Portfolio Optimization Under Partial Information With Expert Opinions
AbstractThis 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by World Scientific Publishing Co. Pte. Ltd. in its journal International Journal of Theoretical and Applied Finance.
Volume (Year): 15 (2012)
Issue (Month): 01 ()
Contact details of provider:
Web page: http://www.worldscinet.com/ijtaf/ijtaf.shtml
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- R\"udiger Frey & Ralf Wunderlich, 2013. "Dynamic Programming Equations for Portfolio Optimization under Partial Information with Expert Opinions," Papers 1303.2513, arXiv.org.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Tai Tone Lim).
If references are entirely missing, you can add them using this form.