کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
415674 | 681223 | 2006 | 15 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Comparison of nonnested asymmetric heteroskedastic models Comparison of nonnested asymmetric heteroskedastic models](/preview/png/415674.png)
The GJR-GARCH model is a popular choice among nonlinear models of the well-known asymmetric volatility phenomenon in financial market data. However, recent work employs double threshold nonlinear models to capture both mean and volatility asymmetry. A Bayesian model comparison procedure is proposed to compare the GJR-GARCH with various double threshold GARCH specifications, by designing a reversible jump Markov chain Monte Carlo algorithm. A simulation experiment illustrates good performance in estimation and model selection over reasonable sample sizes. In a study of seven markets strong evidence is found that the DTGARCH, with US market news as threshold variable, outperforms the GJR-GARCH and traditional self-exciting DTGARCH models. This result was consistent across six markets, excluding Canada.
Journal: Computational Statistics & Data Analysis - Volume 51, Issue 4, 15 December 2006, Pages 2164–2178