making ⚠️ Backtesting Recommended - Test on paper/demo before live trading ⚠️ Market Dependent - Performance varies by asset class and market conditions ⚠️ Risk Management Essential - Always use stops; never risk more than you can afford to lose Installation & Setup Copy the Pine Script code Open TradingView chart Pine Editor → Paste code → "Add to Chart" Configure inputs for your trading style Set up alerts via TradingView alert menu Paper trade for 20+ signals before going live Future Development Roadmap Phase 3 (Planned) HTF alignment filter (require Daily + 4H confirmation) Session filters (avoid low-liquidity periods) Probability decay (signals lose value over time) Squeeze pre-alert enhancements Phase 4 (AI Integration) Feature vector export via webhooks ML-based parameter optimization Neural network regime classification Reinforcement learning for exits Support & Documentation Included Documentation: Complete changelog with implementation details Technical guide explaining all components Risk management best practices Alert configuration guide Best Practices: Start with default settings Enable Confirm-on-Close initially Use 1% risk per trade or less Focus on Premium (🔥) entries first Keep a trade journal to track performance Credits & Methodology Indicators Used: TTM Squeeze (John Carter) VWAP (Volume-Weighted Average Price) MACD (Gerald Appel) Exponential Moving Averages Average True Range (Wilder) Relative Volume Original Contributions: Multi-component probability weighting system Volatility regime adaptation framework Confluence scoring methodology Integrated risk management calculator Dashboard-centric visualization License & Terms Usage: Free for personal trading Modification: Open source, modify as needed Distribution: Credit original author if sharing modified versions Commercial Use: Contact author for licensing No Warranty: This indicator is provided "as-is" without guarantees of profitability. Trading involves substantial risk. Past performance does not guarantee future results. Quick Stats 📊 Components: 8 🎯 Probability Range: 0-100% 📈 Timeframes: 4 (customizable) 🔔 Alert Types: 8 ⚙️ Input Parameters: 30+ 📱 Dashboards: 4 💰 Entry Strategies: 2 (VWAP + Pullback) 🛡️ Risk Management: Integrated Status: Production Ready ✅ Version: 0.1.2 Last Updated: November 2025 Pine Script: v6 File Name: PA_AI_PRE_GO_v0.1.2_FIXED.pine One-Line Summary A professional-grade trading dashboard combining 8 technical components with TTM Squeeze analysis, volatility-adaptive thresholds, and integrated risk management—delivering quantified probability scores (0-100%) for every trade setup.
Indicador Pine Script®
por DayTradingMD1992
Squeeze Momentum ProSQUEEZE MOMENTUM PRO - Enhanced Visual Dashboard A modernized version of the TTM Squeeze Momentum indicator, designed for cleaner visual interpretation and faster decision-making. ═══════════════════════════════════════════ 📊 WHAT IS THE SQUEEZE? ═══════════════════════════════════════════ The "squeeze" occurs when Bollinger Bands contract inside Keltner Channels, indicating extremely low volatility. This compression typically precedes explosive directional moves - the tighter the squeeze, the bigger the potential breakout. John Carter's TTM Squeeze concept (from "Mastering the Trade") combines this volatility compression with momentum direction to identify high-probability setups. ═══════════════════════════════════════════ ✨ WHAT'S NEW IN THIS VERSION ═══════════════════════════════════════════ 🎯 VISUAL STATUS BAR - Real-time squeeze state with clear labels - Color-coded backgrounds (Red = Building, Green = Fired Bullish, Orange = Fired Bearish) - Squeeze duration counter to gauge compression time 📊 ENHANCED HISTOGRAM - 4-color momentum gradient (Strong Bull/Weak Bull/Weak Bear/Strong Bear) - Instantly shows both direction AND strength - Background shading for current market state 🔥 SQUEEZE INTENSITY GAUGE - 5-dot pressure indicator showing compression tightness - Percentage display of squeeze strength - Only appears during active squeezes 📈 REAL-TIME METRICS PANEL - Current momentum value - Direction indicator (increasing/decreasing) - Strength assessment (strong/weak) 🔔 COMPREHENSIVE ALERTS - Squeeze started - Squeeze fired (bullish/bearish) - Momentum crossovers ═══════════════════════════════════════════ 🎮 HOW TO USE ═══════════════════════════════════════════ 1. WAIT FOR SQUEEZE • Red status bar appears • Intensity dots show compression level • Longer duration = potentially bigger move 2. WATCH FOR RELEASE • Status changes to "FIRED - BULLISH" or "FIRED - BEARISH" • Histogram color confirms momentum direction • Background highlights the event 3. MANAGE POSITION • Monitor momentum strength in metrics panel • Exit when histogram changes color (momentum reversal) • Use with trend/volume confirmation ═══════════════════════════════════════════ ⚙️ CUSTOMIZATION ═══════════════════════════════════════════ - Toggle status bar, metrics, intensity dots independently - Adjustable BB/KC parameters - Custom color schemes - Show/hide squeeze duration ═══════════════════════════════════════════ 🙏 CREDITS ═══════════════════════════════════════════ Original TTM Squeeze concept: John F. Carter Original indicator code: LazyBear (@LazyBear) This builds on LazyBear's excellent implementation of the TTM Squeeze Momentum indicator, adding modern visual elements and real-time dashboards for improved usability. Original indicator: "Squeeze Momentum Indicator " ═══════════════════════════════════════════ ⚠️ DISCLAIMER ═══════════════════════════════════════════ This indicator is for educational purposes. Always use proper risk management and combine with other forms of analysis. No indicator guarantees profitable trades. ═══════════════════════════════════════════ Best used on: Day trading timeframes (1m-15m) for momentum plays Combine with: Volume analysis, trend filters, support/resistance levels
Indicador Pine Script®
por DayTradingMD1992
Adaptive Volatility Bands | AlphaNattAdaptive Volatility Bands (AVB) | AlphaNatt Professional-grade dynamic bands that adapt to market volatility and trend strength, featuring smooth gradient visualization for enhanced chart clarity. 🎯 CORE CONCEPT AVB creates self-adjusting bands around a customizable basis line, expanding during trending markets and contracting during consolidation. The gradient fill provides instant visual feedback on price position within the volatility envelope. ✨ KEY FEATURES 5 Basis Types: Choose between SMA, EMA, ALMA, KAMA, or VWMA for the centerline calculation Adaptive Band Width: Bands automatically widen in strong trends and tighten in ranging markets Smooth Gradient Fills: 10-layer gradient on each side for professional depth visualization Multiple Volatility Metrics: ATR, Standard Deviation, or Range-based calculations Squeeze Detection: Identifies Bollinger/Keltner squeeze conditions for breakout anticipation Dynamic Color States: Cyan (#00F1FF) for bullish, Magenta (#FF019A) for bearish conditions 📊 HOW IT WORKS The basis line is calculated using your selected moving average type Volatility is measured using ATR, StDev, or Range Trend strength is quantified via linear regression Band width adapts based on normalized trend strength (when enabled) Gradient layers create smooth visual transitions from bands to basis Color state changes based on price position and basis direction 🔧 PARAMETER GROUPS Basis Configuration: Basis Type: Moving average calculation method Basis Length (20): Period for centerline calculation ALMA Settings: Offset (0.85) and Sigma (6) for ALMA basis Volatility Settings: Volatility Method: ATR, Standard Deviation, or Range Volatility Length (14): Lookback for volatility calculation Band Multiplier (2.0): Distance of bands from basis Adaptive Settings: Enable Adaptive (true): Toggle dynamic band adjustment Adaptation Period (50): Trend strength measurement window Squeeze Detection: BB/KC Parameters: Settings for squeeze identification Expansion Threshold: Multiplier for expansion signals 📈 TRADING SIGNALS Long Conditions: Price crosses above basis Basis line is rising Band color shifts to cyan Short Conditions: Price crosses below basis Basis line is falling Band color shifts to magenta 💡 USAGE STRATEGIES Trend Following: Trade with the basis direction when bands are expanding Mean Reversion: Fade moves to outer bands during squeeze conditions Breakout Trading: Enter on expansion signals after squeeze periods Support/Resistance: Use bands as dynamic S/R levels Position Sizing: Wider bands suggest higher volatility - adjust size accordingly 🎨 VISUAL ELEMENTS Gradient Fills: 10 opacity layers creating smooth band transitions Dynamic Colors: State-dependent coloring for instant trend recognition Basis Line: Bold centerline changes color with trend state Band Lines: Outer boundaries with matching state colors ⚡ BEST PRACTICES The AVB indicator works optimally on liquid instruments with consistent volume. The adaptive feature performs best in trending markets but can generate false signals during choppy conditions. Consider using alongside momentum indicators for confirmation. The gradient visualization helps identify price position within the volatility envelope at a glance. 🔔 ALERTS INCLUDED Long/Short Signals Squeeze Conditions Expansion Breakouts Band Touch Events Version 6 | Pine Script™ | © AlphaNatt
Indicador Pine Script®
por AlphaNatt
3
SuperBandsI've been seeing a lot of volatility band indicators pop up recently, and after watching this trend for a while, I figured it was time to throw my two chips in. The original spark for this idea came years ago from RicardoSantos's Vector Flow Channel script, which used decay channels with timed events in an interesting way. That concept stuck with me, and I kept thinking about how to build something that captured the same kind of dynamic envelope behavior but with a different mathematical foundation. What I ended up with is a hybrid that takes the core logic of supertrend trailing stops, smooths them heavily with exponential moving averages, and wraps them in Donchian-style filled bands with momentum-based color gradients. The basic mechanism here is pretty straightforward. Standard supertrend calculates a trailing stop based on ATR offset from price, then flips direction when price crosses the trail. This implementation does the same thing but adds EMA smoothing to the trail calculation itself, which removes a lot of the choppiness you get from raw supertrend during sideways periods. The smoothing period is adjustable, so you can tune how reactive versus stable you want the bands to be. Lower smoothing values make the bands track price more aggressively, higher values create wider, slower-moving envelopes that only respond to sustained directional moves. Where this diverges from typical supertrend implementations is in the visual presentation and the separate treatment of bullish and bearish conditions. Instead of a single flipping line, you get persistent upper and lower bands that each track their own trailing stops independently. The bullish band trails below price and stays active as long as price doesn't break below it. The bearish band trails above price and remains active until price breaks above. Both bands can be visible simultaneously, which gives you a dynamic channel that adapts to volatility on both sides of price action. When price is trending strongly, one band will dominate and the other will disappear. During consolidation, both bands tend to compress toward price. The color gradients are calculated by measuring the rate of change in each band's position and converting that delta into an angle using arctangent scaling. Steeper angles, which correspond to the band moving quickly to catch up with accelerating price, get brighter colors. Flatter angles, where the band is moving slowly or staying relatively stable, fade toward more muted tones. This gives you a visual sense of momentum within the bands themselves, not just from price movement. A rapidly brightening band often precedes expansion or breakout conditions, while fading colors suggest the trend is losing steam or entering consolidation. The filled regions between price and each band serve a similar function to Donchian channels or Keltner bands, creating clearly defined zones that represent normal price behavior relative to recent volatility. When price hugs one band and the fill area compresses, you're in a strong directional regime. When price bounces between both bands and the fills expand, you're in a ranging environment. The transparency gradients in the fills make it easier to see when price is near the edge of the envelope versus safely inside it. Configuration is split between bullish and bearish settings, which lets you asymmetrically tune the indicator if you find that your market or timeframe has different characteristics in uptrends versus downtrends. You can adjust ATR period, ATR multiplier, and smoothing independently for each direction. This flexibility is useful for instruments that exhibit different volatility profiles during bull and bear phases, or for strategies that want tighter trailing on longs than shorts, or vice versa. The ATR period controls the lookback window for volatility measurement. Shorter periods make the bands react quickly to recent volatility spikes, which can be beneficial in fast-moving markets but also leads to more frequent whipsaws. Longer periods smooth out volatility estimates and create more stable bands at the cost of slower adaptation. The multiplier scales the ATR offset, directly controlling how far the bands sit from price. Smaller multipliers keep the bands tight, triggering more frequent direction changes. Larger multipliers create wider envelopes that give price more room to move without breaking the trail. One thing to note is that this indicator doesn't generate explicit buy or sell signals in the traditional sense. It's a regime filter and envelope tool. You can use band breaks as directional cues if you want, but the primary value comes from understanding the current volatility environment and whether price is respecting or violating its recent behavioral boundaries. Pairing this with momentum oscillators or volume analysis tends to work better than treating band breaks as standalone entries. From an implementation perspective, the supertrend state machine tracks whether each direction's trail is active, handles resets when price breaks through, and manages the EMA smoothing on the trail points themselves rather than just post-processing the supertrend output. This means the smoothing is baked into the trailing logic, which creates a different response curve than if you just applied an EMA to a standard supertrend line. The angle calculations use RMS estimation for the delta normalization range, which adapts to changing volatility and keeps the color gradients responsive across different market conditions. What this really demonstrates is that there are endless ways to combine basic technical concepts into something that feels fresh without reinventing mathematics. ATR offsets, trailing stops, EMA smoothing, and Donchian fills are all standard building blocks, but arranging them in a particular way produces behavior that's distinct from each component alone. Whether this particular arrangement works better than other volatility band systems depends entirely on your market, timeframe, and what you're trying to accomplish. For me, it scratched the itch I had from seeing Vector Flow years ago and wanting to build something in that same conceptual space using tools I'm more comfortable with.
