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
Cerca negli script per "几内亚黄金2025价目表"
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
US Elections Democrate-Republicain (1920-2025)This script shows the different U.S. presidents and indicates whether each was Democratic or Republican. It allows users to analyze the market based on the president in office.
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.
// ───────────────────────────────────────────────────────────────────────────────
Futubull VWAPTo apply Futubull’s VWAP (Volume Weighted Average Price) indicator to TradingView, the key is to understand Futubull’s VWAP calculation logic and features, then replicate them using TradingView’s Pine Script language. Below are detailed steps and methods, incorporating the provided context and prior discussions, to help you create a custom VWAP indicator in TradingView that mirrors Futubull’s functionality. The script will be tailored for day trading CIEN (Ciena Corporation) on September 4, 2025, during pre-market (Hong Kong time 11:25 PM, equivalent to US Eastern Time 11:25 AM), leveraging its earnings-driven breakout ($115.50, +21.81%).
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.
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.
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.
Sorry Cryptoface Market Cypher B//@version=5
indicator("Sorry Cryptoface Market Cypher B", shorttitle="SorryCF B", overlay=false)
// 🙏 Respect to Cryptoface
// Market Cipher is the brainchild of Cryptoface, who popularized the
// combination of WaveTrend, Money Flow, RSI, and divergence signals into a
// single package that has helped thousands of traders visualize momentum.
// This script is *not* affiliated with or endorsed by him — it’s just an
// open-source educational re-implementation inspired by his ideas.
// Whether you love him or not, Cryptoface deserves credit for taking complex
// oscillator theory and making it accessible to everyday traders.
// -----------------------------------------------------------------------------
// Sorry Cryptoface Market Cypher B
//
// ✦ What it is
// A de-cluttered, optimized rework of the popular Market Cipher B concept.
// This fork strips out repaint-prone code and redundant signals, adds
// higher-timeframe and trend filters, and introduces volatility &
// money-flow gating to cut down on the "confetti signals" problem.
//
// ✦ Key Changes vs. Original MC-B
// - Non-repainting security(): switched to request.security(..., lookahead_off)
// - Inputs updated to Pine v5 (input.int, input.float, etc.)
// - Trend filter: EMA or HTF WaveTrend required for alignment
// - Volatility filter: minimum ADX & ATR % threshold to avoid chop
// - Money Flow filter: signals require minimum |MFI| magnitude
// - WaveTrend slope check: reject flat or contra-slope crosses
// - Cooldown filter: prevents multiple signals within N bars
// - Bar close confirmation: dots/alerts only fire once a candle is closed
// - Hidden divergences + “second range” divergences disabled by default
// (to reduce noise) but can be toggled on
//
// ✦ Components
// - WaveTrend oscillator (2-line system + VWAP line)
// - Money Flow Index + RSI overlay
// - Stochastic RSI
// - Divergence detection (WT, RSI, Stoch)
// - Optional Schaff Trend Cycle
// - Optional Sommi flags/diamonds (HTF confluence markers)
//
// ✦ Benefits
// - Fewer false positives in sideways markets
// - Signals aligned with trend & volatility regimes
// - Removes repaint artifacts from higher-timeframe sources
// - Cleaner chart (reduced “dot spam”)
// - Still flexible: all original toggles/visuals retained
//
// ✦ Notes
// - This is NOT the official Market Cipher.
// - Educational / experimental use only. Do your own testing.
// - Best tested on 2H–4H timeframes; short TFs may still look choppy
//
// ✦ Credits
// Original open-source inspirations by LazyBear, RicardoSantos, LucemAnb,
// falconCoin, dynausmaux, andreholanda73, TradingView community.
// This fork modified by Lumina+Thomas (2025).
// -----------------------------------------------------------------------------
MATEOANUBISANTIDear traders, investors, and market enthusiasts,
We are excited to share our High-Low Indicator Range for on . This report aims to provide a clear and precise overview of the highest and lowest values recorded by during this specific hour, equipping our community with a valuable tool for making informed and strategic market decisions.
MATEOANUBISANTI-BILLIONSQUATDear traders, investors, and market enthusiasts,
We are excited to share our High-Low Indicator Range for on . This report aims to provide a clear and precise overview of the highest and lowest values recorded by during this specific hour, equipping our community with a valuable tool for making informed and strategic market decisions.
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)
44 MA Near & Green Candle ScannerStocks that have closed just about 44 MA on 14th Aug 2025 and are forming green candles now
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 :) )
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
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.
