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Inflection Nexus - SPAInflection Nexus - SPA: Self-Adapting Trend Reversal System Overview Inflection Nexus - SPA (Shadow Portfolio Adaptation) is an adaptive trend-following indicator that automatically optimizes its parameters in real-time through a unique shadow testing methodology. Unlike traditional static indicators that use fixed ATR periods and multipliers, this system continuously evaluates multiple parameter combinations in the background and dynamically adjusts to current market conditions without manual intervention. What Makes This Original The core innovation is the Shadow Portfolio Adaptation (SPA) engine, which runs parallel virtual portfolios in the background to test different ATR period and multiplier combinations. The system tracks the performance of these shadow portfolios over rolling windows and automatically switches to the best-performing parameter set. This creates a self-improving indicator that adapts to changing volatility regimes, trending vs. ranging markets, and shifting market dynamics without requiring user reconfiguration. This is not simply a combination of existing indicators. The SPA engine is a novel approach that transforms the traditional Supertrend methodology from a static tool into an adaptive system with built-in machine learning principles. Core Components and How They Work Together 1. Adaptive Supertrend Foundation The base trend detection uses an ATR-based Supertrend calculation with your chosen source (default: hlcc4 for smoothness). Rather than using fixed parameters, the system starts with your configured ATR Period and Multiplier as baseline values. 2. Shadow Portfolio Adaptation Engine This is where the innovation happens. The system simultaneously tests multiple parameter variations in the background: - Creates shadow portfolios with different ATR periods (spanning from your base period minus a range to plus a range) - Tests different ATR multipliers for each period - Each shadow portfolio tracks virtual trade performance over a configurable lookback window - Calculates a confidence score based on win rate, profit factor, and trade frequency - Automatically switches to the best-performing parameter combination - Implements smooth transitions to prevent whipsaw from parameter changes The adaptation happens continuously, allowing the system to shift from tight, responsive settings during low volatility to wider, more conservative settings during high volatility periods. 3. Signal Generation Logic The system offers two complementary signal modes: Reversal Mode (default): Identifies potential trend exhaustion points. A sell signal requires price to make a new structural high while the trend is bullish, then flip bearish. This captures the exact moment a trend runs out of momentum. The "Require New High/Low During Trend" filter ensures signals only occur at genuine extremes, not mid-range noise. Breakout Mode (optional): Identifies trend continuation. Signals occur when price breaks to new highs/lows in the direction of the current trend, confirming momentum rather than reversing it. 4. Multi-Layer Confirmation Filters Each signal passes through optional quality filters: - RSI Momentum Filter : Ensures buy signals occur after RSI has been oversold (preventing buying into exhaustion) and sell signals occur after RSI has been overbought - Volume Spike Confirmation : Requires increased volume relative to recent average, confirming conviction behind the move - Major Level Filter : Ensures signals only occur after significant price moves (measured in ATR multiples), filtering out minor fluctuations 5. Risk Management Integration The dashboard displays real-time metrics including: - Current regime classification (Trending, Volatile, Ranging) - Shadow portfolio performance tracking - Adaptive confidence scores - Parameter evolution log - Market heat map showing probability zones How to Use This Indicator Setup: 1. Apply the indicator to your chart 2. Start with default settings for your first session 3. The SPA engine requires a warm-up period (controlled by "Learning Window") to gather sufficient data - expect optimal adaptation after 100-200 bars 4. Enable the dashboard to monitor the adaptation process and current market regime Signal Interpretation: - Long signals (green triangles below price): Enter long when the system detects a potential bullish reversal or breakout - Short signals (red triangles above price): Enter short when the system detects a potential bearish reversal or breakout - Dashboard color coding : Green regime = favorable for trend-following, Yellow = volatile (use caution), Red = choppy (consider reducing position size) Best Practices: - Use Reversal Mode in swing trading environments where you want to catch major turning points - Use Breakout Mode in strong trending markets where you want confirmation entries - Enable both modes for comprehensive coverage, but filter by the regime indicator - The "Min Bars Between Signals" setting prevents over-trading - start at 10-12 bars for most timeframes - Pay attention to the "Map Heat" metric - higher active cells indicate more defined market structure Parameter Optimization: The system is designed to self-optimize, but you can guide it: - Sensitivity : Lower values (15-25) for intraday scalping, higher values (40-60) for swing trading - ATR Period : Your baseline starting point - the SPA engine will explore around this value - Multiplier : Your baseline band width - the engine tests variations of this - Learning Window : How many bars of data the shadow portfolios evaluate (200-500 for most markets) - Adaptation Frequency : How often the system checks for better parameters (30-50 bars balances responsiveness and stability) Dashboard Insights: The three-panel dashboard provides real-time intelligence: - Panel A shows current signal state, trend direction, and overall market regime - Panel B displays shadow portfolio statistics, confidence scores, and the adaptation log - The regime classification helps you understand if current market conditions favor trending strategies or if you should reduce exposure Calculation Methodology The system operates in three phases: Phase 1 - Base Calculation: - Calculates ATR using your specified period and method (RMA for smoothness) - Identifies structural highs/lows using the sensitivity parameter - Computes initial Supertrend bands: Price ± (ATR × Multiplier) Phase 2 - Shadow Testing: - Creates a grid of parameter combinations (ATR periods from base-5 to base+15, multipliers from base-0.5 to base+1.0) - For each combination, simulates trade entries and exits over the learning window - Tracks metrics: win rate, profit factor, max drawdown, trade count - Calculates a confidence score using weighted metrics (win rate × 0.4 + profit factor × 0.3 + normalized trade frequency × 0.3) Phase 3 - Adaptive Selection: - Every N bars (adaptation frequency), ranks all shadow portfolios by confidence score - Selects the highest-scoring parameter set - Implements parameter change with transition smoothing to prevent signal disruption - Logs the change and updates the dashboard This creates a continuous feedback loop where the indicator learns from recent market behavior and adjusts its sensitivity accordingly. Ideal Market Conditions Best Performance: - Markets with clear swing structure (forex majors, liquid stocks, major indices) - Timeframes from 5-minute to daily (indicator adapts across timeframes) - Trending markets with periodic consolidations (where reversals are meaningful) Challenging Conditions: - Extremely low liquidity assets (insufficient price action for adaptation) - Very low timeframes (1-minute or below) where noise dominates - Markets in deep consolidation for extended periods (the system will reduce signal frequency appropriately) Technical Notes - The indicator uses lookback functions with a 5000-bar maximum, ensuring sufficient historical context - Shadow portfolios are lightweight - they don't execute actual trades, only track hypothetical P&L - The confidence-based selection prevents the system from chasing random variations - The minimum bars between signals prevents over-fitting to short-term fluctuations - All calculations are performed on closed bars to prevent repainting Recommended Settings by Trading Style Day Trading (5-15 min charts): - Sensitivity: 20-30 - ATR Period: 14-20 - Multiplier: 1.2-1.5 - Min Bars Between Signals: 8-12 - Enable RSI Filter: Yes Swing Trading (1H-4H charts): - Sensitivity: 30-50 - ATR Period: 20-30 - Multiplier: 1.5-2.0 - Min Bars Between Signals: 10-15 - Enable Major Levels Only: Optional Position Trading (Daily charts): - Sensitivity: 50-80 - ATR Period: 30-40 - Multiplier: 2.0-2.5 - Min Bars Between Signals: 5-10 - Enable Breakout Mode: Consider The SPA engine will refine these starting points automatically based on actual market performance. Important Disclaimers This indicator is a technical analysis tool designed to identify potential trend changes and continuation points. It should not be used as a standalone trading system. Always combine with proper risk management, position sizing, and additional confirmation methods. Past performance of the adaptation engine does not guarantee future results. The shadow portfolio system is designed to improve parameter selection, but no indicator can predict market movements with certainty. — Dskyz, Trade with insight. Trade with anticipation.
Wskaźnik Pine Script®
od DskyzInvestments
Quantum Market Harmonics [QMH]# Quantum Market Harmonics - TradingView Script Description ## 📊 OVERVIEW Quantum Market Harmonics (QMH) is a comprehensive multi-dimensional trading indicator that combines four independent analytical frameworks to generate high-probability trading signals with quantifiable confidence scores. Unlike simple indicator combinations that display multiple tools side-by-side, QMH synthesizes temporal analysis, inter-market correlations, behavioral psychology, and statistical probabilities into a unified confidence scoring system that requires agreement across all dimensions before generating a confirmed signal. --- ## 🎯 WHAT MAKES THIS SCRIPT ORIGINAL ### The Core Innovation: Weighted Confidence Scoring Most indicators provide binary signals (buy/sell) or display multiple indicators separately, leaving traders to interpret conflicting information. QMH's originality lies in its weighted confidence scoring system that: 1. **Combines Four Independent Methods** - Each framework (described below) operates independently and contributes points to an overall confidence score 2. **Requires Multi-Dimensional Agreement** - Signals only fire when multiple frameworks align, dramatically reducing false positives 3. **Quantifies Signal Strength** - Every signal includes a numerical confidence rating (0-100%), allowing traders to filter by quality 4. **Adapts to Market Conditions** - Different market regimes activate different component combinations ### Why This Combination is Useful Traditional approaches suffer from: - **Single-dimension bias**: RSI shows oversold, but trend is still down - **Conflicting signals**: MACD says buy, but volume is weak - **No prioritization**: All signals treated equally regardless of strength QMH solves these problems by requiring multiple independent confirmations and weighting each component's contribution to the final signal. This multi-dimensional approach mirrors how professional traders analyze markets - not relying on one indicator, but waiting for multiple pieces of evidence to align. --- ## 🔬 THE FOUR ANALYTICAL FRAMEWORKS ### 1. Temporal Fractal Resonance (TFR) **What It Does:** Analyzes trend alignment across four different timeframes simultaneously (15-minute, 1-hour, 4-hour, and daily) to identify periods of multi-timeframe synchronization. **How It Works:** - Uses `request.security()` with `lookahead=barmerge.lookahead_off` to retrieve confirmed price data from each timeframe - Calculates "fractal strength" for each timeframe using this formula: ``` Fractal Strength = (Rate of Change / Standard Deviation) × 100 ``` This creates a momentum-to-volatility ratio that measures trend strength relative to noise - Computes a Resonance Index when all four timeframes show the same directional bias - The index averages the absolute strength values when all timeframes align **Why This Method:** Fractal Market Hypothesis suggests that price patterns repeat across different time scales. When trends align from short-term (15m) to long-term (Daily), the probability of trend continuation increases substantially. The momentum/volatility ratio filters out low-conviction moves where volatility dominates direction. **Contribution to Confidence Score:** - TFR Bullish = +25 points - TFR Bearish = +25 points (to bearish confidence) - No alignment = 0 points --- ### 2. Cross-Asset Quantum Entanglement (CAQE) **What It Does:** Analyzes correlation patterns between the current asset and three reference markets (Bitcoin, US Dollar Index, and Volatility Index) to identify both normal correlation behavior and anomalous breakdowns that often precede significant moves. **How It Works:** - Retrieves price data from BTC (BINANCE:BTCUSDT), DXY (TVC:DXY), and VIX (TVC:VIX) using confirmed bars - Calculates Pearson correlation coefficient between the main asset and each reference: ``` Correlation = Covariance(X,Y) / (StdDev(X) × StdDev(Y)) ``` - Computes an Intermarket Pressure Index by weighting each reference asset's momentum by its correlation strength: ``` Pressure = (Corr₁ × ROC₁ + Corr₂ × ROC₂ + Corr₃ × ROC₃) / 3 ``` - Detects "correlation breakdowns" when average correlation drops below 0.3 **Why This Method:** Markets don't operate in isolation. Inter-market analysis (developed by John Murphy) recognizes that: - Crypto assets often correlate with Bitcoin - Risk assets inversely correlate with VIX (fear gauge) - Dollar strength affects commodity and crypto prices When these normal correlations break down, it signals potential regime changes. The term "quantum" reflects the interconnected nature of these relationships - like quantum entanglement where distant particles influence each other. **Contribution to Confidence Score:** - CAQE Bullish (positive pressure, stable correlations) = +25 points - CAQE Bearish (negative pressure, stable correlations) = +25 points (to bearish) - Correlation breakdown = Warning marker (potential reversal zone) --- ### 3. Adaptive Market Psychology Matrix (AMPM) **What It Does:** Classifies the current market emotional state into six distinct categories by analyzing the interaction between momentum (RSI), volume behavior, and volatility acceleration (ATR change). **How It Works:** The system evaluates three metrics: 1. **RSI (14-period)**: Measures overbought/oversold conditions 2. **Volume Analysis**: Compares current volume to 20-period average 3. **ATR Rate of Change**: Detects volatility acceleration Based on these inputs, the market is classified into: - **Euphoria**: RSI > 80, volume spike present, volatility rising (extreme bullish emotion) - **Greed**: RSI > 70, normal volume (moderate bullish emotion) - **Neutral**: RSI 40-60, declining volatility (balanced state) - **Fear**: RSI 40-60, low volatility (uncertainty without panic) - **Panic**: RSI < 30, volume spike present, volatility rising (extreme bearish emotion) - **Despair**: RSI < 20, normal volume (capitulation phase) **Why This Method:** Behavioral finance principles (Kahneman, Tversky) show that markets follow predictable emotional cycles. Extreme psychological states often mark reversal points because: - At Euphoria/Greed peaks, everyone bullish has already bought (no buyers left) - At Panic/Despair bottoms, everyone bearish has already sold (no sellers left) AMPM provides contrarian signals at these extremes while respecting trends during Fear and Greed intermediate states. **Contribution to Confidence Score:** - Psychology Bullish (Panic/Despair + RSI < 35) = +15 points - Psychology Bearish (Euphoria/Greed + RSI > 65) = +15 points - Neutral states = 0 points --- ### 4. Time-Decay Probability Zones (TDPZ) **What It Does:** Creates dynamic support and resistance zones based on statistical probability distributions that adapt to changing market volatility, similar to Bollinger Bands but with enhancements for trend environments. **How It Works:** - Calculates a 20-period Simple Moving Average as the basis line - Computes standard deviation of price over the same period - Creates four probability zones: - **Extreme Upper**: Basis + 2.5 standard deviations (≈99% probability boundary) - **Upper Zone**: Basis + 1.5 standard deviations - **Lower Zone**: Basis - 1.5 standard deviations - **Extreme Lower**: Basis - 2.5 standard deviations (≈99% probability boundary) - Dynamically adjusts zone width based on ATR (Average True Range): ``` Adjusted Upper = Upper Zone + (ATR × adjustment_factor) Adjusted Lower = Lower Zone - (ATR × adjustment_factor) ``` - The adjustment factor increases during high volatility, widening the zones **Why This Method:** Traditional support/resistance levels are static and don't account for volatility regimes. TDPZ zones are probability-based and mean-reverting: - Price has ≈99% probability of staying within extreme zones in normal conditions - Touches to extreme zones represent statistical outliers (high-probability reversal opportunities) - Zone expansion/contraction reflects volatility regime changes - ATR adjustment prevents false signals during unusual volatility The "time-decay" concept refers to mean reversion - the further price moves from the basis, the higher the probability of eventual return. **Contribution to Confidence Score:** - Price in Lower Extreme Zone = +15 points (bullish reversal probability) - Price in Upper Extreme Zone = +15 points (bearish reversal probability) - Price near basis = 0 points --- ## 🎯 HOW THE CONFIDENCE SCORING SYSTEM WORKS ### Signal Generation Formula QMH calculates separate Bullish and Bearish confidence scores each bar: **Bullish Confidence (0-100%):** ``` Base Score: 20 points + TFR Bullish: 25 points (if all 4 timeframes aligned bullish) + CAQE Bullish: 25 points (if intermarket pressure positive) + AMPM Bullish: 15 points (if Panic/Despair contrarian signal) + TDPZ Bullish: 15 points (if price in lower probability zones) ───────── Maximum Possible: 100 points ``` **Bearish Confidence (0-100%):** ``` Base Score: 20 points + TFR Bearish: 25 points (if all 4 timeframes aligned bearish) + CAQE Bearish: 25 points (if intermarket pressure negative) + AMPM Bearish: 15 points (if Euphoria/Greed contrarian signal) + TDPZ Bearish: 15 points (if price in upper probability zones) ───────── Maximum Possible: 100 points ``` ### Confirmed Signal Requirements A **QBUY** (Quantum Buy) signal generates when: 1. Bullish Confidence ≥ User-defined threshold (default 60%) 2. Bullish Confidence > Bearish Confidence 3. No active sell signal present A **QSELL** (Quantum Sell) signal generates when: 1. Bearish Confidence ≥ User-defined threshold (default 60%) 2. Bearish Confidence > Bullish Confidence 3. No active buy signal present ### Why This Approach Is Different **Example Comparison:** Traditional RSI Strategy: - RSI < 30 → Buy signal - Result: May buy into falling knife if trend remains bearish QMH Approach: - RSI < 30 → Psychology shows Panic (+15 points) - But requires additional confirmation: - Are all timeframes also showing bullish reversal? (+25 points) - Is intermarket pressure turning positive? (+25 points) - Is price at a statistical extreme? (+15 points) - Only when total ≥ 60 points does a QBUY signal fire This multi-layer confirmation dramatically reduces false signals while maintaining sensitivity to genuine opportunities. --- ## 🚫 NO REPAINT GUARANTEE **QMH is designed to be 100% repaint-free**, which is critical for honest backtesting and reliable live trading. ### Technical Implementation: 1. **All Multi-Timeframe Data Uses Confirmed Bars** ```pinescript tf1_close = request.security(syminfo.tickerid, "15", close , lookahead=barmerge.lookahead_off) ``` Using `close ` instead of `close ` ensures we only reference the previous confirmed bar, not the current forming bar. 2. **Lookahead Prevention** ```pinescript lookahead=barmerge.lookahead_off ``` This parameter prevents the function from accessing future data that wouldn't be available in real-time. 3. **Signal Timing** Signals appear on the bar AFTER all conditions are met, not retroactively on the bar where conditions first appeared. ### What This Means for Users: - **Backtest Accuracy**: Historical signals match exactly what you would have seen in real-time - **No Disappearing Signals**: Once a signal appears, it stays (though price may move against it) - **Honest Performance**: Results reflect true predictive power, not hindsight optimization - **Live Trading Reliability**: Alerts fire at the same time signals appear on the chart The dashboard displays "✓ NO REPAINT" to confirm this guarantee. --- ## 📖 HOW TO USE THIS INDICATOR ### Basic Trading Strategy **For Trend Followers:** 1. **Wait for Signal Confirmation** - QBUY label appears below a bar = Confirmed bullish entry opportunity - QSELL label appears above a bar = Confirmed bearish entry opportunity 2. **Check Confidence Score** - 60-70%: Moderate confidence (consider smaller position size) - 70-85%: High confidence (standard position size) - 85-100%: Very high confidence (consider larger position size) 3. **Enter Trade** - Long entry: Market or limit order near signal bar - Short entry: Market or limit order near signal bar 4. **Set Targets Using Probability Zones** - Long trades: Target the adjusted upper zone (lime line) - Short trades: Target the adjusted lower zone (red line) - Alternatively, target the basis line (yellow) for conservative exits 5. **Set Stop Loss** - Long trades: Below recent swing low minus 1 ATR - Short trades: Above recent swing high plus 1 ATR **For Mean Reversion Traders:** 1. **Wait for Extreme Zones** - Price touches extreme lower zone (dotted red line below) - Price touches extreme upper zone (dotted lime line above) 2. **Confirm with Psychology** - At lower extreme: Look for Panic or Despair state - At upper extreme: Look for Euphoria or Greed state 3. **Wait for Confidence Build** - Monitor dashboard until confidence exceeds threshold - Requires patience - extreme touches don't always reverse immediately 4. **Enter Reversal** - Target: Return to basis line (yellow SMA 20) - Stop: Beyond the extreme zone **For Position Traders (Longer Timeframes):** 1. **Use Daily Timeframe** - Set chart to daily for longer-term signals - Signals will be less frequent but higher quality 2. **Require High Confidence** - Filter setting: Min Confidence Score 80%+ - Only take the strongest multi-dimensional setups 3. **Confirm with Resonance Background** - Green tinted background = All timeframes bullish aligned - Red tinted background = All timeframes bearish aligned - Only enter when background tint matches signal direction 4. **Hold for Major Targets** - Long trades: Hold until extreme upper zone or opposite signal - Short trades: Hold until extreme lower zone or opposite signal --- ## 📊 DASHBOARD INTERPRETATION The QMH Dashboard (top-right corner) provides real-time market analysis across all four dimensions: ### Dashboard Elements: 1. **✓ NO REPAINT** - Green confirmation that signals don't repaint - Always visible to remind users of signal integrity 2. **SIGNAL: BULL/BEAR XX%** - Shows dominant direction (whichever confidence is higher) - Displays current confidence percentage - Background color intensity reflects confidence level 3. **Psychology: ** - Current market emotional state - Color coded: - Orange = Euphoria (extreme bullish emotion) - Yellow = Greed (moderate bullish emotion) - Gray = Neutral (balanced state) - Purple = Fear (uncertainty) - Red = Panic (extreme bearish emotion) - Dark red = Despair (capitulation) 4. **Resonance: ** - Multi-timeframe alignment strength - Positive = All timeframes bullish aligned - Negative = All timeframes bearish aligned - Near zero = Timeframes not synchronized - Emoji indicator: 🔥 (bullish resonance) ❄️ (bearish resonance) 5. **Intermarket: ** - Cross-asset pressure measurement - Positive = BTC/DXY/VIX correlations supporting upside - Negative = Correlations supporting downside - Warning ⚠️ if correlation breakdown detected 6. **RSI: ** - Current RSI(14) reading - Background colors: Red (>70 overbought), Green (<30 oversold) - Status: OB (overbought), OS (oversold), or • (neutral) 7. **Status: READY BUY / READY SELL / WAIT** - Quick trade readiness indicator - READY BUY: Confidence ≥ threshold, bias bullish - READY SELL: Confidence ≥ threshold, bias bearish - WAIT: Confidence below threshold ### How to Use Dashboard: **Before Entering a Trade:** - Verify Status shows READY (not WAIT) - Check that Resonance matches signal direction - Confirm Psychology isn't contradicting (e.g., buying during Euphoria) - Note Intermarket value - breakdowns (⚠️) suggest caution **During a Trade:** - Monitor Psychology shifts (e.g., from Fear to Greed in a long) - Watch for Resonance changes that could signal exit - Check for Intermarket breakdown warnings --- ## ⚙️ CUSTOMIZATION SETTINGS ### TFR Settings (Temporal Fractal Resonance) - **Enable/Disable**: Turn TFR analysis on/off - **Fractal Sensitivity** (5-50, default 14): - Lower values = More responsive to short-term changes - Higher values = More stable, slower to react - Recommendation: 14 for balanced, 7 for scalping, 21 for position trading ### CAQE Settings (Cross-Asset Quantum Entanglement) - **Enable/Disable**: Turn CAQE analysis on/off - **Asset 1** (default BTC): Reference asset for correlation analysis - **Asset 2** (default DXY): Second reference asset - **Asset 3** (default VIX): Third reference asset - **Correlation Length** (10-100, default 20): - Lower values = More sensitive to recent correlation changes - Higher values = More stable correlation measurements - Recommendation: 20 for most assets, 50 for less volatile markets ### Psychology Settings (Adaptive Market Psychology Matrix) - **Enable/Disable**: Turn AMPM analysis on/off - **Volume Spike Threshold** (1.0-5.0x, default 2.0): - Lower values = Detect smaller volume increases as spikes - Higher values = Only flag major volume surges - Recommendation: 2.0 for stocks, 1.5 for crypto ### Probability Settings (Time-Decay Probability Zones) - **Enable/Disable**: Turn TDPZ visualization on/off - **Probability Lookback** (20-200, default 50): - Lower values = Zones adapt faster to recent price action - Higher values = Zones based on longer statistical history - Recommendation: 50 for most uses, 100 for position trading ### Filter Settings - **Min Confidence Score** (40-95%, default 60%): - Lower threshold = More signals, more false positives - Higher threshold = Fewer signals, higher quality - Recommendation: 60% for active trading, 75% for selective trading ### Visual Settings - **Show Entry Signals**: Toggle QBUY/QSELL labels on chart - **Show Probability Zones**: Toggle zone visualization - **Show Psychology State**: Toggle dashboard display --- ## 🔔 ALERT CONFIGURATION QMH includes four alert conditions that can be configured via TradingView's alert system: ### Available Alerts: 1. **Quantum Buy Signal** - Fires when: Confirmed QBUY signal generates - Message includes: Confidence percentage - Use for: Entry notifications 2. **Quantum Sell Signal** - Fires when: Confirmed QSELL signal generates - Message includes: Confidence percentage - Use for: Entry notifications or exit warnings 3. **Market Panic** - Fires when: Psychology state reaches Panic - Use for: Contrarian opportunity alerts 4. **Market Euphoria** - Fires when: Psychology state reaches Euphoria - Use for: Reversal warning alerts ### How to Set Alerts: 1. Right-click on chart → "Add Alert" 2. Condition: Select "Quantum Market Harmonics" 3. Choose alert type from dropdown 4. Configure expiration, frequency, and notification method 5. Create alert **Recommendation**: Set alerts for Quantum Buy/Sell signals with "Once Per Bar Close" frequency to avoid intra-bar false triggers. --- ## 💡 BEST PRACTICES ### For All Users: 1. **Backtest First** - Test on your specific market and timeframe before live trading - Different assets may perform better with different confidence thresholds - Verify that the No Repaint guarantee works as described 2. **Paper Trade** - Practice with signals on a demo account first - Understand typical signal frequency for your timeframe - Get comfortable with the dashboard interpretation 3. **Risk Management** - Never risk more than 1-2% of capital per trade - Use proper stop losses (not just mental stops) - Position size based on confidence score (larger size at higher confidence) 4. **Consider Context** - QMH signals work best in clear trends or at extremes - During tight consolidation, false signals increase - Major news events can invalidate technical signals ### Optimal Use Cases: **QMH Works Best When:** - ✅ Markets are trending (up or down) - ✅ Volatility is normal to elevated - ✅ Price reaches probability zone extremes - ✅ Multiple timeframes align - ✅ Clear inter-market relationships exist **QMH Is Less Effective When:** - ❌ Extremely low volatility (zones contract too much) - ❌ Sideways choppy markets (conflicting timeframes) - ❌ Flash crashes or news events (correlations break down) - ❌ Very illiquid assets (irregular price action) ### Session Considerations: - **24/7 Markets (Crypto)**: Works on all sessions, but signals may be more reliable during high-volume periods (US/European trading hours) - **Forex**: Best during London/New York overlap when volume is highest - **Stocks**: Most reliable during regular trading hours (not pre-market/after-hours) --- ## ⚠️ LIMITATIONS AND RISKS ### This Indicator Cannot: - **Predict Black Swan Events**: Sudden unexpected events invalidate technical analysis - **Guarantee Profits**: No indicator is 100% accurate; losses will occur - **Replace Risk Management**: Always use stop losses and proper position sizing - **Account for Fundamental Changes**: Company news, economic data, etc. can override technical signals - **Work in All Market Conditions**: Less effective during extreme low volatility or major news events ### Known Limitations: 1. **Multi-Timeframe Lag**: Uses confirmed bars (`close `), so signals appear one bar after conditions met 2. **Correlation Dependency**: CAQE requires sufficient history; may be less reliable on newly listed assets 3. **Computational Load**: Multiple `request.security()` calls may cause slower performance on older devices 4. **Repaint of Dashboard**: Dashboard updates every bar (by design), but signals themselves don't repaint ### Risk Warnings: - Past performance doesn't guarantee future results - Backtesting results may not reflect actual trading results due to slippage, commissions, and execution delays - Different markets and timeframes may produce different results - The indicator should be used as a tool, not as a standalone trading system - Always combine with your own analysis, risk management, and trading plan --- ## 🎓 EDUCATIONAL CONCEPTS This indicator synthesizes several established financial theories and technical analysis concepts: ### Academic Foundations: 1. **Fractal Market Hypothesis** (Edgar Peters) - Markets exhibit self-similar patterns across time scales - Implemented via multi-timeframe resonance analysis 2. **Behavioral Finance** (Kahneman & Tversky) - Investor psychology drives market inefficiencies - Implemented via market psychology state classification 3. **Intermarket Analysis** (John Murphy) - Asset classes correlate and influence each other predictably - Implemented via cross-asset correlation monitoring 4. **Mean Reversion** (Statistical Arbitrage) - Prices tend to revert to statistical norms - Implemented via probability zones and standard deviation bands 5. **Multi-Timeframe Analysis** (Technical Analysis Standard) - Higher timeframe trends dominate lower timeframe noise - Implemented via fractal resonance scoring ### Learning Resources: To better understand the concepts behind QMH: - Read "Intermarket Analysis" by John Murphy (for CAQE concepts) - Study "Thinking, Fast and Slow" by Daniel Kahneman (for psychology concepts) - Review "Fractal Market Analysis" by Edgar Peters (for TFR concepts) - Learn about Bollinger Bands (for TDPZ foundation) --- ## 🔄 VERSION HISTORY AND UPDATES **Current Version: 1.0** This is the initial public release. Future updates will be published using TradingView's Update feature (not as separate publications). Planned improvements may include: - Additional reference assets for CAQE - Optional machine learning-based weight optimization - Customizable psychology state definitions - Alternative probability zone calculations - Performance metrics tracking Check the "Updates" tab on the script page for version history. --- ## 📞 SUPPORT AND FEEDBACK ### How to Get Help: 1. **Read This Description First**: Most questions are answered in the detailed sections above 2. **Check Comments**: Other users may have asked similar questions 3. **Post Comments**: For general questions visible to the community 4. **Use TradingView Messaging**: For private inquiries (if available) ### Providing Useful Feedback: When reporting issues or suggesting improvements: - Specify your asset, timeframe, and settings - Include a screenshot if relevant - Describe expected vs. actual behavior - Check if issue persists with default settings ### Continuous Improvement: This indicator will evolve based on user feedback and market testing. Constructive suggestions for improvements are always welcome. --- ## ⚖️ DISCLAIMER This indicator is provided for **educational and informational purposes only**. It does **not constitute financial advice, investment advice, trading advice, or any other type of advice**. **Important Disclaimers:** - You should **not** rely solely on this indicator to make trading decisions - Always conduct your own research and due diligence - Past performance is not indicative of future results - Trading and investing involve substantial risk of loss - Only trade with capital you can afford to lose - Consider consulting with a licensed financial advisor before trading - The author is not responsible for any trading losses incurred using this indicator **By using this indicator, you acknowledge:** - You understand the risks of trading - You take full responsibility for your trading decisions - You will use proper risk management techniques - You will not hold the author liable for any losses --- ## 🙏 ACKNOWLEDGMENTS This indicator builds upon the collective knowledge of the technical analysis and trading community. While the specific implementation and combination are original, the underlying concepts draw from: - The Pine Script community on TradingView - Academic research in behavioral finance and market microstructure - Classical technical analysis methods developed over decades - Open-source indicators that demonstrate best practices in Pine Script coding Special thanks to TradingView for providing the platform and Pine Script language that make indicators like this possible. --- ## 📚 ADDITIONAL RESOURCES **Pine Script Documentation:** - Official Pine Script Manual: www.tradingview.com **Related Concepts to Study:** - Multi-timeframe analysis techniques - Correlation analysis in financial markets - Behavioral finance principles - Mean reversion strategies - Bollinger Bands methodology **Recommended TradingView Tools:** - Strategy Tester: To backtest signal performance - Bar Replay: To see how signals develop in real-time - Alert System: To receive notifications of new signals --- **Thank you for using Quantum Market Harmonics. Trade safely and responsibly.**
Wskaźnik Pine Script®
od Smart-Day-Trader
Average Daily Range [Blaz]Version 1.0 – Published October 2025: Initial release 1. Overview & Purpose The Average Daily Range is an advanced volatility assessment tool designed to give traders a clear, real-time view of the market's expected daily movement. It calculates the average range between daily highs and lows over a user-defined historical period and projects this average onto the current trading session. By visualising the potential high and low boundaries for the day, this indicator assists in setting realistic profit targets, managing risk effectively, and identifying when price action is becoming overextended relative to its recent volatility profile. It is an essential tool for day traders and swing traders across all markets, including Forex, Stocks, Crypto, Futures, and Commodities. 2. Core Functionality & Key Features The indicator provides a dynamic, multi-faceted analysis of daily volatility: Historical ADR Calculation: Automatically computes the Average Daily Range based on the specified number of previous trading days (configurable from 1 to 20). Real-Time Range Tracking: Monitors and displays the current day's live price range as it develops. Percentage Used Metric: Shows the percentage of the historical ADR that the current day's range has already consumed, providing an immediate gauge of remaining volatility potential. Remaining Range Projection: Visually highlights the potential upward and downward movement remaining to meet the average range, displayed as semi-transparent areas on the chart. Daily Open Reference: Plots customisable vertical separation lines and horizontal price lines at the daily open to clearly anchor the current session's price action. 3. Visual Components & Analytical Insights A fully configured Average Daily Range setup displays several key analytical components that work together to provide a comprehensive volatility overview. 3.1. Information Table A highly customizable data table provides a concise summary of all critical metrics at a glance: Historical Ranges: Displays the individual daily ranges for the selected lookback period. ADR Value: The calculated average range. Today's Range: The live, developing range for the current session. % Used: A colour-coded percentage (turning orange upon exceeding 100% and red upon exceeding 150%) showing how much of the average volatility has been consumed. 3.2. Visual Range Projections Remaining Range Zones: When the current day's range is below the historical average, semi-transparent zones extend from the current day's extreme high and low, illustrating the additional movement required to reach the ADR. This provides an instant visual cue for potential target zones. Daily Open Markers: Clean, customisable lines mark the start of each trading day (vertical line) and the daily open price (horizontal line), helping to contextualise intraday price moves. 4. Input Parameters and Settings 4.1. General Settings Lookback: Set the number of days used to calculate the Average Daily Range (1-20). Set Alert: Configure alerts to be notified when the current day's range consumes a significant portion (e.g., 100% or more) of the historical ADR. 4.2. Table Customization Visibility & Style: Toggle the table and historical data on/off. Fully customise the header and body colours, text colours, border style, and font sizes. Placement & Orientation: Precisely position the table anywhere on the chart (Top/Bottom/Centre, Left/Right) and choose between Horizontal or Vertical layout to best suit your chart layout. 4.3. Visual Style Controls Remaining Range: Toggle the projection zones on/off and customise their colour and transparency. Daily Open Markers: Independently control the visibility, colour, style, and width of the daily separation line and the open price line. 5. Protected Logic & Original Design The Average Daily Range indicator incorporates proprietary logic for efficiently tracking intraday extremes, managing historical data arrays, and dynamically rendering visual elements. The closed-source nature of this tool protects the author's original code structure and optimisation techniques, particularly the real-time area fill projection logic for the remaining daily range and the dynamic table management system. This ensures the indicator remains performant and reliable while being freely accessible to the entire TradingView community. 6. Disclaimer & Terms of Use This indicator, titled Average Daily Range , has been independently developed by the author. The code and its structural logic are original and were written entirely from scratch to reflect a unique and efficient approach to volatility analysis. The internal mechanics were written from scratch and are not based on any publicly available script or third-party code. This tool is provided solely for educational and informational purposes. It is not intended as financial advice, investment guidance, or a specific recommendation to buy or sell any financial instrument. The indicator is designed to assist with technical analysis based on volatility but does not guarantee accuracy or profitability. Trading financial markets involves significant risk, including the possibility of loss of capital. By using this indicator, you acknowledge and accept that you are solely responsible for any decisions you make and for all trading outcomes. No part of this script should be considered a signal or assurance of success in the market.
