Quant Synthesis Strategy [JOAT]Quant Synthesis Strategy
Introduction
QSS Quant Synthesis Strategy is an open-source PulseWire strategy that integrates regime detection, higher-timeframe bias, confirmed structure, session opening-range context, volume participation, trend energy, ATR exits, cooldowns, and session risk controls.
The strategy is designed as a realistic research baseline, not an optimized profit promise. Its purpose is to demonstrate how the JOAT indicator concepts can be combined into a non-repainting strategy framework with explicit risk management.
Core Concepts
1. Market Regime Detection
The regime model uses EMA spread, ADX from DMI, and ATR percentage context to classify Trend, Expansion, Balance, or Transition.
2. Higher-Timeframe Bias
The strategy requests higher-timeframe EMAs with lookahead disabled. Long bias requires the HTF fast EMA above the slow EMA with positive slope; short bias is mirrored.
3. Confirmed Structure
Pivot-based structure checks whether recent highs and lows form bullish or bearish structure. Pivot confirmation is delayed by design to avoid repainting.
4. Session Opening Range
The strategy tracks a configurable trading session and opening range. Entries can require session context so trades are not taken randomly outside the selected window.
5. Risk and Exits
Position size is estimated from a percentage of equity and ATR stop distance. Exits include ATR stop, ATR target, maximum bars in trade, regime/bias exit, cooldown, and session flattening.
Features
Regime engine: Trend, Expansion, Balance, and Transition classification
HTF bias filter: Uses non-lookahead request.security() higher-timeframe EMAs
Confirmed structure filter: Pivot-based bullish/bearish structure state
Session opening range: Optional session context for entries
Volume participation filter: Uses volume z-score and directional volume
Confluence score: Separate long and short scores gate entries
ATR exits: Stop loss and take profit scale with volatility
Risk controls: Risk percent, cooldown, max entries per session, max bars in trade, and session flattening
Visuals: EMA cloud, opening-range lines, stop/target plots, and top-right dashboard
Default Strategy Properties
Initial capital: 100000
Commission: 0.01 percent
Slippage: 1 tick
Pyramiding: 0
Order processing: process orders on close
Position sizing: fixed quantity calculated internally from risk settings
How to Use
Step 1: Select a market and timeframe with enough historical data.
Step 2: Review the dashboard regime and HTF bias before interpreting trades.
Step 3: Adjust risk percent, ATR stop, ATR target, cooldown, and session settings conservatively.
Step 4: Evaluate results across multiple symbols and timeframes. Avoid optimizing only one market segment.
Limitations
Backtest results are historical simulations and do not guarantee future performance
More trades can increase sample size but can also increase noise and transaction costs
Pivot confirmation creates intentional signal delay
Strategy results depend on symbol liquidity, timeframe, session settings, slippage, and commission assumptions
The strategy is a research framework, not a recommendation to trade
Originality Statement
QSS is an original JOAT strategy framework that integrates regime detection, HTF bias, structure, session context, volume participation, and ATR risk management into one non-repainting Pine Script v6 strategy.
Disclaimer
This strategy is for educational and informational purposes only. It is not financial advice and does not guarantee profitability. Trading involves substantial risk of loss. Historical backtests can be inaccurate or misleading if assumptions do not match live execution.
Made with passion by jackofalltrades
Strategy
CISD Projection Ledger [JOAT]CISD Projection Ledger
Introduction
CPL CISD Projection Ledger is an open-source projection overlay that detects confirmed directional delivery shifts, then projects a structured target ledger from the qualifying run range.
The indicator focuses on one job: finding a qualifying run, confirming the open-cross shift on a closed bar, and tracking which projection tiers have been reached or invalidated.
Core Concepts
1. Directional Run Engine
Bars are grouped into directional runs based on close-to-close progression. A run must meet the minimum bar count before it can qualify.
2. Edge Filter
The prior run must form near the upper or lower region of the recent lookback range before a CISD event can trigger.
3. Open-Cross Confirmation
A bullish CISD requires a prior bearish run and a confirmed close back above the prior run open. Bearish logic is mirrored.
4. Projection Ledger
Five tiers are projected from the confirmed run range using configurable multipliers.
5. Reached and Invalid States
Each tier fades after it is reached. The whole ledger invalidates if price closes beyond the opposite reference side.
Features
Confirmed CISD trigger: Uses closed-bar open-cross confirmation
Range edge filter: Avoids projecting every minor run flip
Five-tier ledger: Customizable projection multipliers
Reached-level tracking: Levels visually fade after completion
Invalidation logic: Opposite-side failure changes state
Ledger band: Transparent fill from base to furthest target
Top-right dashboard: Shows base, range, tier prices, reached status, and active state
Alerts: Includes bullish and bearish CISD confirmations
Input Parameters
Run Engine:
Minimum Run Bars
Range Lookback
Edge Window
Ledger:
Tier 1 through Tier 5 multipliers
How to Use
Step 1: Wait for a confirmed bullish or bearish CISD state in the dashboard.
Step 2: Use the base level and projected tiers as a structured map of possible delivery objectives.
Step 3: Watch reached status. Faded levels indicate completed tiers.
Step 4: Respect invalidation. An invalid ledger means the original delivery thesis failed.
Limitations
Projection levels are analytical references, not guaranteed targets
Strong reversals can invalidate a ledger quickly
The edge filter may skip valid-looking setups that are not near the configured range edge
The indicator should not be used without independent trade management
Originality Statement
CPL is an original JOAT implementation that transforms directional run logic into a confirmed CISD ledger with tier tracking, invalidation, and a restrained institutional visual system.
Disclaimer
This script is for educational and informational purposes only. It is not financial advice and does not guarantee future results. Trading involves risk, and users should apply their own risk management.
Made with passion by jackofalltrades
Indicator
Structure Probability Blocks [JOAT]Structure Probability Blocks
Introduction
Structure Probability Blocks is an open-source market structure and quality-zone overlay. It detects confirmed structure breaks, searches for the most relevant opposing candle, scores the resulting block, and highlights the strongest active block without filling the chart with redundant zones.
The problem it solves is order block clutter. Many zone tools draw every candidate equally. Structure Probability Blocks filters for impulse, candle quality, relative volume, recency, and overlap so the displayed blocks have cleaner context. The enhanced chart layer also projects BOS/CHoCH break rails, impulse guide lines, and compact score labels directly beside the structure event.
Core Concepts
1. Confirmed Pivot Tracking
Swing highs and lows are confirmed using symmetric pivots. Because pivots require bars on both sides, this is intentionally delayed and non-repainting.
2. Break Qualification
A structure break requires price to close through the tracked pivot and meet a minimum ATR-based impulse requirement.
3. Seed Candle Search
After a break, the script searches backward for the best opposing candle candidate. The score considers body quality, wick behavior, volume rank, and recency.
4. Strongest Active Block Highlight
Among active blocks, the highest-scored block receives stronger border and midline treatment. Weaker overlapping blocks can be removed when the overlap guard is enabled.
5. Break Rails and Impulse Guides
When a qualified BOS or CHoCH forms, the indicator can draw a dashed horizontal break rail from the pivot level to the right edge and a dotted impulse guide from the selected seed candle to the break close. The on-chart tag includes score, zone range, drive, RVOL, and break price.
6. Strongest Block Ribbon
The highest-scored active block is also projected as a subtle ribbon using plot/fill logic. This gives a clean strongest-zone read even when several historical boxes remain visible.
Features
Confirmed structure breaks: Breaks require closed-bar confirmation
Quality-scored blocks: Scores combine impulse, candle structure, relative volume, and recency
BOS/CHoCH context: Block labels identify continuation or character-shift context
BOS/CHoCH break rails: Dashed projected levels mark the exact pivot level that price broke
Impulse guide lines: Dotted guides connect the seed candle to the break close
Expanded score tags: Labels show score, zone range, drive, RVOL, and break level
Prime block highlight: Highest active score receives stronger visual emphasis
Strongest block ribbon: Highest active zone is projected as a lightweight filled band
Overlap guard: Keeps the stronger of overlapping active blocks
Prime candle tint: Candles can be softly colored by the strongest active structure bias
Broken block handling: Keep, fade, extend, or remove resolved blocks
Top-right dashboard: Active count, bull/bear count, best score, break state, last pulse, volume rank, and break mode
Alerts: New bullish and bearish quality block events
Input Parameters
Structure:
Pivot Length: Swing confirmation sensitivity
Search Span: Bars searched for a seed candle
Break Impulse: Minimum ATR expansion required for a break
Volume Span: Lookback used for volume rank
Min Score: Minimum block quality score required
How to Use This Indicator
Step 1: Use the dashboard to identify current bull/bear structural bias.
Step 2: Focus on the strongest highlighted active block first.
Step 3: Use the dashed BOS/CHoCH rail as the exact structural break reference.
Step 4: Treat broken/faded blocks as resolved context rather than fresh opportunities.
Step 5: Combine with a regime or pressure tool before making directional decisions.
Indicator Limitations
Pivot confirmation is delayed by the pivot length, which is intentional non-repainting behavior
A high block score does not imply a guaranteed reaction
Volume rank can be less useful on instruments with unreliable volume
The script identifies structural context, not complete risk-defined trades
Originality Statement
Structure Probability Blocks is original in its quality-scored seed selection, impulse qualification, overlap prioritization, prime block highlighting, and compact structural dashboard. It does not copy third-party source code.
Disclaimer
This open-source indicator is provided for educational and informational purposes only. It is not financial advice. Structural zones can fail, and traders should always use independent analysis and proper risk management.
-Made with passion by jackofalltrades
Indicator
Regime Execution Strategy [JOAT]Regime Execution Strategy
Introduction
Regime Execution Strategy is an open-source PulseWire strategy that integrates adaptive forecast context, extreme-channel state, trend pressure, relative volume, and EMA structure into a single rule-based execution model. The strategy is designed to be realistic, non-repainting, and readable rather than curve-fit to one symbol.
The problem it solves is trade filtering. A single signal source can trigger too often in poor conditions. Regime Execution Strategy requires multiple independent votes before entries are allowed, then uses ATR-based stop and target logic for consistent risk framing.
Core Concepts
1. Adaptive Forecast Bias
The strategy estimates a dynamic mean and band structure. Price above or below the adaptive mean contributes to directional bias.
2. Extreme Channel Bias
Persistent upper and lower channel levels define a midpoint and directional state. The channel contributes a second independent vote.
3. Pressure and Structure Gate
Momentum, pullback location, and fast/slow EMA structure contribute to the regime score. A minimum vote count and relative-volume filter are required before entry.
longSignal = barstate.isconfirmed and bullVotes >= voteThreshold and bullRegime and (longBreakout or longReclaim)
4. ATR-Based Risk Management
Stops and targets are derived from ATR and position average price. The strategy also includes max drawdown and max intraday filled order risk controls.
