The Wishart Autoregressive process of multivariate stochastic volatility

被引：137

作者：

Gourieroux, C. ^{[1
]}

Jasiak, J. ^{[2
]}

Sufana, R. ^{[2
]}

机构：

[1] Univ Toronto, CREST, Toronto, ON M5S 1A1, Canada

[2] York Univ, Toronto, ON M3J 2R7, Canada

来源：

JOURNAL OF ECONOMETRICS | 2009年 / 150卷 / 02期

基金：

加拿大自然科学与工程研究理事会;

关键词：

Stochastic volatility; Car process; Autoregressive gamma process; Factor analysis; Reduced rank; Realized volatility; TRANSMISSION; MODEL;

D O I：

10.1016/j.jeconom.2008.12.016

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

The Wishart Autoregressive (WAR) process is a dynamic model for time series of multivariate stochastic volatility. The WAR naturally accommodates the positivity and symmetry of volatility matrices and provides closed-form non-linear forecasts. The estimation of the WAR is straighforward, as it relies on standard methods such as the Method of Moments and Maximum Likelihood. For illustration, the WAR is applied to a sequence of intraday realized volatility-covolatility matrices from the Toronto Stock Market (TSX). (c) 2009 Published by Elsevier B.V.

引用

页码：167 / 181

页数：15

共 45 条

[1] Quadratic term structure models: Theory and evidence [J].