摘要：Systematic traders employ algorithmic strategies to manage their investments. As a resultof the deterministic nature of such strategies, it is possible to determine their exact responses toany conceivable set of market conditions. Consequently, sensitivity analysis can be conducted tosystematically uncover undesirable strategy behavior and enhance strategy robustness by addingcontrols to reduce exposure during periods of poor performance/unfavorable market conditions, orto increase exposure during periods of strong performance/favorable market conditions. In this study,we formulate both a simple systematic trend-following strategy (i.e., trading model) to simulateinvestment decisions and a market model to simulate the evolution of instrument prices. We thenmap the relationship between market model parameters under various conditions and strategyperformance. We focus, in particular, on identifying the performance impact of changes in both serialdependence in price variability and changes in the trend. The long-range serial dependence of thetrue range worsens performance of the simple classic trend-following strategy. During periods ofstrong performance, the dispersion of trading outcomes increases significantly as long-range serialdependence increases.
关键词：trend-following; Monte Carlo; sensitivity analysis
