Grothendieck-Teichmüller Geometric SynthesisDskyz's Grothendieck-Teichmüller Geometric Synthesis (GTGS)
THEORETICAL FOUNDATION: A SYMPHONY OF GEOMETRIES
The 🎓 GTGS is built upon a revolutionary premise: that market dynamics can be modeled as geometric and topological structures. While not a literal academic implementation—such a task would demand computational power far beyond current trading platforms—it leverages core ideas from advanced mathematical theories as powerful analogies and frameworks for its algorithms. Each component translates an abstract concept into a practical market calculation, distinguishing GTGS by identifying deeper structural patterns rather than relying on standard statistical measures.
1. Grothendieck-Teichmüller Theory: Deforming Market Structure
The Theory : Studies symmetries and deformations of geometric objects, focusing on the "absolute" structure of mathematical spaces.
Indicator Analogy : The calculate_grothendieck_field function models price action as a "deformation" from its immediate state. Using the nth root of price ratios (math.pow(price_ratio, 1.0/prime)), it measures market "shape" stretching or compression, revealing underlying tensions and potential shifts.
2. Topos Theory & Sheaf Cohomology: From Local to Global Patterns
The Theory : A framework for assembling local properties into a global picture, with cohomology measuring "obstructions" to consistency.
Indicator Analogy : The calculate_topos_coherence function uses sine waves (math.sin) to represent local price "sections." Summing these yields a "cohomology" value, quantifying price action consistency. High values indicate coherent trends; low values signal conflict and uncertainty.
3. Tropical Geometry: Simplifying Complexity
The Theory : Transforms complex multiplicative problems into simpler, additive, piecewise-linear ones using min(a, b) for addition and a + b for multiplication.
Indicator Analogy : The calculate_tropical_metric function applies tropical_add(a, b) => math.min(a, b) to identify the "lowest energy" state among recent price points, pinpointing critical support levels non-linearly.
4. Motivic Cohomology & Non-Commutative Geometry
The Theory : Studies deep arithmetic and quantum-like properties of geometric spaces.
Indicator Analogy : The motivic_rank and spectral_triple functions compute weighted sums of historical prices to capture market "arithmetic complexity" and "spectral signature." Higher values reflect structured, harmonic price movements.
5. Perfectoid Spaces & Homotopy Type Theory
The Theory : Abstract fields dealing with p-adic numbers and logical foundations of mathematics.
Indicator Analogy : The perfectoid_conv and type_coherence functions analyze price convergence and path identity, assessing the "fractal dust" of price differences and price path cohesion, adding fractal and logical analysis.
The Combination is Key : No single theory dominates. GTGS ’s Unified Field synthesizes all seven perspectives into a comprehensive score, ensuring signals reflect deep structural alignment across mathematical domains.
🎛️ INPUTS: CONFIGURING THE GEOMETRIC ENGINE
The GTGS offers a suite of customizable inputs, allowing traders to tailor its behavior to specific timeframes, market sectors, and trading styles. Below is a detailed breakdown of key input groups, their functionality, and optimization strategies, leveraging provided tooltips for precision.
Grothendieck-Teichmüller Theory Inputs
🧬 Deformation Depth (Absolute Galois) :
What It Is : Controls the depth of Galois group deformations analyzed in market structure.
How It Works : Measures price action deformations under automorphisms of the absolute Galois group, capturing market symmetries.
Optimization :
Higher Values (15-20) : Captures deeper symmetries, ideal for major trends in swing trading (4H-1D).
Lower Values (3-8) : Responsive to local deformations, suited for scalping (1-5min).
Timeframes :
Scalping (1-5min) : 3-6 for quick local shifts.
Day Trading (15min-1H) : 8-12 for balanced analysis.
Swing Trading (4H-1D) : 12-20 for deep structural trends.
Sectors :
Stocks : Use 8-12 for stable trends.
Crypto : 3-8 for volatile, short-term moves.
Forex : 12-15 for smooth, cyclical patterns.
Pro Tip : Increase in trending markets to filter noise; decrease in choppy markets for sensitivity.
🗼 Teichmüller Tower Height :
What It Is : Determines the height of the Teichmüller modular tower for hierarchical pattern detection.
How It Works : Builds modular levels to identify nested market patterns.
Optimization :
Higher Values (6-8) : Detects complex fractals, ideal for swing trading.
Lower Values (2-4) : Focuses on primary patterns, faster for scalping.
Timeframes :
Scalping : 2-3 for speed.
Day Trading : 4-5 for balanced patterns.
Swing Trading : 5-8 for deep fractals.
Sectors :
Indices : 5-8 for robust, long-term patterns.
Crypto : 2-4 for rapid shifts.
Commodities : 4-6 for cyclical trends.
Pro Tip : Higher towers reveal hidden fractals but may slow computation; adjust based on hardware.
🔢 Galois Prime Base :
What It Is : Sets the prime base for Galois field computations.
How It Works : Defines the field extension characteristic for market analysis.
Optimization :
Prime Characteristics :
2 : Binary markets (up/down).
3 : Ternary states (bull/bear/neutral).
5 : Pentagonal symmetry (Elliott waves).
7 : Heptagonal cycles (weekly patterns).
11,13,17,19 : Higher-order patterns.
Timeframes :
Scalping/Day Trading : 2 or 3 for simplicity.
Swing Trading : 5 or 7 for wave or cycle detection.
Sectors :
Forex : 5 for Elliott wave alignment.
Stocks : 7 for weekly cycle consistency.
Crypto : 3 for volatile state shifts.
Pro Tip : Use 7 for most markets; 5 for Elliott wave traders.
Topos Theory & Sheaf Cohomology Inputs
🏛️ Temporal Site Size :
What It Is : Defines the number of time points in the topological site.
How It Works : Sets the local neighborhood for sheaf computations, affecting cohomology smoothness.
Optimization :
Higher Values (30-50) : Smoother cohomology, better for trends in swing trading.
Lower Values (5-15) : Responsive, ideal for reversals in scalping.
Timeframes :
Scalping : 5-10 for quick responses.
Day Trading : 15-25 for balanced analysis.
Swing Trading : 25-50 for smooth trends.
Sectors :
Stocks : 25-35 for stable trends.
Crypto : 5-15 for volatility.
Forex : 20-30 for smooth cycles.
Pro Tip : Match site size to your average holding period in bars for optimal coherence.
📐 Sheaf Cohomology Degree :
What It Is : Sets the maximum degree of cohomology groups computed.
How It Works : Higher degrees capture complex topological obstructions.
Optimization :
Degree Meanings :
1 : Simple obstructions (basic support/resistance).
2 : Cohomological pairs (double tops/bottoms).
3 : Triple intersections (complex patterns).
4-5 : Higher-order structures (rare events).
Timeframes :
Scalping/Day Trading : 1-2 for simplicity.
Swing Trading : 3 for complex patterns.
Sectors :
Indices : 2-3 for robust patterns.
Crypto : 1-2 for rapid shifts.
Commodities : 3-4 for cyclical events.
Pro Tip : Degree 3 is optimal for most trading; higher degrees for research or rare event detection.
🌐 Grothendieck Topology :
What It Is : Chooses the Grothendieck topology for the site.
How It Works : Affects how local data integrates into global patterns.
Optimization :
Topology Characteristics :
Étale : Finest topology, captures local-global principles.
Nisnevich : A1-invariant, good for trends.
Zariski : Coarse but robust, filters noise.
Fpqc : Faithfully flat, highly sensitive.
Sectors :
Stocks : Zariski for stability.
Crypto : Étale for sensitivity.
Forex : Nisnevich for smooth trends.
Indices : Zariski for robustness.
Timeframes :
Scalping : Étale for precision.
Swing Trading : Nisnevich or Zariski for reliability.
Pro Tip : Start with Étale for precision; switch to Zariski in noisy markets.
Unified Field Configuration Inputs
⚛️ Field Coupling Constant :
What It Is : Sets the interaction strength between geometric components.
How It Works : Controls signal amplification in the unified field equation.
Optimization :
Higher Values (0.5-1.0) : Strong coupling, amplified signals for ranging markets.
Lower Values (0.001-0.1) : Subtle signals for trending markets.
