Improving the value at risk forecasts: Theory and evidence from the financial crisis
AbstractThe 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.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Economic Dynamics and Control.
Volume (Year): 36 (2012)
Issue (Month): 8 ()
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Web page: http://www.elsevier.com/locate/jedc
Value-at-risk; Optimal forecast combination; Quantile regression; Method of moments; Financial crisis;
Find related papers by JEL classification:
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- C5 - Mathematical and Quantitative Methods - - Econometric Modeling
- G01 - Financial Economics - - General - - - Financial Crises
- G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
- G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
- G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
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