Time Varying Covariances: A Factor Stochastic Volatility Approach (with discussion
Time Varying Covariances: A Factor Stochastic Volatility Approach (with discussion
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时变协方差：因子随机波动率方法（带讨论
DOI：
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发表时间：
1998
期刊：
影响因子：
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通讯作者：
M. Pitt
中科院分区：
文献类型：
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作者：
N. Shephard;M. Pitt
我们提出了一个因子模型，当被建模的序列数目变得很大时，该模型允许简约地表示协方差的时间序列演化。这些因素来自一个标准的随机波动率模型，与每个系列相关的特殊噪声也是如此。我们使用了一种有效的方法来推导该模型参数的后验分布。此外，我们还针对这类模型提出了一种有效的贝叶斯模型选择方法。最后，我们考虑了针对特定模型的诊断措施。
We propose a factor model which allows a parsimonious representation of the time series evolution of covariances when the number of series being modelled becomes very large. The factors arise from a standard stochastic volatility model as does the idiosyncratic noise associated with each series. We use an efficient method for deriving the posterior distribution of the parameters of this model. In addition we propose an effective method of Bayesian model selection for this class of models. Finally, we consider diagnostic measures for specific models.