Volatility Cluster Pressure [JOAT]Volatility Cluster Pressure
Introduction
Volatility Cluster Pressure tracks EWMA variance, realized volatility, vol-of-vol, jump intensity, compression, expansion, and unstable cluster states.
This open-source indicator is designed as a context tool, not a standalone trading system. It focuses on explaining the current market state with restrained visuals and confirmed-bar logic where signals are used.
Core Concepts
1. EWMA Variance
A recursive lambda model emphasizes recent returns while retaining volatility memory.
2. Volatility Rank
EWMA volatility is ranked within a historical window.
3. Jump Intensity
Absolute return deviations identify abnormal movement relative to recent behavior.
4. Pressure Rails
Volatility and instability expand adaptive pressure rails around price.
ewmaVar := lambda * ewmaVar + (1 - lambda) * logRet * logRet
Features
EWMA/GARCH-style variance pressure
Volatility rank and vol-of-vol
Jump z-score
Compression, expansion, and unstable states
Adaptive pressure rails and HUD
Input Parameters
Cluster window and EWMA lambda
Cluster pressure and compression gates
Cooldown
Rails, candles, and HUD toggles
HUD position selector
How to Use This Script
Use VCP to understand volatility conditions before interpreting signals. Compression, expansion, and unstable states describe risk environment.
Limitations
The script uses historical OHLCV data and cannot know future prices.
Signals and states can be late during fast reversals because confirmed-bar logic is used to reduce repainting.
Model outputs should be interpreted with market context, risk controls, and independent analysis.
No visual state should be treated as a certain trade outcome.
Originality Statement
VCP is original in combining recursive variance, vol rank, jump pressure, instability, and adaptive rails.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any financial instrument. All calculations are derived from historical market data and may produce inaccurate readings in some market conditions. No indicator can predict future market behavior. Use proper risk management and independent judgment.
-Made with passion by jackofalltrades
Indicator
Thorp Kelly Risk Engine [JOAT]Thorp Kelly Risk Engine
Introduction
Thorp Kelly Risk Engine is a risk-quality study that tracks virtual outcomes, Kelly estimates, Bayesian shrinkage, drawdown pressure, survival score, and deployment state.
This open-source indicator is designed as a context tool, not a standalone trading system. It focuses on explaining the current market state with restrained visuals and confirmed-bar logic where signals are used.
Core Concepts
1. Virtual Outcome Tracker
Trend setups create virtual reward/risk outcomes measured in ATR units.
2. Kelly Estimate
Win rate and payoff ratio produce full and fractional Kelly-style estimates.
3. Bayesian Shrinkage
A prior win rate reduces overconfidence when sample size is small.
4. Survival and Desk Score
Drawdown, volatility, signal density, convexity, and uncertainty combine into risk state.
kelly = (payoff * winRate - lossRate) / payoff
Features
Virtual outcome sampling
Fractional and Bayesian Kelly estimates
Drawdown throttle and volatility brake
Ruin-adjusted Kelly
Prime, defense, and lockdown states
Input Parameters
Trend, RSI, and ATR lengths
Reward and risk ATR
Kelly fraction and max allocation
Minimum sample and drawdown brake
Display toggles and HUD position
How to Use This Script
Use TKR as risk context. Prime states suggest healthier virtual samples; defensive and lockdown states warn that model risk is elevated.
Limitations
The script uses historical OHLCV data and cannot know future prices.
Signals and states can be late during fast reversals because confirmed-bar logic is used to reduce repainting.
Model outputs should be interpreted with market context, risk controls, and independent analysis.
No visual state should be treated as a certain trade outcome.
Originality Statement
TKR is original in combining Kelly math, Bayesian shrinkage, drawdown throttling, survival scoring, and uncertainty cones.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any financial instrument. All calculations are derived from historical market data and may produce inaccurate readings in some market conditions. No indicator can predict future market behavior. Use proper risk management and independent judgment.
-Made with passion by jackofalltrades
Indicator
Markowitz Frontier Compass [JOAT]Markowitz Frontier Compass
Introduction
Markowitz Frontier Compass compares the chart symbol against a peer basket using inverse-volatility weights, correlation drag, diversification benefit, factor scores, and active risk budget.
This open-source indicator is designed as a context tool, not a standalone trading system. It focuses on explaining the current market state with restrained visuals and confirmed-bar logic where signals are used.
Core Concepts
1. Inverse-Volatility Basket
Each peer receives an inverse-volatility weight to form a portfolio-context benchmark.
2. Correlation Drag
Average pairwise correlation reduces diversification value when assets move together.
3. Factor Composite
Quality, momentum, low-volatility, and carry-style behavior are combined.
4. Risk Budget
Institutional grade, entropy, concentration, and factor state become active or defensive budget context.
frontierScore = efficiency + diversification - correlationDrag - concentration
Features
Peer basket context
Inverse-volatility weighting
Correlation drag and diversification benefit
Factor composite and allocation entropy
Risk-on, defense, and factor-prime states
Input Parameters
Peer symbols
Return window and smoothing
Risk-free annual percent
Correlation stress and concentration gates
Display toggles and HUD position
How to Use This Script
Use MFC as cross-asset context. Risk-on or factor-prime states suggest constructive basket behavior; defense states warn of stress.
Limitations
The script uses historical OHLCV data and cannot know future prices.
Signals and states can be late during fast reversals because confirmed-bar logic is used to reduce repainting.
Model outputs should be interpreted with market context, risk controls, and independent analysis.
No visual state should be treated as a certain trade outcome.
Originality Statement
MFC is original in combining portfolio theory, factor scoring, entropy, and risk-budget logic in one open-source study.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any financial instrument. All calculations are derived from historical market data and may produce inaccurate readings in some market conditions. No indicator can predict future market behavior. Use proper risk management and independent judgment.
-Made with passion by jackofalltrades
Indicator
Entry Gate - ADR% / ADV / ATR MultipleThree critical pre-trade filters, always visible right on your chart.
Before entering any swing trade, three questions determine whether the setup is even worth considering: is this stock volatile enough to move my account, is it liquid enough to trade cleanly, and is it too extended to enter now? Entry Gate answers all three at a glance, in a single corner of your chart.
ADR% (Average Daily Range) measures how much a stock moves on an average day. Too low and it won't move your portfolio. Too high and daily noise will stop you out randomly.
ADV (Average Dollar Volume) measures how much money flows through the stock each day. Liquid stocks respect key levels, pull back cleanly to moving averages, and don't gap on low volume. Illiquid stocks do the opposite.
ATR Multiple measures how extended the price is above its 50-day moving average, expressed in ATR units. The further extended, the higher the probability of a pause or reversal. Based on jfsrev's published formula: % Gain from MA divided by ATR%.
ATR% rounds out the dashboard with the raw volatility number for context.
All values are color-coded against your thresholds:
🟢 Green — within your ideal range
🟠 Orange — borderline, proceed with caution
🔴 Red — outside your criteria
A yellow dot also plots above the bar when the ATR Multiple exceeds your trigger level, marking historically extended zones at a glance.
Fully customizable:
Independent thresholds for ADR%, ADV, and ATR Multiple
Warning zones for borderline values
Lookback periods for each calculation
Font size, table position, dot size and offset
Color customization for good / warning / bad / ATR / dot
All values are pulled from the daily timeframe via request.security, so the numbers stay consistent whether you're on a daily, weekly, or intraday chart.
Default thresholds are calibrated for swing traders running mid-sized accounts. Adjust to match your strategy.
Credits to ArmerSchlucker for the original ADR% table indicator, MikeC / TheScrutiniser and GlinckEastwoot for the ADR% formula, and jfsrev / Fred6724 for the ATR% Multiple from 50-MA approach. Indicator
Black Merton Volatility Engine [JOAT]Black Merton Volatility Engine
Introduction
Black Merton Volatility Engine blends multiple realized-volatility estimators with expected-move rails, cone rank, jump pressure, and tail-state classification.
This open-source indicator is designed as a context tool, not a standalone trading system. It focuses on explaining the current market state with restrained visuals and confirmed-bar logic where signals are used.
Core Concepts
1. Composite Realized Volatility
Close-to-close, Parkinson, Garman-Klass, Rogers-Satchell, and Yang-Zhang-style estimates contribute to the volatility state.
2. Volatility Cone
Current volatility is ranked against a historical cone to identify squeeze and shock conditions.
3. Expected Move Rails
Annualized volatility is converted into a multi-day expected move around price.
4. Tail and Jump Pressure
Large returns, rail breaches, and volatility divergence contribute to tail and jump states.
expectedMove = close * realizedVol * math.sqrt(days / 252)
Features
Composite realized volatility
Expected-move rails
Squeeze and shock regimes
Gamma pin, tail shock, clean expansion, and jump labels
Movable quant HUD
Input Parameters
Fast, base, and slow vol windows
Vol cone window
Expected move days
Squeeze and shock percentiles
Cooldown and display toggles
How to Use This Script
Use the rails as volatility context. Squeeze, shock, tail, and jump states describe volatility conditions, not a certain direction.
Limitations
The script uses historical OHLCV data and cannot know future prices.
Signals and states can be late during fast reversals because confirmed-bar logic is used to reduce repainting.
Model outputs should be interpreted with market context, risk controls, and independent analysis.
No visual state should be treated as a certain trade outcome.
Originality Statement
BMV is original in blending several volatility estimators, cone ranking, jump pressure, and expected-move visualization.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any financial instrument. All calculations are derived from historical market data and may produce inaccurate readings in some market conditions. No indicator can predict future market behavior. Use proper risk management and independent judgment.
-Made with passion by jackofalltrades
Indicator
Nexus Kinetic Reactor [JOAT]Nexus Kinetic Reactor
Introduction
Nexus Kinetic Reactor estimates price as a noisy state process. It tracks state, velocity, uncertainty, confidence, and optional projection cones.
This open-source indicator is designed as a context tool, not a standalone trading system. It focuses on explaining the current market state with restrained visuals and confirmed-bar logic where signals are used.
Core Concepts
1. Recursive State Estimate
A smoothing lambda updates the estimated price state bar by bar.
2. Velocity Regime
Changes in the state estimate create velocity and acceleration-style context.
3. Uncertainty Bands
Noise windows and sigma bands show how uncertain the current estimate is.
4. Confidence Gate
Signals require tracking confidence and expectancy thresholds before labels appear.
state := state + lambdaAdjustment * (price - state)
Features
Recursive price-state estimator
Velocity and acceleration regime logic
Uncertainty bands
Projection cone
Blocked signal markers and dashboard
Input Parameters
Smoothing lambda and noise window
ATR length and velocity threshold
Minimum confidence and expectancy
Band sigma and projection bars
Cone, candle, and panel toggles
How to Use This Script
Use the state estimate and uncertainty bands as kinetic context. Labels only appear when the model clears confidence and expectancy gates.
Limitations
The script uses historical OHLCV data and cannot know future prices.
Signals and states can be late during fast reversals because confirmed-bar logic is used to reduce repainting.
Model outputs should be interpreted with market context, risk controls, and independent analysis.
No visual state should be treated as a certain trade outcome.
Originality Statement
Nexus is original in combining state estimation, velocity gating, uncertainty bands, expectancy filtering, and projection visualization.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any financial instrument. All calculations are derived from historical market data and may produce inaccurate readings in some market conditions. No indicator can predict future market behavior. Use proper risk management and independent judgment.
-Made with passion by jackofalltrades
Indicator
Helios Pullback Framework [JOAT]Helios Pullback Framework
Introduction
Helios Pullback Framework evaluates pullback quality using ALMA trend stack, regression trajectory, pullback depth, wick recovery, liquidity capture, compression, and HTF bias.
This open-source indicator is designed as a context tool, not a standalone trading system. It focuses on explaining the current market state with restrained visuals and confirmed-bar logic where signals are used.
