In Defense of Portfolio Optimization: What If We Can Forecast?

Allen, D; Lizieri, C; Satchell, S

In Defense of Portfolio Optimization: What If We Can Forecast?

Allen, D Lizieri, C Satchell, S

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Publication Type:: Journal Article
Citation:: Financial Analysts Journal, 2019, 75 (3), pp. 20 - 38
Issue Date:: 2019-01-01

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Field	Value	Language
dc.contributor.author	Allen, D	en_US
dc.contributor.author	Lizieri, C	en_US
dc.contributor.author	Satchell, S https://orcid.org/0000-0002-5258-762X	en_US
dc.date.issued	2019-01-01	en_US
dc.identifier.citation	Financial Analysts Journal, 2019, 75 (3), pp. 20 - 38	en_US
dc.identifier.issn	0015-198X	en_US
dc.identifier.uri	http://hdl.handle.net/10453/138827
dc.description.abstract	© 2019, © 2019, CFA Institute. We challenge the academic consensus that estimation error makes mean–variance portfolio strategies inferior to passive equal-weighted approaches. We demonstrate analytically, via simulation, and empirically that investors endowed with modest forecasting ability benefit substantially from a mean–variance approach. An investor with some forecasting ability improves expected utility by increasing the number of assets considered. We frame our study realistically using budget constraints, transaction costs, and out-of-sample testing for a wide range of investments. We derive practical decision rules to choose between passive and mean–variance optimization and generate results consistent with much financial market practice and the original Markowitz formulation.	en_US
dc.relation.ispartof	Financial Analysts Journal	en_US
dc.relation.isbasedon	10.1080/0015198X.2019.1600958	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.classification	Finance	en_US
dc.title	In Defense of Portfolio Optimization: What If We Can Forecast?	en_US
dc.type	Journal Article
utslib.citation.volume	3	en_US
utslib.citation.volume	75	en_US
utslib.for	1502 Banking, Finance and Investment	en_US
utslib.for	1501 Accounting, Auditing and Accountability	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 Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Business/Finance Discipline
utslib.copyright.status	closed_access	*
pubs.issue	3	en_US
pubs.publication-status	Published	en_US
pubs.volume	75	en_US

Abstract:

© 2019, © 2019, CFA Institute. We challenge the academic consensus that estimation error makes mean–variance portfolio strategies inferior to passive equal-weighted approaches. We demonstrate analytically, via simulation, and empirically that investors endowed with modest forecasting ability benefit substantially from a mean–variance approach. An investor with some forecasting ability improves expected utility by increasing the number of assets considered. We frame our study realistically using budget constraints, transaction costs, and out-of-sample testing for a wide range of investments. We derive practical decision rules to choose between passive and mean–variance optimization and generate results consistent with much financial market practice and the original Markowitz formulation.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/138827