Portfolio Optimization under Partial Information with Expert Opinions
This paper investigates optimal portfolio strategies in a market with partial information on the drift. The drift is modelled as a function of a continuous-time Markov chain with finitely many states which is not directly observable. Information on the drift is obtained from the observation of st...
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ndltd-VIENNA-oai-epub.wu-wien.ac.at-38442015-04-02T05:03:17Z Portfolio Optimization under Partial Information with Expert Opinions Frey, Rüdiger Gabih, Abdelali Wunderlich, Ralf portfolio optimization / hidden Markov model / dynamic programming This paper investigates optimal portfolio strategies in a market with partial information on the drift. The drift is modelled as a function of a continuous-time Markov chain with finitely many states which is not directly observable. Information on the drift is obtained from the observation of stock prices. Moreover, expert opinions in the form of signals at random discrete time points are included in the analysis. We derive the filtering equation for the return process and incorporate the filter into the state variables of the optimization problem. This problem is studied with dynamic programming methods. In particular, we propose a policy improvement method to obtain computable approximations of the optimal strategy. Numerical results are presented at the end. (author's abstract) World Scientific Publishing 2012 Article PeerReviewed en application/pdf http://epub.wu.ac.at/3844/1/Frey.pdf http://dx.doi.org/10.1142/S0219024911006486 http://www.worldscientific.com/ http://dx.doi.org/10.1142/S0219024911006486 http://epub.wu.ac.at/3844/ |
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en |
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Others
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portfolio optimization / hidden Markov model / dynamic programming
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portfolio optimization / hidden Markov model / dynamic programming
Frey, Rüdiger Gabih, Abdelali Wunderlich, Ralf Portfolio Optimization under Partial Information with Expert Opinions |
description |
This paper investigates optimal portfolio strategies in a market with partial information
on the drift. The drift is modelled as a function of a continuous-time Markov chain
with finitely many states which is not directly observable. Information on the drift is
obtained from the observation of stock prices. Moreover, expert opinions in the form
of signals at random discrete time points are included in the analysis. We derive the
filtering equation for the return process and incorporate the filter into the state variables
of the optimization problem. This problem is studied with dynamic programming
methods. In particular, we propose a policy improvement method to obtain computable
approximations of the optimal strategy. Numerical results are presented at the end. (author's abstract) |
author |
Frey, Rüdiger Gabih, Abdelali Wunderlich, Ralf |
author_facet |
Frey, Rüdiger Gabih, Abdelali Wunderlich, Ralf |
author_sort |
Frey, Rüdiger |
title |
Portfolio Optimization under Partial Information with Expert Opinions |
title_short |
Portfolio Optimization under Partial Information with Expert Opinions |
title_full |
Portfolio Optimization under Partial Information with Expert Opinions |
title_fullStr |
Portfolio Optimization under Partial Information with Expert Opinions |
title_full_unstemmed |
Portfolio Optimization under Partial Information with Expert Opinions |
title_sort |
portfolio optimization under partial information with expert opinions |
publisher |
World Scientific Publishing |
publishDate |
2012 |
url |
http://epub.wu.ac.at/3844/1/Frey.pdf http://dx.doi.org/10.1142/S0219024911006486 |
work_keys_str_mv |
AT freyrudiger portfoliooptimizationunderpartialinformationwithexpertopinions AT gabihabdelali portfoliooptimizationunderpartialinformationwithexpertopinions AT wunderlichralf portfoliooptimizationunderpartialinformationwithexpertopinions |
_version_ |
1716799915503386624 |