Timeframes :
Scalping : 0.5-0.8 for quick, strong signals.
Swing Trading : 0.1-0.3 for trend confirmation.
Sectors :
Crypto : 0.5-1.0 for volatility.
Stocks : 0.1-0.3 for stability.
Forex : 0.3-0.5 for balance.
Pro Tip : Default 0.137 (fine structure constant) is a balanced starting point; adjust up in choppy markets.
📐 Geometric Weighting Scheme :
What It Is : Determines the framework for combining geometric components.
How It Works : Adjusts emphasis on different mathematical structures.
Optimization :
Scheme Characteristics :
Canonical : Equal weighting, balanced.
Derived : Emphasizes higher-order structures.
Motivic : Prioritizes arithmetic properties.
Spectral : Focuses on frequency domain.
Sectors :
Stocks : Canonical for balance.
Crypto : Spectral for volatility.
Forex : Derived for structured moves.
Indices : Motivic for arithmetic cycles.
Timeframes :
Day Trading : Canonical or Derived for flexibility.
Swing Trading : Motivic for long-term cycles.
Pro Tip : Start with Canonical; experiment with Spectral in volatile markets.
Dashboard and Visual Configuration Inputs
📋 Show Enhanced Dashboard, 📏 Size, 📍 Position :
What They Are : Control dashboard visibility, size, and placement.
How They Work : Display key metrics like Unified Field , Resonance , and Signal Quality .
Optimization :
Scalping : Small size, Bottom Right for minimal chart obstruction.
Swing Trading : Large size, Top Right for detailed analysis.
Sectors : Universal across markets; adjust size based on screen setup.
Pro Tip : Use Large for analysis, Small for live trading.
📐 Show Motivic Cohomology Bands, 🌊 Morphism Flow, 🔮 Future Projection, 🔷 Holographic Mesh, ⚛️ Spectral Flow :
What They Are : Toggle visual elements representing mathematical calculations.
How They Work : Provide intuitive representations of market dynamics.
Optimization :
Timeframes :
Scalping : Enable Morphism Flow and Spectral Flow for momentum.
Swing Trading : Enable all for comprehensive analysis.
Sectors :
Crypto : Emphasize Morphism Flow and Future Projection for volatility.
Stocks : Focus on Cohomology Bands for stable trends.
Pro Tip : Disable non-essential visuals in fast markets to reduce clutter.
🌫️ Field Transparency, 🔄 Web Recursion Depth, 🎨 Mesh Color Scheme :
What They Are : Adjust visual clarity, complexity, and color.
How They Work : Enhance interpretability of visual elements.
Optimization :
Transparency : 30-50 for balanced visibility; lower for analysis.
Recursion Depth : 6-8 for balanced detail; lower for older hardware.
Color Scheme :
Purple/Blue : Analytical focus.
Green/Orange : Trading momentum.
Pro Tip : Use Neon Purple for deep analysis; Neon Green for active trading.
⏱️ Minimum Bars Between Signals :
What It Is : Minimum number of bars required between consecutive signals.
How It Works : Prevents signal clustering by enforcing a cooldown period.
Optimization :
Higher Values (10-20) : Fewer signals, avoids whipsaws, suited for swing trading.
Lower Values (0-5) : More responsive, allows quick reversals, ideal for scalping.
Timeframes :
Scalping : 0-2 bars for rapid signals.
Day Trading : 3-5 bars for balance.
Swing Trading : 5-10 bars for stability.
Sectors :
Crypto : 0-3 for volatility.
Stocks : 5-10 for trend clarity.
Forex : 3-7 for cyclical moves.
Pro Tip : Increase in choppy markets to filter noise.
Hardcoded Parameters
Tropical, Motivic, Spectral, Perfectoid, Homotopy Inputs : Fixed to optimize performance but influence calculations (e.g., tropical_degree=4 for support levels, perfectoid_prime=5 for convergence).
Optimization : Experiment with codebase modifications if advanced customization is needed, but defaults are robust across markets.
🎨 ADVANCED VISUAL SYSTEM: TRADING IN A GEOMETRIC UNIVERSE
The GTTMTSF ’s visuals are direct representations of its mathematics, designed for intuitive and precise trading decisions.
Motivic Cohomology Bands :
What They Are : Dynamic bands ( H⁰ , H¹ , H² ) representing cohomological support/resistance.
Color & Meaning : Colors reflect energy levels ( H⁰ tightest, H² widest). Breaks into H¹ signal momentum; H² touches suggest reversals.
How to Trade : Use for stop-loss/profit-taking. Band bounces with Dashboard confirmation are high-probability setups.
Morphism Flow (Webbing) :
What It Is : White particle streams visualizing market momentum.
Interpretation : Dense flows indicate strong trends; sparse flows signal consolidation.
How to Trade : Follow dominant flow direction; new flows post-consolidation signal trend starts.
Future Projection Web (Fractal Grid) :
What It Is : Fibonacci-period fractal projections of support/resistance.
Color & Meaning : Three-layer lines (white shadow, glow, colored quantum) with labels showing price, topological class, anomaly strength (φ), resonance (ρ), and obstruction ( H¹ ). ⚡ marks extreme anomalies.
How to Trade : Target ⚡/● levels for entries/exits. High-anomaly levels with weakening Unified Field are reversal setups.
Holographic Mesh & Spectral Flow :
What They Are : Visuals of harmonic interference and spectral energy.
How to Trade : Bright mesh nodes or strong Spectral Flow warn of building pressure before price movement.
📊 THE GEOMETRIC DASHBOARD: YOUR MISSION CONTROL
The Dashboard translates complex mathematics into actionable intelligence.
Unified Field & Signals :
FIELD : Master value (-10 to +10), synthesizing all geometric components. Extreme readings (>5 or <-5) signal structural limits, often preceding reversals or continuations.
RESONANCE : Measures harmony between geometric field and price-volume momentum. Positive amplifies bullish moves; negative amplifies bearish moves.
SIGNAL QUALITY : Confidence meter rating alignment. Trade only STRONG or EXCEPTIONAL signals for high-probability setups.
Geometric Components :
What They Are : Breakdown of seven mathematical engines.
How to Use : Watch for convergence. A strong Unified Field is reliable when components (e.g., Grothendieck , Topos , Motivic ) align. Divergence warns of trend weakening.
Signal Performance :
What It Is : Tracks indicator signal performance.
How to Use : Assesses real-time performance to build confidence and understand system behavior.
🚀 DEVELOPMENT & UNIQUENESS: BEYOND CONVENTIONAL ANALYSIS
The GTTMTSF was developed to analyze markets as evolving geometric objects, not statistical time-series.
Why This Is Unlike Anything Else :
Theoretical Depth : Uses geometry and topology, identifying patterns invisible to statistical tools.
Holistic Synthesis : Integrates seven deep mathematical frameworks into a cohesive Unified Field .
Creative Implementation : Translates PhD-level mathematics into functional Pine Script , blending theory and practice.
Immersive Visualization : Transforms charts into dynamic geometric landscapes for intuitive market understanding.
The GTTMTSF is more than an indicator; it’s a new lens for viewing markets, for traders seeking deeper insight into hidden order within chaos.
" Where there is matter, there is geometry. " - Johannes Kepler
— Dskyz , Trade with insight. Trade with anticipation.
Indicators and strategies
BackTestLibLibrary "BackTestLib"
Allows backtesting indicator performance. Tracks typical metrics such as won/loss, profit factor, draw down, etc. Trading View strategy library provides similar (and more comprehensive)
functionality but only works with strategies. This libary was created to address performance tracking within indicators.
