Conditional Value-at-Risk for General Loss Distributions

34 Pages Posted: 30 Apr 2001

See all articles by R. Tyrrell Rockafellar

R. Tyrrell Rockafellar

University of Washington - Department of Mathmatics

Stanislav P. Uryasev

University of Florida

Date Written: April 4, 2001

Abstract

Fundamental properties of conditional value-at-risk, as a measure of risk with significant advantages over value-at-risk, are derived for loss distributions in finance that can involve discreetness. Such distributions are of particular importance in applications because of the prevalence of models based on scenarios and finite sampling. Conditional value-at-risk is able to quantify dangers beyond value-at-risk, and moreover it is coherent. It provides optimization shortcuts which, through linear programming techniques, make practical many large-scale calculations that could otherwise be out of reach. The numerical efficiency and stability of such calculations, shown in several case studies, are illustrated further with an example of index tracking.

Keywords: Value-at-risk, conditional value-at-risk, mean shortfall, coherent risk measures, risk sampling, scenarios, hedging, index tracking, portfolio optimization, risk management

JEL Classification: G0

Suggested Citation

Rockafellar, R. Tyrrell and Uryasev, Stanislav P., Conditional Value-at-Risk for General Loss Distributions (April 4, 2001). Available at SSRN: https://ssrn.com/abstract=267256 or http://dx.doi.org/10.2139/ssrn.267256

R. Tyrrell Rockafellar

University of Washington - Department of Mathmatics ( email )

Box 354350
Seattle, WA 98195-4350
United States

Stanislav P. Uryasev (Contact Author)

University of Florida ( email )

303 Weil Hall
Gainesville, FL 32611-6595
United States
352-392-3091 (Phone)
352-392-3537 (Fax)

HOME PAGE: http://www.ise.ufl.edu/uryasev/

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