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The Great East Japan Earthquake and Stock Prices

Author

Listed:
  • Jacques Jaussaud

    (University of Pau et Pays de l''Adour)

  • Sophie Nivoix

    (University of poitiers, France)

  • Serge Rey

    (CATT-UNIV PAU & PAYS ADOUR)

Abstract

The Great East Japan Earthquake of March 11, 2011, which led to a massive tsunami and the nuclear accident at Fukushima, moved Japanese authorities to close most of the country's nuclear reactors for inspection (only 2 of 54 total currently are working), as well as to reassess its national energy policy. This article investigates the volatility of stock prices before and after the disaster. The evolution of stock prices of electric utility companies differs greatly, compared with those of firms in other industries.

Suggested Citation

  • Jacques Jaussaud & Sophie Nivoix & Serge Rey, 2015. "The Great East Japan Earthquake and Stock Prices," Economics Bulletin, AccessEcon, vol. 35(2), pages 1237-1261.
  • Handle: RePEc:ebl:ecbull:eb-13-00844
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    References listed on IDEAS

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    1. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    2. Marcucci Juri, 2005. "Forecasting Stock Market Volatility with Regime-Switching GARCH Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(4), pages 1-55, December.
    3. Donald R. Davis & David E. Weinstein, 2008. "A Search For Multiple Equilibria In Urban Industrial Structure," Journal of Regional Science, Wiley Blackwell, vol. 48(1), pages 29-65, February.
    4. De Bondt, Werner F M & Thaler, Richard, 1985. "Does the Stock Market Overreact?," Journal of Finance, American Finance Association, vol. 40(3), pages 793-805, July.
    5. Peter Gordon & James E. Moore & Harry W. Richardson & Masanobu Shinozuka & Donghwan An & Sungbin Cho, 2004. "Earthquake Disaster Mitigation for Urban Transportation Systems: An Integrated Methodology that Builds on the Kobe and Northridge Experiences," Advances in Spatial Science, in: Yasuhide Okuyama & Stephanie E. Chang (ed.), Modeling Spatial and Economic Impacts of Disasters, chapter 11, pages 205-232, Springer.
    6. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    7. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    8. Rey, Clément & Rey, Serge & Viala, Jean-Renaud, 2014. "Detection of high and low states in stock market returns with MCMC method in a Markov switching model," Economic Modelling, Elsevier, vol. 41(C), pages 145-155.
    9. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    10. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    11. Franc Klaassen, 2002. "Improving GARCH volatility forecasts with regime-switching GARCH," Empirical Economics, Springer, vol. 27(2), pages 363-394.
    12. Pelletier, Denis, 2006. "Regime switching for dynamic correlations," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 445-473.
    13. Michael Wong, 1997. "Abnormal Stock Returns Following Large One-day Advances and Declines: Evidence from Asia-Pacific Markets," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 4(2), pages 171-177, May.
    14. Dueker, Michael J, 1997. "Markov Switching in GARCH Processes and Mean-Reverting Stock-Market Volatility," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 26-34, January.
    15. Robin L. Lumsdaine & David H. Papell, 1997. "Multiple Trend Breaks And The Unit-Root Hypothesis," The Review of Economics and Statistics, MIT Press, vol. 79(2), pages 212-218, May.
    16. Monica Billio & Massimiliano Caporin, 2005. "Multivariate Markov switching dynamic conditional correlation GARCH representations for contagion analysis," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 14(2), pages 145-161, November.
    17. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    18. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    19. Ziobrowski, Alan J. & Cheng, Ping & Boyd, James W. & Ziobrowski, Brigitte J., 2004. "Abnormal Returns from the Common Stock Investments of the U.S. Senate," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 39(4), pages 661-676, December.
    20. Donald R. Davis & David E. Weinstein, 2002. "Bones, Bombs, and Break Points: The Geography of Economic Activity," American Economic Review, American Economic Association, vol. 92(5), pages 1269-1289, December.
    21. De Bondt, Werner F M & Thaler, Richard H, 1987. "Further Evidence on Investor Overreaction and Stock Market Seasonalit y," Journal of Finance, American Finance Association, vol. 42(3), pages 557-581, July.
    22. Clément Rey & Serge Rey & Jean-Renaud Viala, 2014. "Detection of high and low states in stock market returns with MCMC method in a Markov switching model," Post-Print hal-01885287, HAL.
    23. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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    Cited by:

    1. Mohamed El Abdellaoui & Gilles Pache, 2019. "Effects of disruptive events within the supply chain on perceived logistics performance," Economics Bulletin, AccessEcon, vol. 39(1), pages 41-54.
    2. Harada, Kimie & Okimoto, Tatsuyoshi, 2021. "The BOJ's ETF purchases and its effects on Nikkei 225 stocks," International Review of Financial Analysis, Elsevier, vol. 77(C).
    3. Christian F. Durach & Tomas Repasky & Frank Wiengarten, 2023. "Patterns in firms’ inventories and flexibility levels after a low‐probability, high‐impact disruption event: Empirical evidence from the Great East Japan Earthquake," Production and Operations Management, Production and Operations Management Society, vol. 32(6), pages 1705-1723, June.

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    More about this item

    Keywords

    stock market; Japan; risk; volatility; earthquake; electric utility companies;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables

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