Core Concepts
1. ALMA Trend Stack
Fast and slow ALMA lines define execution and institutional spines.
2. Regression Trajectory
A regression envelope provides dynamic path context rather than static zones.
3. Pullback Quality
Pullback depth, wick recovery, phase impulse, and stretch are scored.
4. Liquidity Capture
Confirmed sweeps of recent highs or lows contribute only when aligned with bias.
score = bias + pullDepth + wickRecovery + sweep + compression + htf
Features
ALMA trend stack
Regression trajectory envelope
Pullback depth and wick recovery scoring
Liquidity capture markers
Sparse P+ and P- labels
Input Parameters
ALMA lengths
Volatility and trajectory length
HTF and optional session gate
Signal score, cooldown, and max stretch
Display toggles
How to Use This Script
Use P+ and P- labels as pullback-quality events inside an existing bias. Gold circles mark liquidity capture without full confirmation.
Limitations
The script uses historical OHLCV data and cannot know future prices.
Signals and states can be late during fast reversals because confirmed-bar logic is used to reduce repainting.
Model outputs should be interpreted with market context, risk controls, and independent analysis.
No visual state should be treated as a certain trade outcome.
Originality Statement
Helios is original in replacing supply/demand boxes with a cleaner model that scores pullback elasticity, trajectory, and liquidity capture.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any financial instrument. All calculations are derived from historical market data and may produce inaccurate readings in some market conditions. No indicator can predict future market behavior. Use proper risk management and independent judgment.
-Made with passion by jackofalltrades
Indicator
Super QuantumX Trend Shift Indicator V2Overview
The Super QuantumX Trend Shift Indicator V2 is an institutional-grade confluence engine designed for professional scalpers and intraday trend followers. While many retail indicators focus on a single metric (like price momentum), Super QuantumX recognizes that institutional moves are driven by a convergence of Momentum, Volume, Volatility, and Market Structure.
- This indicator is a sophisticated "Decision Matrix." It is not simply a collection of indicators on one chart; it is a gated signal system. A BUY or SELL signal is only generated when six distinct market dimensions align perfectly. This multi-layered approach filters out the noise of low-liquidity sessions and identifies the exact moment "Smart Money" enters the market.
Core Institutional Components & Why They Are Used:
1. Refined Momentum (Supertrend Logic): Used to define the primary active zones. We use Cyan for bullish and Purple for bearish momentum to provide an immediate visual bias.
2. Institutional Moving Averages (Multi-Type EMA Cross): Standard retail crosses are often too slow. We provide 6 adjustable MA types (EMA, TEMA, HMA, etc.) to confirm that the short-term trend is supported by institutional moving average baselines.
3. Accumulation Detection (Squeeze Pro): Before an institutional move occurs, the market often consolidates. We integrate Bollinger Band and Keltner Channel compression logic (Yellow bars) to identify these high-pressure zones where big orders are being filled.
4. Relative Aggression (CVD Proxy): Using a Cumulative Volume Delta proxy, the script ensures that signals are backed by aggressive market participants rather than thin retail volume.
5. Velocity & Strength (MACD/RSI/ADX): MACD tracks the velocity of the move, RSI confirms strength relative to the last 14 bars, and ADX filters out "Chop" zones by muting signals when volatility is too low to sustain a scalp.
6. Tactical Confirmation (Candle Pattern Recognition): Even if indicators align, we require a price action "trigger." The script looks for institutional-grade Engulfing patterns to ensure an impulse candle is behind every signal.
Advanced Profit Target Hierarchy
Unlike standard pivot points, our target system is dynamic and vertically aligned for a clean "R1-R3" look:
- HVN TARGET #1 & #2: Uses High Volume Nodedetection over a 100-bar and 25-bar lookback to find the Point of Control where liquidity is most dense.
- TARGET #3 & #4: Uses 1.618 and 2.618 Fibonacci Extensions of the higher-timeframe move to identify trend exhaustion levels.
The Multi-Timeframe Dashboard
A real-time dashboard tracks the health of the trade by showing the status of the Current, 15-minute, and 1-hour trend alignments. This ensures you never scalp against the "Master Trend" of the day.
How to Use
- The Setup: Wait for Yellow bars (Squeeze) to appear. This indicates institutional interest is building.
- The Trigger: A BUY or SELL label will appear when all 6 internal strategies align.
- The Zones: Only take long signals in Cyan zones and short signals in Purple zones.
- The Exit: Take profit at the horizontal HVN or Fib target levels and trail your stop along the Quantum Line .
Settings & Customization
Traders have full control over signal sensitivity, including an ATR Strength Filter to ensure candles have enough range to trade, and an optional Signal Cooldown to prevent repetitive labels during volatile sessions. Indicator
Veyra Shift Ledger [JOAT]Veyra Shift Ledger
Introduction
Veyra Shift Ledger is an open-source execution-context ledger that combines trend, pressure, structure, auction location, displacement, and volatility state. It also draws qualified supply and demand zones anchored to confirmed swing memory.
The indicator is designed to show when several independent context layers align, while keeping signals confirmed and visually organized.
Core Concepts
1. Trend and Regime
Fast, mid, and slow EMAs define trend alignment. ADX, RSI, MACD, and VWAP context contribute to directional quality.
2. Pressure Engine
Signed candle body, range location, and volume are used to estimate bid or ask pressure.
3. Auction Location
Weighted price and deviation bands identify premium, discount, and value conditions.
4. Structure and Displacement
Confirmed pivots define swing memory. BOS, sweeps, and FVG-style gaps contribute to the structure side of the ledger.
5. Supply and Demand Zones
Zones are created only when quality gates pass. Demand zones anchor around confirmed pivot lows and supply zones anchor around confirmed pivot highs, with ATR-scaled height.
Features
Long and short ledger scores: Combines trend, momentum, pressure, structure, auction, and HTF context
Confirmed HTF filter: Optional higher-timeframe EMA uses confirmed previous HTF data
Supply/demand zones: Anchored to confirmed swing memory and ATR-scaled
Zone lifecycle: Zones change appearance when mitigated or invalidated
Execution rails: Optional educational entry, stop, and target projections
Dashboard: Shows scores, pressure, auction, structure, volatility, HTF, and trigger state
Input Parameters
EMA lengths control trend memory
Pressure and auction inputs control volume/weighted-price calculations
Pivot confirmation controls structure sensitivity
Score thresholds control signal selectivity
Risk inputs control optional rail projection
How to Use This Indicator
Step 1: Compare ledger scores
The dashboard shows whether long or short context has stronger evidence.
Step 2: Inspect zones
Supply and demand zones are contextual areas, not certain turning points.
Step 3: Watch mitigation state
Zone color changes help distinguish active, mitigated, and invalidated areas.
Indicator Limitations
Supply and demand zones are approximations from chart data
Pivot confirmation creates natural delay
Pressure is candle-derived and not true order book data
Execution rails are educational projections only
Originality Statement
Veyra Shift Ledger combines a multi-factor score ledger with swing-anchored supply/demand zones, auction context, pressure state, displacement logic, and zone lifecycle visualization.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Zones and scores can fail in live markets.
-Made with passion by jackofalltrades
Indicator
Indicator
Median ATR SD OscillatorMedian ATR SD Oscillator
Median ATR SD Oscillator is a trend-following volatility oscillator that measures the distance between price and two independent reference levels — an ATR band and a standard deviation band — both anchored to a percentile-based median. The asymmetric design uses different volatility measures for long and short signals, creating a natural bias toward staying in bullish trends longer while reacting quickly to breakdowns.
The result is an area oscillator that expands above zero in a confirmed bullish state and contracts below zero in a bearish state, with a white EMA line as a momentum confluence filter.
How It Works
A percentile median is calculated from a configurable price source — giving a robust, noise-resistant central reference level that adapts to recent price behavior.
Two independent volatility bands are then derived from this median:
ATR Band — median plus ATR multiplied by a configurable factor. The short condition uses the ATR band — price must fall below it to confirm a bearish state
SD Band — median plus the standard deviation of close. The long condition uses the standard deviation band — price must break above it to confirm a bullish state
Once a directional state is confirmed, the oscillator measures the distance between price and its reference level. An EMA of this distance acts as a confluence filter — the final signal only confirms when the distance is not only positive or negative but also above or below its own EMA, ensuring momentum is genuinely building in that direction.
Why This Approach Works
Most oscillators use a single volatility measure for both long and short signals. The Median ATR SD Oscillator deliberately uses two different measures — ATR for shorts and SD for longs — because they capture different market dynamics and create a natural asymmetry between entries and exits.
This asymmetric design reflects the structural reality of markets like crypto — price spends more time trending upward than downward. Longs require a statistically significant breakout above the SD band, while shorts only need price to fall back below the ATR band. The result is a system that stays in bullish trends longer while reacting quickly when momentum fades.
Settings
Median Source — Price source for the percentile median calculation (default: hl2)
Median Length — Lookback period for the percentile median (default: 63)
ATR Length — Lookback period for the ATR calculation (default: 4)
ATR Factor — Controls the width of the ATR band (default: 1.0)
SD Length — Lookback period for the standard deviation calculation (default: 29)
Use EMA — Enables the EMA confluence filter (default: true)
EMA Length — Lookback period for the EMA confluence filter (default: 35)
Use Bar Coloring — Colors bars based on the current state (default: true)
Color Background — Enables background coloring of the chart based on the current state (default: false)
Background Transparency — Controls the transparency of the background color (default: 85)
How to trade it
Long — when the oscillator expands above zero and the area turns blue, a bullish state has been confirmed. This is the signal to look for long entries or to hold existing long positions
Short / Cash — when the oscillator contracts below zero and the area turns red, the momentum has faded. This is the signal to exit longs, move to cash, or look for short entries depending on your strategy
EMA line — when the area is above the white EMA line momentum is building, when it crosses below momentum is weakening
Recommended Usage
Best used on the 1D timeframe for clean and reliable signal generation
Should not be used alone for trade entries — combine with an additional confirmation indicator for best results
The asymmetric ATR/SD design makes this oscillator particularly well suited for bullish-biased markets like crypto
Higher ATR Factor values make short exits more sensitive — lower values make them less reactive
Higher SD Length values create more stable long signals — lower values make them more reactive to short-term price movements
All signals are confirmed on bar close. Indicator
Nyx Transition Corridor [JOAT]Nyx Transition Corridor
Introduction
Nyx Transition Corridor is an open-source probabilistic regime corridor. It estimates whether the current bullish, bearish, or neutral state has recently tended to persist, then draws adaptive volatility corridors around price. The indicator is built for context, probability, and controlled visualization rather than aggressive signal clutter.
Core Concepts
1. Regime State
The script classifies each bar as bullish, bearish, or neutral using EMA alignment, adaptive basis location, and return behavior.
2. Rolling Transition Model
Recent state transitions are counted to estimate continuation probability for the current state.
pBullBull = math.sum(fromBull * toBull, transitionLen) / math.sum(fromBull, transitionLen)
3. Adaptive Basis
The basis reacts faster when price movement is efficient and slower when the market is choppy.
4. Probability Corridor
ATR, volatility rank, and continuation probability determine the corridor width. Outer rails identify stretched conditions.
5. Compact Execution Rails
Optional small rails mark educational entry, stop, and targets when a probability reclaim or continuation event occurs.
Features
Three-state regime model: Bull, bear, and neutral states
Transition probability: Rolling persistence estimate for current state
Adaptive basis: Efficiency-weighted smoothing
Volatility-ranked corridor: Bands expand and contract with market stress
Confirmed HTF filter: Optional higher-timeframe EMA uses confirmed previous HTF data
Compact trade rails: Smaller educational rails to reduce chart obstruction
Dashboard: Shows probabilities, spread, efficiency, volatility rank, and HTF state
Input Parameters
Adaptive basis length controls centerline memory
Transition memory controls probability stability
Continuation threshold controls signal selectivity
Rail settings control optional educational projections
How to Use This Indicator
Step 1: Read the regime
The dashboard shows whether the model is bullish, bearish, or neutral.
