Title: Proximity-Structured Multivariate Volatility Models
Citation: ECONOMETRIC REVIEWS vol. 34 no. 5 p. 559-593
Publication Year: 2015
JRC N°: JRC53383
ISSN: 0747-4938
URI: http://www.tandfonline.com/doi/abs/10.1080/07474938.2013.807102#.VJFIiyuG8t0
DOI: 10.1080/07474938.2013.807102
Type: Articles in periodicals and books
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.
JRC Directorate:Joint Research Centre Corporate Activities

Files in This Item:
There are no files associated with this item.

Items in repository are protected by copyright, with all rights reserved, unless otherwise indicated.