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Reversing Momentum: The Optimal Dynamic Momentum Strategy

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Abstract

We study the optimal dynamic trading strategy between a riskless asset and a risky asset with momentum (momentum asset). The most salient characteristic of momentum is that positive price shocks predict positive future returns. This characteristic leads to big swings in returns over multiple periods. Investors with relative risk aversion greater than one dislike such big swings. We show that it is optimal for such investors to reverse momentum by holding less or even shorting the momentum asset. We find that the optimal portfolio weight also depends on the historical price path, in addition to momentum. Different historical price paths, even if they have the same momentum, lead to different optimal portfolio weights. In particular, with rebound path (a historical price path that decreases at the beginning and then rebounds later to have a positive momentum), it is optimal for investors to hold less or may short the momentum asset and hence suffer less or even benefit from momentum crashes.

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  • Kai Li & Jun Liu, 2016. "Reversing Momentum: The Optimal Dynamic Momentum Strategy," Research Paper Series 370, Quantitative Finance Research Centre, University of Technology, Sydney.
    • Handle: RePEc:uts:rpaper:370
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    File URL: https://www.uts.edu.au/sites/default/files/qfr-archive-03/QFR-rp370.pdf
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    Cited by:

    1. He, Xue-Zhong & Li, Kai & Li, Youwei, 2018. "Asset allocation with time series momentum and reversal," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 441-457.
    2. Roberto Dieci & Xue-Zhong He, 2018. "Heterogeneous Agent Models in Finance," Research Paper Series 389, Quantitative Finance Research Centre, University of Technology, Sydney.

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    More about this item

    Keywords

    portfolio selection; momentum crashes; dynamic optimal momentum strategy;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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