Step 2: Compare probabilities
Large spreads between bull and bear odds indicate clearer directional context.
Step 3: Use the corridor
The corridor shows where price is trading relative to the adaptive probability field.
Indicator Limitations
Transition probabilities are historical estimates, not forecasts
Neutral markets can persist even when price briefly crosses the basis
The optional rails are visual projections and not trading advice
Originality Statement
Nyx Transition Corridor combines a state-transition model, efficiency-adjusted basis, volatility-ranked width, confirmed HTF filtering, and compact execution visuals. Its purpose is to map probabilistic state context, not to duplicate a standard moving-average band.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Probability estimates are based on historical state transitions and do not predict future behavior.
-Made with passion by jackofalltrades
Indicator
Indicator
Helios Institutional Synthesis Strategy [JOAT]Helios Institutional Synthesis Strategy
Introduction
Helios Institutional Synthesis Strategy is an open-source Pine v6 strategy that integrates regime detection, trend bias, VWAP location, premium/discount context, liquidity sweeps, volatility gating, structured ATR stops, target levels, trailing exits, time exits, and visual trade-zone boxes.
The strategy is designed as a realistic testing framework, not a performance promise. It uses confirmed-bar triggers, process-on-close order handling, commission, slippage, risk sizing, and daily risk guard logic. The default settings were made active enough to generate more samples across timeframes while still keeping basic risk controls in place.
Core Concepts
1. Regime and Trend Bias
An adaptive baseline, EMA momentum, DMI/ADX, and volatility score determine whether the market is bullish, bearish, or ranging. Long setups require bullish context, and short setups require bearish context unless other confluence factors compensate.
2. VWAP and Premium/Discount Context
The strategy compares price to session VWAP and to a rolling premium/discount range. This helps distinguish continuation entries from recovery or rejection setups.
3. Liquidity and Retest Triggers
Confirmed sweeps, daily level reclaims/rejections, VWAP bounces, baseline crosses, and channel reclaim/rejection logic can contribute to entries. This creates more than one path into a trade while still requiring a confluence score.
4. Volatility and Risk Gates
The strategy filters by volatility score, ATR percent of price, daily equity guard, and minimum planned R. These controls are included to avoid unbounded entries in abnormal conditions.
5. Structured Exits
Stops use ATR and recent key levels. Targets use ATR multiples. A trailing stop can tighten the exit as price moves, and a max-hold rule can close trades that remain open too long.
Default Strategy Properties
Initial capital: 100000
Commission: 0.01 percent
Slippage: 1 tick
Pyramiding: 0
Orders processed on close: true
calc_on_every_tick: false
Default risk per trade: 1.0 percent
Default minimum confluence score: 4 out of 8
Default cooldown: 4 bars
Default ATR stop multiple: 1.8
Default ATR target multiple: 2.8
Default trailing ATR multiple: 1.35
Default daily equity guard: 3 percent
Features
8-point confluence model: Combines regime, VWAP, premium/discount, momentum, volatility, sweeps, squeeze release, and HTF bias
Confirmed-bar entries: Long and short triggers use barstate.isconfirmed
HTF confirmation: Uses request.security() with lookahead off and previous higher-timeframe values
Risk-based sizing: Calculates quantity from equity, stop distance, and risk percentage
ATR stop and target: Structured stop/target logic with optional trailing behavior
Daily guard: Blocks new trades after a configured intraday equity drawdown threshold
Max-hold exit: Closes positions that exceed the configured bar count
Trade-zone boxes: Shows reward/risk boxes on the chart
Right-side risk rails: Labels active entry, stop, target, and R:R
Dashboard: Shows regime, position, confluence, risk gate, setup, volatility, VWAP sigma, liquidity, HTF bias, PD state, session, day guard, hold bars, stops, and key levels
Input Parameters
Core Engine:
Adaptive Baseline Length
Efficiency Lookback
ATR Length
ADX / DMI Length
Institutional Anchor Length
Confirmation Timeframe
Filters:
Enable Longs and Enable Shorts
Restrict to Session
Min Confluence Score
Cooldown Bars
Volatility score bounds
Risk Controls:
Risk percent per trade
ATR stop, target, and trailing multiples
Minimum planned R multiple
Max ATR percent of price
Daily equity guard percent
Max hold bars
How to Use This Strategy
Step 1: Start with a private draft
Before publishing results, test the strategy privately and verify the chart, settings, and description.
Step 2: Use realistic costs
The script defaults to 0.01 percent commission and 1 tick slippage. Adjust them to match the market being tested.
Step 3: Check sample size
Use enough historical data to evaluate whether the strategy has a meaningful number of trades. Avoid drawing conclusions from a small sample.
Step 4: Review the dashboard
The dashboard shows whether a blocked trade is caused by risk, volatility, session, confluence, or daily guard logic.
Strategy Limitations
Backtests are hypothetical and do not ensure future results
Performance can vary significantly by symbol, session, timeframe, and cost settings
The strategy may trade frequently on lower timeframes; costs and slippage matter
HTF confirmation uses non-lookahead requests, but higher-timeframe context can still evolve while a higher-timeframe bar is unfinished
Risk controls reduce some bad conditions but cannot remove market risk
Originality Statement
Helios Institutional Synthesis Strategy combines adaptive regime detection, VWAP sigma location, premium/discount context, liquidity sweep triggers, squeeze state, higher-timeframe confirmation, risk-based sizing, ATR exits, daily guard logic, time exits, and visual trade-zone mapping in one open-source Pine v6 strategy. Its purpose is to test a multi-factor decision process with transparent components rather than present a black-box signal system.
Disclaimer
This strategy is for educational and informational use only. It is not financial advice, and backtested results do not ensure future performance. Trading involves substantial risk of loss. Always test with realistic commissions, slippage, and position sizing before making any decision.
-Made with passion by jackofalltrades
Strategy
Helios Volatility Atlas [JOAT]Helios Volatility Atlas
Introduction
Helios Volatility Atlas is an open-source regime and volatility mapping indicator. It combines an adaptive baseline, DMI/ADX trend strength, volatility scoring, VWAP sigma bands, premium/discount structure, squeeze detection, retest zones, right-side level rails, and a top-right dashboard.
The problem Helios addresses is market context. A trend signal means something different in compression than it does during expansion. A retest means something different near discount than it does at an outer volatility channel. Helios brings those layers into one chart so users can interpret price action with regime, volatility, and location in view.
Core Concepts
1. Adaptive Baseline
The baseline blends an EMA-style trend component with an efficiency-ratio adaptive component. When price moves efficiently, the adaptive side reacts more. During choppy movement, the baseline becomes slower and more stable.
2. Volatility Score
ATR is compared against its own moving average and standard deviation. The result is normalized into a 0-100 volatility score so the dashboard can distinguish low, moderate, and high volatility states.
3. Institutional Channels
Helios draws a channel around a mean using ATR-based distances. Inner channels describe normal volatility, while outer pockets mark more extended price areas where reversion or continuation context may matter.
4. Squeeze and Expansion State
The squeeze model compares a Bollinger-style width against a Keltner-style width. When compression releases, the chart highlights a transition from low-energy conditions into expansion.
5. Retest Zones and Rails
Confirmed retests can create projected zones. Right-side rails label important live references such as baseline, VWAP, channels, premium/discount levels, and previous day levels.
Features
Adaptive baseline: Blends trend-following and efficiency-aware smoothing
Volatility score: Converts ATR expansion/compression into a dashboard value
Trend cloud: Fills the space between baseline and VWAP
VWAP sigma bands: Shows price stretch around VWAP
Premium/discount map: Uses a rolling anchor range with equilibrium, discount, and premium levels
Squeeze detection: Highlights compression and release states
Retest zones: Projects confirmed bullish and bearish retest areas
Right-side rails: Labels baseline, VWAP, channels, premium/discount, and day levels
Theme presets: Includes Helios, Consensus Aqua, Sentinel Neon, and Cobalt Risk color families
Top-right dashboard: Shows regime, bias, volatility, squeeze, channel, VWAP sigma, price state, and key levels
Input Parameters
Core Engine:
Adaptive Baseline Length
Efficiency Lookback
ATR Length
ADX / DMI Length
Volatility Window
Volatility System:
Channel Memory
Base Channel ATR Multiple
Outer Channel ATR Multiple
Squeeze Length
Squeeze BB and KC multipliers
Display:
Show Trend Cloud
Show VWAP Sigma Bands
Show Retest Zones
Show Right-Side Level Rails
Theme Preset
Dashboard Text Size
How to Use This Indicator
Step 1: Read the regime
The dashboard classifies the current state as bullish, bearish, expansion, or range.
Step 2: Check volatility
Use the volatility score and squeeze row to decide whether the market is compressed or expanding.
Step 3: Compare price to VWAP and channels
VWAP sigma and ATR channels show whether price is near value, stretched, or reverting from an outer area.
Step 4: Use retest zones as context
Retest zones mark recent confirmed reactions. They are contextual levels, not automatic entries.
Indicator Limitations
Adaptive baselines can lag during sudden reversals
Squeeze release does not define direction by itself
Retest zones can fail in strong momentum conditions
Higher volatility symbols may require adjusted ATR/channel settings
Originality Statement
Helios Volatility Atlas combines adaptive trend state, DMI/ADX confirmation, ATR volatility scoring, VWAP sigma distance, squeeze detection, premium/discount location, projected retest zones, and right-edge rails into a single open-source Pine v6 regime atlas. The components are designed to work as one context engine, not as a loose mashup.
Disclaimer
This script is for educational and informational use only. It is not financial advice and does not predict future price direction. Use independent analysis and risk management.
-Made with passion by jackofalltrades
Indicator
Fractional CUSUM Regime Filter [Jamallo]🔹 Intro
The Fractional CUSUM Regime Filter is a quantitative trend and volatility channel indicator designed to identify structural market regimes with high stability. Unlike traditional filters that suffer from lag or whipsaw signals, this indicator applies a dual-layered preprocessor combining Lopez de Prado’s Fixed-Window Fractional Differentiation (FFD) with a classic Cumulative Sum (CUSUM) statistical trigger.
🔹 Break down
Fractional Differentiation (FFD) : Stationarizes pricing input while retaining long-term historical memory (controlled by the "d" parameter).
Classic CUSUM Filter : Accumulates deviations from a rolling baseline relative to current volatility. When cumulative deviation exceeds the threshold multiplier (h), a new regime change is triggered, and the baseline steps dynamically to the new price level.
Vol-Adjusted Percentile Bands : Linear interpolation percentiles of price deviation relative to the stepped baseline. The distances are "locked" and only update on CUSUM regime triggers to prevent wobbly bands.
🔹 Visual Guide: Indicator Anatomy
Here we have the structure of the indicator, including the CUSUM baseline, the 68% inner percentile band, and the 95% outer percentile band.
How to use: Mean Reversion (Pullbacks to the Mean)
The channel boundaries represent statistical extremes. When the price is pushed outside the bands, it is mathematically overextended and highly likely to revert back to the CUSUM baseline.
Long Setup (Pullbacks in Bullish Trend): During a green CUSUM uptrend, watch for price to pull back to the lower bands ("micro pullback") and enter as it heads back up to the baseline mean.
Short Setup (Pullbacks in Bearish Trend): During a red CUSUM downtrend, watch for price to rally into the upper bands ("micro pullback") and enter as it reverts down to the baseline mean.
🔹 How to use: Trend Following & Risk Management
The indicator is designed to capture sustained macro trends while providing clear risk parameters.
Entering on Breakthroughs : Enter when the BUY/SELL signal flags appear (indicating a new CUSUM regime shift).
