Seasonal Strategies V1Seasonal Strategies V1 is a rule-based futures seasonality framework built around predefined calendar windows per asset.
The strategy automatically detects the current symbol and activates long or short trading phases strictly based on historically observed seasonal tendencies. All entries and exits are fully time-based — no indicators, no predictions, no discretionary input.
Key Features
Asset-specific seasonal windows (MMDD-based)
Automatic long and short activation
Fully time-based entries and exits
One position at a time (no pyramiding)
Clean chart visualization using subtle background shading
No indicators, no filters, no curve fitting
Philosophy:
This strategy is designed as a structural trading tool, not a forecasting model.
It focuses on when a market historically shows seasonal tendencies — not why or how far price might move.
Seasonal Strategies V1 intentionally keeps the chart clean and minimal, making it suitable as a baseline framework for research, portfolio-style seasonal approaches, or further extensions in later versions.
Intended Use:
Futures and commodity markets
Seasonality research and testing
Systematic, calendar-driven strategies
Educational and analytical purposes
Disclaimer
This script is provided for educational and research purposes only.
Past seasonal tendencies do not guarantee future performance.
Risk management, position sizing, and portfolio decisions are the responsibility of the user.
In den Scripts nach "curve" suchen
Debye-Einstein Trend Oscillator [Dual Mode] | IkkeOmarDebye-Einstein Trend Oscillator
Indicator Settings Guide
Visual Settings View Mode: Switches the chart display. Select "Standard Flow" to see the raw physics energy bars and crossover lines. Select "Trend Diff (MACD)" to see the histogram that highlights momentum shifts and chaos spikes.
Physics Engine Trend Lookback: Defines the "Mass" of the trend. This sets the long-term baseline (default 1500 bars). Higher values filter out noise and focus only on macro-cycles; lower values make the system faster but noisier. Chaos Threshold (%): Controls the trigger for the Einstein (Chaos) state. Set to 95, only the top 5% of highest-energy volume events will trigger the vertical white spikes. Lowering this value makes the system more sensitive to volatility.
Flow Moving Averages MA Type: Choose between SMA (Simple) or EMA (Exponential) for the smoothing calculation. Fast / Slow Length: These settings determine the sensitivity of the momentum logic. The difference between these two lengths creates the histogram in "Trend Diff" mode.
1. Concept & Theoretical Basis
This script applies principles from Solid State Physics—specifically the Debye and Einstein models of specific heat capacity—to financial market trend analysis.
The core hypothesis is that market trends behave like physical lattices:
Low Energy State (Debye Model): The market moves in a coordinated, wave-like manner (phonons). Trends are sustainable and correlated.
High Energy State (Einstein Model): The market becomes chaotic. Individual participants (atoms) vibrate independently and violently. This represents capitulation or euphoria.
We model "Price" as the position of particles and "Volume × Range" as the thermal energy (Temperature) entering the system.
2. Implementation Models
We constructed the oscillator using three primary physical components:
A. The Trend Vector (Mass)
We assume the "Mass" of the market is its inertia relative to a long-term baseline.
Model: Distance from a 1500-period SMA, normalized by ATR.
Assumption: Price deviation from a deep baseline indicates the magnitude of the trend "force."
B. Thermodynamics (Temperature)
We define "Work" as Volume * True Range.
Temperature (T): The Percentile Rank of this Work over the lookback period (1500 bars).
Assumption: High volume combined with high range equals high thermal energy.
C. The Dual Regimes (Amplifiers)
This is the engine of the script. We apply a scalar multiplier to the Trend Vector based on the current Temperature (T).
Debye Regime (Sustainable): When T is below the critical threshold (95%), we use a polynomial function (T^2). This mimics the Debye T^3 law where energy scales smoothly.
Effect: Smoothly amplifies standard trends.
Einstein Regime (Chaos): When T breaches the critical threshold (95%), we switch to an exponential function derived from the Einstein Solid model.
Effect: Creates massive vertical spikes during trend exhaustions or breakouts.
3. Code Explanation
The Physics Scalars
debye_amp(t) => 1.0 + (math.pow(t, 2) * 5.0)
Defines the sustainable state multiplier. Squaring the temperature t creates a non-linear but smooth response curve that gradually increases with volatility.
einstein_amp(t) => 1.0 + ((1.0 / (math.exp(1.0 / t_safe) - 1.0)) * 15.0)
Deep Dive: This function applies the Bose-Einstein distribution formula (1 / (e^(1/T) - 1)).
The Physics: In quantum mechanics, this formula calculates the occupancy of energy states. At low temperatures, the value is effectively zero (the "frozen" state).
The Function: As our market "Temperature" (T) rises, the denominator shrinks, causing the output to grow exponentially.
The Result: This mathematically forces the system to ignore low-volatility noise but react explosively once the "Boiling Point" is reached, creating the vertical spikes seen on the chart.
is_einstein = (T * 100) >= thresh_einstein
A boolean check that determines if the current market energy (Temperature) has exceeded the user-defined chaos threshold (default 95%).
physics_scalar = is_einstein ? einstein_amp(T) : debye_amp(T)
The regime switch. If the threshold is breached, the system applies the exponential Einstein scalar; otherwise, it applies the polynomial Debye scalar.
Trend Differentiation Logic
final_flow = trend_vector * physics_scalar
Calculates the primary oscillator value by multiplying the directional Trend Vector (Mass) by the active Physics Scalar (Energy).
diff_val = ma_fast - ma_slow
Calculates the momentum of the flow itself by subtracting the Slow Moving Average from the Fast Moving Average. This creates the MACD-style histogram.
4. Visual Reporting & Chart Analysis
Referring to the generated charts (Trend Diff Mode):
The Histogram: Represents the diff_val (Fast MA - Slow MA).
Cyan/Pink: Standard trend momentum (Debye mode).
White Spikes: These represent the Einstein Threshold (Chaos). These spikes generally appear at local bottoms or explosive breakout points, confirming that "Temperature" has exceeded the 95th percentile.
Zero Line: Crossing the zero line implies the trend momentum has shifted (Fast MA crossed Slow MA).
5. Assumptions & Limitations
A. The "Always in Trend" Bias
The "Trend Diff" mode calculates the delta between two moving averages of the flow.
Risk: MAs are laggy by definition. By using a 200/500 MA combo on the oscillator, we are smoothing the data significantly.
Consequence: In a ranging market, the MAs will converge near zero. However, if a sudden burst of Volume enters (Temperature rises) without price moving much, the Einstein scalar will trigger. This may amplify a small move into a large signal, implying a trend where there is only volatility.
B. Lag
The lookback period is 1500 bars. This is a "Macro" trend system. It will not react quickly to short-term reversals unless the Volume/Range shock is massive enough to trigger the Einstein scalar immediately.
Example "physics values"
In the Standard Flow view, the vertical columns represent the raw energy of the trend—Teal and Red bars indicate normal, sustainable market movement (Debye state), while bright Lime and Fuchsia bars signal chaotic, high-volatility events (Einstein state). The height of these bars shows the combined strength of price direction and volume. Overlaying these columns are two moving averages, a fast Blue line and a slow Red line, which smooth out this data to show the underlying momentum. When the Blue line crosses the Red line, it signals a shift in the trend's direction, while the color of the bars warns you if that move is stable or nearing exhaustion.
Mid-Term Refuges (RMP)════════════
ENGLISH VERSION (SPANISH TEXT AT THE END)
════════════
MID-TERM REFUGES (RMP) V1.0
The Mid-Term Refuges (RMP) indicator plots psychological support and resistance levels based on a methodology used by institutional investors since auction floor days. RMP automatically calculates 31 key levels (refuges) from the asset's annual opening price.
METHODOLOGY
• RESISTANCES (R1-R15): Projected at +10% intervals from annual opening, identifying selling pressure zones
• SUPPORTS (S1-S15): Calculated at -10% intervals, marking buyer interest areas
• ANNUAL OPENING PRICE (PA): Central reference level
The 10% intervals represent significant psychological thresholds that capture market indecision, consolidation, or reversal moments. When critical mass of participants uses these same levels, they become self-fulfilling prophecies.
VALIDATION
Test RMP effectiveness on your assets:
1. Use TradingView's Bar Replay
2. Review periods with +/-10% movements
3. Count price reactions at refuge levels
4. Higher frequency = higher institutional usage probability
ECOSYSTEM INTEGRATION
RMP integrates with our other indicators:
• RLP/RLPS (Long-Term Refuges): Structural analysis
• RS (Weekly Refuges): Short-term tactical analysis
FEATURES
• 31 configurable levels with individual switches
• Professional visualization with formatted prices
• Complete customization (colors, widths, styles)
• Native integration with TradingView's price scale
• Bar Replay compatible
PHILOSOPHY
RMP doesn't predict the future—it observes price action at objective levels. No oscillators, no curve-fitting. Pure technical analysis based on auction floor techniques proven over decades.
══════════════
VERSION EN ESPANIOL
══════════════
(La version completa con entrada de datos y textos de ayuda en espaniol (Roman Paladino) estara proximamente disponible en mi repositorio GH: aj-poolom-maasewal)
REFUGIOS DE MEDIANO PLAZO (RMP) V1.0
El indicador Refugios de Mediano Plazo (RMP) traza niveles psicologicos de soporte y resistencia basados en una metodologia utilizada por inversores institucionales desde los tiempos de los pisos de subastas. RMP calcula automaticamente 31 niveles clave (refugios) a partir del precio de apertura anual del activo.
METODOLOGIA
• RESISTENCIAS (R1-R15): Proyectadas a intervalos de +10% desde la apertura anual, identificando zonas de presion vendedora
• SOPORTES (S1-S15): Calculados a intervalos de -10%, marcando areas de interes comprador
• PRECIO DE APERTURA ANUAL (PA): Nivel de referencia central
Los intervalos del 10% representan umbrales psicologicos significativos que capturan momentos de indecision, consolidacion o reversion del mercado. Cuando una masa critica de participantes utiliza estos mismos niveles, se convierten en profecias autocumplidas.
VALIDACION
Pruebe la efectividad de RMP en sus activos:
1. Use el Reproductor de Barras de TradingView
2. Revise periodos con movimientos de +/-10%
3. Cuente las reacciones del precio en los niveles refugio
4. Mayor frecuencia = mayor probabilidad de uso institucional
INTEGRACION CON NUESTRO ECOSISTEMA DE INDICADORES DE REFUGIOS CON ACCION DEL PRECIO
(Disponibles para descarga proximamente)
Este indicador RMP se complementa fuertemente con el uso de los siguientes indicadores nuestros:
• RLP (Refugios de Largo Plazo): Busqueda y definicion automatizada de fases preponderantes.
• RLPS (Refugios de Largo Plazo Simplificado): Analisis en base a fase preponderante ya conocida.
• RS (Refugios Semanales): Analisis tactico de fases de corto plazo.
CARACTERISTICAS
• 31 niveles configurables con switches individuales
• Visualizacion profesional con precios formateados
• Personalizacion completa (colores, grosores, estilos)
• Integracion nativa con la escala de precios de TradingView
• Compatible con Reproductor de Barras
FILOSOFIA
RMP no predice el futuro. Observa la accion del precio en niveles objetivos. Sin osciladores, sin sobreajustes. Analisis tecnico puro basado en tecnicas de piso de subastas probadas durante decadas.
════════════════════════════════════════════════════════════
Desarrollado por: aj p'oolom masewal
Codificado con la colaboracion de: Claude Sonnet 4.5 de Anthropic
════════════════════════════════════════════════════════════
Archetype Zones, Defense Confirmation OverlayArchetype Zones + Defense Confirmation Overlay (MST) v1.0
This indicator is a time-structure execution overlay built for fast intraday futures trading. It highlights a curated set of high-ROI market timing windows (MST / America/Denver) and applies lightweight “not-too-strict” logic to classify each window as a likely:
Driver (initiative / directional push)
Continuation (follow-through of the parent move)
Trap (liquidity sweep + stall / possible flip)
Rotation (VWAP churn + contraction / stand down conditions)
On top of the time zones, it includes a Defense Confirmation Overlay designed for 1–5 second execution, helping identify moments when price shows “defense behavior” aligned with the expected directional bias of the active zone.
What It Does
1) Time-Based Archetype Zones (MST)
The script shades key intraday windows with a configurable soft buffer (+/- minutes) so the user can anticipate action before/after the exact minute.
Each zone can output an expected directional lean using:
Displacement vs. window span
VWAP location
VWAP crossing count (chop filter)
Basic structure checks for continuation
Sweep/stall logic for trap detection
Churn + contraction logic for rotation regimes
2) Expected Direction Engine
When a zone is active, the indicator calculates the “expected direction” for that specific zone using the archetype logic.
This expected direction is used as the baseline for the Defense module, so defense markers are context-aware.
3) Defense Confirmation Overlay (Execution Layer)
Defense is intended to represent institutional-style protection or rejection inside an active zone.
It looks for:
Strong wick dominance (wick as a percentage of total candle span)
Close location in the top/bottom portion of the candle
Optional absorption highlight: volume spike plus compressed candle span (high volume, low range)
When conditions align with the zone’s expected direction, the script can show:
Defense wick markers (below-bar for buy defense, above-bar for sell defense)
Absorption highlight on bars showing absorption behavior
4) Micro Defense Box
When a defense event triggers, the script can draw a small “defense box” at the defended level with tick-padding.
The box extends right until invalidated (price closes through the box boundary).
This provides a clean visual reference for:
Defended price location
Invalidation threshold
Follow-through behavior after defense
5) Entry Permission Label
When Defense + Absorption occur together during an active zone, the script can print an “Entry Permission” label to highlight that multiple confirmations aligned.
Inputs and Customization
Zone buffer (+/- minutes)
Zone shading opacity
Toggle zone labels, defense markers, absorption highlighting, defense box, permission label
Adjustable “not too strict” archetype thresholds (designed for practical use, not curve-fitting)
Adjustable defense wick/close thresholds and absorption parameters
Notes and Disclaimer
This indicator does not predict the market with certainty.
It is designed to provide time-structure context plus execution confirmation, not standalone buy/sell signals.
It is best used alongside trend/bias tools (VWAP, structure, higher-timeframe levels, key session highs/lows).
Always test settings on your market and timeframe before live use.
MA Crossover with R SquaredThis indicator enhances the classic Moving Average (MA) crossover strategy with statistical filtering and prediction capabilities.
Let me explain what it does:
Instead of just showing when a fast MA crosses above/below a slow MA, this indicator adds R² (R-squared) filtering to identify higher-quality crossovers and predicts future crossovers.
What is R²?
R² (Coefficient of Determination) is a statistical measure that shows how well one variable explains the movement of another variable. In simpler terms:
R² = 1.0: Perfect relationship - 100% of the movement in one MA is explained by the other MA
R² = 0.8: Strong relationship - 80%
R² = 0.5: Moderate relationship - 50%
R² = 0.0: No relationship - 0%
Imagine two cars driving on a highway:
High R² (0.9): Both cars are in the same lane, moving together consistently
Low R² (0.3): One car is weaving between lanes while the other stays straight - poor coordination.
Traditional MA crossovers often generate false signals during:
Choppy markets (price bouncing around)
Sideways/ranging markets
Low volatility periods
News events causing temporary spikes
The R² Solution:
R² acts as a "quality filter" that answers: "How meaningful this crossover is?"
What this means:
Before R² filtering: Every crossover generates a signal
After R² filtering: Only crossovers with R² > threshold generate signals
Result: Fewer but higher-quality signals.
MARKET REGIME DETECTION
High R² (> 0.7): Strong trending market - MA crossovers are reliable
Medium R² (0.4-0.7): Moderate trending - use with caution
Low R² (< 0.4): Choppy/range-bound market - avoid MA crossover signals
Increasing R²: MAs are converging/moving together more closely
Decreasing R²: MAs are diverging/losing coordination
Sudden R² drop: Potential market regime change.
Why Square the Correlation?
Correlation: Measures direction AND strength (-1 to +1)
R²: Measures strength ONLY (0 to 1)
In trading: We care about relationship strength, not direction
Direction is already indicated by crossover type (bullish/bearish)
Real-World Interpretation:
If R² = 0.64, it means:
64% of the variation in the fast MA is explained by the slow MA
36% is "noise" or unexplained movement
The MAs are moderately coordinated.
R² Trend Confirmation:
Entry: When crossover occurs AND R² is above threshold
Confirmation: R² continues rising after entry
Exit: R² drops below threshold (relationship weakening)
Multi-Timeframe R² Analysis
Check R² on higher timeframe for trend context
Use current timeframe for entry signals
Example: Daily R² > 0.7 gives bullish bias, use 1-hour for entries.
R² LIMITATIONS & CAUTIONS
1. Lagging Nature
R² is calculated from past data
By the time R² is high, the trend may already be established
2. Not a Standalone Indicator
R² should confirm other signals, not generate them alone
Always combine with price action, volume, support/resistance
3. Curve Fitting Risk
Don't over-optimize R² thresholds on historical data
What worked in the past may not work in the future
Use R² as a filter, not a predictor
4. Market-Specific Behavior
R² thresholds that work in trending stocks may fail in Forex
Cryptocurrencies may require different R² settings than commodities
Always test on your specific market/instrument
Before Taking Any Signal:
✅ Does the crossover have a colored circle? (R² > threshold)
✅ What's the R² number shown? (Higher = better)
✅ Is R² rising or falling? (Rising = strengthening relationship)
✅ Check history table - what happened with similar R² values?
