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. (C) 2012 Elsevier B.V. All rights reserved
The evaluation of volatility forecasts is not straightforward and some issues can arise. A standard ...
The evaluation of multivariate volatility models can be done through a direct or indirect approach....
The aim of this paper is to compare the forecasting performance of competing volatility models, in ...
The ranking of multivariate volatility models is inherently problematic because when the unobservabl...
A large number of parameterizations have been proposed to model conditional vari-ance dynamics in a ...
A large number of parameterizations have been proposed to model conditional variance dynamics in a m...
A large number of parameterizations have been proposed to model conditional variance dynamics in a m...
The consistent ranking of multivariate volatility models by means of statistical loss function is a ...
This article surveys the most important developments in volatility forecast comparison and model sel...
The use of a conditionally unbiased, but imperfect, volatility proxy can lead to undesirable outcome...
The use of a conditionally unbiased, but imperfect, volatility proxy can lead to undesirable out- co...
Multivariate volatility forecasts are an important input in many financial applications, in particul...
Recent work has emphasized the importance of evaluating estimates of a statistical functional (such ...
The use of a conditionally unbiased, but imperfect, volatility proxy can lead to undesirable outcome...
Forecast accuracy is typically measured in terms of a given loss function. However, as a consequence...
The evaluation of volatility forecasts is not straightforward and some issues can arise. A standard ...
The evaluation of multivariate volatility models can be done through a direct or indirect approach....
The aim of this paper is to compare the forecasting performance of competing volatility models, in ...
The ranking of multivariate volatility models is inherently problematic because when the unobservabl...
A large number of parameterizations have been proposed to model conditional vari-ance dynamics in a ...
A large number of parameterizations have been proposed to model conditional variance dynamics in a m...
A large number of parameterizations have been proposed to model conditional variance dynamics in a m...
The consistent ranking of multivariate volatility models by means of statistical loss function is a ...
This article surveys the most important developments in volatility forecast comparison and model sel...
The use of a conditionally unbiased, but imperfect, volatility proxy can lead to undesirable outcome...
The use of a conditionally unbiased, but imperfect, volatility proxy can lead to undesirable out- co...
Multivariate volatility forecasts are an important input in many financial applications, in particul...
Recent work has emphasized the importance of evaluating estimates of a statistical functional (such ...
The use of a conditionally unbiased, but imperfect, volatility proxy can lead to undesirable outcome...
Forecast accuracy is typically measured in terms of a given loss function. However, as a consequence...
The evaluation of volatility forecasts is not straightforward and some issues can arise. A standard ...
The evaluation of multivariate volatility models can be done through a direct or indirect approach....
The aim of this paper is to compare the forecasting performance of competing volatility models, in ...