RSI DJ GUTO 2025RSI do Samuca, tem de trocar as cores, esse e o usado nas lives, tem de trocar as cores pra ficar igual ao do Samuca pois aqui nao consegui trocar as cores.
Samuca's RSI, you have to change the colors, this is the one used in the lives, you have to change the colors to be the same as Samuca's because I couldn't change the colors here.
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.
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.
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
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.
ECG chart - mauricioofsousaMGO Primary – Matriz Gráficos ON
The Blockchain of Trading applied to price behavior
The MGO Primary is the foundation of Matriz Gráficos ON — an advanced graphical methodology that transforms market movement into a logical, predictable, and objective sequence, inspired by blockchain architecture and periodic oscillatory phenomena.
This indicator replaces emotional candlestick reading with a mathematical interpretation of price blocks, cycles, and frequency. Its mission is to eliminate noise, anticipate reversals, and clearly show where capital is entering or exiting the market.
What MGO Primary detects:
Oscillatory phenomena that reveal the true behavior of orders in the book:
RPA – Breakout of Bullish Pivot
RPB – Breakout of Bearish Pivot
RBA – Sharp Bullish Breakout
RBB – Sharp Bearish Breakout
Rhythmic patterns that repeat in medium timeframes (especially on 12H and 4H)
Wave and block frequency, highlighting critical entry and exit zones
Validation through Primary and Secondary RSI, measuring the real strength behind movements
Who is this indicator for:
Traders seeking statistical clarity and visual logic
Operators who want to escape the subjectivity of candlesticks
Anyone who values technical precision with operational discipline
Recommended use:
Ideal timeframes: 12H (high precision) and 4H (moderate intensity)
Recommended assets: indices (e.g., NASDAQ), liquid stocks, and futures
Combine with: structured risk management and macro context analysis
Real-world performance:
The MGO12H achieved a 92% accuracy rate in 2025 on the NASDAQ, outperforming the average performance of major global quantitative strategies, with a net score of over 6,200 points for the year.
Nifty50 Swing Trading Super Indicator# 🚀 Nifty50 Swing Trading Super Indicator - Complete Guide
**Created by:** Gaurav
**Date:** August 8, 2025
**Version:** 1.0 - Optimized for Indian Markets
---
## 📋 Table of Contents
1. (#quick-start-guide)
2. (#indicator-overview)
3. (#installation-instructions)
4. (#parameter-settings)
5. (#signal-interpretation)
6. (#trading-strategy)
7. (#risk-management)
8. (#optimization-tips)
9. (#troubleshooting)
---
## 🎯 Quick Start Guide
### What You Get
✅ **2 Complete Pine Script Indicators:**
- `swing_trading_super_indicator.pine` - Universal version for all markets
- `nifty_optimized_super_indicator.pine` - Specifically optimized for Nifty50 & Indian stocks
✅ **Key Features:**
- Multi-component signal confirmation system
- Optimized for daily and 3-hour timeframes
- Built-in risk management with dynamic stops and targets
- Real-time signal strength monitoring
- Gap analysis for Indian market characteristics
### Immediate Setup
1. Copy the Pine Script code from `nifty_optimized_super_indicator.pine`
2. Paste into TradingView Pine Editor
3. Add to chart on daily or 3-hour timeframe
4. Look for 🚀BUY and 🔻SELL signals
5. Use the information table for signal confirmation
---
## 🔍 Indicator Overview
### Core Components Integration
**🎯 Range Filter (35% Weight)**
- Primary trend identification using adaptive volatility filtering
- Optimized sampling period: 21 bars for Indian market volatility
- Enhanced range multiplier: 3.0 to handle market gaps
- Provides trend direction and strength measurement
**⚡ PMAX (30% Weight)**
- Volatility-adjusted trend confirmation using ATR-based calculations
- Dynamic multiplier adjustment based on market volatility
- 14-period ATR with 2.5 multiplier for swing trading sensitivity
- Offers trailing stop functionality
**🏗️ Support/Resistance (20% Weight)**
- Dynamic level identification using pivot point analysis
- Tighter channel width (3%) for precise Indian market levels
- Enhanced strength calculation with historical interaction weighting
- Provides entry/exit timing and breakout signals
