Gilles de Truchis
Sébastien Laurent : sebastien.laurent[at]univ-amu.fr
This paper proposes a simple and parsimonious semi-parametric testing procedure for variance transmission. Our test focuses on conditional extreme values of the un-observed process of integrated variance since they are of utmost concern for policy makers due to their sudden and destabilizing effects. The test statistic is based on realized measures of variance and has a convenient asymptotic χ2 distribution under the null hypothesis of no Granger causality, which is free of estimation risk. Extensive Monte Carlo simulations show that the test has good small sample size and power properties. An extension to the case of spillovers in quadratic variation is also de-veloped. An empirical application on extreme variance transmission from US to EU equity markets is further proposed. We ﬁnd that the test performs very well in identi-fying periods of signiﬁcant causality in extreme variance, that are subsequently found to be correlated with changes in US monetary policy.