Multi-Factor Regime Scoring & Alerts [HYPR-run]DESCRIPTION:
Composite regime scoring system that fuses eight independent market dimensions into a single normalized Regime Factor (-1 to +1). The sweet spot is the +/-0.2 zone: when the Regime Factor crosses through this zone (dim white circles on chart), the regime just shifted from one side to the other through neutral. That crossover, with the HMA-smoothed Regime Curve sloping in the same direction, is the highest-conviction entry the composite produces. The alerts are built around this: Regime Pivot fires at +/-0.25 with volatility band confirmation.
DISCOVERING EDGE
Pursuing a mechanical edge in entry/exit timing, confirmation and conviction sizing led us to developing an oscillating expression of most of the key criteria we use in building automated strategies. We discovered there is a sweet-spot for higher conviction trades in the +/-0.2 - .+/-0.3 zone. For example if a SFP presents, waiting for the REGIME Factor to enter the zone has a higher probability of trending than if taken earlier. In addition, for earlier reversion trades, XO/XU the outer most levels of +/-0.6 are excellent early entries when following a disciplined sizing methodology.
EIGHT SCORING DIMENSIONS
1. Macro Pivot (+/-10): ROC regime exhaustion into inflection
2. ROC Filter (+/-9): layered rate of change momentum states
3. ADXVMA (+/-9): adaptive trend direction with regime gradient
4. OBVIX (+/-5): on-balance volume, volatility, and trend composite
5. Convergence (+/-7): multi-timeframe alignment across 7 timeframes
6. Mean Reversion (+/-10): blow-off detection and spike revert signals
7. Levels (+/-8): positioning relative to 50d, 200d, 10w moving averages
8. Mechanical Hold (+/-5): price action hold signals with squeeze detection
Macro pivot and mean reversion (+/-10 each) are the heaviest. When both fire in the same direction, they swing the composite by nearly a third of its total range.
HOW TO USE
Add to chart, adjust ADXVMA and Turtle periods to match your setup. Read the Regime Factor, not the price. Above +0.6 = strong bullish; XO/XU these levels for early starter positions. Below -0.6 = strong bearish. The +/-0.2 zone is the sweet spot: crossovers here (dim white circles) mark high-probability entries or confirmation to other set-ups like an SFP. The Regime Curve shows the trend of the regime itself; when the curve slopes against the score, the regime is decelerating.
When the composite is ambiguous (between 0.2 and 0.6), the dashboard tells you why. Macro pivot green but ROC filter yellow = inflection detected, momentum hasn't confirmed. Convergence bright green but ADXVMA yellow = multi-TF aligned but local MA still flat.
CROSS-DIMENSIONAL READS
The power is reading 2-3 dashboard rows together:
- Macro pivot firing while ROC filter still green = earliest warning of trend exhaustion
- "Macro Lc confirmed" + convergence at +5 or higher = highest-conviction reversal entry
- ADXVMA "Early Bull" + convergence at +5 = trend birth signal
- Convergence at +7 = strongest trend confirmation AND trigger for mean reversion detection. Maximum agreement = maximum overextension risk
- "Blow-Off" + "Hodl S" = hold confirmed but reversion loading against you; tighten
- "Legit Squeeze" + "Chopperoni" + convergence +/-5 = compressed energy, directional break coming
- Regime Factor +0.7 but Curve flattening = regime decelerating; leading signal of rollover
ALERTS
Regime Pivot fires when the Regime Factor crosses +/-0.25 with volatility band confirmation; solid arrows on chart. Built around the sweet spot: fires at the regime shift, not after the move has run. Spike Revert fires on mean reversion after blow-off; counter-trend edge from extreme overextension. Toggle each independently. For notifications without webhooks: condition = this indicator, "Any alert() function call", select push/email/popup. For webhook execution: paste endpoint URL, set Open-ended, create.
REGIME FACTOR THRESHOLD ZONES
+0.6 to +1.0 strong bullish (solid green hline)
+0.2 to +0.6 moderate bullish (dotted line)
-0.2 to +0.2 sweet spot entries (dim white circles); XO/XU here
-0.6 to -0.2 moderate bearish (dotted line)
-1.0 to -0.6 strong bearish (solid red hline)
DASHBOARD (9 rows)
1. MACRO PIVOT - Green: Pivoting ↑, Lc ↗ (confirmed), L In Play ↗. Red: inverse. Black: neutral.
2. ROC FILTER - Bright Green: Momentum ↑. Green: Trending ↗ / Rolling Over ↓. Yellow: Continuation / Stage 1 / Reversion. Orange: Exhaustion. White: Sideways. Red/Bright Red: inverse.
3. ADXVMA - Green: D Trend ↗, Trending ↗, Early Bull. Yellow: Pivoting, Consolidation, Chopperoni. Red: inverse.
4. OBVIX - Green: positive. Red: negative. Black: flat.
5. CONVERGENCE - Bright Green: All Lined Up ↑ (7/7). Gradient green: +5 to +6. Dim: +3 to +4. Black: near 0. Red gradient: inverse.
6. MEAN REVERSION - Yellow: Blow-Off, High Potential, Possible. Green: Spike Revert ↑ / MR In Play ↗. Red: inverse.
7. LEVELS - Green: Bouncing key MAs, XO events. Red: Rejecting, XU events. MA combo: above/below 50d, 100d, 200d + 10w anchor.
8. MECHANICAL HOLD - Squeeze gradient: Legit Squeeze / Squeezing. Green: Hodl L. Red: Hodl S. Black: Get Ready / Neutral.
9. REGIME FACTOR - Composite score with gradient color and numeric display.
CREDITS
ADXVMA: Linnsoft
ADX: J. Welles Wilder (1978)
VIDYA: Tushar S. Chande, TASC March 1992
Advance/Decline gradient: LucF
Turtle breakout concept: Richard Donchian Indicator
AG Pro KAMA Efficiency Zones [AGPro Series]AG Pro KAMA Efficiency Zones
Overview
KAMA stands for Kaufman’s Adaptive Moving Average.
AG Pro KAMA Efficiency Zones is built around KAMA not as a simple trend-following line, but as an adaptive market reference for evaluating how efficiently price is moving. Instead of focusing only on direction, the script is designed to classify the quality of directional travel and separate cleaner movement from noisier, lower-clarity conditions.
The core idea is straightforward: markets do not move with the same quality all the time. Some phases show relatively efficient directional travel where price stays organized around an adaptive path. Other phases become mixed, unstable, or reversion-prone, where direction weakens and noise becomes more dominant. This script is designed to map those changes visually through adaptive KAMA-based zones, state labels, and a compact panel that summarizes the current condition.
This makes the tool structurally different from a basic moving average overlay. The objective is not to present KAMA as a one-line signal source. The objective is to use KAMA as the center of a state engine that helps users distinguish efficient trend phases from transitional or noisy environments.
What this script does
AG Pro KAMA Efficiency Zones evaluates price behavior around a Kaufman’s Adaptive Moving Average and organizes that behavior into visual market states. It does this by combining adaptive smoothing, slope behavior, distance from KAMA, and persistence around the KAMA path.
The result is a chart framework that can help answer questions such as:
• Is price moving in an efficient bullish or bearish path?
• Is the market entering a mixed transition phase?
• Has movement quality deteriorated into a noisier reversion-prone environment?
• Is the adaptive path becoming stronger, weaker, or less stable?
By turning those questions into zones and state-based chart feedback, the script aims to improve context rather than replace judgment.
Unique edge
The distinguishing feature of this script is that it does not treat KAMA as a standard moving average. Instead, it uses KAMA as the center of a layered efficiency model.
That model focuses on the quality of movement, not just the existence of movement.
Many tools emphasize momentum, volatility, volume pressure, or overbought/oversold conditions. This script is designed for a different purpose. It is a movement-quality map. It attempts to show whether price is traveling in a relatively efficient path or whether that path is degrading into a noisier condition where directional clarity may be weaker.
This means the script is less about predicting a move and more about classifying the environment in which a move is taking place.
How it works
The script begins with KAMA, or Kaufman’s Adaptive Moving Average. KAMA is useful because it adapts its responsiveness according to market behavior. In cleaner directional phases it can respond more quickly, while in noisier phases it can become more conservative. That makes it a practical centerline for an efficiency-based state model.
On top of KAMA, the script evaluates several components:
1. Efficiency behavior
The script measures how directly price is moving relative to its recent path. This helps estimate whether price action is acting efficiently or becoming more erratic.
2. KAMA slope behavior
The slope of KAMA is normalized so that directional angle can be evaluated in a more consistent way. Stronger and more persistent slope behavior supports higher-quality trend classifications.
3. Price-to-KAMA relationship
Price position around KAMA helps determine whether movement is aligned with the adaptive path or drifting around it without clear structure.
4. Persistence
The script also looks at how consistently price remains on one side of KAMA. That persistence can help distinguish a more stable move from a weaker and less durable one.
These components are blended into a composite efficiency model that drives the active state and the corresponding visual zone.
States and zones
The script classifies market behavior into four main states:
Efficient Bull Trend
This state reflects a comparatively organized bullish environment where price and adaptive slope are aligned in a cleaner upward path.
Efficient Bear Trend
This state reflects a comparatively organized bearish environment where price and adaptive slope are aligned in a cleaner downward path.
Transition
This is a mixed condition. Direction may be weakening, changing, or failing to achieve the quality required for an efficient trend classification.
Noise / Reversion
This state reflects lower movement quality, weaker slope behavior, or a more unstable relationship between price and the adaptive path.
The visual zone structure is designed to reinforce those classifications on the chart. Instead of using only one line, the script builds layered KAMA-centered bands so the user can read not only direction, but also how structured or fragile the current condition may be.
How to read the chart
The KAMA line is the adaptive spine of the script.
The outer and inner bands represent zone structure around that adaptive path. In stronger trend states, the script increases the visual emphasis of the KAMA path and its supporting zone layers. In weaker or more mixed conditions, the script softens those visuals and allows the chart to communicate reduced clarity.
State labels appear when the script confirms a meaningful shift in condition. These labels are intended to highlight a change in market state, not to promise a trade outcome.
The on-chart panel summarizes the active reading using fields such as State, Efficiency, Score Band, Adaptive Bias, Active Zone, and Stability. This gives the user a compact interpretation layer without requiring every decision to be made directly from raw chart inspection.
Key inputs
KAMA Efficiency Length
Controls the lookback used in the KAMA efficiency logic. Lower values react faster. Higher values smooth more noise.
KAMA Fast Response and KAMA Slow Response
Define the adaptive responsiveness range of the KAMA engine.
ATR Length
Used to normalize slope and distance so the tool behaves more consistently across different symbols and volatility conditions.
KAMA Slope Lookback
Controls how the script measures directional slope over time.
Persistence Length
Influences how much consistency price must show around KAMA before a move is treated as more structured.
Efficient Trend Threshold and Noise Threshold
These thresholds help determine when the model classifies a move as higher quality or lower quality.
Zone Band ATR Width
Adjusts the width of the adaptive visual zone.
State Hold Bars
Helps reduce rapid state flipping by requiring a condition to persist before the active state changes.
Panel Font Size and Label Size
Allow visual customization for different chart layouts and monitor sizes.
Alerts
The script includes state-oriented alerts intended to notify the user when market condition changes. These are designed around state transitions and movement-quality shifts rather than promotional “buy now” style messaging.
Examples include bullish and bearish efficiency shifts, transition detection, noise-zone detection, efficiency recovery, efficiency breakdown, and trend strengthening.
Alerts should be interpreted as contextual information. They are intended to support review and analysis, not to function as a standalone decision system.
What this script is not
This script is not a guarantee engine.
It does not predict future price with certainty.
It does not eliminate risk.
It is not a substitute for broader market structure analysis, execution planning, or risk management.
It should not be treated as a self-sufficient entry/exit system without additional confirmation and user judgment.
Limitations and transparency
All adaptive models are sensitive to parameter choices. Changing responsiveness, thresholds, smoothing, or persistence settings can materially affect the way states appear on the chart.
Because the script is state-based, some shifts will naturally occur after the earliest turning point in price. That is part of the tradeoff involved in using confirmation and persistence to reduce noise.
In highly erratic or news-driven conditions, classification can also become less stable. During those periods, transition or noise-oriented readings may occur more often, and users should interpret the visual output in that context.
The script is best viewed as an analytical framework for movement quality and adaptive context, not as a promise of directional success.
Practical use cases
Users may find the script useful for:
• separating cleaner trend phases from mixed or unstable phases
• filtering chart environments before applying another workflow
• evaluating whether direction is gaining or losing efficiency
• adding adaptive context to discretionary analysis
• comparing how different symbols behave around a KAMA-centered efficiency structure
Risk disclosure
This script is for analytical and educational use. It does not provide financial advice, investment advice, or guaranteed outcomes. Market conditions can change quickly, and any indicator can produce false, delayed, or incomplete signals. Users remain responsible for their own decisions, validation process, and risk management.
In short, AG Pro KAMA Efficiency Zones is designed to help read the quality of movement, not just the direction of movement. It uses KAMA as an adaptive reference point and converts that reference into a structured zone and state model so users can assess whether price behavior appears efficient, transitional, or noisy.
Indicator
Macro Environment Dashboard SPX/Nasdaq Levels============================================================
Macro Environment Dashboard SPX/Nasdaq Levels
This indicator aims to show an actual snapshot of the current macro situation, so you can estimate what to expect from the day.
This is a result of a long AI conversation, in order to gather market principles into a usable dashboard. Hope you find it useful.
Purpose
Provides a structured macro environment dashboard for equity index trading, combining liquidity, volatility, credit, and trend signals into a single regime framework. It automatically determines support and resistance levels, evaluates market risk conditions, and generates contextual alerts for potential breakout or breakdown events.
The tool is designed for discretionary traders, systematic traders, and macro-aware technical traders who want to align execution decisions with the prevailing macro regime.
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1. Market Principles the Script Is Based On
The indicator is built on a multi-factor macro model. It assumes that equity index behavior is primarily driven by liquidity conditions, financial stress signals, interest rates, volatility, and trend structure.
Core Principle: Markets Move With Liquidity
When liquidity expands:
* risk assets tend to rise
* volatility tends to fall
* credit conditions improve
When liquidity contracts:
* risk assets tend to weaken
* volatility tends to rise
* financial stress increases
The Model Uses Eight Core Signals
Liquidity
Measures global central bank balance sheets relative to liquidity drains.
Liquidity Delta
Measures short-term liquidity changes from funding sources.
Dollar (DXY)
A stronger dollar tightens global financial conditions.
10Y Yield
Higher yields increase discount rates and pressure equities.
Credit
Credit spreads reflect financial system health.
VIX
Market volatility represents risk perception.
SPX Trend
Trend direction of the S&P 500.
Nasdaq Trend
Trend direction of the Nasdaq index.
These signals are combined into a weighted score that determines the market regime.
Regime Model
STRONG RISK ON
High liquidity alignment and positive market conditions.
RISK ON
Supportive macro environment but not fully aligned.
NEUTRAL
Mixed signals or transitional environment.
RISK OFF
Defensive environment with elevated risk.
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2. Table Rows — All Possible Values and Meaning
Liquidity
Injection
Liquidity is expanding.
Typically bullish for equities.
Drain
Liquidity is contracting.
Typically bearish for equities.
Impact Interpretation
Injection → upward price pressure
Drain → downward price pressure
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Liq Delta
Improving
Short-term liquidity is increasing.
Deteriorating
Short-term liquidity is decreasing.
Impact Interpretation
Improving → short-term support
Deteriorating → short-term risk
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Dollar
Weak USD
Financial conditions are easing.
Strong USD
Financial conditions are tightening.
Impact Interpretation
Weak USD → risk assets supported
Strong USD → risk assets pressured
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10Y Yield
Falling
Discount rates are declining.
Rising
Discount rates are increasing.
Impact Interpretation
Falling → equities supported
Rising → equities pressured
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Credit
Healthy
Credit markets are stable.
Stress
Credit risk is increasing.
Impact Interpretation
Healthy → supportive risk environment
Stress → elevated financial risk
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VIX
Low Vol
Market risk perception is low.
High Vol
Market risk perception is elevated.
Impact Interpretation
Low Vol → stable conditions
High Vol → unstable conditions
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SPX Trend
Bullish
Short-term trend is upward.
Bearish
Short-term trend is downward.
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Nasdaq Trend
Bullish
Short-term trend is upward.
Bearish
Short-term trend is downward.
---
Selected
Bullish
The currently selected execution market trend is positive.
Bearish
The currently selected execution market trend is negative.
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Support 1
Automatically calculated key support level.
Meaning
Primary downside structure level.
Behavior
Break below support indicates potential continuation lower.
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Resistance 1
Automatically calculated key resistance level.
Meaning
Primary upside structure level.
Behavior
Break above resistance indicates potential continuation higher.
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Persistence / Risk
Confirmed
The macro regime has persisted for the required number of bars.
Pending
The regime is still forming.
Risk Layer Values
TRENDING
Directional movement is strong and sustained.
CONSOLIDATING
Market is range-bound.
UNSTABLE
Volatility expansion or elevated risk conditions.
Impact Interpretation
TRENDING
Trend continuation likely.
CONSOLIDATING
Breakout risk increasing.
UNSTABLE
Risk management priority.
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Regime / Score
Displays the macro regime and confidence percentage.
Possible Values
STRONG RISK ON
Score above 75%
RISK ON
Score between 55% and 75%
NEUTRAL
Score between 35% and 55%
RISK OFF
Score below 35%
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Glyph Symbols
▲
Bullish or supportive signal
▼
Bearish or negative signal
•
Neutral condition
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3. Settings Explanation
Auto Detect Market
Automatically determines whether the chart represents:
SPX
or
NASDAQ
If enabled
The script identifies the instrument automatically.
If disabled
Manual selection is used.
