Evaluating changes in correlations during periods of high market volatility

In computing measures of the market risk of a portfolio, such as Value at Risk, 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, and if there are sufficient data to allow them to be estimated fairly precisely. The task is vastly more difficult if the correlations change abruptly as a result of structural breaks in the mechanisms that determine asset returns – perhaps owing to the impact of contagion on the links between markets, changes in the sources of shocks, or new market structures or practices. However, changes in correlation patterns may be no more than the natural and predictable effects of fluctuations in asset return volatility. In such cases, the problem facing risk managers should be less difficult, as the empirical challenge then consists of modelling the time-varying nature of asset return volatilities. In periods of heightened market volatility, correlations between returns on financial assets tend to increase relative to correlations estimated during periods of normal volatility. For example, the average correlation between yield spreads for selected fixed income securities rose to 0.37 following the Russian crisis in August 1998 from 0.11 in the first half of 1998 (Committee on the Global Financial System (1999), Table A18). The increased correlation of returns during periods of high volatility is often explained as resulting from changes in the underlying relationships that determine returns.13 Yet, probability theory shows that correlations between asset returns depend on market volatility even if the underlying relationships between returns have not changed; variations in correlations measured over different periods of time may merely be the consequence of variations in realised volatility.