Two primary outputs are generated:
1. Summary Table: Displays overall performance metrics for the indicator over the chart's loaded timeframe and history
2. Details Table: Displays a table of individual trade entries and exits. This table can grow larger than the available chart space. It does have a max number of rows supported. I haven't
found a way to add scroll bars or scroll bar equivalents yet.
f_init(data, _defaultStopLoss, _defaultTakeProfit, _useTrailingStop, _useTraingStopToBreakEven, _trailingStopActivation, _trailingStopOffset)
f_init Initialize the backtest data type. Called prior to using the backtester functions
Parameters:
data (backtesterData) : backtesterData to initialize
_defaultStopLoss (float) : Default trade stop loss to apply
_defaultTakeProfit (float) : Default trade take profit to apply
_useTrailingStop (bool) : Trailing stop enabled
_useTraingStopToBreakEven (bool) : When trailing stop active, trailing stop will increase no further than the entry price
_trailingStopActivation (int) : When trailing stop active, trailing will begin once price exceeds base stop loss by this number of points
_trailingStopOffset (int) : When trailing stop active, it will trail the max price achieved by this number of points
Returns: Initialized data set
f_buildResultStr(_resultType, _price, _resultPoints, _numWins, _pointsWon, _numLoss, _pointsLost)
f_buildResultStr Helper function to construct a string of resutling data for exit tooltip labels
Parameters:
_resultType (string)
_price (float)
_resultPoints (float)
_numWins (int)
_pointsWon (float)
_numLoss (int)
_pointsLost (float)
f_buildResultLabel(data, labelVertical, labelOffset, long)
f_buildResultLabel Helper function to construct an Exit label for display on the chart
Parameters:
data (backtesterData)
labelVertical (bool)
labelOffset (int)
long (bool)
f_updateTrailingStop(_entryPrice, _curPrice, _sl, _tp, trailingStopActivationInput, trailingStopOffsetInput, useTrailingStopToBreakEven)
f_updateTrailingStop Helper function to advance the trailing stop as price action dictates
Parameters:
_entryPrice (float)
_curPrice (float)
_sl (float)
_tp (float)
trailingStopActivationInput (float)
trailingStopOffsetInput (float)
useTrailingStopToBreakEven (bool)
Returns: Updated stop loss for current price action
f_enterShort(data, entryPrice, fixedStopLoss)
f_enterShort Helper function to enter a short and collect data necessary for tracking the trade entry
Parameters:
data (backtesterData)
entryPrice (float)
fixedStopLoss (float)
Returns: Updated backtest data
f_enterLong(data, entryPrice, fixedStopLoss)
f_enterLong Helper function to enter a long and collect data necessary for tracking the trade entry
Parameters:
data (backtesterData)
entryPrice (float)
fixedStopLoss (float)
Returns: Updated backtest data
f_exitTrade(data)
f_enterLong Helper function to exit a trade and update/reset tracking data
Parameters:
data (backtesterData)
Returns: Updated backtest data
f_checkTradeConditionForExit(data, condition, curPrice, enableRealTime)
f_checkTradeConditionForExit Helper function to determine if provided condition indicates an exit
Parameters:
data (backtesterData)
condition (bool) : When true trade will exit
curPrice (float)
enableRealTime (bool) : When true trade will evaluate if barstate is relatime or barstate is confirmed; otherwise just checks on is confirmed
Returns: Updated backtest data
f_checkTrade(data, curPrice, curLow, curHigh, enableRealTime)
f_checkTrade Helper function to determine if current price action dictates stop loss or take profit exit
Parameters:
data (backtesterData)
curPrice (float)
curLow (float)
curHigh (float)
enableRealTime (bool) : When true trade will evaluate if barstate is relatime or barstate is confirmed; otherwise just checks on is confirmed
Returns: Updated backtest data
f_fillCell(_table, _column, _row, _title, _value, _bgcolor, _txtcolor, _text_size)
f_fillCell Helper function to construct result table cells
Parameters:
_table (table)
_column (int)
_row (int)
_title (string)
_value (string)
_bgcolor (color)
_txtcolor (color)
_text_size (string)
Returns: Table cell
f_prepareStatsTable(data, drawTesterSummary, drawTesterDetails, summaryTableTextSize, detailsTableTextSize, displayRowZero, summaryTableLocation, detailsTableLocation)
f_fillCell Helper function to populate result table
Parameters:
data (backtesterData)
drawTesterSummary (bool)
drawTesterDetails (bool)
summaryTableTextSize (string)
detailsTableTextSize (string)
displayRowZero (bool)
summaryTableLocation (string)
detailsTableLocation (string)
Returns: Updated backtest data
backtesterData
backtesterData - container for backtest performance metrics
Fields:
tradesArray (array) : Array of strings with entries for each individual trade and its results
pointsBalance (series float) : Running sum of backtest points won/loss results
drawDown (series float) : Running sum of backtest total draw down points
maxDrawDown (series float) : Running sum of backtest total draw down points
maxRunup (series float) : Running sum of max points won over the backtest
numWins (series int) : Number of wins of current backtes set
numLoss (series int) : Number of losses of current backtes set
pointsWon (series float) : Running sum of points won to date
pointsLost (series float) : Running sum of points lost to date
entrySide (series string) : Current entry long/short
tradeActive (series bool) : Indicates if a trade is currently active
tradeComplete (series bool) : Indicates if a trade just exited (due to stop loss or take profit)
entryPrice (series float) : Current trade entry price
entryTime (series int) : Current trade entry time
sl (series float) : Current trade stop loss
tp (series float) : Current trade take profit
defaultStopLoss (series float) : Default trade stop loss to apply
defaultTakeProfit (series float) : Default trade take profit to apply
useTrailingStop (series bool) : Trailing stop enabled
useTrailingStopToBreakEven (series bool) : When trailing stop active, trailing stop will increase no further than the entry price
trailingStopActivation (series int) : When trailing stop active, trailing will begin once price exceeds base stop loss by this number of points
trailingStopOffset (series int) : When trailing stop active, it will trail the max price achieved by this number of points
resultType (series string) : Current trade won/lost
exitPrice (series float) : Current trade exit price
resultPoints (series float) : Current trade points won/lost
summaryTable (series table) : Table to deisplay summary info
tradesTable (series table) : Table to display per trade info
Boring Candles by The School of Dalal StreetThis indicator highlights the "boring" candles. These are candles where the body is less than 50% in length as compared to the high and low length. This allows us to quickly find the lower timeframe demand/supply without switching the chart timeframe. The use case is to quickly find our targets based on lower time frames.
Luma DCA Tracker (BTC)Luma DCA Tracker (BTC) – User Guide
Function
This indicator simulates a regular Bitcoin investment strategy (Dollar Cost Averaging). It calculates and visualizes:
Accumulated BTC amount
Average entry price
Total amount invested
Current portfolio value
Profit/loss in absolute and percentage terms
Settings
Investment per interval
Fixed amount to be invested at each interval (e.g., 100 USD)
Start date
The date when DCA simulation begins
Investment interval
Choose between:
daily, weekly, every 14 days, or monthly
Show investment data
Displays additional chart lines (total invested, value, profit, etc.)
Chart Elements
Orange line: Average DCA entry price
Grey dots: Entry points based on selected interval
Info box (bottom left): Live summary of all key values
Notes
Purchases are simulated at the closing price of each interval
No fees, slippage, or taxes are included
The indicator is a simulation only and not linked to an actual portfolio
Copper to Bitcoin RatioRatio: Divides copper price by Bitcoin price (copper / bitcoin). Since copper is in USD per pound and Bitcoin is in USD, the ratio is unitless but reflects copper’s value relative to Bitcoin.
Plotting: The ratio is plotted as a blue line, with an optional 20-period simple moving average (red line) for smoothing.
This can reflect market sentiment (e.g., industrial demand vs. crypto speculation).
Copper to Gold Ratioratio = copper / gold: Calculates the ratio by dividing copper price by gold price.
plot(ratio): Plots the ratio as a blue line.
ma = ta.sma(ratio, 20): Adds a 20-period simple moving average (optional) to smooth the ratio, plotted as a red line.
A rising Copper/Gold ratio often signals economic expansion (strong copper demand relative to gold), while a falling ratio may indicate economic uncertainty or recession fears, as gold outperforms copper.
The ratio is also used as a leading indicator for 10-year U.S. Treasury yields, with a rising ratio often correlating with higher yields.
PriceLevels GBGoldbach Price Levels – Identify Algorithmic Key Zones
This open-source indicator is designed to help traders identify potential algorithmic key zones by highlighting price levels ending with specific numbers such as 03, 11, 29, 35, 65, and 71. These levels may act as inflection points or hesitation areas based on observed behavioral patterns in price movement.
