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Backtesting parametric value-at-risk with estimation risk

Backtesting parametric value-at-risk with estimation risk
Backtesting parametric value-at-risk with estimation risk
One of the implications of the creation of the Basel Committee on Banking Supervision was the implementation of Value-at-Risk (VaR) as the standard tool for measuring market risk. Since then, the capital requirements of commercial banks with trading activities are based on VaR estimates. Therefore, appropriately constructed tests for assessing the out-of-sample forecast accuracy of the VaR model (backtesting procedures) have become of crucial practical importance. In this article we show that the use of the standard unconditional and independence backtesting procedures to assess VaR models in out-of-sample composite environments can be misleading. These tests do not consider the impact of estimation risk, and therefore, may use wrong critical values to assess market risk. The purpose of this article is to quantify such estimation risk in a very general class of dynamic parametric VaR models and to correct standard backtesting procedures to provide valid inference in out-of-sample analyses. A Monte Carlo study illustrates our theoretical findings in finite-samples and shows that our corrected unconditional test can provide more accurately sized and more powerful tests than the uncorrected one. Finally, an application to the S&P 500 Index shows the importance of this correction and its impact on capital requirements as imposed by the Basel Accord
0735-0015
36-51
Escanciano, J. Carlos
96e0133a-669a-4e2e-aba2-b3d858f604c1
Olmo, J.
706f68c8-f991-4959-8245-6657a591056e
Escanciano, J. Carlos
96e0133a-669a-4e2e-aba2-b3d858f604c1
Olmo, J.
706f68c8-f991-4959-8245-6657a591056e

Escanciano, J. Carlos and Olmo, J. (2010) Backtesting parametric value-at-risk with estimation risk. Journal of Business and Economic Statistics, 28 (1), 36-51. (doi:10.1198/jbes.2009.07063).

Record type: Article

Abstract

One of the implications of the creation of the Basel Committee on Banking Supervision was the implementation of Value-at-Risk (VaR) as the standard tool for measuring market risk. Since then, the capital requirements of commercial banks with trading activities are based on VaR estimates. Therefore, appropriately constructed tests for assessing the out-of-sample forecast accuracy of the VaR model (backtesting procedures) have become of crucial practical importance. In this article we show that the use of the standard unconditional and independence backtesting procedures to assess VaR models in out-of-sample composite environments can be misleading. These tests do not consider the impact of estimation risk, and therefore, may use wrong critical values to assess market risk. The purpose of this article is to quantify such estimation risk in a very general class of dynamic parametric VaR models and to correct standard backtesting procedures to provide valid inference in out-of-sample analyses. A Monte Carlo study illustrates our theoretical findings in finite-samples and shows that our corrected unconditional test can provide more accurately sized and more powerful tests than the uncorrected one. Finally, an application to the S&P 500 Index shows the importance of this correction and its impact on capital requirements as imposed by the Basel Accord

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jbes.2009.07063 - Other
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Published date: 1 January 2010
Organisations: Economics

Identifiers

Local EPrints ID: 348558
URI: http://eprints.soton.ac.uk/id/eprint/348558
ISSN: 0735-0015
PURE UUID: 5e274f60-6591-40db-b175-df7b257371c2
ORCID for J. Olmo: ORCID iD orcid.org/0000-0002-0437-7812

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Date deposited: 15 Feb 2013 09:50
Last modified: 15 Mar 2024 03:46

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Contributors

Author: J. Carlos Escanciano
Author: J. Olmo ORCID iD

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