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Analysis of a Global Futures Trend-Following Strategy

School of Professional Studies, University of New York, 119 W 31st Street, New York, NY 10001, USA
Department of Health Administration, Texas State University, 601 University Drive, San Marcos, TX 78666, USA
Author to whom correspondence should be addressed.
J. Risk Financial Manag. 2019, 12(3), 111;
Received: 9 June 2019 / Revised: 22 June 2019 / Accepted: 25 June 2019 / Published: 29 June 2019
(This article belongs to the Section Financial Markets)
PDF [4015 KB, uploaded 29 June 2019]


Systematic traders employ algorithmic strategies to manage their investments. As a result of the deterministic nature of such strategies, it is possible to determine their exact responses to any conceivable set of market conditions. Consequently, sensitivity analysis can be conducted to systematically uncover undesirable strategy behavior and enhance strategy robustness by adding controls to reduce exposure during periods of poor performance/unfavorable market conditions, or to 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 simulate investment decisions and a market model to simulate the evolution of instrument prices. We then map the relationship between market model parameters under various conditions and strategy performance. We focus, in particular, on identifying the performance impact of changes in both serial dependence in price variability and changes in the trend. The long-range serial dependence of the true range worsens performance of the simple classic trend-following strategy. During periods of strong performance, the dispersion of trading outcomes increases significantly as long-range serial dependence increases. View Full-Text
Keywords: trend-following; Monte Carlo; sensitivity analysis trend-following; Monte Carlo; sensitivity analysis

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Nokes, D.; Fulton, L. Analysis of a Global Futures Trend-Following Strategy. J. Risk Financial Manag. 2019, 12, 111.

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J. Risk Financial Manag. EISSN 1911-8074 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
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