Veyra Shift Ledger [JOAT]Veyra Shift Ledger
Introduction
Veyra Shift Ledger is an open-source execution-context ledger that combines trend, pressure, structure, auction location, displacement, and volatility state. It also draws qualified supply and demand zones anchored to confirmed swing memory.
The indicator is designed to show when several independent context layers align, while keeping signals confirmed and visually organized.
Core Concepts
1. Trend and Regime
Fast, mid, and slow EMAs define trend alignment. ADX, RSI, MACD, and VWAP context contribute to directional quality.
2. Pressure Engine
Signed candle body, range location, and volume are used to estimate bid or ask pressure.
3. Auction Location
Weighted price and deviation bands identify premium, discount, and value conditions.
4. Structure and Displacement
Confirmed pivots define swing memory. BOS, sweeps, and FVG-style gaps contribute to the structure side of the ledger.
5. Supply and Demand Zones
Zones are created only when quality gates pass. Demand zones anchor around confirmed pivot lows and supply zones anchor around confirmed pivot highs, with ATR-scaled height.
Features
Long and short ledger scores: Combines trend, momentum, pressure, structure, auction, and HTF context
Confirmed HTF filter: Optional higher-timeframe EMA uses confirmed previous HTF data
Supply/demand zones: Anchored to confirmed swing memory and ATR-scaled
Zone lifecycle: Zones change appearance when mitigated or invalidated
Execution rails: Optional educational entry, stop, and target projections
Dashboard: Shows scores, pressure, auction, structure, volatility, HTF, and trigger state
Input Parameters
EMA lengths control trend memory
Pressure and auction inputs control volume/weighted-price calculations
Pivot confirmation controls structure sensitivity
Score thresholds control signal selectivity
Risk inputs control optional rail projection
How to Use This Indicator
Step 1: Compare ledger scores
The dashboard shows whether long or short context has stronger evidence.
Step 2: Inspect zones
Supply and demand zones are contextual areas, not certain turning points.
Step 3: Watch mitigation state
Zone color changes help distinguish active, mitigated, and invalidated areas.
Indicator Limitations
Supply and demand zones are approximations from chart data
Pivot confirmation creates natural delay
Pressure is candle-derived and not true order book data
Execution rails are educational projections only
Originality Statement
Veyra Shift Ledger combines a multi-factor score ledger with swing-anchored supply/demand zones, auction context, pressure state, displacement logic, and zone lifecycle visualization.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Zones and scores can fail in live markets.
-Made with passion by jackofalltrades
Indicator
Probability Horizon - Bayesian SVJD Model# Probability Horizon — Bayesian SVJD Model
## What it does
Probability Horizon is a forward-looking probability projection tool. It does **not** generate buy or sell signals, does **not** act as a strategy, and does **not** place orders. Its single purpose is to display, at each bar, where price **may** be over a user-set horizon, drawn as a forward cone with three percentile lines (25%, 50%, 75%) plus an 8-row diagnostic dashboard.
The cone is the visual answer to two questions the indicator computes every bar:
1. **How wide should the distribution of forward outcomes be?** — set by expected total variance over the horizon.
2. **Should the distribution tilt up or down?** — set by a Bayesian-averaged probability of an up-move.
The wider the cone, the more uncertain the model is. The more the cone tilts, the more directionally confident the model is. A flat, narrow cone means "I expect range-bound, low-vol conditions." A wide, steeply tilted cone means "I expect a directional move under elevated variance."
## Why these components are combined (justification for the mashup)
This script combines several quantitative methods — KAMA, z-score, Haar wavelet, Kalman filter, Hamilton regime-switching, Hawkes process, Heston stochastic volatility, Merton jump-diffusion, Bayesian model averaging, and a calibration tracker. To a reviewer this can look like a collection of indicators bolted together, but it is not. It is **one** statistical model — a Stochastic Volatility Jump-Diffusion (SVJD) framework — whose pieces are mathematically required to produce a forward probability distribution.
Each component has a specific structural role:
- **Forward variance estimation.** A probability cone needs a forward-variance number. The naive choice is realized volatility × √horizon (pure Brownian motion), but this ignores two well-documented facts about financial returns: variance is mean-reverting (Heston, 1993) and returns have fat tails from discrete jumps (Merton, 1976). The Heston + jump-diffusion combination addresses both. The script uses the Heston integrated-variance closed form for the mean-reverting diffusion component, adds a Merton jump-variance contribution, and optionally adds a vol-of-vol uncertainty term. The result is a horizon-dependent variance estimate that dynamically narrows when volatility is elevated (expected to decay back to mean) and widens when volatility is depressed (expected to rise).
- **Directional probability.** To tilt the cone, a probability of direction is required. A single signal is unreliable, so five orthogonal sub-models each output their own P(up):
- A short-term KAMA-trend model
- A z-score mean-reversion model
- A Haar wavelet decomposition model (price denoised into trend + cycle + noise; signal fires only on the trend band)
- A Kalman-adaptive smoothing model (smoothing factor adapts to noise level in real time)
- A Hamilton 3-state regime model with Gaussian observation likelihoods (Bull / Bear / Range)
- **Sub-model combination.** The five P(up) values are combined via Bayesian model averaging with online weight updates. Each bar, after a fixed evaluation horizon, every sub-model is scored by log-loss against the actual outcome. Weights update via exponential decay: a model that predicted correctly gains weight; a model that failed loses weight. A minimum weight floor prevents any model from being silenced completely, so it can recover if its regime returns. Weights are renormalised to sum to 1.
- **Crisis dampening.** A Hawkes self-exciting point process monitors volatility clustering. Each large absolute return is treated as an event that boosts the process's intensity by α and decays exponentially at rate β. When intensity rises above a threshold multiple of its baseline, the final Bayesian probability is shrunk toward 0.5 — the higher the intensity, the stronger the shrinkage. This is how the model says "I have no idea — treat this as a coin flip" during regime breaks.
- **Self-correcting calibration.** A calibration tracker logs every prediction and checks the realized outcome after a fixed horizon. Predictions are binned by predicted probability (50–60%, 60–70%, etc.). If a bin's actual historical hit rate is below its predicted midpoint, future predictions in that bin are shrunk further toward 0.5. This is the model's honesty mechanism: it learns from its own miscalibration and tones itself down where it has been overconfident.
Each component answers a specific structural question. Remove any one and a specific capability disappears: no Heston → cone width does not adapt to vol regime; no calibration → no self-correction; no Hawkes → no crisis dampening; no Bayesian averaging → one model dominates and the system becomes brittle.
## How the components interact (data flow)
Every confirmed bar, the script executes the following pipeline:
1. **Measure** five raw market dimensions: KAMA slope, z-score vs trend, realized-vol percentile, OBV/price divergence, higher-TF trend.
2. **Each sub-model** maps its directional bias and strength to a probability in . The maximum single-model probability is capped at 0.60 because empirical calibration on multiple markets showed that anything higher is overconfident.
3. **Bayesian model averaging** combines the five sub-model probabilities into a single raw P(up), weighted by each sub-model's recent log-loss accuracy.
4. **Hawkes modifier** is applied: if intensity is above its warning threshold, the raw P(up) is pulled toward 0.5 in proportion to how far above threshold the intensity is.
5. **Calibration shrinkage** is applied: the post-Hawkes probability is checked against its calibration bin's historical hit rate, and shrunk further toward 0.5 if that bin has been overconfident.
6. **Forward variance** is computed separately: Heston integrated variance + Merton jump variance + optional vol-of-vol uncertainty, all over the projection horizon.
7. **The cone is drawn** with width set by the square root of forward variance and tilt set by the final shrunk probability. Three percentile lines (P25, P50, P75) are plotted from the current bar to the horizon endpoint.
Direction (sub-model probabilities → Bayesian average → Hawkes modifier → calibration shrinkage) is one half of the pipeline. Variance (Heston + jumps + vol-of-vol) is the other half. They meet at the cone, where one determines tilt and the other determines width.
## How to use it
**On the chart.** The cone shows the model's current view of the forward distribution. The P50 line is the median expected level given the implied drift. The P25 and P75 lines bracket the interquartile range. If P25 and P75 are roughly equidistant from current price, the model has no strong directional view; if the cone tilts noticeably up or down, the Bayesian probability favours that direction. A wider cone means more uncertainty; a narrower cone means tighter forward variance.
**The optional Monte Carlo cloud** (off by default) overlays bootstrap-resampled forward paths drawn from the asset's actual recent returns. Unlike the cone, it makes no Gaussian assumption — it shows the empirical distribution of forward outcomes given the asset's own recent return history.
**The 8-row dashboard** (top-right) is where the model exposes its full state:
- **Row 1 — Verdict.** Current direction (Bull / Bear / Neutral) and final P(up) percentage.
- **Row 2 — Direction.** A 10-character probability bar plus the size of the calibration shrinkage applied in percentage points.
- **Row 3 — 5 Models.** Up/down icons for each sub-model and the agreement count (e.g., "4/5 agree"). Trust the verdict more when 4 or 5 of 5 agree; trust it less when only 3 of 5 agree.
- **Row 4 — Regime.** Combined market regime (Quiet Bull / Quiet Bear / Volatile-Range / Crisis) plus the Hamilton dominant state.
- **Row 5 — Vol.** Volatility state vs long-run mean: HIGH (above mean, cone narrowing as vol decays), LOW (below mean, cone widening as vol rises), or AT MEAN. Includes the current sigma.
- **Row 6 — Risk.** Hawkes status: ✓ calm or ⚠ CRISIS. When CRISIS fires, the probability has been shrunk toward 0.5.
- **Row 7 — Honesty.** This is the most important diagnostic. It shows the actual historical hit rate for predictions in the 50–60% probability bin, with a Wilson confidence interval. If the system has predicted 55% many times and the actual rate is 53–58%, it is well-calibrated. If actual is below 50%, the system is currently overconfident and shrinkage is active.
- **Row 8 — Samples.** Total confirmed predictions and a trust level (low / warm-up / OK). Trust the cone less when total samples are below 50; trust it most when samples exceed 200.