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Manual Market Override
Used only when auto detection is disabled.
Options
SPX
NASDAQ
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Fast Length
Short-term moving average period.
Used for trend detection.
Typical values
3
5
10
---
Slow Length
Longer moving average period.
Used for trend confirmation.
Typical values
15
20
30
---
Show Dashboard Table
Enables or disables the macro dashboard display.
---
Show Macro Background
Colors the chart background according to the macro regime.
Green
Risk-on environment
Orange
Neutral environment
Red
Risk-off environment
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Show Support / Resistance Levels
Displays automatically calculated levels.
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Show S/R Price Labels
Displays price labels to the right of the last bar.
Example
S1: 5120
R1: 5185
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Levels Mode
Determines how support and resistance are calculated.
Options
Swing
Uses recent highs and lows.
ATR
Uses volatility-based levels.
Pivot
Uses pivot structure detection.
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Swing Lookback 1
Short-term support/resistance window.
Typical
20
---
Swing Lookback 2
Longer-term support/resistance window.
Typical
50
---
ATR Length
Volatility measurement period.
Typical
14
---
ATR Basis Length
Moving average used as ATR center.
Typical
20
---
ATR Mult 1
Primary volatility distance.
Typical
1.0
---
ATR Mult 2
Secondary volatility distance.
Typical
2.0
---
Pivot Left Bars
Number of bars before pivot.
---
Pivot Right Bars
Number of bars after pivot.
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Regime Confirmation Bars
Number of bars required to confirm a regime.
Higher value
More stability
Less noise
Lower value
Faster signals
More sensitivity
Typical
3
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Liquidity Delta Smoothing
Smoothing factor for liquidity change signal.
Typical
3
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Liquidity Delta Lookback
Historical comparison period.
Typical
5
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Risk Layer Fast Trend
Short-term trend period.
---
Risk Layer Slow Trend
Longer trend period.
---
Risk Layer Range Length
Range measurement window.
---
Trending Threshold %
Minimum trend strength required.
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Unstable ATR % Threshold
Volatility threshold for instability detection.
---
Consolidation Range % Threshold
Range size threshold for consolidation detection.
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4. Use Cases / How To Use
Use Case 1 — Trend Continuation
Conditions
Regime
STRONG RISK ON
Risk Layer
TRENDING
Signal
Price breaks Resistance 1
Interpretation
High-probability continuation setup.
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Use Case 2 — Breakdown Risk
Conditions
Regime
RISK OFF
Risk Layer
UNSTABLE
Signal
Price breaks Support 1
Interpretation
Downside continuation likely.
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Use Case 3 — Range Trading
Conditions
Risk Layer
CONSOLIDATING
Signal
Price moves between Support and Resistance.
Interpretation
Mean-reversion environment.
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Use Case 4 — Early Risk Warning
Conditions
Liquidity
Drain
Credit
Stress
VIX
High Vol
Interpretation
Elevated systemic risk.
Risk management priority.
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Use Case 5 — Regime Transition
Conditions
Regime
Pending
Interpretation
Market environment changing.
Wait for confirmation.
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Best Practices
Use the indicator for:
Context
Risk management
Trade confirmation
Market regime identification
Do not use it as:
A standalone entry signal
A prediction tool
A guarantee of market direction
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Indicator
Phantom Whale Hunter [JOAT]Phantom Whale Hunter
Introduction
The Phantom Whale Hunter is an advanced open-source institutional footprint tracking system that combines Chaikin Money Flow, Money Flow Index, On-Balance Volume, VWAP analysis, and Accumulation/Distribution to detect institutional buying and selling pressure. This indicator reveals when large institutional players (whales) are accumulating or distributing positions, providing traders with insights into smart money positioning before major price moves occur.
Unlike basic volume indicators, the Phantom Whale Hunter provides multi-dimensional institutional flow analysis through money flow calculations, volume-weighted analysis, cumulative volume tracking, and phase detection. The indicator is designed for traders who understand that institutional money moves markets and that detecting whale footprints early provides significant trading advantages.
Why This Indicator Exists
This indicator addresses the need for systematic institutional flow analysis. By combining five distinct money flow methodologies with phase detection, it reveals:
Chaikin Money Flow (CMF): Measures buying/selling pressure based on close position within range
Money Flow Index (MFI): Volume-weighted RSI showing money flow strength
On-Balance Volume (OBV): Cumulative volume indicator tracking institutional accumulation/distribution
VWAP Analysis: Volume-weighted average price with deviation bands
Accumulation/Distribution (A/D): Cumulative indicator measuring money flow into/out of security
Institutional Flow Index: Composite measure combining all five components
Phase Detection: Classifies market as Strong Accumulation, Accumulation, Neutral, Distribution, or Strong Distribution
Smart Money Divergence: Detects when price and flow move in opposite directions
Core Components Explained
1. Chaikin Money Flow (CMF)
CMF measures the relationship between close position and volume:
Money Flow Volume: ((Close - Low) - (High - Close)) / (High - Low) × Volume
CMF Calculation: Sum of MFV over period / Sum of volume over period
CMF Smoothing: 7-period EMA for noise reduction
Interpretation: CMF > 0 = buying pressure, CMF < 0 = selling pressure
CMF values above +0.1 indicate strong buying pressure, while values below -0.1 indicate strong selling pressure.
2. Money Flow Index (MFI)
MFI is a volume-weighted momentum indicator:
Typical Price: (High + Low + Close) / 3
Raw Money Flow: Typical Price × Volume
Positive Flow: Money flow when typical price rises
Negative Flow: Money flow when typical price falls
Money Ratio: Sum of positive flow / Sum of negative flow
MFI: 100 - (100 / (1 + Money Ratio))
MFI above 80 indicates overbought with high volume (potential distribution), while MFI below 20 indicates oversold with high volume (potential accumulation).
3. On-Balance Volume (OBV)
OBV tracks cumulative volume flow:
Calculation: Add volume on up days, subtract volume on down days
Cumulative: Running total from start of data
Normalization: Scaled to 0-100 range using 100-bar high/low
Zero-Centering: Subtract 50 for composite integration
Rising OBV with rising price confirms uptrend (accumulation). Falling OBV with rising price warns of distribution.
4. VWAP (Volume-Weighted Average Price)
VWAP calculates the average price weighted by volume:
Calculation: Sum(Typical Price × Volume) / Sum(Volume)
Daily Reset: VWAP resets at start of each trading day
Standard Deviation: Measures price dispersion from VWAP
Deviation Bands: VWAP ± (StdDev × Multiplier)
Price vs VWAP: Percentage distance from VWAP
Price above VWAP indicates bullish institutional positioning. Price below VWAP indicates bearish institutional positioning. Large deviations often mean-revert.
5. Accumulation/Distribution (A/D) Line
A/D measures cumulative money flow:
Money Flow Multiplier: ((Close - Low) - (High - Close)) / (High - Low)
Money Flow Volume: Multiplier × Volume
A/D Line: Cumulative sum of money flow volume
Smoothing: EMA smoothing (default 14) for trend identification
Normalization: Scaled to 0-100 range, then zero-centered
Rising A/D with rising price confirms accumulation. Falling A/D with rising price signals distribution (bearish divergence).
6. Institutional Flow Index Calculation
All five components are combined into a unified flow index:
Flow Index = (CMF × 50 + (MFI - 50) + (OBV - 50) + (A/D - 50)) / 4
This composite index ranges from approximately -50 to +50, with:
Flow Index > 30 = Strong institutional buying
Flow Index > 10 = Institutional buying
Flow Index -10 to +10 = Neutral/balanced
Flow Index < -10 = Institutional selling
Flow Index < -30 = Strong institutional selling
7. Phase Detection System
The indicator classifies institutional positioning into five phases:
Strong Accumulation (Phase 2): Flow Index > 30, CMF > 0.1, MFI > 50
Accumulation (Phase 1): Flow Index > 10, CMF > 0
Neutral (Phase 0): Flow Index between -10 and +10
Distribution (Phase -1): Flow Index < -10, CMF < 0
Strong Distribution (Phase -2): Flow Index < -30, CMF < -0.1, MFI < 50
Phase classification helps identify when institutions are actively positioning.
8. Smart Money Divergence Detection
Divergences occur when price and flow move in opposite directions:
Price Momentum: 14-period rate of change in price
Flow Momentum: 14-period rate of change in Flow Index
Bullish Divergence: Price falling (momentum < 0), Flow rising (momentum > 0)
Bearish Divergence: Price rising (momentum > 0), Flow falling (momentum < 0)
Smart money divergences indicate institutions positioning against current price trend, often preceding reversals.
9. Institutional Pressure Detection
The indicator identifies strong institutional buying/selling:
Buy Pressure: CMF > 0, MFI > 50, OBV > 50, Volume Surge
Sell Pressure: CMF < 0, MFI < 50, OBV < 50, Volume Surge
Volume Surge: Current volume > average volume × 2.25
Anti-Overlap: Minimum 25 bars between pressure signals
Institutional pressure with volume confirmation indicates significant whale activity.
10. Flow Velocity and Acceleration
The indicator tracks flow momentum:
Flow Velocity: Change in Flow Index (first derivative)
Flow Acceleration: Change in velocity (second derivative)
Accelerating flow indicates increasing institutional participation. Decelerating flow warns of waning institutional interest.
Visual Elements
Institutional Flow Line: Main line showing composite flow with phase-based coloring (green = accumulation, red = distribution, yellow = neutral)
Component Lines: Four thin lines showing CMF, MFI, OBV, and A/D (all normalized)
Zero Line: Horizontal line at zero
Threshold Lines: Dashed lines at +30 (strong accumulation), +10 (accumulation), -10 (distribution), -30 (strong distribution)
Zone Fills: Shaded areas above +30 (green) and below -30 (red)
Volume Surge Background: Purple background when volume surges occur
Smart Money Divergence Circles: Small circles marking divergence points
Institutional Pressure Triangles: Triangles marking strong buy/sell pressure
Flow Velocity Histogram: Shows rate of change in flow
Information Dashboard: Displays phase, flow index, CMF, MFI, OBV, A/D, volume ratio, price vs VWAP, flow velocity, and signal status
How to Use This Indicator
Step 1: Check Current Phase
Monitor the dashboard for institutional phase (Strong Accumulation, Accumulation, Neutral, Distribution, Strong Distribution).
Step 2: Analyze Flow Index
Flow Index > 20 = institutional buying, Flow Index < -20 = institutional selling. Trade in direction of institutional flow.
Step 3: Confirm with Components
Check CMF, MFI, OBV, and A/D for confirmation. All four positive = strongest accumulation signal.
Step 4: Monitor Volume Ratio
Volume surges (> 2x average) with positive flow confirm institutional buying. Volume surges with negative flow confirm institutional selling.
Step 5: Check Price vs VWAP
Price above VWAP with positive flow = bullish institutional positioning. Price below VWAP with negative flow = bearish institutional positioning.
Step 6: Watch for Smart Money Divergences
Divergences at extreme flow levels often precede reversals. Purple circles mark these critical points.
Step 7: Look for Institutional Pressure
Triangles mark strong institutional buy/sell pressure with volume confirmation. These are high-probability signals.
Best Practices
Trade in direction of institutional phase - don't fight whale positioning
Wait for Strong Accumulation/Distribution phases for highest conviction
Confirm flow signals with volume surges - flow without volume may be weak
Use smart money divergences as early reversal warnings
Monitor flow velocity - accelerating flow indicates increasing institutional participation
Combine with price action and support/resistance for entry timing
Be patient - institutional accumulation/distribution can take time
Use higher timeframe flow for stronger significance
Input Parameters
Chaikin Money Flow:
CMF Length: Period for CMF calculation (default: 20)
Money Flow Index:
MFI Length: Period for MFI calculation (default: 14)
MFI Overbought: Threshold for overbought (default: 80)
MFI Oversold: Threshold for oversold (default: 20)
Volume Configuration:
Volume MA Length: Period for average volume (default: 20)
Surge Threshold: Multiplier for volume surges (default: 2.0x)
Show Volume Profile: Toggle volume display (default: enabled)
VWAP Analysis:
VWAP Std Dev: Standard deviation multiplier (default: 2.0)
Accumulation/Distribution:
A/D Smoothing: EMA smoothing period (default: 14)
Phase Threshold: Threshold for phase classification (default: 0.5)
Visual Configuration:
Accumulation/Distribution/Neutral/Smart Money Colors: Customizable colors
Originality Statement
This indicator is original in its comprehensive institutional flow approach. While individual components (CMF, MFI, OBV, VWAP, A/D) are established concepts, this indicator is justified because:
It combines five distinct money flow methodologies into a unified institutional flow index
The phase detection system classifies institutional positioning systematically
Smart money divergence detection identifies when institutions position against price
Institutional pressure detection with volume confirmation reveals whale activity
Flow velocity and acceleration tracking predict institutional momentum changes
Integration of VWAP analysis provides institutional price positioning context
The comprehensive dashboard presents all institutional flow metrics simultaneously
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Trading involves substantial risk of loss. Institutional flow analysis does not guarantee profitable trades. Whale activity does not guarantee price direction. Always use proper risk management and never risk more than you can afford to lose.
-Made with passion by officialjackofalltrades Indicator
Turbulence Fractal Scanner [JOAT]Turbulence Fractal Scanner
Introduction
The Turbulence Fractal Scanner is an advanced open-source volatility chaos prediction engine that combines ATR, Bollinger Band Width, Keltner Channels, Historical Volatility, and Squeeze detection into a unified volatility analysis system. This indicator measures market turbulence across multiple dimensions, creating a comprehensive volatility index that reveals expansion/contraction cycles, squeeze conditions, and breakout predictions.
Unlike single-dimension volatility indicators, the Turbulence Fractal Scanner provides multi-layered volatility intelligence through percentile ranking, composite indexing, regime classification, and squeeze detection. The indicator is designed for traders who understand that volatility precedes price movement and that multi-dimensional volatility analysis provides early warning of significant market shifts.
Why This Indicator Exists
This indicator addresses the need for comprehensive volatility analysis that goes beyond simple ATR or Bollinger Bands. By combining five distinct volatility methodologies, it reveals:
ATR Analysis: Average True Range measures actual price movement volatility
Bollinger Band Width: Measures price dispersion relative to moving average
Keltner Channels: ATR-based bands for volatility envelope detection
Historical Volatility: Statistical measure of price returns volatility
Squeeze Detection: Identifies when Bollinger Bands contract inside Keltner Channels
Composite Volatility Index: Unified measure combining all five components
Regime Classification: Categorizes volatility as Low, Normal, High, or Squeeze
Breakout Prediction: Detects squeeze breakouts with directional bias
Core Components Explained
1. ATR (Average True Range) Analysis
ATR measures the average range of price movement:
True Range: Maximum of (high - low), (high - previous close), (previous close - low)
ATR Calculation: Moving average of true range over period (default 14)
ATR Smoothing: Additional EMA smoothing (default 7) reduces noise
ATR Percent: ATR divided by close, expressed as percentage
ATR Percentile: ATR ranked against 100-bar history (0-100 scale)
ATR percentile shows whether current volatility is high or low relative to recent history. High percentile (> 70) indicates elevated volatility, low percentile (< 30) indicates compressed volatility.
2. Bollinger Band Width Analysis
BB Width measures price dispersion:
Bollinger Bands: SMA ± (standard deviation × multiplier)
BB Width: (Upper band - Lower band) / Middle band × 100
BB Width Percentile: Current width ranked against 100-bar history
Narrow BB Width indicates low volatility and potential breakout setup. Wide BB Width indicates high volatility and potential mean reversion.
3. Keltner Channel Analysis
Keltner Channels use ATR for volatility bands:
Basis: EMA of close (default 20 periods)
Range: ATR × multiplier (default 1.5)
Upper/Lower: Basis ± Range
Keltner Channels adapt to volatility changes and are used in squeeze detection.
4. Squeeze Detection
Squeeze occurs when Bollinger Bands contract inside Keltner Channels:
Squeeze On: BB Lower > KC Lower AND BB Upper < KC Upper
Squeeze Off: Bands no longer contracted
Squeeze Breakout: Transition from Squeeze On to Squeeze Off
Breakout Direction: Determined by close comparison (close > close = bullish)
Squeezes indicate extreme volatility compression. Breakouts from squeezes often lead to significant directional moves.
5. Historical Volatility (HV) Calculation
HV measures statistical volatility of returns:
Returns: Logarithmic price changes (log(close / close ))
Standard Deviation: StdDev of returns over period (default 20)
Annualization: Multiply by sqrt(252) for annual volatility (optional)
HV Percentile: Current HV ranked against 100-bar history
HV provides a statistical measure of actual price volatility, complementing the technical measures (ATR, BB Width).
6. Composite Volatility Index
All three percentile measures are combined into a unified index:
Volatility Index = (ATR Percentile + BB Width Percentile + HV Percentile) / 3
This composite index provides a balanced view of volatility across multiple methodologies. Values range from 0 (extremely low volatility) to 100 (extremely high volatility).
7. Volatility Regime Classification
The indicator classifies volatility into four regimes:
Squeeze (Priority): When squeeze is active, regardless of volatility index
Low Volatility: Volatility Index < threshold (default 30)
Normal Volatility: Volatility Index between low and high thresholds (30-70)
High Volatility: Volatility Index > threshold (default 70)
Regime classification helps traders adapt strategies to current volatility conditions.
8. Volatility Trend Analysis
The indicator tracks volatility direction:
Volatility Trend: 5-period SMA of Volatility Index
Rising Volatility: Trend rising for 3+ consecutive bars
Falling Volatility: Trend falling for 3+ consecutive bars
Expansion: Volatility Index rising for 3+ consecutive bars
Contraction: Volatility Index falling for 3+ consecutive bars
Volatility trends help predict whether turbulence is increasing or decreasing.
