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The Tail Behavior of Stock Returns: Emerging versus Mature Markets

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  • ROCKINGER, Michael
  • JONDEAU, Eric

    (Banque de France, Centre de recherche)

Abstract

For Central Banks, institutional, and individual investors it is crucial to understand the frequency and importance of drops or sudden rises in financial markets. Extreme value theory (evt) is an interesting tool providing answers to questions such as: -with what frequency do we find variations of returns beyond a given threshold ? -over a given period, what type of extreme variation can be expected? - with what type of unconditional distribution of returns are the tails of returns compatible? -in a cross country setting of emerging and mature financial markets do extreme variations behave in a similar manner? - can we learn about the evolution of returns of presently developing economies from the early returns of presently mature markets? - do countries behave similarly in terms of up or down crashes for a given level of development? In the following paper we start with a review of theoretical elements of evt. In the empirical section of this study we consider five mature markets, nine Asian, six Eastern European, and seven Latin American emerging markets. The tail-behavior of returns is found to be compatible with the existence of up to the third moment but not beyond. The estimation of the tail distribution as a Generalized Pareto Distribution shows that great care has to be taken for emerging markets where little data is available and returns' distribution is subjet to violate the iid assumption. Using a subsample of countries we demonstrate the limitations of evt. We also show that little can be learned from 19th century US data about presently emerging markets' tail behavior.

Suggested Citation

  • ROCKINGER, Michael & JONDEAU, Eric, 1999. "The Tail Behavior of Stock Returns: Emerging versus Mature Markets," HEC Research Papers Series 668, HEC Paris.
  • Handle: RePEc:ebg:heccah:0668
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    Cited by:

    1. Allen, David E. & Singh, Abhay K. & Powell, Robert J., 2013. "EVT and tail-risk modelling: Evidence from market indices and volatility series," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 355-369.
    2. Singh, Abhay K. & Allen, David E. & Robert, Powell J., 2013. "Extreme market risk and extreme value theory," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 310-328.
    3. Jorge A. Chan-Lau & Donald J. Mathieson & James Y. Yao, 2004. "Extreme Contagion in Equity Markets," IMF Staff Papers, Palgrave Macmillan, vol. 51(2), pages 1-8.
    4. Timotheos Angelidis & Alexandros Benos & Stavros Degiannakis, 2007. "A robust VaR model under different time periods and weighting schemes," Review of Quantitative Finance and Accounting, Springer, vol. 28(2), pages 187-201, February.
    5. Abhay K. Singh & David E. Allen & Robert J. Powell, 2017. "Tail dependence analysis of stock markets using extreme value theory," Applied Economics, Taylor & Francis Journals, vol. 49(45), pages 4588-4599, September.
    6. Timotheos Angelidis & Alexandros Benos, 2008. "Value-at-Risk for Greek Stocks," Multinational Finance Journal, Multinational Finance Journal, vol. 12(1-2), pages 67-104, March-Jun.
    7. Bi, Guang & Giles, David E., 2009. "Modelling the financial risk associated with U.S. movie box office earnings," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(9), pages 2759-2766.
    8. Gu, Zhiye & Ibragimov, Rustam, 2018. "The “Cubic Law of the Stock Returns” in emerging markets," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 182-190.
    9. Faias, José Afonso, 2023. "Predicting the equity risk premium using the smooth cross-sectional tail risk: The importance of correlation," Journal of Financial Markets, Elsevier, vol. 63(C).
    10. Kaizoji, Taisei & Leiss, Matthias & Saichev, Alexander & Sornette, Didier, 2015. "Super-exponential endogenous bubbles in an equilibrium model of fundamentalist and chartist traders," Journal of Economic Behavior & Organization, Elsevier, vol. 112(C), pages 289-310.
    11. Niklas Wagner & Terry Marsh, 2004. "Tail index estimation in small smaples Simulation results for independent and ARCH-type financial return models," Statistical Papers, Springer, vol. 45(4), pages 545-561, October.
    12. Pontines, Victor & Siregar, Reza, 2007. "The Yen, the US dollar, and the trade weighted basket of currencies: Does the choice of anchor currencies matter in identifying incidences of speculative attacks?," Japan and the World Economy, Elsevier, vol. 19(2), pages 214-235, March.
    13. Lux, Thomas, 2008. "Stochastic behavioral asset pricing models and the stylized facts," Economics Working Papers 2008-08, Christian-Albrechts-University of Kiel, Department of Economics.
    14. Wagner, Niklas & Marsh, Terry A., 2005. "Measuring tail thickness under GARCH and an application to extreme exchange rate changes," Journal of Empirical Finance, Elsevier, vol. 12(1), pages 165-185, January.
    15. Sornette, Didier, 2001. "Fokker–Planck equation of distributions of financial returns and power laws," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 290(1), pages 211-217.
    16. Evis Këllezi & Manfred Gilli, 2000. "Extreme Value Theory for Tail-Related Risk Measures," FAME Research Paper Series rp18, International Center for Financial Asset Management and Engineering.
    17. Manfred Gilli & Evis këllezi, 2006. "An Application of Extreme Value Theory for Measuring Financial Risk," Computational Economics, Springer;Society for Computational Economics, vol. 27(2), pages 207-228, May.
    18. Heng-Chih Chou & David K. Wang, 2014. "Estimation of tail-related value-at-risk measures: range-based extreme value approach," Quantitative Finance, Taylor & Francis Journals, vol. 14(2), pages 293-304, February.

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    More about this item

    Keywords

    extreme value theory; generalized Pareto distribution; stock market returns;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • O16 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Financial Markets; Saving and Capital Investment; Corporate Finance and Governance

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