EXTREME DEPENDENCE IN THE NASDAQ AND S&P COMPOSITE INDEXES

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.