**📊 EMA Alignment (15% Weight)**
- Multi-timeframe moving average confirmation
- Key EMAs: 9, 21, 50, 200 (popular in Indian markets)
- Hierarchical alignment scoring for trend strength
- Additional trend validation layer
### Advanced Features
**🌅 Gap Analysis**
- Automatic detection of significant price gaps (>2%)
- Gap strength measurement and impact on signals
- Specific optimization for Indian market overnight gaps
- Visual gap markers on chart
**⏰ Multi-Timeframe Integration**
- Higher timeframe bias from daily/weekly data
- Configurable daily bias weight (default 70%)
- 3-hour confirmation for precise entry timing
- Prevents counter-trend trades against major timeframe
**🛡️ Risk Management**
- Dynamic stop-loss calculation using multiple methods
- Automatic profit target identification
- Position sizing guidance based on signal strength
- Anti-whipsaw logic to prevent false signals
---
## 📥 Installation Instructions
### Step 1: Access TradingView
1. Open TradingView.com
2. Navigate to Pine Editor (bottom panel)
3. Create a new indicator
### Step 2: Copy the Code
**For Nifty50 & Indian Stocks (Recommended):**
```pinescript
// Copy entire content from nifty_optimized_super_indicator.pine
```
**For Universal Use:**
```pinescript
// Copy entire content from swing_trading_super_indicator.pine
```
### Step 3: Configure and Apply
1. Click "Add to Chart"
2. Select daily or 3-hour timeframe
3. Adjust parameters if needed (defaults are optimized)
4. Enable alerts for signal notifications
### Step 4: Verify Installation
- Check that all components are visible
- Confirm information table appears in top-right
- Test with known trending stocks for signal validation
---
## ⚙️ Parameter Settings
### 🎯 Range Filter Settings
```
Sampling Period: 21 (optimized for Indian market volatility)
Range Multiplier: 3.0 (handles overnight gaps effectively)
Source: Close (most reliable for swing trading)
```
### ⚡ PMAX Settings
```
ATR Length: 14 (standard for daily/3H timeframes)
ATR Multiplier: 2.5 (balanced for swing trading sensitivity)
Moving Average Type: EMA (responsive to price changes)
MA Length: 14 (matches ATR period for consistency)
```
### 🏗️ Support/Resistance Settings
```
Pivot Period: 8 (shorter for Indian market dynamics)
Channel Width: 3% (tighter for precise levels)
Minimum Strength: 3 (higher quality levels only)
Maximum Levels: 4 (focus on strongest levels)
Lookback Period: 150 (sufficient historical data)
```
### 🚀 Super Indicator Settings
```
Signal Sensitivity: 0.65 (balanced for swing trading)
Trend Strength Requirement: 0.75 (high quality signals)
Gap Threshold: 2.0% (significant gap detection)
Daily Bias Weight: 0.7 (strong higher timeframe influence)
```
### 🎨 Display Options
```
Show Range Filter: ✅ (trend visualization)
Show PMAX: ✅ (trailing stops)
Show S/R Levels: ✅ (key price levels)
Show Key EMAs: ✅ (trend confirmation)
Show Signals: ✅ (buy/sell alerts)
Show Trend Background: ✅ (visual trend state)
Show Gap Markers: ✅ (gap identification)
```
---
## 📊 Signal Interpretation
### 🚀 BUY Signals
**Requirements for BUY Signal:**
- Price above Range Filter with upward trend
- PMAX showing bullish direction (MA > PMAX line)
- Support/resistance breakout or favorable positioning
- EMA alignment supporting upward movement
- Higher timeframe bias confirmation
- Overall signal strength > 75%
**Signal Strength Indicators:**
- **90-100%:** Extremely strong - Maximum position size
- **80-89%:** Very strong - Large position size
- **75-79%:** Strong - Standard position size
- **65-74%:** Moderate - Reduced position size
- **<65%:** Weak - Wait for better opportunity
### 🔻 SELL Signals
**Requirements for SELL Signal:**
- Price below Range Filter with downward trend
- PMAX showing bearish direction (MA < PMAX line)
- Resistance breakdown or unfavorable positioning
- EMA alignment supporting downward movement
- Higher timeframe bias confirmation
- Overall signal strength > 75%
### ⚖️ NEUTRAL Signals
**Characteristics:**
- Conflicting signals between components
- Low overall signal strength (<65%)
- Range-bound market conditions
- Wait for clearer directional bias
### 📈 Information Table Guide
**Component Status:**
- **BULL/BEAR:** Current signal direction
- **Strength %:** Component contribution strength
- **Status:** Additional context (STRONG/WEAK/ACTIVE/etc.)
