NK-Macd + Rsi3Here in one table you can see the MACD of the different time frame that what is the status of the MACD, is it above zero line or below zero line.
Second you will see in table that RSI number of all time frame, so here we dont need to go and check RSI by switching the chart and time frame.
at one place you will see both RSI and MACD, and by seeing the number you can check when the price in oversold zone and when it will in overbought also you can see the when the price in momentum and when not.
Example :- let assume RSI table showing above 40 in 1 hr and 67 in daily that means RSI is in swing momentum in hrly but momentum in daily.
Oscillators
LCS DynamicUses adaptive calculations to generate signals each signal has different rules to trade which will be updated shortly
Triple-Timeframe Stochastic Alerts (Smart Filtered)multi time stochastic w/ volume.
Smart filters, volume cool off,
3 adjustable time stochastic.
volume filter
Williams %R smoothed🌍 English Description
Williams %R Smoothed – by Ján Salma
This is the first smoothed version of the Williams %R indicator published on TradingView.
The traditional Williams %R is a momentum oscillator that can be very choppy and noisy. Many traders find it hard to use because of the constant whipsaws.
This indicator solves that problem by applying an EMA smoothing on top of the raw Williams %R values.
Why is this special?
[* ]📉 Reduces noise → much cleaner signal, fewer false spikes.
🔍 Highlights real momentum shifts → easier to spot when the market truly changes direction.
🎯 Customizable smoothing → you decide how sensitive or smooth the curve should be.
⚡ Unique → currently, there is no other smoothed Williams %R available on TradingView.
Settings
Length → default 14 (standard Williams %R period).
Smoothing → default 3 EMA (smooths out the raw values).
Levels: -20 (overbought), -80 (oversold), -50 (mid-level).
This indicator is great for scalpers and swing traders who love Williams %R but hate the noise.
Now you can finally use %R with more confidence and clarity.
--------------------------------------------------------------------
Slovenský popis
Williams %R Smoothed – od Jána Salmu
Toto je prvá vyhladená verzia Williams %R indikátora publikovaná na TradingView.
Klasický Williams %R je oscilátor hybnosti, ktorý je často veľmi „roztrasený“ a plný šumu. Mnoho traderov s ním preto pracuje ťažko, pretože dáva veľa falošných signálov.
Tento indikátor to rieši tak, že na pôvodné hodnoty Williams %R aplikuje EMA vyhladenie .
Čo robí tento indikátor výnimočným?
📉 Redukuje šum → výsledná krivka je čistejšia, s menej falošnými výkyvmi.
🔍 Zvýrazňuje skutočné zmeny hybnosti → jasnejšie vidíš, kedy sa trh naozaj otáča.
🎯 Nastaviteľné vyhladenie → citlivosť indikátora si prispôsobíš podľa seba.
⚡ Unikát → na TradingView zatiaľ neexistuje žiadny iný vyhladený Williams %R.
Nastavenia
Dĺžka → predvolená hodnota 14 (štandardný Williams %R).
Smoothing (EMA) → predvolená hodnota 3 (vyhladenie krivky).
Úrovne: -20 (prekúpený trh), -80 (prepredaný trh), -50 (stredová hodnota).
Tento indikátor je skvelý pre scalperov aj swing traderov, ktorí majú radi Williams %R, ale chcú ho používať s väčšou presnosťou a prehľadnosťou.
LRSlope - Linear Regression SlopeThis indicator attempts to predict the direction of the trend using least squares moving averages (LSMA).
The indicator's core purpose is to determine whether the price trajectory has a positive or negative slope and calculate directional changes. It also measures the strength of price momentum by calculating how strongly the slope.
The indicator calculates the slope of the curve for each bar and the EMA of these slopes for the specified period (Curve Length). It is consists of a histogram and two lines named "Average Slope"(white line) and "Simple" (green line).
The "Average Slope" is the simple moving average of the calculated EMA values.
" Simple " is SMA of calculated slopes.
The color of the histogram changes depending on the relative position of these two lines and zero line.
Simply put, the green bars of the histogram indicate an uptrend, blue bars indicate a horizontal or reverse movement, and red bars indicate a downtrend.
It is possible to see the strength of the momentum by the amount of change in the " Simple" (green line).
PowerDelta Oscillator [FxScripts]PowerDelta Oscillator
The PowerDelta Oscillator measures real-time buying and selling pressure using the proprietary PowerDelta Algorithm. By quantifying order flow, it identifies whether the market conditions favor bullish or bearish activity, helping traders determine directional bias for both trend and countertrend setups.
Calculation Methodology
The PowerDelta computes the delta (difference) between buying and selling pressure by integrating both price movement and volume behavior rather than relying solely on volume or price-based approximations like other oscillators.
