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MAG7 Market Cap Weighted Index [Reflex]Summary A synthetic intraday index built from the MAG7, weighted by market cap and plotted as true OHLC candles. Usage This indicator was designed for market breadth analyses. Since it uses market cap weighting, it behaves like any other index (eg. SPX). It shows where mega-cap leadership is actually trading, making it useful for trend confirmation, divergence analysis versus NQ/ES, and contextualizing the breadth of the market. The index is intentionally gated to the NY RTH session to avoid distorted behavior when component data is unavailable.
Indicatore Pine Script®
di ReflexSignals
[GYTS] VolatilityToolkit LibraryVolatilityToolkit Library 🌸 Part of GoemonYae Trading System (GYTS) 🌸 🌸 --------- INTRODUCTION --------- 🌸 💮 What Does This Library Contain? VolatilityToolkit provides a comprehensive suite of volatility estimation functions derived from academic research in financial econometrics. Rather than relying on simplistic measures, this library implements range-based estimators that extract maximum information from OHLC data — delivering estimates that are 5–14× more efficient than traditional close-to-close methods. The library spans the full volatility workflow: estimation, smoothing, and regime detection. 💮 Key Categories • Range-Based Estimators — Parkinson, Garman-Klass, Rogers-Satchell, Yang-Zhang (academically-grounded variance estimators) • Classical Measures — Close-to-Close, ATR, Chaikin Volatility (baseline and price-unit measures) • Smoothing & Post-Processing — Asymmetric EWMA for differential decay rates • Aggregation & Regime Detection — Multi-horizon blending, MTF aggregation, Volatility Burst Ratio 💮 Originality To the best of our knowledge, no other TradingView script combines range-based estimators (Parkinson, Garman-Klass, Rogers-Satchell, Yang-Zhang), classical measures, and regime detection tools in a single package. Unlike typical volatility implementations that offer only a single method, this library: • Implements four academically-grounded range-based estimators with proper mathematical foundations • Handles drift bias and overnight gaps, issues that plague simpler estimators in trending markets • Integrates with GYTS FiltersToolkit for advanced smoothing (10 filter types vs. typical SMA-only) • Provides regime detection tools (Burst Ratio, MTF aggregation) for systematic strategy integration • Standardises output units for seamless estimator comparison and swapping 🌸 --------- ADDED VALUE --------- 🌸 💮 Academic Rigour Each estimator implements peer-reviewed methodologies with proper mathematical foundations. The library handles aspects that are easily missed, e.g. drift independence, overnight gap adjustment, and optimal weighting factors. All functions include guards against edge cases (division by zero, negative variance floors, warmup handling). 💮 Statistical Efficiency Range-based estimators extract more information from the same data. Yang-Zhang achieves up to 14× the efficiency of close-to-close variance, meaning you can achieve the same estimation accuracy with far fewer bars — critical for adapting quickly to changing market conditions. 💮 Flexible Smoothing All estimators support configurable smoothing via the GYTS FiltersToolkit integration. Choose from 10 filter types to balance responsiveness against noise reduction: • Ultimate Smoother (2-Pole / 3-Pole) — Near-zero lag; the 3-pole variant is a GYTS design with tunable overshoot • Super Smoother (2-Pole / 3-Pole) — Excellent noise reduction with minimal lag • BiQuad — Second-order IIR filter with quality factor control • ADXvma — Adaptive smoothing based on directional volatility • MAMA — Cycle-adaptive moving average • A2RMA — Adaptive autonomous recursive moving average • SMA / EMA — Classical averages (SMA is default for most estimators) Using Infinite Impulse Response (IIR) filters (e.g. Super Smoother, Ultimate Smoother) instead of SMA avoids the "drop-off artefact" where volatility readings crash when old spikes exit the window. 💮 Plug-and-Play Integration Standardised output units (per-bar log-return volatility) make it trivial to swap estimators. The annualize() helper converts to yearly volatility with a single call. All functions work seamlessly with other GYTS components. 🌸 --------- RANGE-BASED ESTIMATORS --------- 🌸 These estimators utilise High, Low, Open, and Close prices to extract significantly more information about the underlying diffusion process than close-only methods. 💮 parkinson() The Extreme Value Method -- approximately 5× more efficient than close-to-close, requiring about 80% less data for equivalent accuracy. Uses only the High-Low range, making it simple and robust. • Assumption: Zero drift (random walk). May be biased in strongly trending markets. • Best for: Quick volatility reads when drift is minimal. • Parameters: smoothing_length (default 14), filter_type (default SMA), smoothing_factor (default 0.7) Source: Parkinson, M. (1980). The Extreme Value Method for Estimating the Variance of the Rate of Return. Journal of Business, 53 (1), 61–65. DOI 💮 garman_klass() Extends Parkinson by incorporating Open and Close prices, achieving approximately 7.4× efficiency over close-to-close. Implements the "practical" analytic estimator (σ̂²₅) which avoids cross-product terms whilst maintaining near-optimal efficiency. • Assumption: Zero drift, continuous trading (no gaps). • Best for: Markets with minimal overnight gaps and ranging conditions. • Parameters: smoothing_length (default 14), filter_type (default SMA), smoothing_factor (default 0.7) Source: Garman, M.B. & Klass, M.J. (1980). On the Estimation of Security Price Volatilities from Historical Data. Journal of Business, 53 (1), 67–78. DOI 💮 rogers_satchell() The drift-independent estimator correctly isolates variance even in strongly trending markets where Parkinson and Garman-Klass become significantly biased. Uses the formula: ln(H/C)·ln(H/O) + ln(L/C)·ln(L/O). • Key advantage: Unbiased regardless of trend direction or magnitude. • Best for: Trending markets, crypto (24/7 trading with minimal gaps), general-purpose use. • Parameters: smoothing_length (default 14), filter_type (default SMA), smoothing_factor (default 0.7) Source: Rogers, L.C.G. & Satchell, S.E. (1991). Estimating Variance from High, Low and Closing Prices. Annals of Applied Probability, 1 (4), 504–512. DOI 💮 yang_zhang() The minimum-variance composite estimator — both drift-independent AND gap-aware. Combines overnight returns, open-to-close returns, and the Rogers-Satchell component with optimal weighting to minimise estimator variance. Up to 14× more efficient than close-to-close. • Parameters: lookback (default 14, minimum 2), alpha (default 1.34, optimised for equities). • Best for: Equity markets with significant overnight gaps, highest-quality volatility estimation. • Note: Unlike other estimators, Yang-Zhang does not support custom filter types — it uses rolling sample variance internally. Source: Yang, D. & Zhang, Q. (2000). Drift-Independent Volatility Estimation Based on High, Low, Open, and Close Prices. Journal of Business, 73 (3), 477–491. DOI 🌸 --------- CLASSICAL MEASURES --------- 🌸 💮 close_to_close() Classical sample variance of logarithmic returns. Provided primarily as a baseline benchmark — it is approximately 5–8× less efficient than range-based estimators, requiring proportionally more data for the same accuracy. • Parameters: lookback (default 14), filter_type (default SMA), smoothing_factor (default 0.7) • Use case: Comparison baseline, situations requiring strict methodological consistency with academic literature. 💮 atr() Average True Range -- measures volatility in price units rather than log-returns. Directly interpretable for stop-loss placement (e.g., "2× ATR trailing stop") and handles gaps naturally via the True Range formula. • Output: Price units (not comparable across different price levels). • Parameters: smoothing_length (default 14), filter_type (default SMA), smoothing_factor (default 0.7) • Best for: Position sizing, trailing stops, any application requiring volatility in currency terms. Source: Wilder, J.W. (1978). New Concepts in Technical Trading Systems . Trend Research. 