Williams AD + MA“I’ve added an MA to the Williams Accumulation/Distribution (AD) indicator. You can use it to infer potential trend inflection points and to assess the persistence of the trend.”
M-oscillator
Nic RSI + MACD (single pane)📊 SPACE-SAVING COMBINED INDICATOR FOR FREE USERS
This indicator combines RSI and MACD into a single pane, perfect for TradingView users with limited indicator slots. Designed to match the default TradingView styling you're familiar with.
🎯 USE AS A PACKAGE:
For optimal trading analysis, use this indicator together with "Nic SMA 9, SMA 200, 9 count" which displays moving averages and the 9 count on your main chart. Together, these two indicators give you a complete technical analysis setup while staying within the 2-3 indicator limit for free TradingView accounts.
📈 WHAT'S INCLUDED:
✅ RSI (Relative Strength Index) - Top Section:
• Default purple line matching TradingView's built-in RSI
• Reference lines at 30, 50, and 70 levels
• Background shading for overbought (>70) and oversold (<30) zones
• Takes up 55% of the pane for better visibility
• Fully customizable period (default: 14)
✅ MACD (Moving Average Convergence Divergence) - Bottom Section:
• Classic histogram with TradingView's default color scheme:
- Teal/cyan for positive momentum
- Red/pink for negative momentum
• Blue MACD line and orange Signal line
• Clear zero line for easy reference
• Takes up 45% of the pane
• Fully customizable periods (default: 12, 26, 9)
⚙️ CUSTOMIZATION OPTIONS:
• Adjust RSI length and source
• Customize RSI line color
• Adjust MACD fast, slow, and signal periods
• Customize MACD source
• Modify gap size between RSI and MACD sections
💡 WHY USE THIS?
• Saves indicator slots - combines 2 indicators into 1
• Professional appearance matching TradingView defaults
• Clean, uncluttered display
• All the functionality of separate RSI and MACD indicators
• Perfect for traders on free or limited plans
📋 RECOMMENDED SETUP:
1. Add "Nic SMA 9, SMA 200, 9 count" to your main chart (published separately)
2. Add this "Nic RSI top + MACD bottom" indicator
3. Optionally add Volume indicator if you have a slot available
This gives you moving averages, the 9 count, RSI, and MACD - everything you need for comprehensive technical analysis!
🔔 WORKS WITH FREE ACCOUNTS:
Both indicators in the Nic package are designed to maximize your analysis capabilities within TradingView's indicator limits.
#RSI #MACD #TechnicalAnalysis #FreeIndicators #SpaceSaving #CombinedIndicator
MCL RSI Conflux v2.5 — Multi-Timeframe Momentum & Z-Score Full Description
Overview
The MCL RSI Conflux v2.5 is a multi-timeframe momentum model that integrates daily, weekly, and monthly RSI values into a unified composite. It extends the classical RSI framework with adaptive overbought/oversold thresholds and statistical normalization (Z-score confluence).
This combination allows traders to visualize cross-timeframe alignment, identify synchronized momentum shifts, and detect exhaustion zones with higher statistical confidence.
Methodology
The script extracts RSI data from three major time horizons:
Daily RSI (short-term momentum)
Weekly RSI (intermediate trend)
Monthly RSI (macro bias)
Each RSI is optionally smoothed, weighted, and aggregated into a Composite RSI.
A Z-score transformation then measures how far each RSI deviates from its historical mean, revealing when momentum strength is statistically extreme or aligned across timeframes.
Key Features
Multi-Timeframe RSI Engine – Computes RSI across D/W/M intervals with individual weighting controls.
Adaptive Overbought/Oversold Bands – Automatically adjusts OB/OS thresholds based on rolling volatility (standard deviation of daily RSI).
Composite RSI Score – Weighted consensus RSI that represents total market momentum.
Z-Score Confluence Analysis – Identifies when all three timeframes are statistically synchronized.
Z-Composite Histogram – Displays aggregated Z-score strength around the midline (50).
Divergence Detection – Flags confirmed pivot-based bull and bear divergences on the daily RSI.
Dynamic Gradient Background – Shifts from red to green based on composite momentum regime.
Customizable Control Panel – Displays RSI values, Z-scores, state, and adaptive bands for each timeframe.
Integrated Alerts – For crossovers, risk-on/off thresholds, alignment, and Z-confluence events.
Interpretation
All RSI values above 50: multi-timeframe bullish alignment.
All RSI values below 50: multi-timeframe bearish alignment.
Composite RSI > 60: risk-on environment; momentum expansion.
Composite RSI < 45: risk-off environment; momentum contraction.
Adaptive OB/OS hits: potential exhaustion or mean reversion setup.
Green Z-ribbon: all Z-scores positive and aligned (statistical confirmation).
Red Z-ribbon: all Z-scores negative and aligned (broad market weakness).
Divergences: short-term warning signals against the prevailing momentum bias.
Practical Application
Use the Composite RSI as a global momentum gauge for position bias.
Trade only in the direction of higher-timeframe alignment (avoid countertrend RSI).
Combine Z-ribbon confirmation with Composite RSI crosses to filter noise.
Use divergence labels and adaptive thresholds for risk reduction or exit timing.
Ideal for swing traders and macro momentum models seeking trend synchronization filters.
Recommended Settings
Market Mode k-Band Lookback Use Case
Stocks / ETFs Adaptive 0.85 200 Medium-term rotation filter
Crypto Adaptive 1.00 150 Volatility-responsive swing filter
Commodities Fixed 70/30 100 Mean reversion model
Alerts Included
Daily RSI crossed above/below Weekly RSI
Composite RSI > Risk-On threshold
Composite RSI < Risk-Off threshold
All RSI aligned above/below 50
Z-Score Conformity (All positive or all negative)
Overbought/Oversold triggers
Author’s Note
This indicator was designed for research and systematic confluence analysis within Mongoose Capital Labs.
It is not financial advice and should be used in combination with independent risk assessment, volume confirmation, and higher-timeframe context.
Ultimate MACD Suite [BigBeluga]🔵 OVERVIEW
The Ultimate MACD Suite is an advanced momentum-based system that enhances the classic MACD with modern features tailored for professional traders.
It transforms MACD into a full market-decision engine — offering multi-timeframe confluence, adaptive histogram behavior, divergence detection, heatmap trend visualization, and actionable reversal signals.
This toolkit goes far beyond standard MACD, helping traders identify trend momentum shifts, exhaustion zones, high-probability reversal areas, and breakout confirmation signals across multiple timeframes simultaneously. It's to be used as part of a major trading system and to simplify usage of the MACD.
⚠️ Note:
This is not a traditional MACD — it uses normalized values , enhanced visual feedback, and a multi-timeframe dashboard engine for superior signal quality and clarity.
🔵 CONCEPTS
Combines MACD momentum, signal-line crossovers, and histogram reversals into one system
Uses normalized scaling to detect extreme momentum levels and exhaustion zones
Multi-timeframe dashboard displays consensus signal alignment across several timeframes
Divergence engine identifies bullish & bearish trend weakening early
Heatmap mode visually distinguishes strong trend phases from neutral or fading momentum
Reversal arrows & crosses highlight actionable turning points on chart
🔵 FEATURES
Normalized MACD Engine — improves signal clarity across all assets/timeframes
MACD Heatmap Mode — color-coded slope intensity for trend strength monitoring
MACD Rising and Falling Mode — color-coded rising and falling MACD regimes
Histogram Reversal Detection — early momentum fade signal before price turns
Signal-Line Momentum Shifts — bullish ▲ & bearish ▼ alerts on cross-confirmation
Overbought/Oversold Bands — enhanced visual thresholds at ±80 levels
Smart Divergence Detection (Non-Lag) — confirms regular bullish & bearish divergences
Multi-Timeframe Dashboard — MACD, signal, histogram & divergence signals across 5+ TFs
Reversal Push-Filter — ensures only clean signals after confirmed momentum inflection
On-Chart Reversal Labels — optional compact signal markers for clean visual execution
Histogram Color Logic — rising/falling or heatmap mode for deeper momentum reading
🔵 HOW TO USE
Look for MACD crossing above signal + green histogram to confirm bullish momentum
Use ▼ and ▲ arrows to catch confirmed momentum reversals
Monitor the dashboard — the more timeframes align, the stronger the setup
Watch divergences for trend exhaustion or reversal setups
Treat histogram trend shifts as early momentum clues before price reacts
Use ±80 levels to identify overheated conditions & fade opportunities
Combine with structure, volume, or BigBeluga liquidity tools for higher accuracy
🔵 ALERTS
The indicator includes a full alert suite for automation and real-time trade readiness:
MACD crossovers (Bullish / Bearish)
Histogram reversals & zero-line shifts
Bullish / Bearish divergence detection
Overbought / Oversold MACD alerts
Bullish ▲ and bearish ▼ reversal triggers
Use these alerts to automate signal monitoring or feed algorithmic systems.
🔵 CONCLUSION
The Ultimate MACD Suite transforms a classic indicator into a powerful trading engine.
With multi-timeframe alignment, heatmapping, divergence logic, normalized scaling and automated signals, it becomes an elite momentum-confirmation and reversal-timing system built for serious traders.
Whether scalping intraday or managing swing positions, this MACD engine helps identify the most profitable phases of trend movement — while warning early when a trend is weakening.
Script de pago
Local Hurst Slope [Dynamic Regime]1. HOW THE INDICATOR WORKS (Math → Market Edge)Step
Math
Market Intuition
1. Log-Returns
r_t = log(P_t / P_{t-1})
Removes scale, makes series stationary
2. R/S per τ
R = max(cum_dev) - min(cum_dev)
S = stdev(segment)
Measures memory strength over window τ
3. H(τ) = log(R/S) / log(τ)
Di Matteo (2007)
H > 0.5 → Trend memory
H < 0.5 → Mean-reversion
4. Slope = dH/d(log τ)
Linear regression of H vs log(τ)
Slope > 0.12 → Trend accelerating
Slope < -0.08 → Reversion emerging
LEADING EDGE: The slope changes 3–20 bars BEFORE price confirms
→ You enter before the crowd, exit before the trap
Slope > +0.12 + Strong Trend = Bullish = Long
Slope +0.05 to +0.12 = Weak Trend = Cautious = Hold/Trail
Slope -0.05 to +0.05 = Random = No Edge
Slope-0.08 to -0.05 = Weak Reversion = Bearish setup = Prepare Short
Slope < -0.08 = Strong Reversion = Bearish= Short
PRO TIPS
Only trade in direction of 200-day SMA
Filters false signals
Avoid trading 3 days before/after earnings
Volatility kills edge
Use on ETFs (SPY, QQQ)
Cleaner than single stocks
Combine with RSI(14)
RSI < 30 + Hurst short = nuclear reversal
Crypto Breadth Engine [alex975]
A normalized crypto market breadth indicator with a customizable 40 coin input panel — revealing whether rallies are broad and healthy across major coins and altcoins or led by only a few.
📊 Overview
The Crypto Breadth Engine measures the real participation strength of the crypto market by analyzing the direction of the 40 largest cryptocurrencies by market capitalization.
⚙️ How It Works
Unlike standard breadth tools that only count assets above a moving average, this indicator measures actual price direction:
+1 if a coin closes higher, –1 if lower, 0 if unchanged.
The total forms a Breadth Line, statistically normalized using standard deviation to maintain consistent readings across timeframes and volatility conditions.
🧩 Dynamic Input Mask
All 40 cryptocurrencies are fully editable via the input panel, allowing users to easily replace or customize the basket (Top 40, Layer-1s, DeFi, Meme Coins, AI Tokens, etc.) without touching the code.
This flexibility keeps the indicator aligned with the evolving crypto market.
🧭 Trend Bias
The indicator classifies market structure as Bullish, Neutral, or Bearish, based on how the Breadth Line aligns with its moving averages (10, 20, 50).