Features
Integrated regime detection: Forecast, channel, pressure, and EMA structure combine into a regime score
Multi-vote entry logic: Entries require several independent components to align
More active defaults: Default RVOL and regime thresholds are permissive enough to participate across many timeframes
ATR stop and target: Risk is framed with volatility-adjusted exits
Bias-flip exits: Positions can close when the opposing regime gains enough votes
Risk controls: Max drawdown and max intraday filled orders are included
Overlay visuals: Forecast bands and adaptive channel context can be displayed on chart
Top-right dashboard: Regime, score, pressure, RVOL, votes, position, band width, and setup
Alerts: Long and short setup events
Input Parameters
Forecast:
Source, Forgetting Factor, Regression Horizon, Band Multiplier, ATR Blend, and Rebase Interval
Regime:
Fast EMA and Slow EMA: Trend structure references
Pressure Length: Momentum and pullback window
Pressure Threshold: Minimum pressure vote threshold
Min RVOL: Participation filter
Min Votes: Minimum number of aligned components for entries
Risk:
Stop ATR: Stop distance multiplier
Target ATR: Target distance multiplier
Max Drawdown %: Strategy risk halt setting
Max Intraday Filled Orders: Limits daily trade frequency
How to Use This Strategy
Step 1: Read the dashboard regime before judging entries.
Step 2: Use votes and pressure to understand why a setup qualified.
Step 3: Review stop and target settings for the symbol and timeframe being tested.
Step 4: Evaluate results across multiple markets and date ranges, not one optimized window.
Strategy Limitations
This strategy is not optimized for a specific symbol or timeframe
More active defaults can increase trade count and also increase exposure to choppy periods
Backtest fills are simulated by PulseWire and may not match live execution
All entry signals use confirmed-bar logic, so entries can occur after the intrabar move has begun
Strategy performance should be evaluated with realistic commission, slippage, and position sizing
Originality Statement
Regime Execution Strategy is original in its integration of adaptive forecast bias, extreme-channel state, pressure voting, relative volume gating, EMA structure, ATR exits, and dashboard reporting into one open-source strategy. It does not copy third-party source code.
Disclaimer
This open-source strategy is for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any instrument. Backtested results do not predict future performance. Trading involves substantial risk, and users are responsible for their own risk management.
-Made with passion by jackofalltrades
Strategy
Kivra Liquidity Nodes [JOAT]Kivra Liquidity Nodes
Introduction
Kivra Liquidity Nodes is an open-source right-edge volume profile that finds high-participation price areas inside a configurable lookback window. It distributes each bar's volume across price rows, smooths the result, highlights the point of control, and labels local liquidity nodes.
The problem it solves is volume context. A raw profile can show where trading occurred, but it often becomes visually heavy. Kivra Liquidity Nodes keeps the profile compact, separates bullish and bearish participation estimates, and prioritizes POC, value area, and node labels. The profile is offset to the right of price, while the lookback range and value area remain visible on the active chart so the levels have context.
Core Concepts
1. Price-Overlap Volume Allocation
Each bar contributes volume to every row it overlaps. This makes the profile more representative than assigning all volume to a single close price.
2. Participation Split
The script estimates bullish and bearish participation from candle direction and close location inside the bar range. This is a proxy designed for visual context, not bid/ask delta.
3. Smoothed Node Detection
Profile rows are smoothed with neighboring rows. Local peaks above an average-volume threshold become liquidity nodes.
4. Value Area Expansion
The value area expands from the POC until the selected portion of total profile volume is covered.
5. Context Bands and Candle Tinting
The script shades the full lookback range, marks the value area across the live price region, draws node bands across the profiled window, prints VAH/VAL and POC labels far to the right of the profile to avoid overlap, and can tint candles using a pressure blend from trend location and candle direction.
Features
Right-edge profile: Clean horizontal profile projected to the right of the chart
POC line and label: Dashed level marking the highest-volume row
POC line and label: Dashed level marking the highest-volume row with price and row volume
VAH and VAL labels: Right-edge value-area high and low labels with dotted guide lines
Value area boxes: Shaded profile zone plus live-chart value band across the lookback
Lookback range box: Subtle range boundary around the profiled window
Bull/bear split bars: Row coloring estimates directional participation
Node labels: Local high-volume nodes with participation share and volume
Node bands: High-participation node rows project back across the profiled price window
Offset label rail: POC, VAH/VAL, and node labels are projected beyond the histogram so they do not sit on top of the profile
Pressure candle tint: Candles can be softly colored from bearish red to bullish green using trend location and candle direction
No-volume fallback: Uses range proxy when reliable volume is not available
Top-right dashboard: POC, node count, value area width, bias, range, and source
Input Parameters
Calculation:
Lookback Bars: Historical bars used for the profile
Profile Rows: Vertical resolution of the profile
Profile Width: Maximum right-edge width
Profile Offset: Distance from current bar to the profile
Value Area Portion: Portion of total profile volume included in value area
Node Threshold: Required row strength for node detection
Node Merge Gap: Distance allowed between merged node peaks
Max Node Labels: Maximum labels drawn for detected nodes
How to Use This Indicator
Step 1: Use the POC as the dominant participation level in the current lookback.
Step 2: Use the value area to understand where volume is concentrated.
Step 3: Watch VAH and VAL as acceptance/rejection boundaries.
Step 4: Watch labeled nodes as potential reaction or acceptance zones.
Step 5: Read the dashboard bias and candle tint as context, not as standalone entry signals.
Indicator Limitations
Bull/bear participation is an estimate based on candle structure, not exchange bid/ask data
The profile is recalculated on the latest bar and depends on the selected lookback
High node count can add visual density on small screens
Volume data quality varies by market and symbol
Originality Statement
Kivra Liquidity Nodes is original in its compact right-edge implementation combining overlap-based volume allocation, smoothed node detection, value area expansion, participation split visualization, and no-volume fallback logic. It does not copy third-party source code.
Disclaimer
This open-source indicator is provided for educational and informational purposes only. It is not financial advice. Volume nodes identify historical participation zones and do not guarantee future reactions.
-Made with passion by jackofalltrades
Indicator
Extreme Reversal Channel [JOAT]Extreme Reversal Channel
Introduction
Extreme Reversal Channel is an open-source adaptive channel that tracks persistent upper and lower extremes, gradually resets stale levels, and marks confirmed reversal conditions when price rejects a fresh extreme through the channel midpoint.
The problem it solves is stale channel context. Fixed lookback channels can jump abruptly as old bars roll out. Extreme Reversal Channel uses persistent state and controlled interpolation, creating smoother structural boundaries while still adapting to current price.
Core Concepts
1. Persistent Extreme Tracking
The upper channel updates when a new high exceeds the current upper core. The lower channel updates when a new low breaks the current lower core.
2. Counter-Based Reset
If no new extreme appears after the selected reset length, the stale level interpolates toward current price using the reset alpha setting.
upperCore := upperCore * (1.0 - alpha) + high * alpha
lowerCore := lowerCore * (1.0 - alpha) + low * alpha
3. Midpoint Reversal Confirmation
A bullish reversal requires a fresh lower extreme and a confirmed close back above the midpoint. A bearish reversal requires a fresh upper extreme and a confirmed close back below the midpoint.
4. Channel vs Trail Mode
Channel mode shows the upper, lower, and midpoint. Trail mode shows a single adaptive trailing reference derived from the current trend state.
Features
Adaptive upper/lower extremes: Persistent channel boundaries that update with new highs/lows
Reset interpolation: Stale levels drift toward current price instead of disappearing abruptly
Midpoint reversal logic: Reversal labels require closed-bar confirmation
Gradient channel fills: Upper and lower channel regions are lightly shaded
Optional trail mode: Converts the channel into a single adaptive stop reference
Top-right dashboard: Trend, mode, width, price position, reset age, and signal state
Alerts: Confirmed bullish and bearish reversal events
Input Parameters
Channel:
Reset Length: Bars allowed before an untouched extreme resets
Reset Alpha: Interpolation speed toward current price
Body Filter: Minimum candle body quality for reversal labels
Trailing Mode: Switches from full channel to trail display
How to Use This Indicator
Step 1: Use the channel boundaries as adaptive structural extremes.
Step 2: Watch for midpoint rejections after fresh extremes.
Step 3: Use trail mode when you want a simpler directional reference.
Step 4: Read price position and channel width in the dashboard before interpreting a reversal.
Indicator Limitations
Reversal labels can be early in strong breakout conditions
Very narrow channels require caution because small moves can cross the midpoint easily
The channel is adaptive context, not a complete trade system
Signals are confirmed on closed bars and do not use future references
Originality Statement
Extreme Reversal Channel is original in its combination of persistent extreme tracking, reset interpolation, midpoint rejection logic, optional trail mode, and compact dashboard output. It does not copy third-party source code.
Disclaimer
This open-source indicator is provided for educational and informational purposes only. It is not financial advice. Market conditions can invalidate reversal context, and risk management remains essential.
-Made with passion by jackofalltrades
Indicator
Market Euphoria Index - MEI - Predict Market Tops & BottomsA composite macro indicator designed to peak BEFORE major equity market tops — not during the crash.
Most "fear & greed" gauges are coincident: they spike with the panic, not before it. The MEI flips that. It measures how much euphoria and late-cycle stress have built up over months of bull market, so it tends to peak in the run-up to a top rather than at the bottom.
What it captured historically (visual backtest on monthly SPX):
— Climbed into the red zone ahead of the August 1987 top
— Peaked ahead of the March 2000 dot-com top
— Peaked ahead of the October 2007 GFC top
— Peaked ahead of the January 2022 top
— Dropped to the extreme-fear zone near every major bear-market bottom that followed
The six components (default weights):
— Price extension vs 5-year SMA (30%) — the primary leading signal. SPX has been 25-55% above its 5-year average at every major top since 1980.
— Yield curve un-inversion clock (25%) — tracks months since the 10Y-2Y spread last went negative. Peak warning is 0-12 months after the curve un-inverts (this is the actual recession trigger, historically).
— VIX 12-month average (15%) — captures sustained complacency, not single panic spikes. Low for a year = top buildup.
— Inflation re-acceleration (10%) — 6-month change in CPI YoY. Late-cycle inflation shocks (2000, 2007, 2022) are the classic top catalyst.
— Real rate stress (10%) — 10Y nominal yield minus CPI YoY. High and rising = tightening financial conditions.
— Fed cycle position (10%) — high and plateauing = peak late cycle; aggressive cuts = bottom signal.
