Not logged in.

Contribution Details

Type Journal Article
Scope Discipline-based scholarship
Title Computational aspects of minimizing conditional value-at-risk
Organization Unit
Authors
  • János Mayer
  • Alexandra Künzi-Bay
Item Subtype Original Work
Refereed Yes
Status Published in final form
Language
  • English
Journal Title Computational Management Science (CMS)
Publisher Springer
Geographical Reach international
ISSN 1619-697X
Volume 3
Number 1
Page Range 3 - 27
Date 2006
Abstract Text We consider optimization problems for minimizing conditional value-at-risk (CVaR) from a computational point of view, with an emphasis on financial applications. As a general solution approach, we suggest to reformulate these CVaR optimization problems as two-stage recourse problems of stochastic programming. Specializing the L-shaped method leads to a new algorithm for minimizing conditional value-at-risk. We implemented the algorithm as the solver CVaRMin. For illustrating the performance of this algorithm, we present some comparative computational results with two kinds of test problems. Firstly, we consider portfolio optimization problems with 5 random variables. Such problems involving conditional value at risk play an important role in financial risk management. Therefore, besides testing the performance of the proposed algorithm, we also present computational results of interest in finance. Secondly, with the explicit aim of testing algorithm performance, we also present comparative computational results with randomly generated test problems involving 50 random variables. In all our tests, the experimental solver, based on the new approach, outperformed by at least one order of magnitude all general-purpose solvers, with an accuracy of solution being in the same range as that with the LP solvers.
Free access at DOI
Digital Object Identifier 10.1007/s10287-005-0042-0
Other Identification Number merlin-id:3602
PDF File Download from ZORA
Export BibTeX
EP3 XML (ZORA)