## Abstract Recent research has suggested that forecast evaluation on the basis of standard statistical loss functions could prefer models which are subβoptimal when used in a practical setting. This paper explores a number of statistical models for predicting the daily volatility of several key UK
Evaluation of correlation forecasting models for risk management
β Scribed by Vasiliki D. Skintzi; Spyros Xanthopoulos-Sisinis
- Publisher
- John Wiley and Sons
- Year
- 2007
- Tongue
- English
- Weight
- 234 KB
- Volume
- 26
- Category
- Article
- ISSN
- 0277-6693
- DOI
- 10.1002/for.1036
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β¦ Synopsis
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 valueβatβrisk 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.ββCopyright Β© 2007 John Wiley & Sons, Ltd.
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