A Benchmark Approach to Portfolio Optimization under Partial Information
This paper proposes a filtering methodology for portfolio optimization when some factors of the underlying model are only partially observed. The level of information is given by the observed quantities that are here supposed to be the primary securities and empirical log-price covariations. For a given level of information we determine the growth optimal portfolio, identify locally optimal portfolios that are located on a corresponding Markowitz efficient frontier and present an approach for expected utility maximization. We also present an expected utility indifference pricing approach under partial information for the pricing of nonreplicable contracts. This results in a real world pricing formula under partial information that turns out to be independent of the subjective utility of the investor and for which an equivalent risk neutral probability measure need not exist.
|Date of creation:||01 Jan 2007|
|Date of revision:|
|Publication status:||Published as: Platen, E. and Runggaldier, W., 2007, "A Benchmark Approach to Portfolio Optimization under Partial Information", Asia-Pacific Financial Markets, 14(1), 25-43.|
|Contact details of provider:|| Postal: PO Box 123, Broadway, NSW 2007, Australia|
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Web page: http://www.qfrc.uts.edu.au/
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77, Quantitative Finance Research Centre, University of Technology, Sydney.
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- Jörn Sass & Ulrich Haussmann, 2004. "Optimizing the terminal wealth under partial information: The drift process as a continuous time Markov chain," Finance and Stochastics, Springer, vol. 8(4), pages 553-577, November.
- Nicole Bäuerle & Ulrich Rieder, 2007. "Portfolio Optimization With Jumps And Unobservable Intensity Process," Mathematical Finance, Wiley Blackwell, vol. 17(2), pages 205-224.
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