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Robust optimization approaches to single period portfolio allocation problem

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Gulpinar, Nalan and Hu, Zhezhi (2016) Robust optimization approaches to single period portfolio allocation problem. In: Doumpos , Michael and Zopounidis , Constantin and Grigoroudis , Evangelos , (eds.) Robustness Analysis in Decision Aiding, Optimization, and Analytics. International Series in Operations Research & Management Science, 241 . Springer, pp. 265-283. ISBN 9783319331195

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Official URL: http://dx.doi.org/10.1007/978-3-319-33121-8_12

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Abstract

Portfolio management is one of the fundamental problems in financial decision making. In a typical portfolio management problem, an investor is concerned with an optimal allocation of the capital among a number of available financial assets to maximize the return on the investment while minimizing the risk. This problem was formulated in the mean-variance portfolio management framework proposed by Markowitz in 1952. Since then, it has been widely studied by researchers and the practitioners. However, the solution is sensitive to model parameters due to data uncertainty. In this chapter, we review robust approaches to deal with data uncertainty for a single-period portfolio allocation problem. We first introduce the main ideas of robust optimization using symmetric and asymmetric uncertainty sets where the uncertain asset returns belong to. We then focus on data driven and distributionally robust optimization approaches.

Item Type: Book Item
Divisions: Faculty of Social Sciences > Warwick Business School > Operational Research & Management Sciences
Faculty of Social Sciences > Warwick Business School
Series Name: International Series in Operations Research & Management Science
Publisher: Springer
ISBN: 9783319331195
ISSN: 0884-8289
Book Title: Robustness Analysis in Decision Aiding, Optimization, and Analytics
Editor: Doumpos , Michael and Zopounidis , Constantin and Grigoroudis , Evangelos
Official Date: July 2016
Dates:
DateEvent
July 2016Published
Volume: 241
Page Range: pp. 265-283
DOI: 10.1007/978-3-319-33121-8_12
Status: Peer Reviewed
Publication Status: Published

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