✅ Consider prediction - does it align with current signal?
Simple R² Rules of Thumb:
R² > 0.8: Excellent signal quality
R² 0.6-0.8: Good signal quality
R² 0.4-0.6: Moderate - use additional confirmation
R² < 0.4: Poor - avoid or use extreme caution
Think of R² as:
A quality control inspector for MA crossovers
A relationship therapist for your moving averages
A statistical bouncer that only lets strong signals through
Higher win rate + Better risk/reward = More profitable trading
This script transforms the basic "when lines cross" approach into a sophisticated, statistically-validated trading system. R² is the secret sauce that separates random crossovers (Golden/Death) from meaningful trend changes.
DISCLAIMER: This information is provided for educational purposes only and should not be considered financial, investment, or trading advice. Please do boost if you like it. Happy Trading.
Ultimate MACD [captainua]Ultimate MACD - Comprehensive MACD Trading System
Overview
This indicator combines traditional MACD calculations with advanced features including divergence detection, volume analysis, histogram analysis tools, regression forecasting, strong top/bottom detection, and multi-timeframe confirmation to provide a comprehensive MACD-based trading system. The script calculates MACD using configurable moving average types (EMA, SMA, RMA, WMA) and applies various smoothing methods to reduce noise while maintaining responsiveness. The combination of these features creates a multi-layered confirmation system that reduces false signals by requiring alignment across multiple indicators and timeframes.
Core Calculations
MACD Calculation:
The script calculates MACD using the standard formula: MACD Line = Fast MA - Slow MA, Signal Line = Moving Average of MACD Line, Histogram = MACD Line - Signal Line. The default parameters are Fast=12, Slow=26, Signal=9, matching the traditional MACD settings. The script supports four moving average types:
- EMA (Exponential Moving Average): Standard and most responsive, default choice
- SMA (Simple Moving Average): Equal weight to all periods
- RMA (Wilder's Moving Average): Smoother, less responsive
- WMA (Weighted Moving Average): Recent prices weighted more heavily
The price source can be configured as Close (standard), Open, High, Low, HL2, HLC3, or OHLC4. Alternative sources provide different sensitivity characteristics for various trading strategies.
Configuration Presets:
The script includes trading style presets that automatically configure MACD parameters:
- Scalping: Fast/Responsive settings (8,18,6 with minimal smoothing)
- Day Trading: Balanced settings (10,22,7 with minimal smoothing)
- Swing Trading: Standard settings (12,26,9 with moderate smoothing)
- Position Trading: Smooth/Conservative settings (15,35,12 with higher smoothing)
- Custom: Full manual control over all parameters
Histogram Smoothing:
The histogram can be smoothed using EMA to reduce noise and filter minor fluctuations. Smoothing length of 1 = raw histogram (no smoothing), higher values (3-5) = smoother histogram. Increased smoothing reduces noise but may delay signals slightly.
Percentage Mode:
MACD values can be converted to percentage of price (MACD/Close*100) for cross-instrument comparison. This is useful when comparing MACD signals across instruments with different price levels (e.g., BTC vs ETH). The percentage mode normalizes MACD values, making them comparable regardless of instrument price.
MACD Scale Factor:
A scale factor multiplier (default 1.0) allows adjusting MACD display size for better visibility. Use 0.3-0.5 if MACD appears too compressed, or 2.0-3.0 if too small.
Dynamic Overbought/Oversold Levels:
Overbought and oversold levels are calculated dynamically based on MACD's mean and standard deviation over a lookback period. The formula: OB = MACD Mean + (StdDev × OB Multiplier), OS = MACD Mean - (StdDev × OS Multiplier). This adapts to current market conditions, widening in volatile markets and narrowing in calm markets. The lookback period (default 20) controls how quickly the levels adapt: longer periods (30-50) = more stable levels, shorter (10-15) = more responsive.
OB/OS Background Coloring:
Optional background coloring can highlight the entire panel when MACD enters overbought or oversold territory, providing prominent visual indication of extreme conditions. The background colors are drawn on top of the main background to ensure visibility.
Divergence Detection
Regular Divergence:
The script uses the MACD line (not histogram) for divergence detection, which provides more reliable signals. Bullish divergence: Price makes a lower low while MACD line makes a higher low. Bearish divergence: Price makes a higher high while MACD line makes a lower high. Divergences often precede reversals and are powerful reversal signals.
Pivot-Based Divergence:
The divergence detection uses actual pivot points (pivotlow/pivothigh) instead of simple lowest/highest comparisons. This provides more accurate divergence detection by identifying significant pivot lows/highs in both price and MACD line. The pivot-based method compares two recent pivot points: for bullish divergence, price makes a lower low while MACD makes a higher low at the pivot points. This method reduces false divergences by requiring actual pivot points rather than just any low/high within a period.
The pivot lookback parameters (left and right) control how many bars on each side of a pivot are required for confirmation. Higher values = more conservative pivot detection.
Hidden Divergence:
Continuation patterns that signal trend continuation rather than reversal. Bullish hidden divergence: Price makes a higher low but MACD makes a lower low. Bearish hidden divergence: Price makes a lower high but MACD makes a higher high. These patterns indicate the trend is likely to continue in the current direction.
Zero-Line Filter:
The "Don't Touch Zero Line" option ensures divergences occur in proper context: for bullish divergence, MACD must stay below zero; for bearish divergence, MACD must stay above zero. This filters out divergences that occur in neutral zones.
Range Filtering:
Minimum and maximum lookback ranges control the time window between pivots to consider for divergence. This helps filter out divergences that are too close together (noise) or too far apart (less relevant).
Volume Confirmation System
Volume threshold filtering requires current volume to exceed the volume SMA multiplied by the threshold factor. The formula: Volume Confirmed = Volume > (Volume SMA × Threshold). If the threshold is set to 1.0 or lower, volume confirmation is effectively disabled (always returns true). This allows you to use the indicator without volume filtering if desired. Volume confirmation significantly increases divergence and signal reliability.
Volume Climax and Dry-Up Detection:
The script can mark bars with extremely high volume (volume climax) or extremely low volume (volume dry-up). Volume climax indicates potential reversal points or strong momentum continuation. Volume dry-up indicates low participation and may produce unreliable signals. These markers use standard deviation multipliers to identify extreme volume conditions.
Zero-Line Cross Detection
MACD zero-line crosses indicate momentum shifts: above zero = bullish momentum, below zero = bearish momentum. The script includes alert conditions for zero-line crosses with cooldown protection to prevent alert spam. Zero-line crosses can provide early warning signals before MACD crosses the signal line.
Histogram Analysis Tools
Histogram Moving Average:
A moving average applied to the histogram itself helps identify histogram trend direction and acts as a signal line for histogram movements. Supports EMA, SMA, RMA, and WMA types. Useful for identifying when histogram momentum is strengthening or weakening.
Histogram Bollinger Bands:
Bollinger Bands are applied to the MACD histogram instead of price. The calculation: Basis = SMA(Histogram, Period), StdDev = stdev(Histogram, Period), Upper = Basis + (StdDev × Deviation Multiplier), Lower = Basis - (StdDev × Deviation Multiplier). This creates dynamic zones around the histogram that adapt to histogram volatility. When the histogram touches or exceeds the bands, it indicates extreme conditions relative to recent histogram behavior.
Stochastic MACD (StochMACD):
Stochastic MACD applies the Stochastic oscillator formula to the MACD histogram instead of price. This normalizes the histogram to a 0-100 scale, making it easier to identify overbought/oversold conditions on the histogram itself. The calculation: %K = ((Histogram - Lowest Histogram) / (Highest Histogram - Lowest Histogram)) × 100. %K is smoothed, and %D is calculated as the moving average of smoothed %K. Standard thresholds are 80 (overbought) and 20 (oversold).
Regression Forecasting
The script includes advanced regression forecasting that predicts future MACD values using mathematical models. This helps anticipate potential MACD movements and provides forward-looking context for trading decisions.
Regression Types:
- Linear: Simple trend line (y = mx + b) - fastest, works well for steady trends
- Polynomial: Quadratic curve (y = ax² + bx + c) - captures curvature in MACD movement
- Exponential Smoothing: Weighted average with more weight on recent values - responsive to recent changes
- Moving Average: Uses difference between short and long MA to estimate trend - stable and smooth
Forecast Horizon:
Number of bars to forecast ahead (default 5, max 50 for linear/MA, max 20 for polynomial due to performance). Longer horizons predict further ahead but may be less accurate.
Confidence Bands:
Optional upper/lower bands around forecast show prediction uncertainty based on forecast error (standard deviation of prediction vs actual). Wider bands = higher uncertainty. The confidence level multiplier (default 1.5) controls band width.
Forecast Display:
Forecast appears as dotted lines extending forward from current bar, with optional confidence bands. All forecast values respect percentage mode and scale factor settings.
Strong Top/Bottom Signals
The script detects strong recovery from extreme MACD levels, generating "sBottom" and "sTop" signals. These identify significant reversal potential when MACD recovers substantially from overbought/oversold extremes.
Strong Bottom (sBottom):
Triggered when:
1. MACD was at or near its lowest point in the bottom period (default 10 bars)
2. MACD was in or near the oversold zone
3. MACD has recovered by at least the threshold amount (default 0.5) from the lowest point
4. Recovery persists for confirmation bars (default 2 consecutive bars)
5. MACD has moved out of the oversold zone
6. Volume is above average
7. All enabled filters pass
8. Minimum bars have passed since last signal (reset period, default 5 bars)
Strong Top (sTop):
Triggered when:
1. MACD was at or near its highest point in the top period (default 7 bars)
2. MACD was in or near the overbought zone
3. MACD has declined by at least the threshold amount (default 0.5) from the highest point
4. Decline persists for confirmation bars (default 2 consecutive bars)
5. MACD has moved out of the overbought zone
6. Volume is above average
7. All enabled filters pass
8. Minimum bars have passed since last signal (reset period, default 5 bars)
Label Placement:
sTop/sBottom labels appear on the historical bar where the actual extreme occurred (not on current bar), showing the exact MACD value at that extreme. Labels respect the unified distance checking system to prevent overlaps with Buy/Sell Strength labels.
Signal Strength Calculation
The script calculates a composite signal strength score (0-100) based on multiple factors:
- MACD distance from signal line (0-50 points): Larger separation indicates stronger signal
- Volume confirmation (0-15 points): Volume above average adds points
- Secondary timeframe alignment (0-15 points): Higher timeframe agreement adds points
- Distance from zero line (0-20 points): Closer to zero can indicate stronger reversal potential
Higher scores (70+) indicate stronger, more reliable signals. The signal strength is displayed in the statistics table and can be used as a filter to only accept signals above a threshold.
Smart Label Placement System
The script includes an advanced label placement system that tracks MACD extremes and places Buy/Sell Strength labels at optimal locations:
Label Placement Algorithm:
- Labels appear on the current bar at confirmation (not on historical extreme bars), ensuring they're visible when the signal is confirmed
- The system tracks pending signals when MACD enters OB/OS zones or crosses the signal line
- During tracking, the system continuously searches for the true extreme (lowest MACD for buys, highest MACD for sells) within a configurable historical lookback period
- Labels are only finalized when: (1) MACD exits the OB/OS zone, (2) sufficient bars have passed (2x minimum distance), (3) MACD has recovered/declined by a configurable percentage from the extreme (default 15%), and (4) tracking has stopped (no better extreme found)
Label Spacing and Overlap Prevention:
- Minimum Bars Between Labels: Base distance requirement (default 5 bars)
- Label Spacing Multiplier: Scales the base distance (default 1.5x) for better distribution. Higher values = more spacing between labels
- Effective distance = Base Distance × Spacing Multiplier (e.g., 5 × 1.5 = 7.5 bars minimum)
- Unified distance checking prevents overlaps between all label types (Buy Strength, Sell Strength, sTop, sBottom)
Strength-Based Filtering:
- Label Strength Minimum (%): Only labels with strength at or above this threshold are displayed (default 75%)
- When multiple potential labels are close together, the system automatically compares strengths and keeps only the strongest one
- This ensures only the most significant signals are displayed, reducing chart clutter
Zero Line Polarity Enforcement:
- Enforce Zero Line Polarity (default enabled): Ensures labels follow traditional MACD interpretation
- Buy Strength labels only appear when the tracked extreme MACD value was below zero (negative territory)
- Sell Strength labels only appear when the tracked extreme MACD value was above zero (positive territory)
- This prevents counter-intuitive labels (e.g., Buy labels above zero line) and aligns with standard MACD trading principles
Recovery/Decline Confirmation:
- Recovery/Decline Confirm (%): Percent move away from the extreme required before finalizing (default 15%)
- For Buy labels: MACD must recover by at least this percentage from the tracked bottom
- For Sell labels: MACD must decline by at least this percentage from the tracked top
- Higher values = more confirmation required, fewer but more reliable labels
Historical Lookback:
- Historical Lookback for Label Placement: Number of bars to search for true extremes (default 20)
- The system searches within this period to find the actual lowest/highest MACD value
- Higher values analyze more history but may be slower; lower values are faster but may miss some extremes
Cross Quality Score
The script calculates a MACD cross quality score (0-100) that rates crossover quality based on:
- Cross angle (0-50 points): Steeper crosses = stronger signals
- Volume confirmation (0-25 points): Volume above average adds points
- Distance from zero line (0-25 points): Crosses near zero line are stronger
This score helps identify high-quality crossovers and can be used as a filter to only accept signals meeting minimum quality threshold.
Filtering System
Histogram Filter:
Requires histogram to be above zero for buy signals, below zero for sell signals. Ensures momentum alignment before generating signals.
Signal Strength Filter:
Requires minimum signal strength score for signals. Higher threshold = only strongest signals pass. This combines multiple confirmation factors into a single filter.
Cross Quality Filter:
Requires minimum cross quality score for signals. Rates crossover quality based on angle, volume, momentum, and distance from zero. Only signals meeting minimum quality threshold will be generated.
All filters use the pattern: filterResult = not filterEnabled OR conditionMet. This means if a filter is disabled, it always passes (returns true). Filters can be combined, and all must pass for a signal to fire.
Multi-Timeframe Analysis
The script can display MACD from a secondary (higher) timeframe and use it for confirmation. When secondary timeframe confirmation is enabled, signals require the higher timeframe MACD to align (bullish/bearish) with the signal direction. This ensures signals align with the larger trend context, reducing counter-trend trades.
Secondary Timeframe MACD:
The secondary timeframe MACD uses the same calculation parameters (fast, slow, signal, MA type) as the main MACD but from a higher timeframe. This provides context for the current timeframe's MACD position relative to the larger trend. The secondary MACD lines are displayed on the chart when enabled.
Noise Filtering
Noise filtering hides small histogram movements below a threshold. This helps focus on significant moves and reduces chart clutter. When enabled, only histogram movements above the threshold are displayed. Typical threshold values are 0.1-0.5 for most instruments, depending on the instrument's price range and volatility.
Signal Debounce
Signal debounce prevents duplicate MACD cross signals within a short time period. Useful when MACD crosses back and forth quickly, creating multiple signals. Debounce ensures only one signal per period, reducing signal spam during choppy markets. This is separate from alert cooldown, which applies to all alert types.
Background Color Modes
The script offers three background color modes:
- Dynamic: Full MACD heatmap based on OB/OS conditions, confidence, and momentum. Provides rich visual feedback.
- Monotone: Soft neutral background but still allows overlays (OB/OS zones). Keeps the chart clean without overpowering candles.
- Off: No MACD background (only overlays and plots). Maximum chart cleanliness.
When OB/OS background colors are enabled, they are drawn on top of the main background to ensure visibility.
Statistics Table
A real-time statistics table displays current MACD values, signal strength, distance from zero line, secondary timeframe alignment, volume confirmation status, and all active filter statuses. The table dynamically adjusts to show only enabled features, keeping it clean and relevant. The table position can be configured (Top Left, Top Right, Bottom Left, Bottom Right).
Performance Statistics Table
An optional performance statistics table shows comprehensive filter diagnostics:
- Total buy/sell signals (raw crossover count before filters)
- Filtered buy/sell signals (signals that passed all filters)
- Overall pass rates (percentage of signals that passed filters)
- Rejected signals count
- Filter-by-filter rejection diagnostics showing which filters rejected how many signals
This table helps optimize filter settings by showing which filters are most restrictive and how they impact signal frequency. The diagnostics format shows rejections as "X B / Y S" (X buy signals rejected, Y sell signals rejected) or "Disabled" if the filter is not active.
