A0645
Title: Testing and modelling for the structural change in covariance matrix time series with multiplicative form
Authors: Wai-keung Li - The Education University of Hong Kong (Hong Kong) [presenting]
Abstract: A new generalized Hausman test is constructed for detecting the structural change in a multiplicative form of the covariance matrix time series model. This generalized Hausman test is asymptotically pivotal, and it has non-trivial power in detecting a broad class of alternatives. Moreover, we propose a new semiparametric covariance matrix time series model, which has a time-varying long-run component to take the structural change into account, and a BEKK-type short-run component to capture the temporal dependence. A two-step estimation procedure is proposed to estimate this semiparametric model, and the asymptotic properties of the related estimators are established. Finally, the importance of the generalized Hausman test and the semiparametric model is illustrated by simulations and an application to realized covariance matrix data