## Suitable timeframes
The script auto-scales internal lookbacks to the chart timeframe relative to a 15-minute reference, so the same defaults work across 15-minute, 1-hour, 4-hour, and daily charts without manual tuning. Below 15 minutes the Hamilton 3-state model is automatically disabled because sample sizes become too small for reliable likelihood estimation; the other four sub-models continue to operate.
## What is original
Combining KAMA, wavelets, Kalman, Hamilton, Heston, Merton jumps, and a Hawkes process is not by itself new — these are all published methods. The original aspects of this script are:
- The **specific combination**: a five-model Bayesian ensemble for direction, with Hawkes-process crisis dampening and a self-correcting calibration tracker, all wrapped around a Heston + jump-diffusion variance estimate. I am not aware of a public Pine Script that combines all of these into a single probability cone with this data flow.
- The **calibration shrinkage mechanism**: the model logs every prediction, scores it after a fixed horizon, and applies bin-specific shrinkage to future predictions in bins where it has been overconfident. This is a self-correcting honesty layer that runs entirely on-chart, with Wilson confidence intervals and optional regime-specific calibration tables (Bull / Bear / Range).
- The **transparent diagnostic dashboard**: rather than hiding the model behind a single line, the dashboard exposes the verdict, model agreement, regime, vol state, crisis indicator, calibration quality, and sample size in eight rows. Users can see at a glance not only what the model thinks, but how much to trust it.
## Limitations (please read)
- **Pine Script cannot perform true maximum-likelihood estimation.** Heston and jump-diffusion parameters are estimated using approximation methods (AR(1) regression on log-variance, exponential moving averages for jump moments, rolling averages for long-term variance). The directional behaviour is correct — when vol is high, the cone narrows; when jumps are frequent, the cone widens — but exact parameter values are not equivalent to those a quantitative research desk would produce with MLE on tick data.
- **OHLCV data only.** No order-book data, no alternative-data feed, no options input, no fundamental input.
- **Calibration needs sample accumulation.** The Honesty row shows "warming up" until at least ~30 confirmed predictions have matured. Pine has no cross-session persistence, so calibration is rebuilt from chart history each time the indicator loads on a new chart.
- **Monte Carlo is deterministic.** Paths use a Linear Congruential Generator seeded by bar_index for reproducibility within a session. The same chart at the same moment produces the same cloud. This is intentional.
- **This is a probability indicator, not a strategy.** There are no backtest results, no equity curve, no position management. The script cannot tell you what to do; it only tells you what its model currently thinks the distribution of forward outcomes is.
- **Past calibration does not guarantee future calibration.** Market regimes change, parameters drift, and the cone should be treated as a visualisation aid rather than a prediction.
## Inputs of note
The defaults work without modification on most liquid instruments at most timeframes. Inputs worth knowing:
- **Auto-scale lookbacks** (on by default) — keeps the same defaults usable across timeframes.
- **Bayesian learning rate η** (default 0.15) — how fast sub-model weights adapt. Higher = faster but noisier.
- **Min Bayesian Probability** (default 0.62) — the threshold the dashboard uses to call a bar "Bull" or "Bear" rather than "Neutral".
- **Heston κ floor / ceiling** — bounds the mean-reversion-speed estimate. Defaults (0.02 to 0.30) handle most markets.
- **Hawkes warning threshold** (default 2.0× baseline) — when crisis dampening kicks in.
- **Monte Carlo Cloud** (off by default) — overlays bootstrap paths. Turn on if you want an empirical (non-Gaussian) view of forward outcomes alongside the cone.
## Disclaimer
This script is published for educational and analytical purposes only. It does not constitute financial advice, investment advice, a recommendation to buy or sell any financial instrument, or a solicitation of any transaction. The author is not a registered investment adviser and nothing in this script should be construed as personalised investment guidance.
Past performance does not guarantee future results. The probability projections shown by this indicator are model outputs, not forecasts of what will actually happen. Trading and investing involve substantial risk of loss and are not suitable for every investor. Users are solely responsible for their own trading decisions and for verifying that any approach is appropriate for their personal financial situation, risk tolerance, and applicable regulations.
The author and Market_Logic_India accept no liability for any losses, damages, or trading outcomes resulting from the use, misuse, or interpretation of this script. Use at your own risk.
Indicator
Parallax Regime Corridor [JOAT]Parallax Regime Corridor
Introduction
Parallax Regime Corridor is an open-source regime and corridor engine that blends trend efficiency, volatility state, structure change, and transition quality. It visualizes the active regime as a dynamic corridor and marks confirmed regime shifts or CHoCH-style structure changes.
Core Concepts
1. Adaptive Corridor
The corridor is built from an adaptive mean and ATR-based width. The band expands when volatility increases and contracts in quieter conditions.
2. Regime Candidate
Price location, trend slope, and directional evidence determine whether the candidate regime is bullish, bearish, or neutral.
3. Structure Change
Confirmed swing highs and lows are used to detect delayed bullish and bearish changes of character.
4. Transition Quality
The indicator scores whether volatility, trend, and structure agree before highlighting a shift.
5. Dashboard Context
The dashboard summarizes current regime, quality, volatility, structure, and recent shift state.
Features
Dynamic regime corridor: Adaptive mean and ATR width
Bullish, bearish, and neutral regimes: Clear state output
Confirmed CHoCH events: Uses pivot-confirmed structure references
Transition quality score: Combines regime and structure conditions
Candlestick coloring: Candles can reflect the active state
Top-right dashboard: Compact summary of state and quality
Input Parameters
Basis length controls the adaptive mean
ATR length and multiplier control corridor width
Pivot length controls structure sensitivity
Minimum score controls shift selectivity
How to Use This Indicator
Step 1: Read the corridor color
The corridor color identifies whether the script sees bullish, bearish, or neutral control.
Step 2: Watch shift events
Shift events show where the regime candidate changed on a confirmed bar.
Step 3: Treat CHoCH as delayed structure context
CHoCH events rely on pivot confirmation and should be interpreted as confirmed historical structure, not instant prediction.
Indicator Limitations
Pivot-based structure is delayed by the pivot length
Regime transitions can occur late during fast reversals
The corridor is a context layer, not a standalone trading system
Originality Statement
Parallax Regime Corridor combines adaptive corridor visualization, structure-change logic, volatility context, and transition scoring. It is designed to show how regime context evolves rather than simply plot a trendline.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Regime classifications can be wrong or late in unusual market conditions.
-Made with passion by jackofalltrades
Indicator
Caldera Meridian Strategy [JOAT]Caldera Meridian Strategy
Introduction
Caldera Meridian Strategy is an open-source Pine Script v6 strategy that combines trend regime, pressure, structure, auction location, and transition probability into a single rules-based execution model. The strategy is designed to be transparent: each decision component is calculated directly inside the script, and entries are processed on confirmed bars.
This strategy is not intended to prove future profitability. It is a research framework for studying how multiple market-context filters interact with ATR-based risk and staged exits.
Core Concepts
1. Regime Filter
The strategy uses fast, mid, and slow EMAs to classify bullish, bearish, or neutral trend conditions. A confirmed higher-timeframe EMA can also be used as a directional filter.
trendBull = fast > mid and mid > slow and close > mid
trendBear = fast < mid and mid < slow and close < mid
2. Transition Probability
A simple rolling transition model estimates whether the current regime has recently persisted. This is used as a filter rather than a prediction.
3. Pressure and Auction Location
The strategy estimates bid/ask pressure from candle body position, range, and volume. It also tracks VWAP-style weighted price and value deviation bands to avoid entries in poor auction locations.
4. Structure Confirmation
Confirmed pivots are used to detect delayed structure breaks, sweeps, and displacement events. Pivot confirmation is non-repainting but naturally delayed.
5. ATR-Based Risk Management
Entries use ATR or structure-based stops. Exits are staged across TP1, TP2, and TP3 using configurable R multiples.
Features
Rules-based long and short logic: Combines trend, pressure, structure, auction, and probability filters
Confirmed-bar execution: Entry and risk-off logic uses closed-bar conditions
ATR and structure stops: Stops use volatility and recent structure references
Three staged exits: TP1, TP2, and TP3 use configurable R multiples and quantity percentages
Realistic default costs: Commission is set to 0.05% and slippage to 1 tick in the strategy declaration
Dashboard: Shows position state, scores, regime, continuation, pressure, auction, and risk-off status
Default Strategy Properties
Initial capital: 100,000
Commission: 0.05 percent
Slippage: 1 tick
Pyramiding: 0
Orders processed on close
How to Use This Strategy
Step 1: Use a clean chart
For publication and testing, use a standard chart type and avoid adding unrelated scripts to the chart.
Step 2: Review the dashboard
The dashboard explains why the strategy is flat, long, short, or in a risk-off state.
Step 3: Evaluate across markets
Do not judge a strategy from a small sample. Test across multiple symbols, timeframes, and market regimes.
Strategy Limitations
Backtest results do not imply future results
Pivot-based structure is confirmed only after the pivot length has passed
Costs and slippage may differ from live trading conditions
The model can underperform in choppy markets where filters repeatedly conflict
The strategy is a research framework and not a complete trading plan
Originality Statement
Caldera Meridian Strategy integrates multiple independent modules rather than relying on a single crossover or oscillator. Its usefulness comes from studying how regime, structure, pressure, auction location, and transition persistence interact before a trade is allowed.
Disclaimer
This strategy is provided for educational and informational purposes only. It is not financial advice. Trading involves risk of loss. Backtests are historical simulations and do not predict future performance. Always use proper risk management.
-Made with passion by jackofalltrades
Strategy
Ichimoku Regime ClassifierIchimoku Regime Classifier is an open-source market regime filter that labels conditions as TREND UP, TREND DOWN, or VOLATILE.
This script is designed to solve a practical problem: many entries fail because traders apply the same setup in all environments.
Its purpose is to classify the current market context first, so strategy rules can be adapted to regime.
Methodology
The classifier uses Daily Ichimoku structure plus ADX trend-strength confirmation:
Bullish regime:
Price above the Kumo
ADX above threshold
Tenkan above Kijun
Chikou-style confirmation (current price vs past price)
Bearish regime:
Price below the Kumo
ADX above threshold
Tenkan below Kijun
Opposite Chikou-style confirmation
Volatile regime:
If neither bullish nor bearish set is fully confirmed
Why this combination
Ichimoku provides structural trend context, while ADX filters weak directional phases.
