Palandri, Alessandro. (2009) Sequential conditional correlations: Inference and evaluation. Journal of Econometrics, Vol.153 (No.2). pp. 122-132. ISSN 0304-4076

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Abstract

This paper presents a new approach to the modeling of conditional correlation matrices within the multivariate GARCH framework. The procedure, which consists of breaking the matrix into the product of a sequence of matrices with desirable characteristics, in effect converts a highly dimensional and intractable optimization problem into a series of simple and feasible estimations. This in turn allows for richer parameterizations and complex functional forms for the single components. An empirical application involving the conditional second moments of 69 selected stocks from the NASDAQ100 shows how the new procedure results in strikingly accurate measures of the conditional correlations.

Item Type:	Journal Article
Subjects:	H Social Sciences > HG Finance
Divisions:	Faculty of Social Sciences > Warwick Business School > Finance Group Faculty of Social Sciences > Warwick Business School
Journal or Publication Title:	Journal of Econometrics
Publisher:	Elsevier BV * North-Holland
ISSN:	0304-4076
Official Date:	2009
Volume:	Vol.153
Number:	No.2
Number of Pages:	11
Page Range:	pp. 122-132
Identification Number:	10.1016/j.jeconom.2009.05.002
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
URI:	http://wrap.warwick.ac.uk/id/eprint/44856

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