💮 chaikin_volatility() Rate of Change of the smoothed trading range. Unlike level-based measures, Chaikin Volatility shows whether volatility is expanding or contracting relative to recent history. • Output: Percentage change (oscillates around zero). • Parameters: length (default 10), roc_length (default 10), filter_type (default EMA), smoothing_factor (default 0.7) • Interpretation: High values suggest nervous, wide-ranging markets; low values indicate compression. • Best for: Detecting volatility regime shifts, breakout anticipation. 🌸 --------- SMOOTHING & POST-PROCESSING --------- 🌸 💮 asymmetric_ewma() Differential smoothing with separate alphas for rising versus falling volatility. Allows volatility to spike quickly (fast reaction to shocks) whilst decaying slowly (stability). Essential for trailing stops that should widen rapidly during turbulence but narrow gradually. • Parameters: alpha_up (default 0.1), alpha_down (default 0.02). • Note: Stateful function — call exactly once per bar. 💮 annualize() Converts per-bar volatility to annualised volatility using the square-root-of-time rule: σ_annual = σ_bar × √(periods_per_year). • Parameters: vol (series float), periods (default 252 for daily equity bars). • Common values: 365 (crypto), 52 (weekly), 12 (monthly). 🌸 --------- AGGREGATION & REGIME DETECTION --------- 🌸 💮 weighted_horizon_volatility() Blends volatility readings across short, medium, and long lookback horizons. Inspired by the Heterogeneous Autoregressive (HAR-RV) model's recognition that market participants operate on different time scales. • Default horizons: 1-bar (short), 5-bar (medium), 22-bar (long). • Default weights: 0.5, 0.3, 0.2. • Note: This is a weighted trailing average, not a forecasting regression. For true HAR-RV forecasting, it would be required to fit regression coefficients. Inspired by: Corsi, F. (2009). A Simple Approximate Long-Memory Model of Realized Volatility. Journal of Financial Econometrics . 💮 volatility_mtf() Multi-timeframe aggregation for intraday charts. Combines base volatility with higher-timeframe (Daily, Weekly, Monthly) readings, automatically scaling HTF volatilities down to the current timeframe's magnitude using the square-root-of-time rule. • Usage: Calculate HTF volatilities via request.security() externally, then pass to this function. • Behaviour: Returns base volatility unchanged on Daily+ timeframes (MTF aggregation not applicable). 💮 volatility_burst_ratio() Regime shift detector comparing short-term to long-term volatility. • Parameters: short_period (default 8), long_period (default 50), filter_type (default Super Smoother 2-Pole), smoothing_factor (default 0.7) • Interpretation: Ratio > 1.0 indicates expanding volatility; values > 1.5 often precede or accompany explosive breakouts. • Best for: Filtering entries (e.g., "only enter if volatility is expanding"), dynamic risk adjustment, breakout confirmation. 🌸 --------- PRACTICAL USAGE NOTES --------- 🌸 💮 Choosing an Estimator • Trending equities with gaps: yang_zhang() — handles both drift and overnight gaps optimally. • Crypto (24/7 trading): rogers_satchell() — drift-independent without the lag of Yang-Zhang's multi-period window. • Ranging markets: garman_klass() or parkinson() — simpler, no drift adjustment needed. • Price-based stops: atr() — output in price units, directly usable for stop distances. • Regime detection: Combine any estimator with volatility_burst_ratio(). 💮 Output Units All range-based estimators output per-bar volatility in log-return units (standard deviation). To convert to annualised percentage volatility (the convention in options and risk management), use: vol_annual = annualize(yang_zhang(14), 252) // For daily bars vol_percent = vol_annual * 100 // Express as percentage 💮 Smoothing Selection The library integrates with FiltersToolkit for flexible smoothing. General guidance: • SMA: Classical, statistically valid, but suffers from "drop-off" artefacts when spikes exit the window. • Super Smoother / Ultimate Smoother / BiQuad: Natural decay, reduced lag — preferred for trading applications. • MAMA / ADXvma / A2RMA: Adaptive smoothing, sometimes interesting for highly dynamic environments. 💮 Edge Cases and Limitations • Flat candles: Guards prevent log(0) errors, but single-tick bars produce near-zero variance readings. • Illiquid assets: Discretisation bias causes underestimation when ticks-per-bar is small. Use higher timeframes for more reliable estimates. • Yang-Zhang minimum: Requires lookback ≥ 2 (enforced internally). Cannot produce instantaneous readings. • Drift in Parkinson/GK: These estimators overestimate variance in trending conditions — switch to Rogers-Satchell or Yang-Zhang. Note: This library is actively maintained. Suggestions for additional estimators or improvements are welcome.
Libreria Pine Script®
di GoemonYae
Smart Money Flow Oscillator [MarkitTick]💡This script introduces a sophisticated method for analyzing market liquidity and institutional order flow. Unlike traditional volume indicators that treat all market activity equally, the Smart Money Flow Oscillator (SMFO) employs a Logic Flow Architecture (LFA) to filter out market noise and "churn," focusing exclusively on high-impact, high-efficiency price movements. By synthesizing price action, volume, and relative efficiency, this tool aims to visualize the accumulation and distribution activities that are often attributed to "smart money" participants. ✨ Originality and Utility Standard indicators like On-Balance Volume (OBV) or Money Flow Index (MFI) often suffer from noise because they aggregate volume based simply on the close price relative to the previous close, regardless of the quality of the move. This script differentiates itself by introducing an "Efficiency Multiplier" and a "Momentum Threshold." It only registers volume flow when a price move is considered statistically significant and structurally efficient. This creates a cleaner signal that highlights genuine supply and demand imbalances while ignoring indecisive trading ranges. It combines the trend-following nature of cumulative delta with the mean-reverting insights of an In/Out ratio, offering a dual-mode perspective on market dynamics. 🔬 Methodology The underlying calculation of the SMFO relies on several distinct quantitative layers: • Efficiency Analysis The script calculates a "Relative Efficiency" ratio for every candle. This compares the current price displacement (body size) per unit of volume against the historical average. If price moves significantly with relatively low volume, or proportional volume, it is deemed "efficient." If significant volume occurs with little price movement (churn/absorption), the efficiency score drops. This score is clamped between a user-defined minimum and maximum (Efficiency Cap) to prevent outliers from distorting the data. • Momentum Thresholding Before adding any data to the flow, the script checks if the current price change exceeds a volatility threshold derived from the previous candle's open-close range. This acts as a gatekeeper, ensuring that only "strong" moves contribute to the oscillator. • Variable Flow Calculation If a move passes the threshold, the script calculates the flow value by multiplying the Typical Price and Volume (Money Flow) by the calculated Efficiency Multiplier. Bullish Flow: Strong upward movement adds to the positive delta. Bearish Flow: Strong downward movement adds to the negative delta. Neutral: Bars that fail the momentum threshold contribute zero flow, effectively flattening the line during consolidation. • Calculation Modes Cumulative Delta Flow (CDF): Sums the flow values over a rolling period. This creates a trend-following oscillator similar to OBV but smoother and more responsive to real momentum. In/Out Ratio: Calculates the percentage of bullish inflow relative to the total absolute flow over the period. This oscillates between 0 and 100, useful for identifying overextended conditions. 