💡 Dashboard
A compact on-chart table displays in real time:
• Positive and negative coins
• Participation percentage
• Current trend bias
🔍 Interpretation
• Rising breadth → broad, healthy market expansion
• Falling breadth → narrowing participation and structural weakness
Ideal for TOTAL, TOTAL3, or custom crypto baskets on 1D,1W.
Developed by alex975 – Version 1.0 (2025).
-------------------------------------------------------------------------------------
🇮🇹 Versione Italiana
📊 Panoramica
Il Crypto Breadth Engine misura la partecipazione reale del mercato crypto, analizzando la direzione delle 40 principali criptovalute per capitalizzazione.
Non si limita a contare quante coin sono sopra una media mobile, ma calcola la variazione effettiva del prezzo:
+1 se sale, –1 se scende, 0 se invariato.
La somma genera una Breadth Line normalizzata statisticamente, garantendo letture coerenti su diversi timeframe e fasi di volatilità.
🧩 Mascherina dinamica
L’indicatore include una mascherina d’input interattiva che consente di modificare o sostituire liberamente i 40 ticker analizzati (Top 40, Layer-1, DeFi, Meme Coin, ecc.) senza intervenire nel codice.
Questo lo rende sempre aggiornato e adattabile all’evoluzione del mercato crypto.
⚙️ Funzionamento e Trend Bias
Classifica automaticamente il mercato come Bullish, Neutral o Bearish in base alla relazione tra la breadth e le medie mobili (10, 20, 50 periodi).
💡 Dashboard
Una tabella compatta mostra in tempo reale:
• Numero di coin positive e negative
• Percentuale di partecipazione
• Stato attuale del trend
🔍 Interpretazione
• Breadth in crescita → mercato ampio e trend sano
• Breadth in calo → partecipazione ridotta e concentrazione su pochi asset
Ideale per analizzare TOTAL, TOTAL3 o panieri personalizzati di crypto.
Funziona su timeframe 1D, 4H, 1W.
Sviluppato da alex975 – Versione 1.0 (2025).
VIX OscillatorVIX Oscillator for catching vol signals on the same chart as your index of choice.
- Configurable levels that alert you when certain thresholds are broken
- Shaded background that make it simple to tell when you are in low vol/high vol regimes
- Moving line tracking price so that you can easily see bull/bear divergences against SPX building
TICK OscillatorOscillator that makes it easy to see when TICK is hitting extreme readings or establishing a bullish/bearish divergence vs the indices.
- Green coloration means a reading of >+400
- Red coloration means a reading of <-400
- Orange means a reading in between -400 and +400
This was inspired by John F Carter's book "Mastering The Trade", where I first learned about utilizing TICK in my trading.
Momentum Pro [FluxQuant]Momentum Pro — Adaptive Momentum & Regime Filter
Overview
Momentum Pro is a next-generation oscillator that combines rate-of-change (ROC), relative-strength (RSI), and stochastic-momentum frameworks into a unified adaptive model. It dynamically filters momentum through volatility, directional-movement, and trend-strength conditions to highlight only qualified signals in changing market regimes.
🔹 Key Features
Selectable Core Algorithm: Choose between ROC, RSI, or Stochastic momentum engines
Adaptive Signal System: Cross-based entries gated by volatility and trend filters
Quality Filters: Volatility, momentum intensity, and directional bias validation
Overbought / Oversold Zones: Automatic detection with background visualization
Multi-Timeframe Sync: Confirm intraday signals with higher-timeframe momentum
Divergence Scanner: Pivot-based detection of regular bullish / bearish divergences
Smart Dashboard: Real-time summary of market state, momentum strength, and filter status
Dynamic Visual Themes: Gradient, Premium, and Glassmorphism histogram modes
🧠 How It Works
Momentum Pro calculates normalized momentum using your selected algorithm and applies layered filters to ensure that only statistically significant moves are emphasized.
The volatility filter measures current vs. average ATR to confirm expansion.
The trend filter assesses DI +/ DI – differentials for directional bias.
The momentum gate suppresses signals during consolidation or low-range conditions.
Optional higher-timeframe data aligns local momentum with broader bias for cleaner entries.
When these filters agree, momentum crossovers or divergences are visually highlighted as potential study points — not trade instructions.
📈 Interpreting the Dashboard
Field Meaning
Market State Identifies current regime (Bullish, Bearish, Overbought, Oversold, Ranging)
Momentum Current oscillator value (0–100 normalized scale)
Change Recent acceleration / deceleration in momentum
Filter Whether volatility and trend criteria are satisfied
Signal Active cross or directional alignment
Trend / Vol / Intensity Strength metrics (Elite mode)
HTF Sync Confirms alignment with higher-timeframe momentum bias
Use the dashboard as a contextual overlay — not as a mechanical signal generator.
🧩 Configuration Guide
Algorithm: Select ROC for reactive speed, RSI for balanced smoothness, or Stochastic for cyclical range focus.
Signal Line: Enable to visualize crossovers. “Glow” style enhances contrast for clarity.
Filters: Keep “Enable Filter” active to limit noise. Adjust Volatility & Trend thresholds for sensitivity.
Zones: Use background fills to mark overbought / oversold regions and regime shifts.
Divergence: Turn on for automatic pivot-based divergence marking.
Multi-Timeframe: Enable HTF confirmation to study alignment with larger trend context.
Dashboard: Choose Minimal → Elite modes depending on information density preference.
🧭 Best Practices
Works on all markets — equities, futures, crypto, FX
Ideal for 15 m – 4 h – Daily timeframes
Pairs well with structure or liquidity analysis for confirmation
Use filters to isolate expansion phases; avoid trading during neutral states
⚠️ Disclaimer
Momentum Pro is an educational and analytical tool intended for research and visualization only.
It does not provide financial advice, trade signals, or guaranteed outcomes.
Always conduct independent analysis and risk assessment before making trading decisions.
🛠 Release Notes
v 1.0 — Initial Public Release
Multi-algorithm momentum core (ROC / RSI / Stochastic)
Volatility + trend quality filter system
Multi-timeframe synchronization and ribbon overlay
Divergence scanner and contextual dashboard
Dynamic visualization modes
SZS Slow StochasticThe SZS Slow Stochastic is a custom momentum indicator that blends the classic Slow Stochastic Oscillator with a dynamic RSI overlay and enhanced visual cues for overbought and oversold conditions.
This indicator helps identify potential trend reversals, momentum shifts, and exhaustion points in price movements.
Features
Slow Stochastic Calculation
Uses customizable %K and %D periods to measure momentum and potential turning points in price action.
%K Range: default 14
%D Period: default 3
Visual Extremes Highlighting
The plot line dynamically changes color to indicate:
🔴 Overbought Zone (%K ≥ 85)
🔵 Oversold Zone (%K ≤ 15)
⚪ Neutral Zone (between 15 and 85)
Diamond markers appear when %K exits the overbought/oversold regions to visually flag possible reversals.
RSI Momentum Overlay
The RSI (Relative Strength Index) is plotted alongside, colored based on recent momentum extremes:
🟢 RSI has touched above 75 within recent bars → bullish momentum bias
🔴 RSI has touched below 25 within recent bars → bearish momentum bias
Shaded Signal Zones
The area between the 85 and 15 levels is shaded according to current stochastic conditions:
Red shading → overbought pressure
Blue shading → oversold pressure
Alerts Ready
Upper and lower band crossing conditions are included for easy alert configuration.
Usage Tips
Look for color changes and diamond markers as potential early warnings of momentum reversals.
When both Stochastic and RSI show aligned signals (e.g. both indicating overbought or oversold), it strengthens the reversal or continuation signal.
Combine with price structure or volume indicators for higher confidence setups.
Stochastic x11change the multi TF SETTINGS
CHANGE THE COLOR
This indicator is for multiTF anlysis and the indicator by itself in only one setting identifies the reversal point at a time. much so can do with ibndicators that can identify multpile tf settings this can help a lot
[S]Hurst Cycle Channel Clone Oscillator [LazyBear] — v6 CleanHurst Cycle Channel Clone Oscillator — v6 Clean
Overview
This is a modernized and refactored version of LazyBear's popular Hurst Cycle Channel Clone Oscillator, updated to Pine Script v6 with improved readability, proper input grouping, and enhanced code structure. This indicator helps traders identify cyclical price movements and potential reversal points based on J.M. Hurst's cycle analysis principles.
What It Does
The indicator creates two normalized oscillators that measure price position relative to dynamic channel envelopes:
Fast Oscillator (Red): Tracks short-term cycle movements based on current price position
Slow Oscillator (Green): Tracks medium-term cycle momentum based on the short cycle's midpoint
Both oscillators are normalized between 0.0 and 1.0, making overbought/oversold conditions easy to identify:
Above 1.0 = Overbought territory (purple histograms)
0.5 = Neutral midpoint
Below 0.0 = Oversold territory (purple histograms)
Key Features
✓ Dual-Timeframe Cycle Analysis: Combines short and medium cycle lengths for comprehensive market rhythm detection
✓ ATR-Based Dynamic Channels: Automatically adjusts to market volatility
✓ Clear Visual Signals: Histogram bars highlight extreme overbought/oversold conditions
✓ Customizable Parameters: Adjust cycle lengths and multipliers to match your trading style
✓ Built-in Alert Conditions: Get notified on key crossover events
✓ Optional Bar Coloring: Visual price bar colors based on oscillator position
How to Use
Basic Interpretation:
Fast crosses below 0.0 → Potential BUY opportunity (oversold)
Fast crosses above 1.0 → Potential SELL opportunity (overbought)
Fast crosses Slow → Momentum shift indication
Purple histograms → Extreme conditions requiring attention
Best Practices:
Use in conjunction with price action and trend analysis
Look for divergences between price and oscillator
Pay attention when both oscillators reach extremes simultaneously
Adjust cycle lengths to match the asset's dominant cycle period
Settings
Cycle Lengths:
Short Cycle Length (default: 10) — Fast oscillator sensitivity
Medium Cycle Length (default: 30) — Slow oscillator smoothing
Multipliers:
Short Cycle Multiplier (default: 1.0) — Controls short channel width
Medium Cycle Multiplier (default: 1.8) — Controls medium channel width
Alerts:
Pre-configured alert conditions for all major crossover events
Credits
Original indicator by LazyBear
This is a clean refactor maintaining the original logic while improving code quality and Pine Script version compliance.
Multi-Timeframe RSI TableIt can print RSI values of any four chosen periods in a tabular format on the chart itself. The table can be placed in any of the six positions, as required. If the RSI values are more than 40 or less than 40, these values are shown in bright Red, else it is light Red.
Rate Of Change📊 הסבר על האינדיקטור | Indicator Explanation
עברית:
1️⃣ VWAP של שינוי המחיר: מחשב ממוצע משוקלל לפי נפח (VWAP) של ההפרש בין מחיר הסגירה הנוכחי למחיר לפני כחודש – מאפשר להבין אם המחיר נע מעל או מתחת לממוצע האחרון.
2️⃣ קצב שינוי (ROC) ממוצע: מודד את אחוז השינוי במחיר לאורך 8 נרות, ואז מחשב עליו VWAP כדי להחליק תנודות חדות.
🟢 הקו הכתום מייצג את ה-VWAP של קצב השינוי, והקו השני את ערכי ה-ROC עצמם.
ב"ה בעתיד אצור גרסה דינמית שתאפר למשתמש לשלוט יותר בכלי הזה.
English:
1️⃣ VWAP of Price Difference: Calculates a volume-weighted average (VWAP) of the difference between the current close price and the close from Month ago — showing if the price is trending above or below its recent average.
2️⃣ Smoothed Rate of Change (ROC): Measures the 8-bar price change percentage, then smooths it with VWAP to reduce noise and highlight the trend direction.
🟢 The orange line shows the VWAP of the ROC, while the other line shows the raw ROC values.
next Version be with GUI improvements stat tuned :)
VTTOS — Volatility & Trend Transition OscillatorShort Description (one-line summary)
Displays volatility-based trend transitions using EMA relationships and adaptive percentile thresholds.
