Backtesting the impact of stop-loss mechanisms on trading strategy performance

Details

Supervisors

Iania, Leonardo

Faculty

Louvain School of Management

Degree label

Master [120] : ingénieur de gestion, à finalité spécialisée

Abstract

This thesis investigates the impact of stop-loss settings on the performance of trading strategies across various financial assets. Utilizing a comprehensive quantitative approach, including Multivariate Analysis of Variance (MANOVA) followed by detailed Ordinary Least Squares (OLS) regression analysis, this study assesses how different stop-loss levels influence key trading performance metrics such as Sharpe Ratio, Worst Trade, Maximum Drawdown, Win Rate, Volatility , and Average Trade. The research specifically examines the effects of stop-loss settings ranging from very tight (2%) to more adaptive (ATR-based) configurations. The findings indicate that while stop-loss settings significantly impact on certain performance metrics—most notably in mitigating severe losses and reducing volatility—they do not universally enhance risk-adjusted returns. The results show that more aggressive stop-loss settings generally lead to greater reductions in volatility and maximum drawdown, but also reduce the win rate and average profitability per trade. Notably, the study reveals that none of the tests for Sharpe Ratio, Sortino Ratio, nor the Annualized Return was statistically significant, suggesting that stop-losses may not improve the long-term risk-adjusted performance of trading strategies. Furthermore, the analysis highlights that the ATR-based stop-loss level provides a balanced approach, demonstrating consistent effectiveness across various performance metrics, which suggests its suitability for managing trading risks in diverse market conditions. This thesis underscores the trade-offs involved in implementing stop-losses and emphasizes the importance of tailoring stop-loss strategies to align with specific trading objectives and risk tolerance levels. The implications of this research are significant for traders and portfolio managers seeking to optimize trading strategies in volatile and uncertain financial markets. By providing a nuanced understanding of how stop-losses affect trading outcomes, this thesis contributes to the broader discussion on risk management in trading and offers practical insights for improving the robustness and effectiveness of trading strategies.