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Evaluating multivariate volatility forecasts

By Adam Clements, Mark Doolan, Stan Hurn and Ralf Becker

Abstract

The performance of techniques for evaluating univariate volatility forecasts are well understood. In the multivariate setting however, the efficacy of the evaluation techniques is not developed. Multivariate forecasts are often evaluated within an economic application such as portfolio optimisation context. This paper aims to evaluate the efficacy of such techniques, along with traditional statistical based methods. It is found that utility based methods perform poorly in terms of identifying optimal forecasts whereas statistical methods are more effective.Multivariate volatility, forecasts, forecast evaluation, Model confidence set

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