Alert System
The script includes separate alert conditions for each signal type:
- MACD Cross: MACD line crosses above/below Signal line (with or without secondary confirmation)
- Zero-Line Cross: MACD crosses above/below zero
- Divergence: Regular and hidden divergence detections
- Secondary Timeframe: Higher timeframe MACD crosses
- Histogram MA Cross: Histogram crosses above/below its moving average
- Histogram Zero Cross: Histogram crosses above/below zero
- StochMACD: StochMACD overbought/oversold entries and %K/%D crosses
- Histogram BB: Histogram touches/breaks Bollinger Bands
- Volume Events: Volume climax and dry-up detections
- OB/OS: MACD entry/exit from overbought/oversold zones
- Strong Top/Bottom: sTop and sBottom signal detections
Each alert type has its own cooldown system to prevent alert spam. The cooldown requires a minimum number of bars between alerts of the same type, reducing duplicate alerts during volatile periods. Alert types can be filtered to only evaluate specific alert types (All, MACD Cross, Zero Line, Divergence, Secondary Timeframe, Histogram MA, Histogram Zero, StochMACD, Histogram BB, Volume Events, OB/OS, Strong Top/Bottom).
How Components Work Together
MACD crossovers provide the primary signal when the MACD line crosses the Signal line. Zero-line crosses indicate momentum shifts and can provide early warning signals. Divergences identify potential reversals before they occur.
Volume confirmation ensures signals occur with sufficient market participation, filtering out low-volume false breakouts. Histogram analysis tools (MA, Bollinger Bands, StochMACD) provide additional context for signal reliability and identify significant histogram zones.
Signal strength combines multiple confirmation factors into a single score, making it easy to filter for only the strongest signals. Cross quality score rates crossover quality to identify high-quality setups. Multi-timeframe confirmation ensures signals align with higher timeframe trends, reducing counter-trend trades.
Usage Instructions
Getting Started:
The default configuration shows MACD(12,26,9) with standard EMA calculations. Start with default settings and observe behavior, then customize settings to match your trading style. You can use configuration presets for quick setup based on your trading style.
Customizing MACD Parameters:
Adjust Fast Length (default 12), Slow Length (default 26), and Signal Length (default 9) based on your trading timeframe. Shorter periods (8,17,7) for faster signals, longer (15,30,12) for smoother signals. You can change the moving average type: EMA for responsiveness, RMA for smoothness, WMA for recent price emphasis.
Price Source Selection:
Choose Close (standard), or alternative sources (HL2, HLC3, OHLC4) for different sensitivity. HL2 uses the midpoint of the high-low range, HLC3 and OHLC4 incorporate more price information.
Histogram Smoothing:
Set smoothing to 1 for raw histogram (no smoothing), or increase (3-5) for smoother histogram that reduces noise. Higher smoothing reduces false signals but may delay signals slightly.
Percentage Mode:
Enable percentage mode when comparing MACD across instruments with different price levels. This normalizes MACD values, making them directly comparable.
Dynamic OB/OS Levels:
The dynamic thresholds automatically adapt to volatility. Adjust the multipliers (default 1.5) to fine-tune sensitivity: higher values (2.0-3.0) = more extreme thresholds (fewer signals), lower (1.0-1.5) = more frequent signals. Adjust the lookback period to control how quickly levels adapt. Enable OB/OS background colors for visual indication of extreme conditions.
Volume Confirmation:
Set volume threshold to 1.0 (default, effectively disabled) or higher (1.2-1.5) for standard confirmation. Higher values require more volume for confirmation. Set to 0.1 to completely disable volume filtering.
Filters:
Enable filters gradually to find your preferred balance. Start with histogram filter for basic momentum alignment, then add signal strength filter (threshold 50+) for moderate signals, then cross quality filter (threshold 50+) for high-quality crossovers. Combine filters for highest-quality signals but expect fewer signals.
Divergence:
Enable divergence detection and adjust pivot lookback parameters. Pivot-based divergence provides more accurate detection using actual pivot points. Hidden divergence is useful for trend-following strategies. Adjust range parameters to filter divergences by time window.
Zero-Line Crosses:
Zero-line cross alerts are automatically available when alerts are enabled. These provide early warning signals for momentum shifts.
Histogram Analysis Tools:
Enable Histogram Moving Average to see histogram trend direction. Enable Histogram Bollinger Bands to identify extreme histogram zones. Enable Stochastic MACD to normalize histogram to 0-100 scale for overbought/oversold identification.
Multi-Timeframe:
Enable secondary timeframe MACD to see higher timeframe context. Enable secondary confirmation to require higher timeframe alignment for signals.
Signal Strength:
Signal strength is automatically calculated and displayed in the statistics table. Use signal strength filter to only accept signals above a threshold (e.g., 50 for moderate, 70+ for strong signals only).
Smart Label Placement:
Configure label placement settings to control label appearance and quality:
- Label Strength Minimum (%): Set threshold (default 75%) to show only strong signals. Higher = fewer, stronger labels
- Label Spacing Multiplier: Adjust spacing (default 1.5x) for better distribution. Higher = more spacing between labels
- Recovery/Decline Confirm (%): Set confirmation requirement (default 15%). Higher = more confirmation, fewer labels
- Enforce Zero Line Polarity: Enable (default) to ensure Buy labels only appear when tracked extreme was below zero, Sell labels only when above zero
- Historical Lookback: Adjust search period (default 20 bars) for finding true extremes. Higher = more history analyzed
Cross Quality:
Cross quality score is automatically calculated for crossovers. Use cross quality filter to only accept high-quality crossovers (threshold 50+ for moderate, 70+ for high quality).
Alerts:
Set up alerts for your preferred signal types. Enable alert cooldown (default enabled, 5 bars) to prevent alert spam. Use alert type filter to only evaluate specific alert types (All, MACD Cross, Zero Line, Divergence, Secondary Timeframe, Histogram MA, Histogram Zero, StochMACD, Histogram BB, Volume Events, OB/OS, Strong Top/Bottom). Each signal type has its own alert condition, so you can be selective about which signals trigger alerts.
Visual Elements and Signal Markers
The script uses various visual markers to indicate signals and conditions:
- MACD Line: Green when above signal (bullish), red when below (bearish) if dynamic colors enabled. Optional black outline for enhanced visibility
- Signal Line: Orange line with optional black outline for enhanced visibility
- Histogram: Color-coded based on direction and momentum (green for bullish rising, lime for bullish falling, red for bearish falling, orange for bearish rising)
- Zero Line: Horizontal reference line at MACD = 0
- Fill to Zero: Green/red semi-transparent fill between MACD line and zero line showing bullish/bearish territory
- Fill Between OB/OS: Blue semi-transparent fill between overbought/oversold thresholds highlighting neutral zone
- OB/OS Background Colors: Background coloring when MACD enters overbought/oversold zones
- Background Colors: Dynamic or monotone backgrounds indicating MACD state, or custom chart background
- Divergence Labels: "🐂" for bullish, "🐻" for bearish, "H Bull" for hidden bullish, "H Bear" for hidden bearish
- Divergence Lines: Colored lines connecting pivot points when divergences are detected
- Volume Climax Markers: ⚡ symbol for extremely high volume
- Volume Dry-Up Markers: 💧 symbol for extremely low volume
- Buy/Sell Strength Labels: Show signal strength percentage (e.g., "Buy Strength: 75%")
- Strong Top/Bottom Labels: "sTop" and "sBottom" for extreme level recoveries
- Secondary MACD Lines: Purple lines showing higher timeframe MACD
- Histogram MA: Orange line showing histogram moving average
- Histogram BB: Blue bands around histogram showing extreme zones
- StochMACD Lines: %K and %D lines with overbought/oversold thresholds
- Regression Forecast: Dotted blue lines extending forward with optional confidence bands
Signal Priority and Interpretation
Signals are generated independently and can occur simultaneously. Higher-priority signals generally indicate stronger setups:
1. MACD Cross with Multiple Filters - Highest priority: Requires MACD crossover plus all enabled filters (histogram, signal strength, cross quality) and secondary timeframe confirmation if enabled. These are the most reliable signals.
2. Zero-Line Cross - High priority: Indicates momentum shift. Can provide early warning signals before MACD crosses the signal line.
3. Divergence Signals - Medium-High priority: Pivot-based divergence is more reliable than simple divergence. Hidden divergence indicates continuation rather than reversal.
4. MACD Cross with Basic Filters - Medium priority: MACD crosses signal line with basic histogram filter. Less reliable alone but useful when combined with other confirmations.
Best practice: Wait for multiple confirmations. For example, a MACD crossover combined with divergence, volume confirmation, and secondary timeframe alignment provides the strongest setup.
Chart Requirements
For proper script functionality and compliance with TradingView requirements, ensure your chart displays:
- Symbol name: The trading pair or instrument name should be visible
- Timeframe: The chart timeframe should be clearly displayed
- Script name: "Ultimate MACD " should be visible in the indicator title
These elements help traders understand what they're viewing and ensure proper script identification. The script automatically includes this information in the indicator title and chart labels.
Performance Considerations
The script is optimized for performance:
- Calculations use efficient Pine Script functions (ta.ema, ta.sma, etc.) which are optimized by TradingView
- Conditional execution: Features only calculate when enabled
- Label management: Old labels are automatically deleted to prevent accumulation
- Array management: Divergence label arrays are limited to prevent memory accumulation
The script should perform well on all timeframes. On very long historical data with many enabled features, performance may be slightly slower, but it remains usable.
Known Limitations and Considerations
- Dynamic OB/OS levels can vary significantly based on recent MACD volatility. In very volatile markets, levels may be wider; in calm markets, they may be narrower.
- Volume confirmation requires sufficient historical volume data. On new instruments or very short timeframes, volume calculations may be less reliable.
- Higher timeframe MACD uses request.security() which may have slight delays on some data feeds.
- Stochastic MACD requires the histogram to have sufficient history. Very short periods on new charts may produce less reliable StochMACD values initially.
- Divergence detection requires sufficient historical data to identify pivot points. Very short lookback periods may produce false positives.
Practical Use Cases
The indicator can be configured for different trading styles and timeframes:
Swing Trading:
Use MACD(12,26,9) with secondary timeframe confirmation. Enable divergence detection. Use signal strength filter (threshold 50+) and cross quality filter (threshold 50+) for higher-quality signals. Enable histogram analysis tools for additional context.
Day Trading:
Use MACD(8,17,7) or use "Day Trading" preset with minimal histogram smoothing for faster signals. Enable zero-line cross alerts for early signals. Use volume confirmation with threshold 1.2-1.5. Enable histogram MA for momentum tracking.
Trend Following:
Use MACD(12,26,9) or longer periods (15,30,12) for smoother signals. Enable secondary timeframe confirmation for trend alignment. Hidden divergence signals are useful for trend continuation entries. Use cross quality filter to identify high-quality crossovers.
Reversal Trading:
Focus on divergence detection (pivot-based for accuracy) combined with zero-line crosses. Enable volume confirmation. Use histogram Bollinger Bands to identify extreme histogram zones. Enable StochMACD for overbought/oversold identification.
Multi-Timeframe Analysis:
Enable secondary timeframe MACD to see context from larger timeframes. For example, use daily MACD on hourly charts to understand the larger trend context. Enable secondary confirmation to require higher timeframe alignment for signals.
Practical Tips and Best Practices
Getting Started:
Start with default settings and observe MACD behavior. The default configuration (MACD 12,26,9 with EMA) is balanced and works well across different markets. After observing behavior, customize settings to match your trading style. Consider using configuration presets for quick setup.
Reducing Repainting:
All signals are based on confirmed bars, minimizing repainting. The script uses confirmed bar data for all calculations to ensure backtesting accuracy.
Signal Quality:
MACD crosses with multiple filters provide the highest-quality signals because they require alignment across multiple indicators. These signals have lower frequency but higher reliability. Use signal strength scores to identify the strongest signals (70+). Use cross quality scores to identify high-quality crossovers (70+).
Filter Combinations:
Start with histogram filter for basic momentum alignment, then add signal strength filter for moderate signals, then cross quality filter for high-quality crossovers. Combining all filters significantly reduces false signals but also reduces signal frequency. Find your balance based on your risk tolerance.
Volume Filtering:
Set volume threshold to 1.0 (default, effectively disabled) or lower to effectively disable volume filtering if you trade instruments with unreliable volume data or want to test without volume confirmation. Standard confirmation uses 1.2-1.5 threshold.
MACD Period Selection:
Standard MACD(12,26,9) provides balanced signals suitable for most trading. Shorter periods (8,17,7) for faster signals, longer (15,30,12) for smoother signals. Adjust based on your timeframe and trading style. Consider using configuration presets for optimized settings.
Moving Average Type:
EMA provides balanced responsiveness with smoothness. RMA is smoother and less responsive. WMA gives more weight to recent prices. SMA gives equal weight to all periods. Choose based on your preference for responsiveness vs. smoothness.
Divergence:
Pivot-based divergence is more reliable than simple divergence because it uses actual pivot points. Hidden divergence indicates continuation rather than reversal, useful for trend-following strategies. Adjust pivot lookback parameters to control sensitivity.
Dynamic Thresholds:
Dynamic OB/OS thresholds automatically adapt to volatility. In volatile markets, thresholds widen; in calm markets, they narrow. Adjust the multipliers to fine-tune sensitivity. Enable OB/OS background colors for visual indication.
Zero-Line Crosses:
Zero-line crosses indicate momentum shifts and can provide early warning signals before MACD crosses the signal line. Enable alerts for zero-line crosses to catch these early signals.
Alert Management:
Enable alert cooldown (default enabled, 5 bars) to prevent alert spam. Use alert type filter to only evaluate specific alert types. Signal debounce (default enabled, 3 bars) prevents duplicate MACD cross signals during choppy markets.
Technical Specifications
- Pine Script Version: v6
- Indicator Type: Non-overlay (displays in separate panel below price chart)
- Repainting Behavior: Minimal - all signals are based on confirmed bars, ensuring accurate backtesting results
- Performance: Optimized with conditional execution. Features only calculate when enabled.
- Compatibility: Works on all timeframes (1 minute to 1 month) and all instruments (stocks, forex, crypto, futures, etc.)
- Edge Case Handling: All calculations include safety checks for division by zero, NA values, and boundary conditions. Alert cooldowns and signal debounce handle edge cases where conditions never occurred or values are NA.
Technical Notes
- All MACD values respect percentage mode conversion when enabled
- Volume confirmation uses cached volume SMA for performance
- Label arrays (divergence) are automatically limited to prevent memory accumulation
- Background coloring: OB/OS backgrounds are drawn on top of main background to ensure visibility
- All calculations are optimized with conditional execution - features only calculate when enabled (performance optimization)
- Signal strength calculation combines multiple factors into a single score for easy filtering
- Cross quality calculation rates crossover quality based on angle, volume, and distance from zero
- Secondary timeframe MACD uses request.security() for higher timeframe data access
- Histogram analysis features (Bollinger Bands, MA, StochMACD) provide additional context beyond basic MACD signals
- Statistics table dynamically adjusts to show only enabled features, keeping it clean and relevant
- Divergence detection uses MACD line (not histogram) for more reliable signals
- Configuration presets automatically optimize MACD parameters for different trading styles
- Smart label placement: Labels appear on current bar at confirmation, using strength from tracked extreme point
- Label spacing uses effective distance (base distance × spacing multiplier) for better distribution
- Zero line polarity enforcement ensures Buy labels only appear when tracked extreme MACD < 0, Sell labels only when tracked extreme MACD > 0
- Label finalization requires MACD exit from OB/OS zone, sufficient bars passed, and recovery/decline percentage confirmation
- Strength-based filtering automatically compares and keeps only the strongest label when multiple signals are close together
- Enhanced visualization: Line outlines drawn behind main lines for superior visibility (black default, configurable)
- Enhanced visualization: Fill between MACD and zero line provides instant visual feedback (green above, red below)
- Enhanced visualization: Fill between OB/OS thresholds highlights neutral zone when dynamic levels are active
- Custom chart background overrides background mode when enabled, allowing theme-consistent indicator panels
Hurst-Optimized Adaptive Channel [Kodexius]Hurst-Optimized Adaptive Channel (HOAC) is a regime-aware channel indicator that continuously adapts its centerline and volatility bands based on the market’s current behavior. Instead of using a single fixed channel model, HOAC evaluates whether price action is behaving more like a trend-following environment or a mean-reverting environment, then automatically selects the most suitable channel structure.
At the core of the engine is a robust Hurst Exponent estimation using R/S (Rescaled Range) analysis. The Hurst value is smoothed and compared against user-defined thresholds to classify the market regime. In trending regimes, the script emphasizes stability by favoring a slower, smoother channel when it proves more accurate over time. In mean-reversion regimes, it deliberately prioritizes a faster model to react sooner to reversion opportunities, similar in spirit to how traders use Bollinger-style behavior.
The result is a clean, professional adaptive channel with inner and outer bands, dynamic gradient fills, and an optional mean-reversion signal layer. A minimalist dashboard summarizes the detected regime, the current Hurst reading, and which internal model is currently preferred.
🔹 Features
🔸 Robust Regime Detection via Hurst Exponent (R/S Analysis)
HOAC uses a robust Hurst Exponent estimate derived from log returns and Rescaled Range analysis. The Hurst value acts as a behavioral filter:
- H > Trend Start threshold suggests trend persistence and directional continuation.
- H < Mean Reversion threshold suggests anti-persistence and a higher likelihood of reverting toward a central value.
Values between thresholds are treated as Neutral, allowing the channel to remain adaptive without forcing a hard bias.
