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Orthogonal GARCH and Covariance Matrix Forecasting in a Stress Scenario: The Nordic Stock Markets During the Asian Financial Crisis 1997-1998

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Author Info

  • Byström, Hans

    ()
    (Department of Economics, Lund University)

Abstract

In Risk Management, modelling large numbers of assets and their variances and covariances together in a unified framework is often important. In such multivariate frameworks, it is difficult to incorporate GARCH models and thus a new member of the ARCH-family, Orthogonal GARCH, has been suggested as a remedy to inherent estimation problems in multivariate ARCH-modelling. Orthogonal GARCH creates positive definite covariance matrices of any size but builds on assumptions that partly break down during stress scenarios. In this article, I therefore assess the stress performance of the model by looking at four Nordic Stock Indices and covariance matrix forecasts during the highly volatile years of 1997 and 1998. Overall, I find Orthogonal GARCH to perform significantly better than traditional historical variance and moving average methods. As out of sample evaluation measures, I use symmetric loss functions (RMSE), asymmetric loss functions, operational methods suggested by the Basle Committee on Banking Supervision, as well as a forecast evaluation methodology based on pricing of simulated "rainbow options".

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Bibliographic Info

Paper provided by Lund University, Department of Economics in its series Working Papers with number 2000:14.

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Length: 25 pages
Date of creation: 28 Sep 2000
Date of revision:
Publication status: Published in European Journal of Finance, 2004, pages 44-67.
Handle: RePEc:hhs:lunewp:2000_014

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Postal: Department of Economics, School of Economics and Management, Lund University, Box 7082, S-220 07 Lund,Sweden
Phone: +46 +46 222 0000
Fax: +46 +46 2224613
Web page: http://www.nek.lu.se/en
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Keywords: principal components; multivariate GARCH; covariance matrix; forecast evaluation.;

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