Indicador Pine Script®
por The_Peaceful_Lizard
7
Swing AURORA v4.0 — Refined Trend Signals### Swing Algo v4.0 — Refined Trend Signals #### Overview Swing Algo v4.0 is an advanced technical indicator designed for TradingView, built to detect trend changes and provide actionable buy/sell signals in various market conditions. It combines multiple technical elements like moving averages, ADX for trend strength, Stochastic RSI for timing, and RSI divergence for confirmation, all while adapting to different timeframes through auto-tuning. This indicator overlays on your chart, highlighting trend regimes with background colors, displaying buy/sell labels (including "strong" variants), and offering early "potential" signals for proactive trading decisions. It's suitable for swing trading, trend following, or as a filter for other strategies across forex, stocks, crypto, and other assets. #### Purpose The primary goal of Swing Algo v4.0 is to help traders identify high-probability trend reversals and continuations early, reducing noise and false signals. It aims to provide clear, non-repainting signals that align with market structure, volatility, and momentum. By incorporating filters like higher timeframe (HTF) alignment, bias EMAs, and divergence, it refines entries for better accuracy. The indicator emphasizes balanced performance across aggressive, balanced, and conservative modes, making it versatile for both novice and experienced traders seeking to optimize their decision-making process. #### What It Indicates - **Trend Regimes (Background Coloring)**: The chart background changes color to reflect the current market regime: - **Green (Intense for strong uptrends, faded when cooling)**: Indicates bullish trends where price is above the baseline and EMAs are aligned upward. - **Red/Maroon (Intense maroon for strong downtrends, faded red when cooling)**: Signals bearish trends with price below the baseline and downward EMA alignment. - **Faded Yellow**: Marks "no-trade" zones or potential trend changes, where conditions are choppy, weak, or neutral (e.g., low ADX, near baseline, or low volatility). - **Buy/Sell Signals**: Labels appear on the chart for confirmed entries: - "BUY" or "STRONG BUY" for bullish signals (strong variants require higher scores and optional divergence). - "SELL" or "STRONG SELL" for bearish signals. - **Potential Signals**: Early warnings like "Potential BUY" or "Potential SELL" appear before full confirmation, allowing traders to anticipate moves (confirmed after a few bars based on the trigger window). - **Divergence Marks**: Small "DIV↑" (bullish) or "DIV↓" (bearish) labels highlight RSI divergences on pivots, adding confluence for strong signals. - **Lines**: Optional plots for baseline (teal), EMA13/21 (lime/red based on crossover), providing visual trend context. Signals are anchored either to the current bar or confirmed pivots, ensuring alignment with price action. The indicator avoids repainting by confirming on close if enabled. #### Key Parameters and Customization Swing Algo v4.0 offers minimal yet efficient parameters for fine-tuning, with defaults optimized for common use cases. Most can be auto-tuned based on timeframe for simplicity: - **Confirm on Close (no repaint)**: Boolean (default: true) – Ensures signals don't repaint by waiting for bar confirmation. - **Auto-tune by Timeframe**: Boolean (default: true) – Automatically adjusts lengths and sensitivity for 5-15m, 30-60m, 2-4h, or higher frames. - **Mode**: String (options: Aggressive, Balanced , Conservative) – Controls signal thresholds; Aggressive for more signals, Conservative for fewer but higher-quality ones. - **Signal Anchor**: String (options: Pivot (divLB) , Current bar) – Places labels on confirmed pivots or the current bar. - **Trigger Window (bars)**: Integer (default: 3) – Window for signal timing; auto-tuned if enabled. - **Baseline Type**: String (options: HMA , EMA, ALMA) – Core trend line; lengths auto-tune (e.g., 55 for short frames). - **Use Bias EMA Filter**: Boolean (default: false) – Adds a long-term EMA for trend bias. - **Use HTF Filter**: Boolean (default: false) – Aligns with higher timeframe (auto or manual like 60m, 240m, D); override for stricter scoring. - **Sensitivity (10–90)**: Integer (default: 55) – Adjusts ADX threshold for trend detection; higher = more sensitive. - **Use RSI-Stoch Trigger**: Boolean (default: true) – Enables Stochastic RSI for entry timing; customizable lengths, smooths, and levels. - **Use RSI Divergence for STRONG**: Boolean (default: true) – Requires divergence for strong signals; pivot lookback (default: 5). - **Visual Options**: Booleans for background regime, labels, divergence marks, and lines (all default: true). These parameters are grouped for ease, with tooltips in TradingView for quick reference. Start with defaults and tweak based on backtesting. #### How It Works At its core, Swing Algo v4.0 calculates a baseline (e.g., HMA) to define the trend direction. It then scores potential buys/sells using factors like: - **Trend Strength**: ADX above a dynamic threshold, combined with EMA crossovers (13/21) and slope analysis. - **Volatility/Volume**: Bollinger/Keltner squeeze exits, volume z-score, and ATR filters to avoid choppy markets. - **Timing**: Stochastic RSI crossovers or micro-timing via DEMA/TEMA for precise entries. - **Filters**: Bias EMA, HTF alignment, gap from baseline, and no-trade zones (weak ADX, near baseline, low vol). - **Divergence**: RSI pivots confirm strong signals. - **Scoring**: Buy/sell scores (min 3-5 based on mode) trigger labels only when all gates pass, with early "potential" detection for foresight. The algorithm processes these in real-time, auto-adapting to timeframe for efficiency. Signals flip only on direction changes to prevent over-trading. For best results, use on liquid assets and combine with risk management. #### Disclaimer This indicator is for educational and informational purposes only and does not constitute financial advice, investment recommendations, or trading signals. Trading involves significant risk of loss and is not suitable for all investors. Past performance is not indicative of future results. Always backtest the indicator on your preferred assets and timeframes, and consult a qualified financial advisor before making any trading decisions. The author assumes no liability for any losses incurred from using this script. Use at your own risk.
