Robust scenario-based value-at-risk optimization

This paper develops and tests a heuristic algorithm for scenario-based value-at-risk (VaR) optimization. Due to the high computational complexity of VaR optimization, conditional value-at-risk-based proxies are utilized for VaR objectives. It is shown that our heuristic algorithm obtains robust resu...

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Veröffentlicht in:	Annals of operations research 2016-02, Vol.237 (1-2), p.203-218
Hauptverfasser:	Romanko, Oleksandr, Mausser, Helmut
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Business and Management Combinatorics Complexity Computation Heuristic Heuristic methods Heuristic programming Methods Operations research Operations Research/Decision Theory Optimization Optimization algorithms Optimization techniques Proxies Random variables Risk management Sampling error Studies Theory of Computation
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Beschreibung
Zusammenfassung:	This paper develops and tests a heuristic algorithm for scenario-based value-at-risk (VaR) optimization. Due to the high computational complexity of VaR optimization, conditional value-at-risk-based proxies are utilized for VaR objectives. It is shown that our heuristic algorithm obtains robust results with low computational complexity.
ISSN:	0254-5330 1572-9338
DOI:	10.1007/s10479-015-1822-8