Full Description
Overview
A framework for studying volatility transitions and market phase shifts through adaptive EMA relationships.
VTTOS (Volatility & Trend Transition Oscillator System) is a technical-analysis framework that displays market behavior through volatility dynamics and EMA-based motion.
It is designed to support technical analysis and enhance market context interpretation.
VTTOS uses percentile thresholds derived from past volatility ranges to help identify transitions between trending and ranging market phases.
The indicator is built for traders who prefer to interpret market structure through volatility expansion and contraction, using clear visual markers to highlight possible sequence changes.
________________________________________
What Makes This Script Distinct
VTTOS applies adaptive percentile thresholds calculated from recent Tug Line and Tanker Line movements.
These thresholds automatically adjust based on recent data, allowing the plotted tags to represent potential market phases dynamically.
The focus is not on the EMA lines themselves, but on how price interacts relative to the percentile thresholds.
This integrated approach provides a structured volatility-based framework for contextual analysis.
________________________________________
Core Components
• Tug Line – Represents relative volatility derived from smoothed EMA relationships.
• Tanker Line – A slower baseline signal reflecting broader directional pressure.
• Threshold Bands – Adaptive percentile levels computed from recent pivot ranges.
• Sequence Markers – Numbered, colored labels that display phase progressions within the current trend.
• Multi-Market Compatibility – Can be applied to any asset or timeframe.
________________________________________
How to Read It
• When the Tug Line crosses above or below the percentile thresholds, the oscillator enters a new phase.
• Colored sequence labels display ongoing trend transitions (e.g., blue → orange → green for uptrends, purple → orange → green for downtrends).
• Opposite-side conditions automatically reset sequences to maintain clarity during volatile periods.
________________________________________
Usage Notes
• VTTOS does not generate trade entries, exit signals, or financial recommendations.
• Red or green labels only display possible late-phase conditions within a trend.
• X labels indicate when the oscillator crosses the zero line, visually marking a potential phase transition.
• All visuals are intended for analytical and educational purposes only.
• Users are encouraged to integrate VTTOS within their own analytical or confirmation framework.
• Numerical labels are iterative and do not carry standalone predictive meaning.
• The distance between the Tanker Line and percentile bands can help display relative trend strength visually, but it should not be interpreted as a forecast or signal.
________________________________________
Access
This is an invite-only script.
Access is restricted to users who have been granted permission by the author.
To request access, please use the standard “Request access” button on the indicator’s TradingView page.
Approved users will find the indicator under Invite-only scripts in the TradingView Indicators panel.
________________________________________
Disclaimer
VTTOS is provided strictly for informational and educational purposes.
It does not constitute financial advice, investment guidance, or performance assurance.
All users should conduct independent analysis and manage their own risk responsibly.
CVD Divergence ISAK EditedCVD Divergence with Price Lines
This indicator automatically detects **divergences between Price and CVD (Cumulative Volume Delta)** directly on the chart.
It supports multiple CVD periods (5, 7, 14, 21, 28) and visually displays divergence lines on price action.
**Features:**
* Detects 🟢 *Bullish* and 🔴 *Bearish* divergences
* Supports *Periodic* and *EMA* calculation modes
* Volume filter for stronger divergence signals
* Price labels and divergence lines for clarity
* Built-in alerts for new divergence detections
Ideal for **scalping and intraday trading** (1m–1h timeframes).
Manifold Singularity EngineManifold Singularity Engine: Catastrophe Theory Detection Through Multi-Dimensional Topology Analysis
The Manifold Singularity Engine applies catastrophe theory from mathematical topology to multi-dimensional price space analysis, identifying potential reversal conditions by measuring manifold curvature, topological complexity, and fractal regime states. Unlike traditional reversal indicators that rely on price pattern recognition or momentum oscillators, this system reconstructs the underlying geometric surface (manifold) that price evolves upon and detects points where this topology undergoes catastrophic folding—mathematical singularities that correspond to forced directional changes in price dynamics.
The indicator combines three analytical frameworks: phase space reconstruction that embeds price data into a multi-dimensional coordinate system, catastrophe detection that measures when this embedded manifold reaches critical curvature thresholds indicating topology breaks, and Hurst exponent calculation that classifies the current fractal regime to adaptively weight detection sensitivity. This creates a geometry-based reversal detection system with visual feedback showing topology state, manifold distortion fields, and directional probability projections.
What Makes This Approach Different
Phase Space Embedding Construction
The core analytical method reconstructs price evolution as movement through a three-dimensional coordinate system rather than analyzing price as a one-dimensional time series. The system calculates normalized embedding coordinates: X = normalize(price_velocity, window) , Y = normalize(momentum_acceleration, window) , and Z = normalize(volume_weighted_returns, window) . These coordinates create a trajectory through phase space where price movement traces a path across a geometric surface—the market manifold.
This embedding approach differs fundamentally from traditional technical analysis by treating price not as a sequential data stream but as a dynamical system evolving on a curved surface in multi-dimensional space. The trajectory's geometric properties (curvature, complexity, folding) contain information about impending directional changes that single-dimension analysis cannot capture. When this manifold undergoes rapid topological deformation, price must respond with directional change—this is the mathematical basis for catastrophe detection.
Statistical normalization using z-score transformation (subtracting mean, dividing by standard deviation over a rolling window) ensures the coordinate system remains scale-invariant across different instruments and volatility regimes, allowing identical detection logic to function on forex, crypto, stocks, or indices without recalibration.
Catastrophe Score Calculation
The catastrophe detection formula implements a composite anomaly measurement combining multiple topology metrics: Catastrophe_Score = 0.45×Curvature_Percentile + 0.25×Complexity_Ratio + 0.20×Condition_Percentile + 0.10×Gradient_Percentile . Each component measures a distinct aspect of manifold distortion:
Curvature (κ) is computed using the discrete Laplacian operator: κ = √ , which measures how sharply the manifold surface bends at the current point. High curvature values indicate the surface is folding or developing a sharp corner—geometric precursors to catastrophic topology breaks. The Laplacian measures second derivatives (rate of change of rate of change), capturing acceleration in the trajectory's path through phase space.
Topological Complexity counts sign changes in the curvature field over the embedding window, measuring how chaotically the manifold twists and oscillates. A smooth, stable surface produces low complexity; a highly contorted, unstable surface produces high complexity. This metric detects when the geometric structure becomes informationally dense with multiple local extrema, suggesting an imminent topology simplification event (catastrophe).
Condition Number measures the Jacobian matrix's sensitivity: Condition = |Trace| / |Determinant|, where the Jacobian describes how small changes in price produce changes in the embedding coordinates. High condition numbers indicate numerical instability—points where the coordinate transformation becomes ill-conditioned, suggesting the manifold mapping is approaching a singularity.
Each metric is converted to percentile rank within a rolling window, then combined using weighted sum. The percentile transformation creates adaptive thresholds that automatically adjust to each instrument's characteristic topology without manual recalibration. The resulting 0-100% catastrophe score represents the current bar's position in the distribution of historical manifold distortion—values above the threshold (default 65%) indicate statistically extreme topology states where reversals become geometrically probable.
This multi-metric ensemble approach prevents false signals from isolated anomalies: all four geometric features must simultaneously indicate distortion for a high catastrophe score, ensuring only true manifold breaks trigger detection.
Hurst Exponent Regime Classification
The Hurst exponent calculation implements rescaled range (R/S) analysis to measure the fractal dimension of price returns: H = log(R/S) / log(n) , where R is the range of cumulative deviations from mean and S is the standard deviation. The resulting value classifies market behavior into three fractal regimes:
Trending Regime (H > 0.55) : Persistent price movement where future changes are positively correlated with past changes. The manifold exhibits directional momentum with smooth topology evolution. In this regime, catastrophe signals receive 1.2× confidence multiplier because manifold breaks in trending conditions produce high-magnitude directional changes.
Mean-Reverting Regime (H < 0.45) : Anti-persistent price movement where future changes tend to oppose past changes. The manifold exhibits oscillatory topology with frequent small-scale distortions. Catastrophe signals receive 0.8× confidence multiplier because reversal significance is diminished in choppy conditions where the manifold constantly folds at minor scales.
Random Walk Regime (H ≈ 0.50) : No statistical correlation in returns. The manifold evolution is geometrically neutral with moderate topology stability. Standard 1.0× confidence multiplier applies.
This adaptive weighting system solves a critical problem in reversal detection: the same geometric catastrophe has different trading implications depending on the fractal regime. A manifold fold in a strong trend suggests a significant reversal opportunity; the same fold in mean-reversion suggests a minor oscillation. The Hurst-based regime filter ensures detection sensitivity automatically adjusts to market character without requiring trader intervention.
The implementation uses logarithmic price returns rather than raw prices to ensure
stationarity, and applies the calculation over a configurable window (default 5 bars) to balance responsiveness with statistical validity. The Hurst value is then smoothed using exponential moving average to reduce noise while maintaining regime transition detection.
Multi-Layer Confirmation Architecture
The system implements five independent confirmation filters that must simultaneously validate
before any singularity signal generates:
1. Catastrophe Threshold : The composite anomaly score must exceed the configured threshold (default 0.65 on 0-1 scale), ensuring the manifold distortion is statistically extreme relative to recent history.
2. Pivot Structure Confirmation : Traditional swing high/low patterns (using ta.pivothigh and ta.pivotlow with configurable lookback) must form at the catastrophe bar. This ensures the geometric singularity coincides with observable price structure rather than occurring mid-swing where interpretation is ambiguous.
3. Swing Size Validation : The pivot magnitude must exceed a minimum threshold measured in ATR units (default 1.5× Average True Range). This filter prevents signals on insignificant price jiggles that lack meaningful reversal potential, ensuring only substantial swings with adequate risk/reward ratios generate signals.
4. Volume Confirmation : Current volume must exceed 1.3× the 20-period moving average, confirming genuine market participation rather than low-liquidity price noise. Manifold catastrophes without volume support often represent false topology breaks that don't translate to sustained directional change.
5. Regime Validity : The market must be classified as either trending (ADX > configured threshold, default 30) or volatile (ATR expansion > configured threshold, default 40% above 30-bar average), and must NOT be in choppy/ranging state. This critical filter prevents trading during geometrically unfavorable conditions where edge deteriorates.
All five conditions must evaluate true simultaneously for a signal to generate. This conjunction-based logic (AND not OR) dramatically reduces false positives while preserving true reversal detection. The architecture recognizes that geometric catastrophes occur frequently in noisy data, but only those catastrophes that align with confirming evidence across price structure, participation, and regime characteristics represent tradable opportunities.
A cooldown mechanism (default 8 bars between signals) prevents signal clustering at extended pivot zones where the manifold may undergo multiple small catastrophes during a single reversal process.
Direction Classification System
Unlike binary bull/bear systems, the indicator implements a voting mechanism combining four
directional indicators to classify each catastrophe:
Pivot Vote : +1 if pivot low, -1 if pivot high, 0 otherwise
Trend Vote : Based on slow frequency (55-period EMA) slope—+1 if rising, -1 if falling, 0 if flat
Flow Vote : Based on Y-gradient (momentum acceleration)—+1 if positive, -1 if negative, 0 if neutral
Mid-Band Vote : Based on price position relative to medium frequency (21-period EMA)—+1 if above, -1 if below, 0 if at
The total vote sum classifies the singularity: ≥2 votes = Bullish , ≤-2 votes = Bearish , -1 to +1 votes = Neutral (skip) . This majority-consensus approach ensures directional classification requires alignment across multiple timeframes and analysis dimensions rather than relying on a single indicator. Neutral signals (mixed voting) are displayed but should not be traded, as they represent geometric catastrophes without clear directional resolution.
