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عكفة الماكد المتقدمة - أبو فارس ©// 🔒 Advanced MACD Curve © 2025 // 💡 Idea & Creativity: Engineer Abu Elias // 🛠️ Development & Implementation: Abu Fares // 📜 All intellectual rights reserved - Copying, modifying, or redistributing is not permitted // 🚫 Any attempt to tamper with this code or violate intellectual property rights is legally prohibited // 📧 For inquiries and licensing: Please contact the developer, Abu Fares
อินดิเคเตอร์ Pine Script®
โดย ABU_FARIS
NN Crypto Scalping ULTIMATE v6 - MTF mapercivNeural Network Crypto Trading System v6.1 Complete Technical Documentation Author : Neural Network Ensemble Trading System Version : 6.1 - MTF Corrected & Bias Fixed Date : January 2025 Platform : TradingView PineScript v6 Executive Summary The Neural Network Crypto Trading System v6.1 is an advanced algorithmic trading system that combines three specialized neural networks into an intelligent ensemble to generate cryptocurrency trading signals. The system integrates multi-timeframe analysis, crypto-specific optimizations, dynamic risk management, and continuous learning to maximize performance in highly volatile markets. Key Features: Ensemble of 3 specialized Neural Networks (Primary, Momentum, Volatility) Multi-Timeframe Analysis with 5 timeframes (5m, 15m, 1h, 4h, 1D) 22 Advanced Features for each model Anti-repainting guaranteed with confirmed data 8 Market Regime automatic detections 6 Signal Levels (Strong/Moderate/Weak Buy/Sell) Professional dashboard with 15+ real-time metrics Intelligent alert system with webhook integration
อินดิเคเตอร์ Pine Script®
โดย maperciv
Bitcoin Power Law with Cycle BandsBitcoin Power Law with Cycle Bands DescriptionUnlock the power of Bitcoin’s long-term trends with the Bitcoin Power Law with Cycle Bands script, exclusively available through Bitcoin Wealth Edge! This custom TradingView indicator, built for Pine Script v6, models Bitcoin’s price behavior using a 96% R² power law trendline, derived from days since its genesis (January 3, 2009). Designed to predict cycle tops and bottoms, it features:Power Law Trendline: A cyan line representing fair value (e.g., ~$111,000 as of September 2025), based on a logarithmic regression with adjustable coefficients (a = -17.02, b = 5.83). Cycle Bands: Adjustable red (upper) and green (lower) bands, defaulting to 3.5x and -3.5x multipliers, aligning with historical peaks (e.g., $69K in 2021) and troughs (e.g., $16K in 2022). Dynamic Labels: Real-time labels displaying fair value, upper limit ($180K), and lower limit ($40K), updated on the last bar for quick insights. Follow @HodlerRanch for updates!
อินดิเคเตอร์ Pine Script®
โดย PlebDave
FNGAdataDates_Part1FNGAdataDates_Part1 provides historical trading dates for a financial instrument (e.g., FNGA index or related asset) from May 23, 2025, to approximately mid-2021, covering 950 trading days. The dates are organized into 19 chunks (dates_0 to dates_18), each containing 50 timestamps representing trading days (excluding weekends and possibly holidays). This library is part one of a two-part set due to Pine Script token limits and must be used with FNGAdataDates_Part2 for the complete dataset (1,846 dates). It is designed to align with the FNGAopenPrices and FNGAclosePrices libraries for backtesting, technical analysis, or visualization in Pine Script.
ไลบรารี Pine Script®
โดย bsouthhh
Savitzky-Golay Hampel Filter | AlphaNattSavitzky-Golay Hampel Filter | AlphaNatt A revolutionary indicator combining NASA's satellite data processing algorithms with robust statistical outlier detection to create the most scientifically advanced trend filter available on TradingView. "This is the same mathematics that processes signals from the Hubble Space Telescope and analyzes data from the Large Hadron Collider - now applied to financial markets." ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🚀 SCIENTIFIC PEDIGREE Savitzky-Golay Filter Applications: NASA: Satellite telemetry and space probe data processing CERN: Particle physics data analysis at the LHC Pharmaceutical: Chromatography and spectroscopy analysis Astronomy: Processing signals from radio telescopes Medical: ECG and EEG signal processing Hampel Filter Usage: Aerospace: Cleaning sensor data from aircraft and spacecraft Manufacturing: Quality control in precision engineering Seismology: Earthquake detection and analysis Robotics: Sensor fusion and noise reduction ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🧬 THE MATHEMATICS 1. Savitzky-Golay Filter The SG filter performs local polynomial regression on data points: Fits a polynomial of degree n to a sliding window of data Evaluates the polynomial at the center point Preserves higher moments (peaks, valleys) unlike moving averages Maintains derivative information for true momentum analysis Originally published in Analytical Chemistry (1964) Mathematical Properties: Optimal smoothing in the least-squares sense Preserves statistical moments up to polynomial order Exact derivative calculation without additional lag Superior frequency response vs traditional filters 2. Hampel Filter A robust outlier detector based on Median Absolute Deviation (MAD): Identifies outliers using robust statistics Replaces spurious values with polynomial-fitted estimates Resistant to up to 50% contaminated data MAD is 1.4826 times more robust than standard deviation Outlier Detection Formula: |x - median| > k × 1.4826 × MAD Where k is the threshold parameter (typically 3 for 99.7% confidence) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💎 WHY THIS IS SUPERIOR vs Moving Averages: Preserves peaks and valleys (critical for catching tops/bottoms) No lag penalty for smoothness Maintains derivative information Polynomial fitting > simple averaging vs Other Filters: Outlier immunity (Hampel component) Scientifically optimal smoothing Preserves higher-order features Used in billion-dollar research projects Unique Advantages: Feature Preservation: Maintains market structure while smoothing Spike Immunity: Ignores false breakouts and stop hunts Derivative Accuracy: True momentum without additional indicators Scientific Validation: 60+ years of academic research ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚙️ PARAMETER OPTIMIZATION 1. Polynomial Order (2-5) 2 (Quadratic): Maximum smoothing, gentle curves 3 (Cubic): Balanced smoothing and responsiveness (recommended) 4-5 (Higher): More responsive, preserves more features 2. Window Size (7-51) Must be odd number Larger = smoother but more lag Formula: 2×(desired smoothing period) + 1 Default 21 = analyzes 10 bars each side 3. Hampel Threshold (1.0-5.0) 1.0: Aggressive outlier removal (68% confidence) 2.0: Moderate outlier removal (95% confidence) 3.0: Conservative outlier removal (99.7% confidence) (default) 4.0+: Only extreme outliers removed 4. Final Smoothing (1-7) Additional WMA smoothing after filtering 1 = No additional smoothing 3-5 = Recommended for most timeframes 7 = Ultra-smooth for position trading ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 TRADING STRATEGIES Signal Recognition: Cyan Line: Bullish trend with