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2010-08-25Buch DOI: 10.18452/8411
Convex duality in stochastic programming and mathematical finance
dc.contributor.authorPennanen, Teemu
dc.contributor.editorHigle, Julie L.
dc.contributor.editorRömisch, Werner
dc.contributor.editorSen, Surrajeet
dc.date.accessioned2017-06-16T20:23:06Z
dc.date.available2017-06-16T20:23:06Z
dc.date.created2010-08-26
dc.date.issued2010-08-25
dc.date.submitted2010-06-20
dc.identifier.urihttp://edoc.hu-berlin.de/18452/9063
dc.description.abstractThis paper proposes a general duality framework for the problem of minimizing a convex integral functional over a space of stochastic processes adapted to a given filtration. The framework unifies many well-known duality frameworks from operations research and mathematical finance. The unification allows the extension of some useful techniquesfrom these two fields to a much wider class of problems. In particular, combining certain finite-dimensional techniques from convex analysis with measure theoretic techniques from mathematical finance, we are able to close the duality gap in some situations where traditional topological arguments fail.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, Institut für Mathematik
dc.subject.ddc510 Mathematik
dc.titleConvex duality in stochastic programming and mathematical finance
dc.typebook
dc.identifier.urnurn:nbn:de:kobv:11-100174221
dc.identifier.doihttp://dx.doi.org/10.18452/8411
local.edoc.container-titleStochastic Programming E-Print Series
local.edoc.pages32
local.edoc.type-nameBuch
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
local.edoc.container-volume2010
local.edoc.container-issue4
local.edoc.container-erstkatid2936317-2

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