Bootstrap Tests of Mean-Variance Efficiency with Multiple Portfolio Groupings

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Bank of Canada Working Paper ; No. 2014-51

Classification and Topics

• Classification: Wirtschaft ; Hypothesis Testing: General ; Semiparametric and Nonparametric Methods: General ; Statistical Simulation Methods: General ; Asset Pricing; Trading Volume; Bond Interest Rates
• Subject: Econometric and statistical methods ; Asset pricing ; Financial markets

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Gungor, Sermin ; Luger, Richard
• Event: Veröffentlichung
• (who): Bank of Canada
• (where): Ottawa
• (when): 2014

Further information

• DOI: doi:10.34989/swp-2014-51
• Handle: http://hdl.handle.net/10419/123746
• Last update: 10.03.2025, 11:44 AM CET