Stop Loss Placement : Place stop loss orders just below the opposite outer band or below the stepped baseline.
Letting Winners Run : Ride the trend as long as the CUSUM baseline maintains its colored regime state (Green for Long, Red for Short).
🔹 Settings Parameters
d (0.01 - 0.99) : Differentiation order. Lower values retain more historical memory; higher values approach first-difference.
CUSUM Drift & Threshold : Controls baseline sensitivity to regime changes.
Percentile Lookback & Targets : Set the statistical width of the inner and outer boundaries.
Indicator
Intermarket Confluence Engine | AnonycryptousIntermarket Confluence Engine (ICE) | Anonycryptous
Description & user manual
Why this indicator exists
Most indicators analyze one asset in isolation. They look at price, momentum, volume, or volatility — all on the same chart, all based on the same data feed. That is useful, but it leaves out the context that drives markets at a deeper level: the relationship between assets, the macro regime, the direction of capital flow across instruments.
ICE approaches the problem differently.
Instead of analyzing a single price series, it takes two assets and computes their ratio. That ratio becomes the subject of analysis — not the individual prices. The result is a view of relative strength, regime state, and intermarket context that no single-asset indicator can produce.
It runs eight independent analytical engines on that ratio. Each engine returns a directional score. Those scores are weighted based on the selected asset class and combined into a single confluence number from -10 to +10. The dashboard shows the engine breakdown, the macro state, and the current statistical position of the ratio in its historical distribution — all in one compact panel.
ICE is not a signal indicator. It does not tell you when to buy or sell. It tells you what the current relationship between two assets looks like across eight independent dimensions, and how much those dimensions agree with each other.
Important notice
ICE does not generate trading signals.
It does not tell you when to buy or sell.
It does not predict market direction.
It does not guarantee any outcome.
All trading decisions remain entirely with the user.
Always apply your own judgment and manage your own risk.
1. Overview
ICE is a ratio-based intermarket confluence scoring system. It takes two configurable assets, computes their price ratio (Asset A divided by Asset B), and runs that ratio through eight analytical engines simultaneously.
The nine engines are:
- Relative strength — how much Asset A is outperforming or underperforming Asset B on a rate-of-change basis
- Trend — EMA structure and slope direction of the ratio
- Momentum — volume-weighted RSI and MACD histogram alignment on the ratio
- Volatility — Bollinger Band width, ATR percentile, and squeeze state of the ratio
- Statistical extremes — Z-score and historical percentile position of the ratio
- Macro regime — direction of DXY, VIX, and 10-year Treasury yields
- Liquidity — yield curve proxy using 10-year yield rate of change
- Intermarket correlation — rolling correlation between the ratio and each macro feed
- Volume participation — OBV slope and relative volume confirmation on both assets
Each engine is weighted based on the selected asset class. A custom weighting mode is available for manual control. All weights are normalized so the final score always maps to the -10 to +10 range regardless of class selection.
The chart displays the ratio as a line with an EMA stack (21, 50, 200), Bollinger Bands, and statistical deviation bands based on Z-score distance from the historical mean. Signals fire when confluence crosses configurable thresholds. Divergence between the ratio and its volume-weighted RSI is detected mechanically and shown on the chart.
2. The ratio
2.1 What it represents
The ratio is simply the price of Asset A divided by the price of Asset B. If Asset A is gold (XAUUSD) and Asset B is silver (XAGUSD), the ratio is the gold/silver ratio — how many ounces of silver one ounce of gold can buy. If Asset A is NQ futures and Asset B is ES futures, the ratio represents the relative performance of tech versus the broad market.
The ratio rises when Asset A outperforms Asset B. It falls when Asset B outperforms Asset A. All eight engines work on this ratio, not on the underlying prices.
2.2 What is plotted
The ratio line is the primary visual element. It is colored gold when above its 50-period EMA and grey when below. The EMA stack (green for the 21, blue for the 50, white for the 200) shows the structural state of the ratio trend.
Two band systems are visible simultaneously:
Statistical deviation bands — based on Z-score. The upper band is the historical mean plus 2 standard deviations (configurable). The lower band is the mean minus 2 standard deviations. When the ratio is near or beyond these bands, the Statistical engine activates and the dashboard notes an extreme condition.
Bollinger Bands — a separate volatility-based band using a configurable period and multiplier. These bands are lighter and secondary to the statistical bands.
Squeeze markers appear as small squares along the statistical mean when the Bollinger Bands are contained inside the Keltner Channel — indicating compressed volatility and a potential breakout.
2.3 Signal markers
Signals are plotted directly on the ratio chart using triangles and circles. All markers use plotshape, not labels.
Large triangles up (green) — strong bull confluence (score above +6)
Large triangles down (red) — strong bear confluence (score below -6)
Small triangles up (faded green) — moderate bull confluence (score between +3.5 and +6)
Small triangles down (faded red) — moderate bear confluence (score between -3.5 and -6)
Cyan circles — bullish momentum divergence aligned with positive score
Orange circles — bearish momentum divergence aligned with negative score
Purple squares — active volatility squeeze
3. The eight engines
3.1 Relative strength engine
This engine measures how much Asset A is outperforming Asset B on a rate-of-change basis. It computes the ROC of each asset independently over a configurable period (default 14) and subtracts them to get a delta. That delta is then Z-score normalized over a longer lookback (default 50) to assess whether the current outperformance is historically significant.
The engine also tracks the velocity of the ratio itself — the first derivative of the ratio — and whether the ratio is above its own EMA.
Score: +1 when the RS Z-score is above 0.5 and the ratio is above its EMA. -1 when the RS Z-score is below -0.5 and the ratio is below its EMA. 0 otherwise.
The dashboard shows the raw RS Z-score in the state section so you can see how far from neutral the relative strength is reading.
3.2 Trend engine
The trend engine evaluates the EMA alignment of the ratio across three periods (21, 50, 200), the slope direction using linear regression, and optionally a higher timeframe EMA confirmation.
A full bull stack is when EMA 21 is above EMA 50 and EMA 50 is above EMA 200, combined with a positive slope. A full bear stack is the reverse. Transitional states occur when the stack is broken but slope still has a direction.
The HTF trend filter uses a configurable higher timeframe (default weekly) and checks whether the chosen asset is above its 50-period EMA on that timeframe. When enabled, the trend engine only scores positively if the HTF also confirms.
Score: +1 for confirmed bull trend. -1 for confirmed bear trend. 0 for compression or transition.
The trend state shown in the dashboard (Expansion, Contraction, Transitional, Compression) reflects the combination of stack state and slope direction.
3.3 Momentum engine
The momentum engine uses a volume-weighted RSI applied to the ratio. The weighting uses the combined average volume of both assets, normalized by its own moving average. This is the same architecture as VW RSI Pro — gains and losses are scaled by relative volume before the RSI calculation, so bars with above-average volume have more influence on the RSI than bars with below-average volume.
Alongside the VW RSI, the engine computes MACD histogram acceleration (the change in histogram value, not just its level). This distinguishes between momentum that is building and momentum that is present but decelerating.
Score: +1 when VW RSI is above 52 and MACD histogram is positive. -1 when VW RSI is below 48 and MACD histogram is negative. 0 otherwise.
The VW RSI value is shown in the state section of the dashboard. Values above 55 are colored green, below 45 red, between them grey.
3.4 Volatility engine
The volatility engine assesses whether the ratio is in a phase of compression or expansion, and which direction expansion is occurring.
It computes Bollinger Band width relative to its 100-bar average — widening bands indicate expansion, narrowing bands indicate compression. ATR percentile rank over a configurable lookback (default 100 bars) provides a second volatility measure. A squeeze is identified when the Bollinger Bands are fully contained within the Keltner Channel.
Score: +1 when volatility is expanding and the ratio is above the Bollinger midline, or when a squeeze releases upward. -1 for the same conditions in the downward direction. 0 during compression or neutral volatility states.
The vol state (Squeeze, Breakout, Expansion, Compression, Neutral) is shown in the dashboard state section. Squeeze appears in purple, breakout in gold, expansion in the configured bull color.
3.5 Statistical extremes engine
This engine measures where the current ratio stands within its own historical distribution. It computes a Z-score of the ratio over a configurable lookback (default 50) and a historical percentile rank over a longer window (default 252 bars, approximately one year of daily data).
When the ratio is more than 1.5 standard deviations above its mean and above the 80th percentile, it is classified as historically expensive — a potential mean reversion candidate to the downside. When it is more than 1.5 standard deviations below its mean and below the 20th percentile, it is historically cheap — a potential mean reversion candidate to the upside.
Score: +1 at extreme lows (below mean, below 20th percentile). -1 at extreme highs (above mean, above 80th percentile). 0 within normal range.
The Z-score and historical percentile are shown in the dashboard state section. A gold highlight on the Z-score indicates an active extreme condition.
The mean reversion probability displayed in the extended panel is a normalized version of the absolute Z-score distance — a rough proxy for how far the ratio has stretched from its historical center. It is not a probability in the statistical sense, but a relative measure of extension.
3.6 Macro regime engine
The macro regime engine uses three external data feeds — DXY (dollar index), VIX (volatility index), and TNX (10-year Treasury yield) — loaded via request.security(). It evaluates the trend direction of each feed relative to a smoothed EMA (configurable length, default 20) and classifies the current macro environment.
The global regime classification (Risk-On / Risk-Off / Mixed) appears in the dashboard header. It is always based on the same three-signal count regardless of asset class: VIX level, DXY trend, and yield direction.
The macro score, however, is class-aware. Each asset class has its own logic:
Gold / Silver — risk-off conditions (elevated VIX, falling yields, falling dollar) favor Asset A (gold). Risk-on conditions (low VIX, rising yields, rising dollar) favor Asset B (silver outperforms on industrial demand). Score is +1 for acute risk-off, -1 for sustained risk-on.
Crypto — DXY direction is the primary gatekeeper. Falling DXY and falling yields are bullish for crypto. Rising DXY and rising yields are bearish. VIX provides a third signal. Two of the three conditions must align for a score to fire.
Forex — trend-following regime logic. Risk-on environments favor the ratio direction, risk-off favors the reverse.
Indices — same structure as Forex. Risk-on = positive bias.
Commodities — DXY-led. Falling dollar supports commodity ratios.
Score: +1 for regime favorable to Asset A. -1 for regime favorable to Asset B. 0 for mixed.
3.7 Liquidity engine
The liquidity engine uses the 10-year Treasury yield (TNX) rate of change as a proxy for liquidity conditions. Falling long-term yields indicate looser financial conditions — lower cost of capital, more risk appetite. Rising yields indicate tightening.
The TNX rate of change is computed over 20 bars and smoothed with a 10-bar EMA. When the smoothed ROC is below -0.1, conditions are classified as expanding. Above +0.1, contracting.
Score logic is class-aware:
- Gold / Silver — expanding liquidity (falling yields) is positive for the ratio since gold benefits more from low rates. Contracting is negative.
- Crypto — same direction. Loose liquidity benefits risk assets.
- Forex — inverted. Rising yields support yield-differential-driven pairs.
- Other classes — expansion is positive.
Score: +1 for favorable liquidity, -1 for unfavorable, 0 for neutral.
3.8 Intermarket correlation engine
This engine computes the rolling Pearson correlation between the ratio and each macro feed (DXY, VIX, TNX) over a configurable window (default 30 bars). It then assesses whether the current correlations match the expected structural behavior for the selected asset class.
For the Gold/Silver ratio, for example, historically the ratio is positively correlated with VIX (risk-off pushes gold relative to silver) and negatively correlated with DXY (weaker dollar benefits silver less). When those correlations are in place and above a threshold (±0.15), the engine confirms the macro alignment.
A correlation shift is detected when the sign of a correlation flips compared to 10 bars ago — this is flagged in the dashboard as a regime change signal.