The PowerDelta Algorithm evaluates six core price-volume conditions:
Price advancing with increasing volume
Price advancing with decreasing volume
Price consolidating with increasing volume
Price consolidating with decreasing volume
Price declining with increasing volume
Price declining with decreasing volume
From these conditions, the algorithm derives:
Accumulation vs Distribution phases
Buyer/Seller exhaustion points
Effort vs No Result scenarios (volume pressure failing to move price)
Operational Use
The PowerDelta Oscillator has three operational modes:
Trend
Countertrend
Blended (Trend/Countertrend hybrid)
Trend Mode
In Trend Mode, the indicator plots an oscillator that fluctuates between positive and negative values:
Positive readings indicate dominant buying pressure
Negative readings indicate dominant selling pressure
The magnitude of the reading reflects the intensity of the pressure
Crossovers at the zero line provide directional shifts:
Negative → Positive: bullish transition
Positive → Negative: bearish transition
Additionally:
Sustained positive values indicate control by buyers, long bias is favoured
Sustained negative values indicate control by sellers, short bias is favoured
The magnitude of displacement from zero provides additional confirmation of market strength or weakness
Countertrend Mode
In Countertrend Mode, the primary use of the PowerDelta Oscillator is to locate divergences between price and the oscillator (as visualised on the chart above) which helps traders pinpoint potential reversals
The oscillator is much more sensitive in this mode, making highs, lows and hence divergences, easier to spot
Like Trend Mode, the magnitude of displacement from zero provides additional confirmation of market strength or weakness
The various Analytical Scenarios detailed below provide detailed use cases for both Trend and Countertrend Mode
Blended Mode
To provide maximum flexibility, there’s also a third Blended Mode
This mode combines elements of the two primary modes and can be used as part of a hybrid approach making it easier to spot both trends and reversals
Alternative Source
The PowerDelta algorithm utilises volume data therefore it’s best to use the most reliable source of volume data for the instrument being traded
For instance, whilst XAUUSD provides excellent results with most forex brokers, slightly better results may be achieved using GC futures data which comes direct from the exchange (data package required)
To use a third-party source, select 'Alternative' and input the relevant source
This can also be used as a way to monitor correlated pairs by adding two instances of the PowerDelta to the same chart, selecting pair 1 e.g. EURUSD as the first instance and the correlated pair e.g. USDCHF as the second instance
Thorough backtesting advised
Analytical Scenarios
Accumulation: High positive oscillator readings combined with upward price movement suggest active accumulation.
Optimal strategy: Monitor pullbacks for potential long entries or wait for a divergence with price and potential reversal.
Distribution: High negative oscillator readings with downward price movement indicate distribution.
Optimal strategy: Monitor pullbacks for potential short entries or wait for a divergence with price and potential reversal.
Buyer Exhaustion: Price forms higher highs while oscillator value declines. Indicates weakening buying strength and potential bearish reversal.
Seller Exhaustion: Price forms lower lows while oscillator value contracts. Indicates weakening selling strength and potential bullish reversal.
Effort / No Result (Buyers): Positive oscillator expansion without higher highs indicates aggressive buying without price confirmation, suggesting overbought conditions and a potential bearish reversal.
Effort / No Result (Sellers): Negative oscillator expansion without lower lows indicates aggressive selling without price confirmation, suggesting oversold conditions and a potential bullish reversal.
Alerts
To trigger alerts when market bias transitions across the zero line:
Right-click on chart → Add Alert on PowerDelta
Condition: PowerDelta → Select Mode
Type: Crossing
Value: 0
Execution: Once Per Bar Close
Adjust additional parameters as required
Performance and Optimization
Backtesting Results: The PowerDelta Oscillator has undergone extensive backtesting across various instruments, timeframes and market conditions, demonstrating strong performance in identifying strong trends and reversals. User backtesting is strongly encouraged as it allows traders to optimize settings for their preferred instruments and timeframes.
Optimization for Diverse Markets: The PowerDelta Oscillator can be used on crypto, forex, indices, commodities and stocks. The PowerDelta Oscillator's algorithmic foundation ensures consistent performance across a variety of instruments. The Trend, Countertrend and Blended Modes make it easy for the trader to set up based on their individual trading style.
Educational Resources and Support
Users of the PowerDelta Oscillator benefit from comprehensive educational resources and full access to FxScripts Support. This ensures traders can maximize the potential of the PowerDelta Oscillator and other tools in the Sigma Indicator Suite by learning best practices and gaining insights from an experienced team of traders.
Supertrend Channel Histogram OscillatorThis histogram is based on the script "Supertrend Channels "
The idea of the indicator is to visually represent the interaction of price with several different supertrend channels of various lengths in an oscillator in order to make it much more clear to the trader how the longer trends are interacting with shorter trends of the price movement of an asset. I got this idea from the "Kurutoga Cloud" and "Kurutoga Histogram" by D7R which is based on the centerlines of 3 Donchian Channels, however after I started using the Supertrend Channel by LuxAlgo I found that it was a more reliable price range channel than a standard Donchian Channel and I made this indicator to accompany it.
This indicator plots a positive value above 0 when the price is above the centerline of the supertrend channel and a negative value below 0 when the price is below the centerline.
The first supertrend's length and multiple can be adjusted in the settings.
The given supertrend input is then doubled and quadrupled in both length and multiplication so that a supertrend histogram with the values of 3, 3 will be accompanied by 2 additional supertrend histograms with the values of 6, 6 and 12, 12.
The larger price trend histograms are clearly visible behind the short term supertrend channel's histogram, giving traders a balanced view of short and long term trends interacting. The less visible columns of the larger trend remain above or below the 0 line behind the more visible short term channel trend, helping to spot pullbacks within a larger trend.
Additionally, when the 3 separate histograms are all positive or all negative but the histogram columns are separating from each other this can indicate a potential trend exhaustion leading to reversal or pullback about to happen.
The overbought and oversold lines at 50 and -50 are representative primarily of the short term trend with above 50 or below -50 indicating that the price is pushing the boundary and potentially beginning a new short term supertrend in the opposite direction. If values do not noticably exceed these levels, then the current short term trend movement can be viewed as a pullback within a larger trend, with continuation potentially to follow.
I have had troubles converting the original code to v6 so this will be published here in v5 of pinescript to be used in conjunction with the original. I was intending to create a companion indicator for this oscillator that represents 3 supertrends with corresponding 2x and 4x calculations based on LuxAlgo's script, but I can't seem to get it to work correctly in v5.