positive derivative Pink Line: Bearish trend with negative derivative Color Change: Trend reversal with polynomial confirmation 1. Trend Following Strategy Enter when price crosses above cyan filter Exit when filter turns pink Use filter as dynamic stop loss Best in trending markets 2. Mean Reversion Strategy Enter long when price touches filter from below in uptrend Enter short when price touches filter from above in downtrend Exit at opposite band or filter color change Excellent for range-bound markets 3. Derivative Strategy (Advanced) The SG filter preserves derivative information Acceleration = second derivative > 0 Enter on positive first derivative + positive acceleration Exit on negative second derivative (momentum slowing) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📈 PERFORMANCE CHARACTERISTICS Strengths: Outlier Immunity: Ignores stop hunts and flash crashes Feature Preservation: Catches tops/bottoms better than MAs Smooth Output: Reduces whipsaws significantly Scientific Basis: Not curve-fitted or optimized to markets Considerations: Slight lag in extreme volatility (all filters have this) Requires odd window sizes (mathematical requirement) More complex than simple moving averages Best with liquid instruments ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🔬 SCIENTIFIC BACKGROUND Savitzky-Golay Publication: "Smoothing and Differentiation of Data by Simplified Least Squares Procedures" - Abraham Savitzky & Marcel Golay - Analytical Chemistry, Vol. 36, No. 8, 1964 Hampel Filter Origin: "Robust Statistics: The Approach Based on Influence Functions" - Frank Hampel et al., 1986 - Princeton University Press These techniques have been validated in thousands of scientific papers and are standard tools in: NASA's Jet Propulsion Laboratory European Space Agency CERN (Large Hadron Collider) MIT Lincoln Laboratory Max Planck Institutes ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 ADVANCED TIPS News Trading: Lower Hampel threshold before major events to catch spikes Scalping: Use Order=2 for maximum smoothness, Window=11 for responsiveness Position Trading: Increase Window to 31+ for long-term trends Combine with Volume: Strong trends need volume confirmation Multiple Timeframes: Use daily for trend, hourly for entry Watch the Derivative: Filter color changes when first derivative changes sign ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚠️ IMPORTANT NOTICES Not financial advice - educational purposes only Past performance does not guarantee future results Always use proper risk management Test settings on your specific instrument and timeframe No indicator is perfect - part of complete trading system ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🏆 CONCLUSION The Savitzky-Golay Hampel Filter represents the pinnacle of scientific signal processing applied to financial markets. By combining polynomial regression with robust outlier detection, traders gain access to the same mathematical tools that: Guide spacecraft to other planets Detect gravitational waves from black holes Analyze particle collisions at near light-speed Process signals from deep space This isn't just another indicator - it's rocket science for trading . "When NASA needs to separate signal from noise in billion-dollar missions, they use these exact algorithms. Now you can too." ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Developed by AlphaNatt Version: 1.0 Release: 2025 Pine Script: v6 "Where Space Technology Meets Market Analysis" Not financial advice. Always DYOR
อินดิเคเตอร์ Pine Script®
โดย AlphaNatt
3
Laguerre-Kalman Adaptive Filter | AlphaNattLaguerre-Kalman Adaptive Filter |AlphaNatt A sophisticated trend-following indicator that combines Laguerre polynomial filtering with Kalman optimal estimation to create an ultra-smooth, low-lag trend line with exceptional noise reduction capabilities. "The perfect trend line adapts to market conditions while filtering out noise - this indicator achieves both through advanced mathematical techniques rarely seen in retail trading." ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎯 KEY FEATURES Dual-Filter Architecture: Combines two powerful filtering methods for superior performance Adaptive Volatility Adjustment: Automatically adapts to market conditions Minimal Lag: Laguerre polynomials provide faster response than traditional moving averages Optimal Noise Reduction: Kalman filtering removes market noise while preserving trend Clean Visual Design: Color-coded trend visualization (cyan/pink) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 THE MATHEMATICS 1. Laguerre Filter Component The Laguerre filter uses a cascade of four all-pass filters with a single gamma parameter: 4th order IIR (Infinite Impulse Response) filter Single parameter (gamma) controls all filter characteristics Provides smoother output than EMA with similar lag Based on Laguerre polynomials from quantum mechanics 2. Kalman Filter Component Implements a simplified Kalman filter for optimal estimation: Prediction-correction algorithm from aerospace engineering Dynamically adjusts based on estimation error Provides mathematically optimal estimate of true price trend Reduces noise while maintaining responsiveness 3. Adaptive Mechanism Monitors market volatility in real-time Adjusts filter parameters based on current conditions More responsive in trending markets More stable in ranging markets ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚙️ INDICATOR SETTINGS Laguerre Gamma (0.1-0.99): Controls filter smoothness. Higher = smoother but more lag Adaptive Period (5-100): Lookback for volatility calculation Kalman Noise Reduction (0.1-2.0): Higher = more noise filtering Trend Threshold (0.0001-0.01): Minimum change to register trend shift Recommended Settings: Scalping: Gamma: 0.6, Period: 10, Noise: 0.3 Day Trading: Gamma: 0.8, Period: 20, Noise: 0.5 (default) Swing Trading: Gamma: 0.9, Period: 30, Noise: 0.8 Position Trading: Gamma: 0.95, Period: 50, Noise: 1.2 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📈 TRADING SIGNALS Primary Signals: Cyan Line: Bullish trend - price above filter and filter ascending Pink Line: Bearish trend - price below filter or filter descending Color Change: Potential trend reversal point Entry Strategies: Trend Continuation: Enter on pullback to filter line in trending market Trend Reversal: Enter on color change with volume confirmation Breakout: Enter when price crosses filter with momentum Exit Strategies: Exit long when line turns from cyan to pink Exit short when line turns from pink to cyan Use filter as trailing stop in strong trends ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ✨ ADVANTAGES OVER TRADITIONAL INDICATORS Vs. Moving Averages: Significantly less lag while maintaining smoothness Adaptive to market conditions Better noise filtering Vs. Standard Filters: Dual-filter approach provides optimal estimation Mathematical foundation from signal processing Self-adjusting parameters Vs. Other Trend Indicators: Cleaner signals with fewer whipsaws Works across all timeframes No repainting or lookahead bias ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎓 MATHEMATICAL BACKGROUND The Laguerre filter was developed by John Ehlers, applying Laguerre polynomials (used in quantum mechanics) to financial markets. These polynomials provide an elegant solution to the lag-smoothness tradeoff that plagues traditional moving averages. The Kalman filter, developed by Rudolf Kalman in 1960, is used in everything from GPS systems to spacecraft navigation. It provides the mathematically optimal estimate of a system's state given noisy measurements. By combining these two approaches, this indicator achieves what neither can alone: a smooth, responsive trend line that adapts to market conditions while filtering out noise. