Robust portfolio optimization: a categorized bibliographic review

Panos Xidonas (), Ralph Steuer () and Christis Hassapis ()
Additional contact information
Panos Xidonas: ESSCA Business School
Ralph Steuer: University of Georgia
Christis Hassapis: University of Cyprus

Annals of Operations Research, 2020, vol. 292, issue 1, No 21, 533-552

Abstract: Abstract Robust portfolio optimization refers to finding an asset allocation strategy whose behavior under the worst possible realizations of the uncertain inputs, e.g., returns and covariances, is optimized. The robust approach is in contrast to the classical approach, where one estimates the inputs to a portfolio allocation problem and then treats them as certain and accurate. In this paper we provide a categorized bibliography on the application of robust mathematical programming to the portfolio selection problem. With no similar surveys available, one of the aims of this review is to provide quick access for those interested, but maybe not yet in the area, so they know what the area is about, what has been accomplished and where everything can be found. Toward this end, a total of 148 references have been compiled and classified in various ways. Additionally, the number of Scopus© citations by contribution and journal is recorded. Finally, a brief discussion of the review’s major findings is provided and some solid leads on future directions are given.

Keywords: Robust mathematical programming; Portfolio selection; Bibliographic review (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (26)

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DOI: 10.1007/s10479-020-03630-8

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