How to read the line:
— Above 80 (red) = EXTREME EUPHORIA, historical top zone, reduce risk
— 65 to 80 (orange) = Euphoria warning, late cycle, tighten stops
— 35 to 65 (gray) = Neutral
— 20 to 35 (green) = Fear, opportunity zone
— Below 20 (lime) = EXTREME FEAR, historical bottom zone
Best timeframe: monthly (M) or weekly (W) on SPX, NDX, QQQ, or SPY. All economic data is fetched at monthly resolution regardless of your chart's timeframe, so the indicator reads the same whether you're on D, W, or M.
Customizable: every component weight and threshold is exposed in the settings. Bump up "Price extension" if you want more sensitivity to bubbles, or "Yield curve" if you trust macro recession signals more than price action.
Built-in alerts: Euphoria warning, Extreme euphoria, Fear, Extreme fear — all four crossovers are configurable from the alert menu.
To overlay on SPX: right-click the indicator name, then "Move pane to" then "Above", then "Pin to scale" to give it its own axis on the price chart.
Data sources (all free, built into PulseWire):
SP:SPX, FRED:T10Y2Y, CBOE:VIX, ECONOMICS:USIRYY, FRED:FEDFUNDS, TVC:US10Y
Honest limitations:
— This is a macro/cyclical tool, useless for intraday or short-term timing.
— Designed to call major bull/bear turning points, not 10-20% corrections.
— The 2020 COVID crash was an exogenous shock no macro model could predict; the MEI would not have warned you.
— Past patterns are not guarantees. Current dynamics (AI capex, geopolitics, structural inflation) may break historical relationships.
— Not financial advice. Use alongside your own analysis. Indicator
Delta Imbalance Map [JOAT]Delta Imbalance Map
Introduction
Delta Imbalance Map is an open-source imbalance mapping tool that identifies fair value gaps and scores them using gap size, candle drive, volume rank, and lower-timeframe participation tilt. The goal is to show not only where an imbalance exists, but whether the participation behind it is meaningfully tilted.
The problem this indicator solves is noisy zone plotting. Many imbalance tools mark every three-bar gap with equal importance. Delta Imbalance Map uses permissive defaults so important gaps appear often, then manages overlap so newer or stronger zones replace stale overlapping zones. Each active zone can carry its own compact right-edge data tag with price range, score, participation lead, and gap size in ATR units.
Core Concepts
1. Three-Bar Imbalance Detection
The script detects bullish gaps when the current low is above the high two bars back, and bearish gaps when the current high is below the low two bars back.
bullGap = low > high
bearGap = high < low
2. Lower-Timeframe Participation Split
The script requests lower-timeframe volume, close, and open arrays. Intrabars closing up are counted as buyer participation, intrabars closing down are counted as seller participation, and flat intrabars are split.
3. Composite Zone Score
Each new zone receives a quality score from gap size relative to ATR, lower-timeframe tilt, candle body drive, and volume rank. Optional minimum tilt and volume-rank inputs can tighten the feed when a chart becomes too busy.
4. Overlap Management
If a new zone overlaps an existing zone, filled overlaps are cleared and active overlaps are resolved by score. This keeps a generous stream of zones without stacking many boxes at the same price.
5. Zone Rails and Data Tags
Each imbalance draws a subtle outer glow box, direction-colored gradient edge, green buy-participation section, red sell-participation section, dashed top and bottom price rails, a dotted internal participation split line, and compact labels beside the related zone. Visible labels are capped and staggered to avoid covering the chart.
Features
ATR-filtered imbalance detection: Removes tiny gaps below the selected size threshold
Lower-timeframe delta proxy: Uses intrabar candle direction to estimate buyer/seller participation
Split-zone coloring: Zones are divided into bullish and bearish participation areas
Gradient glow boxes: Outer zone shell shifts from cyan/violet into bull/bear edge colors based on score
Price rail system: Top, bottom, and internal split lines extend to the right edge
Compact capped tags: Active and filled tags are limited and staggered to reduce label overlap
Quality score tags: Each active zone can show price range, score, participation lead, and ATR gap size
Mitigation modes: Touch or full-fill logic
Overlap guard: Keeps the stronger of overlapping zones
Color-faded filled zones: Filled zones remain visible by default with compact zone labels
Candle tilt tinting: Candles can be softly tinted by the active imbalance tilt
Birth-bar mitigation guard: New zones cannot be marked filled on the same candle they are created
Top-right dashboard: Active count, filled count, bull/bear count, average score, tilt, lower timeframe, state, and fill mode
Alerts: New bullish and bearish imbalance creation events
Input Parameters
Detection:
Delta Lower TF: Lower timeframe used for participation split
Min Gap ATR: Minimum gap size relative to ATR
Min Delta Tilt: Minimum buyer/seller skew needed to accept a zone
Min Volume Rank: Minimum volume percentile required for plotting a new zone
Mitigation: Touch or Full Fill
Prefer Stronger Overlap: Removes weaker overlapping zones
Zone Life Bars: Maximum active lifetime for unfilled zones
How to Use This Indicator
Step 1: Look for active zones that remain unfilled.
Step 2: Read the tag score and buyer/seller tilt.
Step 3: Use the top and bottom rails as the exact price boundaries of the imbalance.
Step 4: Use the dashboard state to see if active zones lean buyer-led, seller-led, or balanced.
Step 5: Treat mitigated zones as resolved context rather than fresh trade signals.
Indicator Limitations
Lower-timeframe participation is a candle-direction volume proxy, not true bid/ask delta
Some lower timeframes may not be available on every PulseWire plan or symbol
Fair value gaps can remain open for long periods or fail to react when revisited
Signals and zones are created on confirmed bars to reduce repaint risk
Originality Statement
Delta Imbalance Map is original in its combination of ATR filtering, lower-timeframe participation tilt, composite scoring, overlap prioritization, mitigation lifecycle, and dashboard summarization. It does not copy third-party source code.
Disclaimer
This open-source indicator is for educational and informational use only. It is not financial advice and does not predict that an imbalance will fill or reverse price. Always use proper risk management.
-Made with passion by jackofalltrades
Indicator
Aureon Pressure Lens [JOAT]Aureon Pressure Lens
Introduction
Aureon Pressure Lens is an open-source pressure oscillator designed to classify directional participation, conviction, and transition states in a separate pane. It blends price impulse, EMA structure, momentum, range location, candle body pressure, and relative volume into one bounded score.
The problem it solves is signal quality. A single oscillator can fire during weak, low-participation moves. Aureon Pressure Lens requires pressure, signal-line behavior, relative volume, and component consensus to align before confirmed buy or sell labels appear.
Core Concepts
1. Multi-Component Pressure Blend
The oscillator uses several independent inputs: impulse from prior price, fast/slow structural slope, normalized momentum, range position, and candle body direction.
2. Tanh Normalization
Each component is normalized into a stable bounded range so one volatile input does not dominate the entire reading.
pressureScore = f_tanh(pressureBlend * 1.60) * 100.0
signalLine = ta.ema(pressureScore, signalLength)
3. Consensus Filter
The confidence reading measures how closely the components agree. A signal must satisfy the minimum conviction threshold before it can print.
4. Relative Volume Participation
The script measures current volume against a moving average and uses that reading as a participation gate. The default is permissive enough for broad use while still filtering extremely quiet conditions.
Features
Separate-pane pressure score: Bounded -100 to +100 directional pressure reading
Signal line: Smoothed reference for pressure resets and crossovers
Gradient pressure color: Score color transitions between bearish, neutral, and bullish states
Pressure cloud: Optional fill between pressure and signal line
Confirmed BUY/SELL labels: Closed-bar events filtered by consensus and RVOL
Top-right dashboard: State, bias, pressure, signal, RVOL/conviction, and action
Alerts: Bullish and bearish confirmed pressure resets
Input Parameters
Calculation:
Core Lookback: Main analysis window for impulse and range context
Fast Lens / Slow Lens: EMA structure lengths
Signal Lens: Smoothing length for the signal line
Pressure Sensitivity: Normalization intensity
Min Relative Volume: Participation gate for labels
Min Conviction: Minimum component agreement required for labels
How to Use This Indicator
Step 1: Read the pressure score relative to zero.
Step 2: Use the cloud and signal line to identify pressure resets.
Step 3: Check dashboard conviction and RVOL before acting on labels.
Step 4: Combine with an overlay structure or regime tool for full chart context.
Indicator Limitations
The oscillator measures current pressure, not future price direction
Relative volume can behave differently on symbols with limited volume data
Choppy markets can create repeated signal-line crosses
Confirmed labels appear only after the bar closes
Originality Statement
Aureon Pressure Lens is original because it combines impulse, structure, momentum, range position, candle body pressure, relative volume, and component consensus into a single closed-bar pressure engine with a dedicated dashboard. It does not copy third-party source code.
Disclaimer
This open-source indicator is for educational and informational purposes only. It is not financial advice. Markets can change quickly, and no pressure reading guarantees a future move. Use risk controls and independent analysis.
-Made with passion by jackofalltrades
Indicator
Adaptive Forecast Bands [JOAT]Adaptive Forecast Bands
Introduction
Adaptive Forecast Bands is an open-source adaptive regression and mean-reversion framework. It estimates a live fair-value path from price, wraps that path in volatility-aware bands, and marks confirmed re-entry conditions only after the bar closes.
The problem this indicator solves is context around stretched price. A static moving average band can lag badly when volatility changes. Adaptive Forecast Bands uses a recursive regression engine, a live model error estimate, and an ATR blend so the envelope expands and contracts with current market behavior.
Core Concepts
1. Adaptive Regression Mean
The centerline is built from a persistent two-parameter regression state. The script uses normalized local time so the model does not depend on raw bar index growth over long histories.
forecastMean = beta0 + beta1 * xNorm
forecastErr = source - forecastMean
2. Error-Based Confidence Bands
Band width is derived from the model's exponentially weighted error plus an ATR component. This keeps the band reactive to both forecast error and realized volatility.
3. Confirmed Re-Entry Signals
The script arms a long or short setup when price reaches an outer band. A signal only prints when price confirms a re-entry back through the relevant band on `barstate.isconfirmed`.
4. Forecast Guide Lines
The right-edge guide projects the current regression slope forward for visual context. It is a guide, not a prediction, and is redrawn on the last bar to avoid object clutter.
Features
Adaptive fair-value line: Recursive regression centerline based on current price behavior
Volatility-aware envelope: Error variance and ATR combine to form dynamic upper/lower bands
Confirmed long/short labels: Re-entry signals use closed-bar logic
Right-edge forecast guide: Dashed and dotted guide lines show current slope context
Top-right dashboard: Bias, confidence, band width, slope, guide state, and signal state
Alert conditions: Long and short confirmed re-entry events
Input Parameters
Model:
Source: Price source used by the model
Forgetting Factor: How quickly the model adapts to new price information
Regression Horizon: Normalization horizon for the regression slope
Band Multiplier: Multiplier applied to model error
ATR Blend: Extra realized-volatility padding in the band width
Rebase Interval: Periodic reset to keep the adaptive model stable
How to Use This Indicator
Step 1: Use the centerline as an adaptive fair-value reference.
