interpret-mc-results

To interpret Monte Carlo backtest results, apply a five-point decision framework covering sample size sanity, edge persistence, risk of ruin, profit factor sequencing, and P5 drawdown against initial capital to produce a structured deployment verdict.

When analyzing Monte Carlo outputs, check sample size adequacy, edge robustness, risk of ruin probability, profit factor-based sequencing interpretation, and P5 drawdown levels against the initial capital to ensure comprehensive risk assessment.

Use Monte Carlo risk of ruin and P5 drawdown data to evaluate deployment readiness by comparing drawdown budgets against initial capital, ensuring edge persistence, and verifying sample size sanity before generating a final deployment verdict.

You can incorporate position sizing guidance into Monte Carlo performance analysis by reading an optional sizing configuration file, allowing the decision framework to output actionable sizing recommendations alongside the deployment verdict and caveats.

Known limitations of applying a Monte Carlo decision framework include dependencies on historical data assumptions, the exclusion of real-world market impact from random sequencing, and the need to explicitly document consecutive loss planning and confidence interval interpretation caveats.