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Extreme Dependence In The Nasdaq And S&P Composite Indexes

  • John G. Galbraith

    ()

  • Serguei Zernov

    ()

Dependence among large observations in equity markets is usually examined using second-moment models such as those from the GARCH or SV classes. Such models treat the entire set of returns, and tend to produce very similar estimates on the major equity markets, with a sum of estimated GARCH parameters, for example, slightly below one. Using dependence measures from extreme value theory, however, it is possible to characterie dependence among only the largest (or largest negative) financial returns; these alternative characterizations of clustering have important applications in risk management. In this paper we compare the NASDAQ and degree of extreme dependence. Although GARCH-type characterizations of second-moment dependence in the two markets produce similar results, the same is not true in the extremes: we find significantly more extreme dependence in the NASDAQ returns. More generally, the study of extreme dependence may reveal contrasts which are obscured when examining the conditional second moment.

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Paper provided by McGill University, Department of Economics in its series Departmental Working Papers with number 2006-14.

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Length: 23 pages
Date of creation: Sep 2006
Date of revision:
Handle: RePEc:mcl:mclwop:2006-14
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  9. John W. Galbraith, 2004. "Circuit Breakers and the Tail Index of Equity Returns," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 2(1), pages 109-129.
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  16. Phillip Kearns & Adrian Pagan, 1997. "Estimating The Density Tail Index For Financial Time Series," The Review of Economics and Statistics, MIT Press, vol. 79(2), pages 171-175, May.
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