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On the Profitability of Optimal Mean Reversion Trading Strategies

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  • Peng Huang
  • Tianxiang Wang

Abstract

We study the profitability of optimal mean reversion trading strategies in the US equity market. Different from regular pair trading practice, we apply maximum likelihood method to construct the optimal static pairs trading portfolio that best fits the Ornstein-Uhlenbeck process, and rigorously estimate the parameters. Therefore, we ensure that our portfolios match the mean-reverting process before trading. We then generate contrarian trading signals using the model parameters. We also optimize the thresholds and the length of in-sample period by multiple tests. In nine good pair examples, we can see that our pairs exhibit high Sharpe ratio (above 1.9) over the in-sample period and out-of-sample period. In particular, Crown Castle International Corp. (CCI) and HCP, Inc. (HCP) achieve a Sharpe ratio of 2.326 during in-sample period and a Sharpe ratio of 2.425 in out-of-sample test. Crown Castle International Corp. (CCI) and Realty Income Corporation (O) achieve a Sharpe ratio of 2.405 and 2.903 respectively during in-sample period and out-of-sample period.

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  • Peng Huang & Tianxiang Wang, 2016. "On the Profitability of Optimal Mean Reversion Trading Strategies," Papers 1602.05858, arXiv.org.
    • Handle: RePEc:arx:papers:1602.05858
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    References listed on IDEAS

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    1. Tim Leung & Xin Li, 2016. "Optimal Mean Reversion Trading:Mathematical Analysis and Practical Applications," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 9839, August.
    2. Tim Leung & Xin Li & Zheng Wang, 2015. "Optimal Multiple Trading Times Under the Exponential OU Model with Transaction Costs," Papers 1504.04682, arXiv.org.
    3. Evan Gatev & William N. Goetzmann & K. Geert Rouwenhorst, 2006. "Pairs Trading: Performance of a Relative-Value Arbitrage Rule," The Review of Financial Studies, Society for Financial Studies, vol. 19(3), pages 797-827.
    4. Tim Leung & Xin Li, 2015. "Optimal Mean Reversion Trading With Transaction Costs And Stop-Loss Exit," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 18(03), pages 1-31.
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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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