Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/59792
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Type: Journal article
Title: On mean-variance portfolio selection under a hidden Markovian regime-switching model
Author: Elliott, R.
Siu, T.
Badescu, A.
Citation: Economic Modelling, 2010; 27(3):678-686
Publisher: Elsevier Science BV
Issue Date: 2010
ISSN: 0264-9993
1873-6122
Statement of
Responsibility: 
Robert J. Elliott, Tak Kuen Siu and Alex Badescu
Abstract: We study a mean-variance portfolio selection problem under a hidden Markovian regime-switching Black-Scholes-Merton economy. Under this model, the appreciation rate of a risky share is modulated by a continuous-time, finite-state hidden Markov chain whose states represent different states of an economy. We consider the general situation where an economic agent cannot observe the "true" state of the underlying economy and wishes to minimize the variance of the terminal wealth for a fixed level of expected terminal wealth with access only to information about the price processes. By exploiting the separation principle, we discuss the mean-variance portfolio selection problem and the filtering-estimation problem separately. We determine an explicit solution to the mean-variance problem using the stochastic maximum principle so that we do not need the assumption of Markovian controls. We also provide robust estimates of the hidden state of the chain and develop a robust filter-based EM algorithm for online recursive estimates of the unknown parameters in the model. This simplifies the filtering-estimation problem. © 2010 Elsevier B.V. All rights reserved.
Keywords: Mean-variance portfolio selection
Hidden Markov chain
Separation principle
Stochastic maximum principle
Partial observations
Reference probability
Zakai's equation
Gauge transformation
Robust filters
EM algorithm
Rights: © 2010 Elsevier B.V. All rights reserved.
DOI: 10.1016/j.econmod.2010.01.007
Published version: http://dx.doi.org/10.1016/j.econmod.2010.01.007
Appears in Collections:Aurora harvest
Mathematical Sciences publications

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