This regime framework is designed to make the channel selection context-aware rather than purely reactive to recent volatility.
🔸 Dual Channel Engine (Fast vs Slow Models)
Instead of relying on one fixed channel, HOAC computes two independent channel candidates:
Fast model: shorter WMA basis and standard deviation window, intended to respond quickly and fit more reactive environments.
Slow model: longer WMA basis and standard deviation window, intended to reduce noise and better represent sustained directional flow.
Each model produces:
- A midline (basis)
- Outer bands (wider deviation)
- Inner bands (tighter deviation)
This structure gives you a clear core zone and an outer envelope that better represents volatility expansion.
🔸 Rolling Optimization Memory (Model Selection by Error)
HOAC includes an internal optimization layer that continuously measures how well each model fits current price action. On every bar, each model’s absolute deviation from the basis is recorded into a rolling memory window. The script then compares total accumulated error between fast and slow models and prefers the one with lower recent error.
This approach does not attempt curve fitting on multiple parameters. It focuses on a simple, interpretable metric: “Which model has tracked price more accurately over the last X bars?”
Additionally:
If the regime is Mean Reversion, the script explicitly prioritizes the fast model, ensuring responsiveness when reversals matter most.
🔸 Optional Output Smoothing (User-Selectable)
The final selected channel can be smoothed using your choice of:
- SMA
- EMA
- HMA
- RMA
This affects the plotted midline and all band outputs, allowing you to tune visual stability and responsiveness without changing the underlying decision engine.
🔸 Premium Visualization Layer (Inner Core + Outer Fade)
HOAC uses a layered band design:
- Inner bands define the core equilibrium zone around the midline.
- Outer bands define an extended volatility envelope for extremes.
Gradient fills and line styling help separate the core from the extremes while staying visually clean. The midline includes a subtle glow effect for clarity.
🔸 Adaptive Bar Tinting Strength (Regime Intensity)
Bar coloring dynamically adjusts transparency based on how far the Hurst value is from 0.5. When market behavior is more decisively trending or mean-reverting, the tint becomes more pronounced. When behavior is closer to random, the tint becomes more subtle.
🔸 Mean-Reversion Signal Layer
Mean-reversion signals are enabled when the environment is not classified as Trending:
- Buy when price crosses back above the lower outer band
- Sell when price crosses back below the upper outer band
This is intentionally a “return to channel” logic rather than a breakout logic, aligning signals with mean-reversion behavior and avoiding signals in strongly trending regimes by default.
🔸 Minimalist Dashboard (HUD)
A compact table displays:
- Current regime classification
- Smoothed Hurst value
- Which model is currently preferred (Fast or Slow)
- Trend flow direction (based on midline slope)
🔹 Calculations
1) Robust Hurst Exponent (R/S Analysis)
The script estimates Hurst using a Rescaled Range approach on log returns. It builds a returns array, computes mean, cumulative deviation range (R), standard deviation (S), then converts RS into a Hurst exponent.
calc_robust_hurst(int length) =>
float r = math.log(close / close )
float returns = array.new_float(length)
for i = 0 to length - 1
array.set(returns, i, r )
float mean = array.avg(returns)
float cumDev = 0.0
float maxCD = -1.0e10
float minCD = 1.0e10
float sumSqDiff = 0.0
for i = 0 to length - 1
float val = array.get(returns, i)
sumSqDiff += math.pow(val - mean, 2)
cumDev += (val - mean)
if cumDev > maxCD
maxCD := cumDev
if cumDev < minCD
minCD := cumDev
float R = maxCD - minCD
float S = math.sqrt(sumSqDiff / length)
float RS = (S == 0) ? 0.0 : (R / S)
float hurst = (RS > 0) ? (math.log10(RS) / math.log10(length)) : 0.5
hurst
This design avoids simplistic proxies and attempts to reflect persistence (trend tendency) vs anti-persistence (mean reversion tendency) from the underlying return structure.
2) Hurst Smoothing
Raw Hurst values can be noisy, so the script applies EMA smoothing before regime decisions.
float rawHurst = calc_robust_hurst(i_hurstLen)
float hVal = ta.ema(rawHurst, i_smoothHurst)
This stabilized hVal is the value used across regime classification, dynamic visuals, and the HUD display.
3) Regime Classification
The smoothed Hurst reading is compared to user thresholds to label the environment.
string regime = "NEUTRAL"
if hVal > i_trendZone
regime := "TRENDING"
else if hVal < i_chopZone
regime := "MEAN REV"
Higher Hurst implies more persistence, so the indicator treats it as a trend environment.
Lower Hurst implies more mean-reverting behavior, so the indicator enables MR logic and emphasizes faster adaptation.
4) Dual Channel Models (Fast and Slow)
HOAC computes two candidate channel structures in parallel. Each model is a WMA basis with volatility envelopes derived from standard deviation. Inner and outer bands are created using different multipliers.
Fast model (more reactive):
float fastBasis = ta.wma(close, 20)
float fastDev = ta.stdev(close, 20)
ChannelObj fastM = ChannelObj.new(fastBasis, fastBasis + fastDev * 2.0, fastBasis - fastDev * 2.0, fastBasis + fastDev * 1.0, fastBasis - fastDev * 1.0, math.abs(close - fastBasis))
Slow model (more stable):
float slowBasis = ta.wma(close, 50)
float slowDev = ta.stdev(close, 50)
ChannelObj slowM = ChannelObj.new(slowBasis, slowBasis + slowDev * 2.5, slowBasis - slowDev * 2.5, slowBasis + slowDev * 1.25, slowBasis - slowDev * 1.25, math.abs(close - slowBasis))
Both models store their structure in a ChannelObj type, including the instantaneous tracking error (abs(close - basis)).
5) Rolling Error Memory and Model Preference
To decide which model fits current conditions better, the script stores recent errors into rolling arrays and compares cumulative error totals.
var float errFast = array.new_float()
var float errSlow = array.new_float()
update_error(float errArr, float error, int maxLen) =>
errArr.unshift(error)
if errArr.size() > maxLen
errArr.pop()
Each bar updates both error histories and computes which model has lower recent accumulated error.
update_error(errFast, fastM.error, i_optLookback)
update_error(errSlow, slowM.error, i_optLookback)
bool preferFast = errFast.sum() < errSlow.sum()
This is an interpretable optimization approach: it does not attempt to brute-force parameters, it simply prefers the model that has tracked price more closely over the last i_optLookback bars.
6) Winner Selection Logic (Regime-Aware Hybrid)
The final model selection uses both regime and rolling error performance.
ChannelObj winner = regime == "MEAN REV" ? fastM : (preferFast ? fastM : slowM)
rawMid := winner.mid
rawUp := winner.upper
rawDn := winner.lower
rawUpInner := winner.upper_inner
rawDnInner := winner.lower_inner
In Mean Reversion, the script forces the fast model to ensure responsiveness.
Otherwise, it selects the lowest-error model between fast and slow.
7) Optional Output Smoothing
After the winner is selected, the script optionally smooths the final channel outputs using the chosen moving average type.
smooth(float src, string type, int len) =>
switch type
"SMA" => ta.sma(src, len)
"EMA" => ta.ema(src, len)
"HMA" => ta.hma(src, len)
"RMA" => ta.rma(src, len)
=> src
float finalMid = i_enableSmooth ? smooth(rawMid, i_smoothType, i_smoothLen) : rawMid
float finalUp = i_enableSmooth ? smooth(rawUp, i_smoothType, i_smoothLen) : rawUp
float finalDn = i_enableSmooth ? smooth(rawDn, i_smoothType, i_smoothLen) : rawDn
float finalUpInner = i_enableSmooth ? smooth(rawUpInner, i_smoothType, i_smoothLen) : rawUpInner
float finalDnInner = i_enableSmooth ? smooth(rawDnInner, i_smoothType, i_smoothLen) : rawDnInner
This preserves decision integrity since smoothing happens after model selection, not before.
8) Dynamic Visual Intensity From Hurst
Transparency is derived from the distance of hVal to 0.5, so stronger behavioral regimes appear with clearer tints.
int dynTrans = int(math.max(20, math.min(80, 100 - (math.abs(hVal - 0.5) * 200))))
BTC - BEAM: Adaptive Multiple (Open-Source)Title: BTC - BEAM: Adaptive Multiple Cycle Oscillator | RM
Overview & Philosophy
The BTC - BEAM (Bitcoin Economics Adaptive Multiple) is a premier macro-valuation tool designed to identify the "Logarithmic Pulse" of Bitcoin's 4-year cycles. Unlike standard oscillators that lose relevance as the network grows, BEAM uses an adaptive baseline that tracks Bitcoin’s fundamental growth curve with precision.
It identifies the harmonic distance between the current price and its multi-year mean, helping you spot the rare windows of deep capitulation and terminal euphoria.
Methodology
This edition is a hardened, gap-proof and Open-Source implementation of the canonical BEAM model.
1. The 1400-Day Anchor (200 Weeks):
The model is anchored to a 1400-day Simple Moving Average. On the Weekly chart, this aligns with the legendary 200-week moving average—the historical "floor" of the Bitcoin network. It represents one full halving cycle of data.
2. Daily-Lock Architecture:
Even when viewed on the 1W chart, the script performs its calculations using Daily data. This ensures that the oscillator captures the exact peak day of a cycle, providing a "high-resolution" signal within a "low-noise" weekly environment.
3. Logarithmic Normalization:
We calculate the natural logarithm of the price-to-mean relationship, scaled by a factor of 2.5: Score = ln(Price / 1400d MA) / 2.5 This creates a standardized "Multiple" that remains comparable across all Bitcoin eras.
How to Read the Chart (1W Context)
🟧 The BEAM Line (Orange): Tracks the "macro heat" of the market. On the 1W chart, look for the slope of this line to identify cycle acceleration.
🔴 The Cycle Ceiling (Score > 1.0): Historical Cycle Tops. When the weekly candle sustains in this zone, the market has reached a state of unsustainable mania. Every major blow-off top has been captured in this red corridor.
🟢 The Cycle Floor (Score < 0.1): Generational Accumulation. On the 1W chart, these zones appear as extended "green troughs." These are the only times in history where Bitcoin is fundamentally "too cheap" relative to its 4-year trend.
The Status Dashboard
The bottom-right monitor provides immediate cycle classification:
• BEAM Score: The exact logarithmic multiple.
• Cycle Regime: ACCUMULATION , NEUTRAL , or OVERHEATED .
Credits
BitcoinEcon: For the original concept of the BEAM adaptive model.
⚠️ RECOMMENDATION: While this indicator captures daily data, it is strongly recommended to be viewed on the Weekly (1W) Timeframe. The 1W chart filters market noise and perfectly reveals the long-term "Cycle Narrative."
Disclaimer
This script is for research and educational purposes only. Macro indicators provide structural context; they are not crystal balls. Always manage your risk according to your personal financial plan.
Tags
bitcoin, btc, beam, macro, cycle, halving, log-growth, valuation, on-chain, Rob Maths
CandelaCharts - Composite Pressure Index 📝 Overview
The CandelaCharts – Composite Pressure Index (CPI) is a multi-factor oscillator that blends RSI , Money Flow Index (MFI) , and Chaikin Money Flow (CMF) into a single, stretchable “pressure” line. Instead of looking at three separate indicators, CPI compresses price momentum and volume flow into one normalized curve around 0 , then amplifies extremes using a rolling z-score .
The result is a dynamic gauge of buying vs. selling pressure that can travel beyond ±1 during strong regime shifts, helping you spot exhaustion, climaxes, and trend-strength phases more intuitively.
📦 Features
Composite pressure engine – Combines RSI, MFI, and CMF into a single normalized oscillator around 0, giving you a unified view of market pressure.
Custom weighting of components – Independently weight RSI, MFI, and CMF to prioritize pure price momentum or volume-driven signals.
Rolling z-score stretch – Uses a configurable z-score window to “stretch” the composite values, letting the line exceed ±1 during extremes instead of staying capped.
Adaptive amplitude control – An amplitude (gain) factor lets you scale how aggressive or subtle the CPI swings appear.
EMA smoothing – Optional smoothing removes noise while preserving the timing of swings and reversals.
Visual pressure band – Zero, +1, and -1 reference lines with a shaded band make it easy to see when pressure is “normal” vs. extended.
Dynamic color gradients – Warm/orange tones above 0 for bullish pressure and cool/blue tones below 0 for bearish pressure, with saturation increasing as pressure intensifies.
NA-safe statistics – Custom mean and standard deviation routines ensure stable behavior from the start of the chart and during partial history.
⚙️ Settings
RSI Length : Lookback length for RSI . Higher values smooth the RSI component; lower values make it more reactive to short-term price momentum.
MFI Length : Lookback length for the manual Money Flow Index . Adjust this to control how sensitive CPI is to price–volume interaction.
CMF Length : Lookback length for Chaikin Money Flow . This defines the window used to assess accumulation/distribution through volume flow.
RSI Weight : Relative importance of RSI within the composite. Increasing this emphasizes pure price momentum in the CPI.
MFI Weight : Relative importance of MFI. Higher values strengthen the influence of volume-weighted price moves.
CMF Weight : Relative importance of CMF. Raising this highlights accumulation/distribution as a driver of the pressure index.
Smoothing : EMA length applied to the stretched CPI line. A value of 1 effectively disables smoothing, while higher values reduce noise at the cost of a slight lag.
Z-score Window : Rolling window used to compute the mean and standard deviation of the raw composite. This defines the statistical context for what counts as “extreme”. Shorter windows adapt faster; longer windows give a more stable regime.
Amplitude : Gain factor applied to the z-scored composite. Values above 1.0 exaggerate swings and make extremes more visually pronounced; values below 1.0 compress them.
⚡️ Showcase
Composite Pressure Index
Mean Line
Divergences
📒 Usage
1. Identify directional pressure regimes
Use 0 as the key balance line:
CPI > 0 → Net bullish pressure (buyers in control).
CPI < 0 → Net bearish pressure (sellers in control).
You can treat prolonged stays above or below 0 as confirmations of trend direction, especially when price structure agrees.
2. Read statistical extremes instead of fixed levels
Because CPI is stretched via a z-score , values beyond ±1 typically represent statistically meaningful extremes within your chosen window:
CPI > +1 → Overextended bullish pressure / potential euphoria.
CPI < -1 → Overextended bearish pressure / potential capitulation.
These zones are not automatic reversal signals, but they highlight areas where monitoring for exhaustion, blow-offs, or risk-reward shifts can be beneficial.
3. Spot divergences with price
Classic divergence logic applies particularly well when pressure is composite:
Bearish divergence – Price makes higher highs, but CPI makes lower highs or fails to confirm.
Bullish divergence – Price makes lower lows, but CPI makes higher lows or shows less downside extension.
These patterns can be integrated with support/resistance, liquidity levels, and other CandelaCharts tools.
4. Tune the weights to your strategy
Adjust the three weights to match your focus:
Higher RSI weight → More sensitivity to pure price momentum (good for breakout or trend-following systems).
Higher MFI weight → Greater emphasis on price–volume interaction (ideal for spotting volume-confirmed moves).
Higher CMF weight → Stronger focus on accumulation/distribution (helpful for swing and position traders).
5. Integrate with existing setups
The CPI is designed to sit comfortably below price:
Use it as a “context” oscillator underneath your main price-action and liquidity models.
Combine CPI extremes and divergences with key levels, range models, or order flow signals for higher-confluence entries.
🚨 Alerts
The indicator does not provide any alerts!
⚠️ Disclaimer
Trading involves significant risk, and many participants may incur losses. The content on this site is not intended as financial advice and should not be interpreted as such. Decisions to buy, sell, hold, or trade securities, commodities, or other financial instruments carry inherent risks and are best made with guidance from qualified financial professionals. Past performance is not indicative of future results.
Auto-Anchored Fibonacci Volume Profile [Custom Array Engine]Description:
1. The Theoretical Foundation: Structure vs. Participation In professional technical analysis, traders often struggle to reconcile two distinct datasets: Price Geometry (where price should go) and Market Participation (where money actually went).
Why Fibonacci? (The Structure) Fibonacci Retracements map the mathematical structure of a trend. They identify psychological and algorithmic "interest zones" (0.382, 0.5, 0.618) where a correction is statistically likely to terminate. However, Fibonacci levels are theoretical—they are "lines in the sand" that do not guarantee liquidity or reaction.
Why Volume Profile? (The Verification) Volume Profile maps the historical exchange of shares at specific price levels. It reveals "fair value" (High Volume Nodes) and "market imbalance" (Low Volume Nodes). It is the only tool that verifies if a specific price level was actually accepted by institutional participants.
2. Underlying Calculations (The Custom Engine) This script operates on a custom-built calculation engine that bypasses standard built-in functions entirely. It uses Pine Script Arrays to build a Volume Profile from scratch. Here is the breakdown of the proprietary code logic:
A. The "Smart-Fill" Distribution Algorithm (Solves Gapping)
The Problem: Standard volume scripts often assign a candle's entire volume to a single price row. In volatile markets or steep trends, this creates visual "gaps" or a "barcode" effect because price moved too fast to register on every row.