The combination aims to reduce false directional bias during choppy periods and keep regime logic explicit.
How to use
TREND UP: prioritize long-biased setups
TREND DOWN: prioritize short-biased setups
VOLATILE: reduce risk, be selective, or wait for structure
This indicator is intentionally minimal on-chart (single regime label) to keep output readable and unambiguous.
Limitations
Regime transitions can lag, especially after sharp reversals.
This tool is a context filter, not a standalone entry/exit system.
Open-source notice
Published as open source for transparency, review, and customization.
Educational content only. Not financial advice. Indicator
Helios Institutional Synthesis Strategy [JOAT]Helios Institutional Synthesis Strategy
Introduction
Helios Institutional Synthesis Strategy is an open-source Pine v6 strategy that integrates regime detection, trend bias, VWAP location, premium/discount context, liquidity sweeps, volatility gating, structured ATR stops, target levels, trailing exits, time exits, and visual trade-zone boxes.
The strategy is designed as a realistic testing framework, not a performance promise. It uses confirmed-bar triggers, process-on-close order handling, commission, slippage, risk sizing, and daily risk guard logic. The default settings were made active enough to generate more samples across timeframes while still keeping basic risk controls in place.
Core Concepts
1. Regime and Trend Bias
An adaptive baseline, EMA momentum, DMI/ADX, and volatility score determine whether the market is bullish, bearish, or ranging. Long setups require bullish context, and short setups require bearish context unless other confluence factors compensate.
2. VWAP and Premium/Discount Context
The strategy compares price to session VWAP and to a rolling premium/discount range. This helps distinguish continuation entries from recovery or rejection setups.
3. Liquidity and Retest Triggers
Confirmed sweeps, daily level reclaims/rejections, VWAP bounces, baseline crosses, and channel reclaim/rejection logic can contribute to entries. This creates more than one path into a trade while still requiring a confluence score.
4. Volatility and Risk Gates
The strategy filters by volatility score, ATR percent of price, daily equity guard, and minimum planned R. These controls are included to avoid unbounded entries in abnormal conditions.
5. Structured Exits
Stops use ATR and recent key levels. Targets use ATR multiples. A trailing stop can tighten the exit as price moves, and a max-hold rule can close trades that remain open too long.
Default Strategy Properties
Initial capital: 100000
Commission: 0.01 percent
Slippage: 1 tick
Pyramiding: 0
Orders processed on close: true
calc_on_every_tick: false
Default risk per trade: 1.0 percent
Default minimum confluence score: 4 out of 8
Default cooldown: 4 bars
Default ATR stop multiple: 1.8
Default ATR target multiple: 2.8
Default trailing ATR multiple: 1.35
Default daily equity guard: 3 percent
Features
8-point confluence model: Combines regime, VWAP, premium/discount, momentum, volatility, sweeps, squeeze release, and HTF bias
Confirmed-bar entries: Long and short triggers use barstate.isconfirmed
HTF confirmation: Uses request.security() with lookahead off and previous higher-timeframe values
Risk-based sizing: Calculates quantity from equity, stop distance, and risk percentage
ATR stop and target: Structured stop/target logic with optional trailing behavior
Daily guard: Blocks new trades after a configured intraday equity drawdown threshold
Max-hold exit: Closes positions that exceed the configured bar count
Trade-zone boxes: Shows reward/risk boxes on the chart
Right-side risk rails: Labels active entry, stop, target, and R:R
Dashboard: Shows regime, position, confluence, risk gate, setup, volatility, VWAP sigma, liquidity, HTF bias, PD state, session, day guard, hold bars, stops, and key levels
Input Parameters
Core Engine:
Adaptive Baseline Length
Efficiency Lookback
ATR Length
ADX / DMI Length
Institutional Anchor Length
Confirmation Timeframe
Filters:
Enable Longs and Enable Shorts
Restrict to Session
Min Confluence Score
Cooldown Bars
Volatility score bounds
Risk Controls:
Risk percent per trade
ATR stop, target, and trailing multiples
Minimum planned R multiple
Max ATR percent of price
Daily equity guard percent
Max hold bars
How to Use This Strategy
Step 1: Start with a private draft
Before publishing results, test the strategy privately and verify the chart, settings, and description.
Step 2: Use realistic costs
The script defaults to 0.01 percent commission and 1 tick slippage. Adjust them to match the market being tested.
Step 3: Check sample size
Use enough historical data to evaluate whether the strategy has a meaningful number of trades. Avoid drawing conclusions from a small sample.
Step 4: Review the dashboard
The dashboard shows whether a blocked trade is caused by risk, volatility, session, confluence, or daily guard logic.
Strategy Limitations
Backtests are hypothetical and do not ensure future results
Performance can vary significantly by symbol, session, timeframe, and cost settings
The strategy may trade frequently on lower timeframes; costs and slippage matter
HTF confirmation uses non-lookahead requests, but higher-timeframe context can still evolve while a higher-timeframe bar is unfinished
Risk controls reduce some bad conditions but cannot remove market risk
Originality Statement
Helios Institutional Synthesis Strategy combines adaptive regime detection, VWAP sigma location, premium/discount context, liquidity sweep triggers, squeeze state, higher-timeframe confirmation, risk-based sizing, ATR exits, daily guard logic, time exits, and visual trade-zone mapping in one open-source Pine v6 strategy. Its purpose is to test a multi-factor decision process with transparent components rather than present a black-box signal system.
Disclaimer
This strategy is for educational and informational use only. It is not financial advice, and backtested results do not ensure future performance. Trading involves substantial risk of loss. Always test with realistic commissions, slippage, and position sizing before making any decision.
-Made with passion by jackofalltrades
Strategy
Volume Participation Curve [JOAT]Volume Participation Curve
Introduction
VPC Volume Participation Curve is an open-source volume seasonality indicator that compares current volume against historical participation for the same time bucket. It helps answer a simple but important question: is current activity meaningful compared with what usually happens at this time?
Instead of treating all volume bars equally, VPC builds recurring buckets by minute, hour, day, or month, then compares live volume against the expected bucket value. It also tracks session pace so traders can see whether the session is leading or lagging expected participation.
Core Concepts
1. Time-Bucketed Expected Volume
The indicator builds historical volume samples by time bucket. Auto mode chooses practical buckets based on the chart timeframe.
2. Median or Mean Summary
Expected volume can be calculated by median or mean. Median is the default because it is more robust against abnormal spikes.
3. Participation Ratio
The main curve is current smoothed volume divided by expected volume. A value above 1.0 means current activity is above expectation.
4. Session Pace
Session cumulative volume is compared with cumulative expected volume to determine whether the whole session is leading or lagging.
5. Regime Bands
Expansion and compression thresholds are shown as clean bands around the 1.0 baseline.
Features
Expected volume engine: Learns recurring volume behavior from historical buckets
Participation curve: Displays current volume relative to expected activity
Session pace curve: Shows whether cumulative session activity is ahead or behind
Expansion and compression bands: Identifies above-expected or below-expected participation
Dark-mode fills: Uses restrained green/red/neutral blends
Top-right dashboard: Shows bucket, participation, pace, surprise, growth, state, and sample count
Confirmed alerts: Includes expansion, compression, pace lead, and pace lag alerts
Input Parameters
Seasonality:
Historical Samples per Bucket
Bucket Mode: Auto, Minute, Hour, Day, or Month
Expected Value: Median or Mean
Curve:
Volume Smoothing
Session Pace Window
Visual:
Show Regime Bands
Show Pace Curve
Color Background
How to Use
Step 1: Read the participation curve relative to the 1.0 baseline.
Step 2: Treat readings above 1.2 as expansion context and readings below 0.8 as compression context.
Step 3: Confirm whether session pace agrees with the current bar's participation.
Step 4: Use the output as a participation filter for breakout, continuation, or reversal tools.
Limitations
New symbols or sparse histories may need time to build useful bucket samples
Unusual news or event-driven sessions can distort expected-volume comparisons
Volume reporting differs by asset class and exchange
This indicator does not predict direction; it measures participation context
Originality Statement
VPC is an original JOAT volume model combining time-bucketed expected volume, session pace, expansion/compression bands, and confirmed alerts in a Pine Script v6 pane indicator.
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
Trend Energy Divergence [JOAT]Trend Energy Divergence
Introduction
TED Trend Energy Divergence is an open-source oscillator that measures trend energy from EMA spread, linear-regression slope, projected support/resistance pressure, confirmed structure, and pivot divergence.
The indicator is built for trend-quality context. It shows whether the current move has internal energy, whether structure agrees with that energy, and whether confirmed divergence is appearing against it.
Core Concepts
1. Normalized EMA Spread
Fast and slow EMA spread is normalized by ATR so the oscillator adapts across symbols and timeframes.
2. Slope Pressure
Linear-regression slope contributes directional pressure to the energy model.
3. Projected Support and Resistance
Confirmed pivots build simple projected support and resistance references. Closing beyond those projections adds break pressure.
4. Confirmed Divergence
Pivot highs and lows are compared with oscillator values at the pivot offset to identify bullish or bearish divergence.
5. Energy Signal Line
Trend energy is smoothed and compared with a signal line to show positive or negative shifts.
Features
ATR-normalized energy: Adapts the oscillator to volatility
EMA and slope model: Blends trend spread and regression pressure
Structure-aware pressure: Adds support/resistance break pressure
Confirmed divergence: Uses confirmed pivots and offset oscillator values
Regime dashboard: Shows trend, expansion, or balance context
Projected levels: Displays pane-level support and resistance projections
Alerts: Includes bull shift, bear shift, and divergence confirmations
Input Parameters
Trend Engine:
Fast EMA
Slow EMA
Signal Smoothing
Energy Smoothing
ATR Length
Slope Length
Structure:
Pivot Left and Pivot Right
Structure Lookback
ADX/DMI Trend Threshold
How to Use
Step 1: Read the oscillator relative to the zero line and signal line.