For best visualization of the trends 3 LuxAlgo Supertrend channels with 2x and 4x values should be used in conjunction with each other to fully visualize the histogram.
Used in conjunction with other indicators this can be a very effective strategy to capture larger trend moves and pullbacks within trends, as well as warn of potential price trend exhaustion.
Volatility Cone Forecaster Lite [PhenLabs]📊 Volatility Cone Forecaster
Version: PineScript™v6
📌Description
The Volatility Cone Forecaster (VCF) is an advanced indicator designed to provide traders with a forward-looking perspective on market volatility. Instead of merely measuring past price fluctuations, the VCF analyzes historical volatility data to project a statistical “cone” that outlines a probable range for future price movements. Its core purpose is to contextualize the current market environment, helping traders to anticipate potential shifts from low to high volatility periods (and vice versa). By identifying whether volatility is expanding or contracting relative to historical norms, it solves the critical problem of preparing for significant market moves before they happen, offering a clear statistical edge in strategy development.
This indicator moves beyond lagging measures by employing percentile analysis to rank the current volatility state. This allows traders to understand not just what volatility is, but how significant it is compared to the recent past. The VCF is built for discretionary traders, system developers, and options strategists who need a sophisticated understanding of market dynamics to manage risk and identify high-probability opportunities.
🚀Points of Innovation
Forward-Looking Volatility Projection: Unlike standard indicators that only show historical data, the VCF projects a statistical cone of future volatility.
Percentile-Based Regime Analysis: Ranks current volatility against historical data (e.g., 90th, 75th percentiles) to provide objective context.
Automated Regime Detection: Automatically identifies and labels the market as being in a ‘High’, ‘Low’, or ‘Normal’ volatility regime.
Expansion & Contraction Signals: Clearly indicates whether volatility is currently increasing or decreasing, signaling shifts in market energy.
Integrated ATR Comparison: Plots an ATR-equivalent volatility measure to offer a familiar point of reference against the statistical model.
Dynamic Visual Modeling: The cone visualization directly on the price chart provides an intuitive guide for future expected price ranges.
🔧Core Components
Realized Volatility Engine: Calculates historical volatility using log returns over multiple user-defined lookback periods (short, medium, long) for a comprehensive view.
Percentile Analysis Module: A custom function calculates the 10th, 25th, 50th, 75th, and 90th percentiles of volatility over a long-term lookback (e.g., 252 days).
Forward Projection Calculator: Uses the calculated volatility percentiles to mathematically derive and draw the upper and lower bounds of the future volatility cone.
Volatility Regime Classifier: A logic-based system that compares current volatility to the historical percentile bands to classify the market state.
🔥Key Features
Customizable Lookback Periods: Adjust short, medium, and long-term lookbacks to fine-tune the indicator’s sensitivity to different market cycles.
Configurable Forward Projection: Set the number of days for the forward cone projection to align with your specific trading horizon.
Interactive Display Options: Toggle visibility for percentile labels, ATR levels, and regime coloring to customize the chart display.
Data-Rich Information Table: A clean, on-screen table displays all key metrics, including current volatility, percentile rank, regime, and trend.
Built-in Alert Conditions: Set alerts for critical events like volatility crossing the 90th percentile, dropping below the 10th, or switching between expansion and contraction.
🎨Visualization
Volatility Cone: Shaded bands projected onto the future price axis, representing the probable price range at different statistical confidence levels (e.g., 75th-90th percentile).
Color-Coded Volatility Line: The primary volatility plot dynamically changes color (e.g., red for high, green for low) to reflect the current volatility regime, providing instant context.
Historical Percentile Bands: Horizontal lines plotted across the indicator pane mark the key percentile levels, showing how current volatility compares to the past.
On-Chart Labels: Clear labels automatically display the current volatility reading, its percentile rank, the detected regime, and trend (Expanding/Contracting).
📖Usage Guidelines
Setting Categories
Short-term Lookback: Default: 10, Range: 5-50. Controls the most sensitive volatility calculation.
Medium-term Lookback: Default: 21, Range: 10-100. The primary input for the current volatility reading.
Long-term Lookback: Default: 63, Range: 30-252. Provides a baseline for long-term market character.
Percentile Lookback Period: Default: 252, Range: 100-1000. Defines the period for historical ranking; 252 represents one trading year.
Forward Projection Days: Default: 21, Range: 5-63. Determines how many bars into the future the cone is projected.
✅Best Use Cases
Breakout Trading: Identify periods of deep consolidation when volatility falls to low percentile ranks (e.g., below 25th) and begins to expand, signaling a potential breakout.
Mean Reversion Strategies: Target trades when volatility reaches extreme high percentile ranks (e.g., above 90th), as these periods are often unsustainable and lead to contraction.
Options Strategy: Use the cone’s projected upper and lower bounds to help select strike prices for strategies like iron condors or straddles.
Risk Management: Widen stop-losses and reduce position sizes when the indicator signals a transition into a ‘High’ volatility regime.
⚠️Limitations
Probabilistic, Not Predictive: The cone represents a statistical probability, not a guarantee of future price action. Extreme, unpredictable news events can drive prices outside the cone.
Lagging by Nature: All calculations are based on historical price data, meaning the indicator will always react to, not pre-empt, market changes.
Non-Directional: The indicator forecasts the *magnitude* of future moves, not the *direction*. It should be paired with a directional analysis tool.
💡What Makes This Unique
Forward Projection: Its primary distinction is projecting a data-driven, statistical forecast of future volatility, which standard oscillators do not do.
Contextual Analysis: It doesn’t just provide a number; it tells you what that number means through percentile ranking and automated regime classification.
