Correlation Structure of International Equity Markets During Extremely Volatile Periods

Recent 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 over time. 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 on 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 on 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 returns is not inconsistent with multivariate normality, while the correlation of large negative returns is much greater than expected.

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