Step 2: Treat outer-band touches as stretched conditions, not immediate entries.
Step 3: Wait for confirmed re-entry labels when enabled.
Step 4: Read the dashboard confidence and slope before interpreting the signal.
Indicator Limitations
The right-edge guide is a visualization of current model slope, not a forecast guarantee
Mean-reversion signals can underperform during strong directional trends
The model periodically rebases by design to reduce long-history numerical drift
Signals are confirmed on closed bars and can appear after the intrabar extreme occurred
Originality Statement
Adaptive Forecast Bands is an original JOAT implementation combining normalized recursive regression, error-based confidence bands, ATR blending, confirmed re-entry logic, and a compact interpretive dashboard. It does not copy third-party source code.
Disclaimer
This open-source indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any financial instrument. Trading involves risk, and historical behavior does not ensure future results. Always use proper risk management.
-Made with passion by jackofalltrades
Indicator
Sentinel Trailing Bench [JOAT]Sentinel Trailing Bench
Introduction
Sentinel Trailing Bench is an open-source contextual trailing-stop overlay designed to behave differently from a standard ATR stop. It blends a sorted price-distribution engine, ATR protection, adaptive recovery behavior, and a benchmark rail so the trailing structure can react to both volatility and local value geometry.
The problem Sentinel solves is stop quality. Simple trailing stops either hug price too tightly in noisy conditions or drift too far away to be useful. Sentinel uses neighborhood structure from a sorted close buffer to estimate contextual bands, then mixes that with ATR logic and recovery tightening when the active side is under pressure.
Core Concepts
1. Sorted distribution engine
The script maintains a rolling close buffer and a sorted mirror of that buffer. This allows it to derive contextual neighborhood slices around the current price instead of relying on ATR alone.
2. Percentile-derived context bands
Supportive and defensive reference levels are estimated from the nearby distribution rather than only from recent swing points.
3. ATR-backed resilience
An ATR anchor remains part of the design so the stop still respects current volatility when distribution structure becomes thin or unstable.
4. Recovery tightening
If price moves materially against the active side relative to the last switch price, the adaptive rail is pulled closer to price to avoid stale trailing behavior.
5. Institutional bench display
The overlay shows the active stop, a benchmark line, the adaptive rail, directional clouding, candle tinting, and a compact dashboard that summarizes trend state, value state, stop gap, and recovery status.
Features
Distribution-aware trailing stop: Uses a sorted close engine and local neighborhood structure
ATR defensive anchor: Keeps the stop grounded in current volatility
Adaptive recovery pull: Tightens the guidance rail when the active side is stressed
Benchmark line and adaptive rail: Adds visual context beyond the raw stop itself
Directional cloud and candle tint: Clean visual bias cues without retail-style arrows
Top-right dashboard: Reports trend state, regime context, value position, stop gap, and recovery status
Confirmed-bar flips: Regime flips are confirmed on closed bars only
Input Parameters
Core:
Distribution Buffer
Neighborhood Radius
ATR Length
ATR Anchor
Benchmark Length
Context:
Distribution Blend
Recovery Threshold xATR
Recovery Pull
Anchor Smoothing
Visuals:
Show Benchmark
Show Adaptive Rail
Show Band Clouds
Color Candles
Show Dashboard
How to Use This Indicator
Step 1: Read the active side
The dashboard and cloud color show whether the stop is currently managing an ascent or descent state.
Step 2: Watch stop gap and rail gap
The dashboard shows how far price sits from the active stop and adaptive rail in ATR terms. This helps frame whether the trailing structure is loose or tight.
Step 3: Monitor recovery
If recovery becomes active, the stop structure is signaling that the current side is under stress and the rail is tightening.
Step 4: Use it as trade management context
Sentinel is most effective as a management tool layered onto entries generated elsewhere.
Indicator Limitations
Distribution-derived bands depend on the sample window and will evolve as new closes enter the buffer
In extremely fast conditions, any trailing stop can still gap beyond the intended exit area
Recovery tightening improves responsiveness but can also accelerate exits in choppy reversals
Originality Statement
Sentinel Trailing Bench is original in how it fuses sorted-distribution neighborhood structure, ATR resilience, and adaptive recovery behavior into one trailing-stop overlay. It is published because:
The stop uses local price distribution context instead of ATR alone
The recovery module changes behavior when the active side is materially under pressure
The benchmark, rail, cloud, and dashboard turn trailing logic into a full management framework rather than a single line
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice and does not guarantee future market behavior. Trailing stops can still be affected by volatility shocks, gaps, and structural changes in the market. Always use independent judgment and proper risk management.
Indicator
Parallax Density Atlas [JOAT]Parallax Density Atlas
Introduction
Parallax Density Atlas is an open-source price-acceptance overlay that maps where the market has spent the most time doing business across a recent lookback. It combines a kernel density estimate of recent closing prices with percentile-based value rails so the user can see both the smooth acceptance curve and the practical operating envelope around it.
The problem Parallax solves is hidden value structure. Traders often know whether price is moving, but not whether that movement is taking place inside accepted value, above value, or below value. Parallax puts that information directly on the chart through a point of control, value area boundaries, rails, cloud zones, and a concise dashboard.
Core Concepts
1. Kernel density estimation
The script evaluates a Gaussian kernel across recent closes to estimate continuous price density:
densitySum += gaussianKernel((evalPrice - samplePrice) / bandwidth)
densityValue = densitySum / (array.size(closeSample) * bandwidth)
This creates a smooth value map instead of a stepped histogram alone.
2. Point of control and value area
The highest-density node becomes the point of control. From there, the script expands outward until the target percentage of total density is captured, defining the value area high and low.
3. Percentile rails
In parallel with the KDE engine, the script maintains sorted close samples and derives lower and upper rails from user-defined percentiles. Those rails create a stable operating envelope around recent value.
4. Density cloud
Only the densest accepted zones inside the value area are shaded as a cloud, keeping the display focused on high-importance price zones rather than every possible level.
5. Context and skew
The dashboard reports whether current price is accepted inside value, expanding above value, or trading below accepted value, along with skew and rail width.
Features
KDE value map: Smooth density estimate built from recent closes
Point of control: Highest-density price node marked directly on the chart
Value area boundaries: High and low edges of accepted price territory
Percentile value rails: Smoothed lower and upper rails from sorted price samples
Density cloud: Highlights only the strongest accepted zones
Right-side profile: Extends density visually to the right of current price
Optional candle tinting: Reflects where price sits inside the value structure
Top-right dashboard: Shows POC, value area, rail width, skew, and current location state
Input Parameters
Density Engine:
Lookback
Density Steps
Bandwidth Multiplier
Value Area Percent
Value Rails:
Lower Rail Percentile
Upper Rail Percentile
Rail Smoothing
Visual System:
Profile Width Bars
Cloud Threshold
Show Density Cloud
Show Right Profile
Tint Candles
Show Dashboard
How to Use This Indicator
Step 1: Start with location
Read whether price is inside value, above value, or below value. This defines whether the market is rotating in accepted territory or exploring away from it.
Step 2: Use POC as the acceptance anchor
The point of control marks the most accepted price in the sample window. Reactions around it can frame mean-reversion and acceptance behavior.
Step 3: Compare rails with value area
The rails provide a smoothed operating envelope while the value area shows the densest accepted region. Using both together gives a more complete value map.
Step 4: Monitor skew
Positive skew means the density center is leaning upward in the sample range. Negative skew means accepted value is leaning lower.
Indicator Limitations
The density map is lookback-dependent and will evolve as old data leaves the sample
KDE on closing prices is an acceptance approximation, not a full order-flow model
Strong trends can stay outside accepted value for extended periods
Originality Statement
Parallax Density Atlas is original in how it pairs a continuous KDE-based value map with percentile rails and a selective density cloud in one overlay. It is published because:
The script combines smooth value estimation with rail-based structure instead of using one method alone
It focuses the cloud only on high-density accepted regions, preserving chart cleanliness
The dashboard turns the density map into a practical location framework rather than a purely visual profile
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice and does not guarantee future market behavior. Value zones can shift as new data enters the sample, and persistent trends can stay outside accepted areas longer than expected. Always use independent judgment and proper risk management.
Indicator
Meridian Stochastic Regime Suite [JOAT]Meridian Stochastic Regime Suite
Introduction
Meridian Stochastic Regime Suite is an open-source adaptive oscillator built for traders who want more context than a standard stochastic line can provide. The script combines a centered stochastic engine, an adaptive response model, and a regime profile so the oscillator changes character as the market shifts between trend, compression, expansion, and balance.
The problem Meridian solves is signal quality. Standard oscillators often look clean, but they do not explain whether momentum is occurring inside a compressed market, an expanding breakout phase, or a stable trend. Meridian adds that context directly into the oscillator architecture so the same reading can be interpreted differently depending on the active regime profile.
Core Concepts
1. Centered stochastic architecture
Price is pre-smoothed first, then converted into a stochastic reading that is centered around 50 so directional pressure is easy to interpret:
smoothHigh = ta.ema(high, priceSmoothLen)
smoothLow = ta.ema(low, priceSmoothLen)
smoothClose = ta.ema(close, priceSmoothLen)
rawStoch = 100.0 * (smoothClose - ta.lowest(smoothLow, stochLen)) / stochRange
2. Adaptive response engine
The main oscillator does not use static smoothing alone. Its response speed and gain expand or contract based on the regime profile:
gainBias = gainBase + trendScore * 0.38 + expansionScore * 0.18 - compressionScore * 0.12
speedBias = responseBase + trendScore * 0.08 + expansionScore * 0.04
adaptiveOsc := adaptiveOsc + speedBias * (adaptiveSeed - adaptiveOsc )
This helps the oscillator respond differently in directional and compressed conditions.
3. Embedded regime scoring
Meridian computes four internal state scores:
Trend
Compression
Expansion
Balance
Those scores are derived from ATR behavior, path efficiency, and slope strength, then normalized into a regime profile shown in the dashboard.
4. Spread and signal layer
The script compares the adaptive oscillator to a slower signal line and visualizes the spread around the neutral axis. This gives a direct view of acceleration versus drag.
5. Institutional oscillator panel
The panel uses restrained zones, layered fills, and a top-right dashboard instead of loud markers. The result stays readable while still carrying multiple analytical dimensions.