🔬How It Works
1. Data Calculation:
The indicator first calculates the logarithmic returns of the asset’s price. It then computes the annualized standard deviation of these returns over short, medium, and long-term lookback periods to generate realized volatility readings.
2. Percentile Ranking:
Using a 252-day lookback, it analyzes the history of the medium-term volatility and determines the values that correspond to the 10th, 25th, 50th, 75th, and 90th percentiles. This builds a statistical map of the asset’s volatility behavior.
3. Cone Projection:
Finally, it takes these historical percentile values and projects them forward in time, calculating the potential upper and lower price bounds based on what would happen if volatility were to run at those levels over the next 21 days.
💡Note:
The Volatility Cone Forecaster is most effective on daily and weekly charts where statistical volatility models are more reliable. For lower timeframes, consider shortening the lookback periods. Always use this indicator as part of a comprehensive trading plan that includes other forms of analysis.
MTF Stochastic Dashboard What you see:
Top-right table: TF | %K | %D | Signal.
Signal = Bullish (green) if K > D, Bearish (red) if K < D.
Row color: red if K & D ≥ 80, green if K & D ≤ 20.
Number color: ≤30 green, ≥70 red.
Settings
Signal mode:
Always (just K>D or K
Kerzen-Zähler über/unter EMADieses Skript zeigt die Anzahl an Zeitperioden ober/unterhalb eines individuellen EMAs an.
FX Strike — RSI Momentum PanelDescription:
The FX Strike RSI Panel provides a momentum filter for the FX Strike system, using the classic RSI with enhanced visuals.
RSI (14): Standard calculation with clear signals.
50 Midline: Momentum bias filter (above = bullish, below = bearish).
30/70 Zones: Overbought and oversold regions for context.
Colored RSI Line: Teal when bullish, orange when bearish.
Alert Conditions: Triggers when RSI crosses above or below the 50 mid-line.
How to Use:
In trend trading, only take longs if RSI is above 50 and shorts if RSI is below 50.
Use divergences (price vs RSI) to spot early signs of weakening momentum.
Combine with the FX Strike Overlay for a complete 4-pillar strategy (Trend, Volatility, Momentum, Volume).
Combined Continuational Signal - RSI & KeltnerContinuational Signal Indicator
This technical indicator provides trend continuation signals through dual-methodology analysis, offering traders flexibility to choose between RSI-based or Keltner Channel-based signal generation, or utilize both simultaneously for enhanced confirmation.
Core Functionality:
Dual Signal Architecture: Toggle between RSI momentum analysis or Keltner Channel volatility breakout detection
Multi-Confirmation Framework: Incorporates moving average trend filters, slope analysis, and candle pattern validation
Cloud Interaction Filter: Signals activate only when price interacts with the moving average cloud zone
MA Closeness Filter: Uses ATR-based filtering to avoid signals during low-volatility consolidation periods
Signal Logic:
The indicator waits for overbought/oversold conditions (RSI) or band extremes (Keltner), confirms directional bias through slope analysis, validates trend alignment via moving average positioning, then triggers signals on specific candle formations with engulfing characteristics.
Customization Options:
Adjustable RSI parameters and threshold levels
Configurable Keltner Channel settings with multiple calculation methods
Multiple moving average lengths for trend and slope analysis
Various display modes (shapes, backgrounds, candle coloring, vertical lines)
Comprehensive alert system for all signal types
Risk Management Integration:
Built-in filters prevent signals during choppy market conditions and ensure alignment with higher-timeframe trend direction before activation.
Use in conjunction with other confluent variables for optimal results. The default settings are calibrated for specific market conditions, though experimentation with parameters is recommended for different trading styles and timeframes.
Chanpreet RSI(3) Extreme Rays (4H, Adjustable Style)Chanpreet RSI(3) Extreme Rays (4H)
This indicator applies a short-length RSI (3) on the 4-hour timeframe and highlights momentum extremes directly on the chart.
🔎 What it does
Detects when RSI(3) moves into overbought (>80) or oversold (<20) territory.
Groups consecutive candles inside these zones into one “event” instead of marking each bar individually.
For each event:
• In overbought → records the highest high of the stretch and marks it with a horizontal ray.
• In oversold → records the lowest low of the stretch and marks it with a horizontal ray.
Keeps only the most recent N rays (default 5, adjustable).
⚙️ Inputs
Max Rays to Keep → how many unique events are kept visible.
Ray Thickness → adjust line thickness.
Overbought Ray Color → default red.
Oversold Ray Color → default green.
📈 How to use
Apply on any chart; RSI(3) values are always calculated from 4H data (via request.security).
Use rays as reference levels that highlight recent momentum extremes or exhaustion zones.
This is not a buy/sell signal by itself — combine with your own analysis, confirmation tools, and risk management.
Best Recommended time frame is 5 mins, 10 mins & 15 mins for intraday trading.
🧩 Unique features
Groups multiple bars into a single clean ray, reducing clutter.
Uses 4H RSI(3) regardless of the chart’s active timeframe.
Fully customizable appearance (colors, thickness, max events).
⚠️ Disclaimer
This script is provided for educational and informational purposes only.
It does not constitute financial advice or guarantee performance.
Always test thoroughly and use proper risk management before trading live.
3X Sniper BotThe 3X Sniper Bot is built for traders who demand clarity, precision, and confidence in their decision-making. This tool isn’t just another crossover script—it’s a full multi-confirmation system that helps you spot momentum shifts, identify high-probability entries, and filter out the noise.
🔥 Why traders love it:
Triple confirmation engine: Only fires when multiple conditions align, reducing false signals.
Strong vs. Regular vs. Possible setups: Get nuanced alerts that distinguish between high-conviction moves and early opportunities.