My Solution: I wrote a custom loop that calculates the vertical overlap of every candle against the profile grid.
The Math: Volume Per Bin = Total Candle Volume / Bins Touched.
The Result: If a single volatile candle spans 10 price rows (bins), the script mathematically divides that volume and distributes it equally into all 10 array indices. This generates a solid, continuous distribution curve that accurately reflects price action through the entire candle range, not just the close.
B. Dynamic Arrays & Split-Volume Logic The script initializes two separate floating-point arrays (buyVolArray and sellVolArray) sized to the user's resolution (up to 300 rows). It iterates through the specific time-window of the swing:
If Close >= Open, the calculated volume slice is injected into the Buy Array.
If Close < Open, it is injected into the Sell Array.
These arrays are then visually stacked to render the dual-color profile, allowing traders to see the "Delta" (Buyer vs. Seller aggression) at key structural levels.
C. Custom Garbage Collection (Performance) To enable the "Auto-Anchoring" feature without causing chart lag or visual artifacts ("ghosting"), the script includes a Garbage Collection System. Before drawing a new profile, the script iterates through a tracking array of all existing objects (box.delete, line.delete) and clears them from memory. This ensures the indicator remains lightweight and responsive even when dragging chart margins or switching timeframes.
3. The Synthesis: Why Combine Them? The core philosophy of this script is Confluence . A Fibonacci level without volume is merely a suggestion; a Fibonacci level backed by volume is a defensive wall. By algorithmically anchoring a Volume Profile to the exact coordinates of a Fibonacci swing, this tool allows traders to instantly answer critical questions:
"Is the Golden Pocket (0.618) supported by a High Volume Node (HVN), or is it a Low Volume Node (LVN) that price might slice through?"
"Is the Shallow Retracement (0.382) holding because of structural support, or just a lack of selling pressure?"
4. How to Read the Indicator
The Geometry: The script automatically detects the trend and draws standard Fib levels (0, 0.236, 0.382, 0.5, 0.618, 0.786, 1.0).
The Confluence Check: Look for the Point of Control (Red Line). If this High Volume Node aligns with a key Fib level (e.g., the 0.618), the probability of a reversal increases significantly.
The Imbalance Check: Look for "Valleys" in the profile (Low Volume Nodes). These gaps often act as "slippage zones" where price travels quickly between structural levels.
Buy/Sell Splits: The dual-color bars (Teal/Red) reveal the composition of the volume. A 0.618 level held up by dominant Buy Volume is a stronger bullish signal than one with mixed volume.
5. Settings & Customization
Lookback Length: Sensitivity of the swing detection (Default: 200 bars).
Resolution: Granularity of the profile rows (Default: 100). Higher values provide smoother definition.
Width (%): Responsive sizing that scales the profile relative to the trend's duration.
Extend Lines: Option to project structural levels infinitely to the right.
Disclaimer This script is an analytical tool for visualizing historical market data. It does not provide trade signals or financial advice.
Trinity Bollinger Bands Pro with BreakoutsTrinity Bollinger Bands Pro Indicator
The **Trinity Bollinger Bands Pro + Triple Bands & Expansion** is a highly customized, advanced volatility and breakout indicator built on the classic Bollinger Bands framework. It expands the standard single-pair bands into **three independent deviation levels** (typically 1σ, 2σ, and 3σ) around a user-selectable moving average basis (default EMA 20). This creates clear "zones" of volatility, with dynamic trend-based coloring, layered fills, fixed-style labels, and a statistical volatility expansion detector shown as a directional background highlight in a separate pane. The result is a visually intuitive tool that helps traders identify consolidation, building momentum, confirmed trends, and rare explosive moves with high-probability filtering.
### Why It's Good and Different from Standard Indicators
This indicator stands out by addressing common limitations of traditional Bollinger Bands and multi-deviation scripts:
- **Layered statistical significance**: Unlike single (2σ) or basic double-band setups, it provides three distinct levels—early momentum (1σ), standard confirmation (2σ), and extreme/rare breakouts (3σ)—making it easier to stage trades progressively rather than relying on one ambiguous cross.
- **Trend-aware visuals**: Bands, basis, and fills change color based on price position relative to a separate trend MA, giving immediate bullish/bearish bias without needing additional indicators.
- **Clean, fixed labels**: Tiny, arrow-pointing labels ("1/2/3 SD Above/Below", "BB Basis") with consistent colors (purple upper, blue lower, yellow basis) provide instant identification
- **Statistical expansion detection**: Uses percentile ranking of band width "bell curve" concept" to identify abnormally high volatility, triggering directional background highlights (green bullish, red bearish) earlier than raw width spikes.
- **Reduced noise and fakeouts**: Tiered breakouts + expansion filter focus alerts on high-probability moves, unlike most BB scripts that flood signals on every touch.
Compared to popular public scripts (e.g., standard Bollinger Bands, Triple BB variants, or separate BBW Percentile tools), this combines everything into one cohesive indicator with superior visual clarity and statistical rigor.
### Key Features
- **Triple customizable bands**: Enable/disable and adjust multipliers for 1σ (early), 2σ (confirmed), 3σ (extreme) deviations.
- **Trend-based dynamic coloring**: Separate editable colors for each band set (bullish/bearish).
- **Layered zone fills**: Colored between bands with transparency, reflecting current trend.
- **Fixed tiny labels**: All left-pointing arrows with purple (upper), blue (lower), yellow (basis) backgrounds for quick reference.
- **Statistical expansion overlay**: with directional background (green/red) during extreme volatility expansions (earlier trigger using 2σ width).
- **Tiered alerts**: Early (Band 1), Confirmed (Band 2), Extreme (Band 3), High-Probability (Extreme + expansion), and general expansion alerts.
- **Fully configurable basis**: Length, type (SMA/EMA/WMA/RMA), and thin fixed lines for minimal clutter.
### How Traders Can Use It
- **Spot squeezes and breakouts**: Watch for tight bands (low width) → expansion background → price closing outside Band 1 (early entry), Band 2 (add/confirm), Band 3 (strong trend conviction).
- **Filter fakeouts**: Only act on crosses accompanied by expansion background color matching trend direction—dramatically reduces whipsaws.
- **Trend riding**: Price "walking" colored bands (e.g., hugging upper purple-label bands in green background = strong bullish momentum).
- **Scalping/intraday**: On lower timeframes (e.g., 10min), use early Band 1 signals with expansion for quick moves.
- **Swing/position trading**: Wait for Band 3 extreme breakout + colored background for higher-probability, larger moves.
- **Risk management**: Place stops near basis or inner band; trail using outer bands during expansions.
Overall, this indicator excels at turning volatility into actionable, staged signals with visual simplicity—ideal for traders seeking an edge in identifying real explosive trends over noise. It's particularly powerful on volatile stocks like AMD/INTC or indices during news/events.
Adaptive 2-Pole Trend Bands [supfabio]Adaptive 2-Pole Trend Bands is a volatility-aware trend filtering indicator designed to identify the dominant market direction while providing dynamic reference zones around price.
Instead of relying on traditional moving averages, this indicator uses a two-pole digital filter to smooth price action while maintaining responsiveness. Around this central trend line, a multi-band structure based on ATR is applied to help traders evaluate pullbacks, extensions, and potential exhaustion areas within a trend.
Core Concept
The indicator is built around three key ideas:
Digital Trend Filtering
Volatility-Adjusted Bands
Trend Persistence Measurement
These components work together to separate meaningful price movement from noise and to provide context for how far price has moved relative to recent volatility.
Two-Pole Trend Filter
At its core, the indicator uses a two-pole smoothing filter, which produces a cleaner trend curve than common moving averages.
Compared to standard averages, this approach:
Reduces market noise
Produces smoother transitions
Responds faster to genuine trend changes
Avoids excessive lag in trending markets
The result is a trend line that represents the structural direction of price, rather than short-term fluctuations.
Adaptive Multi-Band System
Around the central trend filter, the indicator plots four independent volatility-based bands, each derived from the Average True Range (ATR).
Each band represents a different degree of price extension:
Band 1: Shallow pullbacks and minor reactions
Band 2: Moderate extensions within a trend
Band 3: Strong directional moves
Band 4: Extreme extensions relative to recent volatility
Because the bands are ATR-based, they automatically adapt to changing market conditions, expanding during high volatility and contracting during calmer periods.
This makes the indicator suitable for both slow and fast markets without manual recalibration.
Trend State Detection
The color of the central filter dynamically reflects trend persistence, not just direction:
Sustained upward movement highlights bullish conditions
Sustained downward movement highlights bearish conditions
Transitional phases are visually distinct, helping identify regime changes
This logic is based on how long price has maintained directional behavior, reducing sensitivity to isolated candles or short-lived spikes.
Practical Applications
This indicator can be used as:
A trend filter for discretionary or systematic strategies
A context tool to evaluate pullbacks versus overextension
A risk reference to avoid entries in extreme price zones
A confirmation layer when combined with price action or momentum tools
It performs consistently across different asset classes, including futures, cryptocurrencies, forex, indices, and equities.
Configuration
Key parameters such as filter length, damping factor, and band multipliers are fully configurable, allowing traders to adapt the indicator to different timeframes and trading styles.
Important Notes
This indicator does not predict future price movement
It does not generate guaranteed buy or sell signals
Best results are achieved when used in combination with sound risk management and additional confirmation tools
Past behavior does not imply future performance
Disclaimer
This indicator is provided for educational and analytical purposes only and should not be considered financial advice.
Se quiser, posso:
Criar uma versão resumida para a primeira linha da publicação
Ajustar o texto para um tom mais técnico ou mais comercial
Traduzir para português mantendo o inglês como idioma principal
Revisar o título para SEO dentro da Biblioteca Pública
Mutanabby_AI | ONEUSDT_MR1
ONEUSDT Mean-Reversion Strategy | 74.68% Win Rate | 417% Net Profit
This is a long-only mean-reversion strategy designed specifically for ONEUSDT on the 1-hour timeframe. The core logic identifies oversold conditions following sharp declines and enters positions when selling pressure exhausts, capturing the subsequent recovery bounce.
Backtested Period: June 2019 – December 2025 (~6 years)
Performance Summary
| Metric | Value |
|--------|-------|
| Net Profit | +417.68% |
| Win Rate | 74.68% |
| Profit Factor | 4.019 |
| Total Trades | 237 |
| Sharpe Ratio | 0.364 |
| Sortino Ratio | 1.917 |
| Max Drawdown | 51.08% |
| Avg Win | +3.14% |
| Avg Loss | -2.30% |
| Buy & Hold Return | -80.44% |
Strategy Logic :
Entry Conditions (Long Only):
The strategy seeks confluence of three conditions that identify exhausted selling:
1. Prior Move Filter:*The price change from 5 bars ago to 3 bars ago must be ≥ -7% (ensures we're not entering during freefall)
2. Current Move Filter: The price change over the last 2 bars must be ≤ 0% (confirms momentum is stalling or reversing)
3. Three-Bar Decline: The price change from 5 bars ago to 3 bars ago must be ≤ -5% (confirms a significant recent drop occurred)
When all three conditions align, the strategy identifies a potential reversal point where sellers are exhausted.
Exit Conditions:
- Primary Exit: Close above the previous bar's high while the open of the previous bar is at or below the close from 9 bars ago (profit-taking on strength)
- Trailing Stop: 11x ATR trailing stop that locks in profits as price rises
Risk Management
- Position Sizing:Fixed position based on account equity divided by entry price
- Trailing Stop:11× ATR (14-period) provides wide enough room for crypto volatility while protecting gains
- Pyramiding:Up to 4 orders allowed (can scale into winning positions)
- **Commission:** 0.1% per trade (realistic exchange fees included)
Important Disclaimers
⚠️ This is NOT financial advice.
- Past performance does not guarantee future results
- Backtest results may contain look-ahead bias or curve-fitting
- Real trading involves slippage, liquidity issues, and execution delays
- This strategy is optimized for ONEUSDT specifically — results may differ on other pairs
- Always test before risking real capital
Recommended Usage
- Timeframe:*1H (as designed)
- Pair: ONEUSDT (Binance)
- Account Size: Ensure sufficient capital to survive max drawdown
Source Code
Feedback Welcome
I'm sharing this strategy freely for educational purposes. Please:
- Drop a comment with your backtesting results any you analysis
- Share any modifications that improve performance
- Let me know if you spot any issues in the logic
Happy trading
As a quant trader, do you think this strategy will survive in live trading?
Yes or No? And why?
I want to hear from you guys
ALT Risk Metric StrategyHere's a professional write-up for your ALT Risk Strategy script:
ALT/BTC Risk Strategy - Multi-Crypto DCA with Bitcoin Correlation Analysis
Overview
This strategy uses Bitcoin correlation as a risk indicator to time entries and exits for altcoins. By analyzing how your chosen altcoin performs relative to Bitcoin, the strategy identifies optimal accumulation periods (when alt/BTC is oversold) and profit-taking opportunities (when alt/BTC is overbought). Perfect for traders who want to outperform Bitcoin by strategically timing altcoin positions.
Key Innovation: Why Alt/BTC Matters
Most traders focus solely on USD price, but Alt/BTC ratios reveal true altcoin strength:
When Alt/BTC is low → Altcoin is undervalued relative to Bitcoin (buy opportunity)
When Alt/BTC is high → Altcoin has outperformed Bitcoin (take profits)
This approach captures the rotation between BTC and alts that drives crypto cycles
Key Features
📊 Advanced Technical Analysis
RSI (60% weight): Primary momentum indicator on weekly timeframe
Long-term MA Deviation (35% weight): Measures distance from 150-period baseline
MACD (5% weight): Minor confirmation signal
EMA Smoothing: Filters noise while maintaining responsiveness
All calculations performed on Alt/BTC pairs for superior market timing
💰 3-Tier DCA System
Level 1 (Risk ≤ 70): Conservative entry, base allocation
Level 2 (Risk ≤ 50): Increased allocation, strong opportunity
Level 3 (Risk ≤ 30): Maximum allocation, extreme undervaluation
Continuous buying: Executes every bar while below threshold for true DCA behavior
Cumulative sizing: L3 triggers = L1 + L2 + L3 amounts combined
📈 Smart Profit Management
Sequential selling: Must complete L1 before L2, L2 before L3
Percentage-based exits: Sell portions of position, not fixed amounts
Auto-reset on re-entry: New buy signals reset sell progression
Prevents premature full exits during volatile conditions
🤖 3Commas Automation
Pre-configured JSON webhooks for Custom Signal Bots
Multi-exchange support: Binance, Coinbase, Kraken, Bitfinex, Bybit
Flexible quote currency: USD, USDT, or BUSD
Dynamic order sizing: Automatically adjusts to your tier thresholds
Full webhook documentation compliance
🎨 Multi-Asset Support
Pre-configured for popular altcoins:
ETH (Ethereum)
SOL (Solana)
ADA (Cardano)
LINK (Chainlink)
UNI (Uniswap)
XRP (Ripple)
DOGE
RENDER
Custom option for any other crypto
How It Works
Risk Metric Calculation (0-100 scale):
Fetches weekly Alt/BTC price data for stability
Calculates RSI, MACD, and deviation from 150-period MA
Normalizes MACD to 0-100 range using 500-bar lookback
Combines weighted components: (MACD × 0.05) + (RSI × 0.60) + (Deviation × 0.35)
Applies 5-period EMA smoothing for cleaner signals
Color-Coded Risk Zones:
Green (0-30): Extreme buying opportunity - Alt heavily oversold vs BTC
Lime/Yellow (30-70): Accumulation range - favorable risk/reward
Orange (70-85): Caution zone - consider taking initial profits
Red/Maroon (85-100+): Euphoria zone - aggressive profit-taking
Entry Logic:
Buys execute every candle when risk is below threshold
As risk decreases, position sizing automatically scales up
Example: If risk drops from 60→25, you'll be buying at L1 rate until it hits 50, then L2 rate, then L3 rate
Exit Logic:
Sells only trigger when in profit AND risk exceeds thresholds
Sequential execution ensures partial profit-taking
If new buy signal occurs before all sells complete, sell levels reset to L1
Configuration Guide
Choosing Your Altcoin:
Select crypto from dropdown (or use CUSTOM for unlisted coins)
Pick your exchange
Choose quote currency (USD, USDT, BUSD)
Risk Metric Tuning:
Long Term MA (default 150): Higher = more extreme signals, Lower = more frequent
RSI Length (default 10): Lower = more volatile, Higher = smoother
Smoothing (default 5): Increase for less noise, decrease for faster reaction
Buy Settings (Aggressive DCA Example):
L1 Threshold: 70 | Amount: $5
L2 Threshold: 50 | Amount: $6
L3 Threshold: 30 | Amount: $7
Total L3 buy = $18 per candle when deeply oversold
Sell Settings (Balanced Exit Example):
L1: 70 threshold, 25% position
L2: 85 threshold, 35% position
L3: 100 threshold, 40% position (final exit)
3Commas Setup
Bot Configuration:
Create Custom Signal Bot in 3Commas
Set trading pair to your altcoin/USD (e.g., ETH/USD, SOL/USDT)
Order size: Select "Send in webhook, quote" to use strategy's dollar amounts
Copy Bot UUID and Secret Token
Script Configuration:
Paste credentials into 3Commas section inputs
Check "Enable 3Commas Alerts"
Save and apply to chart
TradingView Alert:
Create Alert → Condition: "alert() function calls only"
Webhook URL: api.3commas.io
Enable "Webhook URL" checkbox
Expiration: Open-ended
Strategy Advantages
✅ Outperform Bitcoin: Designed specifically to beat BTC by timing alt rotations
✅ Capture Alt Seasons: Automatically accumulates when alts lag, sells when they pump
✅ Risk-Adjusted Sizing: Buys more when cheaper (better risk/reward)
✅ Emotional Discipline: Systematic approach removes fear and FOMO
✅ Multi-Asset: Run same strategy across multiple altcoins simultaneously
✅ Proven Indicators: Combines RSI, MACD, and MA deviation - battle-tested tools
Backtesting Insights
Optimal Timeframes:
Daily chart: Best for backtesting and signal generation
Weekly data is fetched internally regardless of display timeframe
Historical Performance Characteristics:
Accumulates heavily during bear markets and BTC dominance periods
Captures explosive altcoin rallies when BTC stagnates
Sequential selling preserves capital during extended downtrends
Works best on established altcoins with multi-year history
Risk Considerations:
Requires capital reserves for extended accumulation periods
Some altcoins may never recover if fundamentals deteriorate
Past correlation patterns may not predict future performance
Always size positions according to personal risk tolerance
Visual Interface
Indicator Panel Displays:
Dynamic color line: Green→Lime→Yellow→Orange→Red as risk increases
Horizontal threshold lines: Dashed lines mark your buy/sell levels
Entry/Exit labels: Green labels for buys, Orange/Red/Maroon for sells
Real-time risk value: Numerical display on price scale
Customization:
All threshold lines are adjustable via inputs
Color scheme clearly differentiates buy zones (green spectrum) from sell zones (red spectrum)
Line weights emphasize most extreme thresholds (L3 buy and L3 sell)
Strategy Philosophy
This strategy is built on the principle that altcoins move in cycles relative to Bitcoin. During Bitcoin rallies, alts often bleed against BTC (high sell, accumulate). When Bitcoin consolidates, alts pump (take profits). By measuring risk on the Alt/BTC chart instead of USD price, we time these rotations with precision.