Features
Centered stochastic core: Keeps the oscillator readable around a neutral midpoint
Adaptive response model: Gain and speed shift with the internal regime profile
Four-state regime map: Trend, Compression, Expansion, and Balance
Fast line and signal line: Shows momentum acceleration versus stabilization
Spread shading: Highlights when the adaptive oscillator is separating from the signal line
Regime dashboard: Displays state, confidence, adaptive reading, signal reading, and regime profile shares
Confirmed-bar flips: Internal state transitions are tracked on closed bars
Non-repainting design: Uses only current-timeframe data and no future references
Input Parameters
Stochastic Core:
Price Pre-Smoothing
Stochastic Length
Fast Smoothing
Adaptive Signal Smoothing
Regime Filter:
Regime Window
ATR Window
Base Oscillator Gain
Base Response Speed
Visual Output:
Show Adaptive Zones
Show Centered Fast Line
How to Use This Indicator
Step 1: Start with the regime
Read the dashboard first. Trend and Expansion regimes support directional interpretation. Compression and Balance call for more caution.
Step 2: Watch adaptive versus signal spread
When the adaptive line separates cleanly from the signal line, momentum is strengthening. When the spread compresses, the move is losing urgency.
Step 3: Use the centered fast line as timing context
The fast line helps show whether short-term momentum is leading or lagging the adaptive engine.
Step 4: Avoid isolated readings
Meridian is strongest when used alongside a structure or value-based tool rather than as a standalone trade trigger.
Indicator Limitations
Like all oscillators, Meridian can remain elevated or depressed during strong directional trends
Compression states may delay re-acceleration readings until volatility expands again
The regime profile is descriptive, not predictive
Originality Statement
Meridian Stochastic Regime Suite is original in how it embeds a four-state regime profile directly into the adaptive behavior of a centered stochastic engine. It is published because:
The oscillator response changes with internal market-state measurements instead of using only fixed smoothing
The script surfaces trend, compression, expansion, and balance as percentages inside the same panel
The panel and dashboard design turn regime context into an interpretable momentum framework rather than a generic stochastic clone
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice or a recommendation to trade. Oscillator readings can remain extreme for extended periods, and regime classifications can shift as conditions evolve. Always use independent judgment and proper risk management.
Indicator
Covenant Regime Register [JOAT]Covenant Regime Register
Introduction
Covenant Regime Register is an open-source market context indicator that classifies whether price is currently behaving like a directional auction or a rotational auction. Instead of treating trend detection as a single yes-or-no output, the script builds two competing probability streams and continuously updates which state has stronger evidence.
The problem this indicator solves is context drift. Many tools are applied the same way in every environment even though trending conditions and ranging conditions reward very different decisions. Covenant Regime Register separates those environments first, then exposes confidence, directional efficiency, and bias so the trader can decide whether to lean into continuation logic or step back into rotation logic.
Core Concepts
1. Multi-factor regime observations
The regime engine does not rely on one input. It blends normalized returns, normalized volatility, directional efficiency, and slope persistence into a two-state regime model:
logReturn = math.log(close / nz(close , close))
realizedVol = ta.stdev(logReturn, volatilityLength)
efficiencyRatio = math.abs(close - close ) / math.sum(math.abs(ta.change(close)), efficiencyLength)
This keeps the classification grounded in both movement quality and volatility behavior.
2. Probabilistic state competition
Directional and rotational states each receive an emission score. Those scores are then smoothed through a persistence-heavy probability engine so the output does not flip on every small fluctuation:
posteriorTrend = emissionTrend * priorTrend
posteriorRange = emissionRange * priorRange
trendProb := trendProb + learningInput * (targetTrend - trendProb)
The result is a stable state register rather than a noisy binary switch.
3. Confidence-aware classification
The script only considers a regime confirmed when the dominant state exceeds the user-defined confidence threshold on a confirmed bar. This helps reduce false transitions during temporary turbulence.
4. Probability spread visualization
Trend probability and range probability are plotted together, while the spread between them is shaded as a separate area. This lets the user see whether the market is decisively one-sided or only marginally biased.
5. Institutional dashboard
The top-right dashboard reports current state, confirmation status, trend probability, range probability, efficiency, and directional bias using a restrained dark palette designed to stay readable on a clean chart.
Features
Two-state regime model: Directional auction versus rotational auction
Multi-factor classification: Uses returns, volatility, efficiency, and slope instead of a single oscillator threshold
Probability outputs: Trend and range are shown as separate probability streams
Confidence gate: Regimes are only considered confirmed above the user-defined threshold
Spread visualization: Shows the separation between the two competing states
Dark institutional dashboard: Compact top-right panel with current state and supporting metrics
Confirmed-bar regime alerts: Alerts only fire when a new regime is confirmed on bar close
Non-repainting design: Uses only current-timeframe information and confirmed-bar state transitions
Input Parameters
Regime Engine:
Return Lookback: Smoothing window for the return series
Volatility Lookback: Window used to normalize realized volatility
Efficiency Length: Measures directional travel versus rotational travel
Probability Learning: Controls how quickly the posterior probabilities adapt
Trend Confirmation Threshold: Minimum dominant probability required before a regime is treated as confirmed
Visual System:
Show Regime Backdrop
Show Probability Spread
Show State Ribbon
Show Dashboard
How to Use This Indicator
Step 1: Read the dominant state
If Trend Probability is above Range Probability and the confidence threshold is met, the market is behaving more directionally. If Range Probability dominates, the market is behaving more rotationally.
Step 2: Check confirmation
Use the confirmation state before treating the output as actionable. Developing readings can still change as the current bar closes.
Step 3: Use efficiency and bias together
High efficiency with strong directional bias supports continuation logic. Low efficiency with range dominance supports mean-reversion or lower-aggression decision making.
Step 4: Apply it as a filter
This indicator is best used as a context layer for other tools. It is not intended to predict the next bar by itself.
Indicator Limitations
Regime models classify the present environment; they do not forecast future direction
Extremely fast reversals can temporarily lower confidence before the new state stabilizes
Range and trend can overlap during transition periods, so marginal readings should be treated cautiously
Originality Statement
Covenant Regime Register is original in how it combines normalized return behavior, normalized volatility, directional efficiency, and slope persistence into a compact two-state probability register with an explicit confidence gate. It is published because:
The script produces competing regime probabilities rather than a single trend flag
The classification emphasizes state persistence and bar-close confirmation instead of hyper-reactive regime flipping
The dashboard surfaces regime context in a compact format suitable for use as a decision filter alongside other indicators
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice and does not guarantee future market behavior. All regime classifications are derived from historical and current price behavior and can produce false or delayed readings. Always use independent judgment and proper risk management.
Indicator
Concordance Allocation Strategy [JOAT]Concordance Allocation Strategy
Introduction
Concordance Allocation Strategy is an open-source PulseWire strategy that integrates regime detection, directional bias, momentum alignment, value-location filtering, and ATR-based risk management into one non-repainting framework. It is designed to trade only when multiple independent layers agree on bar close.
The problem this strategy solves is isolated signal bias. A single good-looking signal can fail quickly if it appears in the wrong market regime, against the wrong directional structure, or in the wrong part of value. Concordance requires those layers to align before it enters a trade, then manages risk with fixed ATR targets and adaptive exits.
Core Concepts
1. Regime filter
The strategy uses a probability-based trend-versus-range classifier. Trades are only considered when the directional regime is confirmed on a closed bar.
2. Directional bias engine
An ATR-based bias band adapts to noisy conditions and recovery stress so long and short bias are not driven by a simple moving average cross.
3. Momentum confirmation
A centered adaptive stochastic spread must align with the directional side. This prevents entries based on trend context alone.
4. Value-location filter
The strategy requires price to be properly aligned with percentile-derived value rails before entries are allowed. This helps avoid chasing direction in poor location.
5. Structured risk management
Every position uses:
ATR stop loss
ATR take profit
Adaptive trailing behavior once price extends far enough
Context exits when regime or momentum deteriorates
Features
Multi-layer entry filter: Regime, bias, momentum, and value must agree
Bar-close confirmation: Entries are evaluated using confirmed-bar logic
ATR stop loss and take profit: Risk is defined from volatility, not fixed ticks
Adaptive exit behavior: Bias band can tighten once the move extends
No higher-timeframe dependency: Uses current-timeframe calculations only
Institutional dashboard: Shows exposure state, regime, momentum, bias band, and value rails
Non-repainting framework: No future references and no lookahead logic
Input Parameters
Regime Layer:
Return Lookback
Volatility Lookback
Efficiency Length
Regime Learning
Trend Gate
Directional Bias:
ATR Length
ATR Base Multiplier
Avoidance Expansion
Recovery Pull
Noise Threshold ATR
Momentum Layer:
Stochastic Length
Stochastic Smoothing
Price Presmoothing
Adaptive Attenuation
Momentum Spread Gate
Value Layer:
Value Lookback
Lower Rail Percentile
Upper Rail Percentile
Rail Smoothing
Risk Layer:
Stop ATR
Take Profit ATR
Trail Activation ATR
Trail Buffer ATR
How to Use This Strategy
Step 1: Read the regime
The strategy only acts when the directional regime is confirmed. If the regime is rotational, it stands down.
Step 2: Confirm directional bias
The ATR bias band must agree with the side of the trade. This avoids taking long momentum setups under bearish structure or the reverse.
Step 3: Check momentum and value together
Momentum must align with the side and price must be operating in the correct value location. Both filters are required.
Step 4: Review risk settings before use
Stop and target multiples should be adjusted to the market and timeframe being tested. The defaults are intended to be realistic rather than aggressively optimized.
Strategy Limitations
No strategy can eliminate false regime transitions or rapid reversals
Percentile value rails adapt to the sample window and may lag sudden structural changes
The strategy is designed for realism and context alignment, not maximum trade frequency
Originality Statement
Concordance Allocation Strategy is original in how it requires regime confirmation, directional bias, momentum agreement, and value-location agreement before allowing entries. It is published because:
The strategy avoids isolated indicator triggers and instead uses a layered confirmation model
Its risk logic combines fixed ATR objectives with adaptive context exits
The design is intentionally current-timeframe, bar-close confirmed, and non-repainting
Disclaimer
This strategy is provided for educational and informational purposes only. It is not financial advice, and backtest results do not guarantee future performance. Trading involves risk of loss, and any strategy can underperform or fail in changing market conditions. Always evaluate settings carefully and use proper risk management.
Strategy
Aurelian Auction Ledger [JOAT]Aurelian Auction Ledger
Introduction
Aurelian Auction Ledger is an open-source range and auction analysis overlay designed to identify compressive trade zones, map their internal value structure, and show how price behaves when it tests the edges of that ledger. The script builds a live range shell, calculates a point of control and value area, tracks sweep events, and presents the active auction state in a top-right dashboard.
