Risk sensitive control of finite state Markov chains in discrete time, with applications to portfolio management

Tomasz Bielecki, Daniel Hernández-Hernández and Stanley R. Pliska

Mathematical Methods of Operations Research, 1999, vol. 50, issue 2, 167-188

Abstract: In this paper we extend standard dynamic programming results for the risk sensitive optimal control of discrete time Markov chains to a new class of models. The state space is only finite, but now the assumptions about the Markov transition matrix are much less restrictive. Our results are then applied to the financial problem of managing a portfolio of assets which are affected by Markovian microeconomic and macroeconomic factors and where the investor seeks to maximize the portfolio's risk adjusted growth rate. Copyright Springer-Verlag Berlin Heidelberg 1999

Keywords: Key words: Risk sensitive Markov decision processes; portfolio optimization; factor modeling (search for similar items in EconPapers)
Date: 1999
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Citations: View citations in EconPapers (15)

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Persistent link: https://EconPapers.repec.org/RePEc:spr:mathme:v:50:y:1999:i:2:p:167-188

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DOI: 10.1007/s001860050094

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