The 3-tier system ensures you're always averaging in at better prices and scaling out at better prices, maximizing your Bitcoin-denominated returns.
Advanced Tips
Multi-Bot Strategy:
Run this on 5-10 different altcoins simultaneously to:
Diversify correlation risk
Capture whichever alt is pumping
Smooth equity curve through rotation
Pairing with BTC Strategy:
Use alongside the BTC DCA Risk Strategy for complete portfolio coverage:
BTC strategy for core holdings
ALT strategies for alpha generation
Rebalance between them based on BTC dominance
Threshold Calibration:
Check 2-3 years of historical data for your chosen alt
Note where risk metric sat during major bottoms (set buy thresholds)
Note where it peaked during euphoria (set sell thresholds)
Adjust for your risk tolerance and holding period
Credits
Strategy Development & 3Commas Integration: Claude AI (Anthropic)
Technical Analysis Framework: RSI, MACD, Moving Average theory
Implementation: pommesUNDwurst
Disclaimer
This strategy is for educational purposes only. Cryptocurrency trading involves substantial risk of loss. Altcoins are especially volatile and many fail completely. The strategy assumes liquid markets and reliable Alt/BTC price data. Always do your own research, understand the fundamentals of any asset you trade, and never risk more than you can afford to lose. Past performance does not guarantee future results. The authors are not financial advisors and assume no liability for trading decisions.
Additional Warning: Using leverage or trading illiquid altcoins amplifies risk significantly. This strategy is designed for spot trading of established cryptocurrencies with deep liquidity.
Tags: Altcoin, Alt/BTC, DCA, Risk Metric, Dollar Cost Averaging, 3Commas, ETH, SOL, Crypto Rotation, Bitcoin Correlation, Automated Trading, Alt Season
Feel free to modify any sections to better match your style or add specific backtesting results you've observed! 🚀Claude is AI and can make mistakes. Please double-check responses. Sonnet 4.5
Macro-Sentiment (Macro_Serie 1:7)Part of a 7-indicator macro series. Combines yield curve dynamics, VIX structure, employment data (jobless claims, NFP), ISM manufacturing, US-Japan carry trade flows, and consumer sentiment into a single adaptive stress score. Color-coded regimes guide strategy from "Aggressive" to "Buy the Crash."
Triple ATR Adaptive MAs + VWAP Option + Clouds + Candle Trend V2Another one of my experiences ... combining things...
📘 Indicator Description – Triple ATR Adaptive Moving Averages with VWAP Influence
This indicator plots three adaptive moving averages whose behavior changes dynamically based on market volatility (ATR) and optionally VWAP deviation.
Because they adapt in real time to both volatility and VWAP pressure, their movement, slope, and reaction speed differ significantly from traditional moving averages.
🔶 1. ATR-Adaptive Moving Averages
Each of the three MAs uses a custom adaptive formula:
ATR (Average True Range) is measured over a chosen period.
Higher ATR → more volatility → the MA becomes more reactive and moves closer to price.
Lower ATR → stable market → the MA becomes smoother and slower.
This creates a volatility-aware smoothing factor, making the MA expand, contract, and respond to market conditions in ways a classic SMA, EMA, or HMA cannot.
🔷 2. Optional VWAP Influence
Each MA has an independent toggle allowing it to be influenced by VWAP.
When enabled:
The MA is gently “pulled” toward VWAP.
The strength of this attraction is determined by the VWAP Influence parameter (0–1).
This causes the moving averages to behave differently from normal MAs:
In trending markets, the ATR and price push the MA away from VWAP.
In mean-reverting or balanced conditions, VWAP pulls the MA back toward fair value.
The result is an MA that reflects both trend pressure and fair-value pressure.
🔶 3. Visual Behavior: Non-Traditional Movement
Because each MA is simultaneously influenced by volatility, trend magnitude, and VWAP deviation, their shape is often very distinct from normal moving averages.
They may:
Respond faster during high volatility
Flatten out earlier during consolidation
Curve toward VWAP when price becomes extended
Separate or compress depending on ATR strength
This is intentional and essential, since the goal is to show:
✔ Volatility expansion
✔ Trend exhaustion
✔ Overextended price relative to VWAP
✔ Dynamic trend confirmation
Rather than simply smoothing past price.
🔷 4. Three Independent Adaptive Lines
Each of the three moving averages has:
Its own ATR length
Its own sensitivity multiplier
Its own optional VWAP influence
Its own color and trail
This allows the user to combine:
a fast volatility-adaptive trend line
a mid-range adaptive baseline
a slow adaptive long-trend MA
All adapting independently to volatility and VWAP conditions.
🔶 5. Optional Candle Coloring
The indicator can color candles according to trend strength derived from the fast/slow MAs.
Stronger trends produce more vivid colors. Neutral or conflicting trends produce softer colors.
This adds a visual layer to identify:
Trend direction
Trend strength
Volatility state
Market compression
at a glance.
📌 Summary
This indicator does not behave like standard SMAs or EMAs because each line dynamically adapts to:
🔸 ATR (volatility)
🔸 VWAP (fair value)
This makes the indicator extremely responsive to market conditions while still reducing noise during stable phases.
It provides a more realistic, context-aware, and intelligent representation of price behavior compared to traditional moving averages.
VV Moving Average Convergence Divergence # VMACDv3 - Volume-Weighted MACD with A/D Divergence Detection
## Overview
**VMACDv3** (Volume-Weighted Moving Average Convergence Divergence Version 3) is a momentum indicator that applies volume-weighting to traditional MACD calculations on price, while using the Accumulation/Distribution (A/D) line for divergence detection. This hybrid approach combines volume-weighted price momentum with volume distribution analysis for comprehensive market insight.
## Key Features
- **Volume-Weighted Price MACD**: Traditional MACD calculation on price but weighted by volume for earlier signals
- **A/D Divergence Detection**: Identifies when A/D trend diverges from MACD momentum
- **Volume Strength Filtering**: Distinguishes high-volume confirmations from low-volume noise
- **Color-Coded Histogram**: 4-color system showing momentum direction and volume strength
- **Real-Time Alerts**: Background colors and alert conditions for bullish/bearish divergences
## Difference from ACCDv3
| Aspect | VMACDv3 | ACCDv3 |
|--------|---------|---------|
| **MACD Input** | **Price (Close)** | **A/D Line** |
| **Volume Weighting** | Applied to price | Applied to A/D line |
| **Primary Signal** | Volume-weighted price momentum | Volume distribution momentum |
| **Use Case** | Price momentum with volume confirmation | Volume flow and accumulation/distribution |
| **Sensitivity** | More responsive to price changes | More responsive to volume patterns |
| **Best For** | Trend following, breakouts | Volume analysis, smart money tracking |
**Key Insight**: VMACDv3 shows *where price is going* with volume weight, while ACCDv3 shows *where volume is accumulating/distributing*.
## Components
### 1. Volume-Weighted MACD on Price
Unlike standard MACD that uses simple price EMAs, VMACDv3 weights each price by its corresponding volume:
```
Fast Line = EMA(Price × Volume, 12) / EMA(Volume, 12)
Slow Line = EMA(Price × Volume, 26) / EMA(Volume, 26)
MACD = Fast Line - Slow Line
```
**Benefits of Volume Weighting**:
- High-volume price movements have greater impact
- Filters out low-volume noise and false moves
- Provides earlier trend change signals
- Better reflects institutional activity
### 2. Accumulation/Distribution (A/D) Line
Used for divergence detection, measuring buying/selling pressure:
```
A/D = Σ ((2 × Close - Low - High) / (High - Low)) × Volume
```
- **Rising A/D**: Accumulation (buying pressure)
- **Falling A/D**: Distribution (selling pressure)
- **Doji Handling**: When High = Low, contribution is zero
### 3. Signal Lines
- **MACD Line** (Blue, #2962FF): The fast-slow difference showing momentum
- **Signal Line** (Orange, #FF6D00): EMA or SMA smoothing of MACD
- **Zero Line**: Reference for bullish (above) vs bearish (below) bias
### 4. Histogram Color System
The histogram uses 4 distinct colors based on **direction** and **volume strength**:
| Condition | Color | Meaning |
|-----------|-------|---------|
| Rising + High Volume | **Dark Green** (#1B5E20) | Strong bullish momentum with volume confirmation |
| Rising + Low Volume | **Light Teal** (#26A69A) | Bullish momentum but weak volume (less reliable) |
| Falling + High Volume | **Dark Red** (#B71C1C) | Strong bearish momentum with volume confirmation |
| Falling + Low Volume | **Light Pink** (#FFCDD2) | Bearish momentum but weak volume (less reliable) |
Additional shading:
- **Light Cyan** (#B2DFDB): Positive but not rising (momentum stalling)
- **Bright Red** (#FF5252): Negative and accelerating down
### 5. Divergence Detection
VMACDv3 compares A/D trend against volume-weighted price MACD:
#### Bullish Divergence (Green Background)
- **Condition**: A/D is trending up BUT MACD is negative and trending down
- **Interpretation**: Volume is accumulating while price momentum appears weak
- **Signal**: Smart money accumulation, potential bullish reversal
- **Action**: Look for long entries, especially at support levels
#### Bearish Divergence (Red Background)
- **Condition**: A/D is trending down BUT MACD is positive and trending up
- **Interpretation**: Volume is distributing while price momentum appears strong
- **Signal**: Smart money distribution, potential bearish reversal
- **Action**: Consider exits, avoid new longs, watch for breakdown
## Parameters
| Parameter | Default | Range | Description |
|-----------|---------|-------|-------------|
| **Source** | Close | OHLC/HLC3/etc | Price source for MACD calculation |
| **Fast Length** | 12 | 1-50 | Period for fast EMA (shorter = more sensitive) |
| **Slow Length** | 26 | 1-100 | Period for slow EMA (longer = smoother) |
| **Signal Smoothing** | 9 | 1-50 | Period for signal line (MACD smoothing) |
| **Signal Line MA Type** | EMA | SMA/EMA | Moving average type for signal calculation |
| **Volume MA Length** | 20 | 5-100 | Period for volume average (strength filter) |
## Usage Guide
### Reading the Indicator
1. **MACD Lines (Blue & Orange)**
- **Blue Line (MACD)**: Volume-weighted price momentum
- **Orange Line (Signal)**: Smoothed trend of MACD
- **Crossovers**: Blue crosses above orange = bullish, below = bearish
- **Distance**: Wider gap = stronger momentum
- **Zero Line Position**: Above = bullish bias, below = bearish bias
2. **Histogram Colors**
- **Dark Green (#1B5E20)**: Strong bullish move with high volume - **most reliable buy signal**
- **Light Teal (#26A69A)**: Bullish but low volume - wait for confirmation
- **Dark Red (#B71C1C)**: Strong bearish move with high volume - **most reliable sell signal**
- **Light Pink (#FFCDD2)**: Bearish but low volume - may be temporary dip
3. **Background Divergence Alerts**
- **Green Background**: A/D accumulating while price weak - potential bottom
- **Red Background**: A/D distributing while price strong - potential top
- Most powerful at key support/resistance levels
### Trading Strategies
#### Strategy 1: Volume-Confirmed Trend Following
1. Wait for MACD to cross above zero line
2. Look for **dark green** histogram bars (high volume confirmation)
3. Enter long on second consecutive dark green bar
4. Hold while histogram remains green
5. Exit when histogram turns light green or red appears
6. Set stop below recent swing low
**Example**:
```
Price: 26,400 → 26,450 (rising)
MACD: -50 → +20 (crosses zero)
Histogram: Light teal → Dark green → Dark green
Volume: 50k → 75k → 90k (increasing)
```
#### Strategy 2: Divergence Reversal Trading
1. Identify divergence background (green = bullish, red = bearish)
2. Confirm with price structure (support/resistance, chart patterns)
3. Wait for MACD to cross signal line in divergence direction
4. Enter on first **dark colored** histogram bar after divergence
5. Set stop beyond divergence area
6. Target previous swing high/low
**Example - Bullish Divergence**:
```
Price: Making lower lows (26,350 → 26,300 → 26,250)
A/D: Rising (accumulation)
MACD: Below zero but starting to curve up
Background: Green shading appears
Entry: MACD crosses signal line + dark green bar
Stop: Below 26,230
Target: 26,450 (previous high)
```
#### Strategy 3: Momentum Scalping
1. Trade only in direction of MACD zero line (above = long, below = short)
2. Enter on dark colored bars only
3. Exit on first light colored bar or opposite color
4. Quick in and out (1-5 minute holds)
5. Tight stops (0.2-0.5% depending on instrument)
#### Strategy 4: Histogram Pattern Trading
**V-Bottom Reversal (Bullish)**:
- Red histogram bars start rising (becoming less negative)
- Forms "V" shape at the bottom
- Transitions to light red → light teal → **dark green**
- Entry: First dark green bar
- Signal: Momentum reversal with volume
**Λ-Top Reversal (Bearish)**:
- Green histogram bars start falling (becoming less positive)
- Forms inverted "V" at the top
- Transitions to light green → light pink → **dark red**
- Entry: First dark red bar
- Signal: Momentum exhaustion with volume
### Multi-Timeframe Analysis
**Recommended Approach**:
1. **Higher Timeframe (15m/1h)**: Identify overall trend direction
2. **Trading Timeframe (5m)**: Time entries using VMACDv3 signals
3. **Lower Timeframe (1m)**: Fine-tune entry prices
**Example Setup**:
```
15-minute: MACD above zero (bullish bias)
5-minute: Dark green histogram appears after pullback
1-minute: Enter on break of recent high with volume
```
### Volume Strength Interpretation
The volume filter compares current volume to 20-period average:
- **Volume > Average**: Dark colors (green/red) - high confidence signals
- **Volume < Average**: Light colors (teal/pink) - lower confidence signals
**Trading Rules**:
- ✓ **Aggressive**: Take all dark colored signals
- ✓ **Conservative**: Only take dark colors that follow 2+ light colors of same type
- ✗ **Avoid**: Trading light colored signals during high volatility
- ✗ **Avoid**: Ignoring volume context during news events
## Technical Details
### Volume-Weighted Calculation
```pine
// Volume-weighted fast EMA
fast_ma = ta.ema(src * volume, fast_length) / ta.ema(volume, fast_length)
// Volume-weighted slow EMA
slow_ma = ta.ema(src * volume, slow_length) / ta.ema(volume, slow_length)
// MACD is the difference
macd = fast_ma - slow_ma
// Signal line smoothing
signal = ta.ema(macd, signal_length) // or ta.sma() if SMA selected
// Histogram
hist = macd - signal
```
### Divergence Detection Logic
```pine
// A/D trending up if above its 5-period SMA
ad_trend = ad > ta.sma(ad, 5)
// MACD trending up if above zero
macd_trend = macd > 0
// Divergence when trends oppose each other
divergence = ad_trend != macd_trend
// Specific conditions for alerts
bullish_divergence = ad_trend and not macd_trend and macd < 0
bearish_divergence = not ad_trend and macd_trend and macd > 0
```
### Histogram Coloring Logic
```pine
hist_color = (hist >= 0
? (hist < hist
? (vol_strength ? #1B5E20 : #26A69A) // Rising: dark/light green
: #B2DFDB) // Positive but falling: cyan
: (hist < hist
? (vol_strength ? #B71C1C : #FFCDD2) // Rising (less negative): dark/light red
: #FF5252)) // Falling more: bright red
```
## Alerts
Built-in alert conditions for divergence detection:
### Bullish Divergence Alert
- **Trigger**: A/D trending up, MACD negative and trending down
- **Message**: "Bullish Divergence: A/D trending up but MACD trending down"
- **Use Case**: Potential reversal or continuation after pullback
- **Action**: Look for long entry setups
### Bearish Divergence Alert
- **Trigger**: A/D trending down, MACD positive and trending up
- **Message**: "Bearish Divergence: A/D trending down but MACD trending up"
- **Use Case**: Potential top or trend reversal
- **Action**: Consider exits or short entries
### Setting Up Alerts
1. Click "Create Alert" in TradingView
2. Condition: Select "VMACDv3"
3. Choose alert type: "Bullish Divergence" or "Bearish Divergence"