Indicador Pine Script®
por Bogdan_TOMOIAGA
2
Squeeze Momentum MACDSqueeze Momentum MACD 🧠 Description Squeeze Momentum MACD combines the concept of market volatility compression (the “squeeze”) from Bollinger Bands (BB) and Keltner Channels (KC) with a MACD-style momentum oscillator to reveal potential breakout phases. The indicator first calculates: BB Width = Upper Band − Lower Band KC Width = Upper Band − Lower Band Then it computes their difference: Δ = BB Width − KC Width When Δ > 0 → BB width is greater than KC width → volatility is expanding → potential momentum breakout. When Δ < 0 → BB is inside KC → volatility is compressing → potential squeeze phase before expansion. This Δ value is then processed through a MACD-style calculation: MACD Line = EMA(fast) − EMA(slow) Signal Line = EMA(MACD, signal length) Histogram = MACD − Signal The result is a visual momentum oscillator that behaves like MACD but measures volatility expansion instead of price direction. 🔹 Features: Dynamic 4-color MACD & Signal lines (positive/negative + rising/falling) Optional display of raw BB & KC widths Fully adjustable parameters for BB, KC, and MACD Works on all timeframes and instruments 🔹 Ideal For: Detecting market squeezes and breakout momentum Timing entries before volatility expansion Integrating volatility and momentum into a single framework
Indicador Pine Script®
por Hay_C
Lorentzian Harmonic Flow - Temporal Market Dynamic Lorentzian Harmonic Flow - Temporal Market Dynamic (⚡LHF) By: DskyzInvestments What this is LHF Pro is a research‑grade analytical instrument that models market time as a compressible medium , extracts directional flow in curved time using heavy‑tailed kernels, and consults a history‑based memory bank for context before synthesizing a final, bounded probabilistic score . It is not a mashup; each subsystem is mathematically coupled to a single clock (time dilation via gamma) and a single lens (Lorentzian heavy‑tailed weighting). This script is dense in logic (and therefore heavy) because it prioritizes rigor, interpretability, and visual clarity. Intended use Education and research. This tool expresses state recognition and regime context—not guarantees. It does not place orders. It is fully functional as published and contains no placeholders. Nothing herein is financial advice. Why this is original and useful Curved time: Markets do not move at a constant pace. LHF Pro computes a Lorentz‑style gamma (γ) from relative speed so its analytical windows contract when the tape accelerates and relax when it slows. Heavy‑tailed lens: Lorentzian kernels weight information with fat tails to respect rare but consequential extremes (unlike Gaussian decay). Memory of regimes: A K‑nearest‑neighbors engine works in a multi‑feature space using Lorentz kernels per dimension and exponential age fade , returning a memory bias (directional expectation) and assurance (confidence mass). One ecosystem: Squeeze, TCI, flow, acceleration, and memory live on the same clock and blend into a single final_score —visualized and documented on the dashboard. Cognitive map: A 2D heat map projects memory resonance by age and flow regime, making “where the past is speaking” visible. Shadow portfolio metaphor: Neighbor outcomes act like tiny hypothetical positions whose weighted average forms an educational pressure gauge (no execution, purely didactic). Mathematical framework (full transparency) 1) Returns, volatility, and speed‑of‑market Log return: rₜ = ln(closeₜ / closeₜ₋₁) Realized vol: rv = stdev(r, vol_len); vol‑of‑vol: burst = |rv − rv | Speed‑of‑market (analog to c): c = c_multiplier × (EMA(rv) + 0.5 × EMA(burst) + ε) 2) Trend velocity and Lorentz gamma (time dilation) Trend velocity: v = |close − close | / (vel_len × ATR) Relative speed: v_rel = v / c Gamma: γ = 1 / √(1 − v_rel²), stabilized by caps (e.g., ≤10) Interpretation: γ > 1 compresses market time → use shorter effective windows. 3) Adaptive temporal scale Adaptive length: L = base_len / γ^power (bounded for safety) Harmonic horizons: Lₛ = L × short_ratio, Lₘ = L × mid_ratio, Lₗ = L × long_ratio 4) Lorentzian smoothing and Harmonic Flow Kernel weight per lag i: wᵢ = 1 / (1 + (d/γ)²), d = i/L Horizon baselines: lw_h = Σ wᵢ·price / Σ wᵢ Z‑deviation: z_h = (close − lw_h)/ATR Harmonic Flow (HFL): HFL = (w_short·zₛ + w_mid·zₘ + w_long·zₗ) / (w_short + w_mid + w_long) 5) Flow kinematics Velocity: HFL_vel = HFL − HFL Acceleration (curvature): HFL_acc = HFL − 2·HFL + HFL 6) Squeeze and temporal compression Bollinger width vs Keltner width using L Squeeze: BB_width < KC_width × squeeze_mult Temporal Compression Index: TCI = base_len / L; TCI > 1 ⇒ compressed time 7) Entropy (regime complexity) Shannon‑inspired proxy on |log returns| with numerical safeguards and smoothing. Higher entropy → more chaotic regime. 8) Memory bank and Lorentzian k‑NN Feature vector (5D): Outcomes stored: forward returns at H5, H13, H34 Per‑dimension similarity: k(Δ) = 1 / (1 + Δ²), weighted by user’s feature weights Age fading: weight_age = mem_fade^age_bars Neighbor score: sᵢ = similarityᵢ × weight_ageᵢ Memory bias: mem_bias = Σ sᵢ·outcomeᵢ / Σ sᵢ Assurance: mem_assurance = Σ sᵢ (confidence mass) Normalization: mem_bias normalized by ATR and clamped into band Shadow portfolio metaphor: neighbors behave like micro‑positions; their weighted net forward return becomes a continuous, adaptive expectation. 9) Blended score and breakout proxy Blend factor: α_mem = 0.45 + 0.15 × (γ − 1) Final score: final_score = (1−α_mem)·tanh(HFL / (flow_thr·1.5)) + α_mem·tanh(mem_bias_norm) Breakout probability (bounded): energy = cap(TCI−1) + |HFL_acc|×k + cap(γ−1)×k + cap(mem_assurance)×k; breakout_prob = sigmoid(energy). Caps avoid runaway “100%” readings. Inputs — every control, purpose, mechanics, and tuning 🔮 Lorentz Core Auto‑Adapt (Vol/Entropy): On = L responds to γ and entropy (breathes with regime), Off = static testing. Base Length: Calm‑market anchor horizon. Lower (21–28) for fast tapes; higher (55–89+) for slow. Velocity Window (vel_len): Bars used in v. Shorter = more reactive γ; longer = steadier. Volatility Window (vol_len): Bars used for rv/burst (c). Shorter = more sensitive c. Speed‑of‑Market Multiplier (c_multiplier): Raises/lowers c. Lower values → easier γ spikes (more adaptation). Aim for strong trends to peak around γ ≈ 2–4. Gamma Compression Power: Exponent of γ in L. <1 softens; >1 amplifies adaptation swings. Max Kernel Span: Upper bound on smoothing loop (quality vs CPU). 🎼 Harmonic Flow Short/Mid/Long Horizon Ratios: Partition L into fast/medium/slow views. Smaller short_ratio → faster reaction; larger long_ratio → sturdier bias. Weights (w_short/w_mid/w_long): Governs HFL blend. Higher w_short → nimble; higher w_long → stable. 📈 Signals Squeeze Strictness: Threshold for BB1 = compressed (coiled spring); <1 = dilated. v/c: Relative speed; near 1 denotes extreme pacing. Diagnostic only. Entropy: Regime complexity; high entropy suggests caution, smaller size, or waiting for order to return. HFL: Curved‑time directional flow; sign and magnitude are the instantaneous bias. HFL_acc: Curvature; spikes often accompany regime ignition post‑squeeze. Mem Bias: Directional expectation from historical analogs (ATR‑normalized, bounded). Aligns or conflicts with HFL. Assurance: Confidence mass from neighbors; higher → more reliable memory bias. Squeeze: ON/RELEASE/OFF from BB
Indicador Pine Script®
por DskyzInvestments
3
Dynamic Gamma Inspired IndicatorDynamic Gamma Inspired Indicator This indicator identifies potential market regime shifts between low-volatility (mean-reverting) and high-volatility (trending) environments by using a dynamic, volatility-adaptive framework inspired by options market gamma exposure concepts. Core Concepts This indicator uses a volatility-based model that mimics how market maker hedging can influence price stability and volatility. While it's not possible to calculate true Gamma Exposure (GEX) in Pine Script without external options data, this script uses the Average True Range (ATR) as a proxy to create dynamic zones that adapt to current market conditions. Positive Gamma Environment (Green Background) When price is contained within the upper and lower walls, it suggests a period of stability where market makers' hedging may suppress volatility. In this "mean-reversion" regime, prices tend to revert to the central pivot. Negative Gamma Environment (Orange Background) When price breaks outside the walls, it signals a potential increase in volatility, where hedging can amplify price moves. This "trend-amplification" regime suggests the potential for strong breakout or trend-following moves. How It Works The indicator is built on three key components that dynamically adjust to market volatility: Dynamic Pivot (Blue Line) An Exponential Moving Average (EMA) acts as the central "zero gamma" pivot point. Dynamic Walls (Red & Green Lines) These upper and lower bands are calculated by adding or subtracting a multiple of the Average True Range (ATR) from the central EMA pivot. This is similar to how Keltner Channels use ATR to create volatility-based envelopes. The walls expand during high volatility and contract during low volatility. How to Use This Indicator The indicator automatically plots signals based on the current market regime: Mean-Reversion Signals (Inside the Walls) Long Reversion: Appears when the price crosses up through the central pivot, suggesting a potential move toward the upper wall. Short Reversion: Appears when the price crosses down through the central pivot, suggesting a potential move toward the lower wall. Breakout Signals (Outside the Walls) Long Breakout: Appears when the price breaks and closes above the upper wall, signaling the start of a potential uptrend. Short Breakout: Appears when the price breaks and closes below the lower wall, signaling the start of a potential downtrend. Customization You can tailor the indicator to different assets and timeframes by adjusting the following inputs: Central Pivot EMA Length: Determines the period for the central moving average. ATR Length for Walls: Sets the lookback period for the Average True Range calculation. ATR Multiplier for Walls: Adjusts the width of the channel. A larger multiplier creates wider walls, filtering out more noise but providing fewer signals. Disclaimer: This indicator is a tool for analysis and should not be used as a standalone trading signal. Always use proper risk management and combine it with other analysis methods. Past performance is not indicative of future results.
Indicador Pine Script®
por guttimg
Phoenix Pattern Scanner v1.3.2 - Multi-Pattern, Score & PresetsAdvanced multi-pattern scanner with intelligent presets and heuristic scoring system. 🎯 KEY FEATURES - 5 Trading Style Presets: Conservative, Balanced, Aggressive, Swing, Scalp - 4 Core Patterns: RVOL (unusual volume), Momentum breakout, RSI bounce, Gap & Go - Heuristic Score (0-100): Visual ranking system for signal quality - Per-Pattern Anti-Noise: Prevents signal spam with configurable minimum distance - Relative Strength %: Compare performance vs benchmark (default SPY) - Squeeze Detection: Identifies low volatility compression (BB inside Keltner) 📊 SMART FILTERS - Minimum price and average dollar volume gates - Weekly trend confirmation (optional) - Separate lookback periods for each pattern - Configurable RSI length and Gap parameters ⚙️ CUSTOMIZATION - All parameters adjustable via settings - Toggle individual components on/off - Clean info panel with real-time metrics - Color-coded score visualization 📍 BEST USED ON - Daily timeframe (primary design) - Liquid stocks above $5 - As a screening tool alongside your analysis ⚠️ IMPORTANT NOTES - Educational/informational tool only - NOT financial advice or trade signals - Heuristic score is diagnostic, not predictive - Past pattern behavior ≠ future results 💡 QUICK START 1. Select a preset matching your style 2. Adjust filters for your market 3. Set alerts for patterns you want to track 4. Use score as relative ranking, not absolute signal Version 1.3.2 - Stable release Open source - Free to use and modify Feedback and improvements welcome
Indicador Pine Script®
por GMak01
Composite Sentiment Indicator (SPY/QQQ/SOXX + VixFix)# Multi-Index Composite Sentiment Indicator A comprehensive sentiment indicator that works across SPY, QQQ, SOXX, and custom symbols. Combines volatility, options flow, macro factors, technicals, and seasonality into a single z-score composite. ## What It Does Takes multiple market sentiment inputs (VIX, put/call ratios, breadth, yields, etc.) and smooshes them into one normalized line. When the composite is high = markets getting spooked. When it's low = markets getting complacent. ## Key Features - **Multi-Index Support**: Automatically adapts for SPY (uses VIX), QQQ (uses VXN), SOXX (uses VixFix), or custom symbols - **VixFix Integration**: Larry Williams' VixFix for indices without dedicated VIX measures - **Signal MA**: Choose from SMA/EMA/WMA/HMA/TEMA/DEMA with color coding (red above MA = risk-on, green below = risk-off) - **September Focus**: Built-in seasonality weighting for September weakness patterns - **Comprehensive Components**: Volatility, options sentiment, macro factors, technicals, and sector-specific metrics ## How to Use **Basic Setup:** 1. Pick your index (SPY/QQQ/SOXX) 2. Choose signal MA type and length (EMA 21 is a good start) 3. Watch for extreme readings and MA crossovers **Color Signals:** - Red composite = above signal MA = bearish sentiment - Green composite = below signal MA = bullish sentiment - Extreme high readings (red background) = potential tops - Extreme low readings (green background) = potential bottoms **For Different Indices:** - **QQQ**: Uses NASDAQ VIX (VXN) when available, falls back to VixFix - **SOXX**: Includes semiconductor cycle indicators, uses VixFix for volatility - **Custom**: Adapts automatically, relies on VixFix and general market metrics ## Components Included **Volatility**: VIX/VXN/VixFix, term structure, historical vol **Options**: Put/call ratios, SKEW index **Macro**: DXY, 10Y yields, yield curve, TIPS spreads **Technical**: RSI deviation, momentum **Seasonality**: September effects, quad witching, month-end patterns **Breadth**: S&P 500 and NASDAQ breadth measures ## Pro Tips - Works well on Daily Timeframe - September gets extra weight automatically - watch for August setup signals - Keltner envelope breaks often mark sentiment exhaustion points - Use alerts for extreme readings and MA crossovers Works best when you understand that sentiment extremes often mark turning points, not continuation signals. High readings don't mean "keep shorting" - they mean "start looking for reversal setups." ## Settings Worth Tweaking - Signal MA type/length for your timeframe - Component weights based on what matters for your index - Envelope multipliers for your risk tolerance - VixFix parameters if default doesn't fit your symbol's volatility The table shows all current component readings so you can see what's driving the signal. Good for context and debugging weird readings.