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 TIPS FOR BEST RESULTS Confirm with Volume: Strong trends should have increasing volume Multiple Timeframes: Use higher timeframe for trend, lower for entry Combine with Momentum: RSI or MACD can confirm filter signals Market Conditions: Adjust noise parameter based on market volatility Backtesting: Always test settings on your specific instrument ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚠️ IMPORTANT NOTES No indicator is perfect - always use proper risk management Best suited for trending markets May produce false signals in choppy/ranging conditions Not financial advice - for educational purposes only ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🚀 CONCLUSION The Laguerre-Kalman Adaptive Filter represents a significant advancement in technical analysis, bringing institutional-grade mathematical techniques to retail traders. Its unique combination of polynomial filtering and optimal estimation provides a clean, reliable trend-following tool that adapts to changing market conditions. Whether you're scalping on the 1-minute chart or position trading on the daily, this indicator provides clear, actionable signals with minimal false positives. "In the world of technical analysis, the edge comes from using better mathematics. This indicator delivers that edge." ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Developed by AlphaNatt | Professional Quantitative Trading Tools Version: 1.0 Last Updated: 2025 Pine Script: v6 License: Open Source Not financial advice. Always DYOR
อินดิเคเตอร์ Pine Script®
โดย AlphaNatt
3
CAP - KC/AC 2.20462 Converter// ─────────────────────────────────────────────────────────────────────────────── // Purpose: Conversion Indicator for ICE “C” (KC) and “C Metric” (AC) Contracts // // Background: // - The Intercontinental Exchange (ICE) is phasing out the legacy Coffee “C” contract (symbol: KC), // which has been quoted in U.S. cents per pound, and replacing it with the new Coffee “C Metric” contract (symbol: AC), // quoted in U.S. dollars per metric ton :contentReference {index=0}. // - The final KC futures expire in March 2028; AC contracts begin trading in September 2025 and use modern specifications // including pricing per metric ton and flexible bulk delivery formats :contentReference {index=1}. // // Why this script matters: // - Traders are accustomed to the KC pricing format (¢/lb); the AC contract’s USD/MT may create confusion. // - This indicator visually converts the current chart price—whether from KC or AC contracts—directly into its equivalent unit, // helping traders quickly assess parity and compare trends across both contract types. // - It simplifies head-to-head comparison during this transition period, improving clarity on chart price behavior. // // Usage instructions: // - If the symbol starts with "KC", the script divides the price by 2.20462 to convert from ¢/lb to approximate ¢/kg. // - If the symbol starts with "AC", the script multiplies the price by 2.20462 to reverse the conversion. // - The results (converted values) are displayed in a table for immediate visual clarity. // ───────────────────────────────────────────────────────────────────────────────
อินดิเคเตอร์ Pine Script®
โดย calinpascual
1
BBMA Enhanced Pro - Multi-Timeframe Band Breakout StrategyShort Title : BBMA Pro Overview The BBMA Enhanced Pro is a professional-grade trading indicator that builds on the Bollinger Bands Moving Average (BBMA) strategy, pioneered by Omar Ali , a Malaysian forex trader and educator. Combining Bollinger Bands with Weighted Moving Averages (WMA) , this indicator identifies high-probability breakout and reversal opportunities across multiple timeframes. With advanced features like multi-timeframe Extreme signal detection, eight professional visual themes, and a dual-mode dashboard, it’s designed for traders seeking precision in trending and consolidating markets. Optimized for dark chart backgrounds, it’s ideal for forex, stocks, and crypto trading. History The BBMA strategy was developed by Omar Ali (BBMA Oma Ally) in the early 2010s, gaining popularity in the forex trading community, particularly in Southeast Asia. Building on John Bollinger’s Bollinger Bands, Omar Ali integrated Weighted Moving Averages and a multi-timeframe approach to create a structured system for identifying reversals, breakouts, and extreme conditions. The BBMA Enhanced Pro refines this framework with modern features like real-time dashboards and customizable visualizations, making it accessible to both novice and experienced traders. Key Features Multi-Timeframe Extreme Signals : Detects Extreme signals (overbought/oversold conditions) on both current and higher timeframes simultaneously, a rare feature that enhances signal reliability through trend alignment. Professional Visual Themes : Eight distinct themes (e.g., Neon Contrast, Fire Gradient) optimized for dark backgrounds. Dual-Mode Dashboard : Choose between Full Professional (detailed metrics) or Simplified Trader (essential info with custom notes). Bollinger Band Squeeze Detection : Identifies low volatility periods (narrow bands) signaling potential sideways markets or breakouts. Confirmation Labels : Displays labels when current timeframe signals align with recent higher timeframe signals, highlighting potential consolidations or squeezes. Timeframe Validation : Prevents selecting the same timeframe for current and higher timeframe analysis. Customizable Visualization : Toggle signal dots, EMA 50, and confirmation labels for a clean chart experience. How It Works The BBMA Enhanced Pro combines Bollinger Bands (20-period SMA, ±2 standard deviations) with WMA (5 and 10 periods) to generate trade signals: Buy Signal : WMA 5 Low crosses above the lower Bollinger Band, indicating a recovery from an oversold condition (Extreme buy). Sell Signal : WMA 5 High crosses below the upper Bollinger Band, signaling a rejection from an overbought condition (Extreme sell). Extreme Signals : Occur when prices or WMAs move significantly beyond the Bollinger Bands (±2σ), indicating statistically rare overextensions. These often coincide with Bollinger Band Squeezes (narrow bands, low standard deviation), signaling potential sideways markets or impending breakouts. Multi-Timeframe Confirmation : The indicator’s unique strength is its ability to detect Extreme signals on both the current and higher timeframe (HTF) within the same chart. When the HTF generates