📖 How to Use Traders can utilize this oscillator to identify trend strength and potential reversals through the following signals: • Signal Line Crossovers The indicator plots the main Flow line (colored gradient) and a Signal line (grey). Bullish (Green Cloud): When the Flow line crosses above the Signal line, it suggests rising buying pressure and efficient upward movement. Bearish (Red Cloud): When the Flow line crosses below the Signal line, it suggests dominating selling pressure. • Divergences The script automatically detects and plots divergences between price and the oscillator: Regular Divergence (Solid Lines): Suggests a potential trend reversal (e.g., Price makes a Lower Low while Oscillator makes a Higher Low). Hidden Divergence (Dashed Lines): Suggests a potential trend continuation (e.g., Price makes a Higher Low while Oscillator makes a Lower Low). "R" labels denote Regular, and "H" labels denote Hidden divergences. • Dashboard A dashboard table is displayed on the chart, providing real-time metrics including the current Efficiency Multiplier, Net Flow value, and the active mode status. • In/Out Ratio Levels When using the Ratio mode: Values above 50 indicate net buying pressure. Values below 50 indicate net selling pressure. Approaching 70 or 30 can indicate overbought or oversold conditions involving volume exhaustion. ⚙️ Inputs and Settings Calculation Mode: Choose between "Cumulative Delta Flow" (Trend focus) or "In/Out Ratio" (Oscillator focus). Auto-Adjust Period: If enabled, automatically sets the lookback period based on the chart timeframe (e.g., 21 for Daily, 52 for Weekly). Manual Period: The rolling lookback length for calculations if Auto-Adjust is disabled. Efficiency Length: The period used to calculate the average body and volume for the efficiency baseline. Eff. Min/Max Cap: Limits the impact of the efficiency multiplier to prevent extreme skewing during anomaly candles. Momentum Threshold: A factor determining how much price must move relative to the previous candle to be considered a "strong" move. Show Dashboard/Divergences: Toggles for visual elements. 🔍 Deconstruction of the Underlying Scientific and Academic Framework This indicator represents a hybrid synthesis of academic Market Microstructure theory and classical technical analysis. It utilizes an advanced algorithm to quantify "Price Impact," leveraging the following theoretical frameworks: • 1. The Amihud Illiquidity Ratio (2002) The core logic (calculating body / volume) functions as a dynamic implementation of Yakov Amihud’s Illiquidity Ratio. It measures price displacement per unit of volume. A high efficiency score indicates that "Smart Money" has moved the price significantly with minimal resistance, effectively highlighting liquidity gaps or institutional control. • 2. Kyle’s Lambda (1985) & Market Depth Drawing from Albert Kyle’s research on market microstructure, the indicator approximates Kyle's Lambda to measure the elasticity of price in response to order flow. By analyzing the "efficiency" of a move, it identifies asymmetries—specifically where price reacts disproportionately to low volume—signaling potential manipulation or specific Market Maker activity. • 3. Wyckoff’s Law of Effort vs. Result From a classical perspective, the algorithm codifies Richard Wyckoff’s "Effort vs. Result" logic. It acts as an oscillator that detects anomalies where "Effort" (Volume) diverges from the "Result" (Price Range), predicting potential reversals. • 4. Quantitative Advantage: Efficiency-Weighted Volume Unlike linear indicators such as OBV or Chaikin Money Flow—which treat all volume equally—this indicator (LFA) utilizes Efficiency-Weighted Volume. By applying the efficiency_mult factor, the algorithm filters out market noise and assigns higher weight to volume that drives structural price changes, adopting a modern quantitative approach to flow analysis. ● Disclaimer All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion.
Indicatore Pine Script®
di MarkitTick
4
MDZ Strategy v4.2 - Multi-factor trend strategyWhat This Strategy Does MDZ (Momentum Divergence Zones) v4.2 is a trend-following strategy that enters long positions when multiple momentum and trend indicators align. It's designed for swing trading on higher timeframes (2H-4H) and uses ATR-based position management. The strategy waits for strong trend confirmation before entry, requiring agreement across five different filters. This reduces trade frequency but aims to improve signal quality. Entry Logic A long entry triggers when ALL of the following conditions are true: 1. EMA Stack (Trend Structure) Price > EMA 20 > EMA 50 > EMA 200 This "stacked" alignment indicates a strong established uptrend 2. RSI Filter (Momentum Window) RSI between 45-75 (default) Confirms momentum without entering overbought territory 3. ADX Filter (Trend Strength) ADX > 20 (default) Ensures the trend has sufficient strength, not a ranging market 4. MACD Confirmation MACD line above signal line Histogram increasing (momentum accelerating) 5. Directional Movement +DI > -DI Confirms bullish directional pressure Exit Logic Positions are managed with ATR-based levels: ParameterDefaultDescriptionStop Loss2.5 × ATRBelow entry priceTake Profit6.0 × ATRAbove entry priceTrailing Stop2.0 × ATROptional, activates after entry The default configuration produces a 1:2.4 risk-reward ratio. Presets The strategy includes optimized presets based on historical testing: PresetTimeframeNotes1H Standard1 HourMore frequent signals2H Low DD2 HourConservative settings3H Optimized3 HourBalanced approach4H Swing4 HourWider stops for swing tradesCustomAnyFull manual control Select "Custom" to adjust all parameters manually. Inputs Explained EMAs Fast EMA (20): Short-term trend Slow EMA (50): Medium-term trend Trend EMA (200): Long-term trend filter RSI Length: Lookback period (default 14) Min/Max: Entry window to avoid extremes ADX Min ADX: Minimum trend strength threshold Risk Stop Loss ATR: Multiplier for stop distance Take Profit ATR: Multiplier for target distance Trail ATR: Trailing stop distance (if enabled) Session (Optional) Filter entries by time of day Recommended OFF for 3H+ timeframes What's Displayed Info Panel (Top Right) Current preset Trend status (Strong/Wait) ADX, RSI, MACD readings Position status Risk-reward ratio Stats Panel (Top Left) Net P&L % Total trades Win rate Profit factor Maximum drawdown Chart EMA lines (20 blue, 50 orange, 200 purple) Green background during strong uptrend Triangle markers on entry signals Important Notes ⚠️ This is a long-only strategy. It does not take short positions. ⚠️ Historical results do not guarantee future performance. Backtests show what would have happened in the past under specific conditions. Markets change, and any strategy can experience drawdowns or extended losing periods. ⚠️ Risk management is your responsibility. The default settings risk 100% of equity per trade for backtesting purposes. In live trading, appropriate position sizing based on your risk tolerance is essential. ⚠️ Slippage and commissions matter. The backtest includes 0.02% commission and 1 tick slippage, but actual execution costs vary by broker and market conditions. Best Practices Test on your specific market — Results vary significantly across different instruments Use appropriate position sizing — Never risk more than you can afford to lose Combine with your own analysis — No indicator replaces understanding market context Paper trade first — Validate the strategy matches your trading style before risking capital Alerts Two alerts are available: MDZ Long Entry: Fires when all entry conditions are met Uptrend Started: Fires when EMA stack first aligns bullish Methodology This strategy is based on the principle that trend continuation has better odds than reversal when multiple timeframe momentum indicators agree. By requiring five independent confirmations, it filters out weak setups at the cost of fewer total signals. The ATR-based exits adapt to current volatility rather than using fixed pip/point targets, which helps the strategy adjust to different market conditions. Questions? Leave a comment below.