What It Does:
📌 Scans and plots horizontal price levels where the price ends with one of the selected number combinations
🎯 Toggle on/off visibility for each number ending
🎨 Customize color and thickness for each level
🏷️ Shows price labels at the end of each line
🌗 Label styles (color/transparency) are adjustable for both dark and light chart themes
🧠 Why Use It:
This tool is ideal for discretionary traders who study market structure through static price anchors. It provides a visual reference for recurring numerical levels that may be used in algorithmic trading models or serve as psychological price zones.
⚠️ Disclaimer:
This script is open-source and intended for educational and analytical purposes only. No trading signals or performance guarantees are provided. Please use your own judgment when applying this tool in a trading context.
Adaptive RSI Oscillator📌 Adaptive RSI Oscillator
This indicator transforms the classic RSI into a fully adaptive, self-optimizing oscillator — normalized between -1 and 1, dynamically smoothed, and enhanced with divergence detection.
🔧 Key Features
Self-Optimizing RSI: Automatically selects the optimal RSI lookback length based on return stability (no hardcoded periods).
Dynamic Smoothing: Adapts to market conditions using a fraction of the optimized length.
Normalized Output : Converts traditional RSI to a consistent scale across all assets and timeframes.
Divergence Detection: Compares RSI behavior vs. price percentile ranks and scales the signal accordingly.
Gradient Visualization: Color-coded background and plot lines reflect the strength and direction of the signal with soft transitions.
Neutral Zone Adaptation: Dynamically widens or narrows the zone of inaction based on volatility, reducing noise.
🎯 Use Cases
Identify extreme momentum zones without relying on fixed 70/30 RSI levels
Detect divergences early with adaptive filtering
Highlight potential exhaustion or continuation
⚠️ Disclaimer: This indicator is for informational and educational purposes only. It does not constitute financial advice or a recommendation to buy or sell any security. Always conduct your own research and consult a licensed financial advisor before making investment decisions. Use at your own risk.
SHYY TFC Candles_Confirmation X 4TF)SHYY Real-Time FTC Confirmation is a multi-timeframe trend alignment tool designed to provide real-time confirmation of market direction across up to four configurable timeframes. Unlike traditional tools that rely on closed candles, this version uses in-progress bars to detect live momentum, allowing traders to respond as trends are forming rather than after they are confirmed.
This script checks the current price direction on each selected timeframe by comparing the current close to the open of the same candle. A timeframe is considered bullish if the close is above the open, bearish if below, and neutral if equal. If all enabled timeframes are aligned in the same direction, the current chart candle is colored accordingly.
White candles indicate that all selected timeframes are currently bullish. Yellow candles indicate that all selected timeframes are currently bearish. If the timeframes are not fully aligned, the candle remains uncolored.
Each of the four timeframes can be configured individually in the settings panel. Users can also enable or disable each timeframe independently using checkboxes, allowing flexibility in how the confirmation logic is applied.
The script uses a single request.security() call per timeframe with lookahead enabled, so that the information shown reflects the live status of each timeframe’s bar, not just completed ones. This makes it suitable for real-time decision-making and strategy filtering.
This tool can assist scalpers, trend followers, and breakout traders in aligning trades with broader market direction. It can be used as a standalone trend filter or in conjunction with other indicators and strategies.
No external dependencies or overlays are required.
This is an original script, built to provide real-time, multi-timeframe confirmation using a clean and efficient approach.
SOT & SA Detector ProSOT & SA Detector Pro- Advanced Reversal Pattern Recognition
OVERVIEW
The SOT & SA Detector is an educational indicator designed to identify potential market reversal points through systematic analysis of candlestick patterns, volume confirmation, and price wave structures. SOT (Shorting of Thrust) signals suggest potential bearish reversals after upward price movements, while SA (Selling Accumulation) signals indicate possible bullish reversals following downward trends. This tool helps traders recognize key market transition points by combining multiple technical criteria for enhanced signal reliability.
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HOW IT WORKS
Technical Methodology
The indicator employs a multi-factor analysis approach that evaluates:
Wave Structure Analysis: Identifies minimum 2-bar directional waves (upward for SOT, downward for SA)
Price Delta Validation: Ensures closing price changes remain within specified percentage thresholds (default 0.3%) best 0.1.
Candlestick Tail Analysis: Measures rejection wicks using configurable tail multipliers
Volume Confirmation: Requires increased volume compared to previous periods
Pattern Confirmation: Validates signals through subsequent price action
Signal Generation Process
Pattern Recognition: Scans for qualifying candlestick formations with appropriate tail characteristics
Volume Verification: Confirms patterns with volume expansion using adjustable multiplier
Price Confirmation: Validates signals when price breaks and closes beyond pattern extremes
Signal Display: Places labeled markers and draws horizontal reference levels
Mathematical Foundation
Delta calculation: math.abs(close - close ) / close <= deltaPercent / 100
Tail analysis: (high - close ) >= tailMultiplier * (close - low ) for SOT
Volume filter: volume >= volume * volumeFactor
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KEY FEATURES
Dual Pattern Recognition: Identifies both bullish (SA) and bearish (SOT) reversal candidates
Volume Integration: Incorporates volume analysis for enhanced signal validation
Customizable Parameters: Adjustable wave length, delta percentage, tail multiplier, and volume factor
Visual Clarity: Color-coded bar highlighting, labeled signals, and horizontal reference levels
Time-Based Filtering: Configurable analysis period to focus on recent market activity
Non-Repainting Signals: Confirmed signals remain stable and do not change with new price data
Alert System: Built-in notifications for both initial signals and subsequent confirmations
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HOW TO USE
Signal Interpretation
Red SOT Labels: Appear above potential bearish reversal candles with downward-pointing markers
Green SA Labels: Display below potential bullish reversal candles with upward-pointing markers
Horizontal Lines: Extend from signal levels to provide ongoing reference points
Bar Coloring: Highlights qualifying pattern candles for visual emphasis
Trading Application
This indicator serves as an educational tool for pattern recognition and should be used in conjunction with additional analysis methods. Consider SOT signals as potential areas of selling pressure following upward moves, while SA signals may indicate buying interest after downward price action.
Best Practices
Combine with trend analysis and support/resistance levels
Consider overall market context and timeframe alignment
Use proper risk management techniques
Validate signals with additional technical indicators
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SETTINGS
Analysis Days (Default: 20)
Controls the lookback period for signal detection. Higher values extend historical analysis while lower values focus on recent activity.
Minimum Bars in Wave (Default: 2)
Sets the minimum consecutive bars required to establish directional wave patterns. Increase for stronger trend confirmation.
Max Close Change % (Default: 0.3) best 0.1.
Defines acceptable closing price variation between consecutive bars. Lower values require tighter price consolidation.
Tail Multiplier (Default: 1.0) best 1.5 or more.
Adjusts sensitivity for candlestick tail analysis. Higher values require more pronounced rejection wicks.
Volume Factor (Default: 1.0)
Sets volume expansion threshold compared to previous period. Values above 1.0 require volume increases.
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LIMITATIONS
Market Conditions
May produce false signals in highly volatile or low-volume conditions
Effectiveness varies across different market environments and timeframes
Requires sufficient volume data for optimal performance
Signal Timing
Signals appear after pattern completion, not in real-time during formation
Confirmation signals depend on subsequent price action
Historical signals do not guarantee future market behavior
Technical Constraints
Limited to analyzing price and volume data only
Does not incorporate fundamental analysis or external market factors
Performance may vary significantly across different trading instruments
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IMPORTANT DISCLAIMERS
This indicator is designed for educational purposes and technical analysis learning. It does not constitute financial advice, investment recommendations, or trading signals. Past performance does not guarantee future results. Trading involves substantial risk of loss, and this tool should be used alongside proper risk management techniques and additional analysis methods.
Always conduct thorough analysis using multiple indicators and consider market context before making trading decisions. The SOT & SA patterns represent potential reversal points but do not guarantee price direction changes.
