A Maximum Principle for Stochastic Control with Partial Information
We study the problem of optimal control of a jump diffusion, that is, a process which is the solution of a stochastic differential equation driven by Lévy processes. It is required that the control process is adapted to a given subfiltration of the filtration generated by the underlying Lévy process...
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Published in | Stochastic analysis and applications Vol. 25; no. 3; pp. 705 - 717 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Philadelphia, PA
Taylor & Francis Group
02.05.2007
Taylor & Francis |
Subjects | |
Online Access | Get full text |
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Summary: | We study the problem of optimal control of a jump diffusion, that is, a process which is the solution of a stochastic differential equation driven by Lévy processes. It is required that the control process is adapted to a given subfiltration of the filtration generated by the underlying Lévy processes. We prove two maximum principles (one sufficient and one necessary) for this type of partial information control. The results are applied to a partial information mean-variance portfolio selection problem in finance. |
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ISSN: | 0736-2994 1532-9356 |
DOI: | 10.1080/07362990701283128 |