Wskaźnik Pine Script®
od Blazarx
Trading Lot & Margin Calculator # 💹 Trading Lot & Margin Calculator - Professional Risk Management Tool ## 🎯 Overview A comprehensive, all-in-one calculator dashboard that helps traders determine optimal position sizes, calculate margin requirements, and manage risk effectively across multiple asset classes. This indicator displays directly on your chart as a customizable table, providing real-time calculations based on current market prices. ## ✨ Key Features ### 📊 Three Powerful Calculation Modes: **1. Calculate Lot Size (Risk-Based Position Sizing)** - Input your risk percentage and stop loss in pips - Automatically calculates the optimal lot size for your risk tolerance - Respects margin limitations (configurable margin % cap) - Ensures positions don't exceed minimum lot size (0.01) - Perfect for risk management and proper position sizing **2. Calculate Margin Cost** - Input desired lot size - See exactly how much margin is required - Shows percentage of deposit used - Displays free margin remaining - Warns when insufficient funds **3. Margin to Lots** - Specify a fixed margin amount you want to use - Calculator shows how many lots/contracts you can buy - Ideal for traders with fixed margin budgets ## 🤖 Auto-Detection of Instruments The calculator **automatically detects** what you're trading and adjusts calculations accordingly: ### ✅ Fully Supported: - **💱 Forex Pairs** - All majors, minors, exotics (EURUSD, GBPJPY, etc.) - Standard lot: 100,000 units - JPY pairs: 0.01 pip size, others: 0.0001 - **🛢️ Commodities** - Gold, Silver, Oil - XAUUSD (Gold): 100 oz per lot - XAGUSD (Silver): 5,000 oz per lot - Oil (WTI/Brent): 1,000 barrels per lot - **📈 Indices** - US500, NAS100, US30, DAX, etc. - Correct contract sizes per point - **📊 Stocks** - All individual stocks - 1 lot = 1 share - Direct share calculations ### ⚠️ Known Limitation: - **₿ Crypto calculations may not work properly** on all crypto pairs. Use manual contract size if needed. ## 📋 Dashboard Information Displayed: - 🎯 Optimal/Requested Lot Size - 💰 Margin Required - 📊 Margin % of Deposit - 💵 Free Margin Remaining - 💎 Position Value - 📈 Pip/Point Value - ⚠️ Safety Warnings (insufficient funds, high risk, etc.) - 🔍 Detected Instrument Type - 📦 Contract Size ## ⚙️ Customizable Settings: **Account Settings:** - Account Deposit - Leverage (1:1 to 1:1000) - Max Margin % of Deposit (default 5% for safety) **Risk Management:** - Risk Percentage (for lot size calculation) - Stop Loss in Pips - Lot Amount (for margin cost calculation) - Margin to Use (for margin-to-lots calculation) **Display Options:** - Show/Hide Dashboard - Position: Top/Middle/Bottom, Left/Right - Auto-detect instrument ON/OFF - Manual contract size override ## 🎨 Professional Design - Clean, modern table interface - Color-coded warnings (red = danger, yellow = caution, green = safe) - Large, readable text - Minimal screen space usage - Non-intrusive overlay ## 💡 Use Cases: 1. **Day Traders** - Quick position sizing based on account risk 2. **Swing Traders** - Calculate optimal positions for longer-term setups 3. **Risk Managers** - Ensure positions stay within margin limits 4. **Beginners** - Learn proper position sizing and risk management 5. **Multi-Asset Traders** - Seamlessly switch between forex, commodities, indices, and stocks ## ⚠️ Important Notes: - ✅ Works on all timeframes - ✅ Updates in real-time with price changes - ✅ Minimum lot size enforced (0.01) - ✅ Margin calculations use current chart price - ⚠️ **Crypto calculations may be inaccurate** - verify with your broker - 📌 Always verify calculations with your broker's specifications - 📌 Contract sizes may vary by broker ## 🚀 How to Use: 1. Add indicator to any chart 2. Click settings ⚙️ icon 3. Enter your account details (deposit, leverage) 4. Choose calculation mode 5. Input your parameters 6. View optimal lot size and margin requirements on dashboard ## 📈 Perfect For: - Forex traders managing multiple currency pairs - Commodity traders (Gold, Silver, Oil) - Index traders (S&P 500, NASDAQ, etc.) - Stock traders - Anyone who wants professional risk management ## 🛡️ Risk Management Features: - Configurable margin % cap prevents over-leveraging - Risk-based position sizing protects your account - Warnings for high risk, insufficient funds, margin limitations - Prevents positions below minimum lot size --- **Trade smarter, not harder. Calculate before you trade!** 📊💪 --- ## Version Notes: - Pine Script v6 - Overlay mode for chart display - No external dependencies - Lightweight and fast **Disclaimer:** This calculator is for educational and informational purposes only. Always verify calculations with your broker and trade at your own risk. Past performance does not guarantee future results. ---
Wskaźnik Pine Script®
od Makshels
Broad Market for Crypto + index# Broad Market Indicator for Crypto ## Overview The Broad Market Indicator for Crypto helps traders assess the strength and divergence of individual cryptocurrency assets relative to the overall market. By comparing price deviations across multiple assets, this indicator reveals whether a specific coin is moving in sync with or diverging from the broader crypto market trend. ## How It Works This indicator calculates percentage deviations from simple moving averages (SMA) for both individual assets and an equal-weighted market index. The core methodology: 1. **Deviation Calculation**: For each asset, the indicator measures how far the current price has moved from its SMA over a specified lookback period (default: 24 hours). The deviation is expressed as a percentage: `(Current Price - SMA) / SMA × 100` 2. **Market Index Construction**: An equal-weighted index is built from selected cryptocurrencies (up to 15 assets). The default composition includes major crypto assets: BTC, ETH, BNB, SOL, XRP, ADA, AVAX, LINK, DOGE, and TRX. 3. **Comparative Analysis**: The indicator displays both the current instrument's deviation and the market index deviation on the same panel, making it easy to spot relative strength or weakness. ## Key Features - **Customizable Asset Selection**: Choose up to 15 different cryptocurrencies to include in your market index - **Flexible Configuration**: Toggle individual assets on/off for display and index calculation - **Current Instrument Tracking**: Automatically plots the deviation of whatever chart you're viewing - **Visual Clarity**: Color-coded lines for easy differentiation between assets, with the market index shown as a filled area - **Adjustable Lookback Period**: Modify the SMA period to match your trading timeframe ## How to Use ### Identifying Market Divergences - When the current instrument deviates significantly above the index, it shows relative strength - When it deviates below, it indicates relative weakness - Assets clustering around zero suggest neutral market conditions ### Trend Confirmation - If both the index and your asset are rising together (positive deviation), it confirms a broad market uptrend - Divergence between asset and index can signal unique fundamental factors or early trend changes ### Entry/Exit Signals - Extreme deviations from the index may indicate overbought/oversold conditions relative to the market - Convergence back toward the index line can signal mean reversion opportunities ## Settings - **Lookback Period**: Adjust the SMA calculation period (default: 24 hours) - **Asset Configuration**: Select which cryptocurrencies to monitor and include in the index - **Display Options**: Show/hide individual assets, current instrument, and market index - **Color Customization**: Personalize colors for better visual analysis ## Best Practices - Use on higher timeframes (4H, Daily) for more reliable signals - Combine with volume analysis for confirmation - Consider fundamental news when assets show extreme divergence - Adjust the asset basket to match your trading focus (DeFi, L1s, memecoins, etc.) ## Technical Notes - The indicator uses `request.security()` to fetch data from multiple symbols - Deviations are calculated independently for each asset - The zero line represents perfect alignment with the moving average - Index calculation automatically adjusts based on active assets ## Default Assets 1. BTC (Bitcoin) - BINANCE:BTCUSDT 2. ETH (Ethereum) - BINANCE:ETHUSDT 3. BNB (Binance Coin) - BINANCE:BNBUSDT 4. SOL (Solana) - BINANCE:SOLUSDT 5. XRP (Ripple) - BINANCE:XRPUSDT 6. ADA (Cardano) - BINANCE:ADAUSDT 7. AVAX (Avalanche) - BINANCE:AVAXUSDT 8. LINK (Chainlink) - BINANCE:LINKUSDT 9. DOGE (Dogecoin) - BINANCE:DOGEUSDT 10. TRX (Tron) - BINANCE:TRXUSDT Additional slots (11-15) are available for custom asset selection. --- This indicator is particularly useful for cryptocurrency traders seeking to understand market breadth and identify opportunities where specific assets are diverging from overall market sentiment.
