On loss functions and ranking forecasting performances of multivariate volatility models

Sébastien Laurent, Jeroen Rombouts and Francesco Violante ()

Journal of Econometrics, 2013, vol. 173, issue 1, 1-10

Abstract: The ranking of multivariate volatility models is inherently problematic because when the unobservable volatility is substituted by a proxy, the ordering implied by a loss function may be biased with respect to the intended one. We point out that the size of the distortion is strictly tied to the level of the accuracy of the volatility proxy. We propose a generalized necessary and sufficient functional form for a class of non-metric distance measures of the Bregman type which ensure consistency of the ordering when the target is observed with noise. An application to three foreign exchange rates is provided.

Keywords: Volatility; Multivariate GARCH; Matrix norm; Loss function; Model confidence set (search for similar items in EconPapers)
JEL-codes: C10 C32 C51 C52 C53 G10 (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (103)

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Related works:
Working Paper: On Loss Functions and Ranking Forecasting Performances of Multivariate Volatility Models (2009)
Working Paper: On Loss Functions and Ranking Forecasting Performances of Multivariate Volatility Models (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:173:y:2013:i:1:p:1-10

DOI: 10.1016/j.jeconom.2012.08.004

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