Proximity-Structured Multivariate Volatility Models

Caporin, Massimiliano; Paruolo, Paolo

doi:10.2139/ssrn.1406419

Download This Paper

Open PDF in Browser

Add Paper to My Library

Proximity-Structured Multivariate Volatility Models

30 Pages Posted: 21 May 2009 Last revised: 12 May 2013

See all articles by Massimiliano Caporin

Massimiliano Caporin

University of Padua - Department of Statistical Sciences

Paolo Paruolo

European Commission DG Joint Research Centre; Joint Research Center of the European Commission

Date Written: December 2012

Abstract

In many multivariate volatility models, the number of parameters increases faster than the cross-section dimension, hence creating a curse of dimensionality problem. This paper discusses specification and identification of structured parameterizations based on weight matrices induced by economic proximity. It is shown that structured specifications can mitigate or even solve the curse of dimensionality problem. Identification and estimation of structured specifications are analyzed, rank and order conditions for identification are given and the specification of weight matrices is discussed. Several structured specifications compare well with alternatives in modelling conditional covariances of six returns from the New York Stock Exchange.

Keywords: MGARCH, Stochastic Volatility, Realized Volatility, spatial models, ANOVA

JEL Classification: C31, C32, G11

Suggested Citation: Suggested Citation

Caporin, Massimiliano and Paruolo, Paolo and Paruolo, Paolo, Proximity-Structured Multivariate Volatility Models (December 2012). Available at SSRN: https://ssrn.com/abstract=1406419 or http://dx.doi.org/10.2139/ssrn.1406419