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
Version
  • 1
Volume
  • 80