Previous studies in international finance have shown that correlation of international equity returns increases during volatile periods. However, correlation should be used with great care. For example, assuming a multivariate normal distribution with constant correlation, conditional correlation during volatile periods (large absolute returns) is higher than conditional correlation during tranquil periods (small absolute returns) even though the correlation of all returns remains constant. In order to test whether 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 correlation conditional to large returns and study the dependence structure of international equity markets during extremely volatile bear and bull periods. We use "extreme value theory" to model the multivariate distribution of large returns. This theory allows one to specify the distribution of correlation conditional to large negative or positive returns under the null hypothesis of multivariate normality with 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 return 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. (1999). Correlation of International Equity Markets during Extremely Volatile Periods. In: Actes de la Conférence de l'AFFI. Université d'Aix-en-Provence, pp. 1-26.