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Comparing density forecasts in a risk management context
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DOI：10.1016/j.ijforecast.2019.07.006.png)
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摘要
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We compare multivariate and univariate approaches to assessing the accuracy of competing density forecasts of a portfolio return in the downside part of the support. We argue that the common practice of performing multivariate forecast comparisons can be problematic in the context of assessing portfolio risk, since better multivariate forecasts do not necessarily correspond to better aggregate portfolio return forecasts. This is illustrated by examples that involve (skew) elliptical distributions and an application to daily returns of a number of US stock prices. In addition, time-varying test statistics and Value-at-Risk forecasts provide empirical evidence of regime changes over the last decades. (C) 2019 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.
Keyword:
Density forecast evaluation
Scoring rules
Skew-elliptical distributions
Portfolio risk assessment
Value-at-Risk forecasts
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被引数:
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