A benchmark approach to portfolio optimization under partial information

Platen, E; Runggaldier, WJ

A benchmark approach to portfolio optimization under partial information

Platen, E

Runggaldier, WJ

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Publication Type:: Journal Article
Citation:: Asia-Pacific Financial Markets, 2007, 14 (1-2), pp. 25 - 43
Issue Date:: 2007-03-01

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Field	Value	Language
dc.contributor.author	Platen, E https://orcid.org/0000-0003-4595-3123	en_US
dc.contributor.author	Runggaldier, WJ	en_US
dc.date.issued	2007-03-01	en_US
dc.identifier.citation	Asia-Pacific Financial Markets, 2007, 14 (1-2), pp. 25 - 43	en_US
dc.identifier.issn	1387-2834	en_US
dc.identifier.uri	http://hdl.handle.net/10453/5452
dc.description.abstract	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. © 2007 Springer Science+Business Media, LLC.	en_US
dc.relation.ispartof	Asia-Pacific Financial Markets	en_US
dc.relation.isbasedon	10.1007/s10690-007-9045-x	en_US
dc.subject.classification	Finance	en_US
dc.title	A benchmark approach to portfolio optimization under partial information	en_US
dc.type	Journal Article
utslib.citation.volume	1-2	en_US
utslib.citation.volume	14	en_US
utslib.for	150201 Finance	en_US
utslib.for	1502 Banking, Finance and Investment	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
pubs.organisational-group	/University of Technology Sydney/Strength - QFRC - Quantitative Finance Research Centre
utslib.copyright.status	open_access
pubs.issue	1-2	en_US
pubs.publication-status	Published	en_US
pubs.volume	14	en_US

Abstract:

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. © 2007 Springer Science+Business Media, LLC.

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http://hdl.handle.net/10453/5452