Optimization of Convex Risk Functions

32 Pages Posted: 2 Mar 2005

See all articles by Andrzej Ruszczynski

Andrzej Ruszczynski

Rutgers, The State University of New Jersey - Rutgers Business School at Newark & New Brunswick

Alexander Shapiro

Georgia Institute of Technology - The H. Milton Stewart School of Industrial & Systems Engineering (ISyE)

Date Written: January 28, 2004

Abstract

We consider optimization problems involving convex risk functions. By employing techniques of convex analysis and optimization theory in vector spaces of measurable functions we develop new representation theorems for risk models, and optimality and duality theory for problems involving risk functions.

Keywords: Convex analysis, stochastic optimization, risk measures, mean-variance models, duality

JEL Classification: C44, C61, D81

Suggested Citation

Ruszczynski, Andrzej and Shapiro, Alexander, Optimization of Convex Risk Functions (January 28, 2004). Available at SSRN: https://ssrn.com/abstract=675461 or http://dx.doi.org/10.2139/ssrn.675461

Andrzej Ruszczynski (Contact Author)

Rutgers, The State University of New Jersey - Rutgers Business School at Newark & New Brunswick ( email )

94 Rockefeller Road
Piscataway, NJ 08854
United States

Alexander Shapiro

Georgia Institute of Technology - The H. Milton Stewart School of Industrial & Systems Engineering (ISyE) ( email )

765 Ferst Drive
Atlanta, GA 30332-0205
United States

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