Robust Performances Hypothesis Testing With the Variance
Year: 2011
Type: article
Abstract: Applied researchers often test for the difference of the variance of two investment strategies; in particular, when the investment strategies under consideration aim to implement the global minimum variance portfolio. A popular tool to this end is the F-test for the equality of variances. Unfortunately, this test is not valid when the returns are correlated, have tails heavier than the normal distribution, or are of time series nature. Instead, we propose the use of robust inference methods. In particular, we suggest constructing a studentized time series bootstrap confidence interval for the ratio of the two variances and declaring the two variances different if the value one is not contained in the obtained interval. This approach has the advantage that one can simply resample from the observed data as opposed to some null-restricted data. A simulation study demonstrates the improved finite-sample performance compared to existing methods. Copyright © 2011 Wilmott Magazine Ltd.
Source: Wilmott
DOI: 10.1002/wilm.10036
Authors: Olivier Ledoit, Michael Wolf
Institution: University of Zurich
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2021614726