Indicador Pine Script®
por ky_yule1010
4
Mean-Reversion Indicator_V2_SamleeOverview This is the second version of my mean reversion indicator. It combines a moving average with adaptive standard deviation bands to detect when the price deviates significantly from its mean. The script provides automatic entry/exit signals, real-time PnL tracking, and shaded trade zones to make mean reversion trading more intuitive. Core Logic Mean benchmark: Simple Moving Average (MA). Volatility bands: Standard deviation of the spread (close − MA) defines upper and lower bands. Trading rules: Price breaks below the lower band → Enter Long Price breaks above the upper band → Enter Short Price reverts to MA → Exit position What’s different vs. classic Bollinger/Keltner Bandwidth is based on the standard deviation of the price–MA spread, not raw closing prices. Entry signals use previous-bar confirmation to reduce intrabar noise. Exit rule is a mean-touch condition, rather than fixed profit/loss targets. Enhanced visualization: A shaded box dynamically shows the distance between entry and current/exit price, making it easy to see profit/loss zones over the holding period. Instant PnL labels display current position side (Long/Short/Flat) and live profit/loss in both pips and %. Entry and exit points are clearly marked on the chart with labels and exact prices. These visualization tools go beyond what most indicators provide, giving traders a clearer, more practical view of trade evolution. Key Features Automatic detection of position status (Long / Short / Flat). Chart labels for entries (“Entry”) and exits (“Exit”). Real-time floating PnL calculation in both pips and %. Info panel (top-right) showing entry price, current price, position side, and PnL. Dynamic shading between entry and current/exit price to visualize profit/loss zones. Usage Notes & Risk Mean reversion may underperform in strong trending markets; parameters (len_ma, len_std, mult) should be validated per instrument and timeframe. Works best on relatively stable, mean-reverting pairs (e.g., AUDNZD). Risk management is essential: use independent stop-loss rules (e.g., limit risk to 1–2% of equity per trade). This script is provided for educational purposes only and is not financial advice.
Indicador Pine Script®
por SamQuant
2
Multi-Band Trend LineThis Pine Script creates a versatile technical indicator called "Multi-Band Trend Line" that builds upon the concept of the popular "Follow Line Indicator" by Dreadblitz. While the original Follow Line Indicator uses simple trend detection to place a line at High or Low levels, this enhanced version combines multiple band-based trading strategies with dynamic trend line generation. The indicator supports five different band types and provides more sophisticated buy/sell signals based on price breakouts from various technical analysis bands. Key Features Multi-Band Support The indicator supports five different band types: - Bollinger Bands: Uses standard deviation to create bands around a moving average - Keltner Channels: Uses ATR (Average True Range) to create bands around a moving average - Donchian Channels: Uses the highest high and lowest low over a specified period - Moving Average Envelopes: Creates bands as a percentage above and below a moving average - ATR Bands: Uses ATR multiplier to create bands around a moving average Dynamic Trend Line Generation (Enhanced Follow Line Concept) - Similar to the Follow Line Indicator, the trend line is placed at High or Low levels based on trend direction - Key Enhancement: Instead of simple trend detection, this version uses band breakouts to trigger trend changes - When price breaks above the upper band (bullish signal), the trend line is set to the low (optionally adjusted with ATR) - similar to Follow Line's low placement - When price breaks below the lower band (bearish signal), the trend line is set to the high (optionally adjusted with ATR) - similar to Follow Line's high placement - The trend line acts as dynamic support/resistance, following the price action more precisely than the original Follow Line ATR Filter (Follow Line Enhancement) - Like the original Follow Line Indicator, an ATR filter can be selected to place the line at a more distance level than the normal mode settled at candles Highs/Lows - When enabled, it adds/subtracts ATR value to provide more conservative trend line placement - Helps reduce false signals in volatile markets - This feature maintains the core philosophy of the Follow Line while adding more precision through band-based triggers Signal Generation - Buy Signal: Generated when trend changes from bearish to bullish (trend line starts rising) - Sell Signal: Generated when trend changes from bullish to bearish (trend line starts falling) - Signals are displayed as labels on the chart Visual Elements - Upper and lower bands are plotted in gray - Trend line changes color based on direction (green for bullish, red for bearish) - Background color changes based on trend direction - Buy/sell signals are marked with labeled shapes How It Works Band Calculation: Based on the selected band type, upper and lower boundaries are calculated Signal Detection: When price closes above the upper band or below the lower band, a breakout signal is generated Trend Line Update: The trend line is updated based on the breakout direction and previous trend line value Trend Direction: Determined by comparing current trend line with the previous value Alert Generation: Buy/sell conditions trigger alerts and visual signals Use Cases Enhanced trend following strategies: More precise than basic Follow Line due to band-based triggers Breakout trading: Multiple band types provide various breakout opportunities Dynamic support/resistance identification: Combines Follow Line concept with band analysis Multi-timeframe analysis with different band types: Choose the most suitable band for your timeframe Reduced false signals: Band confirmation provides better entry/exit points compared to simple trend following
Indicador Pine Script®
por Mr_Rakun
5
Markov Chain [3D] | FractalystWhat exactly is a Markov Chain? This indicator uses a Markov Chain model to analyze, quantify, and visualize the transitions between market regimes (Bull, Bear, Neutral) on your chart. It dynamically detects these regimes in real-time, calculates transition probabilities, and displays them as animated 3D spheres and arrows, giving traders intuitive insight into current and future market conditions. How does a Markov Chain work, and how should I read this spheres-and-arrows diagram? Think of three weather modes: Sunny, Rainy, Cloudy. Each sphere is one mode. The loop on a sphere means “stay the same next step” (e.g., Sunny again tomorrow). The arrows leaving a sphere show where things usually go next if they change (e.g., Sunny moving to Cloudy). Some paths matter more than others. A more prominent loop means the current mode tends to persist. A more prominent outgoing arrow means a change to that destination is the usual next step. Direction isn’t symmetric: moving Sunny→Cloudy can behave differently than Cloudy→Sunny. Now relabel the spheres to markets: Bull, Bear, Neutral. Spheres: market regimes (uptrend, downtrend, range). Self‑loop: tendency for the current regime to continue on the next bar. Arrows: the most common next regime if a switch happens. How to read: Start at the sphere that matches current bar state. If the loop stands out, expect continuation. If one outgoing path stands out, that switch is the typical next step. Opposite directions can differ (Bear→Neutral doesn’t have to match Neutral→Bear). What states and transitions are shown? The three market states visualized are: Bullish (Bull): Upward or strong-market regime. Bearish (Bear): Downward or weak-market regime. Neutral: Sideways or range-bound regime. Bidirectional animated arrows and probability labels show how likely the market is to move from one regime to another (e.g., Bull → Bear or Neutral → Bull). How does the regime detection system work? You can use either built-in price returns (based on adaptive Z-score normalization) or supply three custom indicators (such as volume, oscillators, etc.). Values are statistically normalized (Z-scored) over a configurable lookback period. The normalized outputs are classified into Bull, Bear, or Neutral zones. If using three indicators, their regime signals are averaged and smoothed for robustness. How are transition probabilities calculated? On every confirmed bar, the algorithm tracks the sequence of detected market states, then builds a rolling window of transitions. The code maintains a transition count matrix for all regime pairs (e.g., Bull → Bear). Transition probabilities are extracted for each possible state change using Laplace smoothing for numerical stability, and frequently updated in real-time. What is unique about the visualization? 3D animated spheres represent each regime and change visually when active. Animated, bidirectional arrows reveal transition probabilities and allow you to see both dominant and less likely regime flows. Particles (moving dots) animate along the arrows, enhancing the perception of regime flow direction and speed. All elements dynamically update with each new price bar, providing a live market map in an intuitive, engaging format. Can I use custom indicators for regime classification? Yes! Enable the "Custom Indicators" switch and select any three chart series as inputs. These will be normalized and combined (each with equal weight), broadening the regime classification beyond just price-based movement. What does the “Lookback Period” control? Lookback Period (default: 100) sets how much historical data builds the probability matrix. Shorter periods adapt faster to regime changes but may be noisier. Longer periods are more stable but slower to adapt. How is this different from a Hidden Markov Model (HMM)? It sets the window for both regime detection and probability calculations. Lower values make the system more reactive, but potentially noisier. Higher values smooth estimates and make the system more robust. How is this Markov Chain different from a Hidden Markov Model (HMM)? Markov Chain (as here): All market regimes (Bull, Bear, Neutral) are directly observable on the chart. The transition matrix is built from actual detected regimes, keeping the model simple and interpretable. Hidden Markov Model: The actual regimes are unobservable ("hidden") and must be inferred from market output or indicator "emissions" using statistical learning algorithms. HMMs are more complex, can capture more subtle structure, but are harder to visualize and require additional machine learning steps for training. A standard Markov Chain models transitions between observable states using a simple transition matrix, while a Hidden Markov Model assumes the true states are hidden (latent) and must be inferred from observable “emissions” like price or volume data. In practical terms, a Markov Chain is transparent and easier to implement and interpret; an HMM is more expressive but