Title
Robust portfolio optimization: a categorized bibliographic review
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.
Year
DOI
Venue
2020
10.1007/s10479-020-03630-8
Annals of Operations Research
Keywords
DocType
Volume
Robust mathematical programming, Portfolio selection, Bibliographic review
Journal
292
Issue
ISSN
Citations 
1
0254-5330
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Panos Xidonas100.34
Ralph E. Steuer2922137.35
Christis Hassapis3121.26