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Risk models-at-risk

Boucher, Christophe M., Danielsson, Jon, Kouontchou, Patrick S. and Maillet, Bertrand B. (2014) Risk models-at-risk. Journal of Banking & Finance, 44 . pp. 72-92. ISSN 03784266

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Abstract

The experience from the global financial crisis has raised serious concerns about the accuracy of standard risk measures as tools for the quantification of extreme downward risks. A key reason for this is that risk measures are subject to a model risk due, e.g. to specification and estimation uncertainty. While regulators have proposed that financial institutions assess the model risk, there is no accepted approach for computing such a risk. We propose a remedy for this by a general framework for the computation of risk measures robust to model risk by empirically adjusting the imperfect risk forecasts by outcomes from backtesting frameworks, considering the desirable quality of VaR models such as the frequency, independence and magnitude of violations. We also provide a fair comparison between the main risk models using the same metric that corresponds to model risk required corrections.

Item Type: Article
Official URL: http://www.journals.elsevier.com/journal-of-bankin...
Additional Information: © 2014 Elsevier B.V.
Library of Congress subject classification: H Social Sciences > HG Finance
H Social Sciences > HJ Public Finance
Journal of Economic Literature Classification System: G - Financial Economics > G2 - Financial Institutions and Services > G24 - Investment Banking; Venture Capital; Brokerage; Rating Agencies
Sets: Departments > Finance
Rights: http://www.lse.ac.uk/library/usingTheLibrary/academicSupport/OA/depositYourResearch.aspx
Date Deposited: 29 May 2014 10:37
URL: http://eprints.lse.ac.uk/56869/

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