9. Breakout Prediction System
The indicator predicts breakouts from squeeze conditions:
Squeeze Breakout: Detected when squeeze transitions from On to Off
Direction: Bullish if close > close , bearish if close < close
Volatility Confirmation: Best breakouts occur when Volatility Index < 40 (compressed)
Breakouts from low volatility squeezes often lead to sustained directional moves.
10. Turbulence Shift Detection
The indicator identifies regime changes:
Regime Shift: When volatility regime changes (Low ↔ Normal ↔ High ↔ Squeeze)
Anti-Overlap: Minimum 10 bars between shift signals
High Vol Entry: Shift into High Volatility regime
Low Vol Entry: Shift into Low Volatility regime
Regime shifts provide early warning of changing market conditions.
Visual Elements
Volatility Index Line: Main line showing composite volatility with regime-based coloring (purple = squeeze, red = high, cyan = low, yellow = normal)
Component Lines: Three thin lines showing ATR, BB Width, and HV percentiles
Volatility Trend Line: Step-line showing smoothed volatility trend
Threshold Lines: Horizontal lines at high (70) and low (30) thresholds, plus median (50)
Zone Fills: Shaded areas above high threshold (red) and below low threshold (cyan)
Squeeze Background: Purple background when squeeze is active
Breakout Signals: Triangles marking squeeze breakouts (cyan = bullish, red/orange = bearish)
Regime Shift Circles: Small circles marking regime transitions
Information Dashboard: Displays regime, volatility index, ATR/BB/HV percentiles, squeeze status, volatility trend, expansion/contraction, breakout status, ATR/BB values, and overall signal
How to Use This Indicator
Step 1: Check Volatility Regime
Monitor the dashboard for current regime (Squeeze, Low Vol, Normal, High Vol). Adapt strategy to regime.
Step 2: Monitor Volatility Index
Volatility Index < 30 = compressed (potential breakout setup)
Volatility Index > 70 = elevated (potential mean reversion or continuation)
Step 3: Watch for Squeeze Conditions
Purple background indicates squeeze. Prepare for breakout when squeeze ends.
Step 4: Identify Breakout Direction
When squeeze breakout occurs, triangle color shows direction (cyan = bullish, red = bearish).
Step 5: Check Volatility Trend
Rising volatility = increasing turbulence, falling volatility = calming conditions.
Step 6: Monitor Expansion/Contraction
Expanding volatility often precedes strong moves. Contracting volatility suggests consolidation.
Step 7: Use Regime Shifts as Alerts
Shifts into High Vol or Low Vol regimes provide early warning of changing conditions.
Best Practices
Trade breakouts from squeeze conditions with low volatility index (< 40)
Avoid trend-following strategies in high volatility regimes (> 70)
Use low volatility regimes (< 30) to prepare for breakout setups
Monitor all three components (ATR, BB, HV) for confirmation
Rising volatility in low regime warns of impending breakout
Falling volatility in high regime suggests consolidation ahead
Combine with trend indicators - volatility shows when, trend shows direction
Be cautious of false breakouts - wait for volatility confirmation
Input Parameters
ATR Configuration:
ATR Length: Period for ATR calculation (default: 14)
ATR Smoothing: EMA smoothing period (default: 7)
Bollinger Bands:
BB Length: Period for BB calculation (default: 20)
BB Multiplier: Standard deviation multiplier (default: 2.0)
Keltner Channels:
KC Length: Period for KC basis (default: 20)
KC Multiplier: ATR multiplier for bands (default: 1.5)
Historical Volatility:
HV Length: Period for HV calculation (default: 20)
Annualize HV: Convert to annual volatility (default: enabled)
Regime Thresholds:
Low Volatility: Threshold for low regime (default: 30)
High Volatility: Threshold for high regime (default: 70)
Visual Configuration:
Low/Normal/High/Squeeze Colors: Customizable regime colors
Originality Statement
This indicator is original in its comprehensive volatility analysis approach. While individual components (ATR, BB, KC, HV, Squeeze) are established concepts, this indicator is justified because:
It combines five distinct volatility methodologies into a unified composite index
Percentile ranking normalizes all components to a common 0-100 scale
The regime classification system categorizes volatility conditions systematically
Squeeze detection with breakout prediction provides actionable trading signals
Volatility trend and expansion/contraction analysis predict volatility direction
Turbulence shift detection identifies regime changes early
The comprehensive dashboard presents all volatility dimensions simultaneously
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Trading involves substantial risk of loss. Volatility analysis does not guarantee profitable trades. Low volatility does not guarantee breakouts. High volatility does not guarantee reversals. Always use proper risk management and never risk more than you can afford to lose.
-Made with passion by officialjackofalltrades Indicator
ROC Regime Filter [HYPR-run]DESCRIPTION:
A reliable universal regime filter across all assets, all timeframes. Rate of change filter that classifies price action into regime states. A suite of smoothed EMAs feeds a layered ROC engine that detects when fast momentum aligns with, or diverges from, slow structure. The filter measures; it doesn't predict. When all ROC layers stack in the same direction (parallel alignment), the trend is confirmed by arithmetic. When fast ROC diverges from slow, the regime shifts. The lag is the cost of certainty. Sweet spot is 1hr to 1D; lower timeframes get noisy.
DISCOVERING EDGE
In order to gain a persistent, mechanical edge in which trades are permitted and which are filtered out, we explored a more meaningful expression of regime classification using layered multiple ROC periods to detect when fast momentum aligns with or diverges from slow structure. This resilient regime filter has been the backbone for our automated strategies since 2021.
LAYERED ROC vs SINGLE-INDICATOR REGIME
A single RSI or ADX reading flattens the market into binary (trending/not trending). Layered ROC alignment separates six distinct states, each with different permissible trade types, so the filter matches the complexity of what the market is actually doing. Six regime states gate every decision; the combination of regime color + ROC slope is the trade filter, not either one alone. Phase transitions (green to yellow, orange to green) are the actionable signals; static states just confirm what's already happening. Webhook alerts fire on macro pivots (accumulation/distribution inflections) at the regime transition, not after the move has run.
FEATURES
- Six regime states from layered ROC alignment (see color legend below)
- Early trend detection when all layers accelerate in parallel
- ROC 200 line with regime-colored gradient fill
- Macro pivot detection: strong trend exhausting into sideways, scored by where ROC 200 sits relative to its all-time range
- Accumulation/distribution context in dashboard
- ROC 200 pivot high/low divergence markers on main chart
- Consolidation markers with conviction scoring (normal vs extreme)
- Gradient candle overlay (ROC Sticks; toggle on/off)
- Two-row dashboard: row 1 = macro context (accumulation/distribution), row 2 = current regime state with directional qualifier and slope
- Dashboard dark/light theme toggle for any chart background
- Full ROC stack in data window for manual analysis
- Webhook alerts on macro pivots (accumulation/distribution)
HOW IT WORKS
ROC alignment is the core signal. When all layers stack in the same direction, that's strong trend territory (green). When fast ROC diverges from the slower layers while slow structure still holds, the engine reclassifies from strong trend to sideways (yellow), flagging a pullback rather than trend failure. Deeper corrections where intermediate layers fall below the structural anchor fire orange, indicating a correction within the primary trend. Macro pivots fire at the inflection: strong trend exhausting into sideways for the first time. The consolidation score layers this with where ROC 200 sits in its all-time range. Consolidation at extreme ROC readings (bright green/red dots) is the highest-conviction signal for reversal.
HOW TO USE
Read the regime color, not the price. Green = strong trend long, red = strong trend short, orange = deeper correction, yellow = short pullback, white = directionless. Use regimes as a directional gate: longs during green, shorts during red. Yellow flags a pullback within trend; wait for resolution back to green/red before re-entering. Orange is a deeper correction; patience or fade with confirmation from other tools. The highest-edge signals come from regime transitions, not static states. Watch for: green breaking into yellow (macro pivot, potential reversal), extended yellow resolving back to green (continuation re-entry), and the ROC slope within a regime (slope rising in orange = trend about to resume). The data window shows the full ROC stack across all layers. When fast ROC diverges from slow, that signals continuation or reversion.
MACRO CONTEXT (Dashboard Row 1)
REGIME COLOR LEGEND (Dashboard Row 2)
ALERTS
Macro pivot long fires when accumulation is detected (bull inflection). Macro pivot short fires when distribution is detected (bear inflection). Create alert: condition = this indicator, "Any alert() function call". Paste your webhook URL, set Open-ended, create. Alert payload is built into the script; works with any webhook receiver.
CREDITS
Advance/Decline gradient function: LucF Indicator
Velocity Spectrum Analyzer [JOAT]Velocity Spectrum Analyzer
Introduction
The Velocity Spectrum Analyzer is an advanced open-source momentum wave system that combines Munich Wave methodology with ALMA enhancement and multi-basis momentum tracking. This indicator analyzes momentum across five distinct velocity layers, creating a spectrum of momentum waves that reveal trend strength, regime shifts, and momentum alignment across multiple timeframes.
Unlike single-line momentum indicators, the Velocity Spectrum Analyzer provides multi-dimensional momentum analysis through layered EMA calculations, ALMA enhancement, regime classification, and spread analysis. The indicator is designed for traders who understand that momentum flows in waves and that multi-layer alignment signals institutional conviction.
Why This Indicator Exists
This indicator addresses the need for multi-dimensional momentum analysis. By combining five momentum layers with ALMA enhancement and regime detection, it reveals:
Five Velocity Layers: Fast (9), Medium (21), Slow (55), Very Slow (100), and Ultra Slow (200) EMAs create a momentum spectrum
ALMA Enhancement: Arnaud Legoux Moving Average provides adaptive smoothing with reduced lag
Basis Calculations: Averages between EMA layers create intermediate momentum levels
Regime Classification: Extreme Bull/Bear detection using Bollinger-style bands
Spread Analysis: Distance between fast and slow layers measures momentum strength
Wave State Detection: All layers bullish or bearish signals strong directional momentum
Background Coloring: Visual regime indication shows extreme conditions
Core Components Explained
1. Core Momentum Calculation
The indicator starts with basic momentum (current close minus close N bars ago), then applies ALMA for adaptive smoothing:
The ALMA offset (default 0.85) and sigma (default 6) parameters control the balance between responsiveness and smoothness. Higher offset values shift the average toward recent prices, while higher sigma values increase smoothness.
2. Five EMA Layers
Five EMAs are calculated on the momentum values:
Fast EMA (9): Captures short-term momentum shifts
Medium EMA (21): Tracks intermediate momentum trends
Slow EMA (55): Identifies primary momentum direction
Very Slow EMA (100): Reveals long-term momentum bias
Ultra Slow EMA (200): Shows institutional momentum positioning
Each layer responds at different speeds, creating a spectrum of momentum perspectives.
3. Basis Calculations
Five basis levels are calculated as averages between EMA layers:
Basis 1: Average of Fast and Medium EMAs
Basis 2: Average of Medium and Slow EMAs
Basis 3: Average of Slow and Very Slow EMAs
Basis 4: Average of Very Slow and Ultra Slow EMAs
Basis 5: Average of Ultra Slow and Fast EMAs (wraps around)
These basis levels create intermediate momentum zones that smooth transitions between layers.
4. Trend Classification Functions
Two functions classify momentum direction:
Growing: Momentum > basis (bullish momentum)
Falling: Momentum <= basis AND momentum <= ALMA (bearish momentum)
Each basis is classified independently, creating five separate momentum assessments.
5. Regime Detection with Bollinger-Style Bands
The indicator calculates bands around the average of all five basis levels:
Origin: SMA of basis average (default 25 periods)
Deviation: Standard deviation multiplied by factor (default 6.0)
Top Band: Origin + deviation (extreme bullish threshold)
Bottom Band: Origin - deviation (extreme bearish threshold)
When basis 1 and ALMA both exceed the top band with rising momentum, the indicator signals extreme bullish conditions. When both fall below the bottom band with falling momentum, it signals extreme bearish conditions.
6. Mean Range Calculation
A long-term mean range (default 415 bars) tracks the highest and lowest basis average values. The center of this range serves as a reference point for ALMA positioning. When ALMA is above the center mean with all layers bullish, strong upward momentum is confirmed.
7. Wave State Analysis
The indicator tracks when all five basis levels are simultaneously bullish or bearish:
All Bullish: All five basis levels show growing momentum - strong uptrend
All Bearish: All five basis levels show falling momentum - strong downtrend
Mixed: Some layers bullish, some bearish - transitional or choppy conditions
Wave state alignment indicates institutional conviction across all momentum timeframes.
8. Spread Calculation
The spread between Basis 1 (fastest) and Basis 5 (slowest) measures momentum divergence:
Positive Spread (> 10): Fast momentum exceeds slow momentum - bullish acceleration
Negative Spread (< -10): Fast momentum below slow momentum - bearish acceleration
Extreme Spread (> 20 or < -20): Very strong momentum divergence - potential exhaustion
Large spreads indicate strong directional momentum, while narrowing spreads warn of momentum loss.
Visual Elements
Five Velocity Layer Lines: Thick colored lines showing each basis level with dynamic coloring (cyan = bullish, yellow = bearish, white = neutral)
ALMA Enhanced Line: Separate line showing ALMA-adjusted momentum with tri-color scheme
Wave State Line: Zero line colored based on overall wave state
Background Regime: Red background for extreme bull, green background for extreme bear
Information Dashboard: Displays wave state, regime, spread, ALMA position, momentum value, layer alignment, and signal status
Signal Generation
The indicator generates four types of signals:
Lean Short: Bearish crossover with falling Basis 1 and 2, spread <= -10
Maybe Buy: Bearish crossover with falling Basis 1 and 2, extreme bear regime, spread <= -20 (oversold)
Lean Long: Bullish crossover with growing Basis 1 and 2, spread >= 10
Maybe Sell: Bullish crossover with growing Basis 1 and 2, extreme bull regime, spread >= 20 (overbought)
Additional signals:
All Aqua: All layers bullish for 4+ consecutive bars - strong uptrend confirmation
All Yellow: All layers bearish for 4+ consecutive bars - strong downtrend confirmation
How to Use This Indicator
Step 1: Check Wave State
Monitor the dashboard for wave state (All Bullish, All Bearish, or Mixed). Trade in the direction of wave state alignment.
Step 2: Analyze Regime
Watch for extreme bull/bear regimes (red/green backgrounds). These often precede reversals or strong continuation moves.
Step 3: Monitor Spread
Large spreads (> 20 or < -20) indicate strong momentum but potential exhaustion. Narrowing spreads warn of momentum loss.
Step 4: Check ALMA Position
ALMA above center mean with bullish layers confirms uptrend. ALMA below center mean with bearish layers confirms downtrend.
Step 5: Count Layer Alignment
The dashboard shows how many layers are bullish (X/5). 5/5 bullish = strongest uptrend, 0/5 bullish = strongest downtrend.
Step 6: Wait for Signal Confirmation
Lean Long/Short signals work best when wave state aligns. Maybe Buy/Sell signals at extremes offer reversal opportunities.
Best Practices
Trade with wave state alignment, not against it
Use extreme regimes as reversal warnings, not continuation signals
Monitor spread for momentum strength - large spreads indicate strong trends
Wait for all layers to align (5/5) before taking aggressive positions
Use Maybe Buy/Sell signals only at extreme regimes with high spread
Combine with price action - momentum shows intent, price shows result
Be cautious when layers are mixed (2/5 or 3/5) - indicates choppy conditions
Watch for spread narrowing as early warning of trend exhaustion
Input Parameters
Momentum Engine:
Source: Price input (default: close)
Momentum Length: Period for momentum calculation (default: 21)
ALMA Offset: Offset parameter for ALMA (default: 0.85)
ALMA Sigma: Sigma parameter for ALMA (default: 6)
Momentum Layers:
Fast EMA: Short-term momentum (default: 9)
Medium EMA: Intermediate momentum (default: 21)
Slow EMA: Primary momentum (default: 55)
Very Slow EMA: Long-term momentum (default: 100)
Ultra Slow EMA: Institutional momentum (default: 200)
Regime Classification:
Mean Lookback: Period for mean range (default: 415)
StdDev Length: Period for standard deviation (default: 25)
StdDev Multiplier: Band width multiplier (default: 6.0)
Background Offset: Shift background display (default: 0)
Visual Configuration:
Bullish Color: Color for bullish momentum (default: cyan)
Bearish Color: Color for bearish momentum (default: yellow)
Neutral Color: Color for neutral momentum (default: white)
Enable Alerts: Toggle alert conditions (default: enabled)
Originality Statement
This indicator is original in its multi-layer momentum approach. While individual components (EMAs, ALMA, momentum) are established concepts, this indicator is justified because:
It combines five distinct momentum layers into a unified spectrum analysis
The basis calculation system creates intermediate momentum zones between layers
ALMA enhancement provides adaptive smoothing with reduced lag
Regime detection using Bollinger-style bands on basis average identifies extremes
Wave state analysis tracks alignment across all five layers simultaneously
Spread calculation measures momentum divergence between fast and slow layers
The comprehensive dashboard presents all momentum dimensions simultaneously
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Trading involves substantial risk of loss. Momentum analysis does not guarantee profitable trades. Past momentum patterns do not guarantee future results. Always use proper risk management and never risk more than you can afford to lose.
-Made with passion by officialjackofalltrades Indicator
Rolling KPSS Statistic [LuxAlgo]The Rolling KPSS Statistic indicator evaluates the stationarity of price action within a rolling window using the Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test. This tool helps traders identify whether the current market environment is ranging, trending, or undergoing a structural regime shift by providing a continuous statistical measure of mean reversion.
🔶 USAGE
The indicator is designed to distinguish between stationary price action (where price fluctuates around a mean or trend) and non-stationary price action (where price exhibits random walk or breakout behavior). By applying a rolling window calculation, it provides a real-time assessment of market stability.
