The maximum principle for a jump-diffusion mean-field model and its application to the mean-variance problem

Yang Shen, Tak Kuen Siu*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

44 Citations (Scopus)

Abstract

This paper establishes a necessary and sufficient stochastic maximum principle for a mean-field model with randomness described by Brownian motions and Poisson jumps. We also prove the existence and uniqueness of the solution to a jump-diffusion mean-field backward stochastic differential equation. A new version of the sufficient stochastic maximum principle, which only requires the terminal cost is convex in an expected sense, is applied to solve a bicriteria mean-variance portfolio selection problem.

Original languageEnglish
Pages (from-to)58-73
Number of pages16
JournalNonlinear Analysis
Volume86
DOIs
Publication statusPublished - 2013

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