4. Configure: Email, SMS, webhook, or popup
5. Set frequency: "Once Per Bar Close" recommended
## Comparison Tables
### VMACDv3 vs Standard MACD
| Feature | Standard MACD | VMACDv3 |
|---------|---------------|---------|
| **Price Weighting** | Equal weight all bars | Volume-weighted |
| **Sensitivity** | Fixed | Adaptive to volume |
| **False Signals** | More during low volume | Fewer (volume filter) |
| **Divergence** | Price vs MACD | A/D vs MACD |
| **Volume Analysis** | None | Built-in |
| **Color System** | 2 colors | 4+ colors |
| **Best For** | Simple trend following | Volume-confirmed trading |
### VMACDv3 vs ACCDv3
| Aspect | VMACDv3 | ACCDv3 |
|--------|---------|--------|
| **Focus** | Price momentum | Volume distribution |
| **Reactivity** | Faster to price moves | Faster to volume shifts |
| **Best Markets** | Trending, breakouts | Accumulation/distribution phases |
| **Signal Type** | Where price + volume going | Where smart money positioning |
| **Divergence Meaning** | Volume vs price disagreement | A/D vs momentum disagreement |
| **Use Together?** | ✓ Yes, complementary | ✓ Yes, different perspectives |
## Example Trading Scenarios
### Scenario 1: Strong Bullish Breakout
```
Time: 9:30 AM (market open)
Price: Breaks above 26,400 resistance
MACD: Crosses above zero line
Histogram: Dark green bars (#1B5E20)
Volume: 2x average (150k vs 75k avg)
A/D: Rising (no divergence)
Action: Enter long at 26,405
Stop: 26,380 (below breakout)
Target 1: 26,450 (risk:reward 1:2)
Target 2: 26,500 (risk:reward 1:4)
Result: High probability setup with volume confirmation
```
### Scenario 2: False Breakout (Avoided)
```
Time: 2:30 PM (slow period)
Price: Breaks above 26,400 resistance
MACD: Slightly positive
Histogram: Light teal bars (#26A69A)
Volume: 0.5x average (40k vs 75k avg)
A/D: Flat/declining
Action: Avoid trade
Reason: Low volume, no conviction, potential false breakout
Outcome: Price reverses back below 26,400 within 10 minutes
Saved: Avoided losing trade due to volume filter
```
### Scenario 3: Bullish Divergence Bottom
```
Time: 11:00 AM
Price: Making lower lows (26,350 → 26,300 → 26,280)
MACD: Below zero but curving upward
Histogram: Red bars getting shorter (V-bottom forming)
Background: Green shading (divergence alert)
A/D: Rising despite price falling
Volume: Increasing on down bars
Setup:
1. Divergence appears at 26,280 (green background)
2. Wait for MACD to cross signal line
3. First dark green bar appears at 26,290
4. Enter long: 26,295 (next bar open)
5. Stop: 26,265 (below divergence low)
6. Target: 26,350 (previous swing high)
Result: +55 points (30 point risk, 1.8:1 reward)
Key: Divergence + volume confirmation = high probability reversal
```
### Scenario 4: Bearish Divergence Top
```
Time: 1:45 PM
Price: Making higher highs (26,500 → 26,520 → 26,540)
MACD: Positive but flattening
Histogram: Green bars getting shorter (Λ-top forming)
Background: Red shading (bearish divergence)
A/D: Declining despite rising price
Volume: Decreasing on up bars
Setup:
1. Bearish divergence at 26,540 (red background)
2. MACD crosses below signal line
3. First dark red bar appears at 26,535
4. Enter short: 26,530
5. Stop: 26,555 (above divergence high)
6. Target: 26,475 (support level)
Result: +55 points (25 point risk, 2.2:1 reward)
Key: Distribution while price rising = smart money exiting
```
### Scenario 5: V-Bottom Reversal
```
Downtrend in progress
MACD: Deep below zero (-150)
Histogram: Series of dark red bars
Pattern Development:
Bar 1: Dark red, hist = -80, falling
Bar 2: Dark red, hist = -95, falling
Bar 3: Dark red, hist = -100, falling (extreme)
Bar 4: Light pink, hist = -98, rising!
Bar 5: Light pink, hist = -90, rising
Bar 6: Light teal, hist = -75, rising (crosses to positive momentum)
Bar 7: Dark green, hist = -55, rising + volume
Action: Enter long on Bar 7
Reason: V-bottom confirmed with volume
Stop: Below Bar 3 low
Target: Zero line on histogram (mean reversion)
```
## Best Practices
### Entry Rules
✓ **Wait for dark colors**: High-volume confirmation is key
✓ **Confirm divergences**: Use with price support/resistance
✓ **Trade with zero line**: Long above, short below for best odds
✓ **Multiple timeframes**: Align 1m, 5m, 15m signals
✓ **Watch for patterns**: V-bottoms and Λ-tops are reliable
### Exit Rules
✓ **Partial profits**: Take 50% at first target
✓ **Trail stops**: Use histogram color changes
✓ **Respect signals**: Exit on opposite dark color
✓ **Time stops**: Close positions before major news
✓ **End of day**: Square up before close
### Avoid
✗ **Don't chase light colors**: Low volume = low confidence
✗ **Don't ignore divergence**: Early warning system
✗ **Don't overtrade**: Wait for clear setups
✗ **Don't fight the trend**: Zero line dictates bias
✗ **Don't skip stops**: Always use risk management
## Risk Management
### Position Sizing
- **Dark green/red signals**: 1-2% account risk
- **Light signals**: 0.5% account risk or skip
- **Divergence plays**: 1% account risk (higher uncertainty)
- **Multiple confirmations**: Up to 2% account risk
### Stop Loss Placement
- **Trend trades**: Below/above recent swing (20-30 points typical)
- **Breakout trades**: Below/above breakout level (15-25 points)
- **Divergence trades**: Beyond divergence extreme (25-40 points)
- **Scalp trades**: Tight stops at 10-15 points
### Profit Targets
- **Minimum**: 1.5:1 reward to risk ratio
- **Scalps**: 15-25 points (quick in/out)
- **Swing**: 50-100 points (hold through pullbacks)
- **Runners**: Trail with histogram color changes
## Timeframe Recommendations
| Timeframe | Trading Style | Typical Hold | Advantages | Challenges |
|-----------|---------------|--------------|------------|------------|
| **1-minute** | Scalping | 1-5 minutes | Fast profits, many setups | Noisy, high false signals |
| **5-minute** | Intraday | 15-60 minutes | Balance of speed/clarity | Still requires quick decisions |
| **15-minute** | Swing | 1-4 hours | Clearer trends, less noise | Fewer opportunities |
| **1-hour** | Position | 4-24 hours | Strong signals, less monitoring | Wider stops required |
**Recommendation**: Start with 5-minute for best balance of signal quality and opportunity frequency.
## Combining with Other Indicators
### VMACDv3 + ACCDv3
- **Use**: Confirm volume flow with price momentum
- **Signal**: Both showing dark green = highest conviction long
- **Divergence**: VMACDv3 bullish + ACCDv3 bearish = examine price action
### VMACDv3 + RSI
- **Use**: Overbought/oversold with momentum confirmation
- **Signal**: RSI < 30 + dark green VMACD = strong reversal
- **Caution**: RSI > 70 + light green VMACD = potential false breakout
### VMACDv3 + Elder Impulse
- **Use**: Bar coloring + histogram confirmation
- **Signal**: Green Elder bars + dark green VMACD = aligned momentum
- **Exit**: Blue Elder bars + light colors = momentum stalling
## Limitations
- **Requires volume data**: Will not work on instruments without volume feed
- **Lagging indicator**: MACD inherently follows price (2-3 bar delay)
- **Consolidation noise**: Generates false signals in tight ranges
- **Gap handling**: Large gaps can distort volume-weighted values
- **Not standalone**: Should combine with price action and support/resistance
## Troubleshooting
**Problem**: Too many light colored signals
**Solution**: Increase Volume MA Length to 30-40 for stricter filtering
**Problem**: Missing entries due to waiting for dark colors
**Solution**: Lower Volume MA Length to 10-15 for more signals (accept lower quality)
**Problem**: Divergences not appearing
**Solution**: Verify volume data available; check if A/D line is calculating
**Problem**: Histogram colors not changing
**Solution**: Ensure real-time data feed; refresh indicator
## Version History
- **v3**: Removed traditional MACD, using volume-weighted MACD on price with A/D divergence
- **v2**: Added A/D divergence detection, volume strength filtering, enhanced histogram colors
- **v1**: Basic volume-weighted MACD on price
## Related Indicators
**Companion Tools**:
- **ACCDv3**: Volume-weighted MACD on A/D line (distribution focus)
- **RSIv2**: RSI with A/D divergence detection
- **DMI**: Directional Movement Index with A/D divergence
- **Elder Impulse**: Bar coloring system using volume-weighted MACD
**Use Together**: VMACDv3 (momentum) + ACCDv3 (distribution) + Elder Impulse (bar colors) = complete volume-based trading system
---
*This indicator is for educational purposes. Past performance does not guarantee future results. Always practice proper risk management and never risk more than you can afford to lose.*
Open Interest RSI [BackQuant]Open Interest RSI
A multi-venue open interest oscillator that aggregates OI across major derivatives exchanges, converts it to coin or USD terms, and runs an RSI-style engine on that aggregated OI so you can track positioning pressure, crowding, and mean reversion in leverage flows, not just in price.
What this is
This tool is an RSI built on top of aggregated open interest instead of price. It pulls futures OI from several major exchanges, converts it into a unified unit (COIN or USD), sums it into a single synthetic OI candle, then applies RSI and smoothing to that combined series.
You can then render that Open Interest RSI in different visual modes:
Clean line or colored line for classic oscillator-style reads.
Column-style oscillator for impulse and compression views.
Flag mode that fills between OI RSI and its EMA for trend/mean reversion blends. See:
Heatmap mode that paints the panel based on OI RSI extremes, ideal for scanning. See:
On top of that it includes:
Aggregated OI source selection (Binance, Bybit, OKX, Bitget, Kraken, HTX, Deribit).
Choice of OI units (COIN or USD).
Reference lines and OB/OS zones.
Extreme highlighting for either trend or mean reversion.
A vertical OI RSI meter that acts as a quick strength gauge.
Aggregated open interest source
Under the hood, the indicator builds a synthetic open interest candle by:
Looping over a list of supported exchanges: Binance, Bybit, OKX, Bitget, Kraken, HTX, Deribit.
Looping over multiple contract suffixes (such as USDT.P, USD.P, USDC.P, USD.PM) to capture different contract types on each venue.
Requesting OI candles from each venue + contract combination for the same underlying symbol.
Converting each OI stream into a common unit: In COIN mode, everything is normalized into coin-denominated OI. In USD mode, coin OI is multiplied by price to approximate notional OI.
Summing up open, high, low and close of OI across venues into a single aggregated OI candle.
If no valid OI is available for the current symbol across all sources, the script throws a clear runtime error so you know you are on an unsupported market.
This gives you a single, exchange-agnostic open interest curve instead of being tied to one venue. That aggregated OI is then passed into the RSI logic.
How the OI RSI is calculated
The RSI side is straightforward, but it is applied to the aggregated OI close:
Compute a base RSI of aggregated OI using the Calculation Period .
Apply a simple moving average of length Smoothing Period (SMA) to reduce noise in the raw OI RSI.
Optionally apply an EMA on top of the smoothed OI RSI as a moving average signal line.
Key parameters:
Calculation Period – base RSI length for OI.
Smoothing Period (SMA) – extra smoothing on the RSI value.
EMA Period – EMA length on the smoothed OI RSI.
The result is:
oi_rsi – raw RSI of aggregated OI.
oi_rsi_s – SMA-smoothed OI RSI.
ma – EMA of the smoothed OI RSI.
Thresholds and extremes
You control three core thresholds:
Mid Point – central reference level, typically 50.
Extreme Upper Threshold – high-level OI RSI edge (for example 80).
Extreme Lower Threshold – low-level OI RSI edge (for example 20).
These thresholds are used for:
Reference lines or OB/OS zone fills.
Heatmap gradient bounds.
Background highlighting of extremes.
The Extreme Highlighting mode controls how extremes are interpreted:
None – do nothing special in extreme regions.
Mean-Rev – background turns red on high OI RSI and green on low OI RSI, framing extremes as contrarian zones.
Trend – background turns green on high OI RSI and red on low OI RSI, framing extremes as participation zones aligned with the prevailing move.
Reference lines and OB/OS zones
You can choose:
None – clean plotting without guides.
Basic Reference Lines – mid, upper and lower thresholds as simple gray horizontals.
OB/OS Levels – filled zones between:
Upper OB: from the upper threshold to 100, colored with the short/overbought color.
Lower OS: from 0 to the lower threshold, colored with the long/oversold color.
These guides help visually anchor the OI RSI within "normal" versus "extreme" regions.
Plotting modes
The Plotting Type input controls how OI RSI is drawn. All modes share the same underlying OI and RSI logic, but emphasise different aspects of the signal.
1) Line mode
This is the classic oscillator representation:
Plots the smoothed OI RSI as a simple line using RSI Line Color and RSI Line Width .
Optionally plots the EMA overlay on the same panel.
Works well when you want standard RSI-style signals on leverage flows: crosses of the midline, divergences versus price, and so on.
2) Colored Line mode
In this mode:
The OI RSI is plotted as a line, but its color is dynamic.
If the smoothed OI RSI is above the mid point, it uses the Long/OB Color .
If it is below the mid point, it uses the Short/OS Color .
This creates an instant visual regime switch between "bullish positioning pressure" and "bearish positioning pressure", while retaining the feel of a traditional RSI line.
3) Oscillator mode
Oscillator mode renders OI RSI as vertical columns around the mid level:
The smoothed OI RSI is plotted as columns using plot.style_columns .
The histogram base is fixed at 50, so bars extend above and below the mid line.
Bar color is dynamic, using long or short colors depending on which side of the mid point the value sits.
This representation makes impulse and compression in OI flows more obvious. It is especially useful when you want to focus on how quickly OI RSI is expanding or contracting around its neutral level. See:
4) Flag mode
Flag mode turns OI RSI and its EMA into a two-line band with a filled area between them:
The smoothed OI RSI and its EMA are both plotted.
A fill is drawn between them.
The fill color flips between the long color and the short color depending on whether OI RSI is above or below its EMA.
Black outlines are added to both lines to make the band clear against any background.
This creates a "flag" style region where:
Green fills show OI RSI leading its EMA, suggesting positive positioning momentum.
Red fills show OI RSI trailing below its EMA, suggesting negative positioning momentum.
Crossovers of the two lines can be read as shifts in OI momentum regime.
Flag mode is useful if you want a more structural view that combines both the level and slope behaviour of OI RSI. See:
5) Heatmap mode
Heatmap mode recasts OI RSI as a single-row gradient instead of a line:
A single row at level 1 is plotted using column style.
The color is pulled from a gradient between the lower and upper thresholds: Near the lower threshold it approaches the short/oversold color and near the upper threshold it approaches the long/overbought color.
The EMA overlay and reference lines are disabled in this mode to keep the panel clean.
This is a very compact way to track OI RSI state at a glance, especially when stacking it alongside other indicators. See:
OI RSI vertical meter
Beyond the main plot, the script can draw a small "thermometer" table showing the current OI RSI position from 0 to 100:
The meter is a two-column table with a configurable number of rows.
Row colors form an inverted gradient: red at the top (100) and green at the bottom (0).
The script clamps OI RSI between 0 and 100 and maps it to a row index.
An arrow marker "▶" is drawn next to the row corresponding to the current OI RSI value.
0 and 100 labels are printed at the ends of the scale for orientation.
You control:
Show OI RSI Meter – turn the meter on or off.
OI RSI Blocks – number of vertical blocks (granularity).
OI RSI Meter Position – panel anchor (top/bottom, left/center/right).
The meter is particularly helpful if you keep the main plot in a small panel but still want an intuitive strength gauge.
