Previous studies in international finance have shown that the correlation of international equity returns increases during volatile periods. However, correlation should be used with great care. For example, assuming that we consider a multivariate normal distribution with a constant correlation, the conditional correlation during volatile periods (large absolute returns) is higher than the conditional correlation during tranquil periods (small absolute returns) even though the correlation of all returns remains constant. In order to test whether the correlation increases during volatile periods, the distribution of the conditional correlation under the null hypothesis must then be clearly specified. In this paper we focus on the conditional correlation to large returns and study the dependence structure of international equity markets during extremely volatile bear and bull periods. We use the "extreme value theory" to model the multivariate distribution of large returns. This theory allows one to specify the distribution of the conditional correlation to large negative or positive returns under the null hypothesis of multivariate normality with a constant correlation. Empirically, using monthly data from January 1959 to December 1996 for the five largest stock markets, we find that the correlation of large positive returns is not inconsistent with the assumption of multivariate normality while the correlation of large negative returns is much greater than expected under the assumption of multivariate normality.
LONGIN, F. and SOLNIK, B. (2000). Extreme Correlation of International Equity Market.