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.
2018
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.
File in questo prodotto:
File Dimensione Formato  
duality-II -last.pdf

Solo gestori archivio

Descrizione: Articolo principale
Tipologia: Documento in Pre-print
Licenza: DRM (Digital rights management) non definiti
Dimensione 350.97 kB
Formato Adobe PDF
350.97 kB Adobe PDF   Visualizza/Apri
11385-173273.pdf

Solo gestori archivio

Tipologia: Versione dell'editore
Licenza: DRM (Digital rights management) non definiti
Dimensione 5.44 MB
Formato Adobe PDF
5.44 MB Adobe PDF   Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11385/173273
Citazioni
  • Scopus 5
  • ???jsp.display-item.citation.isi??? 4
social impact