**Overall Signal:**
- **🚀 STRONG BUY:** All systems aligned bullish
- **🔻 STRONG SELL:** All systems aligned bearish
- **⚖️ NEUTRAL:** Mixed or weak signals
---
## 💼 Trading Strategy
### Daily Timeframe Strategy
**Setup:**
1. Apply indicator to daily chart of Nifty50 or Indian stocks
2. Wait for 🚀BUY or 🔻SELL signal with >75% strength
3. Confirm higher timeframe bias alignment
4. Check for significant support/resistance levels
**Entry:**
- Enter on signal bar close or next bar open
- Use 3-hour chart for precise entry timing
- Avoid entries during major news events
- Consider gap analysis for overnight positions
**Position Sizing:**
- **>90% Strength:** 3-4% of portfolio
- **80-89% Strength:** 2-3% of portfolio
- **75-79% Strength:** 1-2% of portfolio
- **<75% Strength:** Avoid or minimal size
### 3-Hour Timeframe Strategy
**Setup:**
1. Confirm daily timeframe bias first
2. Apply indicator to 3-hour chart
3. Look for signals aligned with daily trend
4. Use for entry/exit timing optimization
**Entry Refinement:**
- Wait for 3H signal confirmation
- Enter on pullbacks to key levels
- Use tighter stops for better risk/reward
- Monitor intraday support/resistance
### Risk Management Rules
**Stop Loss Placement:**
1. **Primary:** Use indicator's dynamic stop level
2. **Secondary:** Below/above nearest support/resistance
3. **Maximum:** 2-3% of portfolio per trade
4. **Trailing:** Move stops with PMAX line
**Profit Taking:**
1. **Target 1:** First resistance/support level (50% position)
2. **Target 2:** Second resistance/support level (30% position)
3. **Runner:** Trail remaining 20% with PMAX
**Position Management:**
- Review positions at daily close
- Adjust stops based on new signals
- Exit if trend changes to opposite direction
- Reduce size during high volatility periods
---
## 🎯 Optimization Tips
### For Nifty50 Trading
- Use daily timeframe for primary signals
- Monitor sector rotation impact
- Consider index futures for better liquidity
- Watch for RBI policy and global cues impact
### For Individual Stocks
- Verify stock follows Nifty correlation
- Check sector-specific news and events
- Ensure adequate liquidity for position size
- Monitor earnings calendar for volatility
### Market Condition Adaptations
**Trending Markets:**
- Increase position sizes for strong signals
- Use wider stops to avoid whipsaws
- Focus on trend continuation signals
- Reduce counter-trend trading
**Range-Bound Markets:**
- Reduce position sizes
- Use tighter stops and quicker profits
- Focus on support/resistance bounces
- Increase signal strength requirements
**High Volatility Periods:**
- Reduce overall exposure
- Use smaller position sizes
- Increase stop-loss distances
- Wait for clearer signals
### Performance Monitoring
- Track win rate and average profit/loss
- Monitor signal quality over time
- Adjust parameters based on market changes
- Keep trading journal for pattern recognition
---
## 🔧 Troubleshooting
### Common Issues
**Q: Signals appear too frequently**
A: Increase "Trend Strength Requirement" to 0.8-0.9
**Q: Missing obvious trends**
A: Decrease "Signal Sensitivity" to 0.5-0.6
**Q: Too many false signals**
A: Enable "3H Confirmation" and increase strength requirements
**Q: Indicator not loading**
A: Check Pine Script version compatibility (requires v5)
### Parameter Adjustments
**For More Sensitive Signals:**
- Decrease Signal Sensitivity to 0.5-0.6
- Decrease Trend Strength Requirement to 0.6-0.7
- Increase Range Filter multiplier to 3.5-4.0
**For More Conservative Signals:**
- Increase Signal Sensitivity to 0.7-0.8
- Increase Trend Strength Requirement to 0.8-0.9
- Enable all confirmation features
### Performance Issues
- Reduce lookback periods if chart loads slowly
- Disable some visual elements for better performance
- Use on liquid stocks/indices for best results
---
## 📞 Support & Updates
This super indicator combines the best of Range Filter, PMAX, and Support/Resistance analysis specifically optimized for Indian market swing trading. The multi-component approach significantly improves signal quality while the built-in risk management features help protect capital.
**Remember:** No indicator is 100% accurate. Always combine with proper risk management, market analysis, and your trading experience for best results.
**Happy Trading! 🚀**