Score: +1 when correlations confirm expected behavior for Asset A outperformance. -1 when they confirm the reverse. 0 when correlations are below threshold or mixed.
3.9 Volume participation engine
This engine measures whether the volume behind the ratio's current move confirms its direction. It uses two inputs: the relative volume difference between Asset A and Asset B, and the slope of the on-balance volume (OBV) calculated on the ratio.
The relative volume comparison checks whether Asset A is attracting more volume than Asset B relative to their combined average. When Asset A draws disproportionately more volume, it indicates institutional interest in the primary asset. The OBV slope uses a 20-bar linear regression to determine whether cumulative directional volume is rising or falling.
A bullish confirmation requires the OBV slope to be positive, the ratio to be above its 21 EMA, and Asset A to have higher relative volume. A bearish confirmation requires the reverse. When volume diverges from price direction — OBV falling while price rises, or vice versa — this is flagged in the extended panel as a volume divergence warning.
Score: +1 when volume participation confirms the ratio move upward. -1 when it confirms downward. 0 when volume is inconclusive or mixed.
4. Adaptive weighting
Each engine returns -1, 0, or +1. Each score is multiplied by the engine's weight for the selected asset class. The sum of all nine weighted scores is normalized against the total possible weight to produce the final confluence score on a -10 to +10 scale.
Asset class presets:
Gold / Silver — statistical extremes and macro regime are weighted most heavily (14 each). This reflects the GSR's mean-reverting nature and strong sensitivity to macro conditions. Volume participation carries moderate weight — on the GSR, volume confirmation is useful but less decisive than macro state.
Crypto — liquidity and momentum are weighted most heavily (14 each). Volume participation also carries elevated weight, since capital rotation between an asset and stablecoins is directly visible in relative volume.
Forex — trend and correlation are weighted most heavily (14 each). Currency pairs respond to trend conditions and intermarket relationships more reliably than statistical extremes.
Indices — momentum and liquidity are weighted most heavily (14 each). Volume participation also carries elevated weight — index futures moves backed by strong volume are more reliable than low-volume drifts.
Commodities — relative strength and volatility are weighted most heavily (14 each). Volume participation carries moderate weight since commodity ratio moves are often driven by volume imbalances between the two assets.
Custom — all nine weights are individually configurable from 0 to 20.
The confidence percentage shown in the dashboard is the spread between the normalized bull and bear score components — a measure of how much the engines agree rather than merely how many fire.
5. Dashboard
The dashboard is a single compact panel with four columns and thirteen rows. It shows the complete scoring state, engine breakdown, and market context in one place.
Header row — indicator name, asset class, confluence label, and score out of 10. The header color reflects the net score direction.
Confidence and regime row — confidence percentage and the global macro regime (Risk-On / Risk-Off / Mixed).
Engine scores — eight engines displayed two per row across four columns. Each engine shows its label and its weighted score with direction indicator. A green upward triangle indicates a positive contribution. A red downward triangle indicates a negative contribution. A grey dot indicates a neutral score.
State section — trend state, volatility state, VW RSI value, and Z-score. The trend state label (Expansion, Contraction, Transitional, Compression) reflects the combination of EMA alignment and slope. The vol state (Squeeze, Breakout, Expansion, Compression, Neutral) reflects the Bollinger/Keltner relationship.
Macro feeds — DXY direction, VIX level, 10-year yield direction, and current divergence state.
Brand footer — version reference.
The extended macro panel (disabled by default) can be enabled in settings for a second panel showing full correlation values, ATR percentile, statistical state detail, OBV slope, volume participation score, volume divergence flag, and liquidity state.
6. Asset pair configuration
6.1 Gold/Silver ratio (GSR)
The gold/silver ratio is the primary design case for ICE. It measures how many ounces of silver are required to buy one ounce of gold. Historically the ratio has ranged between 15 and 120. It is mean-reverting over long cycles but can trend persistently for months or years.
Recommended setup:
- Asset A: OANDA:XAUUSD
- Asset B: OANDA:XAGUSD
- Asset class: Gold / Silver
The statistical extremes engine is particularly relevant here. When the ratio is near historical highs (above the 80th percentile, Z-score above 1.5), silver has historically outperformed gold significantly over the following months. When near historical lows, gold has tended to recover its premium.
The macro regime engine is also central. Acute risk-off events (2008, 2020) spike the GSR rapidly as gold outperforms. Sustained risk-on environments with rising yields and industrial demand tend to compress it.
6.2 Crypto setups
For crypto ratio analysis, stablecoin dominance (CRYPTOCAP:USDT.D) as Asset B provides a direct view of capital rotation between an asset and cash equivalents. When the ratio rises, the asset is gaining relative to stablecoins — capital is flowing in. When it falls, capital is rotating out.
Recommended setups:
- BINANCE:BTCUSDT / CRYPTOCAP:USDT.D — Bitcoin vs stablecoin dominance
- BINANCE:SOLUSDT / CRYPTOCAP:USDT.D — SOL vs stablecoin dominance
- BINANCE:ETHUSDT / CRYPTOCAP:USDT.D — ETH vs stablecoin dominance
- Asset class: Crypto for all of the above
BTC.D (Bitcoin dominance, CRYPTOCAP:BTC.D) as Asset B can be used to measure altcoin performance relative to Bitcoin specifically — useful for identifying altseason conditions.
6.3 NQ futures setups
For Nasdaq and MNQ trading, ratio analysis provides directional and regime context.
Recommended setups:
- CME_MINI:NQ1! / CME_MINI:ES1! — Nasdaq vs S&P 500. When this ratio rises, tech is outperforming the broad market. A falling ratio suggests defensive rotation or underperformance of growth. Asset class: Indices.
- CME_MINI:NQ1! / CME_MINI:RTY1! — Nasdaq vs Russell 2000. Large-cap growth vs small-cap. Risk appetite proxy. Asset class: Indices.
- CME_MINI:NQ1! / TVC:DXY — NQ relative to dollar strength. Strong inverse relationship historically. Asset class: Indices.
6.4 Precious metals and commodities
- OANDA:XAUUSD / TVC:DXY — gold relative to dollar. One of the cleanest inverse relationships in macro markets. Asset class: Commodities or Gold/Silver.
- OANDA:XAUUSD / CME_MINI:ES1! — gold vs equities. Risk-off proxy. When this ratio rises, gold is outperforming stocks. Asset class: Commodities.
- TVC:USOIL / TVC:NATGAS — oil vs natural gas relative value. Asset class: Commodities.
6.5 Forex setups
For currency pairs, use the pair itself as a ratio — Asset A as the base currency ETF or index, Asset B as the quote. Alternatively, use currency index feeds directly.
- FX:EURUSD as a direct entry (ratio of EUR to USD)
- TVC:DXY / FX:EURUSD — dollar index vs euro. Asset class: Forex.
7. Macro feeds
The three macro feeds are loaded via request.security() and must resolve on PulseWire.
Default symbols:
- DXY: TVC:DXY
- VIX: CBOE:VIX
- 10-year yield: TVC:TNX
These can be changed in the Macro Feeds settings group if alternative data sources are preferred. Each feed can be individually disabled — if all three are disabled, the macro regime, liquidity, and correlation engines return neutral (0) scores.
On lower timeframes (1m, 3m), macro feeds may have limited bar history, which can cause some engines to return neutral until sufficient data is loaded. From 15m and higher, all engines should be fully active. On very low timeframes, the statistical engines also require a minimum number of bars before the lookbacks are satisfied.
8. How to use
8.1 Reading the score
The confluence score on a -10 to +10 scale communicates direction and intensity simultaneously. It does not communicate timing.
A score of +7 with 70% confidence means six or seven engines are aligned in a bullish direction for Asset A relative to Asset B, with the weighted agreement being high. It does not mean a trade should be entered immediately — it means the current relative conditions strongly favor Asset A.
A score near 0 with low confidence means the engines are split. This is not a bearish signal — it is the absence of a clear signal. In practice, scores between -3 and +3 with confidence below 40% suggest the ratio is in a mixed or transitional regime.
8.2 Using the score with price action
ICE works on the ratio — not on the underlying price. To apply it to a trade on the underlying asset, you need to interpret the score in context.
On a BTC/USDT.D ratio chart with a score of -7, the ratio is falling — BTC is losing ground relative to stablecoin dominance. This is a macro tailwind for a bearish BTC view. It does not tell you where to enter or where to put your stop. It tells you the broader relative conditions are bearish.
Combine ICE with a price-action tool, a structure indicator, or an entry system applied to the actual trading instrument. ICE provides the regime and relative context. The entry decision remains with the user.
8.3 Divergence signals
When the ratio makes a lower low but the VW RSI makes a higher low, a bullish divergence is detected. When the ratio makes a higher high but the VW RSI makes a lower high, a bearish divergence is detected. These are mechanical detections using pivot analysis.
Divergence signals that align with the net confluence score carry more weight. A bullish divergence on a ratio that is already scoring positively on four or five engines is a stronger condition than a divergence in an otherwise neutral scoring environment. Cyan circles mark bull divergence, orange circles mark bear divergence.
8.4 Squeeze and volatility breakouts
When the volatility engine identifies a squeeze (Bollinger Bands inside the Keltner Channel), a purple square appears along the statistical mean line. This indicates compressed volatility and an elevated probability of a significant directional move.
When the squeeze releases, the volatility engine contributes its score in the direction of the breakout. Combined with trend and momentum alignment, a squeeze release can produce a rapid score shift. These moments are marked on the chart and flagged in the dashboard vol state row.
8.5 Statistical extremes
The statistical engine is most useful on the Gold/Silver ratio and other fundamentally mean-reverting pairs. When the Z-score exceeds 1.5 and the ratio is in the top 20% of its historical range, the statistical engine scores negatively — signaling that the ratio has historically tended to revert from this level.
This is not a timing signal. The ratio can remain at extremes for weeks or months. The statistical engine scores the degree of extension, not the moment of reversal. Use it alongside momentum and trend engines to assess whether the extreme is beginning to resolve.
9. Settings reference
Asset configuration
- Asset A — the primary asset. Default: XAUUSD.
- Asset B — the secondary asset. Default: XAGUSD. The ratio is Asset A divided by Asset B.
- Plot ratio line — toggles the main ratio line on the chart.
- Plot ratio EMAs — toggles the 21/50/200 EMA stack on the ratio.
- Plot std dev bands — toggles the statistical deviation bands and Bollinger Bands.
Asset class and weighting
- Asset class — selects the weighting preset. Options: Gold/Silver, Crypto, Forex, Indices, Commodities, Custom.
- Individual weight inputs — only active in Custom mode. Each engine can be weighted from 0 to 20.
Macro feeds
- Use DXY / VIX / TNX — individual toggles for each macro feed.
- DXY / VIX / TNX symbol — configurable symbols. Defaults: TVC:DXY, CBOE:VIX, TVC:TNX.
- Macro smoothing — EMA length for the macro feed trend detection. Default 20.
Relative strength engine
- ROC length — rate of change period for both assets. Default 14.
- RS EMA length — EMA applied to the ratio for trend confirmation. Default 21.
- RS Z-score lookback — lookback for normalization of the RS delta. Default 50.
Trend engine
- Fast / Slow / Macro EMA — the three EMA periods for the ratio. Defaults: 21, 50, 200.
- MTF trend filter — enables the higher timeframe confirmation gate.
- HTF timeframe — the timeframe used for the HTF EMA check. Default weekly.
Momentum engine
- RSI length — period for the VW RSI calculation. Default 14.
- Volume smoothing — SMA length for volume normalization. Default 14.
- Volume weighted RSI — enables volume weighting on the RSI. Default on.
- MACD fast / slow / signal — MACD parameters applied to the ratio. Defaults: 12, 26, 9.
Volatility engine
- BB length / BB multiplier — Bollinger Band parameters. Defaults: 20, 2.0.
