Keywords
risk management, risk measurement, hedging, derivatives, correlation, conditional cor- relation, normal distribution, foreign exchange
Abstract
Correlations are crucial for pricing and hedging derivatives whose payoff depends on more than one asset. Typically, correlations computed separately for ordinary and stressful market conditions differ considerably, a pattern widely termed "correlation breakdown." As a result, risk managers worry that their hedges will be useless when they are most needed, namely during "stressful" market situations. We show that such worries may not be justified since "correlation breakdowns" can easily be generated by data whose distribution is stationary and, in particular, whose correlation coefficient is constant. We make this point analytically, by way of several numerical examples, and via an empirical illustration. But, risk managers should not necessarily relax. Although "correlation breakdown" can be an artifact of poor data analysis, other evidence suggests that correlations do in fact change over time.
Original Publication Citation
Pitfalls in Tests for Changing Correlations (with Michael Gibson and Mico Loretan), 1997, Board of Governors of the Federal Reserve System International Finance Discussion Papers, 597.
BYU ScholarsArchive Citation
Boyer, Brian H.; Gibson, Michael S.; and Loretan, Mico, "Pitfalls in Tests for Changes in Correlations" (1997). Faculty Publications. 8932.
https://scholarsarchive.byu.edu/facpub/8932
Document Type
Peer-Reviewed Article
Publication Date
1997
Publisher
Board of Governors of the Federal Reserve System International Finance Discussion Papers
Language
English
College
Marriott School of Business
Department
Finance
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