DAMGARCH is a new model that extends the VARMA-GARCH model of Ling and McAleer (2003) by introducing multiple thresholds and time-dependent structure in the asymmetry of the conditional variances. Analytical expressions for the news impact surface implied by the new model are also presented. DAMGARCH models the shocks affecting the conditional variances on the basis of an underlying multivariate distribution. It is possible to model explicitly asset-specific shocks and common innovations by partitioning the multivariate density support. This paper presents the model structure, describes the implementation issues, and provides the conditions for the existence of a unique stationary solution, and for consistency and asymptotic normality of the quasi-maximum likelihood estimators. The paper also presents an empirical example to highlight the usefulness of the new model.

Additional Metadata
Keywords asymptotic theory, conditional variance, multivariate asymmetry, multivariate news impact cure, stationarity conditions
JEL Time-Series Models; Dynamic Quantile Regressions (jel C32), Model Construction and Estimation (jel C51), Model Evaluation and Testing (jel C52)
Publisher Erasmus School of Economics
Persistent URL hdl.handle.net/1765/19452
Series Econometric Institute Research Papers
Journal Report / Econometric Institute, Erasmus University Rotterdam
Caporin, M, & McAleer, M.J. (2010). Threshold, news impact surfaces and dynamic asymmetric multivariate GARCH (No. EI 2010-36). Report / Econometric Institute, Erasmus University Rotterdam (pp. 1–51). Erasmus School of Economics. Retrieved from http://hdl.handle.net/1765/19452