Core Calculation Methodology
Embedding Coordinate Generation
Three normalized phase space coordinates are constructed from price data:
X-Dimension (Velocity Space):
price_velocity = close - close
X = (price_velocity - mean) / stdev over hurstWindow
Y-Dimension (Acceleration Space):
momentum = close - close
momentum_accel = momentum - momentum
Y = (momentum_accel - mean) / stdev over hurstWindow
Z-Dimension (Volume-Weighted Space):
vol_normalized = (volume - mean) / stdev over embedLength
roc = (close - close ) / close
Z = (roc × vol_normalized - mean) / stdev over hurstWindow
These coordinates define a point in 3D phase space for each bar. The trajectory connecting these points is the reconstructed manifold.
Gradient Field Calculation
First derivatives measure local manifold slope:
dX/dt = X - X
dY/dt = Y - Y
Gradient_Magnitude = √
The gradient direction indicates where the manifold is "pushing" price. Positive Y-gradient suggests upward topological pressure; negative Y-gradient suggests downward pressure.
Curvature Tensor Components
Second derivatives measure manifold bending using discrete Laplacian:
Laplacian_X = X - 2×X + X
Laplacian_Y = Y - 2×Y + Y
Laplacian_Magnitude = √
This is then normalized:
Curvature_Normalized = (Laplacian_Magnitude - mean) / stdev over embedLength
High normalized curvature (>1.5) indicates sharp manifold folding.
Complexity Accumulation
Sign changes in curvature field are counted:
Sign_Flip = 1 if sign(Curvature ) ≠ sign(Curvature ), else 0
Topological_Complexity = sum(Sign_Flip) over embedLength window
This measures oscillation frequency in the geometry. Complexity >5 indicates chaotic topology.
Condition Number Stability Analysis
Jacobian matrix sensitivity is approximated:
dX/dp = dX/dt / (price_change + epsilon)
dY/dp = dY/dt / (price_change + epsilon)
Jacobian_Determinant = (dX/dt × dY/dp) - (dX/dp × dY/dt)
Jacobian_Trace = dX/dt + dY/dp
Condition_Number = |Trace| / (|Determinant| + epsilon)
High condition numbers indicate numerical instability near singularities.
Catastrophe Score Assembly
Each metric is converted to percentile rank over embedLength window, then combined:
Curvature_Percentile = percentrank(abs(Curvature_Normalized), embedLength)
Gradient_Percentile = percentrank(Gradient_Magnitude, embedLength)
Condition_Percentile = percentrank(abs(Condition_Z_Score), embedLength)
Complexity_Ratio = clamp(Topological_Complexity / embedLength, 0, 1)
Final score:
Raw_Anomaly = 0.45×Curvature_P + 0.25×Complexity_R + 0.20×Condition_P + 0.10×Gradient_P
Catastrophe_Score = Raw_Anomaly × Hurst_Multiplier
Values are clamped to range.
Hurst Exponent Calculation
Rescaled range analysis on log returns:
Calculate log returns: r = log(close) - log(close )
Compute cumulative deviations from mean
Find range: R = max(cumulative_dev) - min(cumulative_dev)
Calculate standard deviation: S = stdev(r, hurstWindow)
Compute R/S ratio
Hurst = log(R/S) / log(hurstWindow)
Clamp to and smooth with 5-period EMA
Regime Classification Logic
Volatility Regime:
ATR_MA = SMA(ATR(14), 30)
Vol_Expansion = ATR / ATR_MA
Is_Volatile = Vol_Expansion > (1.0 + minVolExpansion)
Trend Regime (Corrected ADX):
Calculate directional movement (DM+, DM-)
Smooth with Wilder's RMA(14)
Compute DI+ and DI- as percentages
Calculate DX = |DI+ - DI-| / (DI+ + DI-) × 100
ADX = RMA(DX, 14)
Is_Trending = ADX > (trendStrength × 100)
Chop Detection:
Is_Chopping = NOT Is_Trending AND NOT Is_Volatile
Regime Validity:
Regime_Valid = (Is_Trending OR Is_Volatile) AND NOT Is_Chopping
Signal Generation Logic
For each bar:
Check if catastrophe score > topologyStrength threshold
Verify regime is valid
Confirm Hurst alignment (trending or mean-reverting with pivot)
Validate pivot quality (price extended outside spectral bands then re-entered)
Confirm volume/volatility participation
Check cooldown period has elapsed
If all true: compute directional vote
If vote ≥2: Bullish Singularity
If vote ≤-2: Bearish Singularity
If -1 to +1: Neutral (display but skip)
All conditions must be true for signal generation.
Visual System Architecture
Spectral Decomposition Layers
Three harmonic frequency bands visualize entropy state:
Layer 1 (Surface Frequency):
Center: EMA(8)
Width: ±0.3 × 0.5 × ATR
Transparency: 75% (most visible)
Represents fast oscillations
Layer 2 (Mid Frequency):
Center: EMA(21)
Width: ±0.5 × 0.5 × ATR
Transparency: 85%
Represents medium cycles
Layer 3 (Deep Frequency):
Center: EMA(55)
Width: ±0.7 × 0.5 × ATR
Transparency: 92% (most transparent)
Represents slow baseline
Convergence of layers indicates low entropy (stable topology). Divergence indicates high entropy (catastrophe building). This decomposition reveals how different frequency components of price movement interact—when all three align, the manifold is in equilibrium; when they separate, topology is unstable.
Energy Radiance Fields
Concentric boxes emanate from each singularity bar:
For each singularity, 5 layers are generated:
Layer n: bar_index ± (n × 1.5 bars), close ± (n × 0.4 × ATR)
Transparency gradient: inner 75% → outer 95%
Color matches signal direction
These fields visualize the "energy well" of the catastrophe—wider fields indicate stronger topology distortion. The exponential expansion creates a natural radiance effect.
Singularity Node Geometry
N-sided polygon (default hexagon) at each signal bar:
Vertices calculated using polar coordinates
Rotation angle: bar_index × 0.1 (creates animation)
Radius: ATR × singularity_strength × 2
Connects vertices with colored lines
The rotating geometric primitive marks the exact catastrophe bar with visual prominence.
Gradient Flow Field
Directional arrows display manifold slope:
Spawns every 3 bars when gradient_magnitude > 0.1
Symbol: "↗" if dY/dt > 0.1, "↘" if dY/dt < -0.1, "→" if neutral
Color: Bull/bear/neutral based on direction
Density limited to flowDensity parameter
Arrows cluster when gradient is strong, creating intuitive topology visualization.
Probability Projection Cones
Forward trajectory from each singularity:
Projects 10 bars forward
Direction based on vote classification
Center line: close + (direction × ATR × 3)
Uncertainty width: ATR × singularity_strength × 2
Dashed boundaries, solid center
These are mathematical projections based on current gradient, not price targets. They visualize expected manifold evolution if topology continues current trajectory.
Dashboard Metrics Explanation
The real-time control panel displays six core metrics plus regime status:
H (Hurst Exponent):
Value: Current Hurst (0-1 scale)
Label: TREND (>0.55), REVERT (<0.45), or RANDOM (0.45-0.55)
Icon: Direction arrow based on regime
Purpose: Shows fractal character—only trade when favorable
Σ (Catastrophe Score):
Value: Current composite anomaly (0-100%)
Bar gauge shows relative strength
Icon: ◆ if above threshold, ○ if below
Purpose: Primary signal strength indicator
κ (Curvature):
Value: Normalized Laplacian magnitude
Direction arrow shows sign
Color codes severity (green<0.8, yellow<1.5, red≥1.5)
Purpose: Shows manifold bending intensity
⟳ (Topology Complexity):
Value: Count of sign flips in curvature
Icon: ◆ if >3, ○ otherwise
Color codes chaos level
Purpose: Indicates geometric instability
V (Volatility Expansion):
Value: ATR expansion percentage above 30-bar average
Icon: ● if volatile, ○ otherwise
Purpose: Confirms energy present for reversal
T (Trend Strength):
Value: ADX reading (0-100)
Icon: ● if trending, ○ otherwise
Purpose: Shows directional bias strength
R (Regime):
Label: EXPLOSIVE / TREND / VOLATILE / CHOP / NEUTRAL
Icon: ✓ if valid, ✗ if invalid
Purpose: Go/no-go filter for trading
STATE (Bottom Display):
Shows: "◆ BULL SINGULARITY" (green), "◆ BEAR SINGULARITY" (red), "◆ WEAK/NEUTRAL" (orange), or "— Monitoring —" (gray)
Purpose: Current signal status at a glance
How to Use This Indicator
Initial Setup and Configuration
Apply the indicator to your chart with default settings as a starting point. The default parameters (21-bar embedding, 5-bar Hurst window, 2.5σ singularity threshold, 0.65 topology confirmation) are optimized for balanced detection across most instruments and timeframes. For very fast markets (scalping crypto, 1-5min charts), consider reducing embedding depth to 13-15 bars and Hurst window to 3 bars for more responsive detection. For slower markets (swing trading stocks, 4H-Daily charts), increase embedding depth to 34-55 bars and Hurst window to 8-10 bars for more stable topology measurement.
Enable the dashboard (top right recommended) to monitor real-time metrics. The control panel is your primary decision interface—glancing at the dashboard should instantly communicate whether conditions favor trading and what the current topology state is. Position and size the dashboard to remain visible but not obscure price action.
Enable regime filtering (strongly recommended) to prevent trading during choppy/ranging conditions where geometric edge deteriorates. This single setting can dramatically improve overall performance by eliminating low-probability environments.
Reading Dashboard Metrics for Trade Readiness
Before considering any trade, verify the dashboard shows favorable conditions:
Hurst (H) Check:
The Hurst Exponent reading is your first filter. Only consider trades when H > 0.50 . Ideal conditions show H > 0.60 with "TREND" label—this indicates persistent directional price movement where manifold catastrophes produce significant reversals. When H < 0.45 (REVERT label), the market is mean-reverting and catastrophes represent minor oscillations rather than substantial pivots. Do not trade in mean-reverting regimes unless you're explicitly using range-bound strategies (which this indicator is not optimized for). When H ≈ 0.50 (RANDOM label), edge is neutral—acceptable but not ideal.
Catastrophe (Σ) Monitoring:
Watch the Σ percentage build over time. Readings consistently below 50% indicate stable topology with no imminent reversals. When Σ rises above 60-65%, manifold distortion is approaching critical levels. Signals only fire when Σ exceeds the configured threshold (default 65%), so this metric pre-warns you of potential upcoming catastrophes. High-conviction setups show Σ > 75%.
Regime (R) Validation:
The regime classification must read TREND, VOLATILE, or EXPLOSIVE—never trade when it reads CHOP or NEUTRAL. The checkmark (✓) must be present in the regime cell for trading conditions to be valid. If you see an X (✗), skip all signals until regime improves. This filter alone eliminates most losing trades by avoiding geometrically unfavorable environments.
Combined High-Conviction Profile:
The strongest trading opportunities show simultaneously:
H > 0.60 (strong trending regime)
Σ > 75% (extreme topology distortion)
R = EXPLOSIVE or TREND with ✓
κ (Curvature) > 1.5 (sharp manifold fold)
⟳ (Complexity) > 4 (chaotic geometry)
V (Volatility) showing elevated ATR expansion
When all metrics align in this configuration, the manifold is undergoing severe distortion in a favorable fractal regime—these represent maximum-conviction reversal opportunities.
Signal Interpretation and Entry Logic
Bullish Singularity (▲ Green Triangle Below Bar):
This marker appears when the system detects a manifold catastrophe at a price low with bullish directional consensus. All five confirmation filters have aligned: topology score exceeded threshold, pivot low structure formed, swing size was significant, volume/volatility confirmed participation, and regime was valid. The green color indicates the directional vote totaled +2 or higher (majority bullish).