an Extreme signal (e.g., buy), and the current timeframe follows with an identical signal, it suggests the lower timeframe is aligning with the HTF’s trend, increasing reliability. Labels appear only when this alignment occurs within a user-defined lookback period (default: 50 bars), highlighting periods of band contraction across timeframes. Bollinger Band Squeeze : Narrow bands (low standard deviation) indicate reduced volatility, often preceding consolidation or breakouts. The indicator’s dashboard tracks band width, helping traders anticipate these phases. Why Multi-Timeframe Extremes Matter The BBMA Enhanced Pro’s multi-timeframe approach is rare and powerful. When the higher timeframe shows an Extreme signal followed by a similar signal on the current timeframe, it suggests the market is following the HTF’s trend or entering a consolidation phase. For example: HTF Sideways First : If the HTF Bollinger Bands are shrinking (low volatility, low standard deviation), it signals a potential sideways market. Waiting for the current timeframe to show a similar Extreme signal confirms this consolidation, reducing the risk of false breakouts. Risk Management : By requiring HTF confirmation, the indicator encourages traders to lower risk during uncertain periods, waiting for both timeframes to align in a low-volatility state before acting. Usage Instructions Select Display Mode : Current TF Only : Shows Bollinger Bands and WMAs on the chart’s timeframe. Higher TF Only : Displays HTF bands and WMAs. Both Timeframes : Combines both for comprehensive analysis. Choose Higher Timeframe : Select from 1min to 1D (e.g., 15min, 1hr). Ensure it differs from the current timeframe to avoid validation errors. Enable Signal Dots : Visualize buy/sell Extreme signals as dots, sourced from current, HTF, or both timeframes. Toggle Confirmation Labels : Display labels when current timeframe Extremes align with recent HTF Extremes, signaling potential squeezes or consolidations. Customize Dashboard : Full Professional Mode : View metrics like BB width, WMA trend, and last signal. Simplified Trader Mode : Focus on essential info with custom trader notes. Select Visual Theme : Choose from eight themes (e.g., Ice Crystal, Royal Purple) for optimal chart clarity. Trading Example Setup : 5min chart, HTF set to 1hr, signal dots and confirmation labels enabled. Buy Scenario : On the 5min chart, WMA 5 Low crosses above the lower Bollinger Band (Extreme buy), confirmed by a recent 1hr Extreme buy signal within 50 bars. The dashboard shows narrow bands (squeeze), and a green label appears. Action : Enter a long position, targeting the middle band, with a stop-loss below the recent low. The HTF confirmation suggests a strong trend or consolidation phase. Sell Scenario : WMA 5 High crosses below the upper Bollinger Band on the 5min chart, confirmed by a recent 1hr Extreme sell signal. The dashboard indicates a squeeze, and a red label appears. Action : Enter a short position, targeting the middle band, with a stop-loss above the recent high. The aligned signals suggest a potential reversal or sideways market. Customization Options BBMA Display Mode : Current TF Only, Higher TF Only, or Both Timeframes. Higher Timeframe : 1min to 1D. Visual Theme : Eight professional themes (e.g., Neon Contrast, Forest Glow). Line Style : Smooth or Step Line for HTF plots. Signal Dots : Enable/disable, select timeframe source (Current, Higher, or Both). Confirmation Labels : Toggle and set lookback window (1-100 bars). Dashboard : Enable/disable, choose mode (Full/Simplified), and set position (Top Right, Bottom Left, etc.). Notes Extreme Signals and Squeezes : Extreme signals often occur during Bollinger Band contraction (low standard deviation), signaling potential sideways markets or breakouts. Use HTF confirmation to filter false signals. Risk Management : If the HTF shows a squeeze (narrow bands), wait for the current timeframe to confirm with an Extreme signal to reduce risk in choppy markets. Limitations : Avoid trading Extremes in highly volatile markets without additional confirmation (e.g., volume, RSI). Author Enhanced Professional Edition, inspired by Omar Ali’s BBMA strategy Version : 6.0 Pro - Simplified Last Updated : September 2025 License : Mozilla Public License 2.0 We’d love to hear your feedback! Share your thoughts or questions in the comments below.
อินดิเคเตอร์ Pine Script®
โดย genesismatrixcg
Major & Modern Wars TimelineDescription: This indicator overlays vertical lines and labels on your chart to mark the start and end dates of major global wars and modern conflicts. Features: Displays start (red line + label) and end (green line + label) for each war. Covers 20th century wars (World War I, World War II, Korean War, Vietnam War, Gulf War, Afghanistan, Iraq). Includes modern conflicts: Syrian Civil War, Ukraine War, and Israel–Hamas War. For ongoing conflicts, the end date is set to 2025 for timeline visualization. Customizable: label position (above/below bar), line width. Works on any chart timeframe, overlaying events on financial data. Use case: Useful for historical market analysis (e.g., gold, oil, S&P 500), helping traders and researchers see how wars and conflicts align with market movements.
อินดิเคเตอร์ Pine Script®
โดย dragosmarzac
Major & Modern Wars TimelineDescription: This indicator overlays vertical lines and labels on your chart to mark the start and end dates of major global wars and modern conflicts. Features: Displays start (red line + label) and end (green line + label) for each war. Covers 20th century wars (World War I, World War II, Korean War, Vietnam War, Gulf War, Afghanistan, Iraq). Includes modern conflicts: Syrian Civil War, Ukraine War, and Israel–Hamas War. For ongoing conflicts, the end date is set to 2025 for timeline visualization. Customizable: label position (above/below bar), line width. Works on any chart timeframe, overlaying events on financial data. Use case: Useful for historical market analysis (e.g., gold, oil, S&P 500), helping traders and researchers see how wars and conflicts align with market movements.
อินดิเคเตอร์ Pine Script®
โดย dragosmarzac
Kitti-Playbook ATR Study R0 Date : Aug 22 2025 Kitti-Playbook ATR Study R0 This is used to study the operation of the ATR Trailing Stop on the Long side, starting from the calculation of True Range. 1) Studying True Range Calculation 1.1) Specify the Bar graph you want to analyze for True Range.
Enable "Show Selected Price Bar" to locate the desired bar. 1.2) Enable/disable "Display True Range" in the Settings.
True Range is calculated as:
TR = Max (|H - L|, |H - Cp|, |Cp - L|) • Show True Range:
Each color on the bar represents the maximum range value selected: ◦ |H - L| = Green ◦ |H - Cp| = Yellow ◦ |Cp - L| = Blue • Show True Range on Selected Price Bar:
An arrow points to the range, and its color represents the maximum value chosen: ◦ |H - L| = Green ◦ |H - Cp| = Yellow ◦ |Cp - L| = Blue • Show True Range Information Table:
Displays the actual values of |H - L|, |H - Cp|, and |Cp - L| from the selected bar. 2) Studying Average True Range (ATR) 2.1) Set the ATR Length in Settings.
