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On the efficacy of techniques for evaluating multivariate volatility forecasts

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Author Info
Adam Clements () (QUT)
Mark Doolan () (QUT)
Stan Hurn () (QUT)
Ralf Becker () (University of Manchester)

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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.

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Publisher Info
Paper provided by National Centre for Econometric Research in its series NCER Working Paper Series with number 41.

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Date of creation: 23 Feb 2009
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Handle: RePEc:qut:auncer:2009_50

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Related research
Keywords: Multivariate volatility; forecasts; forecast evaluation; Model confidence set;

Find related papers by JEL classification:
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
G00 - Financial Economics - - General - - - General

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This page was last updated on 2009-11-25.


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