The script offers two primary modes of operation tailored to different market conditions:
🔹 Level Mode
This mode tests for stationarity around a constant mean. It is the optimal setting for detecting ranging or mean-reverting environments. When the KPSS statistic is low in this mode, it suggests the market is staying within a defined horizontal corridor.
🔹 Trend Mode
This mode tests for stationarity around a linear trend. It is used to identify if the market is moving consistently within a trending channel. A low KPSS value here indicates that while the price is moving up or down, it is doing so in a mathematically stable "stationary" trend rather than an erratic or parabolic one.
🔶 DETAILS
The KPSS test operates on the null hypothesis that the series is stationary. Unlike other unit root tests (like the Augmented Dickey-Fuller test), a low value in KPSS indicates stationarity, while a high value suggests the presence of a unit root (non-stationarity).
🔹 Critical Levels
The indicator plots three significance thresholds: 10%, 5%, and 1%.
KPSS < 5% Level: The market is considered stationary. In "Level" mode, this implies a Range. In "Trend" mode, this implies a stable Trend.
KPSS > 5% Level: The null hypothesis is rejected. The market is "Non-Stationary," suggesting a breakout, a trend reversal, or a transition into a random walk state.
KPSS > 1% Level: This indicates a highly significant deviation from stationarity, often seen during impulsive market expansions.
🔹 Visual Feedback
The indicator uses a Viridis gradient theme. Brighter colors (yellow/green) represent stationary, mean-reverting behavior, while darker colors (purple/blue) represent non-stationary or trending behavior. A real-time dashboard is also included to provide an immediate summary of the current market state.
🔶 SETTINGS
🔹 Main Settings
Window Length: The number of bars used for the rolling window. The default of 100 provides a balanced statistical lookback for most timeframes.
Source: The price data used for the calculation (default is Close).
Test Type: Select between "Level" (for ranges) or "Trend" (for trending stationarity).
Newey-West Bandwidth: A lag truncation parameter used to account for serial correlation in the residuals.
🔹 Visuals & Dashboard
Show Critical Levels: Toggles the visibility of the 10%, 5%, and 1% dashed lines.
Dashboard: Enables or disables the on-screen information table.
Position/Size: Controls the location and scale of the dashboard on the chart.
Indicator
Smart Money vs Retail OscWhat This Indicator Does-
The Smart Money vs Retail Oscillator tries to answer one question on every bar: who is controlling price right now — institutions or retail traders? It does this by splitting volume into directional flows, smoothing them at two different speeds, and plotting the difference as two lines. When those lines cross, it signals a potential shift in control.
The Core Idea: Two Speeds of Volume-
The entire indicator is built on one insight — institutions and retail traders behave differently in volume.
Smart Money (institutions) acts fast. When a large fund decides to accumulate or distribute, it moves volume in sharp, decisive bursts. A short EMA captures this.
Retail traders act slow. They chase price, react to news, and pile in after a move is already underway. A long EMA captures this lag.
By measuring the same thing (directional volume bias) at two different speeds, the gap between the two lines reveals who is leading the current move.
Step 1 — Volume Decomposition
Every bar's volume is classified as either bullish or bearish based on whether the candle closed up or down. This is a simplified but effective proxy — a green candle's volume is attributed to buyers, a red candle's to sellers. There is no partial split; each bar is fully assigned to one side.
Step 2 — The Two Oscillators
Smart Money (Yellow Line):
Uses a 7-period EMA. The result is a ratio between -1 and +1 — positive when bulls dominate short-term volume, negative when bears do. The division by total EMA normalizes for overall volume level, so a high-volume session doesn't automatically appear more bullish.
Retail (Purple Line):
Uses a 21-period EMA — exactly 3× slower. By the time this line shifts, the smart money line has already reacted and often reversed. The gap between them, both in timing and direction, is the signal.
Step 3 — Normalization to a 0–3 Scale
Raw ratios are hard to read visually and vary across instruments. Both lines are normalised using a 100-bar rolling window:
Yellow line (SM) is scaled to the full 0–3 range — it swings freely from bottom to top, showing extremes clearly. A reading near 3.0 means SM volume is as bullish as it has been in the last 100 bars. Near 0.0 means maximum bearishness.
Purple line (RT) is compressed to 0.8–2.2 — it never reaches the extremes. This is intentional. Retail sentiment is naturally more stable and mean-reverting. Compressing it into the middle band means:
When yellow is above purple, SM is more bullish than retail → institutions are leading bulls
When yellow is below purple, SM is more bearish than retail → institutions are leading bears
When they overlap, neither side has conviction
Step 4 — The Crossover Signals (Triangles)
This is the primary output most traders use.
Green triangle (▲) — Yellow crosses above purple. Smart Money volume bias has overtaken Retail volume bias. Institutions are now leading to the upside. This tends to appear before a price move rather than during it, because SM acts faster.
Red triangle (▼) — Yellow crosses below purple. Smart Money has flipped bearish relative to Retail. Institutions are now leading to the downside, or distributing into retail buying.
The threshold (sig_thresh, default 0.15) is the minimum gap between the two lines at the moment of crossing. This filters out tangential crosses where the lines barely graze each other and immediately reverse — those are noise, not signals. Set it lower (toward 0.01) and nearly every crossing will produce a triangle. Set it higher (toward 0.20) and only strong, decisive crossovers fire.
The threshold doesn't affect when a cross happens — it only decides whether that cross is significant enough to plot.
Step 5 — Regime Detection
pinereg_label =
adx > 22 and vol_ratio > 1.1 ? "TREND" :
vol_ratio > 1.8 and adx < 22 ? "MANIP" :
adx < 14 and vol_ratio < 0.85 ? "CHOP" :
adx < 18 and vol_ratio < 0.95 ? "RANGE" : "TREND"
The regime classifies the type of market you're in, using two inputs:
ADX (14) — measures trend strength, not direction. High ADX = strong trend. Low ADX = directionless.
Vol ratio — current bar's volume vs its 14-bar SMA. Greater than 1.0 = above-average volume.
Label Meaning Implication for signals TREND ADX > 22, volume elevated Crossover signals are most reliable here RANGE ADX < 18, volume low Signals work but moves are shallower CHOP ADX very low, volume very low Both lines oscillate randomly — treat signals with caution MANIP(manipulation) Volume spike but ADX low Large volume without directional conviction — often stop hunts or news spikes. Most unreliable.
Step 6 — Control State
This is a real-time label derived directly from the gap between the two lines right now (not just at crossovers). It answers: who is currently in control, even between crossover signals?
SMART — yellow is meaningfully above purple. Institutions have the upper hand.
RETAIL — purple is meaningfully above yellow. Retail sentiment is dominating, often a sign of late-stage moves.
BALANCE — the lines are within threshold of each other. No clear dominance — a crossover may be imminent.
Step 7 — Trend Bias
A simple EMA 20/50 crossover on price (not volume). This gives the indicator directional context — the table shows BUY or SELL to indicate which side the medium-term price trend favors. It doesn't suppress signals but helps you decide which crossover signals to act on: buy triangles in a BUY regime, sell triangles in a SELL regime.
Step 8 — Status (EXIT Detection)
ta.cross fires on any crossing (both over and under). When it fires, STS flips to EXIT for that bar, flagging that a position entered on the previous signal may now want to be closed. This also triggers the pink background band (alongside high-volume bars), making exit zones visually obvious on the chart.
Step 9 — Pink Background Bands
The fuchsia/pink background appears in two situations:
Volume spike — the bar's volume is more than 1.8× its average. These bars often mark institutional entries, reversals, or trap moves. Worth watching regardless of the line positions.
Line crossover — any cross between yellow and purple. Confirms the triangle signal visually at the bar level, making the transition easy to spot even without looking at the triangle markers.
How to Read It in Practice?
Bullish setup: Yellow line is below purple → starts rising → crosses above purple → green triangle appears → CTRL flips to SMART → TREND shows BUY → REG shows TREND. All four aligned = high-conviction long signal.
Bearish setup: Yellow line is above purple → starts falling → crosses below purple → red triangle appears → CTRL flips to RETAIL (retail is now leading, SM has stepped back) → TREND shows SELL → REG shows TREND. All four aligned = high-conviction short signal.
Exit: A pink band appears on a crossover bar — STS flips to EXIT. This is the indicator telling you the dynamic between SM and Retail has shifted, and the reason you entered the trade may no longer be valid.
Ignore: REG shows MANIP and a triangle fires. Volume spiked but ADX is low — likely a stop hunt or news-driven move with no follow-through. The indicator will still draw the triangle, but the regime label is your warning to stay out.
Disclaimer: This indicator is for educational purposes only. Always practice proper risk management and combine with your own analysis before making trading decisions. Happy trading.
Indicator
Indicator
Regime Classifier [JOAT]Regime Classifier
Introduction
The Regime Classifier is a sophisticated market state detection system designed to identify and classify market conditions into distinct operational regimes. Understanding the current market regime is perhaps the most critical factor in successful trading - a strategy that works beautifully in a trending market will fail miserably in a ranging market, and vice versa. This indicator solves that fundamental problem by providing clear, actionable classification of market states, allowing traders to adapt their approach to current conditions.
This tool is built for traders who understand that markets are not random but move through distinct phases, each requiring different strategies and risk management approaches. Whether you're a systematic trader needing regime filters, a discretionary trader seeking market context, or a portfolio manager adjusting exposure, this classifier provides the institutional-grade market intelligence needed to navigate any market environment successfully.
Why This Indicator Exists
Most traders apply the same strategy regardless of market conditions, then wonder why their performance is inconsistent. This indicator addresses that critical flaw by:
Regime Classification: Identifies four distinct market states with clear characteristics
Regime Strength: Measures how strongly the market exhibits regime characteristics
Regime Persistence: Tracks how long the current regime has been in place
Regime Quality: Evaluates the reliability of the current regime classification
Session Awareness: Considers session context for regime analysis
Regime Transitions: Detects and signals regime changes for strategy adaptation
The classifier transforms the complex, often subjective process of market analysis into an objective, systematic framework that can be consistently applied across all instruments and timeframes.
Core Components Explained
1. ADX-Based Trend Detection
The Average Directional Index (ADX) is the primary tool for trend detection:
// ADX calculation
float atr_val = ta.rma(ta.tr(true), i_adx_period)
float up_move = high - high
float down_move = low - low
float plus_dm = up_move > down_move and up_move > 0 ? up_move : 0
float minus_dm = down_move > up_move and down_move > 0 ? down_move : 0
float plus_di = 100 * ta.rma(plus_dm, i_adx_period) / atr_val
float minus_di = 100 * ta.rma(minus_dm, i_adx_period) / atr_val
float adx = 100 * ta.rma(math.abs(plus_di - minus_di) / (plus_di + minus_di), i_adx_period)
ADX components:
ADX Value: Trend strength (0-100), regardless of direction
+DI: Bullish directional movement
-DI: Bearish directional movement
Trend Threshold: Minimum ADX for trend classification (default 25)
Directional Bias: +DI vs -DI for trend direction
ADX above 25 indicates a trending market, while below 25 suggests ranging or volatile conditions.
2. ATR-Based Volatility Analysis
The Average True Range (ATR) measures volatility and helps distinguish between different non-trending states:
// ATR analysis
float atr_current = ta.atr(i_atr_period)
float atr_average = ta.sma(atr_current, i_atr_period * 3)
float atr_ratio = atr_average > 0 ? atr_current / atr_average : 1.0
// Volatility thresholds
float expansion_threshold = i_atr_expansion_mult
float contraction_threshold = i_atr_contraction_mult
ATR components:
Current ATR: Recent volatility measurement
Average ATR: Long-term volatility baseline
ATR Ratio: Current volatility relative to average
Expansion Threshold: Ratio indicating high volatility (default 1.4)
Contraction Threshold: Ratio indicating low volatility (default 0.6)
ATR analysis helps distinguish between ranging (low volatility) and volatile (high volatility) markets when ADX is below the trend threshold.
3. Regime Classification Logic
The indicator classifies markets into four distinct regimes:
// Regime classification
int market_regime = 0
if adx >= i_adx_trend
market_regime := 1 // Trending
else if atr_ratio >= expansion_threshold and adx < i_adx_trend
market_regime := 3 // Volatile
else if atr_ratio <= contraction_threshold and adx < i_adx_trend
market_regime := 2 // Ranging
else
market_regime := 0 // Neutral
Regime types:
Trending (ADX ≥ 25): Strong directional movement with clear trend
Ranging (ADX < 25, ATR ratio ≤ 0.6): Low volatility, sideways movement
Volatile (ADX < 25, ATR ratio ≥ 1.4): High volatility, erratic movement
Neutral (ADX < 25, 0.6 < ATR ratio < 1.4): Transition between defined states
Each regime has distinct characteristics that require different trading approaches.
4. Regime Strength Measurement
Not all regimes are created equal - some are stronger and more reliable than others:
// Regime strength calculation
float regime_strength = 0.0
switch market_regime
1 => regime_strength := math.min(adx / 50.0 * 100, 100) // Trending strength
2 => regime_strength := math.min((1 - atr_ratio) / (1 - contraction_threshold) * 100, 100) // Ranging strength
3 => regime_strength := math.min((atr_ratio - 1) / (expansion_threshold - 1) * 100, 100) // Volatile strength
0 => regime_strength := 50.0 // Neutral default
Strength interpretation:
Trending Strength: Based on ADX value (higher ADX = stronger trend)
Ranging Strength: Based on how low volatility is (lower ATR = stronger range)
Volatile Strength: Based on how high volatility is (higher ATR = stronger volatility)
Neutral Strength: Fixed at 50% as baseline
Strength Range: 0-100% indicating regime confidence
Higher strength values indicate more reliable regime classification.
5. Regime Persistence Analysis
The duration of a regime provides additional context about its reliability:
// Regime persistence tracking
var int regime_bars = 0
var int regime_start_bar = 0
if market_regime == market_regime
regime_bars := regime_bars + 1
else
regime_bars := 1
regime_start_bar := bar_index
// Persistence score
float persistence_score = math.min(float(regime_bars) / i_persistence_lookback * 100, 100)
Persistence features:
Regime Bars: Number of consecutive bars in current regime
Regime Start: When the current regime began
Persistence Score: Normalized duration (0-100%)
Lookback Period: Reference period for normalization (default 50)
Mature Regimes: Higher persistence indicates established conditions
Long-lasting regimes are more reliable than newly formed ones.
6. Regime Quality Assessment
Quality evaluates how well the current market fits the regime characteristics:
// Quality assessment
float quality_score = 0.0
float adx_quality = adx / 50.0 * 50 // 50% weight
float atr_quality = market_regime == 2 ? (1 - atr_ratio) / (1 - contraction_threshold) * 50 :
market_regime == 3 ? (atr_ratio - 1) / (expansion_threshold - 1) * 50 : 25
quality_score := adx_quality + atr_quality
Quality components:
ADX Quality: How well trend strength matches regime expectations
ATR Quality: How well volatility matches regime expectations
Quality Score: Combined assessment (0-100%)
High Quality: Clear regime characteristics
Low Quality: Ambiguous or transitioning conditions
High quality scores indicate clear, unambiguous market conditions.
7. Session Context Integration
Market behavior varies significantly across trading sessions:
// Session analysis
bool asian_session = time(timeframe.period, "0000-0800")
bool london_session = time(timeframe.period, "0700-1600")
bool ny_session = time(timeframe.period, "1200-2100")
// Session-specific adjustments
float session_multiplier = 1.0
if london_session
session_multiplier := 1.2 // Higher volatility expected
else if asian_session
session_multiplier := 0.8 // Lower volatility expected
Session features:
Session Detection: Identifies major trading sessions
Session Multipliers: Adjusts expectations based on session characteristics
Session Persistence: Tracks regime duration within current session
Session Quality: Evaluates regime quality within session context
Session Transitions: Identifies regime changes at session opens/closes
Session context helps interpret regime changes and anticipate behavior.
Visual Elements
Regime Histogram: Color-coded bars showing current regime
Strength Meter: Visual representation of regime strength
Persistence Line: Shows regime duration over time
Quality Gauge: Quality score visualization
Background Colors: Regime-based background shading
Session Markers: Visual session boundaries
Dashboard: Real-time regime metrics
Transition Alerts: Visual regime change notifications
The dashboard displays:
1. Current market regime and confidence
2. Regime strength and persistence
3. Quality score and trend direction
4. Session context and behavior
5. Regime history and transitions
6. Recommended strategies for current regime
7. Risk management adjustments
8. Regime forecast based on patterns
Input Parameters
ADX Settings:
ADX Period: Trend strength calculation (default: 14)
Trend Threshold: Minimum ADX for trend regime (default: 25)
ADX Smoothing: Additional smoothing for ADX (default: 3)
ATR Settings:
ATR Period: Volatility calculation (default: 14)
Expansion Multiplier: High volatility threshold (default: 1.4)
Contraction Multiplier: Low volatility threshold (default: 0.6)
Analysis Settings:
Persistence Lookback: Reference for persistence score (default: 50)
Quality Smoothing: Smoothing for quality calculation (default: 5)
Session Awareness: Enable session analysis (default: true)
Visual Settings:
Color Scheme: Customizable regime colors
Background Shading: Enable regime backgrounds
Dashboard Display: Show metrics panel
Alert Settings: Configure regime change alerts
How to Use This Indicator
Step 1: Identify Current Regime
Check the dashboard for the current market regime. Each regime requires a different approach:
Trending: Use trend-following strategies, let winners run
Ranging: Use mean-reversion strategies, take profits at levels
Volatile: Reduce position size, use wider stops, or avoid trading
Neutral: Wait for clarity, reduce trading activity
Step 2: Assess Regime Strength
Higher strength indicates more reliable conditions. In strong regimes (80%+), you can be more aggressive with position sizing. In weak regimes (<50%), reduce exposure and wait for confirmation.
