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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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  • 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".

Suggested Citation

  • Byström, Hans, 2000. "Orthogonal GARCH and Covariance Matrix Forecasting in a Stress Scenario: The Nordic Stock Markets During the Asian Financial Crisis 1997-1998," Working Papers 2000:14, Lund University, Department of Economics.
  • Handle: RePEc:hhs:lunewp:2000_014
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    References listed on IDEAS

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    More about this item

    Keywords

    principal components; multivariate GARCH; covariance matrix; forecast evaluation.;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G19 - Financial Economics - - General Financial Markets - - - Other

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