Default value: ATR Length = 14 2.2) Enable/disable "Display Average True Range (RMA)" in Settings: • Show ATR • Show ATR Length from Selected Price Bar
(An arrow will point backward equal to the ATR Length) 3) Studying ATR Trailing 3.1) Set the ATR Multiplier in Settings.
Default value: ATR Multiply = 3 3.2) Enable/disable "Display ATR Trailing" in Settings: • Show High Line • Show ATR Bands • Show ATR Trailing 4) Studying ATR Trailing Exit (Occurs when the Close price crosses below the ATR Trailing line) Enable/disable "Display ATR Trailing" in Settings: • Show Close Line • Show Exit Points
(Exit points are marked by an orange diamond symbol above the price bar)
อินดิเคเตอร์ Pine Script®
โดย Kittimasak_S
Prime NumbersPrime Numbers highlights prime numbers (no surprise there 😅), tokens and the recent "active" feature in "input". 🔸 CONCEPTS 🔹 What are Prime Numbers? A prime number (or a prime) is a natural number greater than 1 that is not a product of two smaller natural numbers. Wikipedia: Prime number 🔹 Prime Factorization The fundamental theorem of arithmetic states that every integer larger than 1 can be written as a product of one or more primes. More strongly, this product is unique in the sense that any two prime factorizations of the same number will have the same number of copies of the same primes, although their ordering may differ. So, although there are many different ways of finding a factorization using an integer factorization algorithm, they all must produce the same result. Primes can thus be considered the "basic building blocks" of the natural numbers. Wikipedia: Fundamental theorem of arithmetic Math Is Fun: Prime Factorization We divide a given number by Prime Numbers until only Primes remain. Example: 24 / 2 = 12 | 24 / 3 = 8 12 / 3 = 4 | 8 / 2 = 4 4 / 2 = 2 | 4 / 2 = 2 | 24 = 2 x 3 x 2 | 24 = 3 x 2 x 2 or | or 24 = 2² x 3 | 24 = 2² x 3 In other words, every natural/integer number above 1 has a unique representation as a product of prime numbers, no matter how the number is divided. Only the order can change, but the factors (the basic elements) are always the same. 🔸 USAGE The Prime Numbers publication contains two use cases: Prime Factorization: performed on "close" prices, or a manual chosen number. List Prime Numbers: shows a list of Prime Numbers. The other two options are discussed in the DETAILS chapter: Prime Factorization Without Arrays Find Prime Numbers 🔹 Prime Factorization Users can choose to perform Prime Factorization on close prices or a manually given number. ❗️ Note that this option only applies to close prices above 1, which are also rounded since Prime Factorization can only be performed on natural (integer) numbers above 1. In the image below, the left example shows Prime Factorization performed on each close price for the latest 50 bars (which is set with "Run script only on 'Last x Bars'" -> 50). The right example shows Prime Factorization performed on a manually given number, in this case "1,340,011". This is done only on the last bar. When the "Source" option "close price" is chosen, one can toggle "Also current price", where both the historical and the latest current price are factored. If disabled, only historical prices are factored. Note that, depending on the chosen options, only applicable settings are available, due to a recent feature, namely the parameter "active" in settings. Setting the "Source" option to "Manual - Limited" will factorize any given number between 1 and 1,340,011, the latter being the highest value in the available arrays with primes. Setting to "Manual - Not Limited" enables the user to enter a higher number. If all factors of the manual entered number are in the 1 - 1,340,011 range, these factors will be shown; however, if a factor is higher than 1,340,011, the calculation will stop, after which a warning is shown: The calculated factors are displayed as a label where identical factors are simplified with an exponent notation in superscript. For example 2 x 2 x 2 x 5 x 7 x 7 will be noted as 2³ x 5 x 7² 🔹 List Prime Numbers The "List Prime Numbers" option enables users to enter a number, where the first found Prime Number is shown, together with the next x Prime Numbers ("Amount", max. 200) The highest shown Prime Number is 1,340,011. One can set the number of shown columns to customize the displayed numbers ("Max. columns", max. 20). 🔸 DETAILS The Prime Numbers publication consists out of 4 parts: Prime Factorization Without Arrays Prime Factorization List Prime Numbers Find Prime Numbers The usage of "Prime Factorization" and "List Prime Numbers" is explained above. 🔹 Prime Factorization Without Arrays This option is only there to highlight a hurdle while performing Prime Factorization. The basic method of Prime Factorization is to divide the base number by 2, 3, ... until the result is an integer number. Continue until the remaining number and its factors are all primes. The division should be done by primes, but then you need to know which one is a prime. In practice, one performs a loop from 2 to the base number. Example: Base_number = input.int(24) arr = array.new() n = Base_number go = true while go for i = 2 to n if n % i == 0 if n / i == 1 go := false arr.push(i) label.new(bar_index, high, str.tostring(arr)) else arr.push(i) n /= i break Small numbers won't cause issues, but when performing the calculations on, for example, 124,001 and a timeframe of, for example, 1 hour, the script will struggle and finally give a runtime error. How to solve this? If we use an array with only primes, we need fewer calculations since if we divide by a non-prime number, we have to divide further until all factors are primes. I've filled arrays with prime numbers and made libraries of them. (see chapter "Find Prime Numbers" to know how these primes were found). 