This paper introduces a kernel-based nonparametric inferential procedure to test for Granger-causality in distribution. This test is a multivariate extension of the kernel-based Granger-causality test in tail-event introduced by Hong et al. (2009) and hence shares its main advantage, by checking...

The global minimum variance portfolio computed using the sample covariance matrix is known to be negatively affected by parameter uncertainty. Using a robust control approach, we introduce a portfolio rule for investors who wish to invest in the global minimum variance portfolio due to its...

We introduce in this paper a testing approach that allows checking whether two financial institutions are systemically equivalent, with systemic risk measured by CoVaR (Adrian and Brunnermeier, 2011). The test compares the difference in CoVaR forecasts for two financial institutions via a...

This paper investigates the global crude oil market dependence during extreme price movements. To this aim we extend the univariate Granger causality test in extreme risk developed by Hong et al. (2009) in a multivariate context. Asymptotic as well as finite sample properties are delivered....