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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 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)

Identiferoai:union.ndltd.org:VIENNA/oai:epub.wu-wien.ac.at:3844
Date January 2012
CreatorsFrey, RĂĽdiger, Gabih, Abdelali, Wunderlich, Ralf
PublisherWorld Scientific Publishing
Source SetsWirtschaftsuniversität Wien
LanguageEnglish
Detected LanguageEnglish
TypeArticle, PeerReviewed
Formatapplication/pdf
Relationhttp://dx.doi.org/10.1142/S0219024911006486, http://www.worldscientific.com/, http://epub.wu.ac.at/3844/

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