Trading Approach: Consider long entry on the bar immediately following the signal (bar after the triangle). The singularity bar itself is where the geometric catastrophe occurred—entering after allows you to see if price confirms the reversal. Place stop loss below the singularity bar's low (with buffer of 0.5-1.0 ATR for volatility). Initial target can be the previous swing high, or use the probability cone projection as a guide (though not a guarantee). Monitor the dashboard STATE—if it flips to "◆ BEAR SINGULARITY" or Hurst drops significantly, consider exiting even if target not reached.
Bearish Singularity (▼ Red Triangle Above Bar):
This marker appears when the system detects a manifold catastrophe at a price high with bearish directional consensus. Same five-filter confirmation process as bullish signals. The red color indicates directional vote totaled -2 or lower (majority bearish).
Trading Approach: Consider short entry on the bar following the signal. Place stop loss above the singularity bar's high (with buffer). Target previous swing low or use cone projection as reference. Exit if opposite signal fires or Hurst deteriorates.
Neutral Signal (● Orange Circle at Price Level):
This marker indicates the catastrophe detection system identified a topology break that passed catastrophe threshold and regime filters, but the directional voting system produced a mixed result (vote between -1 and +1). This means the four directional components (pivot, trend, flow, mid-band) are not in agreement about which way the reversal should resolve.
Trading Approach: Skip these signals. Neutral markers are displayed for analytical completeness but should not be traded. They represent geometric catastrophes without clear directional resolution—essentially, the manifold is breaking but the direction of the break is ambiguous. Trading neutral signals dramatically increases false signal rate. Only trade green (bullish) or red (bearish) singularities.
Visual Confirmation Using Spectral Layers
The three colored ribbons (spectral decomposition layers) provide entropy visualization that helps confirm signal quality:
Divergent Layers (High Entropy State):
When the three frequency bands (fast 8-period, medium 21-period, slow 55-period) are separated with significant gaps between them, the manifold is in high entropy state—different frequency components of price movement are pulling in different directions. This geometric tension precedes catastrophes. Strong signals often occur when layers are divergent before the signal, then begin reconverging immediately after.
Convergent Layers (Low Entropy State):
When all three ribbons are tightly clustered or overlapping, the manifold is in equilibrium—all frequency components agree. This stable geometry makes catastrophe detection more reliable because topology breaks clearly stand out against the baseline stability. If you see layers converge, then a singularity fires, then layers diverge, this pattern suggests a genuine regime transition.
Signal Quality Assessment:
High-quality singularity signals should show:
Divergent layers (high entropy) in the 5-10 bars before signal
Singularity bar occurs when price has extended outside at least one of the spectral bands (shows pivot extended beyond equilibrium)
Close of singularity bar re-enters the spectral band zone (shows mean reversion starting)
Layers begin reconverging in 3-5 bars after signal (shows new equilibrium forming)
This pattern visually confirms the geometric narrative: manifold became unstable (divergence), reached critical distortion (extended outside equilibrium), broke catastrophically (singularity), and is now stabilizing in new direction (reconvergence).
Using Energy Fields for Trade Management
The concentric glowing boxes around each singularity visualize the topology distortion
magnitude:
Wide Energy Fields (5+ Layers Visible):
Large radiance indicates strong catastrophe with high manifold curvature. These represent significant topology breaks and typically precede larger price moves. Wide fields justify wider profit targets and longer hold times. The outer edge of the largest box can serve as a dynamic support/resistance zone—price often respects these geometric boundaries.
Narrow Energy Fields (2-3 Layers):
Smaller radiance indicates moderate catastrophe. While still valid signals (all filters passed), expect smaller follow-through. Use tighter profit targets and be prepared for quicker exit if momentum doesn't develop. These are valid but lower-conviction trades.
Field Interaction Zones:
When energy fields from consecutive signals overlap or touch, this indicates a prolonged topology distortion region—often corresponds to consolidation zones or complex reversal patterns (head-and-shoulders, double tops/bottoms). Be more cautious in these areas as the manifold is undergoing extended restructuring rather than a clean catastrophe.
Probability Cone Projections
The dashed cone extending forward from each singularity is a mathematical projection, not a
price target:
Cone Direction:
The center line direction (upward for bullish, downward for bearish, flat for neutral) shows the expected trajectory based on current manifold gradient and singularity direction. This is where the topology suggests price "should" go if the catastrophe completes normally.
Cone Width:
The uncertainty band (upper and lower dashed boundaries) represents the range of outcomes given current volatility (ATR-based). Wider cones indicate higher uncertainty—expect more price volatility even if direction is correct. Narrower cones suggest more constrained movement.
Price-Cone Interaction:
Price following near the center line = catastrophe resolving as expected, geometric projection accurate
Price breaking above upper cone = stronger-than-expected reversal, consider holding for larger targets
Price breaking below lower cone (for bullish signal) = catastrophe failing, manifold may be re-folding in opposite direction, consider exit
Price oscillating within cone = normal reversal process, hold position
The 10-bar projection length means cones show expected behavior over the next ~10 bars. Don't confuse this with longer-term price targets.
Gradient Flow Field Interpretation
The directional arrows (↗, ↘, →) scattered across the chart show the manifold's Y-gradient (vertical acceleration dimension):
Upward Arrows (↗):
Positive Y-gradient indicates the momentum acceleration dimension is pushing upward—the manifold topology has upward "slope" at this location. Clusters of upward arrows suggest bullish topological pressure building. These often appear before bullish singularities fire.
Downward Arrows (↘):
Negative Y-gradient indicates downward topological pressure. Clusters precede bearish singularities.
Horizontal Arrows (→):
Neutral gradient indicates balanced topology with no strong directional pressure.
Using Flow Field:
The arrows provide real-time topology state information even between singularity signals. If you're in a long position from a bullish singularity and begin seeing increasing downward arrows appearing, this suggests manifold gradient is shifting—consider tightening stops. Conversely, if arrows remain upward or neutral, topology supports continuation.
Don't confuse arrow direction with immediate price direction—arrows show geometric slope, not price prediction. They're confirmatory context, not entry signals themselves.
Parameter Optimization for Your Trading Style
For Scalping / Fast Trading (1m-15m charts):
Embedding Depth: 13-15 bars (faster topology reconstruction)
Hurst Window: 3 bars (responsive fractal detection)
Singularity Threshold: 2.0-2.3σ (more sensitive)
Topology Confirmation: 0.55-0.60 (lower barrier)
Min Swing Size: 0.8-1.2 ATR (accepts smaller moves)
Pivot Lookback: 3-4 bars (quick pivot detection)
This configuration increases signal frequency for active trading but requires diligent monitoring as false signal rate increases. Use tighter stops.
For Day Trading / Standard Approach (15m-4H charts):
Keep default settings (21 embed, 5 Hurst, 2.5σ, 0.65 confirmation, 1.5 ATR, 5 pivot)
These are balanced for quality over quantity
Best win rate and risk/reward ratio
Recommended for most traders
For Swing Trading / Position Trading (4H-Daily charts):
Embedding Depth: 34-55 bars (stable long-term topology)
Hurst Window: 8-10 bars (smooth fractal measurement)
Singularity Threshold: 3.0-3.5σ (only extreme catastrophes)
Topology Confirmation: 0.75-0.85 (high conviction only)
Min Swing Size: 2.5-4.0 ATR (major moves only)
Pivot Lookback: 8-13 bars (confirmed swings)
This configuration produces infrequent but highly reliable signals suitable for position sizing and longer hold times.
Volatility Adaptation:
In extremely volatile instruments (crypto, penny stocks), increase Min Volatility Expansion to 0.6-0.8 to avoid over-signaling during "always volatile" conditions. In stable instruments (major forex pairs, blue-chip stocks), decrease to 0.3 to allow signals during moderate volatility spikes.
Trend vs Range Preference:
If you prefer trading only strong trends, increase Min Trend Strength to 0.5-0.6 (ADX > 50-60). If you're comfortable with volatility-based trading in weaker trends, decrease to 0.2 (ADX > 20). The default 0.3 balances both approaches.
Complete Trading Workflow Example
Step 1 - Pre-Session Setup:
Load chart with MSE indicator. Check dashboard position is visible. Verify regime filter is enabled. Review recent signals to gauge current instrument behavior.
Step 2 - Market Assessment:
Observe dashboard Hurst reading. If H < 0.45 (mean-reverting), consider skipping this session or using other strategies. If H > 0.50, proceed. Check regime shows TREND, VOLATILE, or EXPLOSIVE with checkmark—if CHOP, wait for regime shift alert.
Step 3 - Signal Wait:
Monitor catastrophe score (Σ). Watch for it climbing above 60%. Observe spectral layers—look for divergence building. If you see curvature (κ) rising above 1.0 and complexity (⟳) increasing, catastrophe is building. Do not anticipate—wait for the actual signal marker.
Step 4 - Signal Recognition:
▲ Bullish or ▼ Bearish triangle appears at a bar. Dashboard STATE changes to "◆ BULL/BEAR SINGULARITY". Energy field appears around the signal bar. Check signal quality:
Was Σ > 70% at signal? (Higher quality)
Are energy fields wide? (Stronger catastrophe)
Did layers diverge before and reconverge after? (Clean break)
Is Hurst still > 0.55? (Good regime)
Step 5 - Entry Decision:
If signal is green/red (not orange neutral), all confirmations look strong, and no immediate contradicting factors appear, prepare entry on next bar open. Wait for confirmation bar to form—ideally it should close in the signal direction (bullish signal → bar closes higher, bearish signal → bar closes lower).
Step 6 - Position Entry:
Enter at open or shortly after open of bar following signal bar. Set stop loss: for bullish signals, place stop at singularity_bar_low - (0.75 × ATR); for bearish signals, place stop at singularity_bar_high + (0.75 × ATR). The buffer accommodates volatility while protecting against catastrophe failure.
Step 7 - Trade Management:
Monitor dashboard continuously:
If Hurst drops below 0.45, consider reducing position
If opposite singularity fires, exit immediately (manifold has re-folded)
If catastrophe score drops below 40% and stays there, topology has stabilized—consider partial profit taking
Watch gradient flow arrows—if they shift to opposite direction persistently, tighten stops
Step 8 - Profit Taking:
Use probability cone as a guide—if price reaches outer cone boundary, consider taking partial profits. If price follows center line cleanly, hold for larger target. Traditional technical targets work well: previous swing high/low, round numbers, Fibonacci extensions. Don't expect precision—manifold projections give direction and magnitude estimates, not exact prices.
Step 9 - Exit:
Exit on: (a) opposite signal appears, (b) dashboard shows regime became invalid (checkmark changes to X), (c) technical target reached, (d) Hurst deteriorates significantly, (e) stop loss hit, or (f) time-based exit if using session limits. Never hold through opposite singularity signals—the manifold has broken in the other direction and your trade thesis is invalidated.
Step 10 - Post-Trade Review:
After exit, review: Did the probability cone projection align with actual price movement? Were the energy fields proportional to move size? Did spectral layers show expected reconvergence? Use these observations to calibrate your interpretation of signal quality over time.
Best Performance Conditions
This topology-based approach performs optimally in specific market environments:
Favorable Conditions:
Well-Developed Swing Structure: Markets with clear rhythm of advances and declines where pivots form at regular intervals. The manifold reconstruction depends on swing formation, so instruments that trend in clear waves work best. Stocks, major forex pairs during active sessions, and established crypto assets typically exhibit this characteristic.
Sufficient Volatility for Topology Development: The embedding process requires meaningful price movement to construct multi-dimensional coordinates. Extremely quiet markets (tight consolidations, holiday trading, after-hours) lack the volatility needed for manifold differentiation. Look for ATR expansion above average—when volatility is present, geometry becomes meaningful.
Trending with Periodic Reversals: The ideal environment is not pure trend (which rarely reverses) nor pure range (which reverses constantly at small scale), but rather trending behavior punctuated by occasional significant counter-trend reversals. This creates the catastrophe conditions the system is designed to detect: manifold building directional momentum, then undergoing sharp topology break at extremes.
