文章基本信息

标题：Comparing and evaluating Bayesian predictive distributions of assets returns
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作者：John Geweke ; Gianni Amisano
期刊名称：Euro Area Balance of Payments and International Investment Position Statistics
印刷版ISSN：1830-3420
电子版ISSN：1830-3439
出版年度：2008
卷号：1
出版社：European Central Bank
摘要：Bayesian inference in a time series model provides exact, out-of-sample predictive distributions that fully and coherently incorporate parameter uncertainty. This study compares and evaluates Bayesian predictive distributions from alternative models, using as an illustration five alternative models of asset returns applied to daily S&P 500 returns from 1976 through 2005. The comparison exercise uses predictive likelihoods and is inherently Bayesian. The evaluation exercise uses the probability integral transform and is inherently frequentist. The illustration shows that the two approaches can be complementary, each identifying strengths and weaknesses in models that are not evident using the other.
关键词：forecasting; GARCH; inverse probability transform; Markov mixture;predictive likelihood; S&P 500 returns; stochastic volatility.