The problem Aurelian solves is hidden range structure. Consolidation zones are often treated as simple rectangles, but not all ranges are equal. Some are balanced, some lean toward accumulation, some toward rejection, and many fail through one-sided sweeps before resolving. Aurelian turns that internal auction structure into something visible.
Core Concepts
1. Compression-based ledger build
The script measures whether recent bars are tight enough in ATR terms, efficient enough in body structure, and balanced enough in directional pressure to qualify as a live auction ledger.
2. Range shell and internal value area
When a ledger is active, the script draws:
The outer ledger shell
The internal value area
The point of control
This separates broad range boundaries from the price zone where most business is actually being done.
3. Right-side auction profile
Volume is accumulated across profile rows inside the active ledger so the script can identify the highest-volume row and estimate the value area around it.
4. Sweep tracking
Upper and lower sweep events are tracked only on confirmed bars. This helps distinguish clean acceptance from failed range probes.
5. Ledger tilt
The indicator maintains a directional tilt metric so the range shell is not displayed as neutral by default. If the auction begins leaning toward acceptance or rejection, the color balance reflects that change.
Features
Compression-driven range detection: Searches for structured auction zones rather than generic boxes
Live range shell: Displays the active ledger high, low, and midpoint
Point of control and value area: Maps where the auction is most concentrated
Right-side profile: Extends the auction structure visually beyond the current bar
Sweep detection: Tracks confirmed probes beyond the ledger edges
Auction tilt readout: Shows whether the range is leaning toward acceptance or rejection
Top-right dashboard: Reports mode, compression, width, POC, value area, sweeps, and tilt
Non-repainting event logic: Sweep and breakout conditions are confirmed on bar close
Input Parameters
Ledger Core:
ATR Length
Ledger Build Bars
Compression Ceiling
Body Efficiency Ceiling
Directional Balance Ceiling
Breakout Buffer
Auction Profile:
Profile Rows
Profile Width
Value Area Coverage
Visuals:
Show Range Shell
Show Right-Side Profile
Show Sweep Marks
Tint Auction Bars
Show Dashboard
How to Use This Indicator
Step 1: Confirm that a ledger is live
Check the dashboard mode first. If the ledger is not active, the script is still scanning for a qualified auction structure.
Step 2: Watch the POC and value area
These levels show where the auction is concentrated and whether price is rotating inside value or challenging the edges.
Step 3: Track sweeps versus acceptance
Confirmed sweep events can mark failed probes. If price repeatedly sweeps one side and returns, the ledger is revealing where excess is being rejected.
Step 4: Use tilt as context, not prediction
Ledger tilt helps interpret which side has more pressure, but the actual resolution still depends on whether price ultimately accepts outside the shell.
Indicator Limitations
The script is designed for structured ranges and will naturally stand down during broad directional moves
Volume distribution inside a candle is approximated using row allocation rather than true intrabar order flow
A qualified ledger can still break without first producing a sweep event
Originality Statement
Aurelian Auction Ledger is original in how it combines a compression-qualified range state, an internal profile-derived value area, sweep tracking, and directional tilt into a single clean overlay. It is published because:
The script distinguishes a structured auction ledger from a generic consolidation rectangle
It combines shell, POC, value area, and sweep tracking in one coherent range workflow
The tilt metric provides additional auction context without cluttering the chart with heavy labels
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice and does not guarantee future market behavior. Range structures can fail abruptly, and volume-based value estimates are still interpretations of historical trading activity. Always use independent judgment and proper risk management.
Indicator
Opening Auction Ledger [JOAT]Opening Auction Ledger
Introduction
Opening Auction Ledger is an open-source session framework built to standardize how the opening range is measured, locked, evaluated, and managed throughout the day.
The indicator is designed around a simple institutional question:
Once the opening auction is complete, is price accepting away from it or failing back into it?
The script answers that by combining:
session-specific opening range capture
high-low or body-based range construction
breakout qualification
relative volume confirmation
objective extension ladders
session profile rendering
adaptive continuation trail management
historical breakout tracking in a dashboard
This makes the opening range usable as more than a static box.
It becomes a complete session ledger.
Core Concepts
1. Opening Range Capture
The script builds the opening range only during the specified session window and then locks that range when the session ends.
This preserves a fixed reference for the rest of the day.
2. Source Flexibility
Users can define the opening range using raw highs and lows or candle bodies.
This changes how strict the opening auction frame is and can make the indicator more stable on noisy instruments.
3. Qualified Breakout Detection
Breaks are not accepted simply because price crosses a range boundary.
The script can require a minimum displacement beyond the range and, optionally, a relative-volume lift compared with recent activity.
4. Objective Laddering
Once a breakout is confirmed, the script projects three extension objectives above and below the opening range using multiples of the locked range size.
5. Continuation Management
An adaptive ATR trail follows the accepted breakout so continuation quality can be monitored after the initial move is underway.
Features
Configurable opening session: user-defined session window and timezone
Opening range lock: session range freezes after the auction ends
Body or high-low source mode: choose the structure used to build the range
Relative-volume breakout filter: optional confirmation prevents weaker breaks from being counted
Minimum displacement filter: breakout must exceed a configurable fraction of the locked range
Extension ladder: three upside and three downside objectives
Session profile: profile-style rendering of activity inside the opening auction
Continuation trail: adaptive ATR trail tracks accepted move quality
Historical outcome counters: dashboard tracks breakout counts and objective hit rates
Institutional dashboard: top-right summary of session state, range size, direction, and objective performance
Input Parameters
Opening Auction
Opening Range Session
Session Days
Timezone
Range Source
Minimum Break % Of Range
Require Relative Volume Lift
Relative Volume Threshold
Extension Ladder
Show Extension Ladder
Objective One
Objective Two
Objective Three
Show Price Labels
Auction Profile
Show Session Profile
Profile Rows
Profile Width Bars
Profile Offset Bars
Continuation Management
Show Adaptive Continuation Trail
Trail ATR Length
Trail ATR Multiplier
Display
Range Fill Transparency
Shade Session State
Dashboard Position
Dashboard Size
How to Use This Indicator
Step 1: Wait for the Range to Lock
Do not treat the opening range as final until the configured auction window is complete.
Before that point, the frame is still forming.
Step 2: Measure the Quality of the First Break
The first breakout matters most when it clears the minimum displacement rule and is supported by the configured relative-volume threshold.
Step 3: Use the Ladder as an Objective Map
The projected targets are not predictions.
They are structured expansion references derived from the opening range itself.
Step 4: Follow the Trail for Acceptance
The continuation trail helps determine whether price is still accepting away from the opening auction or beginning to fail back toward it.
Step 5: Review the Dashboard Statistics
The dashboard can help users understand how often objective ladders are being reached under the current settings and instrument behavior.
Indicator Limitations
The usefulness of the opening range depends heavily on the selected session and market traded
Relative-volume logic is chart-volume based and depends on the instrument's available volume series
Very narrow opening ranges can create closely spaced objectives in low-volatility sessions
A qualified breakout can still fail quickly in event-driven or thin-liquidity conditions
Originality Statement
Opening Auction Ledger extends the classic opening-range idea into a broader session framework by combining range locking, breakout qualification, objective ladders, profile context, continuation management, and outcome tracking in a single open-source script.
Disclaimer
This indicator is provided for educational and informational purposes only.
It is not investment advice and does not guarantee that any breakout or target sequence will succeed.
All calculations are based on historical chart data and should be interpreted with appropriate risk management and independent analysis.
Indicator
Harbor Reversal Ledger [JOAT]Harbor Reversal Ledger
Introduction
Harbor Reversal Ledger is an open-source reversal timing indicator that combines completed higher-timeframe candle context with confirmed local RSI divergence.
The objective is not to predict turning points early.
The objective is to wait for enough evidence that a reversal thesis is becoming structurally credible.
Many reversal tools repaint because they depend on unfinished higher-timeframe candles or unconfirmed pivot comparisons.
Harbor Reversal Ledger avoids that by:
requesting completed higher-timeframe candles only
confirming RSI pivots before evaluating divergence
scoring confluence from multiple independent ingredients
projecting higher-timeframe structure onto the execution chart
rendering a timing ledger in its own pane
Core Concepts
1. Completed Higher-Timeframe Context
The script requests prior higher-timeframe candles rather than reading the currently forming candle.
This keeps the higher-timeframe pattern engine stable and non-repainting.
2. Candle Pattern Recognition
Bullish and bearish engulfing patterns can be enabled, and pin-bar style rejection patterns can also be used.
These patterns contribute directional context, not automatic entries.
3. Confirmed RSI Divergence
Local price and RSI pivots are both confirmed using left/right pivot logic.
Only after the pivots are locked does the script compare price progression against RSI progression to determine bullish or bearish divergence.
4. Distance-to-Extreme Scoring
Reversal evidence becomes more meaningful when price is still close to a recent extreme.
The confluence engine therefore includes distance-based scoring relative to a configurable lookback.
5. Projection and Confluence Zones
Completed higher-timeframe candles can be projected forward on the execution chart, while divergence events can create local confluence zones when the evidence stack is strong enough.
Features
Completed HTF candle projection: prior higher-timeframe range and body projected onto the chart
HTF pattern engine: bullish and bearish engulfing and pin-bar style patterns
Confirmed RSI divergence: bullish and bearish divergence using pivot confirmation
Dual-pane logic: overlay objects explain price context while the pane acts as a reversal timing ledger
Confluence scoring: combines HTF pattern, local divergence, and distance-to-extreme logic
Premium/discount context: position of price relative to the HTF midpoint is plotted
Confluence zones: optional chart zones highlight stronger bullish or bearish reversal regions
State-based RSI coloring: RSI line color reflects the current net confluence
Top-right dashboard: summarizes pattern state, divergence state, confluence, and location context
Non-repainting design: no unfinished HTF candles and no unconfirmed pivot divergence
Input Parameters
Higher Timeframe Context
HTF Candle Source
Enable Engulfing Patterns
Enable Pin Bar Patterns
Project Completed HTF Candle
Projection Offset Bars
Projection Width Bars
Execution Divergence
RSI Length
Pivot Left
Pivot Right
Show Divergence Lines
Show Confluence Zones
Confluence Engine
Distance Lookback
Distance Weight
Pattern Weight
Divergence Weight
Display
Show RSI State Fill
Dashboard Position
Dashboard Size
How to Use This Indicator
Step 1: Start With the Higher-Timeframe Projection
Use the projected completed candle to understand whether the larger reference bar is signaling rejection, acceptance, or neutrality.
Step 2: Wait for Local Divergence Confirmation
The script intentionally waits for confirmed pivots.