Wskaźnik Pine Script®
od AlekMel
VOLUME PROFILE WITH FOOTPRINT AND IMBALANCEVOLUME PROFILE WITH FOOTPRINT AND IMBALANCE A professional-grade market structure analysis tool that combines three powerful trading concepts into one comprehensive indicator: Volume Profile, Footprint Charts, and Imbalance detection. This script provides optimum-level market analysis for trading. KEY FEATURES 1. Multi-Day Volume Profile Customizable Row Density: Adjust price level granularity for precise volume distribution analysis Point of Control (POC): Automatically identifies the price level with highest traded volume Value Area Calculation: Highlights the price range containing 70% of the day's volume (customizable percentage) Value Area High (VAH) & Low (VAL): Clear demarcation of institutional acceptance zones Horizontal Volume Bars: Visual representation of buying vs. selling pressure at each price level Color-Coded Volume: Distinguishes between value area volume and outlier volume for better visual clarity 2. Previous Day Reference Levels Previous Day High/Low (PDH/PDL): Critical support/resistance levels from prior session Previous Day POC: Yesterday's highest volume node - often acts as magnetic price level Previous Day VAH/VAL: Prior session's value boundaries for gap analysis and mean reversion setups All previous day levels extend into current session with customizable colors and line styles 3. Virgin Point of Control (VPOC) Untouched POC Identification: Automatically tracks POC levels that haven't been revisited by price Real-time Validation: Monitors whether subsequent price action has tested each historical POC Multi-Day Tracking: Maintains VPOC levels across multiple sessions until filled High-Probability Targets: Virgin POCs often act as magnets for future price action 4. Footprint Zone Analysis Footprint Zone Detection: Identifies price levels touched only once during the session Automated Ribbon Consolidation: Groups consecutive Footprint Zone into visual zones Price Range Sensitivity: Automatically adjusts granularity based on instrument price Historical Persistence: Consolidates previous day's footprint zones for multi-day context Auction Failure Zones: Footprint Zone often indicate areas of poor liquidity and potential reversal points 5. Three-Candle Imbalance Detection Bullish Imbalance Bearish Imbalance Visual Markers: Clear circular indicators on all three candles forming the imbalance Customizable Colors: Separate colors for bullish and bearish imbalances Gap Validation: Ensures meaningful price displacement before flagging imbalance
Wskaźnik Pine Script®
od HARESHR333
Kernel Market Dynamics🔍 Kernel Market Dynamics Pro - Advanced Distribution Divergence Detection System OVERVIEW Kernel Market Dynamics Pro (KMD Pro) is a revolutionary market regime detection system that employs Maximum Mean Discrepancy (MMD) - a cutting-edge statistical technique from machine learning - to identify when market behavior diverges from its recent historical distribution patterns. The system transforms complex statistical divergence analysis into actionable trading signals through kernel density estimation, regime classification algorithms, and multi-dimensional visualization frameworks that reveal hidden market transitions before traditional indicators can detect them. WHAT MAKES IT ORIGINAL While conventional indicators measure price or momentum divergence, KMD Pro analyzes distribution divergence - detecting when the statistical properties of market returns fundamentally shift from their baseline state. This approach, borrowed from high-frequency trading and quantitative finance, uses kernel methods to map market data into high-dimensional feature spaces where regime changes become mathematically detectable. The system is the first TradingView implementation to combine MMD with real-time regime visualization, making institutional-grade statistical arbitrage techniques accessible to retail traders. HOW IT WORKS (Technical Methodology) 1. KERNEL DENSITY ESTIMATION ENGINE Maximum Mean Discrepancy (MMD) Calculation: The core innovation - measures distance between probability distributions: • Maps return distributions to Reproducing Kernel Hilbert Space (RKHS) • Computes empirical mean embeddings for reference and test windows • Calculates supremum of mean differences across all RKHS functions • MMD = ||μ_P - μ_Q||_H where H is the RKHS induced by kernel k Three Kernel Functions Available: RBF (Radial Basis Function) Kernel: • k(x,y) = exp(-||x-y||²/2σ²) • Gaussian kernel with smooth, infinite-dimensional feature mapping • Bandwidth σ controls sensitivity (0.5-10.0 user configurable) • Optimal for normally distributed returns • Default choice providing balanced sensitivity Laplacian Kernel: • k(x,y) = exp(-|x-y|/σ) • Exponential decay with heavier tails than RBF • More sensitive to outliers and sudden moves • Ideal for volatile, news-driven markets • Faster regime shift detection at cost of more false positives Cauchy Kernel: • k(x,y) = 1/(1 + ||x-y||²/σ²) • Heavy-tailed distribution from statistical physics • Robust to extreme values and fat-tail events • Best for cryptocurrency and emerging markets • Most stable signals with fewer whipsaws Implementation Details: • Reference window: 30-300 bars of baseline distribution • Test window: 10-100 bars of recent distribution • Double-sum kernel matrix computation with O(m*n) complexity • EMA smoothing (period 3) reduces noise in raw MMD • Real-time updates every bar with incremental calculation 2. REGIME DETECTION FRAMEWORK Three-State Regime Classification: STABLE Regime (MMD < threshold): • Market follows historical distribution patterns • Mean-reverting behavior dominates • Low probability of breakouts • Reduced position sizing recommended • Visual: Subtle background coloring SHIFTING Regime (threshold < MMD < 2×threshold): • Distribution divergence detected • Transition period with directional bias emerging • Optimal entry zone for trend-following • Increased volatility expected • Visual: Yellow/orange zone highlighting EXTREME Regime (MMD > 2×threshold): • Severe distribution anomaly • Black swan or structural break potential • Maximum caution required • Consider hedging or exit • Visual: Red/magenta warning zones Adaptive Threshold System: • Base threshold: 0.05-1.0 (default 0.15) • Volatility adjustment: ±30% based on ATR ratio • Regime persistence: 20-bar minimum for stability • Cooldown periods prevent signal clustering 3. DIRECTIONAL BIAS DETERMINATION Multi-Factor Direction Analysis: Distribution Mean Comparison: • Recent mean = SMA(normalized_returns, test_window) • Reference mean = SMA(normalized_returns, reference_window) • Direction = sign(recent_mean - reference_mean) Momentum Confluence: • Price momentum = close - close • Volume momentum = volume/SMA(volume, reference_window) • Weighted composite direction score Trend Alignment: • Fast EMA vs Slow EMA positioning • Slope analysis of regression line • Multi-timeframe bias confirmation (optional) 4. SIGNAL GENERATION ARCHITECTURE Entry Signal Logic: Stage 1 - Regime Shift Detection: • MMD crosses above threshold • Sustained for minimum 2 bars • No signals within cooldown period Stage 2 - Direction Confirmation: • Distribution mean aligns with momentum • Volume ratio > 1.0 (optional) • Price above/below VWAP (optional) Stage 3 - Risk Assessment: • Calculate ATR-based stop distance • Verify risk/reward ratio > 1.5 • Check for nearby support/resistance Stage 4 - Signal Generation: • Long: Regime shift + bullish direction • Short: Regime shift + bearish direction • Extreme: MMD > 2×threshold warning 5. PROBABILITY CLOUD VISUALIZATION Adaptive Confidence Intervals: • Standard deviation multiplier = 1 + MMD × 3 • Inner band: ±0.5 ATR × multiplier (68% probability) • Outer band: ±1.0 ATR × multiplier (95% probability) • Width expands with divergence magnitude • Real-time adjustment every bar Interpretation: • Narrow cloud: Low uncertainty, stable regime • Wide cloud: High uncertainty, shifting regime • Asymmetric cloud: Directional bias present 6. MOMENTUM FLOW VECTORS Three-Style Momentum Visualization: Flow Arrows: • Length proportional to momentum strength • Width indicates confidence (1-3 pixels) • Angle shows rate of change • Frequency: Every 5 bars or on events Gradient Bars: • Vertical lines from price • Height = momentum/ATR ratio • Opacity based on strength • Continuous flow indication Momentum Ribbon: • Envelope around price action • Expands in momentum direction • Color intensity shows strength 7. SIGNAL CONNECTION SYSTEM Relationship Mapping: • Links consecutive signals with lines • Solid lines: Same direction (continuation) • Dotted lines: Opposite direction (reversal) • Maximum 10 connections maintained • Distance limit: 100 bars Purpose: • Identifies signal clusters • Shows trend development • Reveals regime persistence • Confirms directional bias 8. REGIME ZONE MAPPING Unified Zone Visualization: • Main zones: Full regime periods (entry to exit) • Emphasis zones: Specific trigger points • Historical memory: Last 20 regime shifts • Color gradient based on intensity • Border style indicates zone type Zone Analytics: • Duration tracking • Maximum excursion • Retest probability • Support/resistance conversion 9. DYNAMIC RISK MANAGEMENT ATR-Based Position Sizing: • Stop loss: 1.0 × ATR from entry • Target 1: 2.0 × ATR (2R) • Target 2: 4.0 × ATR (4R) • Volatility-adjusted scaling Visual Target System: • Entry pointer lines • Target boxes with prices • Stop boxes with invalidation • Real-time P&L tracking 10. PROFESSIONAL DASHBOARD Real-Time Metrics Display: Primary Metrics: • Current MMD value and threshold • Risk level (MMD/threshold ratio) • Velocity (rate of change) • Acceleration (second derivative) Signal Information: • Active signal type and entry • Stop loss and targets • Current P&L percentage • Bars since signal Market Metrics: • Directional bias (BULL/BEAR) • Confidence percentage • Win rate statistics • Signal count tracking Visual Design: • Four position options • Three size modes • Five color themes • Gauge visualizations • Status banners 11. MMD INFO PANEL Floating Statistics: • Compact 3×4 table • MMD vs threshold comparison • Velocity with direction arrows • Current bias indication • Always-visible reference FIVE COLOR THEMES Quantum: Cyan/Magenta/Yellow - Modern, high contrast, optimal visibility Matrix: Green/Red - Classic terminal aesthetic, traditional Fire: Orange/Gold/Red - Warm spectrum, energetic feel Aurora: Northern lights palette - Unique, beautiful gradients Nebula: Deep space colors - Purple/Blue, futuristic HOW TO USE Step 1: Select Your Kernel • RBF for normal markets (stocks, forex majors) • Laplacian for volatile markets (small-caps, news-driven) • Cauchy for fat-tail markets (crypto, emerging markets) Step 2: Configure Bandwidth • 0.5-2.0: Scalping (high sensitivity) • 2.0-5.0: Day trading (balanced) • 5.0-10.0: Swing trading (smooth signals) Step 3: Set Analysis Windows • Reference: 3-5× your holding period • Test: Reference ÷ 3 approximately • Adjust based on timeframe Step 4: Calibrate Threshold • Start with 0.15 default • Increase if too many signals • Decrease for earlier detection Step 5: Enable Visuals • Probability Cloud for volatility assessment • Momentum Flow for direction confirmation • Regime Zones for historical context • Signal Connections for trend visualization Step 6: Monitor Dashboard • Check MMD vs threshold • Verify regime state • Confirm directional bias • Review confidence metrics Step 7: Execute Signals • Wait for triangle markers • Verify regime shift confirmed • Check risk/reward setup • Enter at close or next open Step 8: Manage Position • Place stop at calculated level • Scale out at Target 1 (2R) • Trail remainder to Target 2 (4R) • Exit if regime reverses OPTIMIZATION GUIDE By Market Type: Forex Majors: • Kernel: RBF • Bandwidth: 2.0-3.0 • Windows: 100/30 • Threshold: 0.15 Stock Indices: • Kernel: RBF • Bandwidth: 3.0-4.0 • Windows: 150/50 • Threshold: 0.20 Cryptocurrencies: • Kernel: Cauchy • Bandwidth: 2.5-3.5 • Windows: 100/30 • Threshold: 0.10-0.15 Commodities: • Kernel: Laplacian • Bandwidth: 2.0-3.0 • Windows: 200/60 • Threshold: 0.15-0.25 By Timeframe: Scalping (1-5m): • Test Window: 10-20 • Reference: 50-100 • Bandwidth: 1.0-2.0 • Cooldown: 5-10 bars Day Trading (15m-1H): • Test Window: 30-50 • Reference: 100-150 • Bandwidth: 2.0-3.0 • Cooldown: 10-20 bars Swing Trading (4H-Daily): • Test Window: 50-100 • Reference: 200-300 • Bandwidth: 3.0-5.0 • Cooldown: 20-50 bars ADVANCED FEATURES Multi-Timeframe Capability: • HTF MMD calculation via security() • Regime alignment across timeframes • Fractal analysis support Statistical Arbitrage Mode: • Pair trading applications • Spread divergence detection • Cointegration breaks Machine Learning Integration: • Export signals for ML training • Regime labels for classification • Feature extraction support PERFORMANCE METRICS Computational Complexity: • MMD calculation: O(m×n) where m,n are window sizes • Memory usage: O(m+n) for kernel matrices • Update frequency: Every bar (real-time) • Optimization: Incremental updates where possible Typical Signal Frequency: • Conservative settings: 2-5 signals/week • Balanced settings: 5-10 signals/week • Aggressive settings: 10-20 signals/week Win Rate Expectations: • Trend following mode: 40-50% wins, 2:1 reward/risk • Mean reversion mode: 60-70% wins, 1:1 reward/risk • Depends heavily on market conditions IMPORTANT DISCLAIMERS • This indicator detects statistical divergence, not future price direction • MMD measures distribution distance, not predictive probability • Past regime shifts do not guarantee future performance • Kernel methods are descriptive statistics, not AI predictions • Requires minimum 100 bars historical data for stability • Performance varies significantly across market conditions • Not suitable for illiquid or heavily manipulated markets • Always use proper risk management and position sizing • Backtest thoroughly on your specific instruments • This is an analysis tool, not a complete trading system THEORETICAL FOUNDATION The Maximum Mean Discrepancy was introduced by Gretton et al. (2012) as a kernel-based statistical test for comparing distributions. In financial markets, we adapt this technique to detect when return distributions shift, indicating potential regime changes. The mathematical rigor of MMD provides a robust, non-parametric approach to identifying market transitions without assuming specific distribution shapes. SUPPORT & UPDATES • Questions or configuration help via TradingView messaging • Bug reports addressed within 48 hours • Feature requests considered for monthly updates • Video tutorials available on request • Join our community for strategy discussions FINAL NOTES KMD Pro represents a paradigm shift in technical analysis - moving from price-based indicators to distribution-based detection. By measuring statistical divergence rather than price divergence, the system identifies regime changes that precede traditional breakouts. This anticipatory capability, combined with comprehensive visualization and risk management, provides traders with an institutional-grade toolkit for navigating modern market dynamics. Remember: The edge comes not from the indicator alone, but from understanding when market distributions diverge from their normal state and positioning accordingly. Use KMD Pro as part of a complete trading strategy that includes fundamental analysis, risk management, and market context.
