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Duality and optimality conditions in stochastic optimization and mathematical finance

Research output: Contribution to journalArticle

Sara Biagini, Teemu Pennanen, Ari-Pekka Perkkio

Original languageEnglish
Pages (from-to)403-420
Issue number2
Accepted/In press29 Aug 2016
PublishedApr 2018

King's Authors


This article studies convex duality in stochastic optimization over finite discrete-time. The first part of the paper gives general conditions that yield explicit expressions for the dual objective in many applications in operations research and mathematical finance. The second part derives optimality conditions by combining general saddle-point conditions from convex duality with the dual representations obtained in the first part of the paper. Several applications to stochastic optimization and mathematical finance are given.

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