Aureate Market Architecture Strategy [JOAT]Aureate Market Architecture Strategy
Introduction
Aureate Market Architecture Strategy is an open-source TradingView 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.
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