Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/80796
Authors: 
Gungor, Sermin
Luger, Richard
Year of Publication: 
2013
Series/Report no.: 
Bank of Canada Working Paper 2013-16
Abstract: 
We develop a finite-sample procedure to test for mean-variance efficiency and spanning without imposing any parametric assumptions on the distribution of model disturbances. In so doing, we provide an exact distribution-free method to test uniform linear restrictions in multivariate linear regression models. The framework allows for unknown forms of non-normalities, and time-varying conditional variances and covariances among the model disturbances. We derive exact bounds on the null distribution of joint F statistics in order to deal with the presence of nuisance parameters, and we show how to implement the resulting generalized non-parametric bounds tests with Monte Carlo resampling techniques. In sharp contrast to the usual tests that are not computable when the number of test assets is too large, the power of the new test procedure potentially increases along both the time and cross-sectional dimensions.
Subjects: 
Econometric and statistical methods
Asset pricing
Financial markets
JEL: 
C12
C15
C33
G11
G12
Document Type: 
Working Paper

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