Step 3: Monitor Persistence
Newly formed regimes (<10 bars) may be false signals. Mature regimes (>20 bars) are more established and reliable. Consider regime persistence in your strategy selection.
Step 4: Evaluate Quality
High quality scores (>75%) indicate clear market conditions. Low quality scores (<50%) suggest ambiguity - reduce trading or wait for clarity.
Step 5: Consider Session Context
Regimes that persist across multiple sessions are more significant. Regime changes at session opens often set the tone for the session.
Step 6: Watch for Transitions
Regime transitions signal strategy changes. A shift from trending to ranging requires switching from trend-following to range-bound strategies.
Best Practices
Always adapt your strategy to the current regime - don't use a trending strategy in ranging markets
High strength + high quality = maximum confidence in regime classification
Low persistence regimes (<10 bars) may be false - wait for confirmation
Session transitions often trigger regime changes - be alert at session opens
Volatile regimes are dangerous for most traders - consider reducing activity
Regime persistence is key - the longer a regime persists, the more reliable it is
Quality scores below 50% suggest waiting for clarity
Combine regime analysis with your existing strategy for better results
Keep a regime journal to track how each instrument behaves in different regimes
Use regime transitions as signals to adjust your entire trading approach
Strategy Applications by Regime
Trending Regime:
Trend-following strategies (moving averages, ADX, momentum)
Let winners run to maximum targets
Use trailing stops to capture extended moves
Add to positions on pullbacks in trend direction
Higher position sizing due to clear direction
Ranging Regime:
Mean-reversion strategies (RSI, Stochastic, Bollinger Bands)
Take profits at support/resistance levels
Use fixed targets - don't let winners turn into losers
Fade extreme moves toward the range middle
Smaller position sizing due to limited moves
Volatile Regime:
Reduce position size significantly (50% or less)
Use wider stops to avoid premature exits
Consider sitting out until conditions improve
Focus on volatility breakout patterns if trading
Quick profit taking - volatile conditions reverse quickly
Neutral Regime:
Wait for clarity before taking new positions
Manage existing positions more actively
Reduce trading frequency
Look for regime transition signals
Focus on longer timeframe analysis for direction
Technical Implementation
Built with Pine Script v6 featuring:
Advanced ADX calculation with directional movement analysis
Multi-timeframe ATR analysis for volatility assessment
Regime classification with confirmation logic
Strength, persistence, and quality scoring systems
Session awareness with timezone handling
Comprehensive visualization with multiple display modes
Real-time dashboard with 10 key metrics
Alert conditions for regime changes and thresholds
Export functions for strategy integration
Historical regime tracking and pattern recognition
The code uses confirmed bars for all calculations to prevent repainting and ensure reliable regime classification.
Originality Statement
This indicator is original in its comprehensive approach to regime classification and market state analysis. While ADX and ATR are established tools, this indicator is justified because:
It synthesizes trend and volatility analysis into a unified regime classification system
The strength, persistence, and quality scoring provides multi-dimensional regime assessment
Session awareness adds critical context often missing from regime analysis
Regime transition detection helps traders adapt strategy changes proactively
The four-regime classification (Trending, Ranging, Volatile, Neutral) covers all market states
Quality assessment helps distinguish between clear and ambiguous market conditions
Persistence analysis identifies mature, reliable regimes versus new, potentially false ones
Comprehensive visualization makes complex regime analysis accessible and actionable
Export functions enable regime-based strategy filtering and adaptation
Each component provides unique insights: ADX shows trend, ATR shows volatility, strength shows conviction, persistence shows duration, and quality shows clarity
The indicator's value lies in transforming the abstract concept of "market conditions" into concrete, actionable classifications that traders can use to adapt their strategies systematically and consistently.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Regime classification is a tool for understanding market conditions, not a prediction system.
Market regimes can change suddenly due to news events, economic data, or changes in market structure. Past regime behavior does not guarantee future patterns. The indicator's classifications are mathematical calculations based on historical patterns and should be used in conjunction with other forms of analysis.
Always use proper risk management, including stop losses and position sizing appropriate for current market conditions. Different regimes require different risk approaches - volatile regimes may require smaller positions and wider stops.
The author is not responsible for any losses incurred from using this indicator. Users assume full responsibility for all trading decisions made using this system.
-Made with passion by officialjackofalltrades
Indicator
Adaptive Volatility Matrix [JOAT]Adaptive Volatility Matrix
Introduction
The Adaptive Volatility Matrix (AVM) is an advanced open-source volatility regime classification indicator that combines Bollinger Band Width Percentile (BBWP), ATR percentile analysis, regime transition prediction, volatility clustering detection, and historical regime statistics to classify market conditions into distinct volatility regimes. This indicator helps traders adapt their strategies to current market conditions by systematically identifying when volatility is expanding, contracting, or transitioning between regimes.
Unlike basic volatility indicators that simply plot ATR or Bollinger Bands, AVM employs a sophisticated dual-metric system that combines BBWP (measuring price range compression/expansion) with ATR percentile (measuring absolute volatility) to create a combined volatility score (0-100%). The indicator then classifies this score into five distinct regimes and predicts regime transitions through momentum analysis.
Why This Indicator Exists
This indicator addresses the challenge of adapting trading strategies to volatility conditions. Different market regimes require different approaches - mean reversion works in low volatility, breakout strategies work in expansion, and risk management becomes critical in extreme volatility. AVM systematically reveals:
BBWP Analysis: Measures Bollinger Band width percentile to identify compression/expansion cycles
ATR Percentile: Tracks normalized ATR percentile to measure absolute volatility levels
Combined Volatility Score: Weighted average (60% BBWP, 40% ATR) for robust regime classification
Regime Classification: Five distinct regimes (Extreme Expansion, Expansion, Normal, Contraction, Extreme Contraction)
Transition Prediction: Momentum-based forecasting of next regime with probability
Volatility Clustering: Detects sustained high/low volatility periods
Historical Statistics: Tracks regime duration and frequency for context
Each component provides unique intelligence. BBWP shows compression cycles, ATR shows absolute volatility, combined score provides robust classification, regime system categorizes conditions, transition prediction anticipates changes, clustering detects persistence, and statistics provide historical context.
Core Components Explained
1. BBWP (Bollinger Band Width Percentile) Calculation
BBWP measures where current Bollinger Band width ranks relative to historical width:
f_calculate_bbwp(int length, int lookback) =>
float basis = ta.sma(close, length)
float dev = ta.stdev(close, length)
float bb_width = (dev * 2) / basis * 100
// Calculate percentile rank
int count = 0
for i = 1 to lookback
if bb_width > nz(bb_width )
count += 1
float bbwp = (count / lookback) * 100
BBWP ranges from 0-100%:
- 0-20%: Extreme compression (volatility squeeze)
- 20-40%: Contraction (below average volatility)
- 40-60%: Normal (average volatility)
- 60-80%: Expansion (above average volatility)
- 80-100%: Extreme expansion (volatility breakout)
2. ATR Percentile Analysis
ATR percentile measures where current normalized ATR ranks historically:
f_atr_percentile(int period, int lookback) =>
float atr_val = ta.atr(period)
float natr = close > 0 ? (atr_val / close) * 100 : 0.0
float percentile = ta.percentrank(natr, lookback)
Normalized ATR (NATR) accounts for price level differences, making volatility comparable across different price ranges. Percentile ranking shows where current volatility sits in historical distribution.
3. Combined Volatility Score & Regime Classification
The combined score weights BBWP more heavily than ATR percentile:
float combined_score = (bbwp_value * 0.6) + (atr_percentile * 0.4)
f_classify_regime(float bbwp_val, float atr_perc, float exp_th, float con_th, float ext_th) =>
string regime = "Normal"
int regime_code = 0
if bbwp_val >= ext_th or atr_perc >= ext_th
regime := "Extreme Expansion"
regime_code := 4
else if bbwp_val >= exp_th or atr_perc >= exp_th
regime := "Expansion"
regime_code := 3
// Additional classifications...
Five regime classifications:
1. Extreme Contraction (code 1): Both metrics <30%, volatility squeeze
2. Contraction (code 2): One metric <40%, below average volatility
3. Normal (code 0): Both metrics 40-60%, average conditions
4. Expansion (code 3): One metric >70%, above average volatility
5. Extreme Expansion (code 4): Both metrics >85%, volatility breakout
4. Regime Transition Prediction
AVM predicts next regime through momentum analysis:
float regime_momentum = combined_score - combined_score
string momentum_direction = regime_momentum > 2 ? "Accelerating" :
regime_momentum < -2 ? "Decelerating" : "Stable"
string predicted_regime = regime_code == 4 and regime_momentum < -5 ? "→ Expansion" :
regime_code == 3 and regime_momentum < -3 ? "→ Normal" :
// Additional predictions...
"Stable"
float transition_prob = math.min(math.abs(regime_momentum) * 10, 100)
Transition probability (0-100%) based on momentum magnitude. >50% probability triggers warning.
5. Volatility Clustering Detection
Clustering identifies sustained high/low volatility periods:
int cluster_lookback = 20
float cluster_threshold = 70.0
int high_vol_count = 0
for i = 0 to cluster_lookback - 1
if combined_score >= cluster_threshold
high_vol_count += 1
float cluster_ratio = high_vol_count / cluster_lookback * 100
bool in_vol_cluster = cluster_ratio >= 60 // 60% of bars are high vol
string cluster_strength = cluster_ratio >= 80 ? "Strong" :
cluster_ratio >= 60 ? "Moderate" :
cluster_ratio >= 40 ? "Weak" : "None"
Clusters indicate persistent volatility conditions that tend to continue.
6. Historical Regime Statistics
AVM tracks regime history for context:
var array regime_history = array.new_int(0)
var array regime_durations = array.new_int(0)
if regime_changed
array.push(regime_history, regime_code)
array.push(regime_durations, bars_in_regime)
// Calculate statistics
float avg_expansion_duration = exp_sum / exp_cnt
float avg_contraction_duration = con_sum / con_cnt
float duration_ratio = bars_in_regime / avg_expansion_duration
bool regime_extended = duration_ratio > 1.5
Statistics show if current regime is extended (>1.5x average duration), suggesting potential transition.
Visual Elements
Combined Score Line: Main plot (0-100%) with regime-based coloring
ATR Percentile Overlay: Circles showing ATR percentile for comparison
Histogram: Gradient-colored bars showing volatility score with regime colors
Reference Lines: 70% (expansion), 50% (neutral), 30% (contraction), 85% (extreme)
Background Zones: Regime-colored backgrounds (purple for expansion, yellow for contraction)
Transition Warnings: ⚠ symbols when transition probability >50%
BBWP Percentile Bands: 20th, 50th, 80th percentile circles for context
Dashboard: Real-time metrics including regime, score, BBWP, ATR%, trend, duration, momentum, transition prediction, cluster status, duration ratio, historical stats
Input Parameters
BBWP Parameters:
BBWP Length: Bollinger Band period (default: 13)
BBWP Lookback: Historical comparison period (default: 252)
ATR Analysis:
ATR Period: ATR calculation period (default: 14)
ATR Percentile Lookback: Historical ranking period (default: 100)
Regime Classification:
Expansion Threshold: Score for expansion regime (default: 70%)
Contraction Threshold: Score for contraction regime (default: 30%)
Extreme Threshold: Score for extreme regimes (default: 85%)
Visualization:
Show Regime Zones: Toggle background coloring
Show Histogram: Toggle volatility histogram
Show ATR Overlay: Toggle ATR percentile circles
How to Use This Indicator
Step 1: Identify Current Regime
Check dashboard "Regime" row. Adjust strategy based on classification.
Step 2: Monitor Combined Score
Score >70% = expansion (use breakout strategies)
Score <30% = contraction (use mean reversion)
Score 40-60% = normal (use balanced approach)
Step 3: Check Momentum Direction
"Accelerating" = volatility increasing
"Decelerating" = volatility decreasing
"Stable" = no significant change
Step 4: Watch for Transition Warnings
⚠ symbols indicate >50% probability of regime change. Prepare to adjust strategy.
Step 5: Assess Cluster Status
"Strong" or "Moderate" cluster = persistent conditions likely to continue
Step 6: Consider Duration Ratio
Ratio >1.5x = extended regime, higher probability of mean reversion
Best Practices
Use regime classification to select appropriate trading strategies
Extreme contraction often precedes volatility breakouts - prepare for expansion
Extreme expansion often mean-reverts - reduce position sizes
Transition warnings provide early signal to adjust risk management
Volatility clusters suggest persistence - don't fight the regime
Extended regimes (>1.5x average) have higher reversal probability
BBWP and ATR percentile divergence suggests regime uncertainty
Historical statistics provide context for current regime duration
Combine with directional indicators - AVM shows conditions, not direction
Indicator Limitations
Regime classification is backward-looking - transitions lag actual changes
BBWP calculation is computationally intensive on large lookback periods
Transition predictions are probabilistic, not deterministic
Extreme regimes can persist longer than expected during major events
Historical statistics require sufficient data (50+ regime changes)
Clustering detection has fixed lookback - may miss longer-term patterns
Combined score weighting (60/40) may not be optimal for all instruments
Regime thresholds may need adjustment for different markets
Technical Implementation
Built with Pine Script v6 using:
Custom BBWP calculation with percentile ranking
ATR percentile analysis with normalized ATR
Weighted combined score (60% BBWP, 40% ATR)
Five-tier regime classification system
Momentum-based transition prediction with probability
Volatility clustering detection (20-bar lookback)
Historical regime tracking with arrays (last 50 regimes)
Duration ratio calculation vs historical averages
BBWP percentile bands (20th, 50th, 80th)
Adaptive background coloring based on regime and duration
Comprehensive dashboard with 12 metrics
The code is fully open-source and can be modified to suit individual trading styles.
Originality Statement
This indicator is original in its comprehensive volatility regime classification approach. While BBWP and ATR are established concepts, this indicator is justified because:
It combines BBWP and ATR percentile into weighted combined score for robust classification
The five-tier regime system provides granular volatility categorization
Momentum-based transition prediction with probability quantification is unique
Volatility clustering detection identifies persistent regime conditions
Historical regime statistics provide context for current regime duration
Duration ratio calculation identifies extended regimes with mean reversion potential
BBWP percentile bands add additional context layers
Adaptive background intensity based on regime stability
Each component contributes unique information: BBWP shows compression cycles, ATR shows absolute volatility, combined score provides robust classification, regime system categorizes conditions, transition prediction anticipates changes, clustering detects persistence, statistics provide context, and duration ratio identifies extremes. The indicator's value lies in presenting these complementary perspectives simultaneously with unified regime framework.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Regime classifications do not guarantee future volatility behavior. Trading involves substantial risk of loss. Past performance does not guarantee future results. Always use proper risk management and never risk more than you can afford to lose.
-Made with passion by officialjackofalltrades Indicator
Crypto Derivatives Dashboard v1█ OVERVIEW
Crypto Derivatives Dashboard is a non-overlay indicator that analyzes futures market positioning data (Open Interest and Premium Index) to classify the current market regime and detect structural divergences between price action and derivatives flow.
It does NOT generate entry/exit signals. Instead, it provides a contextual layer to help you understand WHAT the derivatives market is doing — so you can decide whether to act on your primary strategy signals or wait.
█ WHAT IT MEASURES
1. OPEN INTEREST (OI)
• Daily OI change (%) — bars show inflow/outflow of contracts
• OI Z-Score — normalized deviation from its moving average (SMA 20)
• OI Rate of Change — momentum of OI over a configurable lookback
2. PREMIUM INDEX (Funding Proxy)
• Fetched from Binance PREMIUM tickers (hourly resolution)
• Converted to Z-Score to identify extremes:
→ Z > +2.0 = "Funding Hot" — overcrowded longs, correction risk
→ Z < -2.0 = "Funding Cold" — potential short squeeze setup
3. OI-PRICE DIVERGENCE
• Compares normalized ROC of OI vs Price
• Bearish divergence: price rises but OI doesn't follow (exhaustion)
• Bullish divergence: OI rises faster than price (accumulation)
4. REGIME CLASSIFICATION
Based on OI trend vs Price trend:
🟢 OI↑ + Price↑ = Healthy Trend (genuine demand)
🟡 OI↓ + Price↑ = Short Covering / Exhaustion (caution)
🔴 OI↑ + Price↓ = Shorts Building (avoid longs)
🟠 OI↓ + Price↓ = Long Liquidations (wait)
⚪ Neutral
5. COMPOSITE SCORE
Combines OI momentum, funding extremes, and divergence into a single number:
→ Positive = favorable environment for longs
→ Negative = unfavorable, consider waiting
6. LONG SIGNAL CHECK
A simple GO/WAIT flag: ✅ GO only when regime is healthy (🟢), funding is NOT extreme, AND no bearish divergence is active.
█ SUPPORTED ASSETS
BTC, ETH, SOL, BNB, XRP, PEPE — all via Binance Perpetuals.
Select the asset from the dropdown input. Tickers are constructed dynamically (handles PEPE → 1000PEPEUSDT automatically).
█ VISUAL COMPONENTS
• Column chart: Daily OI change % (teal = inflow, red = outflow)
• Blue line: OI Z-Score with ±2.0 reference levels
• Orange line: Premium Z-Score with configurable extreme thresholds
• Purple stepline: Divergence Score
• Background color: Regime classification (green/yellow/red/orange)
• Shape markers: Bearish/Bullish divergence triangles + Funding extreme icons
• Info Table (top-right): Real-time dashboard showing all metrics at a glance
█ ALERTS (6 CONDITIONS)
1. Regime Bearish — regime shifts to shorts building or liquidations
2. Bearish OI Divergence — price rises but OI doesn't confirm
3. Bullish OI Divergence — OI rises faster than price (accumulation)
4. Funding Hot — overcrowded longs, correction risk
5. Funding Cold — potential short squeeze
6. Derivatives GO — all conditions favorable for longs
█ INPUTS
Asset Selection: BTC / ETH / SOL / BNB / XRP / PEPE
OI Change Lookback: 14 (default)
OI SMA Length: 20 (default)
Divergence Z-Score Threshold: 1.5 (default)
Premium Z-Score Lookback: 50 (default)
Premium Extreme Thresholds: +2.0 / -2.0 (default)
Display toggles: Table, Background, Divergence markers
█ HOW TO USE IT
This indicator is designed as a VETO FILTER, not a signal generator.