Both Buy & Sell coverage: Stay prepared in any market environment.
Smart flexibility: Works across strict or sequenced signal modes, giving you control over how conservative or aggressive you want to trade.
Visual clarity: Clean chart markers and optional regime shading keep your screen easy to read at a glance.
Alert-ready: Set and forget—never miss a move with real-time TradingView alerts.
This indicator was designed to make complex multi-factor analysis simple, giving traders a clear visual edge without clutter or guesswork. Whether you scalp intraday or swing multi-day, the 3X Sniper Bot adapts to your style.
Machine Learning Gaussian Mixture Model | AlphaNattMachine Learning Gaussian Mixture Model | AlphaNatt
A revolutionary oscillator that uses Gaussian Mixture Models (GMM) with unsupervised machine learning to identify market regimes and automatically adapt momentum calculations - bringing statistical pattern recognition techniques to trading.
"Markets don't follow a single distribution - they're a mixture of different regimes. This oscillator identifies which regime we're in and adapts accordingly."
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🤖 THE MACHINE LEARNING
Gaussian Mixture Models (GMM):
Unlike K-means clustering which assigns hard boundaries, GMM uses probabilistic clustering :
Models data as coming from multiple Gaussian distributions
Each market regime is a different Gaussian component
Provides probability of belonging to each regime
More sophisticated than simple clustering
Expectation-Maximization Algorithm:
The indicator continuously learns and adapts using the E-M algorithm:
E-step: Calculate probability of current market belonging to each regime
M-step: Update regime parameters based on new data
Continuous learning without repainting
Adapts to changing market conditions
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🎯 THREE MARKET REGIMES
The GMM identifies three distinct market states:
Regime 1 - Low Volatility:
Quiet, ranging markets
Uses RSI-based momentum calculation
Reduces false signals in choppy conditions
Background: Pink tint
Regime 2 - Normal Market:
Standard trending conditions
Uses Rate of Change momentum
Balanced sensitivity
Background: Gray tint
Regime 3 - High Volatility:
Strong trends or volatility events
Uses Z-score based momentum
Captures extreme moves
Background: Cyan tint
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
💡 KEY INNOVATIONS
1. Probabilistic Regime Detection:
Instead of binary regime assignment, provides probabilities:
30% Regime 1, 60% Regime 2, 10% Regime 3
Smooth transitions between regimes
No sudden indicator jumps
2. Weighted Momentum Calculation:
Combines three different momentum formulas
Weights based on regime probabilities
Automatically adapts to market conditions
3. Confidence Indicator:
Shows how certain the model is (white line)
High confidence = strong regime identification
Low confidence = transitional market state
Line transparency changes with confidence
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚙️ PARAMETER OPTIMIZATION
Training Period (50-500):
50-100: Quick adaptation to recent conditions
100: Balanced (default)
200-500: Stable regime identification
Number of Components (2-5):
2: Simple bull/bear regimes
3: Low/Normal/High volatility (default)
4-5: More granular regime detection
Learning Rate (0.1-1.0):
0.1-0.3: Slow, stable learning
0.3: Balanced (default)
0.5-1.0: Fast adaptation
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📊 TRADING STRATEGIES
Visual Signals:
Cyan gradient: Bullish momentum
Magenta gradient: Bearish momentum
Background color: Current regime
Confidence line: Model certainty
1. Regime-Based Trading:
Regime 1 (pink): Expect mean reversion
Regime 2 (gray): Standard trend following
Regime 3 (cyan): Strong momentum trades
2. Confidence-Filtered Signals:
Only trade when confidence > 70%
High confidence = clearer market state
Avoid transitions (low confidence)
3. Adaptive Position Sizing:
Regime 1: Smaller positions (choppy)
Regime 2: Normal positions
Regime 3: Larger positions (trending)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🚀 ADVANTAGES OVER OTHER ML INDICATORS
vs K-Means Clustering:
Soft clustering (probabilities) vs hard boundaries
Captures uncertainty and transitions
More mathematically robust
vs KNN (K-Nearest Neighbors):
Unsupervised learning (no historical labels needed)
Continuous adaptation
Lower computational complexity
vs Neural Networks:
Interpretable (know what each regime means)
No overfitting issues
Works with limited data
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📈 PERFORMANCE CHARACTERISTICS
Best Market Conditions:
Markets with clear regime shifts
Volatile to trending transitions
Multi-timeframe analysis
Cryptocurrency markets (high regime variation)
Key Strengths:
Automatically adapts to market changes
No manual parameter adjustment needed
Smooth transitions between regimes
Probabilistic confidence measure
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🔬 TECHNICAL BACKGROUND
Gaussian Mixture Models are used extensively in:
Speech recognition (Google Assistant)
Computer vision (facial recognition)
Astronomy (galaxy classification)
Genomics (gene expression analysis)
Finance (risk modeling at investment banks)
The E-M algorithm was developed at Stanford in 1977 and is one of the most important algorithms in unsupervised machine learning.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
💡 PRO TIPS
Watch regime transitions: Best opportunities often occur when regimes change
Combine with volume: High volume + regime change = strong signal
Use confidence filter: Avoid low confidence periods
Multi-timeframe: Compare regimes across timeframes
Adjust position size: Scale based on identified regime
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚠️ IMPORTANT NOTES
Machine learning adapts but doesn't predict the future
Best used with other confirmation indicators
Allow time for model to learn (100+ bars)
Not financial advice - educational purposes
Backtest thoroughly on your instruments
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🏆 CONCLUSION
The GMM Momentum Oscillator brings institutional-grade machine learning to retail trading. By identifying market regimes probabilistically and adapting momentum calculations accordingly, it provides:
Automatic adaptation to market conditions
Clear regime identification with confidence levels
Smooth, professional signal generation
True unsupervised machine learning
This isn't just another indicator with "ML" in the name - it's a genuine implementation of Gaussian Mixture Models with the Expectation-Maximization algorithm, the same technology used in:
Google's speech recognition
Tesla's computer vision
NASA's data analysis
Wall Street risk models
"Let the machine learn the market regimes. Trade with statistical confidence."
