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The Role of the Information Set for Forecasting - with Applications to Risk Management
Company: Annals of Applied Statistics
Company Url: Click here to open
Year Of Publication: 2014
Month Of Publication: April
Resource Link: Click here to open
Pages: 595-621
Download Count: 0
View Count: 1344
Comment Num: 0
Language: English
Source: article
Who Can Read: Free
Date: 7-19-2014
Publisher: Administrator
Summary
we show that the classical Diebold-Mariano test, based on strictly consistent scoring functions and asymptotically ideal forecasts, is a consistent test for the effect of an increase in a sequence of information sets on h-step point forecasts. For the value at risk (VaR), we show that the average score, which corresponds to the average quantile risk, directly relates to the expected shortfall. Thus, increasing the information set will result in VaR forecasts which lead on average to smaller expected shortfalls. We illustrate our results in simulations and applications to stock returns for unconditional versus conditional risk management as well as univariate modeling of portfolio returns versus multivariate modeling of individual risk factors.
(volume 8, number 1)
This document may be downloaded without charge from arXiv.org at this url:http://arxiv.org/abs/1404.7653
Author(s)
Holzmann, Hajo Sign in to follow this author
Eulert, Matthias Sign in to follow this author
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