Step 2: Treat upper/lower confirmation bands as higher-conviction energy zones.
Step 3: Watch divergence states as early warnings that the current move may be losing quality.
Step 4: Use the dashboard to confirm whether the environment is Trend, Expansion, or Balance.
Limitations
Divergence confirms after pivots confirm, so it is intentionally delayed
Oscillators can remain extended during strong trends
Projected support/resistance is model-based, not a guaranteed reaction point
The indicator is not a complete trade management system
Originality Statement
TED is an original JOAT oscillator combining ATR-normalized trend spread, slope, projected structure pressure, and confirmed divergence into one Pine Script v6 energy model.
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
Volatility Trail [EXCAVO]ATR Percentile Rank Painted as a Semi-Transparent Wave Beneath Every Candle
The Volatility Trail takes the four-state volatility regime classification
from the standard ATR-percentile model and renders it directly on the price
chart as a semi-transparent wave hanging under each candle. The wave reads at
a glance: blue under the candles means quiet markets, orange means heating up,
red means volatility extremes. No separate indicator pane is required.
This is not a basic ATR oscillator. The ATR is normalised against its own
historical distribution, smoothed, and classified into four bounded regimes
(Low / Normal / Elevated / Extreme) with adjustable thresholds. The on-chart
trail is the same engine as the standard Volatility Percentile indicator,
just drawn where you actually read price.
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▸ HOW TO USE
Step 1 → Add the indicator. A coloured wave appears beneath every
candle as soon as enough history is available for the percentile
lookback to be meaningful (default 200 bars).
Step 2 → Read the wave colour:
- Blue = Low volatility (compression, mean-reversion regime)
- Grey = Normal volatility
- Orange = Elevated volatility (trend regime)
- Red = Extreme volatility (top decile, exhaustion risk)
Step 3 → Watch transitions. A switch from blue to orange flags a
breakout out of compression. A switch from red back to orange
flags a release from extreme volatility - often the right side
of a spike. The floating state badge to the right of the last
candle shows the current regime name at a glance.
Step 4 → Check the dashboard. State, raw percentile, ATR, ATR / Price,
and Vol Trend show the current regime numerically. Use these to
size positions and pick filters that depend on volatility.
Step 5 → Combine with structure. The trail is a context tool, not a
directional one - it tells you HOW volatile the market is, not
WHICH way it will move. Pair it with your own setup criteria.
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▸ HOW IT CALCULATES
◆ ATR Percentile Rank
The base measure is Average True Range over the user-set length (default 14).
For every bar the current ATR is ranked against its own values over the
Lookback Period (default 200): percentile = 100 x rank / N. A value of 90
means current volatility is higher than 90 percent of bars in the lookback
window. This normalisation makes the reading comparable across instruments
and timeframes - 90th-percentile vol on BTC and on EURUSD are both rare even
though their absolute ATRs differ by orders of magnitude.
◆ Smoothing
The raw percentile is smoothed with a short SMA (default 3) to reduce single-
bar noise. Smoothing = 1 disables this step.
◆ Four-State Classification
The smoothed percentile is bucketed into four regimes:
- Low = below Low / Normal boundary (default 25)
- Normal = between Low / Normal and Normal / Elevated (default 25 to 60)
- Elevated = between Normal / Elevated and Elevated / Extreme (default 60 to 80)
- Extreme = at or above Elevated / Extreme (default 80)
All three boundaries are user-adjustable.
◆ Candle-Anchored Downward Wave
A semi-transparent band hangs directly under each candle. The upper edge
is the bar's low, lightly EMA-smoothed so single-bar wick spikes do not
poke through the ribbon. The lower edge drops below by an ATR-scaled
distance: drop = ATR x (1 + percentile x Wave Distance Scale). At calm
regimes the wave is a thin sliver under price; at volatile extremes it
extends well below. The colour is the active state colour, and the
opacity within each state band is gradient (see next item).
◆ Within-Band Opacity Gradient
The wave colour is the state colour (blue / grey / orange / red), but the
opacity is not flat across each state - it ramps from Min Opacity at the
LOWER edge of the band (regime just entered) to Max Opacity at the UPPER
edge (peak of the regime, about to graduate to the next state). So a fresh
red band that just crossed into Extreme is light red, while a red band at
percentile 95 is a deep saturated red. The same gradient applies inside
the Low / Normal / Elevated bands. This lets you read at a glance whether
the current regime is just beginning, peaking, or about to fade into the
next state - approach and exhaustion are separately readable inside every
band.
◆ Vol Trend
ATR is compared to its 20-bar SMA. Above 1.05x SMA = RISING, below 0.95x =
FALLING, else STABLE. Shown on the dashboard as a quick second-derivative
read of the regime.
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▸ WHAT MAKES IT DIFFERENT
◆ Wave Lives On The Price Chart
Most volatility indicators occupy a separate pane and force the eye to jump
between price action and the oscillator. The wave overlays the same regime
information directly on the candles, so price and volatility are read
together in one view.
◆ Adaptive Across Instruments
Percentile-rank normalisation removes the absolute ATR units. A BTC chart
and a EURUSD chart use the same scale (0 to 100), so the same thresholds
work everywhere without manual tuning.
◆ Four Bounded Regimes Instead Of A Raw Line
A raw ATR plot tells you very little until you have a feel for what is
"normal" on that instrument. The four-state classification answers the
question directly - quiet, normal, elevated, or extreme - using
user-adjustable boundaries.
◆ Within-Band Opacity Gradient
Inside each state band the wave opacity ramps from light (just-entered
regime) to saturated (regime at its peak). A fresh red band reads as
pale red; a deep mature Extreme reads as a saturated red. Approach and
exhaustion are separately readable inside every regime, not just on
state transitions.
◆ Premium Visual Polish
A thin rim-light line follows the upper edge of the wave for definition,
and a contrast-aware state badge floats next to the last candle showing
the current regime name. The badge text colour is picked automatically
by the perceived luminance of the background so the label stays readable
on any state colour.
◆ Optional Bar Coloring And Background
For users who want the regime even more visible, bar-coloring and
background-highlight toggles tint the candles or the chart background with
the active state colour. Both default off so the wave stays as the primary
visual.
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▸ DASHBOARD
Real-time panel (top right) with the current regime readout:
State - LOW / NORMAL / ELEVATED / EXTREME
Percentile - the smoothed ATR percentile (0 to 100)
ATR - raw Average True Range
ATR / Price - ATR as a percentage of close (instrument-independent)
Vol Trend - RISING / STABLE / FALLING based on ATR vs its 20-bar SMA
Lookback - the bar count used for the percentile rank
Legend table (bottom left) explains every colour. Both panels toggle in the
Dashboard settings.
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▸ SETTINGS
Engine
ATR Length - 14 (period for the Average True Range)
Lookback Period - 200 (historical bars used for the percentile rank)
Smoothing - 3 (SMA length applied to the raw percentile; 1 disables it)
State Thresholds
Low / Normal - 25 (boundary between Low and Normal regimes)
Normal / Elevated - 60 (boundary between Normal and Elevated)
Elevated / Extreme - 80 (boundary between Elevated and Extreme)
Visualization
Low Vol Color - blue
Extreme Vol Color - red
Elevated Vol Color - orange
Wave Top Smoothing - 3 (EMA length applied to the wave top; 1 = raw bar low with sharp peaks, 3 to 5 rounds off single-bar spikes while staying tight to price)
Wave Distance Scale - 0.025 (controls how far the wave drops below each candle as volatility rises; drop = ATR x (1 + percentile x scale); default keeps drops modest - approximately 1 ATR at Low regime, 3.5 ATR at Extreme)
Min Opacity - 25 (wave opacity at the LOWER edge of every state band - just-entered regime; very transparent)
Max Opacity - 55 (wave opacity at the UPPER edge of every state band - peak of the regime; visible but kept semi-transparent so the candles stay readable)
Wave Top Highlight - ON (thin rim-light line along the upper edge of the wave; adds definition and a premium glow)
Right-edge State Label - ON (floating badge next to the last candle showing the current state name in the state color)
Bar Coloring - OFF (when ON, also tints the candles with the state color)
Background Highlight - OFF (when ON, tints the chart background)
Dashboard
Show Dashboard - ON
Dashboard Position - Top Right
Show Legend - ON
Alerts
JSON Alerts - OFF (when ON, emits a structured JSON payload via alert())
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▸ ALERTS
Extreme Volatility - state just transitioned into Extreme
Elevated Volatility - state just transitioned into Elevated
Normal Volatility - state just transitioned into Normal
Low Volatility - state just transitioned into Low
With JSON Alerts ON, the alert() call emits a structured payload with
ticker, state, percentile, atr_pct, price, timeframe, and indicator fields -
use "Any alert() function call" as the PulseWire alert event to receive
every state change as JSON on one alert.
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Best regards,
EXCAVO
Disclaimer
Trading involves significant risk. This indicator is a technical analysis tool
and does not constitute financial advice, investment recommendations, or a
guarantee of future results. Past indicator behavior does not guarantee future
performance. Always use proper risk management and your own judgment.
Indicator
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
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
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
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
Obsidian Regime Ribbon [JOAT]Obsidian Regime Ribbon
Introduction
Obsidian Regime Ribbon is an open-source trend-state and execution-context overlay built to classify directional conditions before a trader applies any separate entry model. Instead of using a single moving average or one oscillator threshold, it combines an adaptive range filter, efficiency ratio, ADX strength, choppiness, momentum confirmation, higher-timeframe bias, and EMA alignment into one chart layer.
The problem this script solves is regime confusion. Traders often apply trend-continuation logic in compression or try fading price while directional participation is still strong. Obsidian Regime Ribbon provides a structured state model with a filtered regime line, layered expansion bands, reclaim signals, stretch tags, execution rails, and a compact dashboard so the user can read whether price is trending cleanly, overextending, or losing sponsorship.
Core Concepts
1. Adaptive Range Filter
The central filter line is not a static moving average. It uses ATR distance and an efficiency-ratio-driven multiplier so the filter widens during noisy conditions and tightens when price movement becomes more directional.