That delay is a feature, not a flaw.
Step 3: Read the Net Confluence, Not Just RSI
The pane is not meant to be treated like a normal RSI oscillator.
Its color and context matter because they reflect the broader reversal evidence stack.
Step 4: Use Confluence Zones as Areas of Interest
Zones identify places where the higher-timeframe context and local divergence align.
They are not guaranteed turning points.
Step 5: Respect the Directional Imbalance
If the higher-timeframe candle context is strongly bearish, a minor bullish divergence alone may not be enough to justify a reversal thesis, and vice versa.
Indicator Limitations
Confirmed divergence necessarily appears after the pivot forms, which introduces intentional timing delay
Higher-timeframe pattern quality depends on the selected timeframe and instrument behavior
RSI divergence can persist without immediate reversal in strong directional markets
Projection objects are context tools, not price targets
Originality Statement
Harbor Reversal Ledger is designed as a confluence ledger rather than a single-pattern reversal marker.
Its distinguishing structure comes from pairing completed higher-timeframe candle analysis, confirmed divergence, distance scoring, projected context, and pane-based confluence visualization into one disciplined, non-repainting timing framework.
Disclaimer
This indicator is provided for educational and informational purposes only.
It is not financial advice and should not be used as a standalone reason to enter or exit a market.
All reversal readings are based on historical chart data and can fail, especially in strongly trending or event-driven conditions.
Use proper risk management and independent judgment.
Indicator
Crown Structure Ledger [JOAT]Crown Structure Ledger
Introduction
Crown Structure Ledger is an open-source market structure ledger built to classify price through three structural horizons at the same time: short-term, intermediate-term, and primary-term.
Instead of reducing structure to a single swing model, this script maintains separate rails for each horizon so users can see where local repricing, intermediate repricing, and larger campaign structure are currently positioned.
The indicator is designed to solve a common chart-reading problem:
Traders often know price is moving, but they do not know whether the move is merely a short-term impulse inside a larger range, an intermediate continuation, or a genuine primary expansion.
Crown Structure Ledger addresses that by combining:
confirmed pivot structure
active break state tracking
adaptive ATR corridors
EMA trend context
volume-pressure bias scoring
state-based candle coloring
forward structure projection
a top-right institutional dashboard
The output is intentionally visual but restrained.
Instead of cluttering the chart with excessive markers, the script emphasizes live structural rails, shaded corridors, confirmed state transitions, and a dashboard that summarizes the current condition of each structural layer.
Core Concepts
1. Three-Horizon Structure Mapping
The script confirms three separate pivot systems using different left/right lengths.
This creates a short-term layer for local impulse, an intermediate layer for swing control, and a primary layer for broader directional structure.
Each confirmed pivot updates its own active rail instead of overwriting the other layers.
2. Confirmed Break Logic
Break states are only recognized on confirmed bars.
This means the script does not react to intrabar spikes through a level.
A structural state changes only when price closes through a live rail beyond a small corridor allowance.
3. Adaptive Structure Corridors
Every rail is wrapped in an ATR-based corridor.
When adaptive depth is enabled, the corridor expands or contracts according to volatility conditions so the structure model stays usable across slow and fast environments.
4. Pressure-Weighted Bias
The indicator includes a directional pressure score based on up-volume versus down-volume across a configurable window.
That pressure score is combined with EMA orientation and structure state to create a bias color system rather than a binary trend flag.
5. Forward Projection
Current structural rails can be extended forward so the user can see where the next important structural interaction is likely to occur without manually drawing continuation levels.
Features
Three structure horizons: short, intermediate, and primary rails tracked independently
Adaptive structure corridors: live ATR-based zones around active rails
Confirmed structural transitions: break states only update on confirmed bars
Break labels: optional state labels appear when a new structural expansion or compression is confirmed
EMA trend filter: fast and slow EMA alignment supports the structure interpretation
Volume-pressure bias model: directional pressure is estimated from relative up-volume and down-volume
Bias cloud: optional background cloud reflects broader directional control
Candle coloring: bars can be colored from bearish to bullish using a gradient-like bias response
Forward corridor projection: active rails can extend to the right edge of the chart
Institutional dashboard: top-right summary of structure state, bias, pressure, and live rail context
Input Parameters
Structure Engine
Short Pivot Length
Intermediate Pivot Length
Primary Pivot Length
Structure Corridor ATR
Adaptive Corridor Depth
ATR Length
Bias Filter
Fast EMA
Slow EMA
Pressure Window
Color Candles
Show Structure Cloud
Show Structure Rails
Show Break Labels
Visual System
Show Short Term
Show Intermediate Term
Show Primary Term
Show Forward Corridor
Forward Corridor Bars
Dashboard Position
Dashboard Size
How to Use This Indicator
Step 1: Read the Three States Separately
Start by checking whether short-term, intermediate-term, and primary-term structure agree.
When all three align, the chart is in a cleaner directional condition.
When they diverge, the market is often transitioning or rotating.
Step 2: Watch the Active Rails
The live rails mark the current structural boundaries that still matter.
These are the levels price must reclaim or lose to produce a confirmed structural update.
Step 3: Use the Corridors, Not Just the Line
The corridor around a rail is intentional.
It helps avoid overreacting to shallow level breaches in noisy conditions.
Step 4: Read the Bias Cloud and Candle Tone Together
If candle color, pressure bias, and the structure cloud all point in the same direction, the chart context is stronger than a single rail break by itself.
Step 5: Use the Dashboard as a Summary, Not a Shortcut
The dashboard is there to reduce scanning time.
It is best used as a summary of what the rails are already showing visually.
Indicator Limitations
Pivot-based structure confirms after the configured right-side bars complete, so signals are intentionally delayed for non-repainting behavior
Very aggressive settings can make the short-term layer overly sensitive on low-quality markets
In prolonged compression, structure may appear stable while directional follow-through remains weak
The indicator explains current structure; it does not guarantee continuation after a break
Originality Statement
Crown Structure Ledger is built around a layered structure ledger rather than a single swing map.
Its distinguishing value comes from maintaining three live structure horizons with adaptive corridors, pressure-aware bias scoring, forward projection, and a dashboard that keeps the chart readable while still exposing the full state of the engine.
Disclaimer
This indicator is provided for educational and informational purposes only.
It is not financial advice and should not be treated as a recommendation to buy or sell any financial instrument.
All structural readings are derived from historical price and volume data and can fail in abnormal market conditions.
Always use independent judgment and risk management.
Indicator
Open Interest Suite [QuantAlgo]🟢 Overview
The Open Interest (OI) Suite is a comprehensive OI visualization and analysis tool built specifically for crypto perpetual futures traders. It reads open interest data directly from PulseWire-supported exchanges, giving you a way to monitor how many active contracts are currently open in the market. Whether you are tracking a single exchange or aggregating OI across venues like Binance, Bybit, Bitget, Coinbase, Kraken, HTX, BitMEX, and OKX, this indicator is one of the most powerful contextual tools available, allowing traders to quickly gauge overall perpetual futures market positioning.
🟢 What is Open Interest?
Open interest (OI) is the total number of live contracts between buyers and sellers at any given moment. Every long is matched to a short at a 1:1 ratio, so OI gives you a strong sense of how much capital and how many positions are currently committed to the market. Rising OI suggests new money and new positions are entering. Falling OI suggests positions are being closed or liquidated. When combined with price action, OI becomes one of the most valuable lenses available for understanding what is likely happening beneath the surface of price movement in perpetual markets.
🟢 How It Works
The indicator operates in two distinct modes. In Single (Chart) mode, it automatically reads open interest from whichever supported exchange and perpetual contract you are currently viewing, requiring no manual configuration. In Aggregated mode, it fetches OI from some of the highest-volume exchanges in crypto, for example, Binance, Bybit, Bitget, Coinbase, Kraken, HTX, BitMEX, and OKX, combines them into a single composite total, and gives you a cross-market view of positioning that no individual exchange feed can provide on its own. For each exchange in Aggregated mode, OI is fetched across both USDT and USDC perpetual pairs where applicable, then converted to a unified measure before summing. More exchanges will be added as their data becomes available on PulseWire.
The Measure setting controls how OI values are expressed. In Coins mode, values are kept in their native unit, which may be more useful when you want to observe raw contract volume independent of price fluctuations. In Dollars mode, coin quantities are multiplied by the current bar price to convert values into USD, which is the standard way most traders and data providers report OI and tends to make cross-asset comparisons more intuitive. For exchanges that report natively in USD, the conversion is handled in reverse when Coins mode is active.
🟢 Key Features
▶ View Modes
The indicator offers four ways to visualize OI, each suited to a different analytical purpose.
1. Candles: Renders OI as full OHLC candlesticks, displaying open, high, low, and close OI for every bar. This is the richest view for studying OI structure, trends, compression, and expansion over time. You can watch OI build or unwind bar by bar similarly to how you read price action, which may help with spotting periods of aggressive position-building or rapid deleverage.
2. Lines: Renders OI as a single continuous line using the close value of each bar. Cleaner and less visually demanding than candles, this mode works well for maintaining OI context alongside other indicators without crowding the chart.
3. Change: Displays the bar-over-bar absolute difference in OI as a histogram. Positive bars indicate net new positions were likely opened. Negative bars suggest net positions were closed or liquidated. This mode can help identify the bars where positioning shifted most dramatically, which often corresponds to high-conviction entries, forced liquidations, or possible trend exhaustion.
4. Change (%): The same histogram expressed as a percentage of the prior bar OI value. This normalises the signal across different asset sizes and OI magnitudes, which could make it easier to compare positioning dynamics between a large-cap asset and a smaller altcoin.
▶ Aggregated Mode and Exchange Selection
In Aggregated mode, each of the eight supported exchanges can be toggled on or off independently. This flexibility allows several useful configurations beyond a simple total. You can enable only one exchange to track that specific venue regardless of which chart you are currently viewing. You can also add the indicator to your layout multiple times with a different single exchange selected each time, letting you compare individual exchange OI side by side on the same chart.
▶ Color Presets
Five built-in color presets (Classic, Aqua, Cosmic, Cyber, Neon) allow you to match the indicator's appearance to your chart setup with a single click. A Custom preset exposes individual color pickers for bull, bear, and line colors, giving full control over every visual element including candle bodies, wicks, borders, histogram columns, and the line overlay.
▶ Unsupported Exchange Warning
When Single (Chart) mode is active and the current exchange does not provide open interest data on PulseWire, the indicator displays a warning label on the chart identifying the unsupported exchange and listing supported alternatives.
🟢 Price + OI Interpretation
Reading OI in isolation is only part of the picture. More meaningful analysis tends to come from combining OI direction with price action and, where available, volume data, along with other trend-following or mean-reversion indicators.