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Developed by AlphaNatt | Machine Learning Trading Systems
Version: 1.0
Algorithm: Gaussian Mixture Model with E-M
Classification: Unsupervised Learning Oscillator
Not financial advice. Always DYOR.
AI-Weighted RSI (Zeiierman)█ Overview
AI-Weighted RSI (Zeiierman) is an adaptive oscillator that enhances classic RSI by applying a correlation-weighted prediction layer. Instead of looking only at RSI values directly, this indicator continuously evaluates how other price- and volume-based features (returns, volatility, volume shifts) correlate with RSI, and then weights them accordingly to project the next RSI state.
The result is a smoother, forward-looking RSI framework that adapts to market conditions in real time.
By leveraging feature correlation instead of static formulas, AI-Weighted RSI behaves like a lightweight learning model, adjusting its emphasis depending on which features are most aligned with RSI behavior during the current regime.
█ How It Works
⚪ Feature Extraction
Each bar, the script computes features: log returns, RSI itself, ATR% (volatility), volume, and volume log-change.
⚪ Correlation Screening
Over a rolling learning window, it measures the correlation of each feature against RSI. The strongest relationships are ranked and selected.
⚪ Adaptive Weighting
Features are standardized (z-scored), then combined using their signed correlations as weights, building a rolling, adaptive prediction of RSI.
⚪ Prediction to RSI Weight
The predicted RSI is mapped back into a “weight” scale (±2 by default). Above 0 = bullish bias, below 0 = bearish bias, with color-graded fills to visualize overbought/oversold pressure.
⚪ Signal Line
A smoothing option (signal length) overlays a moving average of the AI-Weighted RSI for clearer trend confirmation.
█ Why AI-Weighted RSI
⚪ Adaptive to Market Regime
Because the model re-evaluates correlations continuously, it naturally shifts which features dominate, sometimes volatility explains RSI best, sometimes volume, sometimes returns.
⚪ Forward-Looking Bias
Instead of simply reflecting RSI, the model provides a projection, helping anticipate shifts in momentum before RSI itself flips.
█ How to Use
⚪ Directional Bias
Read the RSI relative to 0. Above = bullish momentum bias, below = bearish.
⚪ Overbought / Oversold Zones
Shaded fills beyond +0.5 or -0.5 highlight extremes where RSI pressure often exhausts.
⚪ Divergences
When price makes new highs/lows but AI-Weighted RSI fails to confirm, it often signals weakening momentum.
█ Settings
RSI Length: Lookback for the core RSI calculation.
Signal Length: Smoothing applied to the AI-Weighted RSI output.
Learning Window: Bars used for correlation learning and z-scoring.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
BUY & SELL Probability (M5..D1) - MTFMTF Probability Indicator (M5 to D1)
Indicator — Dual Histogram with Buy/Sell Labels
This indicator is designed to provide a probabilistic bias for bullish or bearish conditions by combining three different analytical components across multiple timeframes. The goal is to reduce noise from single-indicator signals and instead highlight confluence where trend, momentum, and strength agree.
Why this combination is useful
- EMA(200) Trend Filter: Identifies whether price is trading above or below a widely used long-term moving average.
- MACD Momentum: Detects short-term directional momentum through line crossovers.
- ADX Strength: Measures how strong the trend is, preventing signals in weak or flat markets.
By combining these, the indicator avoids situations where one tool signals a trade but others do not, helping to filter out low-probability setups.
How it works
- Each timeframe (M5, M15, H1, H4, D1) generates its own trend, momentum, and strength score.
- Scores are weighted according to user-defined importance and then aggregated into a single probability.
- Proximity to recent support and resistance levels can adjust the final score, accounting for nearby barriers.
- The final probability is displayed as:
- Histogram (subwindow): Green bars for bullish probability >50%, red bars for bearish <50%.
- On-chart labels: Showing exact buy/sell percentages on the last bar for quick reference.
Inputs
- EMA length (default 200), MACD settings, ADX period.
- Weights for each timeframe and component (trend, momentum, strength).
- Optional boost for the chart’s current timeframe.
- Smoothing length for probability values.
- Lookback period for support/resistance adjustment.
How to use it
- A green histogram above zero indicates bullish probability >50%.
- A red histogram below zero indicates bearish probability >50%.
- Neutral readings near 50% show low confluence and may be best avoided.
- Users can adjust weights to emphasize higher or lower timeframes, depending on their trading style.
Notes
- This script does not guarantee profitable trades.
- Best used together with price action, volume, or additional confirmation tools.
- Signals are calculated only on closed bars to avoid repainting.
- For testing and learning purposes — not financial advice.
RSI Pivots with Divergence Overlay█ OVERVIEW
The RSI Pivots with Divergence Overlay indicator is an advanced tool based on RSI, displaying dynamic bands on the price chart to simplify the identification of overbought and oversold conditions. Pivot points and divergences between them are derived from these bands, providing a comprehensive view of the market and enabling the creation of various trading strategies based on this single indicator.
█ CONCEPTS
Areas where RSI exits the bands are often reversal points in the market. The concept of this indicator is to highlight places where the probability of a trend reversal increases. Therefore, pivots and divergences have been added to better identify these key moments. Additionally, the bands allow viewing the market context in relation to the RSI indicator, facilitating analysis of momentum and volatility.