Liquid Instruments Where EMAs Reflect True Flow: The spectral layers and frequency decomposition require that moving averages genuinely represent market consensus. Thinly traded instruments with sporadic orders don't create smooth manifold topology. Prefer instruments with consistent volume where EMA calculations reflect actual capital flow rather than random tick sequences.
Challenging Conditions:
Extremely Choppy / Whipsaw Markets: When price oscillates rapidly with no directional persistence (Hurst < 0.40), the manifold undergoes constant micro-catastrophes that don't translate to tradable reversals. The regime filter helps avoid these, but awareness is important. If you see multiple neutral signals clustering with no follow-through, market is too chaotic for this approach.
Very Low Volatility Consolidation: Tight ranges with ATR below average cause the embedding coordinates to compress into a small region of phase space, reducing geometric differentiation. The manifold becomes nearly flat, and catastrophe detection loses sensitivity. The regime filter's volatility component addresses this, but manually avoiding dead markets improves results.
Gap-Heavy Instruments: Stocks that gap frequently (opening outside previous close) create discontinuities in the manifold trajectory. The embedding process assumes continuous evolution, so gaps introduce artifacts. Most gaps don't invalidate the approach, but instruments with daily gaps >2% regularly may show degraded performance. Consider using higher timeframes (4H, Daily) where gaps are less proportionally significant.
Parabolic Moves / Blowoff Tops: When price enters an exponential acceleration phase (vertical rally or crash), the manifold evolves too rapidly for the standard embedding window to track. Catastrophe detection may lag or produce false signals mid-move. These conditions are rare but identifiable by Hurst > 0.75 combined with ATR expansion >2.0× average. If detected, consider sitting out or using very tight stops as geometry is in extreme distortion.
The system adapts by reducing signal frequency in poor conditions—if you notice long periods with no signals, the topology likely lacks the geometric structure needed for reliable catastrophe detection. This is a feature, not a bug: it prevents forced trading during unfavorable environments.
Theoretical Justification for Approach
Why Manifold Embedding?
Traditional technical analysis treats price as a one-dimensional time series: current price is predicted from past prices in sequential order. This approach ignores the structure of price dynamics—the relationships between velocity, acceleration, and participation that govern how price actually evolves.
Dynamical systems theory (from physics and mathematics) provides an alternative framework: treat price as a state variable in a multi-dimensional phase space. In this view, each market condition corresponds to a point in N-dimensional space, and market evolution is a trajectory through this space. The geometry of this space (its topology) constrains what trajectories are possible.
Manifold embedding reconstructs this hidden geometric structure from observable price data. By creating coordinates from velocity, momentum acceleration, and volume-weighted returns, we map price evolution onto a 3D surface. This surface—the manifold—reveals geometric relationships that aren't visible in price charts alone.
The mathematical theorem underlying this approach (Takens' Embedding Theorem from dynamical systems theory) proves that for deterministic or weakly stochastic systems, a state space reconstruction from time-delayed observations of a single variable captures the essential dynamics of the full system. We apply this principle: even though we only observe price, the embedded coordinates (derivatives of price) reconstruct the underlying dynamical structure.
Why Catastrophe Theory?
Catastrophe theory, developed by mathematician René Thom (Fields Medal 1958), describes how continuous systems can undergo sudden discontinuous changes when control parameters reach critical values. A classic example: gradually increasing force on a beam causes smooth bending, then sudden catastrophic buckling. The beam's geometry reaches a critical curvature where topology must break.
Markets exhibit analogous behavior: gradual price changes build tension in the manifold topology until critical distortion is reached, then abrupt directional change occurs (reversal). Catastrophes aren't random—they're mathematically necessary when geometric constraints are violated.
The indicator detects these geometric precursors: high curvature (manifold bending sharply), high complexity (topology oscillating chaotically), high condition number (coordinate mapping becoming singular). These metrics quantify how close the manifold is to a catastrophic fold. When all simultaneously reach extreme values, topology break is imminent.
This provides a logical foundation for reversal detection that doesn't rely on pattern recognition or historical correlation. We're measuring geometric properties that mathematically must change when systems reach critical states. This is why the approach works across different instruments and timeframes—the underlying geometry is universal.
Why Hurst Exponent?
Markets exhibit fractal behavior: patterns at different time scales show statistical self-similarity. The Hurst exponent quantifies this fractal structure by measuring long-range dependence in returns.
Critically for trading, Hurst determines whether recent price movement predicts future direction (H > 0.5) or predicts the opposite (H < 0.5). This is regime detection: trending vs mean-reverting behavior.
The same manifold catastrophe has different trading implications depending on regime. In trending regime (high Hurst), catastrophes represent significant reversal opportunities because the manifold has been building directional momentum that suddenly breaks. In mean-reverting regime (low Hurst), catastrophes represent minor oscillations because the manifold constantly folds at small scales.
By weighting catastrophe signals based on Hurst, the system adapts detection sensitivity to the current fractal regime. This is a form of meta-analysis: not just detecting geometric breaks, but evaluating whether those breaks are meaningful in the current fractal context.
Why Multi-Layer Confirmation?
Geometric anomalies occur frequently in noisy market data. Not every high-curvature point represents a tradable reversal—many are artifacts of microstructure noise, order flow imbalances, or low-liquidity ticks.
The five-filter confirmation system (catastrophe threshold, pivot structure, swing size, volume, regime) addresses this by requiring geometric anomalies to align with observable market evidence. This conjunction-based logic implements the principle: extraordinary claims require extraordinary evidence .
A manifold catastrophe (extraordinary geometric event) alone is not sufficient. We additionally require: price formed a pivot (visible structure), swing was significant (adequate magnitude), volume confirmed participation (capital backed the move), and regime was favorable (trending or volatile, not chopping). Only when all five dimensions agree do we have sufficient evidence that the geometric anomaly represents a genuine reversal opportunity rather than noise.
This multi-dimensional approach is analogous to medical diagnosis: no single test is conclusive, but when multiple independent tests all suggest the same condition, confidence increases dramatically. Each filter removes a different category of false signals, and their combination creates a robust detection system.
The result is a signal set with dramatically improved reliability compared to any single metric alone. This is the power of ensemble methods applied to geometric analysis.
Important Disclaimers
This indicator applies mathematical topology and catastrophe theory to multi-dimensional price space reconstruction. It identifies geometric conditions where manifold curvature, topological complexity, and coordinate singularities suggest potential reversal zones based on phase space analysis. It should not be used as a standalone trading system.
The embedding coordinates, catastrophe scores, and Hurst calculations are deterministic mathematical formulas applied to historical price data. These measurements describe current and recent geometric relationships in the reconstructed manifold but do not predict future price movements. Past geometric patterns and singularity markers do not guarantee future market behavior will follow similar topology evolution.
The manifold reconstruction assumes certain mathematical properties (sufficient embedding dimension, quasi-stationarity, continuous dynamics) that may not hold in all market conditions. Gaps, flash crashes, circuit breakers, news events, and other discontinuities can violate these assumptions. The system attempts to filter problematic conditions through regime classification, but cannot eliminate all edge cases.
The spectral decomposition, energy fields, and probability cones are visualization aids that represent mathematical constructs, not price predictions. The probability cone projects current gradient forward assuming topology continues current trajectory—this is a mathematical "if-then" statement, not a forecast. Market topology can and does change unexpectedly.
All trading involves substantial risk. The singularity markers represent analytical conditions where geometric mathematics align with threshold criteria, not certainty of directional change. Use appropriate risk management for every trade: position sizing based on account risk tolerance (typically 1-2% maximum risk per trade), stop losses placed beyond recent structure plus volatility buffer, and never risk capital needed for living expenses.
The confirmation filters (pivot, swing size, volume, regime) are designed to reduce false signals but cannot eliminate them entirely. Markets can produce geometric anomalies that pass all filters yet fail to develop into sustained reversals. This is inherent to probabilistic systems operating on noisy real-world data.
No indicator can guarantee profitable trades or eliminate losses. The catastrophe detection provides an analytical framework for identifying potential reversal conditions, but actual trading outcomes depend on numerous factors including execution, slippage, spreads, position sizing, risk management, psychological discipline, and market conditions that may change after signal generation.
Use this tool as one component of a comprehensive trading plan that includes multiple forms of analysis, proper risk management, emotional discipline, and realistic expectations about win rates and drawdowns. Combine catastrophe signals with additional confirmation methods such as support/resistance analysis, volume patterns, multi-timeframe alignment, and broader market context.
The spacing filter, cooldown mechanism, and regime validation are designed to reduce noise and over-signaling, but market conditions can change rapidly and render any analytical signal invalid. Always use stop losses and never risk capital you cannot afford to lose. Past performance of detection accuracy does not guarantee future results.
Technical Implementation Notes
All calculations execute on closed bars only—signals and metric values do not repaint after bar close. The indicator does not use any lookahead bias in its calculations. However, the pivot detection mechanism (ta.pivothigh and ta.pivotlow) inherently identifies pivots with a lag equal to the lookback parameter, meaning the actual pivot occurred at bar but is recognized at bar . This is standard behavior for pivot functions and is not repainting—once recognized, the pivot bar never changes.
The normalization system (z-score transformation over rolling windows) requires approximately 30-50 bars of historical data to establish stable statistics. Values in the first 30-50 bars after adding the indicator may show instability as the rolling means and standard deviations converge. Allow adequate warmup period before relying on signals.
The spectral layer arrays, energy field boxes, gradient flow labels, and node geometry lines are subject to TradingView drawing object limits (500 lines, 500 boxes, 500 labels per indicator as specified in settings). The system implements automatic cleanup by deleting oldest objects when limits approach, but on very long charts with many signals, some historical visual elements may be removed to stay within limits. This does not affect signal generation or dashboard metrics—only historical visual artifacts.
Dashboard and visual rendering update only on the last bar to minimize computational overhead. The catastrophe detection logic executes on every bar, but table cells and drawing objects refresh conditionally to optimize performance. If experiencing chart lag, reduce visual complexity: disable spectral layers, energy fields, or flow field to improve rendering speed. Core signal detection continues to function with all visual elements disabled.
The Hurst calculation uses logarithmic returns rather than raw price to ensure stationarity, and implements clipping to range to handle edge cases where R/S analysis produces invalid values (which can occur during extended periods of identical prices or numerical overflow). The 5-period EMA smoothing reduces noise while maintaining responsiveness to regime transitions.
The condition number calculation adds epsilon (1e-10) to denominators to prevent division by zero when Jacobian determinant approaches zero—which is precisely the singularity condition we're detecting. This numerical stability measure ensures the indicator doesn't crash when detecting the very phenomena it's designed to identify.
The indicator has been tested across multiple timeframes (5-minute through daily) and multiple asset classes (forex majors, stock indices, individual equities, cryptocurrencies, commodities, futures). It functions identically across all instruments due to the adaptive normalization approach and percentage-based metrics. No instrument-specific code or parameter sets are required.
The color scheme system implements seven preset themes plus custom mode. Color assignments are applied globally and affect all visual elements simultaneously. The opacity calculation system multiplies component-specific transparency with master opacity to create hierarchical control—adjusting master opacity affects all visuals proportionally while maintaining their relative transparency relationships.
All alert conditions trigger only on bar close to prevent false alerts from intrabar fluctuations. The regime transition alerts (VALID/INVALID) are particularly useful for knowing when trading edge appears or disappears, allowing traders to adjust activity levels accordingly.
— Dskyz, Trade with insight. Trade with anticipation.
RSI Candle 12-Band SpectrumExperience RSI like never before. This multi-band visualizer transforms relative strength into a living color map — directly over price action — revealing momentum shifts long before traditional RSI signals.
🔹 12 Dynamic RSI Bands – A full emotional spectrum from oversold to overbought, colored from deep blue to burning red.
🔹 Adaptive Pulse System – Highlights every shift in RSI state with an intelligent fade-out pulse that measures the strength of each rotation.
