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2000-04-01Buch DOI: 10.18452/8233
The performance of stochastic dynamic and fixed mix portfolio models
dc.contributor.authorFleten, Stein-Erik
dc.contributor.authorHøyland, Kjetil
dc.contributor.authorStein, W.
dc.contributor.editorHigle, Julie L.
dc.contributor.editorRömisch, Werner
dc.contributor.editorSen, Surrajeet
dc.date.accessioned2017-06-16T19:38:03Z
dc.date.available2017-06-16T19:38:03Z
dc.date.created2006-02-09
dc.date.issued2000-04-01
dc.date.submitted2000-01-11
dc.identifier.urihttp://edoc.hu-berlin.de/18452/8885
dc.description.abstractThe purpose of this paper is to demonstrate how to evaluate stochastic programming models, and more specifically to compare two different approaches to asset liability management. The first uses multistage stochastic programming, while the other is a static approach based on so-called constant rebalancing of fixed mix. Particular attention is paid to the methodology used for the comparison. The two alternatives are tested over a large number of realistic scenarios created by means of simulation. We find that due to the ability of the stochastic programming model to adapt to the information in the scenario tree, it dominates the fixed mix approach.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, Institut für Mathematik
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectStochastic programmingeng
dc.subjectNonlinear programmingeng
dc.subjectSimulationeng
dc.subjectPortfolio selectioneng
dc.subjectAsset liability managementeng
dc.subjectPerformance measurementeng
dc.subject.ddc510 Mathematik
dc.titleThe performance of stochastic dynamic and fixed mix portfolio models
dc.typebook
dc.identifier.urnurn:nbn:de:kobv:11-110-18452/8885-3
dc.identifier.doihttp://dx.doi.org/10.18452/8233
local.edoc.type-nameBuch
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
local.edoc.container-year2002
dc.identifier.zdb2936317-2
dcterms.bibliographicCitation.originalpublishernameNorth-Holland Publ. Co.
dcterms.bibliographicCitation.originalpublisherplaceAmsterdam
bua.series.nameStochastic Programming E-Print Series
bua.series.issuenumber2000,9

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