Contemporaneous-threshold smooth transition GARCH models

Abstract

This paper proposes a contemporaneous-threshold smooth transition GARCH (or C-STGARCH) model for dynamic conditional heteroskedasticity. The C-STGARCH model is a generalization to second conditional moments of the contemporaneous smooth transition threshold autoregressive model of Dueker et al. (2007) in which the regime weights depend on the ex ante probability that a contemporaneous latent regime-specific variable exceeds a threshold value. A key feature of the C-STGARCH model is that its transition function depends on all the parameters of the model as well as on the data. The structural properties of the model are investigated, in addition to the finite-sample properties of the maximum likelihood estimator of its parameters. An application to U.S. stock returns illustrates the practical usefulness of the C-STGARCH model.