- ATR length — period for ATR calculation. Default 14.
- ATR percentile lookback — historical window for ATR percentile ranking. Default 100.
- Squeeze KC length / multiplier — Keltner Channel parameters for squeeze detection. Defaults: 20, 1.5.
Statistical extremes engine
- Z-score lookback — window for Z-score calculation. Default 50.
- Percentile lookback — historical window for percentile ranking. Default 252 (approximately one year of daily data).
- Z-score extreme threshold — standard deviations from mean required to classify as extreme. Default 1.5.
Correlation engine
- Correlation window — rolling window for Pearson correlation. Default 30.
Visuals
- Bull / bear / neutral color — configurable colors for all directional elements.
- Ratio line color — color of the main ratio line.
- Show score background — colors the pane background faintly by net score direction.
- Background transparency — transparency level for the score background. Default 93.
Dashboard
- Show dashboard — master toggle. Default on.
- Position — Top Left, Top Right, Bottom Left, Bottom Right. Default Bottom Right.
- Size — Tiny, Small, Normal. Default Tiny.
- Show extended macro panel — enables a second panel with full correlation, volume, and statistical detail. Default off. Recommended for desktop only.
10. Notes
- ICE operates on a ratio of two assets. If either asset has no data on the current chart timeframe, the ratio will be unavailable and the engines will not fire. Ensure both symbols resolve correctly in PulseWire before interpreting the dashboard.
- The macro feeds (DXY, VIX, TNX) are loaded separately via request.security(). On lower timeframes, the feed data may require a few bars to warm up before producing stable readings. All engines should be fully active from the 15m timeframe and above.
- The volume used by the momentum engine is the combined average of both asset volumes. On ratio pairs where one or both assets have zero or unavailable volume (such as some index feeds), the volume-weighted RSI falls back to an unweighted RSI automatically.
- All statistical calculations (Z-score, percentile rank) require a minimum number of bars equal to the lookback period. On charts with limited history or very short timeframes, these engines may return neutral until sufficient bars are loaded.
- The correlation engine requires both assets to have non-constant price series over the correlation window. On very stable or pegged assets, correlation may be undefined and the engine returns neutral.
- ICE does not repaint. All scores and signals are based on confirmed bar data.
- The indicator is designed for ratio analysis. It can technically be used with a single asset by setting Asset B to a constant reference (such as a stablecoin or index), but it was built around the two-asset ratio concept and performs best in that context.
11. Disclaimer
This indicator is provided for educational and informational purposes only.
All outputs are based on historical price data and mathematical calculations.
Past behavior does not guarantee future results.
Trading involves substantial risk of loss.
Use at your own discretion.
Indicator
Dynamic Range RSI [DefinedEdge]🔍 OVERVIEW
Really excited to release this one. I've been working on this for a while and it solves something that always bugged me about RSI: the fixed lookback period. Markets don't move at one speed, so why should your oscillator?
Dynamic Range RSI rethinks the standard RSI by replacing the fixed lookback with a volatility-adaptive engine. The indicator reads the current ATR regime and automatically adjusts its period. Shorter when markets are volatile, longer when they're quiet. No manual switching, no lag when it matters.
It also layers in divergence detection and a higher-timeframe confluence ribbon so you're not trading the oscillator in isolation.
⚙️ HOW IT WORKS
The core calculation uses a range-normalized momentum formula instead of standard RSI math. Price changes are weighted by the current high-low range, which makes the output cleaner during trending moves and less prone to false signals during chop.
The adaptive length is driven by an ATR ratio (fast ATR vs slow ATR). When volatility spikes, the RSI period compresses toward the minimum. When volatility drops, it stretches toward the maximum. Responsive during breakouts, smooth during consolidation.
🎯 FEATURES
→ ATR-adaptive RSI length (user-defined min/max range)
→ Range-normalized momentum calculation
→ 4 smoothing methods: EMA, SMA, RMA, TMA
→ Automatic divergence detection (pivot-based, configurable lookback)
→ Higher-timeframe confluence ribbon (auto or manual HTF selection)
→ Signal line crossover dots filtered to OB/OS zones only
→ 6 built-in alert conditions
→ Dynamic length visible in status line
📊 SIGNALS
• Green circles: signal line cross up inside oversold zone
• Red circles: signal line cross down inside overbought zone
• "Bull" labels: bullish divergence (price lower low, RSI higher low)
• "Bear" labels: bearish divergence (price higher high, RSI lower high)
• Background shading: HTF ribbon turns green/red when the higher timeframe agrees on OB/OS
💡 USAGE TIPS
Works on any market, any timeframe. For crypto I like the 4H. The adaptive length flexes between roughly 1 to 5 days of lookback which catches momentum shifts well. For scalping, 15min with HTF pulling from 4H gives solid confluence.
If the dynamic length stays pinned at minimum too often, bump the Min Length up to 8-10 to smooth it out. Indicator
Aegis Liquidity Ledger [JOAT]Aegis Liquidity Ledger
Introduction
Aegis Liquidity Ledger is an open-source liquidity pressure indicator built to answer a specific execution question:
Where is directional pressure being sourced, and where has that pressure already left behind a meaningful area of interest?
The script approaches that problem through two linked components:
a volatility-normalized pressure oscillator
shelf detection and origin-zone mapping
The oscillator explains whether participation is pushing in a bullish or bearish direction.
The shelf and origin logic explains where that pressure emerged from.
This separation is intentional.
It gives traders both the why and the where without forcing everything into a single overlay object.
Core Concepts
1. Composite Pressure Engine
The script blends multiple rate-of-change windows into one composite pressure signal.
Short-term impulse and slower campaign participation are both included so the output does not depend on a single lookback length.
2. Volatility-Normalized Thresholds
The pressure signal is measured against its own recent standard deviation rather than a fixed threshold.
This allows the expansion bands to adapt to the instrument and timeframe being viewed.
3. Shelf Detection
The script scans for repeated upper and lower interactions using body extremes and wick touches.
That makes the shelf logic more sensitive to areas where liquidity may have repeatedly rested.
4. Expansion Origin Zones
When pressure transitions through an adaptive bound on a confirmed bar, the script creates a source zone around the origin candle that preceded the release.
This zone remains relevant until price fully accepts through it.
5. Mitigation Logic
Shelves are not removed immediately.
They remain live until price fully accepts through the opposite side of the zone, after which they are visually de-emphasized as mitigated.
Features
Four-window pressure model: fast, medium, slow, and macro ROC blended together
Pressure smoothing: EMA smoothing controls oscillator responsiveness
Adaptive expansion thresholds: thresholds scale with recent pressure volatility
Normalized oscillator: pane output compresses pressure into an interpretable range
Demand and supply shelves: persistent shelf zones are drawn directly on the chart
Origin-zone logic: shelf creation is tied to confirmed expansion events
Touch and intensity tracking: shelf labels summarize interaction count and density
Mitigation state: zones are visually softened after full acceptance through them
Pressure-based candle coloring: optional chart bars reflect dominant liquidity pressure
Institutional dashboard: dashboard summarizes pressure, compression, shelf dominance, and state
Input Parameters
Pressure Engine
Fast ROC
Medium ROC
Slow ROC
Macro ROC
Pressure Smoothing
Expansion Threshold Multiplier
Liquidity Shelves
Shelf Window
Shelf Width ATR
Max Live Shelves Per Side
Show Expansion Origin Zones
Show Shelf Labels
Display
Show Pressure Fill
Show Expansion Glow
Show Zero Line
Color Candles By Pressure
Dashboard Position
Dashboard Size
How to Use This Indicator
Step 1: Read Pressure Before Reading Shelves
Start in the pane.
If the pressure engine is neutral or compressed, shelf interactions are more likely to behave as reaction zones than true continuation sources.
Step 2: Watch for Confirmed Expansion
New shelves matter most when they are created by a confirmed expansion through the adaptive threshold.
That is the moment the script treats the move as meaningful enough to register an origin.
Step 3: Distinguish Live From Mitigated Zones
Fresh shelves are stronger contextual references than mitigated shelves.
Once a zone has been fully accepted through, it should be treated as reduced context rather than untouched inventory.
Step 4: Compare Upper and Lower Density
The interaction counts and intensity values help frame whether the instrument has built more meaningful supply or demand shelves in the current environment.
Step 5: Combine With Structure
Aegis Liquidity Ledger is not a standalone regime classifier.
It works best beside structure or session tools that explain the broader context around the pressure source.
Indicator Limitations
Liquidity shelves are inferred from price behavior, not from direct order book or market-by-order data
Aggressive settings can create more shelves than slower traders may want to track
Pressure normalization adapts to the instrument, but abrupt volatility shocks can still distort thresholds temporarily
A shelf is an area of contextual interest, not a guarantee of reversal or continuation
Originality Statement
Aegis Liquidity Ledger is structured around the relationship between a normalized pressure oscillator and persistent source-zone shelves.
Its design emphasizes where pressure comes from, how dense liquidity has been on each side of price, and whether a prior source has been mitigated, rather than simply plotting another momentum line.
Disclaimer
This indicator is provided for educational and informational purposes only.
It is not a recommendation to trade and should not be interpreted as financial advice.
All shelf and pressure readings are model-based interpretations of chart data and can fail under changing market conditions.
Always use independent analysis and risk management.
Indicator
Cadence Reversion Cartography [JOAT]Cadence Reversion Cartography
Introduction
Cadence Reversion Cartography is an open-source mean-reversion and exhaustion overlay designed to locate stretched conditions around an EMA envelope and anchored VWAP framework. It focuses on mapping where price has moved too far from local balance, then grades whether a return toward value has enough supporting evidence to matter.
The problem this script solves is selective reversal timing. Price can stay overextended for longer than expected, so simple band-touch logic is not enough. Cadence Reversion Cartography combines envelope stretch, VWAP stretch, RSI exhaustion, volume impulse, rejection-candle behavior, reclaim logic, and projected response boxes so the user can distinguish weak touches from stronger reversion candidates.
Core Concepts
1. Dual Stretch Model
Price is compared to both an EMA deviation envelope and an anchored VWAP deviation layer. A long-side exhaustion condition requires price to stretch below both lower references. A short-side exhaustion condition requires price to stretch above both upper references.
2. Exhaustion Quality Filters
RSI can require oversold or overbought context, volume can require impulse relative to average participation, and candle structure can require a visible rejection profile.
3. Reclaim And Signal Grading
A setup becomes actionable only after price closes back inside the envelope on a confirmed bar. The script then scores the setup by counting how many filters aligned and promotes stronger signals to a prime grade.
4. Projection Mapping
When a setup forms, the script can draw a forward projection with a risk box, reward box, signal zone, and reclaim line. This is meant to show the structure of the reversion idea rather than acting as a promise of outcome.
Features
EMA reversion envelope: Basis plus statistical deviation bands
Anchored VWAP stretch layer: Secondary value reference around VWAP
RSI exhaustion filter: Optional momentum exhaustion gate
Volume impulse filter: Optional participation confirmation
Rejection-candle filter: Optional candle-structure confirmation
Signal grading: Standard and prime long or short responses
Signal zones and reclaim lines: On-chart response structure around the active setup
Risk and reward projection boxes: Optional forward mapping of stop and target structure
Context candle coloring: Candles can tint with stretch state
Dashboard: Displays stretch, setup bias, and active context
Input Parameters
Reversion Envelope:
Channel Length
Deviation Multiplier
VWAP Stretch Multiplier
Filters And Display:
RSI settings
Volume average and impulse multiplier
Rejection-candle requirement
Projection-box toggle, stop percent, reward multiple, projection length, and signal cooldown
Dashboard, background, candle-color, and signal-zone toggles
How to Use This Indicator
Step 1: Wait for price to stretch beyond both the EMA envelope and the VWAP stretch layer.
Step 2: Check whether RSI, volume, and rejection filters support the move.
