BL-GARCH model with elliptical distributed innovations
Journal article: In this paper, we discuss the class of Bilinear GATRCH (BL-GARCH) models which are capable of capturing simultaneously two key properties of non-linear time series : volatility clustering and leverage effects. It has been observed often that the marginal distributions of such time series have heavy tails ; thus we examine the BL-GARCH model in a general setting under some non-Normal distributions. We investigate some probabilistic properties of this model and we propose and implement a maximum likelihood estimation (MLE) methodology. To evaluate the small-sample performance of this method for the various models, a Monte Carlo study is conducted. Finally, within-sample estimation properties are studied using S&P 500 daily returns, when the features of interest manifest as volatility clustering and leverage effects.
Author(s)
Abdou Kâ Diongue, Dominique Guegan, Rodney C. Wolff
Journal
- Journal of Statistical Computation and Simulation
Date of publication
- 2010
Keywords
- BL-GARCH process
- Elliptical distribution
- Leverage effects
- Maximum Likelihood
- Monte Carlo method
- Volatility clustering
Pages
- 775-791
URL of the HAL notice
Version
- 1
Volume
- 80