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Analysis of Exchange Rate Fluctuations in Japan and Thailand by Using Copula-Based Seemingly Unrelated Regression Model

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Integrated Uncertainty in Knowledge Modelling and Decision Making (IUKM 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14375))

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Abstract

The purpose of this paper is to analyze the factors that affect exchange rate fluctuations and provide help for investors to make investment decisions in the face of uncertainty in the exchange rate market. Comparing with the Conventional SUR model, the Student-t copula SUR is applied in this study. The results show that the interest rate is negative related to the fluctuation of exchange rate for both Thailand and Japan. And the exchange rate of both countries is positively influenced by inflation rate. The empirical result also shows that the current account balance is considered weak evidence affecting the change of exchange rate. And the Market speculation is decisively affecting the fluctuation of exchange rate, while it is negatively affecting for Thailand but positively affecting for Japan.

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Authors and Affiliations

  1. The Faculty of Business Administration and Accountancy, Khon Kaen University, Khon Kaen, Thailand

    Kongliang Zhu & Pensri Jaroenwanit

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

    Xuefeng Zhang

Authors
  1. Kongliang Zhu
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  2. Xuefeng Zhang
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  3. Pensri Jaroenwanit
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Corresponding author

Correspondence to Xuefeng Zhang .

Editor information

Editors and Affiliations

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

    Van-Nam Huynh

  2. Vietnam National University, Ho Chi Minh City, Vietnam

    Bac Le

  3. Osaka Metropolitan University, Sakai, Osaka, Japan

    Katsuhiro Honda

  4. Osaka University, Toyonaka, Osaka, Japan

    Masahiro Inuiguchi

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

    Youji Kohda

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Zhu, K., Zhang, X., Jaroenwanit, P. (2023). Analysis of Exchange Rate Fluctuations in Japan and Thailand by Using Copula-Based Seemingly Unrelated Regression Model. In: Huynh, VN., Le, B., Honda, K., Inuiguchi, M., Kohda, Y. (eds) Integrated Uncertainty in Knowledge Modelling and Decision Making. IUKM 2023. Lecture Notes in Computer Science(), vol 14375. Springer, Cham. https://doi.org/10.1007/978-3-031-46775-2_21

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  • DOI: https://doi.org/10.1007/978-3-031-46775-2_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-46774-5

  • Online ISBN: 978-3-031-46775-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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