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The Tail Behavior of Sotck Returns: Emerging Versus Mature Markets

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  • Jondeau, E.
  • Rockinger, M.

Abstract

In the following paper the authors start with a review of theoretical elements of extreme value theory (evt). In the empirical section of this study they 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. Using a subsample of countries they also demonstrate the limitations of evt. Finally they show that little can be learned from 19th century US data about presently emerging markets' tail behavior.

Suggested Citation

  • Jondeau, E. & Rockinger, M., 1999. "The Tail Behavior of Sotck Returns: Emerging Versus Mature Markets," Working papers 66, Banque de France.
  • Handle: RePEc:bfr:banfra:66
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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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