Step 3: Wait for confirmed re-entry back inside the envelope instead of fading the first touch.
Step 4: Use the signal grade and projection structure to judge whether the setup is marginal or stronger.
Step 5: Use the basis and reclaim line as the first balance reference after entry.
Indicator Limitations
Strong directional trends can keep price stretched for extended periods and delay reversion
Volume-based confirmation is less meaningful on symbols with irregular volume reporting
Projection boxes are planning tools, not guaranteed outcomes
This script is designed for reversion analysis and is not intended to replace broader trend context
Originality Statement
Cadence Reversion Cartography is original in how it coordinates envelope stretch, VWAP stretch, filter-based exhaustion grading, and forward projection structure inside one reversion workflow. The components are combined to answer one analytical problem: not just whether price is stretched, but whether the stretch is mature enough to support a structured return toward value.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Reversion setups can fail during strong trends or regime expansion, so all signals should be used with independent confirmation and risk management.
-Made with passion by jackofalltrades
Indicator
Squeeze Bollinger Bands Tracker [MarkitTick]💡 This institutional-grade analysis suite provides a sophisticated volatility-tracking environment designed to identify market compression phases and high-conviction breakouts. By integrating Bollinger Band standard deviation logic with Z-Score normalization and a non-linear sigmoid volatility engine, the script transforms raw price action into a multi-dimensional heatmap. This approach allows traders to distinguish between low-volatility "coiling" phases and institutional-driven momentum expansions, providing a clear visual representation of market energy.
● ✨ Originality and Utility
The Squeeze Bollinger Bands Tracker distinguishes itself through the implementation of a proprietary "Signal Engine" and a non-linear volatility grading system. Unlike standard Bollinger Band indicators that merely plot static lines, this tool actively monitors the rate of change in channel width relative to its own historical standard deviation.
• Dynamic Volatility Normalization
Most indicators rely on linear calculations that fail to account for the exponential nature of market expansion. This script utilizes a Z-Score calculation to determine how extreme a volatility move is compared to its history, then maps that value through a sigmoid function. This creates a "Heatmap" effect on the candles that reflects institutional participation levels rather than simple price movement.
• Institutional Breakout Grading
The utility is further enhanced by an automated grading system (Grades A, B, and C). By cross-referencing price spread (the distance between open and close) with actual volume metrics during a breakout, the script provides an objective measure of signal quality, helping traders filter out "fakeouts" that lack volume support.
● 🔬 Methodology and Concepts
The logic flow is divided into three core analytical pillars: Compression Detection, Momentum Normalization, and Signal Verification.
• Compression Detection (The Squeeze)
The script calculates the percentage-based width of the Bollinger Bands. When the current width falls below its SMA-based average, the market is classified as being in a "Squeeze" state. This signifies a period where market energy is being stored, often preceding a significant directional expansion.
• Sigmoid-Mapped Z-Score Volatility
To provide the neon heatmap coloring, the script calculates the Z-Score of the channel width. This tells us how many standard deviations the current volatility is from the mean. This Z-Score is then processed through a Sigmoid Function: 100 / (1 + exp(-Z-Score)). This mathematical transformation squashes the infinite Z-Score range into a 0–100 scale, creating a smooth gradient for the "True Institutional Heatmap."
• Breakout Validation Engine
Signals are not generated simply on a price cross. The Signal Engine (a custom User-Defined Type) calculates real-time Entry, Stop Loss (based on the previous basis line), and Take Profit levels. During the moment of crossover, the "calcGrade" method evaluates if the current bar's spread and volume are at least 150% of their historical averages to assign a Grade A "Institutional" breakout.
● 🎨 Visual Guide
The visual interface is designed with a high-contrast "3D Neon" aesthetic to ensure critical data points are immediately recognizable during fast-moving market conditions.
• The 3D Neon Channels
Upper Core & Glow: The upper Bollinger Band is rendered in Cyan (#00FFFF). It features three layers: a 2-pixel core for precision and two wider "Glow" layers with varying transparency (60% and 85%) to create a neon effect.
Lower Core & Glow: The lower band is rendered in Magenta (#FF00FF), following the same three-layer glow architecture to signify the support boundary.
Basis Core: The central moving average is rendered in Yellow (#FFFF00), acting as the dynamic mean and the primary stop-loss anchor.
• True Institutional Heatmap Candles
The candle colors are not fixed; they represent a gradient based on the Sigmoid Volatility score.
Bullish State: Transitions from a deep "Cold" Forest Green (#004D40) during low-volatility rises to a "Hot" Neon Green (#00FF00) during high-momentum surges.
Bearish State: Transitions from a deep "Cold" Purple (#4A148C) during low-volatility drops to a "Hot" Neon Red (#FF0000) during aggressive sell-offs.
Neutral State: Gray (#808080) candles appear when no definitive trend state is identified by the Signal Engine.
• Analytical Dashboard and Labels
Buy/Sell Labels: When a breakout occurs, a Cyan or Magenta label appears. It displays the signal Grade (A, B, or C) and the calculated E (Entry), TP (Take Profit), and SL (Stop Loss) values.
Institutional Analytics Dashboard: Located in the top-right, this table provides real-time data on Trend Maturity (in bars), Volatility State (Squeeze vs. Expanding), and the percentage proximity to the upper and lower breakout levels.
● 🔍 Deconstruction of the Underlying Scientific and Academic Framework
The indicator is built upon the foundation of Statistical Process Control and Information Theory. By treating price movement as a signal-to-noise problem, the script uses the following frameworks:
• Standard Deviation and Gaussian Distribution
The core of the Bollinger Band calculation relies on the assumption that price spends approximately 95% of its time within two standard deviations of the mean. The "Squeeze" logic identifies periods where the distribution is abnormally tight, suggesting an imminent return to the mean or a "Fat Tail" event (a breakout).
• Z-Score Normalization
In statistics, the Z-Score is used to compare observations from different data sets or time periods. By applying Z-Score logic to the width of the bands, the indicator removes the "unit" of price and focuses purely on the intensity of the volatility, allowing for a standardized comparison across different assets (e.g., Bitcoin vs. Apple).
• Non-Linear Sigmoid Mapping
The use of the Sigmoid function (common in Neural Network activation) serves to eliminate outliers in volatility data. This ensures that the candle heatmap provides meaningful color variations even during extreme "Black Swan" events, preventing the visual output from becoming saturated or unreadable.
● 📖 How to Use
Traders should focus on the transition between market states as displayed by the Analytics Dashboard and the Heatmap.
• Step 1: Identify the Squeeze
Monitor the "Volatility State" in the dashboard. When it displays "⚠️ SQUEEZE" in Neon Orange, the market is coiling. This is the preparation phase where no trades should be taken.
• Step 2: Evaluate the Breakout Grade
Wait for a "BUY" or "SELL" label to appear. Priority should be given to "Grade A" signals, as these indicate that both price spread and volume have significantly exceeded their 20-period averages, confirming institutional intent.
• Step 3: Execution and Risk Management
Upon a valid signal, the script provides an automated trade plan. The Stop Loss is set at the Basis (Yellow) line from the previous bar to allow for minor breathing room, while the Take Profit is projected at a 1:1 ratio relative to the width of the band at the time of entry.
● ⚙️ Inputs and Settings
The script provides granular control over the analytical engine and the visual experience.
• Channel Settings
Channel Length: Controls the SMA window for the Bollinger Bands (Default: 20).
Standard Deviation Multiplier: Adjusts the width of the neon boundaries (Default: 2.0).
• Analytics Settings
Squeeze/Z-Score Length: Determines the lookback period used to define what constitutes "average" volatility (Default: 50).
Quality SMA Length: Defines the window for the Grade A/B/C volume and spread verification (Default: 20).
• Color and Heatmap Settings
Users can fully customize the Neon Upper/Lower colors, the Dashboard background transparency, and the specific "Cold" and "Hot" thresholds for the candle gradient engine to match their preferred dark or light chart theme.
⚠️ Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion. Indicator
Indicator
Volume Weighted RSI PRO | AnonycryptousVolume Weighted RSI Pro | Anonycryptous
Description & user manual
Why this indicator is different
Standard RSI treats every bar equally. A bar where 100 lots traded and a bar where 100,000 lots traded produce the same RSI value if the price change was the same. That is a fundamental problem. Price moves on low volume are noise. Price moves on high volume are institutional participation. RSI cannot tell the difference.
Volume Weighted RSI Pro fixes this at the calculation level.
Instead of averaging raw price changes, every gain and loss is multiplied by its relative volume before entering the RSI calculation. A strong move on elevated volume pushes the oscillator harder than the same move on thin participation. A drift in price on below-average volume barely registers. The result is an RSI that reflects who was actually behind the move — not just that a move happened.
But volume-weighted RSI alone is one perspective. The indicator adds a second independent layer through the Money Flow Index — a separate oscillator that weights typical price by volume rather than price change. When both VW RSI and MFI agree on an extreme reading, the confluence is structurally different from either line alone. One can be driven by a single large candle. Two separate calculation methods arriving at the same conclusion is harder to dismiss.
And then there are the liquidity levels.
Most RSI-based indicators live in isolation from price structure. They show you when the oscillator is extended, but not where on the price chart that extension corresponds to meaningful levels. Volume Weighted RSI Pro draws the nearest swing highs and lows directly on the price chart — the levels where stops cluster, where institutions defend positions, and where reversals tend to form. Each level shows the volume ratio at the moment it was created. Each level disappears automatically when price closes through it, and the indicator immediately identifies the next relevant level below or above.
The divergence engine connects oscillator behavior with price structure by drawing lines, endpoint markers, and a highlighted box on the price chart that spans the exact bars involved. Not just a signal — a spatial map of what happened and where.
This is an RSI indicator that knows where it is on the chart.
Important notice
Volume Weighted RSI Pro generates signals based on oscillator behavior, volume analysis, and price structure detection.
These signals are not financial advice.
They do not predict future price movement.
They do not guarantee profitability.
All trading decisions are made entirely by the user.
Always manage your own risk. Always apply your own judgment.
1. Overview
Volume Weighted RSI Pro is a multi-layer oscillator built around a volume-weighted RSI calculation. It combines momentum analysis, divergence detection, volume flow confirmation, and liquidity level mapping in a single indicator across both the oscillator pane and the price chart.
What it includes:
- Volume weighted RSI using relative volume to scale price change contributions
- Money Flow Index as a second independent momentum layer
- EMA signal line with configurable length and crossover markers
- Divergence detection with RSI pane lines and mainchart box visualization
- Liquidity level lines on the price chart from confirmed swing highs and lows
- Volume ratio label per liquidity level showing institutional activity at formation
- Automatic level mitigation: levels disappear when price closes through them
- OB/OS zone boxes with per-zone volume intensity tracking
- Gradient glow fill between the RSI line and midline
- OB/OS exit signals and signal line crossover markers
- Bar coloring and mainchart background based on RSI position
- Live dashboard with RSI value, volume ratio, zone, divergence, signal, and liquidity levels
- Seven alerts covering divergence, exits, and signal line crossovers
2. Core calculation
2.1 Volume weighted RSI
Standard RSI sums gains and losses over a lookback period using Wilder's smoothing (RMA). Volume Weighted RSI Pro applies the same structure but multiplies each bar's price change by its relative volume — the ratio of bar volume to the smoothed volume average — before the RMA smoothing step.
A bar with twice the average volume contributes twice as much to the gain or loss accumulation. A bar with half the average volume contributes half as much. This means the oscillator level reflects participation quality, not just price displacement. In practical terms: trending moves on rising volume push the oscillator to extremes faster. Pullbacks on thin volume barely move it. This creates a cleaner, more institutionally-aware reading than standard RSI.
The volume weighted mode can be toggled off to revert to standard RSI behavior for direct comparison.