🔹 Precision Legend Display – Clear RSI cutoff zones with user-defined thresholds and color ranges.
🔹 Multi-Timeframe Engine – Optionally view higher-timeframe RSI context while scalping lower frames.
🔹 Stealth Mode – Borders-only visualization for minimal chart impact on dark themes.
🔹 Complete Customization – Adjustable band levels, color palettes, and fade behavior.
🧠 Designed for professional traders who move with rhythm, not randomness.
CandelaCharts - Oscillator Concepts 📝 Overview
Oscillator Concepts shows a single, easy‑to‑read line on a scale from −1 to +1 . Near 0 means balance; beyond +1 or −1 means the move is stretched. You can add helpful layers like trend stripes, participation shading, volatility markers, calendar dividers, divergence tags, and simple signal markers. Pick a trading profile (Scalping / Day Trade / Swing / Investment) and the lengths update for you.
📦 Features
A quick tour of the visual layers you can enable. Use this to decide which parts to turn on for reading momentum, extremes, trend bias, participation, and volatility at a glance.
The Line (−1…+1) : A clean momentum read with an optional EMA smooth and clear 0 / ±1 guides.
OS/OB Visualization : Soft gradient fills when price action pushes outside ±1; optional background shading for quick scanning.
Trend Radar : Thin stripes just outside the band that show up‑ or down‑bias using a fast‑vs‑slow EMA spread with anti‑flicker logic.
Participation : Shading that reflects who’s pushing — by MFI, classic up/down volume, delta volume, or a combo model that rewards agreement.
Velocity Pulse : Tiny symbols that only appear when volatility is elevated (outside a neutral 40–60 zone).
Fractal Map : Subtle dashed dividers at Daily / Weekly / Monthly / Yearly / 5‑Year boundaries (Auto picks a sensible cadence).
Divergences : Regular bullish/bearish tags at pivots, with an optional high‑probability filter.
Unified Signals : One common vertical level for triangles (OS/OB re‑entries) and divergence icons so your eye doesn’t hunt.
Profiles : Four presets tune all lookbacks together so the tool stays consistent across timeframes.
Themes : Multiple palettes or fully custom bear/mid/bull colors.
Alerts : Ready for “Any alert() function call” with OS/OB and Divergence options.
⚙️ Settings
Every adjustable input in plain English. Set your profile, show or hide reference levels, pick a theme, and toggle components so the visuals match your style and timeframe.
Trading Profile : Scalping / Day Trade / Swing / Investment — automatically adjusts core lengths.
−1…+1 Levels : Show reference lines at ±1.
Smoothing & Length : EMA smoothing for The Line.
OS/OB Zones & Show Fill : Optional background shade plus gentle gradient fills beyond ±1.
Theme : Presets (Default, Blue–Orange, Green–Red, Teal–Fuchsia, Aqua–Purple, Black–Green, Black–White) or Custom .
Divergences : Turn on detection at pivot highs/lows. Length sets left/right bars. HP filter asks that at least one oscillator anchor sits outside ±1.
Participation : Choose MFI , Volume , Delta Volume , or MFI + Vol + Delta . Set the window; optionally smooth it.
Trend Radar : Up or down stripes just beyond ±1 based on a fast/slow EMA spread. Tune Fast and Slow .
Velocity Pulse : Symbols appear only when volatility exits the 40–60 zone; use Fast / Slow to adjust sensitivity.
Fractal Map : Vertical dividers at time boundaries. Auto selects per timeframe, or pick Daily / Weekly / Monthly / Yearly / 5 Years .
Signals : Show All , only OS/OB , or only Divergence markers (shared height for quick scanning).
Alerts - OS/OB Conditions : Fire when The Line enters extremes (crosses above +1 or below −1).
Alerts - OS/OB Signals : Fire when The Line re‑enters the band (comes back inside from > +1 or < −1).
Alerts - Divergence Conditions : Raw regular divergences right when the pivot forms (no HP filter).
Alerts - Divergence Signals : Confirmed regular divergences that pass the HP filter.
⚡️ Showcase
A visual gallery of the indicator's components. Each image highlights one layer at a time—The Line, OS/OB fills, Trend Radar, Participation, Velocity Pulse, Fractal Map, Divergences, and Signals—so you can quickly recognize how each looks on a live chart.
The Line
Participation
Trend Radar
Velocity Pulse
Fractal Map
Divergences
Signals
Overbought/Oversold
📒 Usage
Hands‑on guidance for reading the line, thresholds, and add‑ons in live markets. Learn when to favor continuation vs. mean‑reversion, how to weigh participation and volatility, and where to set invalidation and targets.
Scale : 0 = balance. ±1 = adaptive extremes. A push beyond ±1 isn’t an automatic fade — check trend stripes, participation, and volatility.
Trend vs Mean‑Revert : With bull stripes, favor pullback buys on OS re‑entries; with bear stripes, favor fades on OB re‑entries.
Participation : Strong positive shading supports continuation; weak/negative during new highs is a caution flag.
Volatility Pulse : Symbols only appear when energy is high. In trends they often mark expansion; counter‑trend they can precede snap‑backs.
Divergences : Raw is early; HP is selective. Treat HP as higher‑quality context, not a stand‑alone signal.
Risk : Use nearby structure (swing points, session highs/lows, or a fractal divider) for invalidation. Scale targets around 0 / ±1 and current vol.
Profiles : If entries feel late/early, try a different profile before hand‑tuning every length.
🚨 Alerts
What you can be notified about and how to turn it on. Covers entering extremes, re‑entries from extremes, and divergence detections, with a recommended schedule (once per bar close).
OS/OB Condition — Entered Overbought → when The Line moves up through +1.
OS/OB Condition — Entered Oversold → when The Line moves down through −1.
OS/OB Signal — Re‑Entry from Overbought/Oversold → when The Line comes back inside from an extreme.
Divergence Condition — Bullish/Bearish (raw) → printed as soon as a regular divergence is detected.
Divergence Signal — Bullish/Bearish (confirmed) → only fires when the high‑probability filter passes.
⚠️ Disclaimer
These tools are exclusively available on the TradingView platform.
Our charting tools are intended solely for informational and educational purposes and should not be regarded as financial, investment, or trading advice. They are not designed to predict market movements or offer specific recommendations. Users should be aware that past performance is not indicative of future results and should not rely on these tools for financial decisions. By using these charting tools, the purchaser agrees that the seller and creator hold no responsibility for any decisions made based on information provided by the tools. The purchaser assumes full responsibility and liability for any actions taken and their consequences, including potential financial losses or investment outcomes that may result from the use of these products.
By purchasing, the customer acknowledges and accepts that neither the seller nor the creator is liable for any undesired outcomes stemming from the development, sale, or use of these products. Additionally, the purchaser agrees to indemnify the seller from any liability. If invited through the Friends and Family Program, the purchaser understands that any provided discount code applies only to the initial purchase of Candela's subscription. The purchaser is responsible for canceling or requesting cancellation of their subscription if they choose not to continue at the full retail price. In the event the purchaser no longer wishes to use the products, they must unsubscribe from the membership service, if applicable.
We do not offer reimbursements, refunds, or chargebacks. Once these Terms are accepted at the time of purchase, no reimbursements, refunds, or chargebacks will be issued under any circumstances.
By continuing to use these charting tools, the user confirms their understanding and acceptance of these Terms as outlined in this disclaimer.
GTI BGTI: RSI Suite (Standard • Stochastic • Smoothed)
A three-layer momentum and trend toolkit that combines Standard RSI, Stochastic RSI, and a Smoothed/“Macro” RSI to help you read intraday swings, trend transitions, and high-probability reversal/continuation spots.
All in one pane with intuitive coloring and optional divergence markers and alerts.
Why this works
* Stochastic RSI (K/D) visualizes fast momentum swings and timing.
* Standard RSI moves more gradually, helping confirm trend transitions that may span several Stochastic cycles.
* Smoothed RSI (Average → Macro) adds a second-pass filter and slope persistence to reveal the macro direction while suppressing noise.
Used together, Stochastic guides entries/exits around local highs/lows, while the RSI layers improve confidence when a small swing is likely part of a larger turn.
What you’ll see
* Standard RSI (yellow; pink above Bull line, aqua below Bear line).
* Stochastic RSI (K/D) with contextual colors:
* Greens when RSI is weak/oversold (bearish conditions → watch for bullish reversals/continuations).
* Reds when RSI is strong/overbought (bullish conditions → watch for bearish reversals/continuations).
* Smoothed (Macro) RSI with trend color:
* Red when macro is ascending (bullish),
* Aqua when macro is descending (bearish).
* Divergences (optional markers):
* Bearish: RSI Lower High + Price Higher High (red ⬇).
* Bullish: RSI Higher Low + Price Lower Low (green ⬆).
* No repaint: pivots confirm after the chosen right-bars window.
How to use it
* Bullish Reversal
* Macro RSI is reversing at a higher low after price has been in a overall downtrend
* Stochastic RSI is switching from green to red in an overall downtrend
* Bullish Oversold
* Macro RSI is reversing from a significantly low level after price has a short but strong dip during an overall uptrend
* Stochastic RSI is switching from green to red in an overall uptrend
* Bullish Continuation
* Macro RSI is ascending with a strong slope or forming a higher low above the 50 line
* Stochastic RSI is reaching a bottom but still painted red
* Bearish Reversal
* Macro RSI is reversing at a lower high after price has been in a overall uptrend
* Stochastic RSI is switching from red to green in an overall uptrend
* Bearish Overbought
* Macro RSI is reversing from a significantly high level after price has a short but strong jump during an overall downtrend
* Stochastic RSI is switching from red to green in an overall downtrend
* Bearish Continuation
* Macro RSI is descending with a strong slope or forming a lower high below the 50 line
* Stochastic RSI is reaching a top but still painted green
* Divergences: Use as signals of exhaustion—best when aligned with Macro RSI color/slope and key levels (e.g., Bull/Bear lines, 50 midline).
*** IMPORTANT ***
* Stack confluence, don’t single-signal trade. Look for:
* 1) Macro RSI color & slope (red = ascending/bullish, aqua = descending/bearish)
* 2) Standard RSI location (above/below Bull/Bear lines or 50)
* 3) Stoch flip + direction
* 4) Price structure (HH/HL vs LH/LL)
* 5) Divergence type (regular vs hidden) at meaningful levels
* Trade with the macro
* Prioritize longs when Macro RSI is red or just flipped up
* Prioritize shorts when Macro RSI is aqua or just flipped down
* Counter-trend setups = smaller size and faster management.
* Location > signal
* The same crossover/divergence is higher quality near Bull (~60)/Bear(~40) or extremes than in the mid-range chop around 50.
* Early vs confirmed
* Use the early pivot heads-up for anticipation, but scale in only after the confirmed pivot (right-bars complete). If early signal fails to confirm, stand down.
* Define invalidation upfront
* For divergence entries, place stops beyond the pivot extreme (LL/HH). If Macro RSI flips against your trade or RSI breaks back through 50 with slope, exit or tighten.
* Multi-timeframe alignment
* Best results come when entry timeframe (e.g., 1H) aligns with higher-TF macro (e.g., 4H/D). If they disagree, treat it as mean-reversion only.
* Avoid common traps
* Skip: isolated Stochastic flips without RSI support, divergences without price HH/LL confirmation, and serial divergences when Macro RSI slope is strong against the idea.
* Parameter guidance
* Start with defaults; then tune: confirmBars 3–7, minSlope 0.05–0.15 RSI pts/bar, pivot left/right tighter for faster but noisier signals, wider for cleaner but fewer.
* Alerts = workflow, not auto-trades
* Use Macro Flip + Divergence alerts as a checklist trigger; enter only when your confluence rules are met and risk is defined.
Key inputs (tweak to your market/timeframe)
* RSI / Stochastic lengths and K/D smoothing.
* Bull / Bear Lines (default 61.1 / 43.6).