How to read it as a market pressure gauge
Because this is an RSI built on aggregated open interest, its extremes and regimes speak to positioning pressure rather than price alone:
High OI RSI (near or above the upper threshold) indicates that open interest has been increasing aggressively relative to its recent history. This often coincides with crowded leverage and a buildup of directional pressure.
Low OI RSI (near or below the lower threshold) indicates aggressive de-leveraging or closing of positions, often associated with flushes, forced unwinds or post-liquidation clean-ups.
Values around the mid point indicate more balanced positioning flows.
You can combine this with price action:
Price up with rising OI RSI suggests fresh leverage joining the move, a more persistent trend.
Price up with falling OI RSI suggests shorts covering or longs taking profit, more fragile upside.
Price down with rising OI RSI suggests aggressive new shorts or levered selling.
Price down with falling OI RSI suggests de-leveraging and potential exhaustion of the move.
Trading applications
Trend confirmation on leverage flows
Use OI RSI to confirm or question a price trend:
In an uptrend, rising OI RSI with values above the mid point indicates supportive leverage flows.
In an uptrend, repeated failures to lift OI RSI above mid point or persistent weakness suggest less committed participation.
In a downtrend, strong OI RSI on the downside points to aggressive shorting.
Mean reversion in positioning
Use thresholds and the Mean-Rev highlight mode:
When OI RSI spends extended time above the upper threshold, the crowd is extended on one side. That can set up squeeze risk in the opposite direction.
When OI RSI has been pinned low, it suggests heavy de-leveraging. Once price stabilises, a re-risking phase is often not far away.
Background colours in Mean-Rev mode help visually identify these periods.
Regime mapping with plotting modes
Different plotting modes give different perspectives:
Heatmap mode for dashboard-style use where you just need to know "hot", "neutral" or "cold" on OI flows at a glance.
Oscillator mode for short term impulses and compression reads around the mid line. See:
Flag mode for blending level and trend of OI RSI into a single banded visual. See:
Settings overview
RSI group
Plotting Type – None, Line, Colored Line, Oscillator, Flag, Heatmap.
Calculation Period – base RSI length for OI.
Smoothing Period (SMA) – smoothing on RSI.
Moving Average group
Show EMA – toggle EMA overlay (not used in heatmap).
EMA Period – length of EMA on OI RSI.
EMA Color – colour of EMA line.
Thresholds group
Mid Point – central reference.
Extreme Upper Threshold and Extreme Lower Threshold – OB/OS thresholds.
Select Reference Lines – none, basic lines or OB/OS zone fills.
Extreme Highlighting – None, Mean-Rev, Trend.
Extra Plotting and UI
RSI Line Color and RSI Line Width .
Long/OB Color and Short/OS Color .
Show OI RSI Meter , OI RSI Blocks , OI RSI Meter Position .
Open Interest Source
OI Units – COIN or USD.
Exchange toggles: Binance, Bybit, OKX, Bitget, Kraken, HTX, Deribit.
Notes
This is a positioning and pressure tool, not a complete system. It:
Models aggregated futures open interest across multiple centralized exchanges.
Transforms that OI into an RSI-style oscillator for better comparability across regimes.
Offers several visual modes to match different workflows, from detailed analysis to compact dashboards.
Use it to understand how leverage and positioning are evolving behind the price, to gauge when the crowd is stretched, and to decide whether to lean with or against that pressure. Attach it to your existing signals, not in place of them.
Also, please check out @NoveltyTrade for the OI Aggregation logic & pulling the data source!
Here is the original script:
Interest Rate ExpectationsThis indicator shows how much rate cuts or hikes are currently priced into SOFR futures. You choose two SOFR contracts and the script converts each contract price into basis points relative to the current effective fed funds rate. This gives you a very clear view of how policy expectations shift over time.
You can switch between using a fixed EFFR value or pulling the live EFFR ticker. Colours for each line and label are fully adjustable. The script also includes an optional grid for the plus or minus 25, 50 and 75 basis point levels so the chart does not zoom out too far.
Labels appear at the end of both lines and display how many basis points of cuts or hikes are priced for each contract. A small reference box is added on the chart to remind you what each quarterly code represents. For example H is March and Z is December.
The background shading highlights changes in the timing of cuts. Green shading means the market is pushing cuts further out in time. Red shading means cuts are being pulled closer. This gives a simple and visual way to track how the curve reprices near term versus long term policy expectations.
This tool is useful for anyone tracking fed path repricing, front end volatility, macro catalysts or cross asset rate sensitivity.
Scalp Boost LONG✦ Overview
Scalp Boost LONG is a visual tool designed to highlight potential short-term upward impulses.
A signal is generated only when multiple market conditions align at the candle close, combining momentum dynamics, local probability shifts, and abnormal volume behavior.
The indicator does not repaint.
✦ Concept
The tool focuses on selective situations where the market shows signs of micro-breakout potential.
If all internal conditions are confirmed — a LONG event is displayed.
If not — the chart remains clean.
This builds a low-noise signal model, prioritizing quality over frequency.
✦ Signal Logic
The LONG signal requires confirmation of all core conditions:
• Local impulse dynamics
Identifies short-term acceleration suggesting a breakout from a compressed price structure.
• Probability beyond a statistical zone
Uses relative breakout probability instead of fixed levels, checking whether price exceeds expected local ranges.
• Abnormal volume activity
Highlights candles with monetary flow above a custom threshold, signaling increased market interest.
• Anti-overheat filter
Conditions avoiding exhausted or low-momentum phases where continuation is less likely.
Only when all filters are aligned a LONG marker appears.
✦ Visual Structure
The chart display is intentionally minimal:
• ROC Curve
Subdued line, showing short-term momentum without distraction.
• LONG Marker
Green triangle below the candle on confirmed events.
• Candle Highlight
Soft background highlight on the signal bar.
• Volume Marker
Small red dot at the bottom of candles with abnormal monetary flow.
All visual elements appear only on candle close.
✦ Alerts
A clean event structure is available for notifications:
LONG Signal
This allows receiving alerts during chart analysis or in automated workflows while keeping full control over decision-making.
✦ Notes & Guidelines
This tool:
is not a trading system,
does not provide targets or stops,
may trigger against the dominant trend,
should be combined with the user’s own methodology.
Signals are rare by design.
Do not interpret each event as a trend continuation — it highlights conditions, not outcomes.
✦ Suggested Use
-(Non-mandatory ideas for advanced users)
-identifying potential micro-breakouts,
-timing entries around volume spikes,
-adding context to scalping models,
-filtering impulsive moves from noise.
-suitable for a 5-minute timeframe
The indicator can be helpful as a confirmation layer, not a standalone decision tool.
BTC STH Proxy vs Realized Price (RP) Ratio | STH : LTH📊 REALIZED PRICE MARKET SIGNAL
Indicator that builds a Short-Term Holder (STH) price proxy using a configurable moving average of Bitcoin’s market price and compares it to Bitcoin’s Realized Price (RP) derived from on-chain data.
Realized Price (RP) is calculated from CoinMetrics Realized Market Cap divided by Glassnode circulating supply.
STH Proxy is a user-defined moving average (EMA/SMA/WMA) of BTC price, designed to mimic the behavior of the true STH Realized Price.
Users can adjust the MA type, length, and RP smoothing to closely replicate the STH curve seen on Glassnode, Bitbo, and Bitcoin Magazine Pro.
Optionally, the indicator can display the STH/RP ratio, which highlights transitions between market phases.
This tool provides a simple but effective way to visualize short-term vs long-term holder cost-basis dynamics using only publicly accessible on-chain aggregates and price data.
----------
💡TLDR: An alt take on the Short-Term Holder Realized Price / Long-Term Holder Realized Price cross model | (STH/LTH cross)
- A mix of MAs are used to mimic STH.
- RP here used as a proxy for the long-term holder (LTH) cost basis.
- Bull/Bear signals are generated when the STH proxy crosses above or below RP.
⭐ Free to use • Leave feedback • Happy trading!
Probability Cone█ Overview:
Probability Cone is based on the Expected Move . While Expected Move only shows the historical value band on every bar, probability panel extend the period in the future and plot a cone or curve shape of the probable range. It plots the range from bar 1 all the way to bar 31.
In this model, we assume asset price follows a log-normal distribution and the log return follows a normal distribution.
Note: Normal distribution is just an assumption; it's not the real distribution of return.
The area of probability range is based on an inverse normal cumulative distribution function. The inverse cumulative distribution gives the range of price for given input probability. People can adjust the range by adjusting the standard deviation in the settings. The probability of the entered standard deviation will be shown at the edges of the probability cone.
The shown 68% and 95% probabilities correspond to the full range between the two blue lines of the cone (68%) and the two purple lines of the cone (95%). The probabilities suggest the % of outcomes or data that are expected to lie within this range. It does not suggest the probability of reaching those price levels.
Note: All these probabilities are based on the normal distribution assumption for returns. It's the estimated probability, not the actual probability.
█ Volatility Models :
Sample SD : traditional sample standard deviation, most commonly used, use (n-1) period to adjust the bias
Parkinson : Uses High/ Low to estimate volatility, assumes continuous no gap, zero mean no drift, 5 times more efficient than Close to Close
Garman Klass : Uses OHLC volatility, zero drift, no jumps, about 7 times more efficient
Yangzhang Garman Klass Extension : Added jump calculation in Garman Klass, has the same value as Garman Klass on markets with no gaps.
about 8 x efficient
Rogers : Uses OHLC, Assume non-zero mean volatility, handles drift, does not handle jump 8 x efficient.
EWMA : Exponentially Weighted Volatility. Weight recently volatility more, more reactive volatility better in taking account of volatility autocorrelation and cluster.
YangZhang : Uses OHLC, combines Rogers and Garmand Klass, handles both drift and jump, 14 times efficient, alpha is the constant to weight rogers volatility to minimize variance.
Median absolute deviation : It's a more direct way of measuring volatility. It measures volatility without using Standard deviation. The MAD used here is adjusted to be an unbiased estimator.
You can learn more about each of the volatility models in out Historical Volatility Estimators indicator.
█ How to use
Volatility Period is the sample size for variance estimation. A longer period makes the estimation range more stable less reactive to recent price. Distribution is more significant on larger sample size. A short period makes the range more responsive to recent price. Might be better for high volatility clusters.
People usually assume the mean of returns to be zero. To be more accurate, we can consider the drift in price from calculating the geometric mean of returns. Drift happens in the long run, so short lookback periods are not recommended.
The shape of the cone will be skewed and have a directional bias when the length of mean is short. It might be more adaptive to the current price or trend, but more accurate estimation should use a longer period for the mean.
Using a short look back for mean will make the cone having a directional bias.
When we are estimating the future range for time > 1, we typically assume constant volatility and the returns to be independent and identically distributed. We scale the volatility in term of time to get future range. However, when there's autocorrelation in returns( when returns are not independent), the assumption fails to take account of this effect. Volatility scaled with autocorrelation is required when returns are not iid. We use an AR(1) model to scale the first-order autocorrelation to adjust the effect. Returns typically don't have significant autocorrelation. Adjustment for autocorrelation is not usually needed. A long length is recommended in Autocorrelation calculation.
Note: The significance of autocorrelation can be checked on an ACF indicator.
ACF
Time back settings shift the estimation period back by the input number. It's the origin of when the probability cone start to estimation it's range.
E.g., When time back = 5, the probability cone start its prediction interval estimation from 5 bars ago. So for time back = 5 , it estimates the probability range from 5 bars ago to X number of bars in the future, specified by the Forecast Period (max 1000).
█ Warnings:
People should not blindly trust the probability. They should be aware of the risk evolves by using the normal distribution assumption. The real return has skewness and high kurtosis. While skewness is not very significant, the high kurtosis should be noticed. The Real returns have much fatter tails than the normal distribution, which also makes the peak higher. This property makes the tail ranges such as range more than 2SD highly underestimate the actual range and the body such as 1 SD slightly overestimate the actual range. For ranges more than 2SD, people shouldn't trust them. They should beware of extreme events in the tails.
The uncertainty in future bars makes the range wider. The overestimate effect of the body is partly neutralized when it's extended to future bars. We encourage people who use this indicator to further investigate the Historical Volatility Estimators , Fast Autocorrelation Estimator , Expected Move and especially the Linear Moments Indicator .
The probability is only for the closing price, not wicks. It only estimates the probability of the price closing at this level, not in between.
Linear Trajectory & Volume StructureThe Linear Trajectory & Volume Structure indicator is a comprehensive trend-following system designed to identify market direction, volatility-adjusted channels, and high-probability entry points. Unlike standard Moving Averages, this tool utilizes Linear Regression logic to calculate the "best fit" trajectory of price, encased within volatility bands (ATR) to filter out market noise.
It integrates three core analytical components into a single interface:
Trend Engine: A Linear Regression Curve to determine the mean trajectory.
Volume Verification: Filters signals to ensure price movement is backed by market participation.
Market Structure: Identifies previous high-volume supply and demand zones for support and resistance analysis.
2. Core Components and Logic
The Trajectory Engine
The backbone of the system is a Linear Regression calculation. This statistical method fits a straight line through recent price data points to determine the current slope and direction.
The Baseline: Represents the "fair value" or mean trajectory of the asset.
The Cloud: Calculated using Average True Range (ATR). It expands during high volatility and contracts during consolidation.
Trend Definition:
Bullish: Price breaks above the Upper Deviation Band.
Bearish: Price breaks below the Lower Deviation Band.
Neutral/Chop: Price remains inside the cloud.
Smart Volume Filter
The indicator includes a toggleable volume filter. When enabled, the script calculates a Simple Moving Average (SMA) of the volume.
High Volume: Current volume is greater than the Volume SMA.
Signal Validation: Reversal signals and structure zones are only generated if High Volume is present, reducing the likelihood of trading false breakouts on low liquidity.
Volume Structure (Smart Liquidity)
The script automatically plots Support (Demand) and Resistance (Supply) boxes based on pivot points.
Creation: A box is drawn only if a pivot high or low is formed with High Volume (if the volume filter is active).
Mitigation: The boxes extend to the right. If price breaks through a zone, the box turns gray to indicate the level has been breached.
3. Signal Guide
Trend Reversals (Buy/Sell Labels)
These are the primary signals indicating a potential change in the macro trend.
BUY Signal: Appears when price closes above the upper volatility band after previously being in a downtrend.
SELL Signal: Appears when price closes below the lower volatility band after previously being in an uptrend.
Pullbacks (Small Circles)
These are continuation signals, useful for adding to positions or entering an existing trend.
Long Pullback: The trend is Bullish, but price dips momentarily below the baseline (into the "discount" area) and closes back above it.
Short Pullback: The trend is Bearish, but price rallies momentarily above the baseline (into the "premium" area) and closes back below it.
4. Configuration and Settings
Trend Engine Settings
Trajectory Length: The lookback period for the Linear Regression. This is the most critical setting for tuning sensitivity.
Channel Multiplier: Controls the width of the cloud.
1.0: Aggressive. Results in narrower bands and earlier signals, but more false positives.
1.5: Balanced (Default).
2.0+: Conservative. Creates a wide channel, filtering out significant noise but delaying entry signals.
Signal Logic
Show Trend Reversals: Toggles the main Buy/Sell labels.
Show Pullbacks: Toggles the re-entry circle signals.
Smart Volume Filter: If checked, signals require above-average volume. Unchecking this yields more signals but removes the volume confirmation requirement.
Volume Structure
Show Smart Liquidity: Toggles the Support/Resistance boxes.
Structure Lookback: Defines how many bars constitute a pivot. Higher numbers identify only major market structures.
Max Active Zones: Limits the number of boxes on the chart to prevent clutter.
5. Timeframe Optimization Guide
To maximize the effectiveness of the Linear Trajectory, you must adjust the Trajectory Length input based on your trading style and timeframe.
Scalping (1-Minute to 5-Minute Charts)
Recommended Length: 20 to 30
Multiplier: 1.2 to 1.5
Logic: Fast-moving markets require a shorter lookback to react quickly to micro-trend changes.
Day Trading (15-Minute to 1-Hour Charts)
Recommended Length: 55 (Default)
Multiplier: 1.5
Logic: A balance between responsiveness and noise filtering. The default setting of 55 is standard for identifying intraday sessions.
Swing Trading (4-Hour to Daily Charts)
Recommended Length: 89 to 100
Multiplier: 1.8 to 2.0
Logic: Swing trading requires filtering out intraday noise. A longer length ensures you stay in the trade during minor retracements.
6. Dashboard (HUD) Interpretation
The Head-Up Display (HUD) provides a summary of the current market state without needing to analyze the chart visually.
Bias: Displays the current trend direction (BULLISH or BEARISH).
Momentum:
ACCELERATING: Price is moving away from the baseline (strong trend).
WEAKENING: Price is compressing toward the baseline (potential consolidation or reversal).
Volume: Indicates if the current candle's volume is HIGH or LOW relative to the average.
Disclaimer
*Trading cryptocurrencies, stocks, forex, and other financial instruments involves a high level of risk and may not be suitable for all investors. This indicator is a technical analysis tool provided for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a guarantee of profit. Past performance of any trading system or methodology is not necessarily indicative of future results.
