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Estimates of the likelihood of extreme returns in international stock markets

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  • Jon Vilasuso
  • David Katz

Abstract

This study applies extreme-value theory to daily international stock-market returns to determine (1) whether or not returns follow a heavy-tailed stable distribution, (2) the likelihood of an extreme return, such as a 20% drop in a single day, and (3) whether or not the likelihood of an extreme event has changed since October 1987. Empirical results reject a heavy-tailed stable distribution for returns. Instead, a Student-t distribution or an autoregressive conditional heteroscedastic process is better able to capture the salient features of returns. We find that the likelihood of a large single-day return diff ers widely across markets and, for the G-7 countries, the 1987 stock-market drop appears to be largely an isolated event. A drop of this magnitude, however, is not rare in the case of Hong Kong. Finally, there is only limited evidence that the chance of a large single-day decline is more likely since the October 1987 market drop; however, exceptions include stock markets in Germany, The Netherlands and the UK.

Suggested Citation

  • Jon Vilasuso & David Katz, 2000. "Estimates of the likelihood of extreme returns in international stock markets," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(1), pages 119-130.
    • Handle: RePEc:taf:japsta:v:27:y:2000:i:1:p:119-130
    DOI: 10.1080/02664760021880
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    Cited by:

    1. Małgorzata Just & Krzysztof Echaust, 2021. "An Optimal Tail Selection in Risk Measurement," Risks, MDPI, vol. 9(4), pages 1-16, April.
    2. Marco Rocco, 2011. "Extreme value theory for finance: a survey," Questioni di Economia e Finanza (Occasional Papers) 99, Bank of Italy, Economic Research and International Relations Area.
    3. Bertrand Groslambert & Wan-Ni Lai, 2020. "Ranking tail risk across international stock markets," Economics Bulletin, AccessEcon, vol. 40(2), pages 1756-1768.
    4. Zheng, Yixing & Ramsey, Austin F., 2022. "Extreme Correlation Between Daily Basis Returns of Local Corn Markets in North Carolina," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322373, Agricultural and Applied Economics Association.

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