A Student-t Full Factor Multivariate GARCH Model

作者：Diamantopoulos K; Vrontos I D^*

来源：Computational Economics, 2010, 35(1): 63-83.

DOI：10.1007/s10614-009-9179-1

• Autoregressive conditional heteroscedasticity
• Fat tails
• Maximum likelihood estimation
• Student-t distribution

We extend the full-factor multivariate GARCH model of Vrontos et al. (Econom J 6:312-334, 2003a) to account for fat tails in the conditional distribution of financial returns, using a multivariate Student-t error distribution. For the new class of Student-t full factor multivariate GARCH models, we derive analytical expressions for the score, the Hessian matrix and the Information matrix. These expressions can be used within classical inferential procedures in order to obtain maximum likelihood estimates for the model parameters. This fact, combined with the parsimonious parameterization of the covariance matrix under the full factor multivariate GARCH models, enables us to apply the models in high dimensional problems. We provide implementation details and illustrations using financial time series on eight stocks of the US market.

• 出版日期2010-1