GMM estimation of a realized stochastic volatility model: A Monte Carlo study

被引：5

作者：

Chausse, Pierre ^{[1
]}

Xu, Dinghai ^{[1
]}

机构：

[1] Univ Waterloo, Dept Econ, Waterloo, ON N2L 3G1, Canada

来源：

ECONOMETRIC REVIEWS | 2018年 / 37卷 / 07期

关键词：

Generalized method of moments; heteroscedasticity and autocorrelation consistent; Monte Carlo simulation; principal component GMM; realized volatility measure; regularized GMM; robust GMM; stochastic volatility model; COVARIANCE-MATRIX ESTIMATION; GENERALIZED-METHOD; HEAVY MODELS; MOMENTS; RESTRICTIONS; VARIANCE; RETURNS; NOISE;

D O I：

10.1080/07474938.2016.1152654

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This article investigates alternative generalized method of moments (GMM) estimation procedures of a stochastic volatility model with realized volatility measures. The extended model can accommodate a more general correlation structure. General closed form moment conditions are derived to examine the model properties and to evaluate the performance of various GMM estimation procedures under Monte Carlo environment, including standard GMM, principal component GMM, robust GMM and regularized GMM. An application to five company stocks and one stock index is also provided for an empirical demonstration.

引用

页码：719 / 743

页数：25

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