2.2 Standard RSI reference line
A standard RSI line is plotted as a secondary reference in the same pane. Its color and width are configurable. Divergence between the volume weighted and standard lines reveals moments where volume is distorting the picture — a large move on thin participation that standard RSI registers but the VW version largely ignores, or vice versa.
2.3 Signal line
An EMA of the volume weighted RSI value acts as a signal line, similar in concept to the signal line in a MACD. The default length is 9. When the VW RSI crosses above the signal line, momentum is accelerating to the upside. When it crosses below, momentum is decelerating. Crossover markers appear at the exact cross point and can be toggled on or off. The signal line is most useful as a filter — only take a setup if the RSI and signal line agree on direction.
2.4 Money Flow Index
The MFI is calculated using typical price ((high + low + close) / 3) multiplied by volume, producing separate positive and negative money flow sums that are then converted to an index between 0 and 100. It shares the same scale as the VW RSI, making direct visual comparison possible.
The MFI responds differently from VW RSI because it weights price level rather than price change. Elevated MFI without elevated VW RSI suggests buying pressure at current levels without strong directional momentum. Both indicators in overbought territory simultaneously is a stronger condition than either alone.
3. Divergence detection
Divergence is detected by comparing pivots in the volume weighted RSI against pivots in price over a configurable lookback window
Bearish divergence: price makes a higher high while VW RSI makes a lower high. Momentum is weakening as price extends — a structural warning.
Bullish divergence: price makes a lower low while VW RSI makes a higher low. Selling pressure is exhausting even as price continues lower — a structural opportunity.
Sensitivity controls the pivot lookback window:
- High: 3-bar pivots. More signals, more false positives.
- Medium: 5-bar pivots. Balanced default.
- Low: 10-bar pivots. Fewer signals, higher quality.
When a divergence confirms, two things are drawn simultaneously. In the RSI pane: a solid line connecting the two pivot RSI values. On the price chart: a box spanning the full price range of the bars involved in the divergence. This makes the spatial relationship between the oscillator event and the price structure immediately visible.
The divergence box does not confirm a trade. It confirms that a structural disagreement between price and momentum occurred, and where on the chart it happened.
4. Liquidity levels
Liquidity levels are drawn on the price chart at confirmed swing highs and lows using a pivot detection engine. They represent the price levels where stop orders are likely to cluster — below swing lows for buy stops and above swing highs for sell stops. These are the levels that institutional participants use as targets when running liquidity.
Each level is a horizontal line that starts at the pivot bar and extends to the right in real time. The nearest level is fully opaque. Additional levels fade with distance from current price.
Each level displays a volume ratio label at its origin — the bar's volume at the time of pivot formation relative to the recent average. A level formed on 2.1x average volume is more institutionally significant than one formed on 0.7x volume. This context is part of reading the level.
When price closes through a level, it is removed immediately. The indicator repopulates from the remaining valid pivots. There is no manual cleanup and no visual clutter from levels that have already been swept.
The detail level setting controls how aggressively levels are detected:
- Minimal: wide pivot lookback, only the most significant structural highs and lows qualify.
- Standard: balanced detection, practical default across most timeframes.
- Full: tighter pivot lookback, more levels are identified.
The dashboard shows the nearest bull side level (BSL) and bear side level (SSL) by price, updated in real time.
5. OB/OS zone tracking
When the VW RSI enters overbought or oversold territory, the indicator begins accumulating the total volume transacted during that period. When price exits the zone, a filled box is drawn over the duration of the zone on the RSI pane.
The box includes a volume intensity label showing how the average volume inside the zone compared to the baseline average. A zone with 1.8x average volume indicates elevated institutional activity during the extreme reading — the extension was not just price drift but active participation. A zone below 1.0x is thin and less meaningful.
OB/OS zones are off by default.
6. Visual guide
RSI pane elements:
- Bright green/red RSI line — volume weighted RSI, color intensity increases toward OB/OS extremes
- Grey reference line — standard RSI, configurable color and width
- Gold line — signal line (EMA of VW RSI)
- Purple line — MFI
- Gradient glow fill — color intensity increases from midline toward the RSI line, creating a visual depth effect that reflects how extended the oscillator is
- OB/OS background — deepens in red or green when RSI is in extreme territory
- ▲ marker — RSI exiting oversold territory
- ▼ marker — RSI exiting overbought territory
- ✕ marker — RSI/signal line crossover (when enabled)
- Divergence line — solid colored line between the two pivot RSI values
Mainchart elements:
- Horizontal lines — liquidity levels, color and opacity by distance from current price
- Volume label at origin — volume ratio at pivot formation bar
- Divergence box — spans the full price range of the divergence bars
- Background color — subtle green above RSI 50, subtle red below
- Bar coloring — gradient intensity based on RSI position
7. Dashboard reference
The dashboard is positioned bottom right by default and updates on every bar close.
VW RSI — current VW RSI value, colored by position.
Vol ratio — current bar volume relative to the smoothed average. Values above 1.5x are highlighted in gold.
Zone — current RSI zone: overbought, oversold, or neutral.
Divergence — active divergence state if detected on the most recent pivot.
Signal — most recent signal condition.
— Liquidity —
Near BSL — nearest bull side liquidity level below current price.
Near SSL — nearest sell side liquidity level above current price.
Liq levels — count of active levels on each side.
Mode — VW (volume weighted) or STD (standard RSI mode).
Anonycryptous — indicator brand and version.
8. Alerts
Seven alert conditions are available:
- Bullish divergence: price lower low with VW RSI higher low confirmed.
- Bearish divergence: price higher high with VW RSI lower high confirmed.
- OS exit signal: RSI crosses back above the oversold level.
- OB exit signal: RSI crosses back below the overbought level.
- Any divergence: fires on either divergence type.
- Signal cross up: VW RSI crosses above the signal line.
- Signal cross down: VW RSI crosses below the signal line.
9. Settings reference
9.1 RSI settings
- RSI length: lookback period for the VW RSI calculation. Default 14.
- Volume smoothing: lookback for the volume moving average. Default 14.
- Volume weighted mode: toggle between volume weighted and standard RSI.
- Show signal line: toggle the EMA signal line.
- Signal line length: EMA period for the signal line. Default 9.
- Show signal crossovers: toggle ✕ markers at signal line crossovers. Default off.
- Show MFI line: toggle the Money Flow Index line.
- MFI length: lookback for MFI calculation. Default 14.
- MFI color: default brand purple.
- MFI line width: 1 to 4. Default 2.
- Overbought level: threshold for OB signals and zone tracking. Default 70.
- Oversold level: threshold for OS signals and zone tracking. Default 30.
9.2 Divergence
- Sensitivity: pivot lookback window — high (3), medium (5), low (10).
- Show bullish divergence.
- Show bearish divergence.
- Divergence box on mainchart: draws the price range box on the price chart.
- Div line width: stroke weight of divergence lines. 1 to 4. Default 2.
9.3 Liquidity levels
- Show liquidity levels: toggle all liquidity lines on the price chart.
- Detail level: minimal, standard, or full pivot sensitivity.
- Pivot lookback: swing detection window. Default 10.
- Max levels each side: maximum lines shown above and below current price. Default 2.
9.4 OB/OS zones
- Show OB/OS zones: toggle zone boxes in the RSI pane. Default off.
- Volume intensity label: show per-zone volume ratio label.
- Zone transparency: fill opacity for OB/OS zone boxes.
9.5 Visuals
- Bull color: primary bull color across all elements.
- Bear color: primary bear color across all elements.
- Bull div color: color for bullish divergence lines and box.
- Bear div color: color for bearish divergence lines and box.
- Std RSI color: color of the standard RSI reference line.
- Std RSI width: stroke weight of the reference line.
- Bar coloring: gradient bar color based on RSI position.
- Signal size: size of OB/OS exit markers — tiny, small, or normal.
- Show background color: subtle mainchart background based on RSI direction.
- Background transparency: opacity of the mainchart background.
9.6 Dashboard
- Show dashboard.
- Position: top left, top right, bottom left, or bottom right.
- Size: tiny, small, or normal.
10. How to use
10.1 Reading divergence
Divergence is not a signal to enter immediately. It is a warning that the relationship between momentum and price is breaking down. The most effective approach is to wait for the divergence box to appear on the price chart and then look for a second confirmation — a signal line crossover, an OB/OS exit marker, or a price reaction at a nearby liquidity level — before treating the setup as actionable.
Divergence on its own can persist for many bars before price reacts. Use it as directional context, not as a trigger.
10.2 Using liquidity levels
The liquidity lines show where the market has unfinished business — swing levels that formed on meaningful volume and have not yet been revisited. When the VW RSI is approaching overbought or showing bearish divergence and price is simultaneously approaching a sell-side liquidity level above, those two conditions are pointing at the same structural event from different angles.
The volume ratio label at each level is particularly useful. A level formed on 0.6x average volume is a weak level that may not generate a meaningful reaction. A level formed on 2.5x average volume suggests a move was initiated or defended with institutional size. Treat these differently.
10.3 Using VW RSI and MFI together
When both lines are in overbought territory simultaneously, the condition is stronger than either alone. VW RSI is extended on momentum. MFI confirms that money flow at current price levels is also elevated. The two calculations are independent — their agreement is not trivial.
When they diverge — VW RSI overbought while MFI is not — one of the components is not confirming the other. This does not mean the move is wrong, but the confluence is weaker.
10.4 OB/OS zone volume
When the zone volume label shows above 1.5x, the extreme RSI reading occurred during elevated participation. That tells you the extension was not just mechanical drift — there was active buying or selling pressure behind it. An exit from that zone after a high-volume OB/OS period carries more weight than an exit from a thin zone.
10.5 Illustrative bull scenario
Educational example only. Not a trading recommendation.
VW RSI drops into oversold on above-average volume. A bull-side liquidity level sits 0.8% below current price, formed three sessions ago on 2.1x volume. VW RSI begins making a higher low while price makes a lower low — bullish divergence is confirmed. A divergence box appears on the price chart. The RSI crosses back above the oversold level, firing a ▲ marker. The signal line crossover fires shortly after. Three separate conditions align: oversold exit, bullish divergence, and signal line confirmation.
10.6 Illustrative bear scenario
Educational example only. Not a trading recommendation.
Price rallies into a sell-side liquidity level visible on the chart at 2.2x formation volume. VW RSI is in overbought territory while MFI is also elevated. Price makes a higher high but VW RSI makes a lower high — bearish divergence is drawn on the RSI pane and a box appears on the price chart covering the divergence range. RSI crosses back below overbought. A ▼ marker fires. The setup has divergence, OB exit, and a liquidity level all at the same location.
11. Tips
The volume ratio in the dashboard is one of the most underused readings. A vol ratio below 0.7 means current price action is thin — institutions are not participating. Signals that fire on low volume ratio are less reliable than those that fire on 1.5x or above.
Signal line crossovers are most useful as filters. Toggle them on during active sessions to see where momentum flips are occurring relative to the rest of the setup. Too many crossovers on a given session usually means the market is ranging — reduce position size or wait for the RSI to expand toward an extreme before taking the cross seriously.
The standard RSI reference line reveals when volume weighting is changing the picture. If the VW RSI is significantly above the standard line, it means recent price movement was driven by above-average volume. If the VW RSI is below the standard line, price moved on thin participation — the market did not commit to the direction.
Liquidity level count in the dashboard tells you how many valid structural references remain. When the count drops — because levels are being swept — it means the market is clearing stops. That is meaningful context for the direction of the current move.
12. Disclaimer
This indicator is provided for educational and informational purposes only. Nothing in this document or in the indicator output constitutes financial advice or any form of recommendation. Trading financial instruments involves substantial risk of loss. Past performance is not indicative of future results. You may lose all of your invested capital.
Anonycryptous accepts no responsibility or liability for any losses incurred as a result of using this indicator. Indicator
