Kalshi Strategy Backtester ⚡

Doctrine-compliant strategy simulation powered by signal processing framework (Article I, V)

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Ava AI Trading Doctrine — Article I (First Principles: Signal Processing Framework), Article IV (Risk Management), Article V (Learning Loop). All simulations enforce SNR-based position sizing and drawdown limits.
v1.0

🎯 Select Strategy

Mean Reversion

Buy when price deviates from moving average — mean reversion on event contract prices

Quant Doctrine: SNR Gate

Momentum Trend

Follow price trends with EMA crossovers and volume confirmation

Quant

EE Signal Processing

Filter bank decomposition — separate signal from noise per Article I framework

Doctrine Core

Matched Filter

Maximum SNR at decision time — detect known event patterns in price action

Doctrine Core

Phase Divergence

Detect divergence between short and long cycle components — early reversal signal

Doctrine Core

⚙️ Parameters

Event / Market
Initial Capital
Start Date
End Date
Max Positions
SNR Threshold (Doctrine min)

🛡️ Doctrine Risk Gates

Daily Max Loss -3% (Article IV)
Weekly Max Loss -6% (Article IV)
Monthly Max Loss -12% (Article IV)
Stablecoin Reserve 20% buffer (Article IV)
Position Sizing By SNR (Article IV)
Correlation Cap 0.70 (Article IV)

Simulates trading with doctrine-compliant risk management