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.

Duality and Optimality Conditions in Stochastic Optimization and Mathematical Finance / Biagini, Sara; Pennanen, Teemu; Perkio, Ari Pekka. - In: JOURNAL OF CONVEX ANALYSIS. - ISSN 0944-6532. - 25:2(2018), pp. 403-420.

Duality and Optimality Conditions in Stochastic Optimization and Mathematical Finance

BIAGINI, SARA;
2018

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.
Duality and Optimality Conditions in Stochastic Optimization and Mathematical Finance / Biagini, Sara; Pennanen, Teemu; Perkio, Ari Pekka. - In: JOURNAL OF CONVEX ANALYSIS. - ISSN 0944-6532. - 25:2(2018), pp. 403-420.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11385/173273
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