Strategia Pine Script®
di VolForge
PHEN ATLAS - Market Map & Playbook [PhenLabs]📊 PHEN ATLAS 🎂 #50 🎂 Version: PineScript™ v6 📌 Description The PHEN ATLAS marks a historic milestone as the 50th official release from PhenLabs . This is a critical release you do not want to miss, serving as a comprehensive Market Map and Playbook designed to provide traders with a complete structural overview of price action. By synthesizing Market Structure, Liquidity concepts, and Regime detection, this script solves the problem of "analysis paralysis" by grading price action in real-time. It moves beyond simple indicators by offering a quantified "Playbook" that scores trade setups from 0 to 100, helping traders focus exclusively on high-probability opportunities while automating the complex math of position sizing and risk management. 🚀 Points of Innovation Proprietary Scoring Engine: Unlike standard indicators, this script assigns a quantitative score (0-100) to every potential trade based on confluence factors like HTF alignment and displacement. Dynamic Regime Detection: Features an integrated dashboard that classifies the market into specific phases (Expansion, Trend, Range) using ADX and EMA alignment logic. Smart Liquidity Pools: Automatically identifies and visualizes resting liquidity, tracking when these pools are "swept" to generate high-probability reversal signals. Integrated Trade Manager: Automates the calculation of Stop Loss, Take Profit (1:2 and 1:3), and Position Size based on account balance and risk percentage directly on the chart. Multi-Mode Interface: Offers three distinct visual modes—Clean, Pro, and Sniper—allowing users to toggle between deep analysis and clutter-free execution instantly. 🔧 Core Components Structure Module: Identifies Pivots, Break of Structure (BOS), and Change of Character (CHoCH) to define the current market bias. Liquidity Engine: Plots liquidity pools at key swing points and detects "Sweeps" where price grabs liquidity before reversing. Regime Filter: Uses a combination of EMAs (21/50) and ADX to determine if the market is trending or ranging, filtering out low-quality signals. Setup Validator: Monitors for three specific setup types (Sweep, Snapback, FVG Retest) and triggers alerts only when specific scoring thresholds are met. 🔥 Key Features Automated detection of High Timeframe (HTF) structure without repainting issues. Real-time grading of price displacement to validate institutional intent. Visual Risk/Reward boxes that automatically adjust to the volatility (ATR) of the asset. Fair Value Gap (FVG) detection with auto-mitigation tracking to clean up the chart. Customizable alerts for A+ setups, regime changes, and trade invalidations. Detailed dashboard displaying current Trend, Phase, Bias, and the score of the last setup. 🎨 Visualization Structure Points: Triangles for BOS and Diamonds for CHoCH events clearly mark trend shifts. Liquidity Lines: Dotted lines extending from pivots indicate un-swept liquidity pools; these dim automatically when swept. Setup Signals: Prominent "A+" labels appear on the chart when a setup meets the minimum score threshold defined by the user. Risk Boxes: Color-coded boxes (Green for Long, Red for Short) show Entry, Stop Loss, and Take Profit levels visually. Dashboard: A compact table in the bottom right corner provides a "Heads Up Display" of the market state. 📖 Usage Guidelines Display Mode: Select between 'Clean' for signals only, 'Pro' for full analysis including FVGs and Structure, or 'Sniper' for only high-score setups. HTF Timeframe: Sets the higher timeframe for structural analysis (Default: 240/4-Hour) to ensure you trade with the dominant trend. Min Score for A+ Setup: Threshold (0-100) required to trigger a signal (Default: 83); increase this to filter for only the absolute best trades. Risk %: Defines the percentage of your account you are willing to risk per trade (Default: 1.0%), used for the position size calculation. Account Balance: Input your current capital (Default: 10,000) to receive accurate unit sizing for every trade setup. ADX Threshold: Adjusts the sensitivity of the Regime detection filter (Default: 20) to determine when the market is trending versus ranging. ✅ Best Use Cases Confluence Trading: Use the scoring system to filter discretionary entries, taking trades only when the system scores them above 80. Prop Firm Trading: Utilize the built-in position size calculator to strictly adhere to risk management rules during evaluations. Trend Following: Wait for the Regime Dashboard to show "Bullish Expansion" before taking Long "Snapback" entries. Reversal Trading: Focus on "Sweep Reclaim" setups where price sweeps a liquidity pool and immediately closes back within range. ⚠️ Limitations This tool is a trend-following and reversal system; it may produce lower scores during undefined, low-volatility chop. The position size calculator is an estimation based on the entry candle; actual execution slippage is not accounted for. HTF data relies on closed candles to prevent repainting, which may result in a slight lag during rapid volatility spikes. 💡 What Makes This Unique Playbook Scoring: Most indicators just give a signal; PHEN ATLAS gives you a "Grade" (e.g., 85/100), allowing you to make informed decisions based on quality, not just frequency. Context Awareness: The script understands "Market Regime" and creates a context-aware bias, rather than blindly firing signals in a range. 🔬 How It Works Step 1 - Regime Definition: The script analyzes the 21/50 EMA relationship and ADX to define if the market is in a Trend or Range. Step 2 - Structure & Liquidity: It maps key pivots and liquidity pools, waiting for a "Sweep" event or a structural break. Step 3 - Setup Trigger: When a specific pattern occurs (like a Sweep Reclaim), the engine calculates a score based on displacement, volume, and key level alignment. Step 4 - Execution Logic: If the score > Threshold, the Trade Manager calculates the invalidation point (SL) and projects 2R/3R targets automatically. 🎉 Message From The Team 🎉 2025 was an amazing year. 12 months of building, shipping, and improving together with you. Hitting our 50th indicator release marks one full year of weekly drops , and we couldn't have done it without this community, and of course, BIG thank you to TradingView and it's team. Thank you for all the feedback, charts, and support. Let's make 2026 even bigger. We can't wait to show you what we've been working on. 🚀 💡 Note For best results, we recommend using the "Pro" mode during analysis to understand the narrative, and switching to "Sniper" or "Clean" during execution to maintain focus. Always ensure your "Account Balance" input matches your broker balance for accurate risk calculations.