█ KEY FEATURES
Dynamic Bands and RSI Signals: The bands are calculated based on the closing price and RSI value, with dynamic scaling adjusted to market volatility. The upper band corresponds to overbought levels, the lower to oversold, and the midline is their average. The price level relative to the bands serves as a visual RSI signal, indicating potential overbought or oversold conditions.
Pivot Points: The indicator identifies local price highs and lows in relation to RSI levels. The pivot level is taken from the high/low of the candle. A high pivot is detected when the high of the candle reaches a local maximum after crossing the upper RSI level (overbought), signaling a potential reversal. A low pivot appears after a local price minimum following a drop below the lower RSI level (oversold), indicating a possible uptrend reversal. The pivot length (default 2 bars) defines the search range for these extremes, meaning that with a length of 2, a potential divergence signal will appear with a 2-candle delay, as this is the minimum time required to confirm a local pivot. Pivot lines are drawn on the chart, and labels display the RSI value (from the close of the candle) and price at the detection moment. Pivot lines disappear after the detection of the next low pivot for lower lines and high pivot for upper lines, but unbreached lines or those with high volume may still serve as support or resistance levels.
Divergence Detection: The indicator automatically detects divergences to predict trend changes. Bearish divergence occurs when the price forms a higher high pivot, but the RSI (from the close of the candle) is lower than in the previous pivot, indicating weakening upward momentum and a potential bearish reversal. Bullish divergence appears when the price forms a lower low pivot, but the RSI is higher, suggesting building momentum and a possible bullish reversal. Divergences are marked in pivot labels (e.g., "Bear Div" or "Bull Div") and supported by alerts upon detection.
Return Signals: The indicator generates buy and sell signals based on RSI (price) returning to the bands after extreme conditions, independently of pivots and divergences. A buy signal is triggered when RSI (price) crosses above the lower level (exiting oversold), suggesting a potential price rise toward the midline or upper band. A sell signal occurs when RSI (price) falls below the upper level (exiting overbought), indicating a possible price drop toward the lower band. Signals are visualized as arrows (up/down triangles) on the chart, with customizable colors.
█ CONFIGURATION
The indicator offers extensive customization options:
RSI Length (rsiLength): Sets the number of periods used to calculate RSI (default 14).
RSI Upper Level (rsiUpper): Defines the overbought threshold (default 70).
RSI Lower Level (rsiLower): Defines the oversold threshold (default 30).
Band Scaling (scale): Determines the scaling multiplier for bands based on market volatility (default 15.0).
SMA Length for Candle Midpoint (length): Number of periods for calculating the moving average of candle midpoints (default 200). This parameter is used to smooth price data, enabling more accurate volatility assessment and band width adjustment to market dynamics.
Pivot Length (pivotLength): Sets the range (in bars) for detecting local price extremes (default 2).
Pivot Label Offset (pivotLabelOffset): Multiplier for the candle range to position pivot labels (default 0.3).
Show Bands (showBands): Enables/disables the display of bands on the chart.
Show Fill (showFill): Enables/disables the fill between bands and the midline.
Show Pivot Lines (showPivotLines): Enables/disables pivot lines on the chart.
Show Pivot Labels (showPivotLabels): Enables/disables labels with RSI and price values at pivots.
Show Return Signals (showReturnSignals): Enables/disables the display of buy and sell signals.
Colors and Style: Customizable colors for bands, fills, pivot lines, labels, and line widths (default 1).
█ USAGE
The indicator performs best when combined with other technical analysis tools, such as Fibonacci levels, moving averages, or trendlines, to confirm pivot, divergence, and return signals. It enables traders to identify key reversal points, detect hidden trend weaknesses through divergences, and confirm trade entries with return signals.
Usage Examples:
Price bounces off a previous pivot with high volume – this increases the probability of a trend change or correction.
A similar situation when RSI is outside the bands strengthens the signal.
If divergence occurs in addition, we have further confirmation.
This can be combined with Fibonacci levels to check if Fibo zones overlap with pivot lines – this may increase the chance of a strong price reaction.
█ ALERTS
The indicator supports alerts for:
Buy and sell signals (RSI returning to bands).
Detection of bearish and bullish divergences.
RSI ALL INOverbought and Oversold with Candle Pattern Confluences
1. Overbought / Oversold signal only
2. RSI + Engulfing Candle
3. RSI + Hammer/Shooting Star
RSI ADX Bollinger Analysis High-level purpose and design philosophy
This indicator — RSI-ADX-Bollinger Analysis — is a compact, educational market-analysis toolkit that blends momentum (RSI), trend strength (ADX), volatility structure (Bollinger Bands) and simple volumetrics to provide traders a snapshot of market condition and trade idea quality. The design philosophy is explicit and layered: use each component to answer a different question about price action (momentum, conviction, volatility, participation), then combine answers to form a more robust, explainable signal. The mashup is intended for analysis and learning, not automatic execution: it surfaces the why behind signals so traders can test, learn and apply rules with risk management.
________________________________________
What each indicator contributes (component-by-component)
RSI (Relative Strength Index) — role and behavior: RSI measures short-term momentum by comparing recent gains to recent losses. A high RSI (near or above the overbought threshold) indicates strong recent buying pressure and potential exhaustion if price is extended. A low RSI (near or below the oversold threshold) indicates strong recent selling pressure and potential exhaustion or a value area for mean-reversion. In this dashboard RSI is used as the primary momentum trigger: it helps identify whether price is locally over-extended on the buy or sell side.
