How to Evaluate a Quantitative Trading Strategy
Summary
This article presents a checklist for judging whether a quantitative strategy is understandable and whether its reported performance reveals its risks. It recommends examining the strategy’s economic or behavioral rationale, the explanation for position sizing, and a frequently updated account-value curve that includes unrealized losses. A curve showing only closed trades can conceal drawdowns or risk from adding to losing positions.
The checklist also calls for trade statistics such as win rate, payoff ratio, average gain and loss, total-loss share, maximum drawdown, Sharpe ratio, and trade count. It highlights the need to consider extreme-market behavior, stop-loss or forced-exit procedures, and the length of live trading history. The author favors broker or platform order interfaces for greater visibility into prices and quantities. These points are due-diligence guidance, not a formal scoring framework: the article supplies no example strategy or comparative evidence, and live history or interface transparency alone cannot establish future profitability or execution quality.
Key ideas
- A strategy should have a coherent rationale and a clear explanation of how it sizes positions.
- Performance reporting should include account equity and unrealized losses, not only closed-trade gains.
- Win rate should be considered alongside payoff, drawdown, loss, and trade-frequency statistics.
- Strategy review should cover extreme-market behavior and a defined way to limit losses.
- A long live record and transparent order reporting can inform due diligence but do not guarantee future results.
Tags
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.