Indicatore Pine Script®
di PhenLabs
2
Apex Adaptive Trend Navigator [Pineify]Apex Adaptive Trend Navigator The Apex Adaptive Trend Navigator is a comprehensive trend-following indicator that combines adaptive moving average technology, dynamic volatility bands, and market structure analysis into a single, cohesive trading tool. Designed for traders who want to identify trend direction with precision while filtering out market noise, this indicator adapts its sensitivity based on real-time market efficiency calculations. Key Features Adaptive Moving Average with efficiency-based smoothing factor Dynamic ATR-based volatility bands that expand and contract with market conditions Market Structure detection including BOS (Break of Structure) and CHoCH (Change of Character) Real-time performance dashboard displaying trend status and efficiency metrics Color-coded cloud visualization for intuitive trend identification How It Works The core of this indicator is built on an Adaptive Moving Average that uses a unique efficiency-based calculation method inspired by the Kaufman Adaptive Moving Average (KAMA) and TRAMA concepts. The efficiency ratio measures the directional movement of price relative to total price movement over the lookback period: Efficiency = |Price Change over N periods| / Sum of |Individual Bar Changes| This ratio ranges from 0 to 1, where values closer to 1 indicate a strong trending market with minimal noise, and values closer to 0 indicate choppy, sideways conditions. The smoothing factor is then squared to penalize noisy markets more aggressively, causing the adaptive line to flatten during consolidation and respond quickly during strong trends. The Dynamic Volatility Bands are calculated using the Average True Range (ATR) multiplied by a user-defined factor. These bands create a channel around the adaptive moving average, helping traders visualize the current volatility regime and potential support/resistance zones. Trading Ideas and Insights When price stays above the adaptive line with the bullish cloud forming, consider this a confirmation of uptrend strength The efficiency percentage in the dashboard indicates trend quality - higher values suggest more reliable trends Watch for price interactions with the upper and lower bands as potential reversal or continuation zones A flat adaptive line indicates consolidation - wait for a clear directional break before entering trades How Multiple Indicators Work Together This indicator integrates three complementary analytical approaches: The Adaptive Moving Average serves as the trend backbone, providing a dynamic centerline that automatically adjusts to market conditions. Unlike fixed-period moving averages, it reduces lag during trends while minimizing whipsaws during ranging markets. The ATR Volatility Bands work in conjunction with the adaptive MA to create a volatility envelope. When the adaptive line is trending and price remains within the cloud (between the MA and outer band), this confirms trend strength. Price breaking through the opposite band may signal exhaustion or reversal. The Market Structure Analysis using swing point detection adds a Smart Money Concepts (SMC) layer. BOS signals indicate trend continuation when price breaks previous swing highs in uptrends or swing lows in downtrends. CHoCH signals warn of potential reversals when the structure shifts against the prevailing trend. Unique Aspects The squared efficiency factor creates a non-linear response that dramatically reduces noise sensitivity Cloud fills only appear on the trend side, providing clear visual distinction between bullish and bearish regimes The integrated dashboard eliminates the need to switch between multiple indicators for trend assessment Pivot-based swing detection ensures accurate market structure identification How to Use Add the indicator to your chart and adjust the Lookback Period based on your trading timeframe (shorter for scalping, longer for swing trading) Monitor the cloud color - green clouds indicate bullish conditions, red clouds indicate bearish conditions Use the efficiency reading in the dashboard to gauge trend reliability before entering positions Consider entries when price pulls back to the adaptive line during strong trends (high efficiency) Use the volatility bands as dynamic take-profit or stop-loss reference levels Customization Lookback Period : Controls the sensitivity of trend detection and swing point identification (default: 20) Volatility Multiplier : Adjusts the width of the ATR bands (default: 2.0) Show Market Structure : Toggle visibility of BOS and CHoCH labels Show Performance Dashboard : Toggle the trend status table Color Settings : Customize bullish, bearish, and neutral colors to match your chart theme Conclusion The Apex Adaptive Trend Navigator offers traders a sophisticated yet intuitive approach to trend analysis. By combining adaptive smoothing technology with volatility measurement and market structure concepts, it provides multiple layers of confirmation for trading decisions. Whether you are a day trader seeking quick trend identification or a swing trader looking for reliable trend-following signals, this indicator adapts to your market conditions and trading style. The efficiency-based calculations ensure you always know not just the trend direction, but also the quality and reliability of that trend.
Indicatore Pine Script®
di Pineify
2
VWAP Bias (STRONG ONLY) + Alerts (Time Window)VWAP Bias + NO TRADE Discipline Label Clean, execution-focused indicator that removes decision noise. Shows LONG / SHORT bias based on price vs VWAP, upgraded to STRONG or WEAK using VWAP slope and EMA(9/20) alignment. A separate NO TRADE label appears when conditions are weak or neutral, enforcing discipline and preventing low-quality entries. Designed for day trading VWAP pullbacks and momentum, especially on 1m–5m charts. No oscillators, no clutter — just directional clarity and risk control.
Indicatore Pine Script®
di NetJacobsson
ALPHA FUSION FIX - RSI Extreme Strategy [Webhook Ready]Overview: This indicator is a simplified, high-precision tool focused on RSI Overbought and Oversold extremes (95/5). It was designed for traders who seek exhaustion points in the market with surgical precision. Key Features: Pure RSI Logic: Signals are triggered strictly at RSI 95 (Short) and RSI 5 (Long), avoiding market noise. Automation Ready: Includes a dynamic JSON Webhook integration for automated trading on exchanges like Binance. Risk Management: Built-in inputs for Margin, Leverage, and Max Positions directly in the UI. Visual Aids: Includes a Trio of EMAs (28, 80, 200) for trend context. How to use: Attach to any chart (Optimized for 15m/1h timeframes). Configure your Webhook Secret and risk parameters. Set an alert using "Any alert() function call".
Indicatore Pine Script®
di MarechalKhan
1
US Election Cycle Strategy [Druckenmiller]US Election Cycle Strategy This indicator allows you to visually backtest and monitor the "US Presidential Election Cycle" theory, famously advocated by legendary investors like Stanley Druckenmiller. The core premise of this strategy is that the stock market tends to demonstrate strong performance in the two years leading up to a US Presidential Election, largely driven by fiscal stimulus, increased government spending, and economic maneuvering aimed at securing re-election. How it works: The script algorithmically calculates the exact date of US Presidential Elections (defined as the Tuesday next after the first Monday in November) for every cycle from 1900 to 2040. It creates a theoretical "Buy" signal exactly two years prior to the election and a "Sell" signal on Election Day itself. Key Features of this Version: Dynamic Date Calculation: Unlike scripts with hard-coded dates, this version uses a mathematical algorithm to determine the precise election date for any given year, ensuring historical accuracy and future-proofing. Maximized History: The script automatically utilizes all available historical data provided by your chart. It does not arbitrarily cut off data (e.g., at 1970) unless you specifically choose a different start year in the settings. Performance Statistics: An integrated dashboard displays key metrics based on the available history, including Average Return, Median Return, and the overall Win Rate of the strategy. Visual Feedback: The "Entry" point is marked with a dashed line, which automatically colors itself Green (Profit) or Red (Loss) once the cycle is completed, giving you an immediate visual heatmap of historical performance. Settings: You can customize the "Start Calculation From Year" to filter the statistics for specific eras (e.g., set it to 2000 to see only modern market behavior). The visual appearance of lines and the statistics table are fully customizable. Note: This "strategy" is best applied to major US Indices (such as the S&P 500 or Dow Jones Industrial Average) on a Daily or Weekly timeframe.
Indicatore Pine Script®
di robinzawa
MACD Matrix: Angle & SettlementThis indicator is a comprehensive Multi-Timeframe (MTF) Dashboard designed for technical traders who rely on MACD not just for crossovers, but for Momentum Angle and Settlement (Hooks). Instead of cluttering your screen with 5 different MACD charts, this Matrix calculates the math in the background and presents a clean "Heads-Up Display" of the MACD state across your specific timeframes (Default: 3m, 15m, 1h, 4h, 16h). The Concept: "Angle Settlement" Standard MACD indicators only show you when a cross happens. By then, the move is often halfway over. This script focuses on the Angle (Slope) of the MACD line to predict turns before they happen: Steep Angle: Momentum is accelerating. (Strong Trend) Settling Angle: The slope is flattening out. The MACD line is "hooking." (Reversal/Cross Imminent) Dashboard Columns Explained TF (Timeframe): Auto-formats your settings into readable text (e.g., "240" becomes "4h"). Zone: > 0 (Green): MACD is above the Zero Line (Bullish Trend context). < 0 (Red): MACD is below the Zero Line (Bearish Trend context). Cross: PCO (Green): Positive Crossover (MACD > Signal). NCO (Red): Negative Crossover (MACD < Signal). Deg (°): The calculated mathematical angle of the MACD line. Positive (+): Momentum is rising. Negative (-): Momentum is falling. State (The Strategy): STEEP (Bright Color): The angle is increasing. Do not trade against this momentum. SETTLE (Dim Color): The angle is decreasing compared to the previous bar. The momentum is "cooling off," often signaling a "Hook" or an upcoming crossover. Settings & Customization Custom Timeframes: You can freely change TF-1, TF-2, etc., in the settings. The table labels will auto-update (e.g., if you change 4h to 1D, the table will display "1D"). MACD Lengths: Fully customizable (Default 12, 26, 9). Angle Sensitivity: A multiplier to calibrate the "Degrees" to your specific asset class (Crypto, Forex, or Indices). If angles look too small, increase this value.