requires statistical inference to estimate hidden states from data. Markov Chain: states are observable; you directly count or estimate transition probabilities between visible states. This makes it simpler, faster, and easier to validate and tune. HMM: states are hidden; you only observe emissions generated by those latent states. Learning involves machine learning/statistical algorithms (commonly Baum–Welch/EM for training and Viterbi for decoding) to infer both the transition dynamics and the most likely hidden state sequence from data. How does the indicator avoid “repainting” or look-ahead bias? All regime changes and matrix updates happen only on confirmed (closed) bars, so no future data is leaked, ensuring reliable real-time operation. Are there practical tuning tips? Tune the Lookback Period for your asset/timeframe: shorter for fast markets, longer for stability. Use custom indicators if your asset has unique regime drivers. Watch for rapid changes in transition probabilities as early warning of a possible regime shift. Who is this indicator for? Quants and quantitative researchers exploring probabilistic market modeling, especially those interested in regime-switching dynamics and Markov models. Programmers and system developers who need a probabilistic regime filter for systematic and algorithmic backtesting: The Markov Chain indicator is ideally suited for programmatic integration via its bias output (1 = Bull, 0 = Neutral, -1 = Bear). Although the visualization is engaging, the core output is designed for automated, rules-based workflows—not for discretionary/manual trading decisions. Developers can connect the indicator’s output directly to their Pine Script logic (using input.source()), allowing rapid and robust backtesting of regime-based strategies. It acts as a plug-and-play regime filter: simply plug the bias output into your entry/exit logic, and you have a scientifically robust, probabilistically-derived signal for filtering, timing, position sizing, or risk regimes. The MC's output is intentionally "trinary" (1/0/-1), focusing on clear regime states for unambiguous decision-making in code. If you require nuanced, multi-probability or soft-label state vectors, consider expanding the indicator or stacking it with a probability-weighted logic layer in your scripting. Because it avoids subjectivity, this approach is optimal for systematic quants, algo developers building backtested, repeatable strategies based on probabilistic regime analysis. What's the mathematical foundation behind this? The mathematical foundation behind this Markov Chain indicator—and probabilistic regime detection in finance—draws from two principal models: the (standard) Markov Chain and the Hidden Markov Model (HMM). How to use this indicator programmatically? The Markov Chain indicator automatically exports a bias value (+1 for Bullish, -1 for Bearish, 0 for Neutral) as a plot visible in the Data Window. This allows you to integrate its regime signal into your own scripts and strategies for backtesting, automation, or live trading. Step-by-Step Integration with Pine Script (input.source) Add the Markov Chain indicator to your chart. This must be done first, since your custom script will "pull" the bias signal from the indicator's plot. In your strategy, create an input using input.source() Example: //@version=5 strategy("MC Bias Strategy Example") mcBias = input.source(close, "MC Bias Source") After saving, go to your script’s settings. For the “MC Bias Source” input, select the plot/output of the Markov Chain indicator (typically its bias plot). Use the bias in your trading logic Example (long only on Bull, flat otherwise): if mcBias == 1 strategy.entry("Long", strategy.long) else strategy.close("Long") For more advanced workflows, combine mcBias with additional filters or trailing stops. How does this work behind-the-scenes? TradingView’s input.source() lets you use any plot from another indicator as a real-time, “live” data feed in your own script (source). The selected bias signal is available to your Pine code as a variable, enabling logical decisions based on regime (trend-following, mean-reversion, etc.). This enables powerful strategy modularity : decouple regime detection from entry/exit logic, allowing fast experimentation without rewriting core signal code. Integrating 45+ Indicators with Your Markov Chain — How & Why The Enhanced Custom Indicators Export script exports a massive suite of over 45 technical indicators—ranging from classic momentum (RSI, MACD, Stochastic, etc.) to trend, volume, volatility, and oscillator tools—all pre-calculated, centered/scaled, and available as plots. // Enhanced Custom Indicators Export - 45 Technical Indicators // Comprehensive technical analysis suite for advanced market regime detection //@version=6 indicator('Enhanced Custom Indicators Export | Fractalyst', shorttitle='Enhanced CI Export', overlay=false, scale=scale.right, max_labels_count=500, max_lines_count=500) // |----- Input Parameters -----| // momentum_group = "Momentum Indicators" trend_group = "Trend Indicators" volume_group = "Volume Indicators" volatility_group = "Volatility Indicators" oscillator_group = "Oscillator Indicators" display_group = "Display Settings" // Common lengths length_14 = input.int(14, "Standard Length (14)", minval=1, maxval=100, group=momentum_group) length_20 = input.int(20, "Medium Length (20)", minval=1, maxval=200, group=trend_group) length_50 = input.int(50, "Long Length (50)", minval=1, maxval=200, group=trend_group) // Display options show_table = input.bool(true, "Show Values Table", group=display_group) table_size = input.string("Small", "Table Size", options= , group=display_group) // |----- MOMENTUM INDICATORS (15 indicators) -----| // // 1. RSI (Relative Strength Index) rsi_14 = ta.rsi(close, length_14) rsi_centered = rsi_14 - 50 // 2. Stochastic Oscillator stoch_k = ta.stoch(close, high, low, length_14) stoch_d = ta.sma(stoch_k, 3) stoch_centered = stoch_k - 50 // 3. Williams %R williams_r = ta.stoch(close, high, low, length_14) - 100 // 4. MACD (Moving Average Convergence Divergence) = ta.macd(close, 12, 26, 9) // 5. Momentum (Rate of Change) momentum = ta.mom(close, length_14) momentum_pct = (momentum / close ) * 100 // 6. Rate of Change (ROC) roc = ta.roc(close, length_14) // 7. Commodity Channel Index (CCI) cci = ta.cci(close, length_20) // 8. Money Flow Index (MFI) mfi = ta.mfi(close, length_14) mfi_centered = mfi - 50 // 9. Awesome Oscillator (AO) ao = ta.sma(hl2, 5) - ta.sma(hl2, 34) // 10. Accelerator Oscillator (AC) ac = ao - ta.sma(ao, 5) // 11. Chande Momentum Oscillator (CMO) cmo = ta.cmo(close, length_14) // 12. Detrended Price Oscillator (DPO) dpo = close - ta.sma(close, length_20) // 13. Price Oscillator (PPO) ppo = ta.sma(close, 12) - ta.sma(close, 26) ppo_pct = (ppo / ta.sma(close, 26)) * 100 // 14. TRIX trix_ema1 = ta.ema(close, length_14) trix_ema2 = ta.ema(trix_ema1, length_14) trix_ema3 = ta.ema(trix_ema2, length_14) trix = ta.roc(trix_ema3, 1) * 10000 // 15. Klinger Oscillator klinger = ta.ema(volume * (high + low + close) / 3, 34) - ta.ema(volume * (high + low + close) / 3, 55) // 16. Fisher Transform fisher_hl2 = 0.5 * (hl2 - ta.lowest(hl2, 10)) / (ta.highest(hl2, 10) - ta.lowest(hl2, 10)) - 0.25 fisher = 0.5 * math.log((1 + fisher_hl2) / (1 - fisher_hl2)) // 17. Stochastic RSI stoch_rsi = ta.stoch(rsi_14, rsi_14, rsi_14, length_14) stoch_rsi_centered = stoch_rsi - 50 // 18. Relative Vigor Index (RVI) rvi_num = ta.swma(close - open) rvi_den = ta.swma(high - low) rvi = rvi_den != 0 ? rvi_num / rvi_den : 0 // 19. Balance of Power (BOP) bop = (close - open) / (high - low) // |----- TREND INDICATORS (10 indicators) -----| // // 20. Simple Moving Average Momentum sma_20 = ta.sma(close, length_20) sma_momentum = ((close - sma_20) / sma_20) * 100 // 21. Exponential Moving Average Momentum ema_20 = ta.ema(close, length_20) ema_momentum = ((close - ema_20) / ema_20) * 100 // 22. Parabolic SAR sar = ta.sar(0.02, 0.02, 0.2) sar_trend = close > sar ? 1 : -1 // 23. Linear Regression Slope lr_slope = ta.linreg(close, length_20, 0) - ta.linreg(close, length_20, 1) // 24. Moving Average Convergence (MAC) mac = ta.sma(close, 10) - ta.sma(close, 30) // 25. Trend Intensity Index (TII) tii_sum = 0.0 for i = 1 to length_20 tii_sum += close > close ? 1 : 0 tii = (tii_sum / length_20) * 100 // 26. Ichimoku Cloud Components ichimoku_tenkan = (ta.highest(high, 9) + ta.lowest(low, 9)) / 2 ichimoku_kijun = (ta.highest(high, 26) + ta.lowest(low, 26)) / 2 ichimoku_signal = ichimoku_tenkan > ichimoku_kijun ? 1 : -1 // 27. MESA Adaptive Moving Average (MAMA) mama_alpha = 2.0 / (length_20 + 1) mama = ta.ema(close, length_20) mama_momentum = ((close - mama) / mama) * 100 // 28. Zero Lag Exponential Moving Average (ZLEMA) zlema_lag = math.round((length_20 - 1) / 2) zlema_data = close + (close - close ) zlema = ta.ema(zlema_data, length_20) zlema_momentum = ((close - zlema) / zlema) * 100 // |----- VOLUME INDICATORS (6 indicators) -----| // // 29. On-Balance Volume (OBV) obv = ta.obv // 30. Volume Rate of Change (VROC) vroc = ta.roc(volume, length_14) // 31. Price Volume Trend (PVT) pvt = ta.pvt // 32. Negative Volume Index (NVI) nvi = 0.0 nvi := volume < volume ? nvi + ((close - close ) / close ) * nvi : nvi // 33. Positive Volume Index (PVI) pvi = 0.0 pvi := volume > volume ? pvi + ((close - close ) / close ) * pvi : pvi // 34. Volume Oscillator vol_osc = ta.sma(volume, 5) - ta.sma(volume, 10) // 35. Ease of Movement (EOM) eom_distance = high - low eom_box_height = volume / 1000000 eom = eom_box_height != 0 ? eom_distance / eom_box_height : 0 eom_sma = ta.sma(eom, length_14) // 36. Force Index force_index = volume * (close - close ) force_index_sma = ta.sma(force_index, length_14) // |----- VOLATILITY INDICATORS (10 indicators) -----| // // 37. Average True Range (ATR) atr = ta.atr(length_14) atr_pct = (atr / close) * 100 // 38. Bollinger Bands Position bb_basis = ta.sma(close, length_20) bb_dev = 2.0 * ta.stdev(close, length_20) bb_upper = bb_basis + bb_dev bb_lower = bb_basis - bb_dev bb_position = bb_dev != 0 ? (close - bb_basis) / bb_dev : 0 bb_width = bb_dev != 0 ? (bb_upper - bb_lower) / bb_basis * 100 : 0 // 39. Keltner Channels Position kc_basis = ta.ema(close, length_20) kc_range = ta.ema(ta.tr, length_20) kc_upper = kc_basis + (2.0 * kc_range) kc_lower = kc_basis - (2.0 * kc_range) kc_position = kc_range != 0 ? (close - kc_basis) / kc_range : 0 // 40. Donchian Channels Position dc_upper = ta.highest(high, length_20) dc_lower = ta.lowest(low, length_20) dc_basis = (dc_upper + dc_lower) / 2 dc_position = (dc_upper - dc_lower) != 0 ? (close - dc_basis) / (dc_upper - dc_lower) : 0 // 41. Standard Deviation std_dev = ta.stdev(close, length_20) std_dev_pct = (std_dev / close) * 100 // 42. Relative Volatility Index (RVI) rvi_up = ta.stdev(close > close ? close : 0, length_14) rvi_down = ta.stdev(close < close ? close : 0, length_14) rvi_total = rvi_up + rvi_down rvi_volatility = rvi_total != 0 ? (rvi_up / rvi_total) * 100 : 50 // 43. Historical Volatility hv_returns = math.log(close / close ) hv = ta.stdev(hv_returns, length_20) * math.sqrt(252) * 100 // 44. Garman-Klass Volatility gk_vol = math.log(high/low) * math.log(high/low) - (2*math.log(2)-1) * math.log(close/open) * math.log(close/open) gk_volatility = math.sqrt(ta.sma(gk_vol, length_20)) * 100 // 45. Parkinson Volatility park_vol = math.log(high/low) * math.log(high/low) parkinson = math.sqrt(ta.sma(park_vol, length_20) / (4 * math.log(2))) * 100 // 46. Rogers-Satchell Volatility rs_vol = math.log(high/close) * math.log(high/open) + math.log(low/close) * math.log(low/open) rogers_satchell = math.sqrt(ta.sma(rs_vol, length_20)) * 100 // |----- OSCILLATOR INDICATORS (5 indicators) -----| // // 47. Elder Ray Index elder_bull = high - ta.ema(close, 13) elder_bear = low - ta.ema(close, 13) elder_power = elder_bull + elder_bear // 48. Schaff Trend Cycle (STC) stc_macd = ta.ema(close, 23) - ta.ema(close, 50) stc_k = ta.stoch(stc_macd, stc_macd, stc_macd, 10) stc_d = ta.ema(stc_k, 3) stc = ta.stoch(stc_d, stc_d, stc_d, 10) // 49. Coppock Curve coppock_roc1 = ta.roc(close, 14) coppock_roc2 = ta.roc(close, 11) coppock = ta.wma(coppock_roc1 + coppock_roc2, 10) // 50. Know Sure Thing (KST) kst_roc1 = ta.roc(close, 10) kst_roc2 = ta.roc(close, 15) kst_roc3 = ta.roc(close, 20) kst_roc4 = ta.roc(close, 30) kst = ta.sma(kst_roc1, 10) + 2*ta.sma(kst_roc2, 10) + 3*ta.sma(kst_roc3, 10) + 4*ta.sma(kst_roc4, 15) // 51. Percentage Price Oscillator (PPO) ppo_line = ((ta.ema(close, 12) - ta.ema(close, 26)) / ta.ema(close, 26)) * 100 ppo_signal = ta.ema(ppo_line, 9) ppo_histogram = ppo_line - ppo_signal // |----- PLOT MAIN INDICATORS -----| // // Plot key momentum indicators plot(rsi_centered, title="01_RSI_Centered", color=color.purple, linewidth=1) plot(stoch_centered, title="02_Stoch_Centered", color=color.blue, linewidth=1) plot(williams_r, title="03_Williams_R", color=color.red, linewidth=1) plot(macd_histogram, title="04_MACD_Histogram", color=color.orange, linewidth=1) plot(cci, title="05_CCI", color=color.green, linewidth=1) // Plot trend indicators plot(sma_momentum, title="06_SMA_Momentum", color=color.navy, linewidth=1) plot(ema_momentum, title="07_EMA_Momentum", color=color.maroon, linewidth=1) plot(sar_trend, title="08_SAR_Trend", color=color.teal, linewidth=1) plot(lr_slope, title="09_LR_Slope", color=color.lime, linewidth=1) plot(mac, title="10_MAC", color=color.fuchsia, linewidth=1) // Plot volatility indicators plot(atr_pct, title="11_ATR_Pct", color=color.yellow, linewidth=1) plot(bb_position, title="12_BB_Position", color=color.aqua, linewidth=1) plot(kc_position, title="13_KC_Position", color=color.olive, linewidth=1) plot(std_dev_pct, title="14_StdDev_Pct", color=color.silver, linewidth=1) plot(bb_width, title="15_BB_Width", color=color.gray, linewidth=1) // Plot volume indicators plot(vroc, title="16_VROC", color=color.blue, linewidth=1) plot(eom_sma, title="17_EOM", color=color.red, linewidth=1) plot(vol_osc, title="18_Vol_Osc", color=color.green, linewidth=1) plot(force_index_sma, title="19_Force_Index", color=color.orange, linewidth=1) plot(obv, title="20_OBV", color=color.purple, linewidth=1) // Plot additional oscillators plot(ao, title="21_Awesome_Osc", color=color.navy, linewidth=1) plot(cmo, title="22_CMO", color=color.maroon, linewidth=1) plot(dpo, title="23_DPO", color=color.teal, linewidth=1) plot(trix, title="24_TRIX", color=color.lime, linewidth=1) plot(fisher, title="25_Fisher", color=color.fuchsia, linewidth=1) // Plot more momentum indicators plot(mfi_centered, title="26_MFI_Centered", color=color.yellow, linewidth=1) plot(ac, title="27_AC", color=color.aqua, linewidth=1) plot(ppo_pct, title="28_PPO_Pct", color=color.olive, linewidth=1) plot(stoch_rsi_centered, title="29_StochRSI_Centered", color=color.silver, linewidth=1) plot(klinger, title="30_Klinger", color=color.gray, linewidth=1) // Plot trend continuation plot(tii, title="31_TII", color=color.blue, linewidth=1) plot(ichimoku_signal, title="32_Ichimoku_Signal", color=color.red, linewidth=1) plot(mama_momentum, title="33_MAMA_Momentum", color=color.green, linewidth=1) plot(zlema_momentum, title="34_ZLEMA_Momentum", color=color.orange, linewidth=1) plot(bop, title="35_BOP", color=color.purple, linewidth=1) // Plot volume continuation plot(nvi, title="36_NVI", color=color.navy, linewidth=1) plot(pvi, title="37_PVI", color=color.maroon, linewidth=1) plot(momentum_pct, title="38_Momentum_Pct", color=color.teal, linewidth=1) plot(roc, title="39_ROC", color=color.lime, linewidth=1) plot(rvi, title="40_RVI", color=color.fuchsia, linewidth=1) // Plot volatility continuation plot(dc_position, title="41_DC_Position", color=color.yellow, linewidth=1) plot(rvi_volatility, title="42_RVI_Volatility", color=color.aqua, linewidth=1) plot(hv, title="43_Historical_Vol", color=color.olive, linewidth=1) plot(gk_volatility, title="44_GK_Volatility", color=color.silver, linewidth=1) plot(parkinson, title="45_Parkinson_Vol", color=color.gray, linewidth=1) // Plot final oscillators plot(rogers_satchell, title="46_RS_Volatility", color=color.blue, linewidth=1) plot(elder_power, title="47_Elder_Power", color=color.red, linewidth=1) plot(stc, title="48_STC", color=color.green, linewidth=1) plot(coppock, title="49_Coppock", color=color.orange, linewidth=1) plot(kst, title="50_KST", color=color.purple, linewidth=1) // Plot final indicators plot(ppo_histogram, title="51_PPO_Histogram", color=color.navy, linewidth=1) plot(pvt, title="52_PVT", color=color.maroon, linewidth=1) // |----- Reference Lines -----| // hline(0, "Zero Line", color=color.gray, linestyle=hline.style_dashed, linewidth=1) hline(50, "Midline", color=color.gray, linestyle=hline.style_dotted, linewidth=1) hline(-50, "Lower Midline", color=color.gray, linestyle=hline.style_dotted, linewidth=1) hline(25, "Upper Threshold", color=color.gray, linestyle=hline.style_dotted, linewidth=1) hline(-25, "Lower Threshold", color=color.gray, linestyle=hline.style_dotted, linewidth=1) // |----- Enhanced Information Table -----| // if show_table and barstate.islast table_position = position.top_right table_text_size = table_size == "Tiny" ? size.tiny : table_size == "Small" ? size.small : size.normal var table info_table = table.new(table_position, 3, 18, bgcolor=color.new(color.white, 85), border_width=1, border_color=color.gray) // Headers table.cell(info_table, 0, 0, 'Category', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70)) table.cell(info_table, 1, 0, 'Indicator', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70)) table.cell(info_table, 2, 0, 'Value', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70)) // Key Momentum Indicators table.cell(info_table, 0, 1, 'MOMENTUM', text_color=color.purple, text_size=table_text_size, bgcolor=color.new(color.purple, 90)) table.cell(info_table, 1, 1, 'RSI Centered', text_color=color.purple, text_size=table_text_size) table.cell(info_table, 2, 1, str.tostring(rsi_centered, '0.00'), text_color=color.purple, text_size=table_text_size) table.cell(info_table, 0, 2, '', text_color=color.blue, text_size=table_text_size) table.cell(info_table, 1, 2, 'Stoch Centered', text_color=color.blue, text_size=table_text_size) table.cell(info_table, 2, 2, str.tostring(stoch_centered, '0.00'), text_color=color.blue, text_size=table_text_size) table.cell(info_table, 0, 3, '', text_color=color.red, text_size=table_text_size) table.cell(info_table, 1, 3, 'Williams %R', text_color=color.red, text_size=table_text_size) table.cell(info_table, 2, 3, str.tostring(williams_r, '0.00'), text_color=color.red, text_size=table_text_size) table.cell(info_table, 0, 4, '', text_color=color.orange, text_size=table_text_size) table.cell(info_table, 1, 4, 'MACD Histogram', text_color=color.orange, text_size=table_text_size) table.cell(info_table, 2, 4, str.tostring(macd_histogram, '0.000'), text_color=color.orange, text_size=table_text_size) table.cell(info_table, 0, 5, '', text_color=color.green, text_size=table_text_size) table.cell(info_table, 1, 5, 'CCI', text_color=color.green, text_size=table_text_size) table.cell(info_table, 2, 5, str.tostring(cci, '0.00'), text_color=color.green, text_size=table_text_size) // Key Trend Indicators table.cell(info_table, 0, 6, 'TREND', text_color=color.navy, text_size=table_text_size, bgcolor=color.new(color.navy, 90)) table.cell(info_table, 1, 6, 'SMA Momentum %', text_color=color.navy, text_size=table_text_size) table.cell(info_table, 2, 6, str.tostring(sma_momentum, '0.00'), text_color=color.navy, text_size=table_text_size) table.cell(info_table, 0, 7, '', text_color=color.maroon, text_size=table_text_size) table.cell(info_table, 1, 7, 'EMA Momentum %', text_color=color.maroon, text_size=table_text_size) table.cell(info_table, 2, 7, str.tostring(ema_momentum, '0.00'), text_color=color.maroon, text_size=table_text_size) table.cell(info_table, 0, 8, '', text_color=color.teal, text_size=table_text_size) table.cell(info_table, 1, 8, 'SAR Trend', text_color=color.teal, text_size=table_text_size) table.cell(info_table, 2, 8, str.tostring(sar_trend, '0'), text_color=color.teal, text_size=table_text_size) table.cell(info_table, 0, 9, '', text_color=color.lime, text_size=table_text_size) table.cell(info_table, 1, 9, 'Linear Regression', text_color=color.lime, text_size=table_text_size) table.cell(info_table, 2, 9, str.tostring(lr_slope, '0.000'), text_color=color.lime, text_size=table_text_size) // Key Volatility Indicators table.cell(info_table, 0, 10, 'VOLATILITY', text_color=color.yellow, text_size=table_text_size, bgcolor=color.new(color.yellow, 90)) table.cell(info_table, 1, 10, 'ATR %', text_color=color.yellow, text_size=table_text_size) table.cell(info_table, 2, 10, str.tostring(atr_pct, '0.00'), text_color=color.yellow, text_size=table_text_size) table.cell(info_table, 0, 11, '', text_color=color.aqua, text_size=table_text_size) table.cell(info_table, 1, 11, 'BB Position', text_color=color.aqua, text_size=table_text_size) table.cell(info_table, 2, 11, str.tostring(bb_position, '0.00'), text_color=color.aqua, text_size=table_text_size) table.cell(info_table, 0, 12, '', text_color=color.olive, text_size=table_text_size) table.cell(info_table, 1, 12, 'KC Position', text_color=color.olive, text_size=table_text_size) table.cell(info_table, 2, 12, str.tostring(kc_position, '0.00'), text_color=color.olive, text_size=table_text_size) // Key Volume Indicators table.cell(info_table, 0, 13, 'VOLUME', text_color=color.blue, text_size=table_text_size, bgcolor=color.new(color.blue, 90)) table.cell(info_table, 1, 13, 'Volume ROC', text_color=color.blue, text_size=table_text_size) table.cell(info_table, 2, 13, str.tostring(vroc, '0.00'), text_color=color.blue, text_size=table_text_size) table.cell(info_table, 0, 14, '', text_color=color.red, text_size=table_text_size) table.cell(info_table, 1, 14, 'EOM', text_color=color.red, text_size=table_text_size) table.cell(info_table, 2, 14, str.tostring(eom_sma, '0.000'), text_color=color.red, text_size=table_text_size) // Key Oscillators table.cell(info_table, 0, 15, 'OSCILLATORS', text_color=color.purple, text_size=table_text_size, bgcolor=color.new(color.purple, 