ADX (Average Directional Index) — role and behavior: ADX measures trend strength independently of direction. When ADX rises above a chosen threshold (e.g., 25), it signals that the market is trending with conviction; ADX below the threshold suggests range or weak trend. Because patterns and momentum signals perform differently in trending vs. ranging markets, ADX is used here as a filter: only when ADX indicates sufficient directional strength does the system treat RSI+BB breakouts as meaningful trade candidates.
Bollinger Bands — role and behavior: Bollinger Bands (20-period basis ± N standard deviations) show volatility envelope and relative price position vs. a volatility-adjusted mean. Price outside the upper band suggests pronounced extension relative to recent volatility; price outside the lower band suggests extended weakness. A band expansion (increasing width) signals volatility breakout potential; contraction signals range-bound conditions and potential squeeze. In this dashboard, Bollinger Bands provide the volatility/structural context: RSI extremes plus price beyond the band imply a stronger, volatility-backed move.
Volume split & basic MA trend — role and behavior: Buy-like and sell-like volume (simple heuristic using close>open or closeopen) or sell-like (close1.2 for validation and compare win rate and expectancy.
4. TF alignment: Accept signals only when higher timeframe (e.g., 4h) trend agrees — compare results.
5. Parameter sensitivity: Vary RSI threshold (70/30 vs 80/20), Bollinger stddev (2 vs 2.5), and ADX threshold (25 vs 30) and measure stability of results.
These exercises teach both statistical thinking and the specific failure modes of the mashup.
________________________________________
Limitations, failure modes and caveats (explicit & teachable)
• ADX and Bollinger measures lag during fast-moving news events — signals can be late or wrong during earnings, macro shocks, or illiquid sessions.
• Volume classification by open/close is a heuristic; it does not equal TAPEDATA, footprint or signed volume. Use it as supportive evidence, not definitive proof.
• RSI can remain overbought or oversold for extended stretches in persistent trends — relying solely on RSI extremes without ADX or BB context invites large drawdowns.
• Small-cap or low-liquidity instruments yield noisy band behavior and unreliable volume ratios.
Being explicit about these limitations is a strong point in a TradingView description — it demonstrates transparency and educational intent.
________________________________________
Originality & mashup justification (text you can paste)
This script intentionally combines classical momentum (RSI), volatility envelope (Bollinger Bands) and trend-strength (ADX) because each indicator answers a different and complementary question: RSI answers is price locally extreme?, Bollinger answers is price outside normal volatility?, and ADX answers is the market moving with conviction?. Volume participation then acts as a practical check for real market involvement. This combination is not a simple “indicator mashup”; it is a designed ensemble where each element reduces the others’ failure modes and together produce a teachable, testable signal framework. The script’s purpose is educational and analytical — to show traders how to interpret the interplay of momentum, volatility, and trend strength.
________________________________________
TradingView publication guidance & compliance checklist
To satisfy TradingView rules about mashups and descriptions, include the following items in your script description (without exposing source code):
1. Purpose statement: One or two lines describing the script’s objective (educational multi-indicator market overview and idea filter).
2. Component list: Name the major modules (RSI, Bollinger Bands, ADX, volume heuristic, SMA trend checks, signal tracking) and one-sentence reason for each.
3. How they interact: A succinct non-code explanation: “RSI finds momentum extremes; Bollinger confirms volatility expansion; ADX confirms trend strength; all three must align for a BUY/SELL.”
4. Inputs: List adjustable inputs (RSI length and thresholds, BB length & stddev, ADX threshold & smoothing, volume MA, table position/size).
5. Usage instructions: Short workflow (check TF alignment → confirm participation → define stop & R:R → backtest).
6. Limitations & assumptions: Explicitly state volume is approximated, ADX has lag, and avoid promising guaranteed profits.
7. Non-promotional language: No external contact info, ads, claims of exclusivity or guaranteed outcomes.
8. Trademark clause: If you used trademark symbols, remove or provide registration proof.
9. Risk disclaimer: Add the copy-ready disclaimer below.
This matches TradingView’s request for meaningful descriptions that explain originality and inter-component reasoning.
________________________________________
Copy-ready short publication description (paste into TradingView)
Advanced RSI-ADX-Bollinger Market Overview — educational multi-indicator dashboard. This script combines RSI (momentum extremes), Bollinger Bands (volatility envelope and band expansion), ADX (trend strength), simple SMA trend bias and a basic buy/sell volume heuristic to surface high-quality idea candidates. Signals require alignment of momentum, volatility expansion and rising ADX; volume participation is displayed to support signal confidence. Inputs are configurable (RSI length/levels, BB length/stddev, ADX length/threshold, volume MA, display options). This tool is intended for analysis and learning — not for automated execution. Users should back test and apply robust risk management. Limitations: volume classification here is a heuristic (close>open), ADX and BB measures lag in fast news events, and results vary by instrument liquidity.
________________________________________
Copy-ready risk & misuse disclaimer (paste into description or help file)
This script is provided for educational and analytical purposes only and does not constitute financial or investment advice. It does not guarantee profits. Indicators are heuristics and may give false or late signals; always back test and paper-trade before using real capital. The author is not responsible for trading losses resulting from the use or misuse of this indicator. Use proper position sizing and risk controls.
________________________________________
Risk Disclaimer: This tool is provided for education and analysis only. It is not financial advice and does not guarantee returns. Users assume all risk for trades made based on this script. Back test thoroughly and use proper risk management.
Daily Percentiles ZoneDaily Percentiles Zone
Shows the distance of price from the 200-day EMA and classifies it into historical percentiles (P25, P50, P65, P76). Helps identify whether the asset is cheap, fair value, acceptable, risky, or very expensive compared to its long-term daily trend.