Bayesian estimation of an extended local scale stochastic volatility model

被引：6

作者：

Deschamps, Philippe J. ^{[1
]}

机构：

[1] Univ Fribourg, Seminaire Econometrie, CH-1700 Fribourg, Switzerland

来源：

JOURNAL OF ECONOMETRICS | 2011年 / 162卷 / 02期

关键词：

State space models; Markov chain Monte Carlo; Simulation smoothing; Generalized error distribution; Generalized t distribution; STATE-SPACE MODELS; CONDITIONAL HETEROSKEDASTICITY; LIKELIHOOD INFERENCE; MARGINAL LIKELIHOOD; RETURNS; LEVERAGE; OUTPUT;

D O I：

10.1016/j.jeconom.2011.02.022

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

A new version of the local scale model of Shephard (1994) is presented. Its features are identically distributed evolution equation disturbances, the incorporation of in-the-mean effects, and the incorporation or variance regressors. A Bayesian posterior simulator and a new simulation smoother are presented. The model is applied to publicly available daily exchange rate and asset return series, and is compared with t-GARCH and Lognormal stochastic volatility formulations using Bayes factors. (C) 2011 Elsevier B.V. All rights reserved.

引用

页码：369 / 382

页数：14

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