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Optimization of Convex Risk Functions

Author

Listed:
  • Andrzej Ruszczynski

    (Rutgers University)

  • Alexander Shapiro

    (Georgia Institute of Technology)

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.

Suggested Citation

  • Andrzej Ruszczynski & Alexander Shapiro, 2004. "Optimization of Convex Risk Functions," Risk and Insurance 0404001, EconWPA, revised 08 Oct 2005.
  • Handle: RePEc:wpa:wuwpri:0404001
    Note: Type of Document - pdf; pages: 26
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    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/ri/papers/0404/0404001.pdf
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    References listed on IDEAS

    as
    1. Ogryczak, Wlodzimierz & Ruszczynski, Andrzej, 1999. "From stochastic dominance to mean-risk models: Semideviations as risk measures," European Journal of Operational Research, Elsevier, vol. 116(1), pages 33-50, July.
    2. Hans Föllmer & Alexander Schied, 2002. "Convex measures of risk and trading constraints," Finance and Stochastics, Springer, vol. 6(4), pages 429-447.
    Full references (including those not matched with items on IDEAS)

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    Keywords

    Convex analysis; stochastic optimization; risk measures; mean- variance models; duality;

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