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Time-Varying Comovement of Foreign Exchange Markets: A GLS-Based Time-Varying Model Approach

Author

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  • Mikio Ito

    (Faculty of Economics, Keio University, 2-15-45 Mita, Minato-ku, Tokyo 108-8345, Japan)

  • Akihiko Noda

    (School of Commerce, Meiji University, 1-1 Kanda-Surugadai, Chiyoda-ku, Tokyo 101-8301, Japan
    Keio Economic Observatory, Keio University, 2-15-45 Mita, Minato-ku, Tokyo 108-8345, Japan)

  • Tatsuma Wada

    (Faculty of Policy Management, Keio University, 5322 Endo, Fujisawa, Kanagawa 252-0882, Japan)

Abstract

How strongly are foreign exchange markets linked in terms of their similarities in long-run fluctuations? Are they cointegrating? To analyze such “comovements,” we present a time-varying cointegration model for the foreign exchange rates of the currencies of Canada, Japan, and the UK vis-à-vis the U.S. dollar from May 1990 through July 2015. Unlike previous studies, we allow the loading matrix in the vector error-correction (VEC) model to be varying over time. Because the loading matrix in the VEC model is associated with the speed at which deviations from the long-run relationship disappear, we propose a new degree of market comovement based on the time-varying loading matrix to measure the strength or robustness of the long-run relationship over time. Since exchange rates are determined by macrovariables, cointegration among exchange rates implies these variables share common stochastic trends. Therefore, the proposed degree measures the degree of market comovement. Our main finding is that the market comovement has become stronger over the past quarter-century, but at a decreasing rate with two major turning points: one in 1995 and the other one in 2008.

Suggested Citation

  • Mikio Ito & Akihiko Noda & Tatsuma Wada, 2021. "Time-Varying Comovement of Foreign Exchange Markets: A GLS-Based Time-Varying Model Approach," Mathematics, MDPI, vol. 9(8), pages 1-13, April.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:8:p:849-:d:535162
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    References listed on IDEAS

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    1. Mikio Ito, 2022. "Detecting Structural Breaks in Foreign Exchange Markets by using the group LASSO technique," Papers 2202.02988, arXiv.org.

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