  We introduce a new framework for the mean-variance spanning (MVS) hypothesis
testing. The procedure can be applied to any test-asset dimension and only
requires stationary asset returns and the number of benchmark assets to be
smaller than the number of time periods. It involves individually testing
moment conditions using a robust Student-t statistic based on the batch-mean
method and combining the p-values using the Cauchy combination test.
Simulations demonstrate the superior performance of the test compared to
state-of-the-art approaches. For the empirical application, we look at the
problem of domestic versus international diversification in equities. We find
that the advantages of diversification are influenced by economic conditions
and exhibit cross-country variation. We also highlight that the rejection of
the MVS hypothesis originates from the potential to reduce variance within the
domestic global minimum-variance portfolio.