🔹 Tokens A hurdle was to fill the libraries with as many prime numbers as possible. Initially, the maximum token limit of a library was 80K. Very recently, that limit was lifted to 100K. Kudos to the TradingView developers! What are tokens? Tokens are the smallest elements of a program that are meaningful to the compiler. They are also known as the fundamental building blocks of the program. I have included a code block below the publication code (// - - - Educational (2) - - - ) which, if copied and made to a library, will contain exactly 100K tokens. Adding more exported functions will throw a "too many tokens" error when saving the library. Subtracting 100K from the shown amount of tokens gives you the amount of used tokens for that particular function. In that way, one can experiment with the impact of each code addition in terms of tokens. For example adding the following code in the library: export a() => a = array.from(1) will result in a 100,041 tokens error, in other words (100,041 - 100,000) that functions contains 41 tokens. Some more examples, some are straightforward, others are not ) // adding these lines in one of the arrays results in x tokens , 1 // 2 tokens , 111, 111, 111 // 12 tokens , 1111 // 5 tokens , 111111111 // 10 tokens , 1111111111111111111 // 20 tokens , 1234567890123456789 // 20 tokens , 1111111111111111111 + 1 // 20 tokens , 1111111111111111111 + 8 // 20 tokens , 1111111111111111111 + 9 // 20 tokens , 1111111111111111111 * 1 // 20 tokens , 1111111111111111111 * 9 // 21 tokens , 9999999999999999999 // 21 tokens , 1111111111111111111 * 10 // 21 tokens , 11111111111111111110 // 21 tokens //adding these functions to the library results in x tokens export f() => 1 // 4 tokens export f() => v = 1 // 4 tokens export f() => var v = 1 // 4 tokens export f() => var v = 1, v // 4 tokens //adding these functions to the library results in x tokens export a() => const arraya = array.from(1) // 42 tokens export a() => arraya = array.from(1) // 42 tokens export a() => a = array.from(1) // 41 tokens export a() => array.from(1) // 32 tokens export a() => a = array.new() // 44 tokens export a() => a = array.new(), a.push(1) // 56 tokens What if we could lower the amount of tokens, so we can export more Prime Numbers? Look at this example: 829111, 829121, 829123, 829151, 829159, 829177, 829187, 829193 Eight numbers contain the same number 8291. If we make a function that removes recurrent values, we get fewer tokens! 829111, 829121, 829123, 829151, 829159, 829177, 829187, 829193 //is transformed to: 829111, 21, 23, 51, 59, 77, 87, 93 The code block below the publication code (// - - - Educational (1) - - - ) shows how these values were reduced. With each step of 100, only the first Prime Number is shown fully. This function could be enhanced even more to reduce recurrent thousands, tens of thousands, etc. Using this technique enables us to export more Prime Numbers. The number of necessary libraries was reduced to half or less. The reduced Prime Numbers are restored using the restoreValues() function, found in the library fikira/Primes_4. 🔹 Find Prime Numbers This function is merely added to show how I filled arrays with Prime Numbers, which were, in turn, added to libraries (after reduction of recurrent values). To know whether a number is a Prime Number, we divide the given number by values of the Primes array (Primes 2 -> max. 1,340,011). Once the division results in an integer, where the divisor is smaller than the dividend, the calculation stops since the given number is not a Prime. When we perform these calculations in a loop, we can check whether a series of numbers is a Prime or not. Each time a number is proven not to be a Prime, the loop starts again with a higher number. Once all Primes of the array are used without the result being an integer, we have found a new Prime Number, which is added to the array. Doing such calculations on one bar will result in a runtime error. To solve this, the findPrimeNumbers() function remembers the index of the array. Once a limit has been reached on 1 bar (for example, the number of iterations), calculations will stop on that bar and restart on the next bar. This spreads the workload over several bars, making it possible to continue these calculations without a runtime error. The result is placed in log.info() , which can be copied and pasted into a hardcoded array of Prime Number values. These settings adjust the amount of workload per bar: Max Size: maximum size of Primes array. Max Bars Runtime: maximum amount of bars where the function is called. Max Numbers To Process Per Bar: maximum numbers to check on each bar, whether they are Prime Numbers. Max Iterations Per Bar: maximum loop calculations per bar. 🔹 The End ❗️ The code and description is written without the help of an LLM, I've only used Grammarly to improve my description (without AI :) )
อินดิเคเตอร์ Pine Script®
โดย fikira
13
Intraday Volume Pulse GSK-VIZAG-AP-INDIAIntraday Volume Pulse Indicator Overview This indicator is designed to track and visualize intraday volume dynamics during a user-defined trading session. It calculates and displays key volume metrics such as buy volume, sell volume, cumulative delta (difference between buy and sell volumes), and total volume. The data is presented in a customizable table overlay on the chart, making it easy to monitor volume pulses throughout the session. This can help traders identify buying or selling pressure in real-time, particularly useful for intraday strategies. The indicator resets its calculations at the start of each new day and only accumulates volume data from the specified session start time onward. It uses simple logic to classify volume as buy or sell based on candle direction: Buy Volume: Assigned to green (up) candles or half of neutral (doji) candles. Sell Volume: Assigned to red (down) candles or half of neutral (doji) candles. All calculations are approximate and based on available volume data from the chart. This script does not incorporate external data sources, order flow, or tick-level information—it's purely derived from standard OHLCV (Open, High, Low, Close, Volume) bars. Key Features Session Customization: Define the start time of your trading session (e.g., market open) and select from common timezones like Asia/Kolkata, America/New_York, etc. Volume Metrics: Buy Volume: Total volume attributed to bullish activity. Sell Volume: Total volume attributed to bearish activity. Cumulative Delta: Net difference (Buy - Sell), highlighting overall market bias. Total Volume: Sum of all volume during the session. Formatted Display: Volumes are formatted for readability (e.g., in thousands "K", lakhs "L", or crores "Cr" for large numbers). Color-Coded Table: Uses a patriotic color scheme inspired by general themes (Saffron, White, Green) with dynamic backgrounds based on positive/negative values for quick visual interpretation. Table Options: Toggle visibility and position (top-right, top-left, etc.) for a clean chart layout. How to Use Add to Chart: Apply this indicator to any symbol's chart (works best on intraday timeframes like 1-min, 5-min, or 15-min). Configure Inputs: Session Start Hour/Minute: Set to your market's open time (default: 9:15 for Indian markets). Timezone: Choose the appropriate timezone to align with your trading hours. Show Table: Enable/disable the metrics table. Table Position: Place the table where it doesn't obstruct your view. Interpret the Table: Monitor for spikes in buy/sell volume or shifts in cumulative delta. Positive delta (green) suggests buying pressure; negative (red) suggests selling. Use alongside