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Pair Trading Rule with Switching Regression GARCH Model

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Integrated Uncertainty in Knowledge Modelling and Decision Making (IUKM 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9978))

Abstract

Pairs trading strategy is a famous strategy and commonly taken by many investors. There are various approaches to define the pairs trading signal which is the important part of the strategy. This study aims to propose an alternative approach, Markov Switching Regression GARCH model, to specify the trading signal for stock pair taking into account the structural change in the pair return. We applied our proposed model to the Stock Exchange of Thailand and the result shows our pairs trading strategy is relatively more effective for financial investment management compared with the single mean return from individual stock method.

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Authors and Affiliations

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

    Kongliang Zhu, Woraphon Yamaka & Songsak Sriboonchitta

Authors
  1. Kongliang Zhu
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  2. Woraphon Yamaka
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  3. Songsak Sriboonchitta
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Corresponding author

Correspondence to Kongliang Zhu .

Editor information

Editors and Affiliations

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

    Van-Nam Huynh

  2. Graduate School of Engineering Science, Osaka University, Toyonaka, Osaka, Japan

    Masahiro Inuiguchi

  3. University of Science, Ho Chi Minh City, Vietnam

    Bac Le

  4. Duy Tan University, Da Nang, Vietnam

    Bao Nguyen Le

  5. Université de Technologie de Compiègne , Compiègne, France

    Thierry Denoeux

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Zhu, K., Yamaka, W., Sriboonchitta, S. (2016). Pair Trading Rule with Switching Regression GARCH Model. In: Huynh, VN., Inuiguchi, M., Le, B., Le, B., Denoeux, T. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2016. Lecture Notes in Computer Science(), vol 9978. Springer, Cham. https://doi.org/10.1007/978-3-319-49046-5_50

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  • DOI: https://doi.org/10.1007/978-3-319-49046-5_50

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49045-8

  • Online ISBN: 978-3-319-49046-5

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