* Average RSI Method/Length (SMA/EMA/RMA/WMA) + Macro Smooth Length.
* Trend confirmation: bars of persistence and minimum slope to reduce flip noise.
* Pivot look-back (left/right) for divergence confirmation strictness.
Alerts included
* Macro Flip Up / Down (Smoothed RSI regime change).
* RSI Bullish/Bearish Divergence (confirmed at pivot).
* Stochastic RSI continuation/divergence (optional).
Tips
* Level + Slope matter. High/low RSI level flags conditions; slope confirms impulse/continuation.
* Let Stochastic time the swing; let Macro RSI filter the trend.
* Tighten or loosen pivot windows to trade fewer/cleaner vs. more/faster signals.
Adaptive AI Polar Oscillator [by Oberlunar]Adaptive AI Oscillator blends trading signals with two order-flow style oscillators and a lightweight online-learning model to keep it reactive, adaptive and computationally feasible.
What it is
A lightweight Multi Layer Perceptron (neural net) updates online on every bar, so it keeps adapting as conditions change.
An adaptive collector that fuses features like Price (close, ohlc4, etc...), a selectable (but not used in the original implementation) Moving Average (EMA/SMA/WMA/RMA/HMA/DEMA/TEMA), RSI, the classic volume datafeeds, plus two “OberPolar” oscillators computed above and below the current integral area price.
What you see
White line — the model’s denormalised forecast (in price units).
Colored price line — actual price, shown aqua when forecast ≥ price (“golden” bias) and red when forecast < price (“death” bias).
Why it helps
Combines heterogeneous information (trend, momentum, participation, regional buy/sell pressure) into a single adaptive forecast.
Online learning reduces regime staleness versus fixed-parameter indicators.
The aqua/red bias offers a quick, visual state for discretionary decisions.
How it works (intuitive)
Each AI input is standardised (z-score) with optional clamping to mitigate outliers.
A rolling window of recent values feeds a 2-layer AI to predict one step ahead.
After each bar closes, the model compares forecast vs. reality and nudges its weights (SGD with momentum, L2, optional gradient clipping).
The forecast is de-standardised back to price units and plotted as the white line.
Reading guide
Crossovers between forecast and price often mark potential bias flips.
Persistent aqua → model perceives supportive/positive conditions.
Persistent red → model perceives headwinds/negative conditions.
Complex Strategy — Oscillator Trendline Break
Connect the first pivot in the fading bias with the first pivot in the new bias, then trade the break of that line in the direction of the new bias.
Idea in one line
Use the Adaptive AI Oscillator (green = bullish bias, red = bearish). When bias flips, build a line across the oscillator pivots that “span” the transition; the break of that line times the entry.
Long setup (mirror for shorts)
Bias transition : a bearish (red) regime is ongoing, then the oscillator turns bullish (green).
Anchor pivots : take the first MIN in red just before/around the flip and the first MAX in green after the flip. Draw a trendline L through these two oscillator values (time–value line).
Trigger : enter LONG on the close that breaks above L —optional confirmations: price above your MA, non-decreasing volume, no immediate supply zone overhead.
Risk : stop below the last oscillator swing low or below a retest of L; first target at 1R–1.5R or at the opposite bias zone; trail under successive oscillator higher lows.
Short setup
Bias turns from green (bullish) to red (bearish).
Connect the first MAX in green to the first MIN in red → line L.
Enter SHORT on a close below L ; stop above the last oscillator swing high; symmetric targets/trailing.
Complex Strategy #2 — Bias-Pivot Breakout with Exit on Line Failure
Connect two pivots of the same bias to build a dynamic barrier; trade the breakout in the bias direction and exit when that line later fails.
Long play (mirror for shorts)
Build the line. During a green (bullish) phase, mark the first two local MAX of the oscillator. Connect them to form the yellow resistance line L (extend it right). If a new, clearer MAX appears before a break, re-anchor using the two most recent highs.
Entry trigger. Go LONG on a close above L (the “Break and LONG” in the image). Optional filters: price above your MA, rising volume, no immediate overhead level.
Risk. Initial stop: below the last oscillator swing low or below the retest of L . Position size for 1–2R baseline.
Exit. Close the long when the oscillator later breaks back below L (the “Break and LONG exit”), or on a bias flip to red, or at a fixed target/trailing under higher lows.
Short play (symmetric)
In a red phase, connect the first two local MIN to form support line L .
Enter SHORT on a close below L ; stop above the last oscillator swing high; exit on a break back above L or on a flip to green.
Notes
Require a minimum slope/spacing between pivots to avoid flat/noisy lines.
Re-anchor the line if fresher pivots emerge before a valid break.
Use with your regime filter (MA slope, higher-timeframe bias) to reduce whipsaws.
Complex Strategy #3 — Lateral Box & Zero-Slope Breakout
An easy way to understand sideways phases and the next price direction: draw two zero-slope lines (flat upper/lower bounds) across the oscillator’s lateral area; when a strong break occurs, trade in the direction of that break.
How to use it
Identify a lateral area on the oscillator (flat, low-variance region). Place a flat upper line on tops and a flat lower line on bottoms (slope ≈ 0).
Wait for a decisive break : close outside the band with expansion (range/true range rising, or a wide candle).
• Break up → bias for LONG .
• Break down → bias for SHORT .
Why it helps
Flat lines isolate congestion; the next impulsive move is often revealed by which side is broken with force.
It filters noise inside the range and focuses attention on the transition from balance → imbalance.
Practical filters (optional)
Require minimum bar body/ATR on the breakout candle to avoid false breaks .
Confirm with your regime filter (e.g., price above/below your MA) or a quick retest that holds.
Invalidate the signal if the price immediately returns inside the band on the next bar.
General Operational notes
If new pivots form before a break, re-anchor the line with the most recent qualifying pair (keeps the structure fresh).
Ignore very shallow lines (near-flat): require a minimum slope or angle to avoid noise.
Combine with your bias filter (e.g., MA slope/regime) to reduce false starts.
Limits & good practice
Adaptive models can react to noise; treat signals as context within a risk-managed plan.
No model predicts the future—this summarises evolving conditions compactly.
— Oberlunar 👁 ★
Smart Moving Average Dynamics [ChartNation]Smart Moving Average Dynamics (SMAD) — by Chart Nation
What it does:
SMAD maps how far price deviates from a chosen moving average and normalizes that distance into a bounded oscillator (−100…+100). It detects extreme expansions and prints non-repainting dots when the move exits an extreme. Price-level rails are drawn from those events (with optional fade/expiry) to highlight likely reaction zones. The MA line is colored by bias. A slim gauge summarizes the current oscillator percentile; a compact info panel shows TF, Trend, Volume rank, and Volatility rank.
How it works (high-level, closed-source)
Core signal: diff = price – MA(type, length) where MA can be SMA/EMA/RMA/WMA/VWMA.
Normalization (choose one):
Highest Abs (N): scales diff by the highest absolute excursion over N bars (fast, adaptive).
Z-Score: scales by stdev(diff, N) and maps ±σ to ±100 via a user factor.
ATR-Scaled: scales by ATR * k, relating deviation to current volatility.
Percent Rank: ranks the magnitude of |diff| over N bars and reapplies the original sign.
All methods clamp to −100…+100 to keep visuals consistent across assets/TFs.
Extremes & confirmation: Dots print only when an extreme exits ±100 (optionally on bar close) and can be filtered by linger bars and short-term slope flip, reducing one-bar spikes.
Rails: When an extreme confirms, a rail is anchored at the corresponding price swing and can soft-fade and/or expire after X bars.
Trend color: MA color = Up (green) when oscillator > threshold and MA slope > 0; Down (magenta) for the opposite; Neutral otherwise.
Context panels:
Slim Gauge: current oscillator bucket (0–20) with the exact normalized reading.
Info Panel: TF, Trend, and 0–100 percent-ranks of Volume and ATR-based volatility grouped as Low / Medium / High.
SMAD isn’t a collection of plots; it’s a single framework that integrates:
a deviation-from-MA engine,
four interchangeable normalization models (selected per market regime),
a gated extreme detector (linger + slope + confirm-on-close), and
time-aware rails with soft fade/expiry, presented with a minimal gauge and info panel so traders can compare regimes across TFs without recalibrating thresholds.
How to use (examples, not signals)
Mean-revert plays: When price exits an extreme and prints a dot, look for reactions near the new rail. Combine with your S/R and risk model.
Trend continuation: In strong trends the oscillator will spend more time above/below zero; the colored MA helps keep you aligned and avoid fading every push.
Regime switching: Try Percent Rank or ATR-Scaled on choppy/alts; Z-Score on majors; Highest Abs (N) when you want fastest adaptation.
Risk ideas: Rails can be used as partial-take or invalidate levels. Always backtest on your pair/TF.
Key settings
Normalization: Highest Abs / Z-Score / ATR-Scaled / Percent Rank (with N & factors).
Filters: Extreme threshold, linger bars, slope lookback, confirm on close.
Rails: Expire after X bars; soft-fade step.
Panels: Slim gauge (bottom-right), Info panel (middle-right).
Notes & limits
Prints confirm after the extreme exits ±100; nothing repaints retroactively.
Normalization can change sensitivity—choose the one matching your asset’s regime.
NSR Dynamic Channel - HTF + ReversionNSR Dynamic Channel – HTF Volatility + Reversion
(Beginner-friendly, pro-grade, non-repainting)
The NSR Dynamic Channel builds an adaptive volatility envelope that compares current price action to a statistically-derived “expected” range pulled from a user-selected higher timeframe (HTF).
Is this just another keltner variation?
In short: Keltner reacts. NSR anticipates.
Keltner says “price moved a lot.”
NSR says “this move is abnormal compared to the last 2 days on a higher timeframe — and here’s the probability it snaps back.”
The channel is not a simple multiple of recent ATR or standard deviation; instead it:
Samples HTF volatility over a rolling window (default: last 2 days on the chosen HTF).
Expected Range
HTF Volatility Spread = StDev of 1-bar ATR on the HTF
Scales this HTF range to the current chart’s volatility using a compression ratio :
compRatio = SMA(High-Low over lookback) / Expected Range
This makes the channel tighten in low-vol regimes and widen in high-vol regimes .
Centers the channel on a composite mean ( AVGMEAN ) calculated from:
Smoothed Adaptive Averages of the current timeframe close
SMA of close over the user-defined lookback ( Slow )
The three means are averaged to reduce lag and noise.
Draws two layers :
HTF Expected Channel (gray fill) = PAMEAN ± expectedD
Dynamic Expected Band (inner gray) = HTF Expected Range
Adds a fast 2σ envelope around AVGMEAN using the standard deviation of close over the lookback period.
Core Calculations (Conceptual Overview)
HTF Baseline → ATR on user HTF → SMA & StDev over a defined number of days
Compression Ratio → Normalizes current range to HTF “normal” volatility
Expected Band Width → Expected Range × CompressionRatio
Bias Detection → % change of composite mean over 2 bars → “bullish” / “bearish” filter
Overextension % → Position of price within the expected band (0–100%)
How to Use It (3 Steps)
Apply to any chart – defaults work on futures (NQ/ES), stocks (SPY), crypto (BTC), forex, etc.
Price is outside both the fast 2σ envelope and the HTF-scaled expected band
Expect some sort of reversion
Enable alerts – two built-in conditions:
NSR Exit Long – bullish bias + high crosses upper expected edge
NSR Exit Short – bearish bias + low crosses lower expected edge
Optional toggles :
Show 2σ Price Range → fast overextension lines
Expected Channel → HTF-based gray fill
Mean → MEAN centerline
Why It Works
Context-aware : Uses HTF “normal” volatility as anchor
Adaptive : Shrinks in consolidation, expands in breakouts
Filtered signals : Only triggers when both statistical layers agree
Non-repainting : All calculations use confirmed bars
Happy trading!
nsrgroup