price action or other indicators for confirmation—e.g., high total volume with positive delta could indicate bullish momentum. Limitations: Volume classification is heuristic and not based on actual order flow (e.g., it splits doji volume evenly). Data accumulation starts from the session time and resets daily; historical backtesting may be limited by the max_bars_back=500 setting. This is for educational and visualization purposes only—do not use as sole basis for trading decisions. Calculation Details Session Filter: Uses timestamp() to define the session start and filters bars with time >= sessionStart. New Day Detection: Resets volumes on daily changes via ta.change(time("D")). Volume Assignment: Buy: Full volume if close > open; half if close == open. Sell: Full volume if close < open; half if close == open. Cumulative Metrics: Accumulated only during the session. Formatting: Custom function f_format() scales large numbers for brevity. Disclaimer This script is for educational and informational purposes only. It does not provide financial advice or signals to buy/sell any security. Always perform your own analysis and consult a qualified financial professional before making trading decisions. © 2025 GSK-VIZAG-AP-INDIA
อินดิเคเตอร์ Pine Script®
โดย prowelltraders
Awesome Indicator# Moving Average Ribbon with ADR% - Complete Trading Indicator ## Overview The **Moving Average Ribbon with ADR%** is a comprehensive technical analysis indicator that combines multiple analytical tools to provide traders with a complete picture of price trends, volatility, relative performance, and position sizing guidance. This multi-faceted indicator is designed for both swing and positional traders looking for data-driven entry and exit signals. ## Key Components ### 1. Moving Average Ribbon System - **4 Customizable Moving Averages** with default periods: 13, 21, 55, and 189 - **Multiple MA Types**: SMA, EMA, SMMA (RMA), WMA, VWMA - **Color-coded visualization** for easy trend identification - **Flexible configuration** allowing users to modify periods, types, and colors ### 2. Average Daily Range Percentage (ADR%) - Calculates the average daily volatility as a percentage - Uses a 20-period simple moving average of (High/Low - 1) * 100 - Helps traders understand the stock's typical daily movement range - Essential for position sizing and stop-loss placement ### 3. Volume Analysis (Up/Down Ratio) - Analyzes volume distribution over the last 55 periods - Calculates the ratio of volume on up days vs down days - Provides insight into buying vs selling pressure - Values > 1 indicate more buying volume, < 1 indicate more selling volume ### 4. Absolute Relative Strength (ARS) - **Dual timeframe analysis** with customizable reference points - **High ARS**: Performance relative to benchmark from a high reference point (default: Sep 27, 2024) - **Low ARS**: Performance relative to benchmark from a low reference point (default: Apr 7, 2025) - Uses NSE:NIFTY as default comparison symbol - Color-coded display: Green for outperformance, Red for underperformance ### 5. Relative Performance Table - **5 timeframes**: 1 Week, 1 Month, 3 Months, 6 Months, 1 Year - Shows stock performance **relative to benchmark index** - Formula: (Stock Return - Index Return) for each period - **Color coding**: - Lime: >5% outperformance - Yellow: -5% to +5% relative performance - Red: <-5% underperformance ### 6. Dynamic Position Allocation System - **6-factor scoring system** based on price vs EMAs (21, 55, 189) - Evaluates: - Price above/below each EMA - EMA alignment (21>55, 55>189, 21>189) - **Allocation recommendations**: - 100% allocation: Score = 6 (all bullish signals) - 75% allocation: Score = 4 - 50% allocation: Score = 2 - 25% allocation: Score = 0 - 0% allocation: Score = -2, -4, -6 (bearish signals) ## Display Tables ### Performance Table (Top Right) Shows relative performance vs benchmark across multiple timeframes with intuitive color coding for quick assessment. ### Metrics Table (Bottom Right) Displays key statistics: - **ADR%**: Average Daily Range percentage - **U/D**: Up/Down volume ratio - **Allocation%**: Recommended position size - **High ARS%**: Relative strength from high reference - **Low ARS%**: Relative strength from low reference ## How to Use This Indicator ### For Trend Analysis 1. **Moving Average Ribbon**: Look for price above ascending MAs for bullish trends 2. **MA Alignment**: Bullish when shorter MAs are above longer MAs 3. **Color coordination**: Use consistent color scheme for quick visual analysis ### For Entry/Exit Timing 1. **Performance Table**: Enter when showing consistent outperformance across timeframes 2. **Volume Analysis**: Confirm entries with U/D ratio > 1.5 for strong buying 3. **ARS Values**: Look for positive ARS readings for relative strength confirmation ### For Position Sizing 1. **Allocation System**: Use the recommended allocation percentage 2. **ADR% Consideration**: Adjust position size based on volatility 3. **Risk Management**: Lower allocation in high ADR% stocks ### For Risk Management 1. **ADR% for Stop Loss**: Set stops at 1-2x ADR% below entry 2. **Relative Performance**: Reduce positions when consistently underperforming 3. **Volume Confirmation**: Be cautious when U/D ratio deteriorates ## Best Practices ### Timeframe Recommendations - **Intraday**: Use lower MA periods (5, 13, 21, 55) - **Swing Trading**: Default settings work well (13, 21, 55, 189) - **Position Trading**: Consider higher periods (21, 50, 100, 200) ### Market Conditions - **Trending Markets**: Focus on MA alignment and relative performance - **Sideways Markets**: Rely more on ADR% for range trading - **Volatile Markets**: Reduce allocation percentage regardless of signals ### Customization Tips 1. Adjust reference dates for ARS calculation based on significant market events 2. Change comparison symbol to sector-specific indices for better relative analysis 3. Modify MA periods based on your trading style and market characteristics ## Technical Specifications - **Version**: Pine Script v6 - **Overlay**: Yes (plots on price chart) - **Real-time Updates**: Yes - **Data Requirements**: Minimum 252 bars for complete calculations - **Compatible Timeframes**: All standard timeframes ## Limitations - Performance calculations require sufficient historical data - ARS calculations depend on selected reference dates - Volume analysis may be less reliable in low-volume stocks - Relative performance is only as good as the chosen benchmark This indicator is designed to provide a comprehensive analysis framework rather than simple buy/sell signals. It's recommended to use this in conjunction with your overall trading strategy and risk management rules.
