On mean-variance portfolio selection under a hidden Markovian regime-switching model

被引:56
|
作者
Elliott, Robert J. [1 ,2 ]
Siu, Tak Kuen [3 ]
Badescu, Alex [4 ]
机构
[1] Univ Calgary, Haskayne Sch Business, Calgary, AB T2N 1N4, Canada
[2] Univ Adelaide, Sch Math Sci, Adelaide, SA 5005, Australia
[3] Macquarie Univ, Fac Business & Econ, Dept Actuarial Studies, Sydney, NSW 2109, Australia
[4] Univ Calgary, Dept Math & Stat, Calgary, AB T2N 1N4, Canada
基金
澳大利亚研究理事会; 加拿大自然科学与工程研究理事会;
关键词
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; PARAMETER-ESTIMATION; TIME; EQUILIBRIUM; INFORMATION; VALUATION; FILTERS;
D O I
10.1016/j.econmod.2010.01.007
中图分类号
F [经济];
学科分类号
02 ;
摘要
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. (C) 2010 Elsevier B.V. All rights reserved.
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页码:678 / 686
页数:9
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