Use it alongside your primary strategy:
1. Check the regime background before entering a trade
2. If 🟢 and no warnings → your strategy signals are confirmed
3. If 🔴🟠🟡 or bearish divergence → consider skipping the signal
4. Monitor funding extremes for contrarian context
5. Set alerts on regime changes to stay informed without watching the chart
█ TIMEFRAME
Optimized for Daily (D1). Works on any timeframe, but regime classification and z-scores are most meaningful on higher timeframes.
█ DATA SOURCES
• Open Interest: BINANCE:{ASSET}USDT.P_OI
• Premium Index: BINANCE:{ASSET}USDT_PREMIUM (1H resolution)
• Price: BINANCE:{ASSET}USDT.P (perpetual close)
█ LIMITATIONS
• Only Binance Perpetuals data (not aggregated across exchanges)
• Premium Index is a proxy for funding rate (not exact funding)
• Funding Rate, Long/Short Ratio, Liquidations, and Taker Buy/Sell Volume are NOT available as native PulseWire tickers
• Regime classification uses smoothed trends — may lag at turning points
Indicator
Indicator
Indicator
Synthetic IV Rank [UAlgo]Synthetic IV Rank is a volatility analysis indicator that creates a practical proxy for IV Rank when direct options implied volatility data is not available. Instead of reading an options chain, the script estimates a synthetic volatility series from price action using a Yang Zhang style historical volatility model, then normalizes that value into a 0 to 100 rank across a user defined lookback window.
This makes the tool especially useful for traders who want an IV Rank style workflow on instruments or markets where true implied volatility is unavailable, limited, or inconsistent. The indicator can be used on stocks, indices, forex, commodities, and crypto, with a dedicated Crypto Mode for annualization based on 365 days.
The script is built as a separate pane indicator and focuses on clear regime awareness. It plots a smooth IV Rank line, adds visual threshold references for high and low volatility zones, and shows a live status label on the most recent bar with both the current rank and the raw synthetic volatility value. The overall design makes it suitable for fast regime checks, mean reversion context, premium selling style filters, and volatility expansion monitoring.
Important note: This is a synthetic IV Rank approximation based on historical price volatility. It is not a substitute for true options implied volatility from an options chain.
🔹 Features
🔸 1) Synthetic IV Rank Using a Yang Zhang Style Volatility Model
The indicator estimates volatility from price data using a Yang Zhang style framework, then converts that estimate into an IV Rank style percentile scale. This gives users an IV Rank like signal even when broker feeds do not provide options implied volatility.
🔸 2) Engine Based Design with Structured Inputs
The script uses a custom VolatilityEngine type to organize the core calculation parameters:
hv_length for volatility estimation length
lookback_length for IV Rank normalization window
annual_factor for market specific annualization
This structure makes the logic easier to maintain and extend.
🔸 3) Stock and Crypto Annualization Modes
The engine supports two annualization conventions through a simple input toggle:
252 day convention for traditional markets
365 day convention for crypto markets
This is a practical detail because the same raw volatility process can produce different annualized values depending on the asset class.
🔸 4) Robust IV Rank Normalization with Safe Fallback
The script computes IV Rank by comparing the current synthetic volatility value against the lowest and highest values over the selected lookback period. If the range collapses to zero, the script safely assigns a neutral rank of 50 instead of causing a division issue.
This improves reliability in flat or low variance periods.
🔸 5) Clear Regime Visualization
The indicator includes a strong visual layout designed for quick interpretation:
A main IV Rank line
A mid reference line at 50
High and low threshold markers at 80 and 20
Gradient fills that visually emphasize extreme zones
This helps users recognize volatility regime shifts at a glance.
🔸 6) Dynamic Last Bar Status Labels
On the latest bar, the script prints a compact status label that shows:
Current IV Rank value
Regime label such as EXTREME FEAR, COMPLACENCY, or NEUTRAL
It also adds a secondary information label showing the raw Yang Zhang synthetic volatility percentage. This gives both normalized context and raw measurement at the same time.
🔸 7) Practical Regime Classification
The script uses simple but effective thresholds for regime tagging:
Above 80 signals elevated volatility conditions
Below 20 signals compressed volatility conditions
Between 20 and 80 is treated as neutral
These thresholds align with common IV Rank style interpretation used in discretionary and systematic workflows.
🔹 Calculations
1) Engine Initialization
On the first bar, the script initializes the custom volatility engine and stores:
The Yang Zhang calculation length
The IV Rank lookback window
The annualization factor based on asset class mode
If Crypto Mode is enabled, the annual factor uses the square root of 365. Otherwise it uses the square root of 252.
2) Synthetic Volatility Source Series
The indicator computes a Yang Zhang style historical volatility estimate from OHLC data. The model combines multiple variance components so it can capture more market behavior than a simple close to close volatility series.
The script calculates:
A first variance component labeled as overnight in the comments
An open to close variance component
A Rogers Satchell style intraday variance component from high, low, open, and close relationships
3) First Variance Component (Commented as Overnight)
In the current implementation, the first component is built from the logarithmic return of close / close , and its rolling variance is measured over the user defined length.
This is important to note because the code comments describe an overnight style component, while the actual formula uses consecutive closes in the current version.
4) Open to Close Variance Component
The script computes the logarithmic open to close return log(close / open) and then applies a rolling variance over the selected length. This measures intrabar movement relative to the bar open.
5) Rogers Satchell Intraday Variance Component
To improve intraday variance estimation, the script calculates a Rogers Satchell style daily variance term using four logarithmic relationships derived from high, low, open, and close. It then smooths this with a rolling simple average across the same volatility length.
This component is useful because it incorporates more intrabar range information than a simple close based measure.
6) Yang Zhang Weighting Factor
The script computes a weighting coefficient k that depends on the volatility length. This weight balances the contribution of the open to close variance and the Rogers Satchell component in the final combined variance.
The implementation follows the standard Yang Zhang style weighting formula shown in the script comments.
7) Combined Synthetic Volatility and Annualization
After computing the variance components, the script combines them into a single Yang Zhang style variance estimate, takes the square root to obtain volatility, and annualizes the result with the engine annual factor. The final synthetic volatility value is expressed as a percentage.
In practical terms, this output is the raw volatility series that the script later converts into Synthetic IV Rank.
8) IV Rank Calculation
The IV Rank logic measures where the current synthetic volatility sits relative to its historical range over the selected lookback:
It finds the lowest synthetic volatility in the lookback window
It finds the highest synthetic volatility in the lookback window
It scales the current value to a 0 to 100 rank
If the lookback range is flat, the script assigns 50.0 as a neutral fallback.
This normalization step is what makes the output behave like an IV Rank style regime indicator rather than a raw volatility plot.
9) Regime State Classification
On the latest bar, the script assigns a text state from the current IV Rank:
EXTREME FEAR when rank is above 80
COMPLACENCY when rank is below 20
NEUTRAL otherwise
The label color also changes with the state, which improves visual scanning.
10) Visual Layer Logic
The visualization includes:
A plotted IV Rank line
Hidden boundary plots for fill anchors
Visible threshold markers at 80 and 20
A midpoint reference line at 50
Gradient fills for high volatility and low volatility zones
The fill logic visually intensifies as the IV Rank moves deeper into an extreme zone, helping users identify volatility compression and expansion phases quickly.
11) What This Indicator Represents in Practice
This script is best understood as a normalized historical volatility regime tool designed to mimic the workflow of IV Rank when direct implied volatility data is not available. It is excellent for context filtering and regime awareness, but it should not be interpreted as a true options market implied volatility feed. Indicator
Ultimate RegimeUltimate Regime | MisinkoMaster
Ultimate Regime is an advanced market environment classification tool designed to identify whether an asset is currently operating in a trending or mean-reverting regime. Instead of focusing on entry signals, the indicator concentrates on answering a more fundamental question: what type of market are we trading right now?
By continuously evaluating market structure, volatility behavior, and directional persistence, the script provides a unified regime view that helps traders adapt strategy selection, risk management, and trade expectations to current conditions.
This makes Ultimate Regime particularly valuable for traders using multiple systems, algorithmic frameworks, or discretionary approaches that perform differently depending on market state.
Core Concept
Markets alternate between expansion phases where directional movement dominates and contraction phases where price oscillates around equilibrium. Strategies built for one condition often underperform in the other.
Ultimate Regime solves this by aggregating several environment measurements into a single regime score that expresses whether the market currently favors:
• Trend continuation strategies
• Breakout participation
• Momentum trading
or instead
• Range trading
• Mean reversion strategies
• Oscillation-based setups
The indicator therefore acts as a decision filter rather than a trade trigger.
Key Features
Unified regime classification combining multiple market characteristics
Automatic detection of trending vs mean-reverting environments
Smooth regime transitions to reduce noise and false flips
Visual histogram representing regime strength
Automatic chart candle coloring based on environment
On-chart regime change labeling for clarity
Configurable lookback and smoothing controls
Works across all timeframes and asset classes
Suitable for discretionary and systematic traders
Designed for integration into multi-indicator workflows
How It Works (Conceptual)
Instead of relying on a single measurement, Ultimate Regime evaluates several dimensions of market behavior simultaneously, such as:
• Price expansion versus contraction
• Volatility shifts
• Directional persistence
• Structural movement characteristics
These components are normalized and combined into a composite regime value. The result is then smoothed to ensure regime changes reflect genuine environment shifts rather than short-term fluctuations.
When the combined regime value turns positive, the market is considered to favor directional movement. When it turns negative, price behavior favors oscillation and mean reversion.
The internal weighting and transformation methods remain proprietary in the invite-only version.
Regime States Explained
Trending Regime
Indicates directional dominance where price tends to move persistently in one direction. Momentum and breakout systems typically perform better under these conditions.
Mean Reverting Regime
Indicates oscillatory behavior where price frequently returns toward equilibrium zones. Range strategies and reversal setups often become more effective.
Neutral Transitions
Short transition periods may occur during regime changes as the environment reorganizes before committing to a dominant state.
Visual Components
Regime Histogram
A histogram displays regime strength and direction, making it easy to gauge whether trending or reverting behavior dominates.
Colored Candles
Price candles automatically change color according to regime classification, allowing instant environment recognition directly on the chart.
Regime Change Labels
Labels appear when regime shifts occur, helping traders visually track transitions between trending and mean-reverting phases.
Reference Thresholds
Visual guide levels help users understand regime extremes and neutral zones.
Inputs Overview
Source
Selects the price data used for regime analysis.
High-Low Difference Lookback
Controls how far back structural price expansion is evaluated.
ATR Lookback
Adjusts how volatility expansion or contraction is measured.
Standard Deviation Lookback
Defines the evaluation window for statistical price dispersion.
ADX Lookback
Controls directional persistence measurement sensitivity.
Smoothing Period
Applies smoothing to regime calculations, balancing responsiveness and stability.
Higher smoothing reduces noise but delays regime changes. Lower smoothing reacts faster but may increase regime flipping.
Usage Guidelines
Use Ultimate Regime as a strategy filter rather than a direct entry signal.
Trending regime environments generally favor:
• Breakout systems
• Momentum entries
• Trend-following approaches
• Pullback continuation trades
Mean-reverting environments generally favor:
• Range trading
• Support and resistance reversals
• Oscillation strategies
• Counter-trend setups
Regime analysis works best when combined with entry and risk tools rather than used standalone.
Practical Applications
Strategy selection switching between trend and range systems
Position sizing adjustments based on environment strength
Filtering trades that conflict with prevailing market behavior
Algorithmic system optimization
Portfolio regime monitoring
Timeframe alignment analysis
Parameter Tuning Notes
Lower lookback values increase responsiveness but may produce faster regime changes.
Higher lookback values stabilize regime detection for swing or position trading.
Short smoothing periods work better for intraday trading.
Longer smoothing periods help long-term traders avoid noise.
Optimal settings vary by asset volatility and timeframe.
Best Practices
Combine regime detection with price structure and confirmation tools.
Avoid forcing trend systems in reverting environments and vice versa.
Use regime awareness to improve trade selection discipline.
Backtest strategies separately for trending and mean-reverting periods.
Summary
Ultimate Regime provides a structured and adaptive view of market conditions by classifying whether the environment favors trend continuation or mean reversion. By separating environment analysis from trade signals, traders gain clarity in strategy selection and improve consistency across changing market conditions.
The invite-only version preserves proprietary calculation methods while delivering a robust regime detection framework suitable for discretionary traders, system developers, and algorithmic strategies alike. Indicator
Market Regime AnalyzerStatistical regime detection with forward-looking transition probabilities. Combines drift testing, variance ratios, and volume delta to classify markets into 5 regimes and quantify transition probabilities.
What Regime Are We In, and What's Likely Next?
That's the question this indicator answers with statistical rigor and forward-looking probabilities.
The Problem:
Most traders classify regimes arbitrarily: "Bull if price > 200 MA" or "Bear if RSI < 30." These rules ignore statistical significance, volume confirmation, and mean reversion patterns. The result? Late entries, false signals, and confusion when markets transition.
The Solution:
Market Regime Analyzer combines drift detection, variance ratio testing, and volume delta analysis to classify markets into 5 distinct regimes. Then it calculates the probability of transitioning to each regime based on historical patterns.
The Benefit:
Know not just where you are, but where you're likely going - with probabilities, not guesses.
The Five Market Regimes
🟢 Strong Bull (Regime 1)
- Statistically significant upward drift (t-stat > 1.96)
- Strong buying pressure (volume delta > 0.3)
- No mean reversion detected
- **Trade:** Trend-following strategies, ride the momentum
🟢 Weak Bull (Regime 2)
- Upward drift present
- BUT weak volume OR mean reversion detected
- **Trade:** Reduce position size, tighten stops, prepare for consolidation
⚪ Consolidation (Regime 3)
- No statistically significant drift
- Mixed volume signals
- Mean reversion likely present
- **Trade:** Range-trading, avoid trend-following systems
🔴 Weak Bear (Regime 4)
- Downward drift present
- BUT weak volume pressure
- **Trade:** Cautious shorts, reduce exposure, prepare for bounce
🔴 Strong Bear (Regime 5)
- Statistically significant downward drift (t-stat < -1.96)
- Strong selling pressure (volume delta < -0.3)
- No mean reversion detected
- **Trade:** Trend-following shorts, protective puts
The Statistical Framework
1. Drift Detection with T-Statistics
Instead of guessing if there's a trend, we test it statistically.
How it works:
- Calculates mean return over lookback period
- Standardizes by volatility
- Compares to significance threshold (default 1.96 = 95% confidence)
What it tells you:
- T-stat > 1.96: Statistically significant uptrend
- T-stat < -1.96: Statistically significant downtrend
- In between: No significant trend (consolidation)
Why it matters:
Only trades trends that are statistically validated, not just visually apparent.
2. Mean Reversion Testing (Variance Ratio)
Based on Lo & MacKinlay (1988) research, this detects when markets are range-bound.
How it works:
- Compares variance at different time scales
- Variance Ratio < 0.8 indicates mean reversion
What it tells you:
- Mean reversion = NO: Trends can continue
- Mean reversion = YES: Expect price to return to mean, not breakout
Why it matters:
Prevents chasing breakouts in range-bound markets.
3. Volume Delta Analysis
Total volume tells you HOW MUCH traded. Volume delta tells you WHO won.
How it works:
- Buying pressure - Selling pressure = Volume Delta
- Normalized to show relative strength
What it tells you:
- Strong positive delta (>0.3): Buyers in control
- Strong negative delta (<-0.3): Sellers in control
- Weak delta: No clear winner
Why it matters:
Price can move up on weak buying or down on weak selling. Volume delta reveals the truth.
4. Transition Probability Matrix
Historical regime changes predict future regime changes.
How it works:
- Tracks every regime transition over last 100 bars (configurable)
- Builds probability distribution for next regime
- Updates continuously
Example:
Current: Strong Bull
Historical transitions from Strong Bull:
- Stayed Strong Bull: 45%
- Became Weak Bull: 30%
- Became Consolidation: 20%
- Became Weak Bear: 4%
- Became Strong Bear: 1%
What it tells you:
Strong Bull has 75% chance of staying bullish (45% + 30%), only 5% chance of bearish turn.
Why it matters:
Adapts to your specific market's behavior patterns.
How to Use This Indicator
Strategy Adaptation
In Strong Bull/Bear Regimes:
- Use trend-following strategies
- Wider stops, let winners run
- Add to positions on pullbacks
- High confidence in directional trades
In Weak Bull/Bear Regimes:
- Reduce position sizes by 50%
- Tighter stops
- Take profits earlier
- Prepare for regime change
In Consolidation:
- Switch to range-trading strategies
- Avoid trend-following systems
- Sell resistance, buy support
- Wait for regime change before trend trades
Risk Management
Position Sizing:
- Strong regime + high continuation probability (>60%) = Normal size
- Weak regime OR high transition probability = Half size
- Consolidation = Quarter size or skip
Stop Loss Placement:
- Strong regime: Use wider stops (2x ATR)
- Weak regime: Tighter stops (1x ATR)
- Consolidation: Very tight stops (0.5x ATR)
Entry Timing
Best entries:
- Regime just changed to Strong Bull/Bear
- High probability (>50%) of staying in current regime
- No divergence signals present
- Drift and volume delta aligned
Avoid entries:
- High probability of regime change
- Divergence signals appearing
- Mean reversion detected in trending regime
- Weak volume despite price movement
Reading the Dashboard
Current Regime
Color-coded for instant recognition:
- Dark Green = Strong Bull
- Light Green = Weak Bull
- Gray = Consolidation
- Light Red = Weak Bear
- Dark Red = Strong Bear
Annualized Drift
Expected annual return based on recent trend.