Wskaźnik Pine Script®
od DskyzInvestments
天干地支标注（当前视窗范围 + 居中标签）🇨🇳 中文说明 天干地支标注（自动匹配周期） 本指标会根据图表的时间周期（年、月、日、小时、分钟）自动计算并在每根 K 线上方显示对应的天干地支。 • 自动识别图表周期（年/月/日/时/分） • 仅显示当前视窗内的柱子，性能高、不卡顿 • 可自定义每隔 N 根显示一次（默认每根） • 支持居中矩形标签（label.style_label_center），清晰易读 • 无需区分暗黑/亮色主题，自动兼容所有图表样式 可作为金融时间序列与中国传统历法（干支纪时）结合的参考工具， 在时间周期研究、风水、气运周期、江恩时间分析等领域有辅助价值。 ⸻ 🇬🇧 English Description (for international visibility) Heavenly Stems & Earthly Branches Marker (Auto-Adaptive Version) This indicator automatically calculates and displays the corresponding Chinese Heavenly Stems and Earthly Branches (Ganzhi) for each candlestick, based on the chart’s timeframe (Year, Month, Day, Hour, or Minute). • Auto-detects chart timeframe • Draws only within the current visible window (optimized performance) • Adjustable display interval (e.g., show every N bars) • Uses centered label style for clarity • Compatible with both dark and light themes Useful for combining Chinese calendar cycles with financial time analysis, time-cycle studies, or Gann-style timing models.
Wskaźnik Pine Script®
od realdan_1
ICOptimizerLibrary "ICOptimizer" Library for IC-based parameter optimization findOptimalParam(testParams, icValues, currentParam, smoothing)   Find optimal parameter from array of IC values   Parameters:      testParams (array) : Array of parameter values being tested      icValues (array) : Array of IC values for each parameter (same size as testParams)      currentParam (float) : Current parameter value (for smoothing)      smoothing (simple float) : Smoothing factor (0-1, e.g., 0.2 means 20% new, 80% old)   Returns: New parameter value, its IC, and array index adaptiveParamWithStarvation(opt, testParams, icValues, smoothing, starvationThreshold, starvationJumpSize)   Adaptive parameter selection with starvation handling   Parameters:      opt (ICOptimizer) : ICOptimizer object      testParams (array) : Array of parameter values      icValues (array) : Array of IC values for each parameter      smoothing (simple float) : Normal smoothing factor      starvationThreshold (simple int) : Number of updates before triggering starvation mode      starvationJumpSize (simple float) : Jump size when in starvation (as fraction of range)   Returns: Updated parameter and IC detectAndAdjustDomination(longCount, shortCount, currentLongLevel, currentShortLevel, dominationRatio, jumpSize, minLevel, maxLevel)   Detect signal imbalance and adjust parameters   Parameters:      longCount (int) : Number of long signals in period      shortCount (int) : Number of short signals in period      currentLongLevel (float) : Current long threshold      currentShortLevel (float) : Current short threshold      dominationRatio (simple int) : Ratio threshold (e.g., 4 = 4:1 imbalance)      jumpSize (simple float) : Size of adjustment      minLevel (simple float) : Minimum allowed level      maxLevel (simple float) : Maximum allowed level   Returns: calcIC(signals, returns, lookback)   Parameters:      signals (float)      returns (float)      lookback (simple int) classifyIC(currentIC, icWindow, goodPercentile, badPercentile)   Parameters:      currentIC (float)      icWindow (simple int)      goodPercentile (simple int)      badPercentile (simple int) evaluateSignal(signal, forwardReturn)   Parameters:      signal (float)      forwardReturn (float) updateOptimizerState(opt, signal, forwardReturn, currentIC, metaICPeriod)   Parameters:      opt (ICOptimizer)      signal (float)      forwardReturn (float)      currentIC (float)      metaICPeriod (simple int) calcSuccessRate(successful, total)   Parameters:      successful (int)      total (int) createICStatsTable(opt, paramName, normalSuccess, normalTotal)   Parameters:      opt (ICOptimizer)      paramName (string)      normalSuccess (int)      normalTotal (int) initOptimizer(initialParam)   Parameters:      initialParam (float) ICOptimizer   Fields:      currentParam (series float)      currentIC (series float)      metaIC (series float)      totalSignals (series int)      successfulSignals (series int)      goodICSignals (series int)      goodICSuccess (series int)      nonBadICSignals (series int)      nonBadICSuccess (series int)      goodICThreshold (series float)      badICThreshold (series float)      updateCounter (series int)
Biblioteka Pine Script®
od cybermediaboy
IC optimiser libLibrary "IC optimiser lib" Library for IC-based parameter optimization findOptimalParam(testParams, icValues, currentParam, smoothing)   Find optimal parameter from array of IC values   Parameters:      testParams (array) : Array of parameter values being tested      icValues (array) : Array of IC values for each parameter (same size as testParams)      currentParam (float) : Current parameter value (for smoothing)      smoothing (simple float) : Smoothing factor (0-1, e.g., 0.2 means 20% new, 80% old)   Returns: New parameter value, its IC, and array index adaptiveParamWithStarvation(opt, testParams, icValues, smoothing, starvationThreshold, starvationJumpSize)   Adaptive parameter selection with starvation handling   Parameters:      opt (ICOptimizer) : ICOptimizer object      testParams (array) : Array of parameter values      icValues (array) : Array of IC values for each parameter      smoothing (simple float) : Normal smoothing factor      starvationThreshold (simple int) : Number of updates before triggering starvation mode      starvationJumpSize (simple float) : Jump size when in starvation (as fraction of range)   Returns: Updated parameter and IC detectAndAdjustDomination(longCount, shortCount, currentLongLevel, currentShortLevel, dominationRatio, jumpSize, minLevel, maxLevel)   Detect signal imbalance and adjust parameters   Parameters:      longCount (int) : Number of long signals in period      shortCount (int) : Number of short signals in period      currentLongLevel (float) : Current long threshold      currentShortLevel (float) : Current short threshold      dominationRatio (simple int) : Ratio threshold (e.g., 4 = 4:1 imbalance)      jumpSize (simple float) : Size of adjustment      minLevel (simple float) : Minimum allowed level      maxLevel (simple float) : Maximum allowed level   Returns: calcIC(signals, returns, lookback)   Parameters:      signals (float)      returns (float)      lookback (simple int) classifyIC(currentIC, icWindow, goodPercentile, badPercentile)   Parameters:      currentIC (float)      icWindow (simple int)      goodPercentile (simple int)      badPercentile (simple int) evaluateSignal(signal, forwardReturn)   Parameters:      signal (float)      forwardReturn (float) updateOptimizerState(opt, signal, forwardReturn, currentIC, metaICPeriod)   Parameters:      opt (ICOptimizer)      signal (float)      forwardReturn (float)      currentIC (float)      metaICPeriod (simple int) calcSuccessRate(successful, total)   Parameters:      successful (int)      total (int) createICStatsTable(opt, paramName, normalSuccess, normalTotal)   Parameters:      opt (ICOptimizer)      paramName (string)      normalSuccess (int)      normalTotal (int) initOptimizer(initialParam)   Parameters:      initialParam (float) ICOptimizer   Fields:      currentParam (series float)      currentIC (series float)      metaIC (series float)      totalSignals (series int)      successfulSignals (series int)      goodICSignals (series int)      goodICSuccess (series int)      nonBadICSignals (series int)      nonBadICSuccess (series int)      goodICThreshold (series float)      badICThreshold (series float)      updateCounter (series int)
Biblioteka Pine Script®
od cybermediaboy
ATR %ATR % Oscillator A simple and effective Average True Range (ATR) indicator displayed as a percentage of the current price in a separate panel. FEATURES: • ATR displayed as percentage of current price for easy cross-asset comparison • EMA smoothing line using the same period as ATR • Configurable ATR period (default: 20) • Clean visualization with zero reference line HOW IT WORKS: The indicator calculates ATR and converts it to a percentage: (ATR / Close) × 100 This normalization allows you to: - Compare volatility across different instruments regardless of price - Identify high and low volatility periods - Use the EMA line to spot volatility trends PARAMETERS: ATR Period - The lookback period for ATR calculation (default: 20) Timeframe - Choose any timeframe for ATR calculation independently from the chart timeframe (default: chart timeframe)
Wskaźnik Pine Script®
od audrius_exe
IPDA Ranges – ProIPDA Ranges – Pro This indicator plots Institutional Price Delivery Algorithm (IPDA) ranges based on lookback periods of 20, 40, and 60 days, as taught by ICT (Inner Circle Trader). It visualizes premium and discount zones, equilibrium levels, quadrants, and sub-quadrants to help traders identify key price areas and potential market biases. Key Features: - Displays IPDA ranges as boxes or lines, with customizable colors for discount, equilibrium, and premium zones. - Optionally shades the 25%-75% mid-zone for each range. - Supports quadrants (25% steps) and sub-quadrants with lines and labels for detailed price segmentation. - Includes a table displaying either discount/premium status or percentage from equilibrium for each range. - Configurable alerts for entry/exit into the mid-zone. - Visual options include line styles, label sizes, price display on labels, and buffers for zone extension. Settings Overview: - IPDA Intervals: Enable/disable IPDA20, IPDA40, IPDA60; toggle quadrants, sub-quadrants, mid-zone shading, and drawing with lines vs. boxes. - Colors and Styles: Customize colors for zones, lines, labels; select solid/dotted/dashed styles for borders and lines. - Appearance: Adjust label and table sizes, table position, and background opacity. - Labels: Show/hide per-range labels and include prices. - Alerts: Enable mid-zone entry/exit alerts. Usage: Add the indicator to your chart and select the desired IPDA intervals. The ranges update dynamically based on daily highs and lows. Use the table for quick reference to current positioning (discount/premium or percentage). The mid-zone shading helps identify consolidation areas, while quadrants and sub-quadrants assist in pinpointing potential support/resistance levels. © MadMonkTrading
Wskaźnik Pine Script®
od MadMonkTrading
1
Kelly Wave Position Matrix 20251024 V1 ZENYOUNGA simple table is designed for use when opening a position. It applies the Kelly formula to calculate a more scientific position size based on win rate and risk–reward ratio. At the same time, it displays 1.65× ATR stop-loss levels for both long and short positions to serve as a reference for comparing with existing stop-loss placements. Additionally, the table back-calculates the corresponding position size based on a 2% total capital loss limit, using the actual loss ratio. It also shows the current wave trend status as a pre-filtering condition. Overall, this table integrates the core elements of trading — trend (wave confirmation), win rate, risk–reward ratio, and position sizing — making it an effective checklist before entering a trade. Its purpose is to help achieve a probabilistic edge and ensure positive expected value in trading decisions.
