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Optimal pair-trading strategy over long/short/square positions—empirical study

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  • Kiyoshi Suzuki

Abstract

Suzuki [Automatica, 2016, 67, 33–45] solves the optimal, finitely iterative, three-regime switching problem for investing in a mean-reverting asset that follows an Ornstein–Uhlenbeck price process and find explicit solutions. The remarkable feature of this model is that the investor can explicitly take either a long, short or square position and can switch the position, with transaction costs, during the investment period. We run empirical simulations of such multiple-regime switching models. There are very few such attempts in the existing literature because it is difficult to find, first, an explicit solution to the problem and second, appropriate financial assets that follow the artificial stochastic process required by the mathematical model. According to the Monte Carlo simulations of the optimal pair-trading strategy, the mean daily Sharp ratio is more than 2.3, whereas the mean Sharp ratio for the historical simulation of the ‘stub’ pairs (combinations of parent/subsidiary companies) is 0.6886. We believe that the results obtained from performing the empirical simulations are remarkable and consider that the optimal switching strategy of the rigorous mathematical model is applicable to businesses in the real world. For the reference many pseudo-program codes are added, which can help to replicate the optimal trading strategies.

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  • Kiyoshi Suzuki, 2018. "Optimal pair-trading strategy over long/short/square positions—empirical study," Quantitative Finance, Taylor & Francis Journals, vol. 18(1), pages 97-119, January.
  • Handle: RePEc:taf:quantf:v:18:y:2018:i:1:p:97-119
    DOI: 10.1080/14697688.2017.1346277
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    References listed on IDEAS

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    Cited by:

    1. Kiyoshi Suzuki, 2021. "Infinite-Horizon Optimal Switching Regions for a Pair-Trading Strategy with Quadratic Risk Aversion Considering Simultaneous Multiple Switchings: A Viscosity Solution Approach," Mathematics of Operations Research, INFORMS, vol. 46(1), pages 336-360, February.
    2. Yaoyuan Zhang & Dewen Xiong, 2023. "Optimal Strategy of the Dynamic Mean-Variance Problem for Pairs Trading under a Fast Mean-Reverting Stochastic Volatility Model," Mathematics, MDPI, vol. 11(9), pages 1-19, May.
    3. Alexander Lipton & Marcos Lopez de Prado, 2020. "A closed-form solution for optimal mean-reverting trading strategies," Papers 2003.10502, arXiv.org.
    4. Gurdal Ertek & Aysha Al-Kaabi & Aktham Issa Maghyereh, 2022. "Analytical Modeling and Empirical Analysis of Binary Options Strategies," Future Internet, MDPI, vol. 14(7), pages 1-23, July.
    5. Weiguang Han & Jimin Huang & Qianqian Xie & Boyi Zhang & Yanzhao Lai & Min Peng, 2023. "Mastering Pair Trading with Risk-Aware Recurrent Reinforcement Learning," Papers 2304.00364, arXiv.org.

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