2. Multi-Factor Regime Gate
ADX checks directional strength, choppiness checks compression, momentum confirms directional pressure, higher-timeframe EMA bias provides external context, and EMA spread measures local alignment. These conditions feed a scorecard so the user can separate weak drift from stronger directional structure.
3. Expansion And Reclaim Framework
Four ATR-derived bands are projected above and below the regime filter. Confirmed regime shifts create labeled accumulation or distribution windows. Pullback reclaim signals print only after price revisits the regime line and closes back through it on a confirmed bar.
4. Execution Rails
Confirmed shifts and reclaim events create forward execution rails and zones directly on the chart. In bullish conditions they behave as demand rails, and in bearish conditions they behave as supply rails.
Features
Adaptive regime filter: ATR-based directional filter with efficiency-ratio adaptation
Layered regime bands: Four expansion bands above and below the filter
EMA structure cloud: Fast and slow structure means with directional fill
Confirmed regime shift labels: Bullish and bearish shifts print only after confirmation
Reclaim signals: Diamond markers when price reclaims the regime line
Execution rails: Demand and supply rails with right-edge price labels
Stretch tags: Labels when price reaches extreme premium or discount relative to the filter
Expansion markers: Additional markers when price pushes through secondary band thresholds
State-based candle coloring: Candle tint changes with regime and score strength
Dashboard: State, conviction, age, ER, ADX, chop, stretch, HTF alignment, and shift counts
Confirmed-bar logic: Regime changes and reclaim signals are designed for confirmed bars only
Input Parameters
Engine:
Range Length and Range Multiplier control the core filter sensitivity
Efficiency Length controls how quickly adaptation reacts to directional efficiency
Base Confirm Bars controls how many bars are required before a regime shift is locked
Stretch Threshold defines when a move is considered overextended in ATR terms
Filters And Display:
ADX, choppiness, momentum, and higher-timeframe controls define the regime gate
Regime band, filter line, candle color, dashboard, execution zone, and stretch tag toggles
How to Use This Indicator
Step 1: Read the current regime from the dashboard and candle state first.
Step 2: Use the conviction score to decide whether the trend is fully structured or transitional.
Step 3: Watch regime shift labels to identify when directional control changes.
Step 4: Use reclaim diamonds and execution rails as retracement reference instead of chasing outer-band extensions.
Step 5: Treat stretch tags as caution zones where reward-to-risk may deteriorate.
Indicator Limitations
Adaptive filters can still lag the first bar of a sharp reversal because confirmation is intentionally delayed
Higher-timeframe alignment can temporarily disagree with local price rotation during early reversals
Stretch conditions do not guarantee reversal; they only identify extended distance from the filter
This script is a context overlay, not a complete trading system by itself
Originality Statement
Obsidian Regime Ribbon is original in the way it combines an adaptive range-state engine, multi-factor regime gate, expansion-band framework, reclaim signals, and forward execution rails into one integrated context overlay. The purpose is not to merge unrelated tools, but to build a single decision layer that explains trend state, extension, and pullback quality together.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Regime, reclaim, and stretch conditions are derived from historical price behavior and do not guarantee future outcomes. Always use independent analysis and risk management.
-Made with passion by jackofalltrades
Indicator
Concord Execution Mandate [JOAT]Concord Execution Mandate
Introduction
Concord Execution Mandate is an open-source strategy that combines regime classification, higher-timeframe bias, structure breaks, daily pivot context, reversion-basis reclaim logic, and divergence safety into one execution framework. It is designed to test whether directional entries improve when multiple context layers are aligned rather than relying on a single trigger.
The problem this strategy solves is unstructured execution. Many strategies either enter too often without context or wait for perfect alignment so long that they never engage. Concord Execution Mandate uses a softer confluence model that can still trade frequently while preserving directional context, confirmed-bar logic, realistic costs, and explicit risk controls.
Core Concepts
1. Regime And Context Layer
The strategy starts with an adaptive range-state engine supported by ADX, choppiness, and higher-timeframe EMA bias. These inputs do not all act as hard blockers; instead, they contribute to whether the environment is favorable enough for execution.
2. Structural And Rotation Triggers
Entries can come from confirmed bullish or bearish BOS behavior, continuation crosses back through the regime filter, or more aggressive rotation entries through the daily pivot, reversion basis, or short EMA.
3. Soft Alignment Model
Daily pivot bias, EMA weave bias, geometry bias, and regime location are combined into a directional alignment score. The strategy requires enough agreement to avoid fully random entries, but it does not require every filter to align perfectly before acting.
4. Risk Management
Stops are based on the closer of pivot structure or ATR distance. Targets are expressed as a reward multiple of live risk, and a trailing stop can activate only after price reaches a configurable multiple of initial risk. Context-flip exits can close trades early when directional state changes materially.
Features
Adaptive regime filter: Core state engine for directional context
Higher-timeframe bias: Optional EMA-based external direction filter
Structure triggers: Confirmed BOS logic using stored pivots
Continuation and rotation entries: Additional execution paths beyond BOS
Daily pivot and EMA weave context: Location-versus-bias inputs for alignment scoring
Reversion reclaim logic: Optional re-entry through a mean basis before entry
Divergence safety filter: Optional block on fresh opposing divergence
ATR and structure-based stops: Dynamic risk anchoring
Reward targets and ATR trailing: Structured exit management
Context-flip exits: Early closure when regime or bias reverses
Realistic defaults: Percent-of-equity sizing, commission, and slippage are defined in the strategy properties
Default Strategy Properties
Initial capital: 100000
Default order size: 5 percent of equity
Commission: 0.02 percent
Slippage: 2 ticks
Order processing: on bar close
Pyramiding: 0
How to Use This Strategy
Step 1: Read the dashboard to confirm the current regime, structural state, and whether the entry stack is armed.
Step 2: Use the strategy on instruments and timeframes where directional movement and retracement behavior are both visible enough to generate a meaningful sample.
Step 3: Review whether aggressive rotation entries or stricter reclaim filters better match the market being tested.
Step 4: Keep the published chart clean and use the same Properties values shown in the strategy description when presenting results.
Step 5: Evaluate the strategy using a broad sample of trades rather than isolated trades or one short backtest segment.
Strategy Limitations
This strategy still relies on lagging structure confirmation and can miss the first portion of fast reversals
More aggressive settings can increase trade count at the cost of lower selectivity
Higher-timeframe bias can conflict with local execution context during turning points
Backtest results depend on symbol, timeframe, session behavior, and execution assumptions
This strategy is designed to be realistic, not optimized for one narrow market condition
Originality Statement
Concord Execution Mandate is original in how it integrates adaptive regime logic, structural breaks, rotation entries, soft alignment scoring, reclaim filtering, divergence safety, and layered exit management into one execution framework. The combination is intentional because the strategy is designed to test whether context-aware execution can remain active without devolving into random signal generation.
Disclaimer
This strategy is provided for educational and informational purposes only. It is not financial advice and does not guarantee future performance. Backtests are based on historical data, configured assumptions, and simulated order handling. Always validate behavior independently and use appropriate risk management.
-Made with passion by jackofalltrades
Strategy
Torsion Range [JOAT]Torsion Range
Introduction
Torsion Range is an open-source compression, expansion, and wave-energy panel designed to track whether the market is coiling, releasing, trending, or exhausting. The script combines wave direction, weighted energy accumulation, compression scoring, and exhaustion logic into one regime-aware panel.
The problem Torsion Range solves is fragmentation between wave tools and volatility tools. Traditional wave studies often ignore whether the market is compressing or expanding, while compression indicators often ignore directional wave state. Torsion Range merges both worlds so the user can monitor directional energy and structural volatility state together.
Core Concepts
1. Wave Direction Engine
The script supports multiple methods for determining directional wave state, including impulse, pressure, and hybrid behavior. This allows the model to adapt to different styles of price movement.
2. Weighted Energy Accumulation
Wave state is not just directional. It is weighted by body, range, ATR context, and optional relative volume to produce a more informative torsion core.
3. Compression Index
A 0-100 compression framework is built from fast and slow comparisons of range, body, and energy behavior. This allows the indicator to identify tight conditions before release.
4. Release and Exhaustion Logic
Confirmed-bar release events occur when compression gives way to directional expansion. Exhaustion logic looks for overstretched waves with weakening internal behavior.
5. Dashboard and Regime Visualization
The panel includes adaptive colors, background overlays, event flashes, and a top-right dashboard that summarizes wave state, bias, compression, and most recent event.
Features
Multi-method wave direction: Impulse, pressure, or hybrid state engine
Weighted energy accumulation: Uses price and optional relative volume
Compression scoring: Tracks coiling conditions on a normalized scale
Confirmed release logic: Detects transition from compression to directional expansion
Exhaustion detection: Flags overextended wave conditions
Adaptive gradient styling: Institutional panel presentation for dark charts
Regime overlays and event flashes: Highlights important state transitions cleanly
Top-right dashboard: Summarizes live wave and compression state
Confirmed event mode: Optional bar-close only event gating
Alertconditions: Wave flips, release events, and exhaustion states
How to Use This Indicator
Step 1: Read the Wave State
Determine whether directional energy currently favors bullish, bearish, or neutral behavior.
Step 2: Check Compression
High compression means stored energy but not yet confirmed release. Low compression with directional energy implies active movement rather than coiling.
Step 3: Watch Release Events
Release events matter most when they occur after genuine compression and align with the active wave bias.
Step 4: Respect Exhaustion
Exhaustion conditions can warn that a strong wave is becoming less efficient, even if trend has not yet fully reversed.
Indicator Limitations
Compression and exhaustion are relative, not absolute, conditions
Wave direction depends on the selected method and will respond differently across market types
This panel does not identify exact reversal bars and should not be treated as one
Release events are strongest when combined with separate structural context
Originality Statement
Torsion Range is original in its fusion of wave-state persistence, weighted energy accumulation, compression analysis, and exhaustion logic within one panel. It is not a basic Weis-style clone and not a plain volatility gauge. Its value comes from combining directional energy and volatility state into a single workflow.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Compression, release, and exhaustion states are analytical conditions derived from historical chart behavior and do not guarantee future outcomes.
