文章基本信息

标题：A Family of Stochastic Unit GARCH Models
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作者：Mamadou Abdoulaye Konte
期刊名称：International Journal of Economics and Finance
印刷版ISSN：1916-971X
电子版ISSN：1916-9728
出版年度：2012
卷号：5
期号：1
页码：177
DOI：10.5539/ijef.v5n1p177
语种：English
出版社：Canadian Center of Science and Education
摘要：A class of Asymmetric GARCH models is presented. It shares the same unconditional variance and volatility forecast formula as the standard GARCH(P,Q) model under the assumption of a symmetric conditional distribution for innovations. use three models of this class to assess their ability to forecast S&P 500 market volatility and to make better decisions for the purpose of risk management and investment. Subsequently, a comparison is made with respect to competing models (GARCH, EGARCH, GJR). It was found that for the in-sample evaluation, the best model is obtained from the Stochastic Unit GARCH (SUGARCH) model where leverage effects are introduced through the GARCH (i.e) parameter. For the out-of-sample evaluation (QLIKE loss function), it is better to use the SUGARCH class where the asymmetry appears on the ARCH (i.e ) parameter.