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International stock market efficiency: a non-Bayesian time-varying model approach

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  • Mikio Ito
  • Akihiko Noda
  • Tatsuma Wada

Abstract

This article develops a non-Bayesian methodology to analyse the time-varying structure of international linkages and market efficiency in G7 countries. We consider a non-Bayesian time-varying vector autoregressive (TV-VAR) model, and apply it to estimate the joint degree of market efficiency in the sense of Fama (1970, 1991). Our empirical results provide a new perspective that the international linkages and market efficiency change over time and that their behaviours correspond well to historical events of the international financial system.

Suggested Citation

  • Mikio Ito & Akihiko Noda & Tatsuma Wada, 2014. "International stock market efficiency: a non-Bayesian time-varying model approach," Applied Economics, Taylor & Francis Journals, vol. 46(23), pages 2744-2754, August.
  • Handle: RePEc:taf:applec:v:46:y:2014:i:23:p:2744-2754
    DOI: 10.1080/00036846.2014.909579
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    References listed on IDEAS

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    1. Yoshiro Tsutsui & Kenjiro Hirayama, 2004. "Appropriate lag specification for daily responses of international stock markets," Applied Financial Economics, Taylor & Francis Journals, vol. 14(14), pages 1017-1025.
    2. Jeon, Bang Nam & Chiang, Thomas C., 1991. "A system of stock prices in world stock exchanges: Common stochastic trends for 1975-1990," Journal of Economics and Business, Elsevier, vol. 43(4), pages 329-338, November.
    3. Toda, Hiro Y. & Yamamoto, Taku, 1995. "Statistical inference in vector autoregressions with possibly integrated processes," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 225-250.
    4. Bénédicte Vidaillet & V. D'Estaintot & P. Abécassis, 2005. "Introduction," Post-Print hal-00287137, HAL.
    5. Corhay, A. & Tourani Rad, A. & Urbain, J. -P., 1993. "Common stochastic trends in European stock markets," Economics Letters, Elsevier, vol. 42(4), pages 385-390.
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    Cited by:

    1. João Paulo Vieito & Wing-Keung Wong & Zhen-Zhen Zhu, 2016. "Could the global financial crisis improve the performance of the G7 stocks markets?," Applied Economics, Taylor & Francis Journals, vol. 48(12), pages 1066-1080, March.
    2. Achal Awasthi & Oleg Malafeyev, 2015. "Is the Indian Stock Market efficient - A comprehensive study of Bombay Stock Exchange Indices," Papers 1510.03704, arXiv.org.
    3. Rahman, Md. Lutfur & Lee, Doowon & Shamsuddin, Abul, 2017. "Time-varying return predictability in South Asian equity markets," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 179-200.
    4. Noda, Akihiko, 2016. "A test of the adaptive market hypothesis using a time-varying AR model in Japan," Finance Research Letters, Elsevier, vol. 17(C), pages 66-71.
    5. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2017. "An Alternative Estimation Method of a Time-Varying Parameter Model," Papers 1707.06837, arXiv.org, revised Dec 2017.
    6. Mikio Ito & Akihiko Noda & Tatsuma Wada, 2016. "Time-Varying Comovement of Foreign Exchange Markets," Papers 1610.04334, arXiv.org.
    7. Lanouar Charfeddine & Karim Ben Khediri & Goodness C. Aye & Rangan Gupta, 2017. "Time-Varying Efficiency of Developed and Emerging Bond Markets: Evidence from Long-Spans of Historical Data," Working Papers 201771, University of Pretoria, Department of Economics.

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