Macroeconomic Forecasting Performance under Alternative Specifications of Time-Varying Volatility
Macroeconomic Forecasting Performance under Alternative Specifications of Time-Varying Volatility
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DOI：
10.1002/jae.2379
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发表时间：
2015-06-01
影响因子：
2.1
通讯作者：
Ravazzolo, Francesco
中科院分区：
文献类型：
--
作者：
Clark, Todd E.;Ravazzolo, Francesco
本文以美国主要宏观经济时间序列的实时点和密度预测的精度为基础，比较了不同的时变波动率模型。我们考虑了贝叶斯自回归和向量自回归模型，它们包含了某种形式的时变波动率、精确随机游动随机波动率、平稳AR过程的随机波动率、带厚尾的随机波动率、GARCH和混合新息模型。结果表明，具有常规随机波动率的AR和VAR规范在一定程度上主导了其他波动率规范，在点预测和密度预测方面也有较大程度的优势。版权所有(C)2014 John Wiley&Sons，Ltd.
This paper compares alternative models of time-varying volatility on the basis of the accuracy of real-time point and density forecasts of key macroeconomic time series for the USA. We consider Bayesian autoregressive and vector autoregressive models that incorporate some form of time-varying volatility, precisely random walk stochastic volatility, stochastic volatility following a stationary AR process, stochastic volatility coupled with fat tails, GARCH and mixture of innovation models. The results show that the AR and VAR specifications with conventional stochastic volatility dominate other volatility specifications, in terms of point forecasting to some degree and density forecasting to a greater degree. Copyright (c) 2014 John Wiley & Sons, Ltd.