90)) table.cell(info_table, 1, 15, 'Awesome Osc', text_color=color.blue, text_size=table_text_size) table.cell(info_table, 2, 15, str.tostring(ao, '0.000'), text_color=color.blue, text_size=table_text_size) table.cell(info_table, 0, 16, '', text_color=color.red, text_size=table_text_size) table.cell(info_table, 1, 16, 'Fisher Transform', text_color=color.red, text_size=table_text_size) table.cell(info_table, 2, 16, str.tostring(fisher, '0.000'), text_color=color.red, text_size=table_text_size) // Summary Statistics table.cell(info_table, 0, 17, 'SUMMARY', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.gray, 70)) table.cell(info_table, 1, 17, 'Total Indicators: 52', text_color=color.black, text_size=table_text_size) regime_color = rsi_centered > 10 ? color.green : rsi_centered < -10 ? color.red : color.gray regime_text = rsi_centered > 10 ? "BULLISH" : rsi_centered < -10 ? "BEARISH" : "NEUTRAL" table.cell(info_table, 2, 17, regime_text, text_color=regime_color, text_size=table_text_size) This makes it the perfect “indicator backbone” for quantitative and systematic traders who want to prototype, combine, and test new regime detection models—especially in combination with the Markov Chain indicator. How to use this script with the Markov Chain for research and backtesting: Add the Enhanced Indicator Export to your chart. Every calculated indicator is available as an individual data stream. Connect the indicator(s) you want as custom input(s) to the Markov Chain’s “Custom Indicators” option. In the Markov Chain indicator’s settings, turn ON the custom indicator mode. For each of the three custom indicator inputs, select the exported plot from the Enhanced Export script—the menu lists all 45+ signals by name. This creates a powerful, modular regime-detection engine where you can mix-and-match momentum, trend, volume, or custom combinations for advanced filtering. Backtest regime logic directly. Once you’ve connected your chosen indicators, the Markov Chain script performs regime detection (Bull/Neutral/Bear) based on your selected features—not just price returns. The regime detection is robust, automatically normalized (using Z-score), and outputs bias (1, -1, 0) for plug-and-play integration. Export the regime bias for programmatic use. As described above, use input.source() in your Pine Script strategy or system and link the bias output. You can now filter signals, control trade direction/size, or design pairs-trading that respect true, indicator-driven market regimes. With this framework, you’re not limited to static or simplistic regime filters. You can rigorously define, test, and refine what “market regime” means for your strategies—using the technical features that matter most to you. Optimize your signal generation by backtesting across a universe of meaningful indicator blends. Enhance risk management with objective, real-time regime boundaries. Accelerate your research: iterate quickly, swap indicator components, and see results with minimal code changes. Automate multi-asset or pairs-trading by integrating regime context directly into strategy logic. Add both scripts to your chart, connect your preferred features, and start investigating your best regime-based trades—entirely within the TradingView ecosystem. References & Further Reading Ang, A., & Bekaert, G. (2002). “Regime Switches in Interest Rates.” Journal of Business & Economic Statistics, 20(2), 163–182. Hamilton, J. D. (1989). “A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle.” Econometrica, 57(2), 357–384. Markov, A. A. (1906). "Extension of the Limit Theorems of Probability Theory to a Sum of Variables Connected in a Chain." The Notes of the Imperial Academy of Sciences of St. Petersburg. Guidolin, M., & Timmermann, A. (2007). “Asset Allocation under Multivariate Regime Switching.” Journal of Economic Dynamics and Control, 31(11), 3503–3544. Murphy, J. J. (1999). Technical Analysis of the Financial Markets. New York Institute of Finance. Brock, W., Lakonishok, J., & LeBaron, B. (1992). “Simple Technical Trading Rules and the Stochastic Properties of Stock Returns.” Journal of Finance, 47(5), 1731–1764. Zucchini, W., MacDonald, I. L., & Langrock, R. (2017). Hidden Markov Models for Time Series: An Introduction Using R (2nd ed.). Chapman and Hall/CRC. On Quantitative Finance and Markov Models: Lo, A. W., & Hasanhodzic, J. (2009). The Heretics of Finance: Conversations with Leading Practitioners of Technical Analysis. Bloomberg Press. Patterson, S. (2016). The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution. Penguin Press. TradingView Pine Script Documentation: www.tradingview.com TradingView Blog: “Use an Input From Another Indicator With Your Strategy” www.tradingview.com GeeksforGeeks: “What is the Difference Between Markov Chains and Hidden Markov Models?” www.geeksforgeeks.org What makes this indicator original and unique? - On‑chart, real‑time Markov. The chain is drawn directly on your chart. You see the current regime, its tendency to stay (self‑loop), and the usual next step (arrows) as bars confirm. - Source‑agnostic by design. The engine runs on any series you select via input.source() — price, your own oscillator, a composite score, anything you compute in the script. - Automatic normalization + regime mapping. Different inputs live on different scales. The script standardizes your chosen source and maps it into clear regimes (e.g., Bull / Bear / Neutral) without you micromanaging thresholds each time. - Rolling, bar‑by‑bar learning. Transition tendencies are computed from a rolling window of confirmed bars. What you see is exactly what the market did in that window. - Fast experimentation. Switch the source, adjust the window, and the Markov view updates instantly. It’s a rapid way to test ideas and feel regime persistence/switch behavior. Integrate your own signals (using input.source()) - In settings, choose the Source . This is powered by input.source() . - Feed it price, an indicator you compute inside the script, or a custom composite series. - The script will automatically normalize that series and process it through the Markov engine, mapping it to regimes and updating the on‑chart spheres/arrows in real time. Credits: Deep gratitude to @RicardoSantos for both the foundational Markov chain processing engine and inspiring open-source contributions, which made advanced probabilistic market modeling accessible to the TradingView community. Special thanks to @Alien_Algorithms for the innovative and visually stunning 3D sphere logic that powers the indicator’s animated, regime-based visualization. Disclaimer This tool summarizes recent behavior. It is not financial advice and not a guarantee of future results.
Indicador Pine Script®
por Fractalyst
10
Linh Index Trend & Exhaustion SuitePurpose: One overlay to judge trend, reversal risk, overextension, and volatility squeezes on indexes (built for VNINDEX/VN30, works on any symbol & timeframe). What it shows Trend state: Bull / Bear / Transition via 20/50/200 EMAs + slope check. Overextension heatmap: Background paints when price is stretched vs the 20-EMA by ATR or % (you set the thresholds). Squeeze detection: Squeeze ON (yellow dot): Bollinger Bands (20,2) inside Keltner Channels (20,1.5). Squeeze OFF + Release: White dot; script confirms direction only when close > BB upper (up) or close < BB lower (down). 52-week context: Distance to 52-week high/low (%). Higher-TF alignment: Optional weekly trend reading shown on the label while you’re on the daily. Anchored VWAP(s): Two optional AVWAPs from dates you choose (e.g., YTD open, last big gap/earnings). Plots & labels EMAs 20/50/200 (toggle on/off). Optional BB & KC bands for diagnostics. AVWAP #1 / #2 (optional). Status label with: Trend, EMAs, Dist to 20-EMA (%, ATR), 52-week distances, HTF state. Built-in alerts (set “Once per bar close”) EMA10 ↔ EMA20 cross (early momentum shift) EMA20 ↔ EMA50 cross (trend confirmation/negation) Price ↔ EMA200 cross (long-term regime) Squeeze Release UP / DOWN (BB breakout after squeeze) Overextension Cool-off UP / DN (stretched vs 20-EMA + momentum rolling) Near 52-week High (within your % threshold) How to use (playbook) Map regime: Prefer trades when Daily = Bull and HTF (Weekly) = Bull (shown on label). Hunt expansion: Yellow → White dot and close beyond BB = fresh move. Avoid chasing stretch: If background is painted (overextended vs 20-EMA), wait for a pullback or intraday base. Locations matter: 52-week proximity + HTF Bull improves breakout quality. Anchors: Add AVWAP from YTD open or last major gap to frame support/resistance. Suggested settings Overextension: ATR = 2.0, % = 4.0 to start; tune per index volatility. Squeeze bands: BB(20,2) & KC(20,1.5) default are balanced; tighten KC (1.3) for more signals, widen (1.8) for fewer/higher quality. Timeframes: Daily for signals, Weekly for bias. Optional 65-min for entries.
Indicador Pine Script®
por EmmaMia1618
S/R Clouds Overview The S/R Clouds Indicator is a sophisticated TradingView tool designed to visualize support and resistance levels through dynamic cloud formations. Built on the principles of Keltner Channels, it employs a central moving average enveloped by volatility-based bands to highlight potential price reversal zones. This indicator enhances chart analysis with customizable aesthetics and practical alerts, making it suitable for traders across various strategies and timeframes. Key Features Dynamic Bands: Calculates upper and lower bands using a configurable moving average (SMA or EMA) offset by multiples of the average true range (derived from high-low ranges), capturing volatility deviations for precise S/R identification. Cloud Visualization: Renders semi-transparent clouds between primary and extended bands, providing a clear, layered view of support (lower) and resistance (upper) areas. Trend Detection: Incorporates a trend state logic based on price position relative to bands and moving average direction, aiding in bullish/bearish market assessments. Customization Options: Select from multiple color themes (e.g., Neon, Grayscale) or use custom colors for bands. Enable glow effects for enhanced visual depth and adjust opacity for chart clarity. Volatility Insights: Monitors band width to detect squeezes (low volatility) and expansions (high volatility), signaling potential breakouts. Alerts System: Triggers notifications for price crossings of bands, trend changes, and other key events to support timely decision-making. How It Works At its core, the indicator centers on a user-defined period moving average. Volatility is measured via an exponential moving average of the high-low range, multiplied by adjustable factors to form the bands. This setup creates adaptive clouds that expand/contract with market volatility, offering a more responsive alternative to static S/R lines. The result is a clean, professional overlay that integrates seamlessly with other technical tools. This high-quality indicator prioritizes usability and visual appeal, ensuring traders can focus on analysis without distraction.
