Abstract

 


 



External Risk Measures and Basel Accords


Steven G. Kou


Columbia University - Department of Industrial Engineering and Operations Research (IEOR)

Xianhua Peng


Hong Kong University of Science & Technology (HKUST) - Department of Mathematics

Chris Heyde


Columbia University

March 10, 2012

Mathematics of Operations Research, Forthcoming

Abstract:     
Choosing a proper external risk measure is of great regulatory importance, as exemplified in the Basel II and Basel III Accord which use Value-at-Risk (VaR) with scenario analysis as the risk measures for setting capital requirements. We argue a good external risk measure should be robust with respect to model misspecification and small changes in the data. A new class of data-based risk measures called natural risk statistics are proposed to incorporate robustness. Natural risk statistics are characterized by a new set of axioms; they include the Basel II and III risk measures and a subclass of robust risk measures as special cases; therefore, they provide a theoretical framework for understanding and, if necessary, extending the Basel accords.

Number of Pages in PDF File: 27

Keywords: financial regulation, capital requirements, risk measure, scenario analysis, robustness, value-at-risk, expected shortfall, tail conditional expectation

JEL Classification: G18, G28, G32, K20, K23

working papers series


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Date posted: May 12, 2012 ; Last revised: February 4, 2013

Suggested Citation

Kou, Steven G., Peng, Xianhua and Heyde, Chris, External Risk Measures and Basel Accords (March 10, 2012). Mathematics of Operations Research, Forthcoming. Available at SSRN: http://ssrn.com/abstract=2055634 or http://dx.doi.org/10.2139/ssrn.2055634

Contact Information

Steven G. Kou (Contact Author)
Columbia University - Department of Industrial Engineering and Operations Research (IEOR) ( email )
331 S.W. Mudd Building
500 West 120th Street
New York, NY 10027
United States
212-854-4334 (Phone)
Xianhua Peng
Hong Kong University of Science & Technology (HKUST) - Department of Mathematics ( email )
Lift 25-26
Clear Water Bay, Kowloon
Hong Kong
Chris Heyde
Columbia University ( email )
3022 Broadway
New York, NY 10027
United States
Feedback to SSRN (Beta)


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