Multivariate contemporaneous-threshold autoregressive models

• Autores: Dueker, Michael J.; Psaradakis, Zacharias; Sola, Martin; Spagnolo, Fabio
• Año de publicación: 2011
• Idioma: inglés
• Tipo de recurso: artículo
• Materia: NONLINEAR AUTOREGRESSIVE MODEL; SMOOTH TRANSITION; STABILITY; THRESHOLD
• Institución: Consejo Nacional de Investigaciones Científicas y Técnicas

This paper proposes a contemporaneous-threshold multivariate smooth transition autoregressive (C-MSTAR) model in which the regime weights depend on the ex-ante probabilities that latent regime-specific variables exceed certain threshold values. A key feature of the model is that the transition function depends on all the parameters of the model as well as on the data. Since the mixing weights are also a function of the regime-specific noise covariance matrix, the model can account for contemporaneous regime-specific co-movements of the variables. The stability and distributional properties of the proposed model are discussed, as well as issues of estimation, testing and forecasting. The practical usefulness of the C-MSTAR model is illustrated by examining the relationship between US stock prices and interest rates.
Fil: Dueker, Michael J.. No especifíca;
Fil: Psaradakis, Zacharias. University of London; Reino Unido
Fil: Sola, Martin. University of London; Reino Unido. Universidad Torcuato Di Tella; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Spagnolo, Fabio. Brunel University; Reino Unido