Backtesting VaR and ES under the magnifying glass

Argyropoulos, C. and Panopoulou, E. (2019) Backtesting VaR and ES under the magnifying glass. International Review of Financial Analysis, 64. pp. 22-37. ISSN 1057-5219

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Abstract

Backtesting provides the means of determining the accuracy of risk forecasts and the corresponding risk model. Given that the actual return generating process is unknown, the evaluation methods rely on various assumptions in order to quantify the models inefficiencies and proceed with the model evaluation. These method specific assumptions, in conjunction with the regulatory policies can introduce distortions in the evaluation process, which affect the reliability of the evaluation results. To investigate such effects from a practitioner's perspective, this paper reviews the major Value at Risk and Expected Shortfall forecast evaluation methods and evaluates their performance under a common simulation and financial application framework. Our findings suggest that focusing on specific individual hypothesis tests provides a more reliable alternative than the corresponding conditional coverage ones. In addition, selecting a two-year out-of-sample period provides a significantly better power to relevance ratio than the more relevant but powerless regulatory one-year specification.

Item Type:
Journal Article
Journal or Publication Title:
International Review of Financial Analysis
Additional Information:
This is the author’s version of a work that was accepted for publication in International Review of Financial Analysis. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Review of Financial Analysis, 65, 2019 DOI: 10.1016/j.irfa.2019.04.005
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2000/2002
Subjects:
ID Code:
133969
Deposited By:
Deposited On:
21 Jun 2019 12:25
Refereed?:
Yes
Published?:
Published
Last Modified:
28 Mar 2020 06:07