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Credits: Original concept and Pine Script implementation by Everyday_Trader_X
Version: Pine Script v6 compatible
Category: Technical Analysis / Reversal Detection
Overlay: Yes (displays on price chart)
Adaptive Quadratic Kernel EnvelopeThis study draws a fair-value curve from a quadratic-weighted (Nadaraya-Watson) regression. Alpha sets how sharply weights decay inside the look-back window, so you trade lag against smoothness with one slider. Band half-width is ATRslow times a bounded fast/slow ATR ratio, giving an instant response to regime shifts without overshooting on spikes. Work in log space when an instrument grows exponentially, equal percentage moves then map to equal vertical steps. NearBase and FarBase define a progression of adaptive thresholds, useful for sizing exits or calibrating mean-reversion logic. Non-repaint mode keeps one-bar delay for clean back-tests, predictive mode shows the zero-lag curve for live decisions.
Key points
- Quadratic weights cut phase error versus Gaussian or SMA-based envelopes.
- Dual-ATR scaling updates width on the next bar, no residual lag.
- Log option preserves envelope symmetry across multi-decade data.
- Alpha provides direct control of curvature versus noise.
- Built-in alerts trigger on the first adaptive threshold, ready for automation.
Typical uses
Trend bias from the slope of the curve.
Entry timing when price pierces an inner threshold and momentum stalls.
Breakout confirmation when closes hold beyond outer thresholds while volatility expands.
Stops and targets anchored to chosen thresholds, automatically matching current noise.
Volume VA with POC Based Percent DeviationsThis is a slightly different take on my previous version that plotted fibonacci retracement levels based on the POC to value area high/low.
This indicator is also based on the volume value area that plots developing POC, VAH, and VAL as well as historical levels. However, instead of plotting fib levels, this script automatically projects percentage deviation levels from the current POC. This can help identify potential overextensions, target areas, or mean-reversion setups.
Knowing where price is and the change in price relative to areas of interest can help identify true value and market imbalances. Hence the name VALUE AREA :)
The percent deviation levels are dynamically plotted in relation to the developing POC. As POC shifts so do the % levels.
Gradient Value Area Fill: Instead of a static color, the Value Area is filled with a dynamic gradient. The adjustable color and transparency shift is based on the current price's distance from the POC, giving you an intuitive feel for where price is relative to the POC.
Enjoy!
"May the fourth leaf bring you extra luck!" 🍀
MTF PO3 Big Candle By Rouro📊 MTF PO3 Big Candle By Rouro
This indicator allows you to visualize candles from higher timeframes (HTF) directly on lower timeframe charts.
It draws:
📉 Past candles from the selected HTF.
📈 A projected current candle of a chosen timeframe, extended to the right of the chart.
It's ideal for traders who want to align decisions on lower timeframes with key HTF structures.
⚙️ Inputs & Configuration
🕐 Past Candle Timeframe
Selects the timeframe to visualize historical candles.
(e.g., 4H on a 5-minute chart)
📅 Projected Candle Timeframe
Chooses the timeframe for the current (live) candle that is drawn to the right of the chart.
(e.g., 1D)
➡️ Right Displacement (bars)
Controls how far to the right the projected candle is drawn.
🟩 Bullish Body Color
Defines the color of bullish candle bodies.
🟥 Bearish Body Color
Defines the color of bearish candle bodies.
🔵 Wick Color
Color of the high/low wicks.
🔲 Body Transparency (0–100)
Controls the transparency of the candle body fill.
📌 Show Wicks
Enables or disables drawing of the wicks on all candles.
💡 Notes
If the projected candle is from a very large timeframe (e.g., 1D) and you are on a small timeframe (e.g., 5m), the projection length is limited to avoid overlapping the chart.
All candle shapes update in real time.
The indicator is optimized for performance and includes fail-safes for TradingView's limits.
💬 Support
If you have any questions, feel free to ask in the comments.
If this indicator has been useful or valuable for your trading, please leave a comment saying so — your feedback helps the community and supports the publication process.
✅ Compliant with TradingView’s house rules: No ads, sales, links, or misleading claims.
📌 This is a visual utility tool designed to support multi-timeframe analysis.
ATR % Line from Day LowHow can you make sure that you're not buying a stock that is too extended?
By limiting your buys to within a certain percentage of either the low-of-the-day (LoD) if you're going long, or to the high-of-the-day (HoD) if you're shorting a stock. This script will help you do just that.
Limiting stock purchases to within a certain percentage of the Average True Range (ATR) from the day's low or high is a risk management technique that offers several key benefits:
Risk Control and Position Sizing
By using ATR as a boundary, you're essentially creating a volatility-adjusted buffer. Since ATR measures recent price volatility, this approach prevents you from buying into stocks that have already moved significantly beyond their normal trading range. This helps avoid entering positions when the stock might be overextended and due for a pullback.
Improved Entry Timing
This strategy encourages patience and discipline. Rather than chasing a stock that's already run up substantially from its low, you wait for better entry points. For example, if you set a limit of 50% of ATR from the day's low, you're only buying when the stock hasn't moved more than half its typical daily range from the bottom.
Volatility Awareness
ATR naturally adjusts for each stock's individual volatility characteristics. A high-volatility stock might have an ATR of $2, while a low-volatility stock might have an ATR of $0.50. This approach scales your entry criteria appropriately for each security rather than using arbitrary dollar amounts.
Reduced Emotional Trading
Having a systematic rule removes the temptation to chase momentum or buy at poor technical levels. It forces you to wait for the stock to come back to more reasonable levels relative to its recent trading behavior.
Better Risk-Reward Ratios
By entering closer to the day's low (within your ATR percentage), you're typically getting a better risk-reward setup. Your stop loss (often placed below the day's low) will be tighter, while your potential upside remains intact.
This approach works particularly well for swing traders and those looking to enter positions on pullbacks or during consolidation periods rather than breakout scenarios.
To save valuable real estate on your chart, there's also an option that can give you a compact version of this indicator which will show only the "Current Day's Low/High" and "Target Price". "Target Price" being the price at which your max buy limit is based on the % ATR you choose in settings.
Trend TraderDescription and Usage of the "Trend Trader" Indicator
The "Trend Trader" indicator, created by Gerardo Mercado as a legacy project, is a versatile trading tool designed to identify potential buy and sell signals across various instruments. While it provides predefined settings for popular instruments like US30, NDX100, GER40, and GOLD, it can be seamlessly adapted to any market, including forex pairs like EUR/USD. The indicator combines moving averages, time-based filters, and MACD confirmation to enhance decision-making for traders.
How It Works
Custom Moving Averages (MAs):
The indicator uses two moving averages:
Short MA: A faster-moving average (default: 10 periods).
Long MA: A slower-moving average (default: 100 periods).
Buy signals are generated when the Short MA crosses above the Long MA.
Sell signals are triggered when the Short MA crosses below the Long MA.
Time-Based Signals:
The user can define specific trading session times (start and end in UTC) to focus on high-activity periods for their chosen market.
Signals and background coloring are only active during the allowed session times.
MACD Confirmation:
A MACD (Moving Average Convergence Divergence) calculation on a 15-minute timeframe ensures stronger confirmation for signals.
Buy signals require the MACD line to be above the signal line.
Sell signals require the MACD line to be at or below the signal line.
Target Levels:
Predefined profit targets are dynamically set based on the selected trading instrument.
While it includes settings for US30, NDX100, GER40, and GOLD, the target levels can be adjusted to fit the volatility and structure of any asset, including forex pairs like EUR/USD.
Target 1 and Target 2 levels display when these thresholds are met after an entry signal.
Adaptability to Any Market:
Although predefined options are included for specific instruments, the indicator's moving averages, time settings, and MACD logic are applicable to any tradable asset, making it suitable for forex, commodities, indices, and more.
Visual Alerts:
Labels appear on the chart to highlight "BUY" and "SELL" signals at crossover points.
Additional labels indicate when price movements reach the predefined target levels.
Bar and background coloring visually represent active signals and MACD alignment.
Purpose
The indicator aims to simplify trend-following and momentum-based trading strategies. By integrating moving averages, MACD, customizable time sessions, and dynamic targets, it offers clear entry and exit points while being adaptable to the needs of individual traders across diverse markets.
How to Use
Setup:
Add the indicator to your TradingView chart.