- Made with passion by jackofalltrades
Indicator
Parallax Covenant Strategy [JOAT]Parallax Covenant Strategy
Introduction
Parallax Covenant Strategy is an open-source, non-repainting PulseWire strategy that integrates multiple analytical engines into one realistic execution framework. It combines regime detection, pressure confirmation, mapped bias, structure context, wave release logic, and ATR-based risk management to produce entries and exits only when several independent conditions agree.
The problem this strategy solves is weak single-factor trading. A crossover alone is rarely enough. A structure break alone is often early. A momentum spike alone can be noisy. Parallax Covenant requires alignment between regime, internal pressure, mapped bias, structural context, and release behavior before taking a trade. This creates a more selective, context-aware model than a one-indicator strategy.
Core Concepts
1. Composite Regime Engine
The strategy builds a directional regime from a structural baseline, tolerance corridors, and expansion/compression state. This acts as the primary directional context.
2. Pressure Confirmation
An internal pressure model blends weighted candle force and channel position to avoid taking trades simply because price is above or below a baseline.
3. Mapping and Higher-Timeframe Bias
The strategy uses a mapped momentum framework and an optional confirmed higher-timeframe bias filter so lower-timeframe entries can align with broader conditions.
4. Structure and Release Filters
Demand and supply context, swing structure, and release-from-compression logic help prevent entries from firing in the middle of low-quality noise.
5. Realistic Risk Management
The strategy uses ATR-based stops, reward-to-risk targets, optional trailing logic after a minimum multiple of risk, and regime-failure exits. This makes the model more realistic than fixed-tick toy strategies.
Features
Multi-engine entry stack: Regime, pressure, mapping, structure, and release alignment
Confirmed-bar logic: Entry conditions are evaluated on confirmed bars
Optional higher-timeframe bias filter: Uses confirmed higher-timeframe values
Demand and supply context: Trade logic includes structural location awareness
ATR stop and target model: Risk adjusts to symbol volatility
Trailing stop activation: Trail can engage after a defined reward threshold
Regime-failure exit: Closes trades when core directional conditions break down
Maximum time-in-trade control: Avoids stale positions
Institutional dashboard: Top-right strategy state summary
Alertconditions: Regime shifts, releases, and setup confirmations
How to Use This Strategy
Step 1: Study the Dashboard
The dashboard shows whether the system currently sees bullish, bearish, or balanced conditions and how the internal engines align.
Step 2: Understand the Entry Stack
Trades only trigger when multiple conditions confirm together. If you see a setup fail to trigger, that is often intentional filtering rather than a bug.
Step 3: Respect the Risk Model
Stops and targets are volatility-based. Results will vary materially across symbols and timeframes because the strategy adapts to local ATR conditions.
Step 4: Evaluate by Regime, Not by Individual Trade
This strategy is meant to be judged over a broad sample. It is a context-and-confirmation model, not a scalping script trying to predict every turn.
Strategy Limitations
The strategy is intentionally selective and may skip many charts or periods
Higher-timeframe confirmation uses confirmed data and can therefore feel slower than live-developing bias models
ATR-based exits adapt to volatility, which means trade statistics can shift significantly across markets
No strategy can remove all adverse conditions, especially during sudden event-driven repricing
Originality Statement
Parallax Covenant Strategy is original in the way it integrates multiple distinct analytical engines into one non-repainting framework. It is not a basic moving average crossover, not a single-oscillator strategy, and not a toy example of ATR stops. Its value comes from requiring alignment between market regime, internal pressure, mapped bias, structure, and release conditions before entering risk.
Disclaimer
This strategy is provided for educational and informational purposes only. It is not financial advice or a recommendation to buy or sell any instrument. Historical backtest results do not guarantee future performance. Always use realistic expectations, proper risk management, and independent judgment.
- Made with passion by jackofalltrades
Strategy
Mercator Pressure [JOAT]Mercator Pressure
Introduction
Mercator Pressure is an open-source institutional-style pressure oscillator built to measure directional force using a blended model of candle pressure, close-location behavior, range expansion, optional volume impulse, and volatility-channel context. The goal is to capture not just whether momentum is positive or negative, but how forceful and structurally aligned that movement is.
The problem Mercator Pressure solves is shallow momentum interpretation. Many oscillators react to price movement but fail to distinguish between weak drift, strong displacement, location inside a volatility envelope, and divergence between price and internal force. Mercator Pressure combines those dimensions in one panel and adds confirmed divergence logic, threshold regimes, layered gradients, and a live dashboard.
Core Concepts
1. Weighted Candle Pressure Engine
The core model scores each bar using a weighted blend of body impulse, close location, range expansion, and optional relative volume impulse. This helps the oscillator react differently to high-conviction bars than to passive movement.
2. Volatility-Channel Context Engine
Pressure is not evaluated in isolation. The script also measures where price sits inside an adaptive volatility envelope and uses that context as part of the composite regime model.
3. Composite Regime and Signal Layer
The pressure and context models are blended into a smoothed composite oscillator and signal line. Regime state is then derived from threshold behavior and internal persistence.
4. Confirmed Divergence Detection
Both regular and hidden divergence are supported using pivot-confirmed logic, which keeps the divergence framework more stable than naive visual divergence methods.
5. Institutional Panel Styling
Mercator Pressure uses layered fills, gradient regime cues, restrained optional divergence markers, and a top-right dashboard rather than retail-style arrow spam.
Features
Multi-factor pressure engine: Body, close location, range expansion, and optional relative volume
Volatility envelope context: Internal force is blended with channel position
Composite oscillator and signal line: Regime interpretation is smoother and more stable
Regular and hidden divergence: Pivot-confirmed divergence conditions
Confirmed-bar event gating: Alerts and key events can be evaluated on closed bars
Layered gradient fills: Smooth panel depth instead of harsh histogram clutter
Regime background tint: Visual context in the panel
Top-right dashboard: Live state readout for regime, slope, context, and divergence
Optional divergence markers: Uses professional square and diamond markers, not arrows
Alertconditions: Regime flips, signal crosses, expansions, and divergences
How to Use This Indicator
Step 1: Read the Composite Line Versus Signal
When the composite line is above the signal and above key thresholds, internal pressure is supportive. The opposite applies during bearish pressure.
Step 2: Check Regime State
Use the dashboard and panel tint to determine whether the script sees a bullish, bearish, or neutral pressure regime.
Step 3: Watch Expansion Conditions
Expansion events are stronger than ordinary threshold crosses because they imply pressure is extending into a more forceful state.
Step 4: Use Divergence as Context
Divergence is best used as a warning or contextual signal, not as a blind reversal trigger.
Indicator Limitations
Divergence only confirms after pivots confirm, which introduces natural delay by design
Pressure is a proxy model derived from chart data, not exchange-level order flow
The composite engine is adaptive and may behave differently across very low-volatility versus very high-volatility symbols
This script is best used as a directional-quality filter or context tool, not a standalone trading system
Originality Statement
Mercator Pressure is original in the way it combines weighted candle pressure, volatility-envelope context, regime hysteresis, and pivot-confirmed divergence inside one coordinated panel. Its value comes from force measurement, contextualization, and divergence structure rather than from any one common oscillator formula.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Pressure and divergence readings are derived from historical price and volume behavior and do not guarantee future results.
- Made with passion by jackofalltrades
Indicator
ATR Volatility Regime [NovaLens]Volatility regime tool built to separate two things ATR alone cannot tell you apart: where volatility currently sits in its own rolling history, and which direction the regime is rotating. Adds a velocity-gated release event on top, so the indicator flags fast coiled-spring releases on the confirmed bar - and refuses to fire on the slow leaks that only look like one.
Most volatility tools collapse one axis. A raw ATR plot tells you the bar range and nothing about whether that range is rare. A percentile-rank histogram tells you the rank but not whether vol is loading or unloading. ATR Volatility Regime separates the two by design:
Tier tracks where volatility sits in its own rolling history (Compression / Quiet / Normal / Elevated).
Phase tracks where volatility is rotating (Rising / Topping / Falling / Bottoming).
A Compression reading is not a breakout signal. It is the market saying "vol is loaded." Whether it actually releases depends on the next move. When a sustained compression actually breaks above mid-rank within a 5-bar velocity window, the indicator prints a Release diamond and pulses the pane background. Slow leaks that drift through Quiet for more than 5 bars are canceled, not reported. That single gate is what separates a real coiled-spring release from a sideways drift.
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◉ HOW IT WORKS
The vol input. Wilder ATR over the chosen length, expressed as a percentage of close so the read is comparable across price levels and instruments. Mathematically guarded to stay clean across historical data gaps and unusual price series.
The percentile rank. The current ATR% is ranked against its own rolling lookback window (100 / 200 / 300 bars by Horizon). This is an asset-calibrated percentile - "P75 on BTC" means "vol higher than 75% of the last 200 BTC readings," not a market-wide cutoff. The same indicator works across SPY, BTC, EURUSD, and XAU without retuning. The raw rank drives the state engine; an EMA-smoothed copy drives the visual line so the plot reads calm without numbing event detection. Warm-up is honest: until the lookback fills, the panel shows "Warming up" and refuses to assign a tier. NA never collapses to a fake Normal.
The tier model. Four tiers cut on rawRank (P25, P50, P75) with asymmetric hysteresis: 1 confirmed bar to step up (so a vol breakout is not missed), 3 confirmed bars to step down (so a tier change only confirms when vol has actually died). The ribbon fill and oscillator line both color by tier. Extreme is a signal class, not a tier; it would flicker on and off at the P90 boundary if we colored the ribbon by it.
The phase model. Four phases (Rising / Topping / Falling / Bottoming) read off the rawRank slope. Slow rotations need 2 bars of confirmation to flip; violent moves with |delta rank| > 15 bypass the confirm and flip immediately. Peak and trough detection is plateau-aware: a strict ( greater-than on both sides) check missed the patterns where ATR percentile pins at 100 for multiple bars, so the algorithm uses greater-or-equal on the left side and greater-than on the right.
The events. Three signature events, each with its own gating:
Compression Release : velocity-gated. The Compression tier must run at least 10 bars to load the spring; on exit, rawRank must reach the mid (>= 50) within a 5-bar window. Slow leaks that drift through Quiet for more than 5 bars are canceled. Re-entering Compression also cancels the pending episode.