Wskaźnik Pine Script®
od xiamenmp08
CNN Fear and Greed Index📊 CNN Fear & Greed Index — by @victhoreb Tap into the emotional heartbeat of the U.S. stock market with this powerful CNN-inspired Fear & Greed Index! 🧠📉📈 Designed to mirror the sentiment framework popularized by CNN Business, this indicator blends 7 key market signals into a single score from 0 (😱 Extreme Fear) to 100 (🚀 Extreme Greed), helping you navigate volatility with confidence. 🧩 What’s Inside? Each component captures a unique behavioral or macroeconomic force: - ⚡ Market Momentum: Tracks how far the S&P 500 is from its 125-day average — a pulse check on trend strength. - 🏛️ Stock Price Strength: Measures the NYSE Highs vs. Lows — are more stocks breaking out or breaking down? - 🌊 Stock Price Breadth: Uses the McClellan Volume Summation Index to assess market-wide participation. - ☎️ Put/Call Ratio: A 5-day average of the equity options market — are traders hedging or chasing? - 🌪️ Volatility (VIX): Compares the VIX to its 50-day average — rising fear or calming nerves? - 🛡️ Safe Haven Demand: Contrasts stock returns with bond returns — are investors seeking shelter or risk? - 💣 Junk Bond Demand: Inverted high-yield spread — tighter spreads = more risk-on appetite. 🎯 Why Use It? This index gives you a quantified view of Wall Street’s mood, helping you: - Spot emotional extremes that often precede reversals - Confirm or challenge your directional bias - Stay grounded when the market gets irrational 🧭 Visual Sentiment Meter A custom offset sentiment meter shows current positioning with intuitive labels: - 😱 Extreme Fear - 😨 Fear - 😐 Neutral - 😄 Greed - 🚀 Extreme Greed Color gradients and dynamic labels make it easy to interpret at a glance. Ready to trade with the crowd—or against it? Add this indicator to your chart and let sentiment guide your strategy! 📈🧠
Wskaźnik Pine Script®
od victhoreb
Crypto Fear and Greed Index📊 Crypto Fear & Greed Index — by @victhoreb Decode the emotional pulse of the crypto market with this all-in-one Fear & Greed Index! 🧠💰 This custom-built indicator blends 7 powerful market signals into a single sentiment score ranging from 0 (😱 Extreme Fear) to 100 (🚀 Extreme Greed), helping you spot potential tops, bottoms, and trend shifts with clarity. 🔍 What’s under the hood? Each component reflects a unique psychological or macroeconomic force: - ⚡ Market Momentum: Measures how far BTC is from its 125-day average — are we overextended or undervalued? - 📈 Crypto Price Strength: Tracks the dominance of altcoins (OTHERS.D) — rising dominance = growing risk appetite. - 💵 Digital Dollar Dominance (USDT.D): A proxy for stablecoin demand — more USDT dominance = risk-off behavior. - 🐦 Twitter Sentiment (LunarCrush): Captures real-time posts on TWITTER about Bitcoin — are the crowds euphoric or panicking? - 🌪️ Volatility (VIX): Inverted VIX deviation — higher fear in traditional markets often spills into crypto. - 🛡️ Safe Haven Demand: Compares BTC returns vs. US10Y bonds — are investors fleeing to safety or embracing risk? - 🧨 Junk Bond Demand (BAMLH0A0HYM2): Inverted high-yield spread — tighter spreads = more greed in credit markets. 🎯 Why use it? This index gives you a quantified view of market sentiment, helping you: - Anticipate reversals during emotional extremes - Confirm trend strength or weakness - Stay objective when the market gets irrational 🧭 Visual Dashboard A custom offset sentiment meter shows current positioning with intuitive labels: - 😱 Extreme Fear - 😨 Fear - 😐 Neutral - 😄 Greed - 🚀 Extreme Greed Color gradients and dynamic labels make it easy to interpret at a glance. Ready to trade with the crowd—or against it? Add this indicator to your chart and let sentiment guide your strategy! 📈🧠
Wskaźnik Pine Script®
od victhoreb
Statistical Price Deviation Index (MAD/VWMA)SPDI is a statistical oscillator designed to detect potential price reversal zones by measuring how far price deviates from its typical behavior within a defined rolling window. Instead of using momentum or moving averages like traditional indicators, SPDI applies robust statistics - a rolling median and Mean Absolute Deviation (MAD) - to calculate a normalized measure of price displacement. This normalization keeps the output bounded (from −1 to +1 by default), producing a stable and consistent oscillator that adapts to changing volatility conditions. The second line in SPDI uses a Volume-Weighted Moving Average (VWMA) instead of a simple price median. This creates a complementary oscillator showing statistically weighted deviations based on traded volume. When both oscillators align in their extremes, strong confluence reversal signals are generated. How It Works For each bar, SPDI calculates the median price of the last N bars (default 100). It then measures how far the current bar’s midpoint deviates from that rolling median. The Mean Absolute Deviation (MAD) of those distances defines a “normal” range of fluctuation. The deviation is normalized and compressed via a tanh mapping, keeping the oscillator in fixed boundaries (−1 to +1). The same logic is applied to the VWMA line to gauge volume-weighted deviations. How to Use The blue line (Price MAD) represents pure price deviation. The green line (VWMA Disp) shows the volume-weighted deviation. Overbought (red) zones indicate statistically extreme upward deviation -> potential short-term overextension. Oversold (green) zones indicate statistically extreme downward deviation -> potential rebound area. Confluence signals (both lines hitting the same extreme) often mark strong reversal points. Settings Tips Lookback length controls how much historical data defines “normal” behavior. Larger = smoother, smaller = more sensitive. Smoothing (RMA length) can reduce noise without changing the overall statistical logic. Output scale can be set to either −1..+1 or 0..100, depending on your visual preference. Alerts and color fills are fully customizable in the Style tab. Summary: SPDI transforms raw price and volume data into a statistically bounded deviation index. When both Price MAD and VWMA Disp reach joint extremes, it highlights probable market turning points - offering traders a clean, data-driven way to spot potential reversals ahead of time.
Wskaźnik Pine Script®
od exploretranspose
OBTrendDelta Volume Delta & Order Block SuiteOB Trend Delta V1 - Order Block & Volume Delta Indicator ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 OVERVIEW OB Trend Delta V1 is a technical indicator that combines Order Blocks analysis (institutional support/resistance zones) with Volume Delta (buying vs selling pressure) to provide insights on setup quality and market dynamics. The indicator visually displays zones of interest, volume pressure, and a quality scoring system to assist in technical analysis of any market. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎯 CORE CONCEPT ▸ ORDER BLOCKS Order Blocks are price zones where large institutions executed significant operations. These areas tend to act as support (Bull OB) or resistance (Bear OB) when price returns to them. How to interpret: 🟢 Bull Order Block: Green zone where institutional buyers entered strongly → Potential support 🔴 Bear Order Block: Red zone where institutional sellers entered strongly → Potential resistance ▸ VOLUME DELTA Volume Delta measures the difference between buying and selling volume in each candle, revealing which side of the market is dominating. How to interpret: ✅ Positive Delta (green histogram): Buyers dominating → Bullish pressure ❌ Negative Delta (red histogram): Sellers dominating → Bearish pressure ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📈 WHAT THE INDICATOR SHOWS 1️⃣ TREND DETECTION The indicator identifies the main market direction using moving averages and trend strength analysis (ADX), visually highlighting when the market is in: Uptrend (Bullish Trend) Downtrend (Bearish Trend) Ranging (Sideways market/no clear trend) 2️⃣ SETUP QUALITY SYSTEM Each trading opportunity is evaluated on 6 independent criteria: ✅ Price inside a valid Order Block ✅ Volume Delta confirming the direction ✅ Order Block is recent and "fresh" ✅ Few previous retests (OB still strong) ✅ Volume confirmation above average ✅ Favorable market regime Setup Quality Score: 0 to 6 points Score 6: Perfect setup (all criteria met) Score 5: Excellent setup (5 of 6 criteria) Score 4: Good setup (4 of 6 criteria) Score 0-3: Weak setup or forming ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🔧 VISUAL COMPONENTS IN THE INDICATOR ▸ VOLUME DELTA HISTOGRAM 🟢 Green Bars: Buying volume > selling volume (bullish pressure) 🔴 Red Bars: Selling volume > buying volume (bearish pressure) 📊 Intensity: The larger the bar, the greater the pressure ▸ ORDER BLOCK ZONES 🟢 Green Boxes (Bull OB): Institutional support zones 🔴 Red Boxes (Bear OB): Institutional resistance zones 🔄 Projection: OBs are extended to the right until invalidated ▸ SETUP QUALITY SIGNALS 📊 Score Labels: Show setup quality (Q4, Q5, Q6) • Q6: Perfect setup (all 6 criteria met) • Q5: Excellent setup (5 of 6 criteria) • Q4: Good setup (4 of 6 criteria) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 HOW TO INTERPRET THE INFORMATION Observe trend direction (EMAs and ADX) Identify active Order Blocks: • Bull OBs (green): Potential support zones • Bear OBs (red): Potential resistance zones Analyze Volume Delta: • Green bars: Dominant buying pressure • Red bars: Dominant selling pressure Check Setup Quality Score: • Q5-Q6: Setups with multiple confirmations • Q4: Setup with moderate confirmations • Q0-Q3: Few criteria met ⚠️ NOTE: The indicator provides technical information. Trading decisions are exclusively yours. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 TECHNICAL CHARACTERISTICS ▸ RECOMMENDED TIMEFRAMES 5 minutes: Scalping / Fast day trading 15 minutes: Day trading 1 hour: Swing trading 4 hours: Medium-term positions Daily: Long-term analysis ▸ COMPATIBLE MARKETS ✅ Forex (all pairs) ✅ Cryptocurrencies (BTC, ETH, altcoins) ✅ Indices (S&P500, Nasdaq, etc) ✅ Commodities (Gold, Oil, etc) ✅ Stocks and CFDs ⚠️ Requirement: Volume data is necessary for Volume Delta calculation ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚠️ IMPORTANT WARNINGS ▸ EDUCATIONAL USE 📊 This indicator is an educational technical analysis tool ⚠️ The indicator does NOT provide buy or sell signals ⚠️ The indicator does NOT guarantee results ⚠️ All trading decisions are your responsibility ▸ RISK MANAGEMENT ⚠️ Always use proper risk management ⚠️ Never trade with money you cannot afford to lose ⚠️ Test the indicator on a demo account before using real money ⚠️ Combine with your own analysis and strategy ▸ LIMITATIONS ❌ No indicator is 100% accurate ❌ Markets can behave unpredictably ❌ Requires confirmation with other analyses ❌ Volume Delta requires reliable volume data ▸ DISCLAIMER 📢 This indicator is educational and does not constitute investment advice. The indicator shows technical information, not trading signals Past results do not guarantee future results Trading involves risk of total capital loss You are 100% responsible for your trading decisions Consult a financial professional before investing ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📚 ADVANCED CONCEPTS ▸ WHAT ARE ORDER BLOCKS? Order Blocks represent zones where "smart money" (institutions, whales) accumulated or distributed positions. When price returns to these zones, there is high probability of reaction due to: Pending limit orders Psychological levels Institutional value zones ▸ VOLUME DELTA VS NORMAL VOLUME Normal volume shows only QUANTITY of trades. Volume Delta shows DIRECTION (who is winning the battle): High volume + Positive delta = Strong accumulation 🚀 High volume + Negative delta = Strong distribution 📉 ▸ MARKET REGIME (ADX) ADX measures TREND STRENGTH: ADX > 25: Strong trend (best time to trade) ADX < 20: Sideways/ranging market (avoid trades) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ✅ BEFORE USING THIS INDICATOR Make sure you: ☑ Understand the Order Blocks concept ☑ Know how to interpret Volume Delta ☑ Understand trend analysis ☑ Have your own trading strategy ☑ Know risk management ☑ Understand the indicator does NOT provide buy/sell signals ☑ Are aware of trading risks ☑ Test on demo account before using real money ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 USE AS AN ANALYSIS TOOL, NOT AS AN AUTOMATIC DECISION SYSTEM! The indicator provides information. You make the decisions. ――――――――――――――――――――――――――――――――――――――――― Version: 1.0 | Type: Order Block + Volume Delta + Trend Analysis | Update: October 2024
Wskaźnik Pine Script®
od Lipezeira