Examples:
1. Price Up + OI Up: New capital is likely entering on the long side. This could indicate bullish trend continuation, with fresh positioning supporting the move rather than just short covering. The stronger the OI growth relative to price movement, the higher the probability that the trend has genuine participation behind it.
2. Price Down + OI Up: New shorts are probably being added aggressively. Bearish momentum may be building through fresh positioning, which tends to be a more sustained signal than a move driven purely by long liquidations.
3. Price Down + OI Down: Longs are likely closing or being liquidated. The selling pressure in this scenario is coming from position unwinds rather than new short entries, which could sometimes suggest exhaustion near a local low rather than fresh trend initiation.
4. Price Up + OI Down: Shorts are probably closing or being squeezed out. This is the likely mechanics of a short squeeze: buyers overwhelm sellers, underwater shorts cover, and the resulting buy pressure may accelerate the move higher. This pattern tends to produce some of the fastest and sharpest price moves seen in crypto perpetual markets.
It is worth noting that for every short there is a long. When OI increases during a downtrend, it does not necessarily mean only shorts are entering. Longs are participating too, often more passively through limit orders. Cumulative Volume Delta (CVD) can help distinguish which side is more likely driving the flow, since it measures aggressive buying versus aggressive selling pressure within each bar.
🟢 Important Notes
1. This indicator is designed exclusively for crypto perpetual futures and will not produce output on spot tickers, equity symbols, or any instrument without a corresponding OI feed on PulseWire. In Single (Chart) mode, if the exchange you are viewing is not among the currently supported venues (Binance, Bybit, Bitget, Coinbase, Kraken, HTX, BitMEX, and OKX), the indicator will display a warning and produce no data. Switching to a supported exchange will restore functionality. More exchanges will be added as their data becomes available on PulseWire.
2. OI is most useful as a context layer rather than a standalone signal. Using it alongside price structure, volume, and order flow analysis may help you assess whether a move is likely backed by new positioning or driven by position unwinds. That distinction could have meaningful implications for how far a move extends and how quickly it might reverse. Indicator
Aureate Market Architecture Strategy [JOAT]Aureate Market Architecture Strategy
Introduction
Aureate Market Architecture Strategy is an open-source PulseWire strategy that integrates regime classification, structure bias, breakout pressure, liquidity confirmation, and risk management into one confirmed-bar execution model.
The strategy is built for users who want a rules-based implementation of the broader JOAT architecture rather than a single-indicator signal stream.
Its design goal is not to maximize trade count.
Its design goal is to trade only when multiple independent conditions agree:
the market is in an expansion-permitted regime
structure bias supports direction
pressure is strong enough to justify participation
liquidity context confirms the move
risk and daily drawdown constraints allow a new position
This produces a strategy that is intentionally selective and explicitly non-repainting.
Core Concepts
1. Regime Detection
The strategy classifies the market into accumulation, expansion, or exhaustion using ATR behavior, balance width, and normalized breakout pressure.
A persistence requirement prevents the regime state from flipping too quickly.
2. Structure Bias Filter
Directional participation is gated by confirmed medium-term structural breaks, EMA orientation, and price location relative to the fast EMA.
An optional higher-timeframe bias filter can be added using completed higher-timeframe candles only.
3. Pressure Confirmation
Breakout pressure is derived from a composite of multiple ROC windows and smoothed into an adaptive signal.
The strategy does not permit entries unless that signal exceeds its volatility-adjusted threshold.
4. Liquidity Context
The strategy estimates upper and lower liquidity anchors, counts relative touch density, and looks for sweep failure behavior to confirm whether the current move has supportive liquidity context.
5. Risk and Exit Stack
Every position uses an initial stop, a take-profit target based on risk multiple, an adaptive trailing component, a daily loss lockout, and a cooldown after exit.
Features
Three-state regime engine: accumulation, expansion, and exhaustion
Persistence logic: regime changes require confirmation across multiple bars
Structure bias filter: confirmed BOS logic combined with EMA alignment
Optional HTF bias filter: completed higher-timeframe candles only
Adaptive breakout pressure: multi-window ROC model normalized by its own volatility
Liquidity confirmation: anchor touches, sweep failures, and relative-volume support
Long and short entry logic: both directions use the same confirmed-bar architecture
Risk management: ATR-based initial stop, target, trailing logic, and daily loss control
Cooldown control: prevents immediate re-entry after an exit
Dashboard and chart overlays: display current state, active bias, and risk context
Default Strategy Properties
Initial Capital: 100000
Order Size: 10% of equity
Commission Model: Percent
Commission Value: 0.01
Pyramiding: 0
Calc On Order Fills: enabled
Calc On Every Tick: disabled
Input Parameters
Regime Engine
Regime ATR Length
Regime Baseline Length
Balance Window
Accumulation Volatility Threshold
Expansion Volatility Threshold
Regime Persistence Bars
Structure Bias
Short Pivot
Medium Pivot
Fast EMA
Slow EMA
Use Confirmed HTF Bias Filter
HTF Bias Timeframe
Breakout Pressure
Fast ROC
Medium ROC
Slow ROC
Macro ROC
Pressure Smoothing
Pressure Threshold Multiplier
Liquidity Context
Liquidity Window
Sweep Depth ATR
Relative Volume Floor
Risk Management
Initial Stop ATR
Take Profit R Multiple
Trail ATR Multiple
Daily Lockout %
Cooldown Bars After Exit
How to Use This Strategy
Step 1: Treat the Regime as the First Gate
The strategy only wants to be active in the expansion state.
If the dashboard shows accumulation or exhaustion, the system is designed to be more selective or inactive.
Step 2: Check Directional Alignment
The cleanest trades occur when structure bias, EMA alignment, pressure, and liquidity all support the same side.
Step 3: Respect the Risk Model
The stop, target, trail, and daily lockout are part of the strategy logic.
They should not be ignored when evaluating results.
Step 4: Expect Selectivity
This strategy is built to filter aggressively.
Users looking for frequent trades may need different settings or a different methodology.
Step 5: Evaluate Over Enough Trades
No strategy should be judged from a very small sample.
Assess it across enough market conditions to understand where the architecture performs well and where it degrades.
Strategy Limitations
This strategy uses chart-derived liquidity and regime approximations rather than exchange microstructure data
Selective filters can reduce trade frequency substantially on some instruments and timeframes
Backtest results depend on instrument, timeframe, commission, slippage assumptions, and session behavior
Non-repainting logic reduces false signals but can also introduce later entries than predictive systems
Originality Statement
Aureate Market Architecture Strategy is original in the way it integrates regime state, structural confirmation, normalized pressure, liquidity context, and layered risk controls into one coherent execution model.
The purpose of the integration is practical: each component addresses a different failure mode that appears when breakout systems rely on only one dimension of evidence.
Disclaimer
This strategy is provided for educational and informational purposes only.
It is not financial advice and does not guarantee profitability.
Backtest outcomes are hypothetical and derived from historical data.
Live trading includes slippage, execution variance, and market conditions that can differ materially from historical results.
Strategy
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
Vesper Divergence Cascade [JOAT]Vesper Divergence Cascade
Introduction
Vesper Divergence Cascade is an open-source divergence and response-structure overlay built around RSI pivots and a smoothed T3 ribbon. It detects regular and hidden bullish or bearish divergence, then maps the likely response area with projected zones, corridors, and target guides directly on the chart.
The problem this script solves is incomplete divergence analysis. Many divergence tools draw a line and stop there. That leaves the user without context about whether the move is aligned with local structure, whether the divergence developed in an overbought or oversold condition, and where price might respond if the divergence matters. Vesper Divergence Cascade adds that missing structure.
Core Concepts
1. Pivot-Based Divergence Detection
Confirmed price pivots are stored alongside the RSI value that existed at the pivot bar. This allows the script to compare current and prior pivot pairs without relying on unstable future references. Regular and hidden divergence types are evaluated independently on both highs and lows.
2. Ribbon Context Filter
The T3 ribbon acts as a directional and location filter. Divergence can optionally require price to be extended beyond the ribbon in the direction of the stretch before the event is accepted.
3. Response Zones And Corridors
When a divergence confirms, the script can project a response zone, midpoint line, reaction corridor, and target line forward from the pivot area. This turns divergence from a simple signal marker into a structured response map.
4. Signal Quality Context
The script uses RSI delta, ATR-normalized price displacement, cooldown logic, and optional overbought or oversold context to grade whether a divergence is meaningful enough to display.
Features
Regular bullish and bearish divergence: Reversal-oriented pivot disagreement
Hidden bullish and bearish divergence: Continuation-oriented pivot disagreement
T3 ribbon filter: Smoothed directional context layer
Reaction envelopes: Premium and discount response bands around ribbon center
Response zones: Forward areas projected from the active divergence
Reaction corridors: Larger projected path zones for follow-through context
Target lines: Simple objective guides derived from ATR structure
Signal labels: On-chart labels with response type and quality readout
Pivot dots and reset markers: Optional event markers for visibility
Dashboard: Displays RSI, zone state, ribbon state, cooldown, and active signal
Confirmed pivots only: Divergence prints only after pivot confirmation
Input Parameters
RSI Core And Divergence:
RSI source and length
Overbought and oversold levels
Pivot length and divergence window
Regular and hidden divergence toggles
Quality And Display:
Signal cooldown
Minimum RSI delta
Minimum ATR move
Extreme-condition requirement
Ribbon-filter requirement
Ribbon, pivot dots, dashboard, response zone, signal label, and reaction corridor toggles
How to Use This Indicator
Step 1: Identify whether the latest signal is regular or hidden, because they imply different response behavior.
Step 2: Check whether the signal formed in overbought or oversold context and whether the ribbon was supportive.
Step 3: Use the response zone and corridor as a framework for how price may react rather than as a guaranteed destination.
Step 4: Use reset markers to track whether momentum is rebalancing after the divergence.
Step 5: Prefer divergence that forms after visible extension, not in flat neutral conditions.
Indicator Limitations
Pivot confirmation introduces intentional delay because divergence is only known after the pivot is confirmed
Divergence can persist or fail completely during strong trends
Hidden divergence is continuation-oriented and should not be interpreted the same way as regular divergence
Projected zones and targets are analytical guides, not forecasts
Originality Statement
Vesper Divergence Cascade is original in how it combines pivot-stored RSI divergence, a T3 ribbon context filter, response envelopes, projected zones, and reaction corridors inside one divergence workflow. The script is designed to explain what kind of divergence formed, where it formed, and how price may structurally respond afterward.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Divergence is a contextual tool and can fail repeatedly during persistent trends, so all use should include independent analysis and risk management.
-Made with passion by jackofalltrades
Indicator
