Large returns, conditional correlation and portfolio diversification: a value-at-risk approach

P. Silvapulle and Clive Granger

Quantitative Finance, 2001, vol. 1, issue 5, 542-551

Abstract: This paper, using daily returns on 30 Dow Jones Industrial stocks for the period 1991-1999, investigates the possibility of portfolio diversification when there are negative large movements in the stock returns (i.e. when the market is bearish). We estimate the quantiles of stock return distributions using non-parametric and parametric methods that are widely being used in measuring value-at-risk (VaR). We find that the average conditional correlation of 30 stocks is much higher when the large movements are negative than that when the market is 'usual'. Further, we find that, contrary to the results of previous studies, there is no notable difference between the average conditional correlations when the large movements are positive and when the market is 'usual'. Moreover, it is evident from the results of the conditional CAPM that the portfolio's diversifiable and non-diversifiable risks, as measured by the error variance of the CAPM and beta respectively, are highly unstable when the market is bearish than that when it is 'usual' or bullish. The overall results suggest that the possibility of portfolio diversification would be eroded when the stock market is bearish. These findings have implications for portfolio diversification and risk management in particular and for finance in general. The ideas presented in this paper can be utilized for testing contagion in the international financial markets, a much-researched topic in international finance.

Date: 2001
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DOI: 10.1080/713665877

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