Configure the moving average periods, trading session times, and target levels according to your preferences.
Select the instrument for predefined target settings or customize them to fit the asset you’re trading (e.g., EUR/USD or other forex pairs).
Interpreting Signals:
Buy Signal: The Short MA crosses above the Long MA, MACD confirms the upward trend, and the session is active.
Sell Signal: The Short MA crosses below the Long MA, MACD confirms the downward trend, and the session is active.
Adapt for Any Instrument:
Adjust the predefined target levels to match the volatility and trading style for your chosen asset.
For forex pairs like EUR/USD, consider typical pip movements to set appropriate profit targets.
Targets:
Use the provided target labels (e.g., 50 or 100 points) or customize them to reflect realistic profit goals based on the asset’s volatility.
Visual Aids:
Pay attention to the background color:
Greenish: Indicates a bullish trend during the allowed session.
Redish: Indicates a bearish trend during the allowed session.
Use the "BUY" and "SELL" labels for actionable insights.
This indicator is a flexible and powerful tool, suitable for traders across all markets. Its adaptability ensures that it can enhance your strategy, whether you’re trading forex, commodities, indices, or other assets. By offering actionable alerts and customizable settings, the "Trend Trader" serves as a valuable addition to any trader’s toolkit. FX:EURUSD
Day of Week Highlighter# 📅 Day of Week Highlighter - Global Market Edition
**Enhanced visual trading tool that highlights each day of the week with customizable colors across all major global financial market timezones.**
## 🌍 Global Market Coverage
This indicator supports **27 major financial market timezones**, including:
- **Asia-Pacific**: Tokyo, Sydney, Hong Kong, Singapore, Shanghai, Seoul, Mumbai, Dubai, Auckland (New Zealand)
- **Europe**: London, Frankfurt, Zurich, Paris, Amsterdam, Moscow, Istanbul
- **Americas**: New York, Chicago, Toronto, São Paulo, Buenos Aires
- **Plus UTC and other key financial centers**
## ✨ Key Features
### 🎨 **Fully Customizable Colors**
- Individual color picker for each day of the week
- Transparent overlays that don't obstruct price action
- Professional color scheme defaults
### 🌐 **Comprehensive Timezone Support**
- 27 major global financial market timezones
- Automatic daylight saving time adjustments
- Perfect for multi-market analysis and global trading
### ⚙️ **Flexible Display Options**
- Toggle individual days on/off
- Optional day name labels with size control
- Clean, professional appearance
### 📊 **Trading Applications**
- **Market Session Analysis**: Identify trading patterns by day of week
- **Multi-Market Coordination**: Track different markets in their local time
- **Pattern Recognition**: Spot day-specific market behaviors
- **Risk Management**: Avoid trading on historically volatile days
## 🔧 How to Use
1. **Add to Chart**: Apply the indicator to any timeframe
2. **Select Timezone**: Choose your preferred market timezone from the dropdown
3. **Customize Colors**: Set unique colors for each day in the settings panel
4. **Enable/Disable Days**: Toggle specific days on or off as needed
5. **Optional Labels**: Show day names with customizable label sizes
## 💡 Pro Tips
- Use different color intensities to highlight your preferred trading days
- Combine with other session indicators for comprehensive market timing
- Perfect for swing traders who want to identify weekly patterns
- Ideal for international traders managing multiple market sessions
## 🎯 Perfect For
- Day traders tracking intraday patterns
- Swing traders analyzing weekly cycles
- International traders managing multiple markets
- Anyone wanting better visual organization of their charts
**Works on all timeframes and instruments. Set it once, trade with confidence!**
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*Compatible with Pine Script v6 | No repainting | Lightweight performance*
Market Sessions Indicator by NomadTradesCustomisable Market session indicator
This indicator visually marks the high and low price levels for the Asia, London, and New York trading sessions directly on the chart, using distinct horizontal lines and color-coding for each session. Each session’s high and low are labelled for easy identification, allowing traders to quickly assess key support and resistance levels established during major global market hours. The indicator is designed for clear session demarcation, helping users identify price reactions at these significant levels and supporting multi-session analysis for intraday and swing trading strategies
X-Day Capital Efficiency ScoreThis indicator helps identify the Most Profitable Movers for Your fixed Capital (ie, which assets offer the best average intraday profit potential for a fixed capital).
Unlike traditional volatility indicators (like ATR or % change), this script calculates how much real dollar profit you could have made each day over a custom lookback period — assuming you deployed your full capital into that ticker daily.
How it works:
Calculates the daily intraday range (high − low)
Filters for clean candles (where body > 60% of the candle range)
Assumes you invested the full amount of capital ($100K set as default) on each valid day
Computes an average daily profit score based on price action over the selected period (default set to 20 days)
Plots the score in dollars — higher = more efficient use of capital
Why It’s Useful:
Compare tickers based on real dollar return potential — not just % volatility
Spot low-priced, high-volatility stocks that are better suited for intraday or momentum trading
Inputs:
Capital ($): Amount you're hypothetically deploying (e.g., 100,000)
Look Back Period: Number of past days to average over (e.g., 20)
Haven Average Daily RangeOverview
This indicator is an enhanced version of the traditional ADR tool that adapts to intraday price movements. Unlike static ADR levels, this indicator dynamically adjusts its range boundaries based on real-time price action while maintaining the original ADR calculation framework.
Key Features
ADR calculation based on multiple periods (5, 10, and 20 days)
ADR levels displayed with automatic style changes upon range reach
Customizable display settings (color, line style)
Price labels for better visualization
The indicator helps traders assess the instrument's volatility, identify potential reversal zones, and plan daily trading targets.
Suitable for all timeframes up to D1 and any trading instrument.
How It Works
Session Start (UTC+0): Calculates ADR based on historical data and sets initial High/Low levels
Dynamic Phase: Monitors price action and adjusts the opposite boundary (ADR Low or High) when new extremes are reached.
When price creates new Day high price above the opening price, the ADR Low level moves upward proportionally.
When price creates new Day low price below the opening price, the ADR High level moves downward proportionally.
Completion Phase: Stops adjustments and highlights breach when price reaches either boundary
Trading Application
Entry and Exit Signals
The ADR boundaries serve as key decision points for trade execution. When price approaches the upper ADR boundary, it often signals a potential selling zone, particularly when confluence exists with other overbought indicators such as RSI divergence or resistance levels. Conversely, price reaching the lower ADR boundary frequently indicates potential buying opportunities, especially when supported by oversold conditions or support confluences.
Trend Continuation Assessment
One of the most valuable applications is gauging the probability of continued directional movement. When the current session's price action has not yet reached either ADR boundary, statistical probability favors trend continuation in the established direction. This information helps traders stay with profitable positions longer rather than exiting prematurely.
Reversal and Consolidation Zones
The visual color change to orange when ADR boundaries are reached provides immediate feedback that the normal daily range has been exhausted. At this point, the probability of trend reversal or sideways consolidation increases significantly. This signal helps traders prepare for potential position adjustments or new counter-trend opportunities.
GCM Price Based ColorIndicator Name:
GCM Price Based Color Indicator
Detailed Description:
The GCM Price Based Color Indicator is a unique tool designed to help traders spot potential "pump" events in the market. Unlike traditional Volume Rate of Change (VROC) indicators, this script is conditional: it calculates a VROC value only when both the average volume and the price are increasing. This focus helps filter out volume surges that don't accompany immediate price appreciation, highlighting more relevant "pump" signals.
Key Features & Calculation Logic:
Conditional Volume Rate of Change (VROC):
It first calculates a Simple Moving Average (SMA) of the volume over a user-defined length (lookback period).
It then checks two conditions:
Is the current SMA volume greater than the previous bar's SMA volume (i.e., volumeIncreasing)?
Is the current close price greater than the previous bar's close price (i.e., valueIncreasing)?
Only if both volume Increasing AND value Increasing are true, a VROC value is calculated as (current _ MA _ volume - previous _ MA _ volume) * (100 / previous _ MA _ volume). Otherwise, the VROC for that bar is 0.
Historical Normalization:
The raw VROC value is then normalized against its own historical maximum value observed since the indicator was applied. This scaling brings all VROC values into a common 0-100 range.
