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Design and analysis of momentum trading strategies

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  • Richard J. Martin

Abstract

We give a complete description of the third-moment (skewness) characteristics of both linear and nonlinear momentum trading strategies, the latter being understood as transformations of a normalised moving-average filter (EMA). We explain in detail why the skewness is generally positive and has a term structure. This paper is a synthesis of two papers published by the author in RISK in 2012, with some updates and comments.

Suggested Citation

  • Richard J. Martin, 2021. "Design and analysis of momentum trading strategies," Papers 2101.01006, arXiv.org, revised Jan 2023.
    • Handle: RePEc:arx:papers:2101.01006
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    File URL: http://arxiv.org/pdf/2101.01006
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    References listed on IDEAS

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    1. Richard Martin & Torsten Schoneborn, 2011. "Mean Reversion Pays, but Costs," Papers 1103.4934, arXiv.org.
    2. Marc Potters & Jean-Philippe Bouchaud, 2005. "Trend followers lose more often than they gain," Papers physics/0508104, arXiv.org.
    3. Tung-Lam Dao & Trung-Tu Nguyen & Cyril Deremble & Yves Lemp'eri`ere & Jean-Philippe Bouchaud & Marc Potters, 2016. "Tail protection for long investors: Trend convexity at work," Papers 1607.02410, arXiv.org.
    4. Richard J. Martin & Aldous Birchall, 2020. "Black to Negative: Embedded optionalities in commodities markets," Papers 2006.06076, arXiv.org, revised Oct 2020.
    5. Richard J. Martin, 2012. "Optimal multifactor trading under proportional transaction costs," Papers 1204.6488, arXiv.org.
    6. Richard J Martin, 2011. "Saddlepoint methods in portfolio theory," Papers 1201.0106, arXiv.org.
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    Cited by:

    1. Ivan Letteri & Giuseppe Della Penna & Giovanni De Gasperis & Abeer Dyoub, 2022. "DNN-ForwardTesting: A New Trading Strategy Validation using Statistical Timeseries Analysis and Deep Neural Networks," Papers 2210.11532, arXiv.org.

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