Mean-variance versus full-scale optimization: Broad evidence for the UK
(2008) In Manchester School 76(s1). p.134-156- Abstract
- Portfolio choice by full-scale optimization applies the empirical return distribution to a parameterized utility function, and the maximum is found through numerical optimization. Using a portfolio choice setting of three UK equity indices we identify several utility functions featuring loss aversion and prospect theory, under which full-scale optimization is a substantially better approach than the mean-variance approach. As the equity indices have return distributions with small deviations from normality, the findings indicate much broader usefulness of full-scale optimization than has earlier been shown. The results hold in- and out-of-sample, and the performance improvements are given in terms of utility as well as certainty... (More)
- Portfolio choice by full-scale optimization applies the empirical return distribution to a parameterized utility function, and the maximum is found through numerical optimization. Using a portfolio choice setting of three UK equity indices we identify several utility functions featuring loss aversion and prospect theory, under which full-scale optimization is a substantially better approach than the mean-variance approach. As the equity indices have return distributions with small deviations from normality, the findings indicate much broader usefulness of full-scale optimization than has earlier been shown. The results hold in- and out-of-sample, and the performance improvements are given in terms of utility as well as certainty equivalents. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1246876
- author
- Hagstroemer, Bjorn ; Anderson, Richard G. ; Binner, Jane M. ; Elger, Thomas LU and Nilsson, Birger LU
- organization
- publishing date
- 2008
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Manchester School
- volume
- 76
- issue
- s1
- pages
- 134 - 156
- publisher
- Wiley-Blackwell
- external identifiers
-
- wos:000259038600007
- scopus:49749105257
- ISSN
- 1463-6786
- DOI
- 10.1111/j.1467-9957.2008.01084.x
- language
- English
- LU publication?
- yes
- id
- c0300b33-a38f-44c8-8a33-419790e38482 (old id 1246876)
- date added to LUP
- 2016-04-01 11:47:55
- date last changed
- 2022-01-26 18:24:33
@article{c0300b33-a38f-44c8-8a33-419790e38482,
abstract = {{Portfolio choice by full-scale optimization applies the empirical return distribution to a parameterized utility function, and the maximum is found through numerical optimization. Using a portfolio choice setting of three UK equity indices we identify several utility functions featuring loss aversion and prospect theory, under which full-scale optimization is a substantially better approach than the mean-variance approach. As the equity indices have return distributions with small deviations from normality, the findings indicate much broader usefulness of full-scale optimization than has earlier been shown. The results hold in- and out-of-sample, and the performance improvements are given in terms of utility as well as certainty equivalents.}},
author = {{Hagstroemer, Bjorn and Anderson, Richard G. and Binner, Jane M. and Elger, Thomas and Nilsson, Birger}},
issn = {{1463-6786}},
language = {{eng}},
number = {{s1}},
pages = {{134--156}},
publisher = {{Wiley-Blackwell}},
series = {{Manchester School}},
title = {{Mean-variance versus full-scale optimization: Broad evidence for the UK}},
url = {{http://dx.doi.org/10.1111/j.1467-9957.2008.01084.x}},
doi = {{10.1111/j.1467-9957.2008.01084.x}},
volume = {{76}},
year = {{2008}},
}