Extreme Touch : rawRank peaks at >= 90. Re-arm runs through a three-valve cascade (rank drop to <= 75, a higher pivot with a +2 rank headroom so a 98 peak after a 97 cannot re-fire, or 2x lookback time decay) so the same Extreme arc cannot duplicate-fire, but a genuinely higher pivot in the same arc still counts.
Cooling : armed when an Extreme fires; fires on the first confirmed bar after where rawRank falls below 75 within a 10-bar window. Disarms on fire or when the window expires. The armed-latch architecture means fast drops out of an Extreme are tracked after the Extreme event arms Cooling, instead of relying on a single fragile cross check that would miss the drop if the threshold was already crossed on the Extreme bar itself.
The Playbook Lens. Pure interpretation layer. Engine, percentile, tier, phase, and objective events are identical across lenses. The Lens recolors three visual surfaces only: the panel Playbook row text and tone, the Playbook Heatmap Strip at y = -5, and an optional Tint Price Candles by Playbook Fit overlay. Switching the Lens dropdown answers a different question against the same volatility truth: "does this regime align with the workflow I am running?" - context, never a directive.
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◈ HOW TO READ IT
The pane shows the smoothed percentile rank line wrapped in a tier-colored ribbon with a Volatility Glow halo that breathes wider in the loaded zones (Compression and Extreme) and tightens in Normal. Threshold lines mark P25, P50, P75, and P90.
Deep blue (Compression): rawRank in [0, 25). Loaded spring.
Light blue (Quiet): rawRank in [25, 50). Below median, not stretched.
Gray (Normal): rawRank in [50, 75). Typical bar ranges.
Orange (Elevated): rawRank in . High vol relative to recent history.
Red (Extreme): event color, not a tier. Drives Extreme Touch markers.
Teal (Release): event color, not a tier. Drives Compression Release markers.
Markers, in order of conviction:
Compression Release (diamond on the line, Release color, with a matching pane background pulse): a >= 10 bar compression run resolved into Normal+ within 5 bars. Non-directional by design - a volatility state change, not a price direction call.
Extreme Touch (small circle anchored to the actual peak bar, Extreme color): rawRank just peaked at or above the 90th percentile of its rolling history. Reads as topping pressure of vol, not a directional reversal call.
Cooling (panel-only event, no chart marker): the first confirmed bar after an Extreme where rawRank fell back below 75 within a 10-bar window. Surfaces in the Last Event row and the Cooling alert.
The info panel synthesizes six rows: Volatility (tier + P-Score), Flow (phase), Age (bars in tier + the per-tier duration percentile so a 200-bar Quiet stretch is compared against historical Quiet stretches, not Elevated), Last Event / Context (state-based decay, no fixed timer), ATR Range (current bar range as % of price, with absolute price-unit ATR in the row tooltip), and Playbook (the Lens context read).
The Last Event row uses state-based decay , not an arbitrary 10-bar timer. A Compression Release stays visible while phase is Rising or tier is Normal+. An Extreme Touch stays visible while tier is Elevated. A Cooling read stays visible while tier is Normal or Elevated. When the event's regime context expires, the row returns to Context and summarizes the current regime instead of resizing or disappearing.
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✦ HOW WE USE IT: THE COILED-SPRING ARC
This is the arc the indicator is built to catch - not the only path. Many compressions resolve sideways without a confirmed release, and the velocity gate is what filters those out.
A common pattern on a liquid index or crypto chart, Swing profile (default), Neutral lens: the line drops into Compression and parks there for 15-30 bars. The ribbon turns deep blue, the Glow widens, and the panel Age row may read something like "Mature · 22 bars" or "Extended · 22 bars" - meaning the current run has already lasted longer than most recent Compression stretches on this market. The spring is loaded.
The full arc reads in four panel updates:
Release. rawRank reaches 50+ within the 5-bar velocity window after exiting Compression. A Release diamond prints on the line, the pane background pulses teal for one bar, and the Last Event row reads "Compression Release".
Run. Within a few bars the tier transitions through Normal into Elevated, the phase row flips Rising, and the smoothed line climbs toward the upper distribution.
Touch. If the move keeps loading, rawRank peaks at 92-98 and an Extreme Touch circle prints on the peak bar - the smoothed line is now in the upper edge of its own rolling distribution. The Last Event row updates to "Extreme Touch".
Unwind. Within 10 bars rawRank falls below 75. Cooling fires and the Last Event row updates again.
The Playbook Lens reframes the same arc without changing a number. Flip to Breakout: the Heatmap Strip lights teal during the release window (favorable) and dims toward red as the move stretches into Extreme (less favorable). Flip to Mean Reversion: the strip stays red through the release (vol is the wrong direction for fading) and only lights teal when Cooling confirms and tier drifts back through Normal toward Quiet. Flip to Risk Control: Compression marks calmer bar-range context, Elevated and Extreme mark the wider-bar context. Same volatility truth, different playbook fit. The engine is identical across lenses; only the interpretation layer changes.
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✦ OTHER APPLICATIONS
Breakout context : Compression Release diamonds after a loaded quiet regime, optionally combined with the Heatmap Strip reading favorable under the Breakout lens
Trend context : Rising Elevated or Rising Normal volatility as movement context for an external trend plan
Mean-reversion context : quieter or cooling regimes that may be more suitable for contained-range workflows
Volatility risk overlay : Elevated and Extreme states as wider-bar context when reviewing size, stops, or trade frequency
Vol regime classifier : use the Volatility row + Flow row in the panel as a top-down filter for any external trade plan, independent of the Lens
Alert-driven workflow : subscribe to Compression Release + Extreme Touch + Cooling and check the chart only when the volatility regime actually changes, not every bar
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⚙ GETTING STARTED
ATR Volatility Regime ships with three pre-tuned Horizon profiles plus a Custom override. Pick a horizon and start reading the regime:
Intraday : ATR 14, lookback 100, smoothing 3. Faster events, lighter hysteresis (1 up / 2 down). Use on 1m through 1H charts.
Swing (default) : ATR 14, lookback 200, smoothing 5. Balanced. Start here on 1H through 1D charts.
Long-Term Hold : ATR 20, lookback 300, smoothing 5. Slower, rarer events, heavier hysteresis (2 up / 3 down). Use on 1D and above.
Custom : full manual control of ATR Period, Lookback Window, and Smoothing.
Core settings:
Horizon : selects the tuning bundle above. Start with Swing.
ATR Period (Custom) : Wilder ATR period for the volatility input, in BARS. 14 is the standard. Shorter = more reactive; longer = smoother. Applies only when Horizon = Custom.
Lookback Window (Custom) : rolling lookback the ATR% is percentile-ranked against. Larger = smoother distribution, fewer extreme reads, slower compression releases. Smaller = sharper, more events.
Smoothing (EMA) (Custom) : EMA bars applied to the percentile-rank for the visual DISPLAY layer (plot, ribbon, panel readouts). The RAW rank still drives tier, phase, and events - smoothing only calms the visual. Set to 1 to disable smoothing.
Playbook Lens:
Neutral (default) : factual regime read, heatmap stays gray. Use this to learn the engine.
Breakout : range-expansion context. Loaded Compression and Compression Release read favorable; already-stretched Elevated or Extreme states shift toward caution.
Trend : directional-movement context. Rising Elevated and Rising Normal regimes read favorable; topping or cooling volatility shifts toward caution.
Mean Reversion : contained-range context. Quiet, Cooling, and Normal/Falling regimes read favorable; Release, Elevated, and Extreme regimes shift toward caution.
Risk Control : stretched-volatility context. Compression reads calm; Elevated and Extreme states warn that bar ranges are wide.
The Lens NEVER changes the engine - same tier, same phase, same Compression Release, same Extreme Touch, same alerts. Only the panel Playbook row text, the Heatmap Strip color, and the optional candle tint move.
Display:
Show Compression Releases (hero): diamond on the line + pane background pulse on release. On by default.
Show Extreme Touches : circle on the peak bar at rawRank >= 90. On by default.
Show Price Chart Markers : mirrors Compression Release diamonds and Extreme bar tints onto the price chart. OFF by default to keep the price chart clean.
Show Raw Rank Line : faint unsmoothed percentile rank line behind the smoothed display line. OFF by default. Toggle on to debug fast vol changes.
Show Volatility Glow : halo that widens at the loaded extremes (Compression and Extreme) and tightens in Normal. On by default.
Show Info Panel : 6-row state panel. On by default.
Panel Position : Top Right (default), Top Left, Bottom Right, Bottom Left, Middle Right.
Theme : Auto (detect chart background), Dark, or Light.
Show Playbook Heatmap Strip : thick band at y = -5 that recolors with the Lens. On by default.
Tint Price Candles by Playbook Fit : paints price-chart candles with the Release / Extreme palette per the active Lens. OFF by default; disabled automatically when Lens = Neutral.
Appearance / Palette (6 color pickers):
Compression, Quiet, Normal, Elevated, Extreme, Release - each on its own line with a state-explainer tooltip. The Display Rank line, Raw Rank, Tier Ribbon fill, Volatility Glow, Heatmap Strip, panel tier text, candle tints, and event markers all reference these inputs so users can adapt the palette (color-blind, light-mode, brand themes) without forking the script.
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△ LIMITATIONS
Warm-up : the lookback window must fill before any tier is assigned. On Swing (200) that is 200 bars; on Long-Term Hold (300) that is 300. Until then, the panel shows "Warming up" and the state engine refuses to fake a Normal read.
Visual smoothing lag : the visible line is intentionally calmer than the raw engine. ATR is a backward-looking Wilder-smoothed measure, and the display line is lightly EMA-smoothed on top, so fast volatility expansions can look slightly delayed in the visible plot. The rawRank engine is the sharper layer underneath and is what actually drives the tier, phase, events, and alerts. The smoothed line is the readable copy; do not read a slight visual delay as the event engine being slow.
Percentile is relative, not absolute : a "Compression" read on a chronically quiet asset can still be wider than an "Elevated" read on a chronically loud asset. The indicator compares each asset against ITS OWN history, not across markets.