Why is this important? Normalization makes the indicator's readings comparable across different assets (e.g., high-volume vs. low-volume stocks/cryptos) and different timeframes, making it easier to interpret the strength of a "pump" relative to its own past.
Dynamic Plot Color (Price-Based):
The plot line's color itself provides an immediate visual cue about the current bar's price action:
Green: close is greater than close (price is up for the current bar).
Red: close is less than close (price is down for the current bar).
Grey: close is equal to close (price is flat for the current bar).
Important Note: The plot color reflects the price movement of the current bar, not the magnitude of the VROC Normalized value itself. This means you can have a high vrocNormalized value (indicating a strong conditional volume surge) but a red plot color if the very next bar's price closes lower, providing a multi-faceted view.
Thresholds & Alerts:
Two horizontal lines (small Pump Threshold and big Pump Threshold) are plotted to visually mark significant levels of normalized pump strength.
Customizable alerts can be set up to notify you when VROC Normalized reaches or exceeds these thresholds, helping you catch potential pump events in real-time.
How to Use It:
Identify Potential Pumps: Look for upward spikes in the VROC Normalized line. Higher spikes indicate stronger pump signals (i.e., a larger increase in average volume coinciding with an increasing price).
Monitor Thresholds: Pay attention when the VROC Normalized line crosses above your small Pump Threshold or big Pump Threshold. These are configurable levels to suit different assets and trading styles.
Observe Plot Color: The line color provides crucial context. A high VROC Normalized (strong pump signal) with a green line indicates current price momentum is still positive. If VROC Normalized is high but the line turns red, it might suggest the initial pump is losing steam or experiencing a pullback.
Combine with Other Tools: This indicator is best used in conjunction with other technical analysis tools (e.g., support/resistance, trend lines, other momentum indicators) for confirmation and a more holistic trading strategy.
Indicator Inputs:
Lookback period (1 - 4999) (default: 420): This length determines the period for the Simple Moving Average (SMA) of volume. A higher value will smooth the volume average more, reacting slower, while a lower value will make it more reactive. Adjust based on the timeframe and asset volatility.
Big Pump Threshold (0.01 - 99.99) (default: 10.0): The normalized VROC Normalized level that signifies a "Big Pump." When VROC Normalized reaches or exceeds this level, an alert can be triggered.
Small Pump Threshold (0.01 - 99.99) (default: 0.5): The normalized VROC Normalized level that signifies a "Small Pump." This is a lower threshold for earlier or less significant pump activity.
Alerts:
Small Pump: Triggers when VROC Normalized crosses above or equals the small Pump Threshold.
Big Pump: Triggers when VROC Normalized crosses above or equals the big Pump Threshold.
Best Practices & Considerations:
Timeframes: The indicator can be used on various timeframes, but its effectiveness may vary. Experiment to find what works best for your chosen asset and trading style.
Volatility: Highly volatile assets might require different threshold settings compared to less volatile ones.
Lag: Due to the use of a Simple Moving Average (SMA) for volume, there will be some inherent lag in the calculation.
Normalization Start: The historic Max for normalization starts with a default value of 10.0. For the very first bars, or if there hasn't been a significant VROC yet, the VROC Normalized might behave differently until a true historical maximum VROC establishes itself.
Not Financial Advice: This indicator is a tool for analysis and does not constitute financial advice. Always perform your own research and manage your risk.
Linear Regression Forecast (ADX Adaptive)Linear Regression Forecast (ADX Adaptive)
This indicator is a dynamic price projection tool that combines multiple linear regression forecasts into a single, adaptive forecast curve. By integrating trend strength via the ADX and directional bias, it aims to visualize how price might evolve in different market environments—from strong trends to mean-reverting conditions.
Core Concept:
This tool builds forward price projections based on a blend of linear regression models with varying lookback lengths (from 2 up to a user-defined max). It then adjusts those projections using two key mechanisms:
ADX-Weighted Forecast Blending
In trending conditions (high ADX), the model follows the raw forecast direction. In ranging markets (low ADX), the forecast flips or reverts, biasing toward mean-reversion. A logistic transformation of directional bias, controlled by a steepness parameter, determines how aggressively this blending reacts to price behavior.
Volatility Scaling
The forecast’s magnitude is scaled based on ADX and directional conviction. When trends are unclear (low ADX or neutral bias), the projection range expands to reflect greater uncertainty and volatility.
How It Works:
Regression Curve Generation
For each regression length from 2 to maxLength, a forward projection is calculated using least-squares linear regression on the selected price source. These forecasts are extrapolated into the future.
Directional Bias Calculation
The forecasted points are analyzed to determine a normalized bias value in the range -1 to +1, where +1 means strongly bullish, -1 means strongly bearish, and 0 means neutral.
Logistic Bias Transformation
The raw bias is passed through a logistic sigmoid function, with a user-defined steepness. This creates a probability-like weight that favors either following or reversing the forecast depending on market context.
ADX-Based Weighting
ADX determines the weighting between trend-following and mean-reversion modes. Below ADX 20, the model favors mean-reversion. Above 25, it favors trend-following. Between 20 and 25, it linearly blends the two.
Blended Forecast Curve
Each forecast point is blended between trend-following and mean-reverting values, scaled for volatility.
What You See:
Forecast Lines: Projected future price paths drawn in green or red depending on direction.
Bias Plot: A separate plot showing post-blend directional bias as a percentage, where +100 is strongly bullish and -100 is strongly bearish.
Neutral Line: A dashed horizontal line at 0 percent bias to indicate neutrality.
User Inputs:
-Max Regression Length
-Price Source
-Line Width
-Bias Steepness
-ADX Length and Smoothing
Use Cases:
Visualize expected price direction under different trend conditions
Adjust trading behavior depending on trending vs ranging markets
Combine with other tools for deeper analysis
Important Notes:
This indicator is for visualization and analysis only. It does not provide buy or sell signals and should not be used in isolation. It makes assumptions based on historical price action and should be interpreted with market context.
Ultra VolumeVisualizes volume intensity using dynamic color gradients and percentile thresholds. Includes optional SMA, bar coloring, and adaptive liquidity boxes to highlight high- and low-volume zones in real time.
Introduction
The Ultra Volume indicator enhances volume analysis by categorizing volume bars into percentile-based intensity levels. It uses color-coded gradients to quickly identify periods of unusually high or low activity. The script also includes an optional simple moving average (SMA), bar coloring, and visual box overlays to highlight zones of significant liquidity shifts.
Detailed Description
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Volume Classification
Volume is segmented into five tiers: Extra High, High, Medium, Normal, and Low, using percentile ranks calculated over a dynamically adjusted historical window. This segmentation adapts based on the chart's timeframe – using 100 bars for daily and 1440/minutes for intraday – allowing for consistent behavior across resolutions.
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Color Gradients
Each volume bar is colored based on its percentile category, smoothly transitioning between thresholds for visual clarity. This makes it easy to spot volume spikes or droughts relative to recent history.
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Simple Moving Average (SMA)
An optional SMA can be plotted on top of the volume bars for trend comparison and baseline reference. Its length and color are fully customizable.
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Bar Coloring
You can optionally color the chart's candlesticks to reflect the same volume intensity as the histogram bars, reinforcing visual cues across the chart.
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Liquidity Boxes
Two adaptive box systems highlight zones of increased or decreased liquidity:
High Liquidity Boxes expand upward when price exceeds the previous box’s top.
Low Liquidity Boxes expand downward when price breaks the previous box’s bottom.
These boxes persist and auto-adjust over time unless reset, helping traders spot key zones of volume-driven price action.
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Box Indexing
A configurable index shift determines how far back in the chart the boxes originate. Setting this to 501 makes them "stick" to the candle where they were first created.
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Data Handling
A safety check ensures the script throws an error if volume data is unavailable (e.g., for some crypto or CFD symbols).
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Summary
Ultra Volume is a practical tool for traders who want more than just raw volume bars. With intelligent percentile-based classification, real-time adaptive liquidity zones, and fully customizable visual elements, it turns volume into a highly readable, actionable signal.
