IJPAM: Volume 55, No. 3 (2009)

ON REBONATO AND JÄCKEL'S PARAMETRIZATION
METHOD FOR FINDING NEAREST
CORRELATION MATRICES

Alec N. Kercheval
Department of Mathematics
The College of Arts and Sciences
Florida State University
1017, Academic Way, P.O. Box 3064510
Tallahassee, FL 32306-4510, USA
e-mail: kercheval@math.fsu.edu


Abstract.Portfolio risk forecasts are often made by estimating an asset or factor correlation matrix. However, estimation difficulties or exogenous constraints can lead to correlation matrix candidates that are not positive semidefinite (psd). Therefore, practitioners need to reimpose the psd property with the minimum possible correction. Rebonato and Jäckel (2000) raised this question and proposed an approach; in this paper we improve on that approach by introducing a more geometric perspective on the problem.

Received: May 18, 2008

AMS Subject Classification: 91B28, 65F30

Key Words and Phrases: correlation matrix, positive semidefinite matrix, portfolio risk forecast

Source: International Journal of Pure and Applied Mathematics
ISSN: 1311-8080
Year: 2009
Volume: 55
Issue: 3