Résumés
Abstract
We propose double bootstrap methods to test the mean-variance efficiency hypothesis when multiple portfolio groupings of the test assets are considered jointly rather than individually. A direct test of the joint null hypothesis may not be possible with standard methods when the total number of test assets grows large relative to the number of available time-series observations, since the estimate of the disturbance covariance matrix eventually becomes singular. The suggested residual bootstrap procedures based on combining the individual group p-values avoid this problem while controlling the overall significance level. Simulation and empirical results illustrate the usefulness of the joint mean-variance efficiency tests.
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Parties annexes
Acknowledgements
We would like to thank Ian Christensen, Antonio Diez de los Rios, Jonathan Witmer, Bo Young Chang, and seminar participants at the Bank of Canada for helpful comments and useful conversations. All remaining errors and omissions are our own.
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