Indicatore Pine Script®
di PratikKharat1990
IFM 2.0only for pips college IFM (Inner Force Model) is a price-action based trading model that focuses on who controls the market internally—buyers or sellers—before the big move happens. It’s not an indicator. It’s a market behavior framework used to read institutional intent. 🔍 What IFM Really Means IFM studies the internal strength (force) inside price by analyzing: Liquidity grabs Market structure shifts Displacement (strong candles) Premium / Discount positioning The goal is simple: 👉 Enter where smart money has already committed
Indicatore Pine Script®
di xenfxeliteofficial
Red Bull Wings [JOAT]RED BULL WINGS - Bullish-Only Institutional Overlay Introduction and Purpose RED BULL WINGS is an open-source overlay indicator that combines five distinct bullish detection methods into a single composite scoring system. The core problem this indicator solves is that individual bullish signals (patterns, volume, zones, trendlines) often disagree or fire in isolation. A bullish engulfing pattern means little if volume is weak and price is far from support. Traders need confluence across multiple dimensions to identify high-probability setups. This indicator addresses that by scoring each bullish component separately, then combining them into a weighted WINGS score (0-100) that reflects overall bullish conviction. When multiple components align, the score rises; when they disagree, the score stays low. Why These Five Modules Work Together Each module measures a different aspect of bullish market structure: 1. Module A - Bullish Candlestick Engine - Detects classic reversal patterns (engulfing, marubozu, hammer, 3-bar cluster). These patterns identify WHERE buyers are stepping in. 2. Module B - PVSRA Volume Climax - Measures spread x volume to detect institutional participation. This tells you WHETHER smart money is involved. 3. Module C - Demand Zone Detection - Identifies and tracks order block zones where buyers previously overwhelmed sellers. This shows you WHERE institutional support exists. 4. Module D - Trendline Channel - Builds dynamic support/resistance from pivot points. This reveals the STRUCTURE of the current trend. 5. Module E - Ichimoku Assist - Optional filter using Tenkan/Kijun cross, cloud position, and Chikou confirmation. This provides TREND PERMISSION context. The combination works because: Patterns alone can fail without volume confirmation Volume alone means nothing without price structure context Zones alone are static without pattern/volume triggers Trendlines alone miss the micro-level entry timing When 3+ modules agree, the probability of a valid bullish setup increases significantly How the Calculations Work Module A - Pattern Detection: Bullish Engulfing - Current bullish bar completely engulfs prior bearish bar: bool engulfingCond = isBullish() and isBearish() and open <= close and close >= open and bodySize() > bodySize() Marubozu - Strong body with minimal wicks (body >= 1.8x average, wick ratio < 20%): float wickRatio = candleRange() > 0 ? (upperWick() + lowerWick()) / candleRange() : 0 bool marubozuCond = isBullish() and bodySize() >= bodySizeAvg * i_maruMult and wickRatio < i_wickRatioMax Hammer - Long lower wick (>= 2.5x body), close in upper third, volume confirmation: bool hammerWick = lowerWick() >= i_hammerWickMult * bodySize() bool hammerClose = close >= low + (candleRange() * 0.66) bool hammerVol = volume >= i_pvsraRisingMult * volAvg 3-Bar Cluster - Three consecutive bullish closes with increasing prices and volume spike: bool threeBarBullish = isBullish() and isBullish() and isBullish() bool increasingCloses = close > close and close > close bool volSpike3Bar = volume >= i_pvsraRisingMult * volAvg or volume >= i_pvsraRisingMult * volAvg Module B - PVSRA Volume Analysis: Uses spread x volume to detect climax conditions: float spreadVol = candleRange() * volume float maxSpreadVol = ta.highest(spreadVol, ADJ_PVSRA_LOOKBACK) bool volClimax = volume >= i_pvsraClimaxMult * volAvg or spreadVol >= maxSpreadVol bool volRising = volume >= i_pvsraRisingMult * volAvg and volume < i_pvsraClimaxMult * volAvg Volume only scores when the candle is bullish, preventing false signals on bearish volume spikes. Module C - Demand Zone Detection: Identifies zones using a two-candle structure: // Small bearish candle A followed by larger bullish candle B bool candleA_bearish = isBearish() bool candleB_bullish = isBullish() bool newZoneCond = candleA_bearish and candleB_bullish and candleB_size >= i_zoneSizeMult * candleA_size Zones are drawn as rectangles and tracked for retests. Score increases when price is near or inside an active zone, with bonus points for rejection candles. Module D - Trendline Channel: Builds dynamic channel from confirmed pivot points: float ph = ta.pivothigh(high, i_pivotLeft, i_pivotRight) float pl = ta.pivotlow(low, i_pivotLeft, i_pivotRight) Pivots are stored and connected to form upper/lower channel lines. The indicator detects breakouts when price closes beyond the channel with volume confirmation. Module E - Ichimoku Assist: Standard Ichimoku calculations with bullish scoring: float tenkan = (ta.highest(high, i_tenkanLen) + ta.lowest(low, i_tenkanLen)) / 2 float kijun = (ta.highest(high, i_kijunLen) + ta.lowest(low, i_kijunLen)) / 2 bool tkCross = ta.crossover(tenkan, kijun) bool priceAboveCloud = close > cloudTop bool chikouAbovePrice = chikou > close Module F - WINGS Composite Score: All module scores are combined using adjustable weights: float WINGS_score = 100 * (nW_pattern * S_pattern + nW_volume * S_vol + nW_zone * S_zone + nW_trend * S_trend + nW_ichi * S_ichi) Default weights: Pattern 30%, Volume 25%, Zone 20%, Trend 15%, Ichimoku 10%. Signal Thresholds WATCH (30-49) - Interesting bullish context forming, not yet actionable MOMENTUM (50-74) - Strong bullish conditions, multiple modules agreeing LIFT-OFF (75+) - High-confidence bullish confluence across most modules WINGS Badge (Dashboard) The right-side panel displays: WINGS Score - Current composite score (0-100) Pattern - Active pattern name and strength, or neutral placeholder Volume - Normal / Rising / CLIMAX status Zone - ACTIVE if price is near a demand zone Trend - Channel position or BREAK status Ichimoku - OFF / Weak / Bullish / STRONG Status - Overall signal level (Neutral / WATCH / MOMENTUM / LIFT-OFF) Input Parameters Module Toggles: Enable Bullish Patterns (true) - Toggle pattern detection Enable PVSRA Volume (true) - Toggle volume analysis Enable Order Blocks (true) - Toggle demand zone detection Enable Trendlines (true) - Toggle pivot channel Enable Ichimoku Assist (false) - Toggle Ichimoku filter (off by default for performance) Enable Visual Effects (false) - Toggle labels, trails, and visual elements LIVE MODE (false) - Enable intrabar signals (WARNING: signals may repaint) Pattern Engine: Pattern Lookback (5) - Bars for body size averaging Marubozu Body Multiplier (1.8) - Minimum body size vs average Hammer Wick Multiplier (2.5) - Minimum lower wick vs body Max Wick Ratio (0.2) - Maximum wick percentage for marubozu Volume / PVSRA: PVSRA Lookback (10) - Period for volume averaging Climax Multiplier (2.0) - Volume threshold