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Pairs Trading via Nonlinear Autoregressive GARCH Models

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Integrated Uncertainty in Knowledge Modelling and Decision Making (IUKM 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10758))

Abstract

Pairs trading is a well-established speculative investment strategy in financial markets. However, the presence of extreme structural change in economy and financial markets might cause simple pairs trading signals to be wrong. To overcome this problem in detecting the buy/sell signals, we propose the use of three non-linear models consisting of Kink, Threshold and Markov Switching models. We would like to model the return spread of potential stock pairs by these three models with GARCH effects and the upper and lower regimes in each model are used to find the trading entry and exit signals. We also identify the best fit nonlinear model using the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). An application to the Dow Jones Industrial Average (DJIA), New York Stock Exchange (NYSE), and NASDAQ stock markets are presented and the results show that Markov Switching model with GARCH effects can perform better than other models. Finally, the empirical results suggest that the regime-switching rule for pairs trading generates positive returns and so it offers an interesting analytical alternative to traditional pairs trading rules.

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Author information

Authors and Affiliations

  1. Faculty of Economics, Ramkhamhaeng University, Bangkok, Thailand

    Benchawanaree Chodchuangnirun

  2. Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand

    Kongliang Zhu & Woraphon Yamaka

  3. Center of Excellence in Econometrics, Chiang Mai University, Chiang Mai, Thailand

    Woraphon Yamaka

Authors
  1. Benchawanaree Chodchuangnirun
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  2. Kongliang Zhu
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  3. Woraphon Yamaka
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Corresponding author

Correspondence to Kongliang Zhu .

Editor information

Editors and Affiliations

  1. Japan Advanced Institute of Science and Technology, Nomi, Japan

    Van-Nam Huynh

  2. Osaka University, Osaka, Japan

    Masahiro Inuiguchi

  3. Hanoi National University of Education, Hanoi, Vietnam

    Dang Hung Tran

  4. Université de Technologie de Compiègne, Compiègne, France

    Thierry Denoeux

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Chodchuangnirun, B., Zhu, K., Yamaka, W. (2018). Pairs Trading via Nonlinear Autoregressive GARCH Models. In: Huynh, VN., Inuiguchi, M., Tran, D., Denoeux, T. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2018. Lecture Notes in Computer Science(), vol 10758. Springer, Cham. https://doi.org/10.1007/978-3-319-75429-1_23

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  • DOI: https://doi.org/10.1007/978-3-319-75429-1_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-75428-4

  • Online ISBN: 978-3-319-75429-1

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