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On Robustness of Double Linear Policy with Time-Varying Weights

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  • Xin-Yu Wang
  • Chung-Han Hsieh

Abstract

In this paper, we extend the existing double linear policy by incorporating time-varying weights instead of constant weights and study a certain robustness property, called robust positive expectation (RPE), in a discrete-time setting. We prove that the RPE property holds by employing a novel elementary symmetric polynomials characterization approach and derive an explicit expression for both the expected cumulative gain-loss function and its variance. To validate our theory, we perform extensive Monte Carlo simulations using various weighting functions. Furthermore, we demonstrate how this policy can be effectively incorporated with standard technical analysis techniques, using the moving average as a trading signal.

Suggested Citation

  • Xin-Yu Wang & Chung-Han Hsieh, 2023. "On Robustness of Double Linear Policy with Time-Varying Weights," Papers 2303.10806, arXiv.org.
    • Handle: RePEc:arx:papers:2303.10806
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    References listed on IDEAS

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    1. Chung-Han Hsieh, 2022. "On Robust Optimal Linear Feedback Stock Trading," Papers 2202.02300, arXiv.org.
    2. Atul Deshpande & B. Ross Barmish, 2018. "A Generalization of the Robust Positive Expectation Theorem for Stock Trading via Feedback Control," Papers 1803.04591, arXiv.org.
    3. Joseph D. O'Brien & Mark E. Burke & Kevin Burke, 2018. "A Generalized Framework for Simultaneous Long-Short Feedback Trading," Papers 1806.05561, arXiv.org, revised Aug 2020.
    4. Chung-Han Hsieh, 2022. "On Robustness of Double Linear Trading with Transaction Costs," Papers 2209.12383, arXiv.org.
    5. Etheridge,Alison, 2002. "A Course in Financial Calculus," Cambridge Books, Cambridge University Press, number 9780521890779.
    6. Atul Deshpande & John A Gubner & B. Ross Barmish, 2020. "On Simultaneous Long-Short Stock Trading Controllers with Cross-Coupling," Papers 2011.09109, arXiv.org.
    7. Etheridge,Alison, 2002. "A Course in Financial Calculus," Cambridge Books, Cambridge University Press, number 9780521813853.
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