Duality and optimality conditions in stochastic optimization and mathematical finance

Sara Biagini; Teemu Pennanen; Ari-Pekka Perkkio

Duality and optimality conditions in stochastic optimization and mathematical finance

Sara Biagini, Teemu Pennanen, Ari-Pekka Perkkio

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5 Citations (Scopus)

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Abstract

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.

Original language	English
Pages (from-to)	403-420
Journal	JOURNAL OF CONVEX ANALYSIS
Volume	25
Issue number	2
Publication status	Published - Apr 2018

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title = "Duality and optimality conditions in stochastic optimization and mathematical finance",

abstract = "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.",

author = "Sara Biagini and Teemu Pennanen and Ari-Pekka Perkkio",

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T1 - Duality and optimality conditions in stochastic optimization and mathematical finance

AU - Biagini, Sara

AU - Pennanen, Teemu

AU - Perkkio, Ari-Pekka

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N2 - 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.

AB - 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.

M3 - Article

SN - 0944-6532

VL - 25

SP - 403

EP - 420

JO - JOURNAL OF CONVEX ANALYSIS

JF - JOURNAL OF CONVEX ANALYSIS

IS - 2

ER -

Duality and optimality conditions in stochastic optimization and mathematical finance

Abstract

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