Increased Correlation in Bear Markets

Posted: 22 Mar 2002

See all articles by Kees C. G. Koedijk

Kees C. G. Koedijk

Tilburg University - Department of Finance

Rachel A.J. Pownall

Tilburg University - Department of Finance; Maastricht University - Department of Finance

Paul Kofman

The University of Melbourne

Abstract

A number of studies have provided evidence of increased correlations in global financial market returns during bear markets. Other studies, however, have shown that some of this evidence may be biased. We derive an alternative to previous estimators for implied correlation that is based on measures of portfolio downside risk and that does not suffer from bias. The unbiased quantile correlation estimates are directly applicable to portfolio optimization and to risk management techniques in general. This simple and practical method captures the increasing correlation in extreme market conditions while providing a pragmatic approach to understanding correlation structure in multivariate return distributions. Based on data for international equity markets, we found evidence of significant increased correlation in international equity returns in bear markets. This finding proves the importance of providing a tail-adjusted mean-variance covariance matrix.

Suggested Citation

Koedijk, Kees G. and Pownall, Rachel Ann Jane and Kofman, Paul, Increased Correlation in Bear Markets. Financial Analysts Journal, Vol. 58, No. 1. Available at SSRN: https://ssrn.com/abstract=301315

Kees G. Koedijk (Contact Author)

Tilburg University - Department of Finance ( email )

P.O. Box 90153
Tilburg, 5000 LE
Netherlands
+31 13 4663048 (Phone)
+31 13 4662052 (Fax)

Rachel Ann Jane Pownall

Tilburg University - Department of Finance ( email )

P.O. Box 90153
Tilburg, 5000 LE
Netherlands

Maastricht University - Department of Finance ( email )

Maastricht, 6200 MD
Netherlands

Paul Kofman

The University of Melbourne ( email )

Faculty of Economics and Commerce
Department of Finance
Parkville, Victoria 3010
Australia
61 3 8344 3794 (Phone)

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