for climax detection Rising Volume Multiplier (1.5) - Volume threshold for rising detection Order Blocks: Zone Size Multiplier (2.0) - Minimum bullish candle size vs bearish Zone Extend Bars (200) - How far zones project forward Max Zones (12) - Maximum active zones displayed Remove Zone on Close Below (true) - Delete broken zones Trendlines: Pivot Left/Right Bars (3/3) - Pivot detection sensitivity Min Slope % (0.25) - Minimum trendline angle Max Trendlines (5) - Maximum pivot points stored Trendline Projection Bars (60) - Forward projection distance Ichimoku: Tenkan Length (9) - Conversion line period Kijun Length (26) - Base line period Senkou B Length (52) - Leading span B period Displacement (26) - Cloud displacement WINGS Score: Weight: Pattern (0.30) - Pattern contribution to score Weight: Volume (0.25) - Volume contribution to score Weight: Zone (0.20) - Zone contribution to score Weight: Trend (0.15) - Trendline contribution to score Weight: Ichimoku (0.10) - Ichimoku contribution to score Lift-Off Threshold (75) - Score required for LIFT-OFF signal Momentum Watch Threshold (50) - Score required for MOMENTUM signal Visuals: Signal Cooldown (8) - Minimum bars between labels Show WINGS Score Badge (true) - Toggle dashboard Show Wing Combos (true) - Show DOUBLE/MEGA WINGS streaks Red Background Wash (true) - Tint chart background Show Lift-Off Trails (false) - Toggle golden trail visuals How to Use This Indicator For Bullish Entry Identification: 1. Monitor the WINGS badge for score changes 2. Wait for MOMENTUM (50+) or LIFT-OFF (75+) signals 3. Check which modules are contributing (Pattern + Volume + Zone = stronger) 4. Use demand zones and trendlines as structural reference for entries For Confluence Confirmation: 1. Use alongside your existing analysis 2. LIFT-OFF signals indicate multiple bullish factors aligning 3. Low scores (< 30) suggest weak bullish context even if one factor looks good For Zone-Based Trading: 1. Watch for price approaching active demand zones 2. Look for pattern + volume confirmation at zone retests 3. Zone score increases with successful retests For Trendline Analysis: 1. Monitor the pivot-based channel for trend structure 2. Breakouts with volume confirmation trigger TREND BREAK alerts 3. Price inside channel with bullish patterns = trend continuation setup 1M and lower timeframes: Alerts Available LIFT-OFF - High-confidence bullish confluence MOMENTUM - Strong bullish conditions Zone Retest - Bullish rejection from demand zone Trendline Break - Breakout with volume confirmation Individual patterns (Engulfing, Marubozu, Hammer, 3-Bar Cluster) Volume Climax - Institutional volume spike DOUBLE WINGS / MEGA WINGS - Consecutive lift-off signals Repainting Behavior By default, the indicator uses confirmed bars only (barstate.isconfirmed), meaning signals appear after the bar closes and do not repaint. However: LIVE MODE - When enabled, signals can appear intrabar but may disappear if conditions change before bar close. A warning label displays when LIVE MODE is active. Trendlines - Pivot detection requires lookback bars, so the most recent trendline segments may adjust as new pivots confirm. This is inherent to pivot-based analysis. Demand Zones - Zones are created on confirmed bars and do not repaint, but they can be removed if price closes below the zone bottom (configurable). Live Mode with 'Enable Visual Effect' turned off in settings: Limitations This is a bullish-only indicator. It does not detect bearish setups or provide short signals. The WINGS score is a confluence measure, not a prediction. High scores indicate favorable conditions, not guaranteed outcomes. Pattern detection uses simplified logic. Not all candlestick nuances are captured. Volume analysis requires reliable volume data. Results may vary on instruments with inconsistent volume reporting. Ichimoku calculations add processing overhead. Disable if not needed. Demand zones are based on a specific two-candle structure. Other valid zones may not be detected. Trendlines use linear regression between pivots. Curved or complex channels are not supported. Timeframe Recommendations 15m-1H: More frequent signals, useful for intraday analysis. Higher noise. 4H-Daily: Best balance of signal quality and frequency for swing trading. Weekly: Fewer but more significant signals for position trading. Adjust lookback periods and thresholds based on your timeframe. Shorter timeframes may benefit from shorter lookbacks. Open-Source and Disclaimer This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. The source code is fully visible and can be studied to understand how each module works. This indicator does not constitute financial advice. The WINGS score and signals do not guarantee profitable trades. Past performance does not guarantee future results. Always use proper risk management, position sizing, and stop-losses. Test thoroughly on your preferred instruments and timeframes before using in live trading. - Made with passion by officialjackofalltrades
Indicatore Pine Script®
di officialjackofalltrades
Sessions and Killzones [Tradeuminati]Tradeuminati – Sessions & Killzones is a New York local time based session toolkit designed for traders who want clean, objective session structure on their chart: session boundaries, killzones, session highs/lows, and previous day levels plus a live “liquidity taken” checklist. Key Features 1) Sessions (New York Time) London Session (0:00 – 6:00 NY) - Vertical start/end lines - Live session High and Low tracking during the session - High/Low levels extend until 16:00 NY - Labels: Ls - H and Ls - L - Option to display only the current day Asia Session (Previous Day, 18:00 – 00:00 NY) - Vertical start/end lines for the previous day session - Live session High and Low tracking - High/Low levels extend into the next day until 16:00 NY - Labels: As - H and As - L - Option to display only the current day 2) Killzones (New York Time) London Killzone: 2:00 – 5:00 NY - Optional DAX-only mode: If enabled, DAX uses 3:00 – 5:00 NY (DAX opening), while other assets remain 2:00 – 5:00 NY New York Killzone (auto-adjust by asset type) - Indices: 9:30 – 11:00 NY - Other assets (FX / Commodities / Crypto): 7:00 – 10:00 NY New York PM Killzone: 14:00 – 15:00 NY (all assets) ll killzone lines are placed from the start of the NY day, so you can see upcoming killzones in advance (not only after candles appear). 3) Previous Day High / Low (PDH / PDL) - Automatically calculates the full previous NY day range (00:00 – 23:59 NY) - Plots PDH and PDL into the current day - Labels: PDH and PDL 4) Live “Liquidity Taken” Table - A compact table in the bottom-left shows whether price has: - swept Asia High / Asia Low - swept London High / London Low - taken PDH / PDL A green checkmark appears instantly once a level is broken. Customization Fully adjustable colors, widths, and line styles for: - Session vertical lines - Session high/low lines - Killzones - PDH/PDL Adjustable label size Day filtering options (current day only) ----- Disclaimer This indicator is for educational and technical analysis purposes only. It does not constitute financial or investment advice. Trading involves risk.