Indicador Pine Script®
por AlchimistOfCrypto
1
Universal Valuation[public code]Universal valuation indicator for all assets. Consists of 12 different indicators which are z-scored and averaged out. > Volatility bands via Keltner Channels with a NWMA > Confluence when price > vol.bands and valuation is high/low. The confluence is marked with red arrows when above the upper third band(green when below the lower on the downside), and 50% transparency when between 2/3 band(green when below the lower 2/3 bands on the downside.) > Can be used separately of course. > Can be used as valuation of indicators, when possible. (eg. Global Liquidity index valuation) Code is a mess a bit, but parts can be extracted and a new strategy/indicator can be made. *Big probs to the creator of this indicator . Inspired by him. I want to make it possible for people to extrapolate and create their own indicators/strategies. And of course, so I can do the same.
Indicador Pine Script®
por boyanoff_B13
1
Multi-Session Levels + EMA Crosses + TP Calculator (GBP/USD)# Multi-Session Levels + EMA Crosses + TP Calculator ## 📋 Description **Advanced trading indicator combining multi-session analysis, EMA cross validation, and automated Take Profit calculations for Forex markets.** This comprehensive tool integrates session-based level analysis with validated EMA crossovers and intelligent TP calculations, designed specifically for serious traders who need precise entry signals with calculated exit strategies. ## 🎯 Key Features ### 📊 **Multi-Session Analysis** - **Asian Session (6PM-1AM Mexico)**: Generates key support/resistance levels - **London Session (1AM-6AM Mexico)**: Analyzes manipulation patterns - **New York Session (8AM-4PM Mexico)**: Dynamic levels with trend confirmation - **AMD Setup Detection**: Combines all sessions for high-probability setups ### 📈 **Advanced EMA System** - **4 EMAs**: 8, 13, 21, and 55 periods with visual display - **Validated Crossovers**: EMA 8 vs EMA 13 with multiple confirmations - **Smart Filtering**: Only shows signals during optimal trading hours (6AM-12PM Mexico) ### ✅ **Triple Validation System** - **MACD Confirmation**: Histogram strength + signal line position + momentum direction - **RSI Filter**: Overbought/oversold levels with moving average confirmation - **Squeeze Momentum**: Bollinger Bands vs Keltner Channels compression detection ### 💰 **Intelligent TP Calculator** - **ADR-Based Targets**: Uses Average Daily Range for realistic profit expectations - **ATR Multipliers**: Conservative (1.5x), Aggressive (2.5x), Very Aggressive (3.5x) - **Session-Aware**: Considers already-traveled distance in NY session - **Real-Time Table**: Live pip calculations for all TP levels - **Visual Levels**: Automatic TP lines drawn on chart with color coding ### 🚨 **Smart Alert System** - **Validated Signals Only**: Alerts trigger only when ALL confirmations align - **TP Integration**: Alerts include suggested take profit levels - **Non-Validated Tracking**: Shows basic crosses that don't meet full criteria ## 📐 **Technical Calculations** ### **ADR (Average Daily Range)** - 20-period average of daily high-low ranges - Converted to pips for easy interpretation - Used for percentage-based TP targets (50%, 75%, 100% of ADR) ### **ATR (Average True Range)** - 14-period ATR from H1 timeframe (configurable) - Accounts for gaps and volatility - Base for multiplier-based TP levels ### **Session Tracking** - Real-time monitoring of NY session range - Calculates remaining potential movement - Optimizes TP placement based on session progress ## 🎨 **Visual Elements** ### **Chart Levels** - **Orange Lines**: Asian and London session levels - **White/Green/Red Lines**: NY session levels (color changes with trend direction) - **TP Lines**: Color-coded take profit levels with different styles ### **EMA Display** - **Blue**: EMA 8 (fastest) - **Green**: EMA 13 (signal line) - **Yellow**: EMA 21 (trend filter) - **Red**: EMA 55 (major trend) ### **Signal Shapes** - **Bright Triangles**: Fully validated signals - **Faded Triangles**: Non-validated basic crosses - **Size Variation**: Signal strength indication ## 📊 **Information Table** Real-time display showing: - **TP Levels**: All calculated take profit targets in pips - **Session Data**: NY range already traveled vs average - **Volatility Metrics**: Current ATR and ADR values - **Clean Design**: Easy-to-read format with color coding ## ⚙️ **Customization Options** ### **Session Times** - Fully configurable session times - Mexico City timezone support - Enable/disable individual session analysis ### **Validation Controls** - Toggle MACD, RSI, Squeeze validation independently - Adjust RSI overbought/oversold levels - Customize MACD and Squeeze parameters ### **Display Options** - Show/hide EMAs, crosses, TP levels, table - Customize TP calculation periods (ADR, ATR) - Choose ATR timeframe for calculations ## 🎯 **Ideal For** - **Forex Day Traders**: Especially USD pairs during NY session - **Session-Based Strategies**: Traders who respect market sessions - **Risk Management Focus**: Those who need calculated exit strategies - **Multi-Timeframe Analysis**: Traders using H1-H4 charts ## 📈 **Best Practices** 1. **Use during high-volume sessions** (London-NY overlap) 2. **Wait for full validation** before entering trades 3. **Consider session context** when setting TPs 4. **Combine with proper risk management** (1-2% per trade) 5. **Backtest thoroughly** before live trading ## ⚠️ **Important Notes** - **Signals work best** during trending market conditions - **AMD setups** provide highest probability entries - **TP levels are suggestions** - adjust based on market context - **Always use stop losses** (not included in this indicator) - **Designed for Forex markets** - may need adjustment for other instruments --- *This indicator combines proven technical analysis concepts with modern session-based trading approaches, providing both entry timing and exit planning in one comprehensive tool.*
Indicador Pine Script®
por ecasvar
Volatility Squeeze – Blue Zone (classic) Volatility Squeeze – Blue Zone Highlights periods when volatility contracts by showing a blue band between the Bollinger Bands (BB) whenever they fall inside the Keltner Channel (KC). Blue zone = squeeze: BB upper & lower are inside KC – market coiling. Automatic breakout alert: optional alert fires on the first bar after the squeeze releases. Fully adjustable: BB/KC length, BB σ, KC ATR multiplier, zone colour & opacity, border on/off. Clean overlay: zone hugs price bar-by-bar and disappears only when the squeeze ends, so past squeezes remain visible for context. Use it to spot low-volatility setups, then watch for momentum or volume confirmations when the squeeze breaks.
Indicador Pine Script®
por awax1978
Ultimate ATR Extreme DetectorUltimate ATR Extreme Detector​ Professional Volatility Analysis Tool for Strategic Trading ​Discover Market Turning Points with Precision​ Key Features ​Smart Extremum Detection: Identifies when ATR reaches its highest or lowest point in your specified lookback period ​Quad Visual Alert System: ▲ Green bottom triangles for low volatility signals ▼ Red top triangles for high volatility signals Background color highlighting for instant state recognition Status panel showing current volatility extremes ​Dual Alert Modes: TradingView native alerts ("ATR Low/High Signal") Visual chart alerts with period details (e.g., "Alert: ATR Low (50 bars)") ​4 Calculation Methods: RMA (Wilder's), SMA, EMA, and WMA ​Fully Customizable: Adjustable ATR period (default: 14) Variable lookback window (default: 50) Toggle features on/off via intuitive input settings ​How It Works​ The indicator scans volatility extremes using proprietary logic: Calculates True Range using selected method (RMA/SMA/EMA/WMA) Compares current ATR value against historical data Flags critical moments when: Volatility contracts to N-period lows (prepare for breakouts) Volatility expands to N-period highs (watch for trend exhaustion) ​Strategic Applications​ markdown 复制 | SIGNAL | MARKET CONDITION | TRADING IMPLICATION | |------------------|-----------------------|--------------------------------| | Low Volatility | Contraction/Consolidation | Anticipate breakout moves | | High Volatility | Expansion/Climax | Prepare for reversals or pauses | ​Position Sizing: Use ATR values to determine optimal stop distances ​Entry Timing: Combine with price action at key support/resistance ​Risk Management: Adjust stops dynamically based on volatility regime ​Optimization Guide​ Day Trading: Short lookback (20-30 periods) Swing Trading: Medium lookback (50-100 periods) Position Trading: Long lookback (100-200 periods) Volatility Analysis: Compare multiple timeframes simultaneously ​Professional Setup Recommendations​ Combine with: ​Breakout Confirmation: Volume spikes, chart patterns ​Reversal Signals: RSI divergence, candlestick reversals ​Volatility Filters: Bollinger Band contraction, Keltner Channel breakout ​Compatibility: Works flawlessly across FX, stocks, crypto, and commodities on all timeframes. ​Why Traders Choose This Indicator​ "Transforms complex volatility analysis into clear, actionable visual cues – the essential tool for breakout traders and risk managers alike." ​Install Now to: Spot consolidation before big moves Identify exhaustion at trend extremes Automate volatility-based position sizing Receive instant alerts at critical volatility turns Master market rhythms with professional-grade volatility intelligence!
Indicador Pine Script®
por Dooogiig
Pivot Squeeze IndicatorThe Pivot Squeeze Indicator is an oscillator that identifies when markets are "squeezed" between recent pivot highs and lows, then signals when they're ready to make their next big move. How it Works The indicator calculates the percentage distance between the current price and the most recent pivot high vs. pivot low. When this distance gets compressed (small), the market is "squeezed" and building energy. When it expands rapidly, you get your breakout signal. The indicator adapts to current market volatility using four different modes: - ATR-Based - Bollinger Bands - Keltner Channels - Fixed % What to Look For 🟠 Orange Background = Squeeze Zone Market is compressed between recent pivots Low volatility, building pressure 🟢 Green Breakout = Bullish Signal Price breaking out above recent highs Momentum shifting upward Time to look for long opportunities 🔴 Red Breakout = Bearish Signal Price breaking down below recent lows Momentum shifting downward Time to look for short opportunities Using Histogram Colors: Green bars = Bullish territory (closer to recent highs) Red bars = Bearish territory (closer to recent lows) Orange bars = Squeeze conditions (compressed between pivots) Using MA Line: When Histogram bars cross below or above MA Line in opposite direction, it might be good time to exit. Default Settings: ATR-based thresholds with 14-period lookback - works great out of the box, but feel free to experiment with the different threshold modes to find what works best for your trading style! Recommended to use with other indicators to confirm signals
Indicador Pine Script®
por ky_yule1010