Should Stock Market Indexes Time Varying Correlations Be Taken Into Account? A Conditional Variance Multivariate Approach

The episodes of stock market crises in Europe and the U.S.A. since the year 2000, and the fragility of the international stock markets, have sparked the interest of researchers in understanding and in modeling the markets’ rising volatilities in order to prevent against crises. Portfolio managers typically rely on estimates of correlations between returns on the financial instruments in the portfolio and on the volatility of those returns. This task is relatively simple if the correlations and volatilities do not change over time. But in reality both volatility and stock market indexes’ correlations do change over time. In this paper we examine the major stock market indexes’ rising volatilities, and we show that time varying correlations should be taken into account when modeling those indexes. We find that all of the indexes that we examine exhibit relatively time varying correlations with the other indexes and we find a strong GARCH effect in all of the examined series