Indicatore Pine Script®
di DonauTrading
EMTIA_MASTER_LIBLibrary "EMTIA_MASTER_LIB" trendUp(emaFast, emaSlow)   Parameters:      emaFast (float)      emaSlow (float) rsiHealthy(rsi)   Parameters:      rsi (float) adxStrong(adx, diPlus, diMinus)   Parameters:      adx (float)      diPlus (float)      diMinus (float) macroSlope(emaFast, emaSlow)   Parameters:      emaFast (float)      emaSlow (float) structureBull(hh, hl)   Parameters:      hh (bool)      hl (bool) calcScore(weeklyTrend, dailyTrend, adxOk, rsiOk, structureOk, macroOk)   Parameters:      weeklyTrend (bool)      dailyTrend (bool)      adxOk (bool)      rsiOk (bool)      structureOk (bool)      macroOk (bool)
Libreria Pine Script®
di eflatunid
Liquidation Bubbles [OmegaTools]🔴🟢 Liquidation Bubbles — Advanced Volume & Price Stress Detector Liquidation Bubbles is a professional-grade analytical tool designed to identify forced positioning events, stop-runs, and liquidation clusters by combining price displacement and volume imbalance into a single, statistically normalized framework. This indicator is not a repainting signal tool and not a simple volume spike detector. It is a contextual market stress mapper, built to highlight areas where one-sided positioning becomes unstable and the probability of forced order execution (liquidations, stops, margin calls) materially increases. --- ## 🔬 Core Concept Market liquidations do not occur randomly. They emerge when price deviates aggressively from its volume-weighted equilibrium while volume itself becomes abnormal. Liquidation Bubbles detects exactly this condition by: * Estimating a **dynamic equilibrium price** using an *inverted volume-weighted moving average* * Measuring **directional price stress** relative to that equilibrium * Measuring **volume stress** relative to its own adaptive baseline * Normalizing both into **Z-score–like metrics** * Highlighting only **statistically extreme, asymmetric events** The result is a clear visual map of stress points where market participants are most vulnerable. --- ⚙️ Methodology (How It Works) 1️⃣ Advanced Inverted VWMA (Equilibrium Engine) The script uses a custom Advanced VWMA, where: * High volume bars receive less weight * Low volume bars receive more weight This produces a **robust equilibrium level**, resistant to manipulation and volume bursts. This equilibrium is used for **both price and volume normalization**, creating a consistent statistical framework. --- 2️⃣ Price Stress (Directional) Price stress is calculated as: * The **maximum deviation** between high/low and equilibrium * Directionally signed (upside vs downside) * Normalized by its own historical volatility This allows the script to distinguish: * Aggressive upside exhaustion * Aggressive downside capitulation --- 3️⃣ Volume Stress Volume stress is measured as: * Deviation from volume equilibrium * Normalized by historical volume dispersion This filters out: * Normal high-volume sessions * Illiquid noise And isolates abnormal participation imbalance. --- 4️⃣ Liquidation Logic A liquidation event is flagged when: * Both price stress and volume stress exceed adaptive thresholds * The imbalance is directional and statistically extreme Optional Combined Score Mode allows aggregation of price & volume stress into a single composite metric for smoother signals. --- 🔵 Bubble System (Signal Hierarchy) The indicator plots **two tiers of bubbles**: 🟢🔴 Small Bubbles * Early warning stress points * Localized stop-runs * Micro-liquidations * Often precede reactions or short-term reversals 🟢🔴 Big Bubbles * Full liquidation clusters * Forced unwinds * High probability exhaustion zones * Frequently align with: * Intraday extremes * Range boundaries * Reversal pivots * Volatility expansions Bubble color: * **Green** → Downside liquidation (sell-side exhaustion) * **Red** → Upside liquidation (buy-side exhaustion) Bubble placement is **ATR-adjusted**, ensuring visual clarity without overlapping price. --- 🔄 Cross-Market Volume Analysis The script allows optional **external volume sourcing**, enabling: * Futures volume applied to CFDs * Index volume applied to ETFs * Spot volume applied to derivatives This is critical when: * Your traded instrument has unreliable volume * You want **institutional-grade confirmation** --- 🧠 How to Use Liquidation Bubbles This indicator is **not meant to be traded alone**. Best use cases: * 🔹 Confluence with support & resistance * 🔹 Contextual confirmation for reversals * 🔹 Identifying fake breakouts * 🔹 Liquidity sweep detection * 🔹 Risk management (avoid entering into liquidation zones) Ideal for: * Futures * Indices * Crypto * High-liquidity FX pairs * Intraday & swing trading --- 🎯 Who This Tool Is For Liquidation Bubbles is designed for: * Advanced discretionary traders * Order-flow & liquidity-based traders * Macro & index traders * Professionals seeking **context**, not signals If you want **where the market is fragile**, not just where price moved — this tool was built for you. --- 📌 Key Characteristics ✔ Non-repainting ✔ Statistically normalized ✔ Adaptive to volatility ✔ Works on all timeframes ✔ Futures & crypto ready ✔ No lagging indicators ✔ No moving average crosses --- Liquidation Bubbles does not predict the future. It shows you where the market is most likely to break. — OmegaTools
Indicatore Pine Script®
di OmegaTools
1
Skewness Indicator偏態分佈指標Skewness Indicator 核心功能 偏度計算 - 測量價格分佈的不對稱性 正偏度:價格傾向於右偏,可能表示上漲趨勢 負偏度:價格傾向於左偏,可能表示下跌趨勢 可自定義參數 計算週期(預設20) 數據源(收盤價、開盤價等) 正負偏態閾值 視覺化元素 藍色線:即時偏度值 橙色線:偏度移動平均(平滑訊號) 背景顏色:綠色表示強正偏態,紅色表示強負偏態 信號標記:三角形標示潛在的交易機會 交易信號 看漲信號:當偏度向上突破負閾值 看跌信號:當偏度向下跌破正閾值 資訊面板 - 右上角顯示當前偏度值和狀態 功能 多時間週期(HTF) - 可選擇在更高時間框架上計算偏度(例如在5分鐘圖上顯示日線的偏度) 交易信號 - 三角形標記顯示潛在的交易機會 資訊面板 - 右上角顯示當前偏度值和市場狀態 視覺提示 - 閾值線和背景顏色提示極端狀態 使用建議 在參數中勾選「使用高時間週期」 選擇你想要的時間週期(如 D=日線, W=週線, 240=4小時) 這樣可以在短週期圖表上看到長週期的偏態趨勢 Core functions Skewness calculation-Measuring the asymmetry of price distribution Positive bias: The price tends to the right, which may indicate an upward trend Negative bias: The price tends to the left, which may indicate a downward trend Customizable parameters Calculation cycle (default 20) Data source (closing price, opening price, etc.) Positive and negative bias threshold Visual elements Blue line: instant skewness value Orange line: skewed moving average (smooth signal) Background color: green indicates a strong positive bias, red indicates a strong negative bias Signal mark: Triangle marks potential trading opportunities Trading signals Bullish signal: when the skewness breaks through the negative threshold upward Bearish signal: when the bias falls below the positive threshold Information panel-the upper right corner displays the current skewness value and status function Multi-time period (HTF)-you can choose to calculate the skewness on a higher time frame (for example, display the skewness of the daily line on a 5-minute chart) Trading signals-Triangle marks show potential trading opportunities Information panel-the upper right corner displays the current skewness value and market status Visual cues-threshold lines and background colors indicate extreme states Recommendations for use Check "Use high time period" in the parameters Choose the time period you want (e.g. D= daily, W= weekly, 240= 4 hours) In this way, you can see the long-cycle bias trend on the short-cycle chart
Indicatore Pine Script®
di YOWYI
Multi KI Agenten Strategie (Final V2)What's included in the Pine Script (Technical Analysis) These features are mathematically implemented in the script and function as "agent logic": • Trend Following: Integrated via EMAs (50, 100, 200). • Volume Analysis: An agent checks for institutional volume spikes. • Supply & Demand: Zones are calculated based on price extremes. • RSI & Fibonacci: Both are built in as decision criteria for the agents. • Controlling AI: The "veto logic" in the code acts as a controlling instance, blocking signals if the risk is too high or divergences exist. • Alerts: The "LONG" and "SHORT" alerts are only triggered after approval by the controlling mechanism.
Strategia Pine Script®
di sven_kittelmann