Regime shifts shrink the window : a structural vol regime change (e.g. a quiet 2-year period followed by a sustained higher-vol regime) takes about one lookback window to fully recalibrate. The first few weeks after a regime shift can read noisier than the steady-state.
Compression Release is non-directional : the diamond and the pane pulse tell you the spring released, not which way price went. Combine with directional context (trend, structure, or a separate momentum tool) for direction.
Extreme Touch is a state read, not a reversal call : rawRank pinning above 90 means vol is rare for this market; it does not mean price is about to reverse. Cooling tells you the unwind has begun, not where the next leg goes.
Playbook Lens is interpretation, not validation : the Heatmap Strip recolors regime context based on the active Lens. It is not a backtested edge - it is a quick visual answer to "does my workflow want this regime?"
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🔔 ALERTS
Four alert conditions are built in so you can monitor without checking every bar manually:
Compression Release : a sustained compression (>= 10 bars) confirmed above mid-rank within 5 bars. The hero event.
Extreme Touch : rawRank peaked above P90. Fires on the bar after the actual peak (peak detection requires the next bar to confirm the turn-down).
Cooling : the first confirmed bar after an Extreme where rawRank falls below 75 within 10 bars.
Compression Entry : rawRank dropped below P25 (sustained tier transition into Compression).
All four alerts fire on bar close (gated on barstate.isconfirmed). Each alert message is a pure JSON payload with ticker, price, timeframe, and timestamp fields for webhook routing.
Four alerts by design - concentrated on the signature events. Tier and phase transitions stay visible in the info panel for users who want them on the chart, but they do not fire alerts. Keeping the alert stream lean is what makes "subscribe and let the regime come to you" a useful workflow instead of a notification flood.
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⌁ NOTES
Based on the classical ATR percentile-rank construction, with asymmetric hysteresis and a velocity-gated compression-release definition layered on top.
Repaint: intrabar-only. Closed-bar alerts are confirmed; current-bar visuals may update until the bar closes. All alert conditions are gated on barstate.isconfirmed. Peak-confirmed events (Extreme Touch) print on the bar AFTER the actual peak, on a one-bar offset, so the marker aligns with the true peak bar.
References: J. Welles Wilder Jr., New Concepts in Technical Trading Systems (1978), Trend Research; percentile-rank concept widely used across volatility studies.
Open-source under MPL 2.0. Free to use, fork, study.
NovaLens Indicator
Cartograph Bands [JOAT]Cartograph Bands
Introduction
Cartograph Bands is an open-source price-space mapping overlay that translates internal momentum and regime pressure into adaptive bands around price. Instead of displaying momentum in a separate pane and forcing the user to mentally translate it back into price context, the script projects a composite regime score directly into layered price envelopes.
The problem Cartograph Bands solves is disconnected interpretation. Oscillators can show strength or weakness, but they often fail to communicate where that state matters on the chart. Cartograph Bands closes that gap by converting internal regime intensity into inner, outer, and far price-space bands, then combining that with multi-timeframe confirmation and volatility-state transitions.
Core Concepts
1. Composite Momentum Engine
The script blends several internal measurements including RSI, CMO, ROC normalization, and slope behavior to create a bounded momentum/regime score. This reduces reliance on any single oscillator.
2. Price-Space Mapping
That composite score is mapped into adaptive offsets around price using ATR and standard deviation inputs. The result is a set of bands that express regime intensity as chart structure rather than as a separate panel line.
3. Layered Band Geometry
Three band families are used:
Inner bands for local equilibrium
Outer bands for state extension
Far bands for exceptional displacement
4. Non-Repainting Higher Timeframe Confirmation
Confirmed higher-timeframe values are requested using offset expressions and lookahead handling intended to avoid future leakage on historical bars.
5. Compression and Expansion State Tracking
Cartograph Bands also classifies whether the current market state is compressing or expanding, which gives context to outer-band tests and re-entry events.
Features
Composite momentum model: Multiple internal regime factors instead of one oscillator
Mapped price-space bands: Regime intensity projected directly onto chart structure
Inner, outer, and far layers: Different depths of price displacement
MTF confirmation dashboard: Top-right summary with higher-timeframe agreement context
Compression and expansion tracking: Identifies volatility-state transitions
Outer-band re-entry events: Useful for exhaustion or reacquisition studies
State candle tinting: Visual context without heavy marker clutter
Gradient cloud system: Layered institutional-style fills
Confirmed-signal mode: Optional bar-close confirmation behavior
Alertconditions: Regime flips, re-entry, expansion, compression, and MTF conflict
How to Use This Indicator
Step 1: Read the Band State
Price inside the inner structure implies local balance. Sustained travel into outer and far layers implies stronger directional pressure.
Step 2: Check the Dashboard
Use the dashboard to confirm whether the chart-timeframe state aligns with higher-timeframe conditions.
Step 3: Watch Re-entry Behavior
Re-entry from outside the outer band can highlight exhaustion or failed extension, especially when expansion begins to fade.
Step 4: Use Compression and Expansion as Context
A compression state reduces the importance of directional interpretation. Expansion after compression matters more than random outer-band wandering.
Indicator Limitations
The mapping is adaptive, so band distance changes with symbol volatility
Higher-timeframe context is intentionally confirmed and may feel slower than live-developing HTF tools
Band interaction alone should not be treated as a complete trade system
The script maps internal regime state into price context, but it does not forecast exact reversal points
Originality Statement
Cartograph Bands is original in the way it blends multiple internal regime measurements and projects them into layered price-space geometry. Its value is not just an oscillator or just bands, but the interaction between regime scoring, mapped offsets, MTF confirmation, and state transitions.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. All mapped bands are analytical references derived from historical price behavior and should be used with sound judgment and risk management.
- Made with passion by jackofalltrades
Indicator
Arbiter Channel [JOAT]Arbiter Channel
Introduction
Arbiter Channel is an open-source market state overlay built to classify directional control, compression, and expansion using a layered baseline-and-channel framework. The script blends an Ichimoku-inspired composite baseline, body-aware tolerance channels, and a confirmed-bar trend-state engine to identify whether price is operating in directional acceptance, compression, or expansion. Rather than acting like a generic moving average channel, Arbiter Channel is designed to map the relationship between equilibrium and displacement.
The problem Arbiter Channel solves is false trend interpretation. Price can trade above a moving average without truly being in an efficient trend, and it can look weak during healthy pullbacks inside a broader expansion. Arbiter Channel separates baseline equilibrium, tolerance acceptance, and directional displacement so that the user can tell whether price is simply oscillating around fair value, compressing inside equilibrium, or expanding away from it with intent.
Core Concepts
1. Composite Baseline Construction
The baseline is built from an Ichimoku-style blend of Conversion, Base, Span A, and Span B components, with user-controlled inclusion and weighting. This creates a smoother and more structurally aware equilibrium anchor than a single moving average:
tenkan = donchianMid(convLen)
kijun = donchianMid(baseLen)
spanA = math.avg(tenkan, kijun)
spanB = donchianMid(spanBLen)
2. ATR and Body Tolerance Channel
Instead of plotting a fixed-width envelope, the channel adapts to both ATR behavior and candle-body pressure. This helps the band respond differently during active displacement than during passive drift. The result is a tolerance corridor where trend acceptance and loss of acceptance become visually obvious.
3. Confirmed-Bar Trend State Machine
Trend transitions are only registered on confirmed bars. This avoids intrabar flipping and helps keep trend-state changes non-repainting for practical signal use. The script distinguishes directional trend shifts from regime changes, so compression and expansion can evolve without necessarily forcing a full directional flip.
4. Compression and Expansion Regimes
Arbiter Channel tracks whether price is contracting around equilibrium or extending away from it. This is important because directional trend and volatility regime are not the same thing. A bullish trend can be compressing before expansion, and expansion can fail back into balance.
5. Institutional Visualization Layer
The overlay uses nested clouds, baseline shadows, state candle tinting, controlled event labels, and a medium top-right dashboard to summarize regime and trend without clutter.
Features
Composite baseline engine: Uses multiple Ichimoku-derived components instead of a single average
Adaptive tolerance channels: Envelope width responds to volatility and body behavior
Compression and expansion classification: Distinguishes rotational balance from directional release
Confirmed-bar trend state engine: Trend shifts only confirm after bar close
Outer reclaim events: Detects price returning inside channel boundaries after extension
Cloud-based regime visualization: Multi-layer fills show equilibrium and displacement zones
State candle tinting: Candles inherit directional context without overwhelming price
Top-right dashboard: Displays current trend, regime, channel state, and internal diagnostics
Fully configurable palette: Built for dark charts with adjustable institutional tones
Confirmed alertconditions: Trend shifts, regime changes, reclaim events, and expansion bursts
How to Use This Indicator
Step 1: Read the Trend State
Start with the dashboard and baseline color. This tells you whether the script currently classifies the market as bullish, bearish, or neutral from a confirmed-bar perspective.
Step 2: Check the Regime
Compression means price is accepting around equilibrium. Expansion means price is actively displacing. Combining trend with regime helps determine whether to expect continuation or wait for release.
Step 3: Use the Channel Structure
The inner and outer bands act as context zones. Price holding outside the inner corridor during expansion is stronger than price simply crossing the baseline.
Step 4: Watch Reclaim Events
When price extends beyond the outer channel and then reclaims back inside it, that event can signal exhaustion, acceptance failure, or a return to balance.
Indicator Limitations
The baseline is a structural equilibrium model, not a predictive model
Compression and expansion are relative to the current symbol and timeframe inputs
Strong news events can create abrupt regime transitions that temporarily distort channel interpretation
The script is best used as a context overlay, not as a standalone trade trigger
Originality Statement
Arbiter Channel is original in the way it separates directional trend, equilibrium tolerance, and volatility regime into one coordinated overlay. It is not a simple moving average channel and not a direct copy of Ichimoku. The value comes from combining a composite baseline, adaptive tolerance geometry, and confirmed-bar regime logic into a single context engine.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice and does not guarantee future market behavior. Always use proper risk management.
- Made with passion by jackofalltrades
Indicator