- Positive = Upward bias
- Negative = Downward bias
- Near zero = No directional edge
T-Statistic
Measures statistical significance of drift.
- > 1.96 = 95% confident in uptrend
- < -1.96 = 95% confident in downtrend
- Between = Not statistically significant
Mean Reversion
- Yes = Expect price to return to mean (range-bound)
- No = Trends can continue (trending market)
Volume Pressure
Normalized volume delta strength.
- > 0.3 = Strong buying
- < -0.3 = Strong selling
- Near 0 = Balanced
Transition Probabilities
Shows most likely next regime.
- Highest probability = Most likely outcome
- Evenly distributed = High uncertainty
- Concentrated = High confidence in direction
Practical Examples
Example 1: Strong Bull with High Continuation
Dashboard shows:
Current Regime: Strong Bull
Drift: +22% annualized
T-Stat: 3.2
Mean Reversion: No
Volume Pressure: +0.45
Probabilities:
→ Strong Bull: 50%
→ Weak Bull: 25%
→ Consolidation: 20%
→ Bears: 5%
Interpretation:
- Strong uptrend (t-stat 3.2 >> 1.96)
- No mean reversion = trends can continue
- Strong buying pressure (0.45 > 0.3)
- 75% chance stays bullish (50% + 25%)
Action:
- Full position size on long setups
- Use trend-following entries
- Wider stops (2x ATR)
- High conviction trades
Example 2: Weak Bull Before Consolidation
Dashboard shows:
Current Regime: Weak Bull
Drift: +8% annualized
T-Stat: 1.2
Mean Reversion: Yes
Volume Pressure: +0.15
Probabilities:
→ Strong Bull: 10%
→ Weak Bull: 30%
→ Consolidation: 50%
→ Weak Bear: 10%
Interpretation:
- Weak drift (t-stat 1.2 < 1.96)
- Mean reversion detected = range-bound likely
- Weak volume (0.15 < 0.3)
- 50% chance of consolidation
Action:
- Reduce long positions
- Tighten stops
- Prepare for range-bound trading
- Avoid new trend trades
Example 3: Regime Transition Alert
Previous: Weak Bull
Current: Consolidation
Volume divergence signal appeared:
Price made new high, volume delta weakened
Interpretation:
- Trend exhausted
- Buyers losing control
- Regime confirmed the transition
Action:
- Exit trend-following longs
- Switch to range-trading approach
- Wait for new regime before new directional trades
Settings Guide
### Regime Detection Period (50)
Number of bars for statistical calculations.
- **30-40:** More responsive, catches changes faster, more regime switches
- **50 (default):** Balanced for daily/4H charts
- **75-100:** More stable, fewer false regime changes, slower to adapt
Transition History Depth (100)
How much history to use for probabilities.
- **50-75:** Adapts quickly to recent behavior
- **100 (default):** Balanced robustness
- **150-200:** More stable probabilities, slower to adapt
Volume Delta Period (14)
Period for volume calculations.
- **7-10:** More sensitive to volume shifts
- **14 (default):** Standard period
- **20-30:** Smoother, less noise
Significance Threshold (1.96)
T-statistic required for trend classification.
- **1.64:** 90% confidence, more trend regimes detected
- **1.96 (default):** 95% confidence, balanced
- **2.58:** 99% confidence, very conservative, mostly consolidation
Best Practices
Do:
- Wait for regime confirmation (at least 3-5 bars in new regime)
- Use probabilities to size positions appropriately
- Combine with support/resistance for entries
- Respect mean reversion signals
- Adapt strategy to current regime
Don't:
- Trade every regime change immediately
- Ignore high transition probabilities
- Use trend strategies in consolidation
- Override statistical signals with gut feel
- Trade against Strong regimes without clear setup
Timeframe Recommendations
Daily Charts:
- Default settings work well
- Most reliable regime detection
- Best for swing trading
4H Charts:
- Use default or slightly higher lookback (60-75)
- Good for active swing trading
- More regime changes than daily
1H Charts:
- Reduce lookback to 30-40
- More noise, use with caution
- Better for intraday position trading
15M and below:
- Not recommended
- Too much noise for statistical validity
- Regimes change too frequently
Combining with Other Indicators
Works Well With:
Moving Averages
- Use regime for directional bias
- MAs for specific entry/exit points
Support/Resistance
- Regime shows context
- S/R shows specific levels
- High probability at confluence
Volume Profile
- Regime shows regime
- Profile shows where volume is
- Target high-volume nodes
RSI/MACD
- Regime provides context
- Momentum shows entry timing
- Combine for higher probability
Example Combined Setup
Regime: Strong Bull
Price: Above 200 MA
Level: Pullback to support
RSI: Oversold (30)
Volume Delta: Still positive
Setup: Long entry
Reason: Trend intact, healthy pullback, buyers still present
Divergence Signals
The indicator shows volume divergence warnings:
Bearish Divergence (Red Triangle Down)
- Price makes new high
- Volume delta makes lower high
- Warning: Buyers weakening, potential reversal
Bullish Divergence (Green Triangle Up)
- Price makes new low
- Volume delta makes higher low
- Warning: Sellers weakening, potential reversal
How to use:
- Divergence in Strong regime = early warning of regime change
- Confirms when regime actually transitions
- Don't trade divergence alone, wait for regime confirmation
Limitations
This Indicator Cannot:
**Predict black swan events** - Unexpected news overrides all technical regimes
**Work in all markets** - Needs liquid markets with reliable volume data
**Guarantee profits** - Probabilities are not certainties
**Replace fundamental analysis** - Technical regimes can diverge from fundamentals
Works Best:
- Liquid markets (major indices, forex, crypto, large-cap stocks)
- Daily and 4H timeframes
- Combined with other analysis
- With proper risk management
- In normal market conditions
Common Questions
"Why did the regime stay consolidation despite strong price move?"
The indicator detected mean reversion (variance ratio < 0.8), indicating the move will likely reverse. Or the move wasn't statistically significant (t-stat < 1.96). Trust the statistics over visual appearance.
"Probabilities show 30% for each regime. What does that mean?"
High uncertainty. The market is at an inflection point. Reduce position sizes and wait for clearer regime formation.
"Can I use this for day trading?"
Not recommended on timeframes below 1H. Statistical tests need sufficient data. Better suited for swing trading.
"Why does this show Strong Bull when my momentum indicators show weakness?"
Momentum can weaken while the trend remains statistically significant. The indicator focuses on drift and volume, not momentum. Consider it a different perspective.
Technical Notes
Volume Delta Approximation
Uses OHLCV data to approximate order flow:
- Buy volume ≈ Volume on up-closes
- Sell volume ≈ Volume on down-closes
- Delta = Buy - Sell
**Note:** Real order flow (from futures or Level 2) is more precise. This approximation works well on liquid markets.
Statistical Tests
Drift T-Test:
- Null hypothesis: No drift (mean return = 0)
- Reject if |t-stat| > threshold
- Based on standard hypothesis testing
Variance Ratio:
- Compares 2-period variance to 1-period variance
- Ratio = 1 for random walk
- Ratio < 1 for mean reversion
- Threshold of 0.8 based on empirical testing
Transition Probability Implementation
Due to Pine Script v5 limitations (no native 2D arrays), the 5×5 transition matrix is stored as a flat 1D array of 25 elements:
- Position maps to index: `row × 5 + col`
- Example: Transition from Regime 2 to Regime 4 is at index `1 × 5 + 3 = 8`
- Laplace smoothing (0.1) prevents zero probabilities
- Row sums normalized to calculate probabilities
This approach is computationally efficient and maintains statistical accuracy.
No Repainting
All calculations confirmed on bar close. Regime changes appear when the bar closes, not during formation. Historical analysis is accurate.
Alert Conditions
Regime Change
- Triggers when regime transitions to any new state
- Message shows new regime number (1-5)
Bearish Divergence
- Triggers when price makes new high but volume delta doesn't confirm
Bullish Divergence
- Triggers when price makes new low but volume delta doesn't confirm
Disclaimer
FOR EDUCATIONAL PURPOSES ONLY
This indicator uses statistical methods to analyze market regimes. It does not predict the future or guarantee trading success.
Markets are probabilistic, not deterministic. A 70% probability of staying bullish means 30% chance of regime change. Always use proper risk management.
Past regime transitions do not guarantee future transitions. Market structure can change. Statistical relationships can break down.
Never risk more than you can afford to lose. Use stop losses on every trade. Test thoroughly before live trading. Consult a qualified financial advisor.
© 2026 | Open Source
Statistical rigor meets practical application Indicator
Cross-Market Regime Scanner [BOSWaves]Cross-Market Regime Scanner - Multi-Asset ADX Positioning with Correlation Network Visualization
Overview
Cross-Market Regime Scanner is a multi-asset regime monitoring system that maps directional strength and trend intensity across correlated instruments through ADX-based coordinate positioning, where asset locations dynamically reflect their current trending versus ranging state and bullish versus bearish bias.
Instead of relying on isolated single-asset trend analysis or static correlation matrices, regime classification, spatial positioning, and intermarket relationship strength are determined through ADX directional movement calculation, percentile-normalized coordinate mapping, and rolling correlation network construction.
This creates dynamic regime boundaries that reflect actual cross-market momentum patterns rather than arbitrary single-instrument levels - visualizing trending assets in right quadrants when ADX strength exceeds thresholds, positioning ranging assets in left quadrants during consolidation, and incorporating correlation web topology to reveal which instruments move together or diverge during regime transitions.
Assets are therefore evaluated relative to ADX-derived regime coordinates and correlation network position rather than conventional isolated technical indicators.
Conceptual Framework
Cross-Market Regime Scanner is founded on the principle that meaningful market insights emerge from simultaneous multi-asset regime awareness rather than sequential single-instrument analysis.
Traditional trend analysis examines assets individually using separate chart windows, which often obscures the broader cross-market regime structure and correlation patterns that drive coordinated moves. This framework replaces isolated-instrument logic with unified spatial positioning informed by actual ADX directional measurements and correlation relationships.
Three core principles guide the design:
Asset positioning should be determined by ADX-based regime coordinates that reflect trending versus ranging state and directional bias simultaneously.
Spatial mapping must normalize ADX values to place assets within consistent quadrant boundaries regardless of instrument volatility characteristics.
Correlation network visualization reveals which assets exhibit coordinated behavior versus divergent regime patterns during market transitions.
This shifts regime analysis from isolated single-chart monitoring into unified multi-asset spatial awareness with correlation context.
Theoretical Foundation
The indicator combines ADX directional movement calculation, coordinate normalization methodology, quadrant-based regime classification, and rolling correlation network construction.
A Wilder's smoothing implementation calculates ADX, +DI, and -DI for each monitored asset using True Range and directional movement components. The ADX value relative to a configurable threshold determines X-axis positioning (ranging versus trending), while the difference between +DI and -DI determines Y-axis positioning (bearish versus bullish). Coordinate normalization caps values within fixed boundaries for consistent quadrant placement. Pairwise correlation calculations over rolling windows populate a network graph where line thickness and opacity reflect correlation strength.
Five internal systems operate in tandem:
Multi-Asset ADX Engine : Computes smoothed ADX, +DI, and -DI values for up to 8 configurable instruments using Wilder's directional movement methodology.
Coordinate Transformation System : Converts ADX strength and directional movement into normalized X/Y coordinates with threshold-relative scaling and boundary capping.
Quadrant Classification Logic : Maps coordinate positions to four distinct regime states—Trending Bullish, Trending Bearish, Ranging Bullish, Ranging Bearish—with color-coded zones.
Historical Trail Rendering : Maintains rolling position history for each asset, drawing gradient-faded trails that visualize recent regime trajectory and velocity.
Correlation Network Calculator : Computes pairwise return correlations across all enabled assets, rendering weighted connection lines in circular web topology with strength-based styling.
This design allows simultaneous cross-market regime awareness rather than reacting sequentially to individual instrument signals.
How It Works
Cross-Market Regime Scanner evaluates markets through a sequence of multi-asset spatial processes:
Data Request Processing : Security function retrieves high, low, and close values for up to 8 configurable symbols with lookahead offset to ensure confirmed bar data.
ADX Calculation Per Asset : True Range computed from high-low-close relationships, directional movement derived from up-moves versus down-moves, smoothed via Wilder's method over configurable period.
Directional Index Derivation : +DI and -DI calculated as smoothed directional movement divided by smoothed True Range, scaled to percentage values.
Coordinate Transformation : X-axis position equals (ADX - threshold) * 2, capped between -50 and +50; Y-axis position equals (+DI - -DI), capped between -50 and +50.
Quadrant Assignment : Positive X indicates trending (ADX > threshold), negative X indicates ranging; positive Y indicates bullish (+DI > -DI), negative Y indicates bearish.
Trail History Management : Configurable-length position history maintains recent coordinates for each asset, rendering gradient-faded lines connecting sequential positions.
Velocity Vector Calculation : 7-bar coordinate change converted to directional arrow overlays showing regime momentum and trajectory.
Return Correlation Processing : Bar-over-bar returns calculated for each asset, pairwise correlations computed over rolling window.
Network Graph Construction : Assets positioned in circular topology, correlation lines drawn between pairs exceeding threshold with thickness/opacity scaled by correlation strength, positive correlations solid green, negative correlations dashed red.
Risk Regime Scoring : Composite score aggregates bullish risk-on assets (equities, crypto, commodities) minus bullish risk-off assets (gold, dollar, VIX), generating overall market risk sentiment with colored candle overlay.
Together, these elements form a continuously updating spatial regime framework anchored in multi-asset momentum reality and correlation structure.
Interpretation
Cross-Market Regime Scanner should be interpreted as unified spatial regime boundaries with correlation context:
Top-Right Quadrant (TREND ▲) : Assets positioned here exhibit ADX above threshold with +DI exceeding -DI - confirmed bullish trending conditions with directional conviction.
Bottom-Right Quadrant (TREND ▼) : Assets positioned here exhibit ADX above threshold with -DI exceeding +DI - confirmed bearish trending conditions with directional conviction.
Top-Left Quadrant (RANGE ▲) : Assets positioned here exhibit ADX below threshold with +DI exceeding -DI - ranging consolidation with bullish bias but insufficient trend strength.
Bottom-Left Quadrant (RANGE ▼) : Assets positioned here exhibit ADX below threshold with -DI exceeding +DI - ranging consolidation with bearish bias but insufficient trend strength.
Position Trails : Gradient-faded lines connecting recent coordinate history reveal regime trajectory - curved paths indicate regime rotation, straight paths indicate sustained directional conviction.
Velocity Arrows : Directional vectors overlaid on current positions show 7-bar regime momentum - arrow length indicates speed of regime change, angle indicates trajectory direction.
Correlation Web : Circular network graph positioned left of main quadrant map displays pairwise asset relationships - solid green lines indicate positive correlation (moving together), dashed red lines indicate negative correlation (diverging moves), line thickness reflects correlation strength magnitude.
Asset Dots : Multi-layer glow effects with color-coded markers identify each asset on both quadrant map and correlation web-symbol labels positioned adjacent to current location.
Regime Summary Bar : Vertical boxes on right edge display condensed regime state for each enabled asset - box background color reflects quadrant classification, border color matches asset identifier.
Risk Regime Candles : Overlay candles on price chart colored by composite risk score - green indicates risk-on dominance (bullish equities/crypto exceeding bullish safe-havens), red indicates risk-off dominance (bullish gold/dollar/VIX exceeding bullish risk assets), gray indicates neutral balance.
Quadrant positioning, trail trajectory, correlation network topology, and velocity vectors outweigh isolated single-asset readings.
Signal Logic & Visual Cues
Cross-Market Regime Scanner presents spatial positioning insights rather than discrete entry signals:
Regime Clustering : Multiple assets congregating in same quadrant suggests broad market regime consensus - all assets in TREND ▲ indicates coordinated bullish momentum across instruments.
Regime Divergence : Assets splitting across opposing quadrants reveals intermarket disagreement - equities in TREND ▲ while safe-havens in TREND ▼ suggests healthy risk-on environment.
Quadrant Transitions : Assets crossing quadrant boundaries mark regime shifts - movement from left (ranging) to right (trending) indicates breakout from consolidation into directional phase.
Trail Curvature Patterns : Sharp curves in position trails signal rapid regime rotation, straight trails indicate sustained directional conviction, loops indicate regime uncertainty with back-and-forth oscillation.
Velocity Acceleration : Long arrows indicate rapid regime change momentum, short arrows indicate stable regime persistence, arrow direction reveals whether asset moving toward trending or ranging state.
Correlation Breakdown Events : Previously strong correlation lines (thick, opaque) suddenly thinning or disappearing indicates relationship decoupling - often precedes major regime transitions.
Correlation Inversion Signals : Assets shifting from positive correlation (solid green) to negative correlation (dashed red) marks structural market regime change - historically correlated assets beginning to diverge.
Risk Score Extremes : Composite score reaching maximum positive (all risk-on bullish, all risk-off bearish) or maximum negative (all risk-on bearish, all risk-off bullish) marks regime conviction extremes.
The primary value lies in simultaneous multi-asset regime awareness and correlation pattern recognition rather than isolated timing signals.
Strategy Integration
Cross-Market Regime Scanner fits within macro-aware and intermarket analysis approaches:
Regime-Filtered Entries : Use quadrant positioning as directional filter for primary trading instrument - favor long setups when asset in TREND ▲ quadrant, short setups in TREND ▼ quadrant.