WorldCup Dashboard + Institutional Sessions© 2025 NewMeta™ — Educational use only. # Full, Premium Description ## WorldCup Dashboard + Institutional Sessions **A trade-ready, intraday framework that combines market structure, real flow, and institutional timing.** This toolkit fuses **Institutional Sessions** with a **price–volume decision engine** so you can see *who is active*, *where value sits*, and *whether the drive is real*. You get: **CVD/Delta**, volume-weighted **Momentum**, **Aggression** spikes, **FVG (MTF)** with nearest side, **Daily Volume Profile (VAH/POC/VAL)**, **ATR regime**, a **24h position gauge**, classic **candle patterns**, IBH/IBL + **first-hour “true close”** lines, and a **10-vote confluence scoreboard**—all in one view. --- ## What’s inside (and how to trade it) ### 🌍 Institutional Sessions (Sydney • Tokyo • London • New York) * Session boxes + a highlighted **first hour**. * Plots the **true close** (first-hour close) as a running line with a label. **Use:** Many desks anchor risk to this print. Above = bullish bias; below = bearish. **IBH/IBL** breaks during London/NY carry the most signal. ### 📊 CVD / Delta (Flow) * Net buyer vs seller pressure with smooth trend state. **Use:** **Rising CVD + acceptance above mid/POC** confirms continuation. Bearish price + rising CVD = caution (possible absorption). ### ⚡ Volume-Weighted Momentum * Momentum adjusted by participation quality (volume). **Use:** Momentum>MA and >0 → trend drive is “real”; <0 and falling → distribution risk. ### 🔥 Aggression Detector * ROC × normalized volume × wick factor to flag **forceful** candles. **Use:** On spikes, avoid fading blindly—wait for pullbacks into **aligned FVG** or for aggression to cool. ### 🟦🟪 Fair Value Gaps (with MTF) * Detects up to 3 recent FVGs and marks the **nearest** side to price. **Use:** Trend pullbacks into **bullish FVG** for longs; bounces into **bearish FVG** for shorts. Optional threshold to filter weak gaps. ### 🧭 24h Gauge (positioning) * Shows current price across the 24h low⇢high with a mid reference. **Use:** Above mid and pushing upper third = momentum continuation setups; below mid = sell the rips bias. ### 🧱 Daily Volume Profile (manual per day) * **VAH / POC / VAL** derived from discretized rows. **Use:** **POC below** supports longs; **POC above** caps rallies. Fade VAH/VAL in ranges; treat them as break/hold levels in trends. ### 📈 ATR Regime * **ATR vs ATR-avg** with direction and regime flag (**HIGH / NORMAL / LOW**). **Use:** HIGH ⇒ give trades room & favor trend following. LOW ⇒ fade edges, scale targets. ### 🕯️ Candle Patterns (contextual, not standalone) * Engulfings, Morning/Evening Star, 3 Soldiers/Crows, Harami, Hammer/Shooting Star, Double Top/Bottom. **Use:** Only with session + flow + momentum alignment. ### 🤝 Price–Volume Classification * Labels each bar as **continuation**, **exhaustion**, **distribution**, or **healthy pullback**. **Use:** Align continuation reads with trend; treat “Price↑ + Vol↓” as a caution flag. ### 🧪 Confluence Scoreboard & B/S Meter * Ten elements vote: 🔵 bull, ⚪ neutral, 🟣 bear. **Use:** Execution filter—take setups when the board’s skew matches your trade direction. --- ## Playbooks (actionable) **Trend Pullback (Long)** 1. London/NY active, Momentum↑, CVD↑, price above 24h mid & POC. 2. Pullback into **nearest bullish FVG**. 3. Invalidate under FVG low or **true-close** line. 4. Targets: IBH → VAH → 24h high. **Range Fade (Short)** 1. Asia/quiet regime, **Price↑ + Vol↓** into **VAH**, ATR low. 2. Nearest FVG bearish or scoreboard skew bearish. 3. Invalidate above VAH/IBH. 4. Targets: POC → VAL. **News/Impulse** Aggression spike? Don’t chase. Let it pull back into the aligned FVG; require CVD/Momentum agreement before entry. --- ## Alerts (included) * **Bull/Bear Confluence ≥ 7/10** * **Intraday Target Achieved** / **Daily Target Achieved** * **Session True-Close Retests** (Sydney/Tokyo/London/NY) *(Keep alerts “Once per bar” unless you specifically want intrabar triggers.)* --- ## Setup Tips * **UTC**: Choose the reference that matches how you track sessions (default UTC+2). * **Volume threshold**: 2.0× is a strong baseline; raise for noisy alts, lower for majors. * **CVD smoothing**: 14–24 for scalps; 24–34 for slower markets. * **ATR lengths**: Keep defaults unless your asset has a persistent regime shift. --- ## Why this framework? Because **timing (sessions)**, **truth (flow)**, and **location (value/FVG)** together beat any single signal. You get *who is trading*, *how strong the push is*, and *where risk lives*—on one screen—so execution is faster and cleaner. --- **Disclaimer**: Educational use only. Not financial advice. Markets are risky—backtest and size responsibly.
Wskaźnik Pine Script®
od onedaywillbebillionaire
IIR One-Pole Price Filter [BackQuant]IIR One-Pole Price Filter A lightweight, mathematically grounded smoothing filter derived from signal processing theory, designed to denoise price data while maintaining minimal lag. It provides a refined alternative to the classic Exponential Moving Average (EMA) by directly controlling the filter’s responsiveness through three interchangeable alpha modes: EMA-Length , Half-Life , and Cutoff-Period . Concept overview An IIR (Infinite Impulse Response) filter is a type of recursive filter that blends current and past input values to produce a smooth, continuous output. The "one-pole" version is its simplest form, consisting of a single recursive feedback loop that exponentially decays older price information. This makes it both memory-efficient and responsive , ideal for traders seeking a precise balance between noise reduction and reaction speed. Unlike standard moving averages, the IIR filter can be tuned in physically meaningful terms (such as half-life or cutoff frequency) rather than just arbitrary periods. This allows the trader to think about responsiveness in the same way an engineer or physicist would interpret signal smoothing. Why use it Filters out market noise without introducing heavy lag like higher-order smoothers. Adapts to various trading speeds and time horizons by changing how alpha (responsiveness) is parameterized. Provides consistent and mathematically interpretable control of smoothing, suitable for both discretionary and algorithmic systems. Can serve as the core component in adaptive strategies, volatility normalization, or trend extraction pipelines. Alpha Modes Explained EMA-Length : Classic exponential decay with alpha = 2 / (L + 1). Equivalent to a standard EMA but exposed directly for fine control. Half-Life : Defines the number of bars it takes for the influence of a price input to decay by half. More intuitive for time-domain analysis. Cutoff-Period : Inspired by analog filter theory, defines the cutoff frequency (in bars) beyond which price oscillations are heavily attenuated. Lower periods = faster response. Formula in plain terms Each bar updates as: yₜ = yₜ₋₁ + alpha × (priceₜ − yₜ₋₁) Where alpha is the smoothing coefficient derived from your chosen mode. Smaller alpha → smoother but slower response. Larger alpha → faster but noisier response. Practical application Trend detection : When the filter line rises, momentum is positive; when it falls, momentum is negative. Signal timing : Use the crossover of the filter vs its previous value (or price) as an entry/exit condition. Noise suppression : Apply on volatile assets or lower timeframes to remove flicker from raw price data. Foundation for advanced filters : The one-pole IIR serves as a building block for multi-pole cascades, adaptive smoothers, and spectral filters. Customization options Alpha Scale : Multiplies the final alpha to fine-tune aggressiveness without changing the mode’s core math. Color Painting : Candles can be painted green/red by trend direction for visual clarity. Line Width & Transparency : Adjust the visual intensity to integrate cleanly with your charting style. Interpretation tips A smooth yet reactive line implies optimal tuning — minimal delay with reduced false flips. A sluggish line suggests alpha is too small (increase responsiveness). A noisy, twitchy line means alpha is too large (increase smoothing). Half-life tuning often feels more natural for aligning filter speed with price cycles or bar duration. Summary The IIR One-Pole Price Filter is a signal smoother that merges simplicity with mathematical rigor. Whether you’re filtering for entry signals, generating trend overlays, or constructing larger multi-stage systems, this filter delivers stability, clarity, and precision control over noise versus lag, an essential tool for any quantitative or systematic trading approach.
Wskaźnik Pine Script®
od BackQuant
Liquidity Stress Index SOFR - IORBLiquidity Stress Index (SOFR - IORB) This indicator tracks the spread between the Secured Overnight Financing Rate (SOFR) and the Interest on Reserve Balances (IORB) set by the Federal Reserve. A persistently positive spread may indicate funding stress or liquidity shortages in the repo market, as it suggests overnight lending rates exceed the risk-free rate banks earn at the Fed. Useful for monitoring monetary policy transmission or market/liquidity stress.
Wskaźnik Pine Script®
od RichmondHillCM
Advanced HMM - 3 States CompleteHidden Markov Model Aconsistent challenge for quantitative traders is the frequent behaviour modification of financial markets, often abruptly, due to changing periods of government policy, regulatory environment and other macroeconomic effects. Such periods are known as market regimes. Detecting such changes is a common, albeit difficult, process undertaken by quantitative market participants. These various regimes lead to adjustments of asset returns via shifts in their means, variances, autocorrelation and covariances. This impacts the effectiveness of time series methods that rely on stationarity. In particular it can lead to dynamically-varying correlation, excess kurtosis ("fat tails"), heteroskedasticity (volatility clustering) and skewed returns. There is a clear need to effectively detect these regimes. This aids optimal deployment of quantitative trading strategies and tuning the parameters within them. The modeling task then becomes an attempt to identify when a new regime has occurred adjusting strategy deployment, risk management and position sizing criteria accordingly. A principal method for carrying out regime detection is to use a statistical time series tech nique known as a Hidden Markov Model . These models are well-suited to the task since they involve inference on "hidden" generative processes via "noisy" indirect observations correlated to these processes. In this instance the hidden, or latent, process is the underlying regime state, while the asset returns are the indirect noisy observations that are influenced by these states. MAIN FEATURES OF THE INDICATOR The "Advanced HMM - 3 States Complete" indicator is an advanced technical analysis tool that uses Hidden Markov Model (HMM) to identify three main market regimes: BULL, BEAR, and SIDEWAYS. 🎯 KEY FEATURES: 1. HMM-based Trend Detection 3 market states: Bull (0), Bear (1), Sideways (2) Dynamic probabilities: Calculates probability for each state based on price data Transition matrix: Models state transitions between regimes 2. Analytical Features Price volatility: Log returns and standard deviation Momentum: Rate of Change (ROC) Volume: Volume ratio vs moving average Data normalization: Standardizes features to common scale 3. Visual Trading Signals text 📍 BUY Signals: - Green upward triangle below bars - "LONG" label in green 📍 SELL Signals: - Red downward triangle above bars - "SHORT" label in red 📍 EXIT Signals: - Orange X marks when transitioning to sideways 4. Information Display Probability table (top-right): Shows percentage for each state State label: Current regime with probability percentages Chart background color: Reflects dominant market state 5. Automated Alerts Alerts when new Bull/Bear market detected Alerts when market transitions to sideways Configurable TradingView notifications 6. Customizable Parameters pinescript length: 100 // Lookback period smoothing_period: 20 // Probability smoothing volatility_threshold: 0.5 // Volatility threshold 💡 PRACTICAL APPLICATIONS: Identify primary trends with quantified probabilities Entry/exit signals based on state transitions Risk management during sideways markets Trend confirmation when combined with other indicators This indicator is particularly useful for market regime analysis and identifying trend transition points using advanced statistical probability methods. 🔧 TECHNICAL IMPLEMENTATION: Composite observation: Weighted combination of returns (40%), momentum (30%), and volatility (30%) Gaussian emission probabilities: Different distributions for each state Manual HMM updates: Avoids matrix computation limitations in Pine Script Real-time smoothing: EMA applied to state probabilities The indicator provides institutional-grade regime detection in a visually intuitive package suitable for both discretionary and systematic traders.
Wskaźnik Pine Script®
od Limitedterminator
ATR Gauge - Audiophile StyleThe ATR Gauge - Audiophile Style indicator is a custom visualization tool. It's designed to give you a quick, retro-inspired snapshot of market volatility using the Average True Range (ATR) metric. Think of it as a dashboard widget styled like the VU meters on old-school audiophile equipment (e.g., vintage stereo amps from brands like McIntosh or Marantz)—simple, elegant, and functional. It sits in one of the corners of your chart and helps you gauge how "hot" or "cool" the current price action is compared to recent levels. Why This Gauge?: Standard ATR plots as a line on your chart, but this turns it into a visual "meter" focused on the last 24 hours. It's like a speedometer for volatility—quick to read at a glance. Useful for day traders, scalpers, or anyone monitoring intraday risk without cluttering the main chart.
Wskaźnik Pine Script®
od Maximilianned