Improving the Value at Risk Forecasts: Theory and Evidence from the Financial Crisis
34 Pages Posted: 15 Apr 2010 Last revised: 25 Oct 2011
Date Written: October 21, 2011
The recent financial crisis has raised numerous questions about the accuracy of value-at-risk (VaR) as a tool to quantify extreme losses. In this paper we develop data-driven VaR approaches that are based on the principle of optimal combination and that provide robust and precise VaR forecasts for periods when they are needed most, such as the recent financial crisis. Within a comprehensive comparative study we provide the latest piece of empirical evidence on the performance of a wide range of standard VaR approaches and highlight the overall outperformance of the newly developed methods.
Keywords: Value-at-Risk, Optimal Forecast Combination, Quantile Regression, Method of Moments, Financial Crisis
JEL Classification: C21, C5, G01, G17, G28, G32
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