อินดิเคเตอร์ Pine Script®
โดย ShRaJaL
Supertrend EMA Vol Strategy V5### Supertrend EMA Strategy V5 **Overview** This is a trend-following strategy designed for cryptocurrency markets like BTC/USD on daily timeframes, combining the Supertrend indicator for dynamic trailing stops with an EMA filter for trend confirmation. It aims to capture strong uptrends while avoiding counter-trend trades, with optional volume filtering for high-conviction entries and ATR-based stop-loss to manage risk. Ideal for long-only setups in bullish assets, it visually highlights trends with green/red bands and fills for easy interpretation. Backtested on BTC from 2024-2025, it shows potential for outperforming buy-and-hold in trending markets, but always use with proper risk management—past performance isn't indicative of future results. **Key Features** - **Supertrend Core**: Uses ATR to plot adaptive uptrend (green) and downtrend (red) lines, flipping on closes beyond prior bands for buy/sell signals. - **EMA Trend Filter**: Entries require price above the EMA (default 21-period) for longs, ensuring alignment with the broader trend. - **Volume Confirmation**: Optional filter only allows entries when volume exceeds its EMA (default 20-period), reducing false signals in low-activity periods. - **Risk Controls**: Built-in ATR-multiplier stop-loss (default 2x) to cap losses; exits on Supertrend flips for trailing profits. - **Visuals**: Green/red lines and highlighter fills for up/down trends, plus buy/sell labels and circles for signals. - **Customizable Inputs**: Tweak ATR period (default 10), multiplier (default 3), EMA length, start date, long/short toggles, SL, and volume filter. - **Alerts**: Built-in for buy/sell and direction changes. **How to Use** 1. Add to your TradingView chart (e.g., BTC/USD 1D). 2. Adjust inputs: Start with defaults for trend-following; increase multiplier for fewer trades/higher win rate. Enable volume filter for volatile assets. 3. Monitor signals: Green "Buy" for long entries (if close > EMA and conditions met); red "Sell" for exits. 4. Backtest in Strategy Tester: Focus on equity curve, win rate (~50-60% in tests), and drawdown (<15% with SL). 5. Live Trading: Use small position sizes (1-2% risk per trade); combine with your analysis. Shorts disabled by default for bull-biased markets.
กลยุทธ์ Pine Script®
โดย d_jaeger
2
Ethereum Logarithmic Regression BandsOverview This indicator displays logarithmic regression bands for Ethereum. Logarithmic regression is a statistical method used to model data where growth slows down over time. I initially created these bands in 2021 using a spreadsheet, and later coded them in TradingView in 2022. Over time, the bands proved effective at capturing bull market peaks and bear market lows. In 2025, I decided to share this indicator because I believe these logarithmic regression bands offer the best fit for the Ethereum chart. How It Works The logarithmic regression lines are fitted to the Ethereum (ETHUSD) chart using two key factors: the 'a' factor (slope) and the 'b' factor (intercept). The formula for logarithmic regression is 10^((a * ln) - b). How to Use the Logarithmic Regression Bands 1. Lower Band: The lower (blue) band forms a potential support area for Ethereum’s price. Historically, Ethereum has found its lows within this band during past market cycles. When the price is within the lower band, it suggests that Ethereum is undervalued. 2. Upper Band: The upper (red) band forms a potential resistance area for Ethereum’s price. The logarithmic band is fitted to the past two market cycle peaks; therefore, there is not enough historical data to be sure it will reach the upper band again. However, the chance is certainly there! If the price is within the upper band, it indicates that Ethereum is overvalued and that a potential price correction may be imminent.
อินดิเคเตอร์ Pine Script®
โดย CryptoRiskAlert
VWAP CALENDARThe VWAP CALENDAR indicator plots up to 20 anchored Volume-Weighted Average Price (VWAP) lines on your chart, each starting from a user-defined date and time (e.g., April 20, 2024). Designed for simplicity, it helps traders visualize VWAPs for key events or dates, with customizable labels and colors. The indicator is optimized for crypto markets (e.g., BTC/USD) but works with any symbol providing volume data. Features: Multiple VWAPs: Configure up to 20 independent VWAPs, each with a custom anchor date and time. Dynamic Labels: Labels update in real-time, aligning precisely with each VWAP line’s price level, positioned to the right of the chart for clarity. Customizable Settings: Adjust label text (e.g., “Event A”), line colors, line widths (1–5 pixels), text colors, and text sizes (8–40 points, default 22). Bubble or No-Background Labels: Choose between bubble-style labels (with colored backgrounds) or plain text labels without backgrounds. Timeframe Support: Accurate on daily, 4-hour, 1-hour, and 30-minute charts for anchors within ~1.5 years (e.g., April 20, 2024, from August 2025). Limitations: VWAP accuracy for anchors like April 20, 2024 (~477 days back) is reliable on 1-hour and larger timeframes. Below 30-minute (e.g., 15-minute, 24-minute), VWAPs may start later or be unavailable due to TradingView’s 5,000-bar historical data limit. For distant anchors, use 4-hour or daily charts to ensure accuracy. Requires sufficient chart history (e.g., premium account or deep exchange data) for older anchors on 1-hour or 30-minute charts. Usage Notes: Set anchor dates via the indicator settings (e.g., “2024-04-20 00:00”). Enable/disable individual VWAPs as needed. Zoom out to load maximum chart history for best results, especially on 1-hour or 30-minute timeframes. Ideal for crypto symbols with continuous trading data, but verify data availability for other markets. Disclaimer: This is a free indicator provided as-is
อินดิเคเตอร์ Pine Script®
โดย fragilety
VWAP CALENDARThe VWAP CALENDAR indicator plots up to 20 anchored Volume-Weighted Average Price (VWAP) lines on your chart, each starting from a user-defined date and time (e.g., April 20, 2024). Designed for simplicity, it helps traders visualize VWAPs for key events or dates, with customizable labels and colors. The indicator is optimized for crypto markets (e.g., BTC/USD) but works with any symbol providing volume data. Features: Multiple VWAPs: Configure up to 20 independent VWAPs, each with a custom anchor date and time. Dynamic Labels: Labels update in real-time, aligning precisely with each VWAP line’s price level, positioned to the right of the chart for clarity. Customizable Settings: Adjust label text (e.g., “Event A”), line colors, line widths (1–5 pixels), text colors, and text sizes (8–40 points, default 22). Bubble or No-Background Labels: Choose between bubble-style labels (with colored backgrounds) or plain text labels without backgrounds. Timeframe Support: Accurate on daily, 4-hour, 1-hour, and 30-minute charts for anchors within ~1.5 years (e.g., April 20, 2024, from August 2025). Limitations: VWAP accuracy for anchors like April 20, 2024 (~477 days back) is reliable on 1-hour and larger timeframes. Below 30-minute (e.g., 15-minute, 24-minute), VWAPs may start later or be unavailable due to TradingView’s 5,000-bar historical data limit. For distant anchors, use 4-hour or daily charts to ensure accuracy. Requires sufficient chart history (e.g., premium account or deep exchange data) for older anchors on 1-hour or 30-minute charts. Usage Notes: Set anchor dates via the indicator settings (e.g., “2024-04-20 00:00”). Enable/disable individual VWAPs as needed. Zoom out to load maximum chart history for best results, especially on 1-hour or 30-minute timeframes. Ideal for crypto symbols with continuous trading data, but verify data availability for other markets. Disclaimer: This is a free indicator provided as-is.
อินดิเคเตอร์ Pine Script®
โดย fragilety