Robust Performance Hypothesis Testing with theVariance

Applied researchers often test for the difference of the variance of two investment strategies;in particular, when the investment strategies under consideration aim to implementthe global minimum variance portfolio. A popular tool to this end is the F-test for theequality 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, wepropose the use of robust inference methods. In particular, we suggest to construct a studentizedtime series bootstrap confidence interval for the ratio of the two variances and todeclare 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 dataas opposed to some null-restricted data. A simulation study demonstrates the improvedfinite-sample performance compared to existing methods.[...]