On loss functions and ranking forecasting performances of multivariate volatility models
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 lev...
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| Veröffentlicht in: | Journal of econometrics 2013-03, Vol.173 (1), p.1-10 |
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| container_title | Journal of econometrics |
| container_volume | 173 |
| creator | Laurent, Sébastien Rombouts, Jeroen V.K. Violante, Francesco |
| description | 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. |
| doi_str_mv | 10.1016/j.jeconom.2012.08.004 |
| format | Article |
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| ispartof | Journal of econometrics, 2013-03, Vol.173 (1), p.1-10 |
| issn | 0304-4076 1872-6895 |
| language | eng |
| recordid | cdi_proquest_journals_1282142104 |
| source | Elsevier ScienceDirect Journals |
| subjects | Economic forecasting Foreign exchange rates Loss function Matrix norm Model confidence set Multivariate analysis Multivariate GARCH Studies Volatility |
| title | On loss functions and ranking forecasting performances of multivariate volatility models |
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