Correlation Confluence Trading : Enter positions when target asset and correlated instruments occupy same quadrant - multiple assets in TREND ▲ provides conviction for long exposure.
Divergence-Based Reversal Anticipation : Monitor for regime divergence between correlated assets - if historically aligned instruments split to opposite quadrants, anticipate mean-reversion or regime rotation.
Breakout Confirmation via Cross-Asset Validation : Confirm primary instrument breakouts by verifying correlated assets simultaneously transitioning from ranging to trending quadrants.
Risk-On/Risk-Off Positioning : Use composite risk score and safe-haven positioning to determine overall market environment - scale risk exposure based on risk regime dominance.
Velocity-Based Timing : Enter during periods of high regime velocity (long arrows) when momentum carries assets decisively into new quadrants, avoid entries during low velocity regime uncertainty.
Multi-Timeframe Regime Alignment : Apply higher-timeframe regime scanner to establish macro context, use lower-timeframe price action for entry timing within aligned regime structure.
Correlation Web Pattern Recognition : Identify regime transitions early by monitoring correlation network topology changes - previously disconnected assets forming strong correlations suggests regime coalescence.
Technical Implementation Details
Core Engine : Wilder's smoothing-based ADX calculation with separate True Range and directional movement tracking per asset
Coordinate Model : Threshold-relative X-axis scaling (trending versus ranging) with directional movement differential Y-axis (bullish versus bearish)
Normalization System : Boundary capping at ±50 for consistent spatial positioning regardless of instrument volatility
Trail Rendering : Rolling array-based position history with gradient alpha decay and width tapering
Correlation Engine : Return-based pairwise correlation calculation over rolling window with configurable lookback
Network Visualization : Circular topology with trigonometric positioning, weighted line rendering based on correlation magnitude
Risk Scoring : Composite calculation aggregating directional states across classified risk-on and risk-off asset categories
Performance Profile : Optimized for 8 simultaneous security requests with efficient array management and conditional rendering
Optimal Application Parameters
Timeframe Guidance:
1 - 5 min : Micro-regime monitoring for intraday correlation shifts and short-term regime rotations
15 - 60 min : Intraday regime structure with meaningful ADX development and correlation stability
4H - Daily : Swing and position-level macro regime identification with sustained trend classification
Weekly - Monthly : Long-term regime cycle tracking with structural correlation pattern evolution
Suggested Baseline Configuration:
ADX Period : 14
ADX Smoothing : 14
Trend Threshold : 25.0
Trail Length : 15
Correlation Period : 50
Min |Correlation| to Show Line : 0.3
Web Radius : 30
Show Quadrant Colors : Enabled
Show Regime Summary Bar : Enabled
Show Velocity Arrows : Enabled
Show Correlation Web : Enabled
These suggested parameters should be used as a baseline; their effectiveness depends on the selected assets' volatility profiles, correlation characteristics, and preferred spatial sensitivity, so fine-tuning is expected for optimal performance.
Parameter Calibration Notes
Use the following adjustments to refine behavior without altering the core logic:
Assets clustering too tightly : Decrease Trend Threshold (e.g., 20) to spread ranging/trending separation, or increase ADX Period for smoother ADX calculation reducing noise.
Assets spreading too widely : Increase Trend Threshold (e.g., 30-35) to demand stronger ADX confirmation before classifying as trending, tightening quadrant boundaries.
Trail too short to show trajectory : Increase Trail Length (20-25) to visualize longer regime history, revealing sustained directional patterns.
Trail too cluttered : Decrease Trail Length (8-12) for cleaner visualization focusing on recent regime state, reducing visual complexity.
Unstable ADX readings : Increase ADX Period and ADX Smoothing (18-21) for heavier smoothing reducing bar-to-bar regime oscillation.
Sluggish regime detection : Decrease ADX Period (10-12) for faster response to directional changes, accepting increased sensitivity to noise.
Too many correlation lines : Increase Min |Correlation| threshold (0.4-0.6) to display only strongest relationships, decluttering network visualization.
Missing significant correlations : Decrease Min |Correlation| threshold (0.2-0.25) to reveal weaker but potentially meaningful relationships.
Correlation too volatile : Increase Correlation Period (75-100) for more stable correlation measurements, reducing network line flickering.
Correlation too stale : Decrease Correlation Period (30-40) to emphasize recent correlation patterns, capturing regime-dependent relationship changes.
Velocity arrows too sensitive : Modify 7-bar lookback in code to longer period (10-14) for smoother velocity representation, or increase magnitude threshold for arrow display.
Adjustments should be incremental and evaluated across multiple session types rather than isolated market conditions.
Performance Characteristics
High Effectiveness:
Macro-aware trading approaches requiring cross-market regime context for directional bias
Intermarket analysis strategies monitoring correlation breakdowns and regime divergences
Portfolio construction decisions requiring simultaneous multi-asset regime classification
Risk management frameworks using safe-haven positioning and risk-on/risk-off scoring
Trend-following systems benefiting from cross-asset regime confirmation before entry
Mean-reversion strategies identifying regime extremes via clustering patterns and correlation stress
Reduced Effectiveness:
Single-asset focused strategies not incorporating cross-market context in decision logic
High-frequency trading approaches where multi-security request latency impacts execution
Markets with consistently weak correlations where network topology provides limited insight
Extremely low volatility environments where ADX remains persistently below threshold for all assets
Instruments with erratic or unreliable ADX characteristics producing unstable coordinate positioning
Integration Guidelines
Confluence : Combine with BOSWaves structure, volume analysis, or primary instrument technical indicators for entry timing within aligned regime
Quadrant Respect : Trust signals occurring when primary trading asset occupies appropriate quadrant for intended trade direction
Correlation Context : Prioritize setups where target asset exhibits strong correlation with instruments in same regime quadrant
Divergence Awareness : Monitor for safe-haven assets moving opposite to risk assets - regime divergence validates directional conviction
Velocity Confirmation : Favor entries during periods of strong regime velocity indicating decisive momentum rather than regime oscillation
Risk Score Alignment : Scale position sizing and exposure based on composite risk score - larger positions during clear risk-on/risk-off environments
Trail Pattern Recognition : Use trail curvature to identify regime stability (straight) versus rotation (curved) versus uncertainty (looped)
Multi-Timeframe Structure : Apply higher-timeframe regime scanner for macro filter, lower-timeframe for tactical positioning within established regime
Disclaimer
Cross-Market Regime Scanner is a professional-grade multi-asset regime visualization and correlation analysis tool. It uses ADX-based coordinate positioning and rolling correlation calculation but does not predict future regime transitions or guarantee relationship persistence. Results depend on selected assets' characteristics, parameter configuration, correlation stability, and disciplined interpretation. Security request timing may introduce minor latency in real-time data retrieval. BOSWaves recommends deploying this indicator within a broader analytical framework that incorporates price structure, volume context, fundamental macro awareness, and comprehensive risk management. Indicator
Trend Strength [OmegaTools]Trend Strength is a quantitative regime oscillator designed to measure directional pressure and trend quality by blending price structure, return-dependence, realized intrabar expansion, and volume participation into a single normalized signal. The goal is not to predict, but to classify market state: when price action is in an expansionary/distributionary phase versus when it is in a contractionary/accumulation phase, so you can align execution and risk with the prevailing environment.
Core concept and methodology
The indicator aggregates four components computed on stable rolling windows and mapped into comparable ranges:
1. Price location / structural positioning (100-bar range)
A normalized price-location metric (position of close within the rolling high–low range) is transformed into a non-linear “strength” profile. This emphasizes meaningful departures from the middle of the range and penalizes indecision, producing a structure-aware contribution rather than a raw oscillator.
2. Return-dependence / directional persistence (100 bars)
A correlation term measures the relationship between the current return (close − close ) and the prior price level (close ). This helps detect environments where movement is more persistent or more mean-reverting, providing a statistical component that complements pure price-location signals.
3. Realized expansion / volatility proxy (50-bar accumulation, 300-bar normalization)
Intrabar expansion is approximated via the absolute candle body relative to the full range, aggregated over a short window to represent realized “effort” and then normalized over a longer window. This captures whether price is moving with meaningful body expansion versus compressing and stalling.
4. Volume participation (11-bar accumulation, 300-bar normalization)
A rolling volume sum is normalized over a longer window to quantify participation. This helps separate “thin” moves from moves supported by broader activity, without relying on exchange-specific volume assumptions.
The final oscillator is a weighted blend of these four normalized components, scaled for readability. The output is intentionally centered around two actionable regimes rather than a symmetric overbought/oversold framework.
How to read the oscillator
Trend Strength is designed around two main thresholds:
- Distribution / Expansion regime (oscillator above 0)
When the oscillator is above 0, the market is classified as being in a higher-pressure expansion regime. This often corresponds to directional continuation potential, stronger impulse behavior, and reduced suitability for tight mean-reversion tactics.
- Accumulation / Contraction regime (oscillator below −1.3)
When the oscillator is below −1.3, the market is classified as being in a contraction/accumulation regime. This frequently corresponds to compression, rotation, and lower directional efficiency, where breakouts may be more fragile and mean-reversion tactics may be more appropriate (depending on instrument and session conditions).
Values between 0 and −1.3 are treated as transitional/neutral, where the market is not clearly committing to either regime.
Continuous Mode vs Standard Mode
Trend Strength includes an optional Continuous Mode to improve interpretability during regime transitions:
- Standard Mode colors only when the oscillator is firmly in one of the two regimes (above 0 or below −1.3). Neutral zones remain uncolored, keeping the display conservative.
- Continuous Mode adds persistence logic: once a regime is confirmed, intermediate values are rendered with a lighter shade of the last confirmed regime until the opposite regime is confirmed. This reduces visual noise, helps maintain a consistent directional bias framework, and is particularly useful for intraday execution and session trend management.
Visual design and bar coloring
The oscillator line is color-coded:
- Purple: distribution / expansion regime
- Orange: accumulation / contraction regime
Neutral/transitional values are displayed in grey (or lightly shaded in Continuous Mode based on last confirmed regime).
Optionally, the indicator can color price bars using the same regime logic, allowing rapid at-a-glance regime recognition directly on the chart.
Practical use cases
- Regime filter for strategies: enable trend-following logic only in expansion regimes; enable mean-reversion or range logic in contraction regimes.
- Risk adjustment: increase/decrease position sizing or tighten/widen stops based on regime classification.
- Confirmation layer: combine with structure tools (market structure, VWAP, key levels) to validate whether conditions support continuation or imply compression.
- Session management: identify when a session is behaving as a trend day versus a rotational day, improving trade selection and reducing overtrading.
Notes
Trend Strength is a regime classifier and contextual tool. It does not guarantee future direction and should be integrated into a complete decision process (risk management, market structure, session context, and instrument-specific behavior).
© OmegaTools Indicator
Indicator
MarketMind LITEM🜁rketMind LITE ────────────────────
Essential Market Awareness, Reduced to Its Core
M🜁rketMind LITE is a lightweight market awareness tool designed to display essential situational context .
It provides basic orientation and movement awareness without interpretation, risk framing, diagnostics, or decision guidance.
This script is designed as a standalone awareness layer. It does not evaluate trade quality, issue signals, or influence decision-making.
WHAT IT DOES ────────────────────
M🜁rketMind LITE presents a minimal, static view of current market conditions focused entirely on awareness rather than analysis.
The system displays only essential context, allowing traders to stay oriented without introducing judgment, noise, or implied direction.
The script provides visibility into:
Time-of-day session context
Basic market regime classification (trending, range-bound, mixed)
Short-term momentum direction only (up, down, neutral)
A clean, static HUD display
M🜁rketMind LITE also includes a minimal visual state indicator that reflects recent price responsiveness, intended to be observed over time alongside the trader’s own experience.
The goal is to support awareness without influence .
HOW TO USE IT ────────────────────
M🜁rketMind LITE is not a signal generator.
It is designed to remain visible in the background of any chart, offering quiet orientation while traders rely entirely on their own process for analysis and execution.
Common use cases include:
Maintaining session awareness
Preserving context during focused trading periods
Reducing cognitive load while monitoring markets
M🜁rketMind LITE does not evaluate risk, alignment, or opportunity.
It simply shows what is happening.
DESIGN PHILOSOPHY ────────────────────
M🜁rketMind LITE is intentionally minimal.
It includes only essential awareness elements and excludes all interpretive or evaluative logic:
Situational context only
Directional momentum (up / down / neutral)
No diagnostics, confidence, or conviction framing
No process, risk, or quality assessment
Presentation controls only (HUD on/off, size, position)
Nothing is inferred.
Nothing is suggested.
This script shows market state without interpretation.
WHO IT IS FOR ────────────────────
M🜁rketMind LITE is suited for traders who:
Want passive situational awareness
Prefer minimal on-chart information
Already operate with a defined decision process
It is not designed for:
Analytical or diagnostic use
Risk evaluation or context synthesis
Traders seeking guidance or confirmation
IMPORTANT NOTES ────────────────────
M🜁rketMind LITE does not provide financial advice
No system can predict future price behavior
This tool is designed for awareness only
Used appropriately, M🜁rketMind LITE helps traders stay oriented without interference. Indicator
Market Pressure Regime [Interakktive]The Market Pressure Regime (MPR) is a 4-state market classifier that models how structural forces create "pressure zones" — regions where price movement is either supported (Release) or suppressed (Pinned) by market microstructure.
It combines compression analysis, follow-through efficiency, and stress detection into a composite pressure score, classifying markets into Release, Suppressed, Transition, or Trap states — helping traders understand WHY price is moving (or not moving) in the current environment.
█ USAGE
MPR addresses a core question traders face: Is the market in a regime where directional moves are likely to follow through, or is it structurally pinned?
For swing traders, MPR identifies Release phases where momentum strategies work best, and Suppressed phases where mean reversion dominates.
For day traders, it highlights Trap conditions — high effort with no follow-through — where reversals are probable and trend entries fail.
🔹 The 4-State Model
The indicator classifies markets into four distinct regimes:
• Release (Teal): Pressure score ≥ +5. Directional flow dominates. Price moves efficiently with follow-through. Favor trend continuation.
• Suppressed (Grey): Pressure score ≤ -5. Compression dominates. Price is range-bound or pinned. Fade extremes, expect reversion.
• Transition (Amber): Score between thresholds OR instability detected. Regime is uncertain — wait for confirmation before committing.
• Trap (Magenta): High stress + low follow-through. Effort without result. Expect reversals.
🔹 Reading the Pressure Histogram
The histogram displays the composite Pressure Score (range approximately -100 to +100):
• Positive values: Follow-through exceeds compression. Market is "releasing" — directional moves are supported.
• Negative values: Compression exceeds follow-through. Market is "suppressed" — price movement is constrained.
• Color reflects confirmed state: The histogram uses persistence filtering — a state must hold for N bars before the color changes, preventing false signals from noise.
🔹 The 5-Stage Calculation
MPR synthesizes five analytical stages into the final state:
1. Compression Score: Measures how tight the current range is relative to ATR. High compression suggests structural forces are pinning price.
2. Follow-Through Score: Measures price path efficiency (MER-style). Efficient moves indicate genuine directional flow, not chop.
3. Stress Score: Detects effort-without-result (ERD-style). High volume or range with no price progress = absorption.
4. Composite Pressure: Combines follow-through and compression into a single directional score.
5. Persistence Filter: Requires states to hold for configurable bars before confirming, eliminating flickering.
█ SETTINGS
Core Settings
• ATR Length: Period for volatility normalization. Default 14.
• Baseline Lookback: Period for compression and efficiency baselines. Default 20.
• Volume Average Length: Period for stress calculation baseline. Default 20.
State Classification
• Release Threshold: Pressure score above this = Release. Default +5.
• Suppressed Threshold: Pressure score below this = Suppressed. Default -5.
• Trap Threshold: Stress score above this (with low follow-through) = Trap. Default 30.
• Persistence Bars: Bars required to confirm state change. Default 3.
• Stability Lookback: Period for stability calculation. Default 20.
• Stability Threshold: Below this = forced Transition state. Default 0.5.
Visual Settings
• Show Pressure Histogram: Display the main pressure score histogram.
• Show Zero Line: Display the zero reference line.
• Show Background Tint: Subtle background color by state (default OFF).
Data Window
• Show Data Window Values: Export all calculated scores for analysis.
█ INTERPRETATION GUIDE
When to Use Trend Strategies (Release):
• Histogram tall and positive
• Teal coloring confirmed
• Price making efficient higher highs or lower lows
When to Use Mean Reversion (Suppressed):
• Histogram flat or negative
• Grey coloring confirmed
• Price oscillating without follow-through
When to Wait (Transition):
• Amber coloring
• Mixed signals — don't force trades
• Wait for state to resolve
When to Expect Reversals (Trap):
• Magenta coloring
• High volume moves that don't stick
• Often occurs at structural inflection points
█ COMPLEMENTARY TOOLS
MPR pairs well with:
• Volatility State Index (VSI) — Confirms whether volatility is expanding into the pressure regime
• Effort-Result Divergence (ERD) — Provides bar-by-bar absorption/vacuum detection
• Market Efficiency Ratio (MER) — Validates follow-through quality
█ SUITABLE MARKETS
Works across all liquid markets:
• Equities: SPY, QQQ, liquid single stocks
• Futures: ES, NQ, CL, GC
• Crypto: BTC, ETH
• Forex: Major pairs
Works on any timeframe, but 1H–Daily provides cleanest regime classification. Intraday (5m–15m) useful for session-level tactical decisions.
█ OPEN SOURCE
This indicator is open-source for educational purposes. Review the code to understand the full calculation methodology.
█ DISCLAIMER
This indicator is for educational and informational purposes only. It does not constitute financial advice. Past performance does not guarantee future results. Always conduct your own analysis and use proper risk management. Indicator
