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- W3036690128 abstract "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." @default.
- W3036690128 created "2020-06-25" @default.
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- W3036690128 date "2010-01-01" @default.
- W3036690128 modified "2023-10-16" @default.
- W3036690128 title "BL-GARCH model with elliptical distributed innovations" @default.
- W3036690128 hasPublicationYear "2010" @default.
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