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In a previous post, we discussed a theoretical model for studying the effectiveness of stop losses. In this post, we will present an empirical study of their efficacy in the commodity market. Reference [1] examined how fixed and trailing stop losses perform in this market. The authors pointed out,
This paper examined the effect of fixed and trailing stop-loss on commodity factor strategies. We found that while unmanaged factors delivered disappointing performance net of transactions costs, commodity factor premia are alive and well when implemented with simple stop-loss strategies on the asset level. With a fixed-stop (trailing-stop), commodity factors on average generate a Sharpe ratio of 0.92 (1.28), with less than 20% maximum drawdown, and a positive return skewness profile (except for the skewness factor). Using momentum as an example, the success of stop-loss in a factor context is not regime-dependent, but its effectiveness is primarily driven by the quality of the signal, commodity return volatility and serial correlations, as well as transactions costs. Accordingly, we demonstrated that the benefit of stop-loss can be amplified through dynamically calibrating loss thresholds with realized volatility. Finally, we highlighted that stop-loss performs best in factors constructed with high conviction weighting schemes. Overall, we emphasize the crucial role of risk management in commodity factor implementation.
In short, in the commodity market, stop losses are effective when the autocorrelation of returns is positive, which is consistent with previous findings. Additionally, the volatility of returns influences how effective stop losses are.
A notable result of this study is that using trailing-stop with dynamic thresholds could enhance factor performance compared to using fixed thresholds.
Let us know what you think in the comments below or in the discussion forum.
References
[1] John Hua FAN, Tingxi ZHANG, Commodity Premia and Risk Management, 2023
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