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Evaluation of correlation forecasting models for risk management

Author

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  • Vasiliki D. Skintzi

    (Department of Economics, School of Management and Economics, University of Peloponnese, Tripolis, Greece)

  • Spyros Xanthopoulos-Sisinis

    (Financial Engineering Research Centre, Department of Management Science and Technology, Athens University of Economics and Business, Athens, Greece)

Abstract

Reliable correlation forecasts are of paramount importance in modern risk management systems. A plethora of correlation forecasting models have been proposed in the open literature, yet their impact on the accuracy of value-at-risk calculations has not been explicitly investigated. In this paper, traditional and modern correlation forecasting techniques are compared using standard statistical and risk management loss functions. Three portfolios consisting of stocks, bonds and currencies are considered. We find that GARCH models can better account for the correlation's dynamic structure in the stock and bond portfolios. On the other hand, simpler specifications such as the historical mean model or simple moving average models are better suited for the currency portfolio. Copyright © 2007 John Wiley & Sons, Ltd.

Suggested Citation

  • Vasiliki D. Skintzi & Spyros Xanthopoulos-Sisinis, 2007. "Evaluation of correlation forecasting models for risk management," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(7), pages 497-526.
    • Handle: RePEc:jof:jforec:v:26:y:2007:i:7:p:497-526
    DOI: 10.1002/for.1036
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    1. Alexei Kolokolov, 2011. "Futures hedging: Multivariate GARCH with dynamic conditional correlations (in Russian)," Quantile, Quantile, issue 9, pages 61-75, July.
    2. Hakim, Abdul & McAleer, Michael, 2009. "Forecasting conditional correlations in stock, bond and foreign exchange markets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(9), pages 2830-2846.

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