RSI of RSI Deviation (RoRD)RSI of RSI Deviation (RoRD) - Advanced Momentum Acceleration Analysis
What is RSI of RSI Deviation (RoRD)?
RSI of RSI Deviation (RoRD) is a insightful momentum indicator that transcends traditional oscillator analysis by measuring the acceleration of momentum through sophisticated mathematical layering. By calculating RSI on RSI itself (RSI²) and applying advanced statistical deviation analysis with T3 smoothing, RoRD reveals hidden market dynamics that single-layer indicators miss entirely.
This isn't just another RSI variant—it's a complete reimagining of how we measure and visualize momentum dynamics. Where traditional RSI shows momentum, RoRD shows momentum's rate of change . Where others show static overbought/oversold levels, RoRD reveals statistically significant deviations unique to each market's character.
Theoretical Foundation - The Mathematics of Momentum Acceleration
1. RSI² (RSI of RSI) - The Core Innovation
Traditional RSI measures price momentum. RoRD goes deeper:
Primary RSI (RSI₁) : Standard RSI calculation on price
Secondary RSI (RSI²) : RSI calculated on RSI₁ values
This creates a "momentum of momentum" indicator that leads price action
Mathematical Expression:
RSI₁ = 100 - (100 / (1 + RS₁))
RSI² = 100 - (100 / (1 + RS₂))
Where RS₂ = Average Gain of RSI₁ / Average Loss of RSI₁
2. T3 Smoothing - Lag-Free Response
The T3 Moving Average, developed by Tim Tillson, provides:
Superior smoothing with minimal lag
Adaptive response through volume factor (vFactor)
Noise reduction while preserving signal integrity
T3 Formula:
T3 = c1×e6 + c2×e5 + c3×e4 + c4×e3
Where e1...e6 are cascaded EMAs and c1...c4 are volume-factor-based coefficients
3. Statistical Z-Score Deviation
RoRD employs dual-layer Z-score normalization :
Initial Z-Score : (RSI² - SMA) / StDev
Final Z-Score : Z-score of the Z-score for refined extremity detection
This identifies statistically rare events relative to recent market behavior
4. Multi-Timeframe Confluence
Compares current timeframe Z-score with higher timeframe (HTF)
Provides directional confirmation across time horizons
Filters false signals through timeframe alignment
Why RoRD is Different & More Sophisticated
Beyond Traditional Indicators:
Acceleration vs. Velocity : While RSI measures momentum (velocity), RoRD measures momentum's rate of change (acceleration)
Adaptive Thresholds : Z-score analysis adapts to market conditions rather than using fixed 70/30 levels
Statistical Significance : Signals are based on mathematical rarity, not arbitrary levels
Leading Indicator : RSI² often turns before price, providing earlier signals
Reduced Whipsaws : T3 smoothing eliminates noise while maintaining responsiveness
Unique Signal Generation:
Quantum Orbs : Multi-layered visual signals for statistically extreme events
Divergence Detection : Automated identification of price/momentum divergences
Regime Backgrounds : Visual market state classification (Bullish/Bearish/Neutral)
Particle Effects : Dynamic visualization of momentum energy
Visual Design & Interpretation Guide
Color Coding System:
Yellow (#e1ff00) : Neutral/balanced momentum state
Red (#ff0000) : Overbought/extreme bullish acceleration
Green (#2fff00) : Oversold/extreme bearish acceleration
Orange : Z-score visualization
Blue : HTF Z-score comparison
Main Visual Elements:
RSI² Line with Glow Effect
Multi-layer glow creates depth and emphasis
Color dynamically shifts based on momentum state
Line thickness indicates signal strength
Quantum Signal Orbs
Green Orbs Below : Statistically rare oversold conditions
Red Orbs Above : Statistically rare overbought conditions
Multiple layers indicate signal strength
Only appear at Z-score extremes for high-conviction signals
Divergence Markers
Green Circles : Bullish divergence detected
Red Circles : Bearish divergence detected
Plotted at pivot points for precision
Background Regimes
Green Background : Bullish momentum regime
Grey Background : Bearish momentum regime
Blue Background : Neutral/transitioning regime
Particle Effects
Density indicates momentum energy
Color matches current RSI² state
Provides dynamic market "feel"
Dashboard Metrics - Deep Dive
RSI² ANALYSIS Section:
RSI² Value (0-100)
Current smoothed RSI of RSI reading
>70 : Strong bullish acceleration
<30 : Strong bearish acceleration
~50 : Neutral momentum state
RSI¹ Value
Traditional RSI for reference
Compare with RSI² for acceleration/deceleration insights
Z-Score Status
🔥 EXTREME HIGH : Z > threshold, statistically rare bullish
❄️ EXTREME LOW : Z < threshold, statistically rare bearish
📈 HIGH/📉 LOW : Elevated but not extreme
➡️ NEUTRAL : Normal statistical range
MOMENTUM Section:
Velocity Indicator
▲▲▲ : Strong positive acceleration
▼▼▼ : Strong negative acceleration
Shows rate of change in RSI²
Strength Bar
██████░░░░ : Visual power gauge
Filled bars indicate momentum strength
Based on deviation from center line
SIGNALS Section:
Divergence Status
🟢 BULLISH DIV : Price making lows, RSI² making highs
🔴 BEARISH DIV : Price making highs, RSI² making lows
⚪ NO DIVERGENCE : No divergence detected
HTF Comparison
🔥 HTF EXTREME : Higher timeframe confirms extremity
📊 HTF NORMAL : Higher timeframe is neutral
Critical for multi-timeframe confirmation
Trading Application & Strategy
Signal Hierarchy (Highest to Lowest Priority):
Quantum Orb + HTF Alignment + Divergence
Highest conviction reversal signal
Z-score extreme + timeframe confluence + divergence
Quantum Orb + HTF Alignment
Strong reversal signal
Wait for price confirmation
Divergence + Regime Change
Medium-term reversal signal
Monitor for orb confirmation
Threshold Crosses
Traditional overbought/oversold
Use as alert, not entry
Entry Strategies:
For Reversals:
Wait for Quantum Orb signal
Confirm with HTF Z-score direction
Enter on price structure break
Stop beyond recent extreme
For Continuations:
Trade with regime background color
Use RSI² pullbacks to center line
Avoid signals against HTF trend
For Scalping:
Focus on Z-score extremes
Quick entries on orb signals
Exit at center line cross
Risk Management:
Reduce position size when signals conflict with HTF
Avoid trades during regime transitions (blue background)
Tighten stops after divergence completion
Scale out at statistical mean reversion
Development & Uniqueness
RoRD represents months of research into momentum dynamics and statistical analysis. Unlike indicators that simply combine existing tools, RoRD introduces several genuine innovations :
True RSI² Implementation : Not a smoothed RSI, but actual RSI calculated on RSI values
Dual Z-Score Normalization : Unique approach to finding statistical extremes
T3 Integration : First RSI² implementation with T3 smoothing for optimal lag reduction
Quantum Orb Visualization : Revolutionary signal display method
Dynamic Regime Detection : Automatic market state classification
Statistical Adaptability : Thresholds adapt to market volatility
This indicator was built from first principles, with each component carefully selected for its mathematical properties and practical trading utility. The result is a professional-grade tool that provides insights unavailable through traditional momentum analysis.
Best Practices & Tips
Start with default settings - they're optimized for most markets
Always check HTF alignment before taking signals
Use divergences as early warning , orbs as confirmation
Respect regime backgrounds - trade with them, not against
Combine with price action - RoRD shows when, price shows where
Adjust Z-score thresholds based on market volatility
Monitor dashboard metrics for complete market context
Conclusion
RoRD isn't just another indicator—it's a complete momentum analysis system that reveals market dynamics invisible to traditional tools. By combining momentum acceleration, statistical analysis, and multi-timeframe confluence with intuitive visualization, RoRD provides traders with a sophisticated edge in any market condition.
Whether you're scalping rapid reversals or positioning for major trend changes, RoRD's unique approach to momentum analysis will transform how you see and trade market dynamics.
See momentum's future. Trade with statistical edge.
Trade with insight. Trade with anticipation.
— Dskyz, for DAFE Trading Systems
