Expectancy Calculation

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Risk Considerations

Risk management for expectancy calculation addresses position limits, stop loss placement, correlation exposure, and worst-case drawdown scenarios. Regular monitoring prevents drift from intended behavior.

Important: Always validate expectancy calculation logic on out-of-sample data before live deployment. Paper trading reveals execution issues that backtests miss.

Core Concepts

Understanding expectancy calculation requires familiarity with market microstructure, order flow dynamics, and execution latency. The following sections detail each component.

Implementation

Implementation of expectancy calculation follows a modular architecture. Configuration files define parameters, strategy modules handle logic, and exchange adapters manage execution.

Common Issues

Common issues with expectancy calculation include look-ahead bias in backtesting, overfitting to historical regimes, inadequate handling of exchange downtime, and insufficient logging for debugging.

Important: Always validate expectancy calculation logic on out-of-sample data before live deployment. Paper trading reveals execution issues that backtests miss.

Production Notes

In production, expectancy calculation requires monitoring for API rate limits, database connection pooling, log rotation, alert thresholds, and automated restart procedures. Document runbooks for incident response.