Optimal Portfolio Choice under Hidden Regime Switching Model

DOI

10.2991/wrarm-17.2017.43How to use a DOI?

Keywords

Portfolio choice; hidden regime switching; stochastic control methods; Monte Carlo simulation

Abstract

We investigate a portfolio optimization problem in a continuous-time Markov-modulated financial market. The unobservable mean return of a risky asset follows a continuous-time, two-state Markov chain whose states are interpreted as different states of market. Using results from filter theory, we reduce this problem to one with complete observation. We solve the problem by stochastic control methods and the optimal portfolio can be explicitly characterized by stochastic integrals. The Monte Carlo simulations are implemented to compute the optimal portfolio allocations. The results show that state uncertainty have a great influence on optimal portfolio choice. The parameter uncertainty prompts the investor to hedge against unanticipated changes in the state variables.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zhiying Chen
AU  - Xuanhua Peng
AU  - Yongkui Li
PY  - 2017/11
DA  - 2017/11
TI  - Optimal Portfolio Choice under Hidden Regime Switching Model
BT  - Proceedings of the Fifth Symposium of Risk Analysis and Risk Management in Western China (WRARM 2017)
PB  - Atlantis Press
SP  - 244
EP  - 249
SN  - 1951-6851
UR  - https://doi.org/10.2991/wrarm-17.2017.43
DO  - 10.2991/wrarm-17.2017.43
ID  - Chen2017/11
ER  -