Complex portfolio selection via convex mixed‐integer quadratic programming: a survey

In this paper, we review convex mixed‐integer quadratic programming approaches to deal with single‐objective single‐period mean‐variance portfolio selection problems under real‐world financial constraints. In the first part, after describing the original Markowitz's mean‐variance model, we anal...

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Vydané v:International transactions in operational research Ročník 26; číslo 2; s. 389 - 414
Hlavní autori: Mencarelli, Luca, D'Ambrosio, Claudia
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Oxford Blackwell Publishing Ltd 01.03.2019
Wiley
Predmet:
Computer Science
Constraint modelling
convex MINLP
Convexity
Empirical analysis
exact methods
mixed‐integer quadratic programming
Operations Research
Portfolio management
portfolio selection
Probabilistic models
Quadratic programming
robust and probabilistic optimization
Variance analysis
ISSN:0969-6016, 1475-3995
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Popis
Shrnutí:In this paper, we review convex mixed‐integer quadratic programming approaches to deal with single‐objective single‐period mean‐variance portfolio selection problems under real‐world financial constraints. In the first part, after describing the original Markowitz's mean‐variance model, we analyze its theoretical and empirical limitations, and summarize the possible improvements by considering robust and probabilistic models, and additional constraints. Moreover, we report some recent theoretical convexity results for the probabilistic portfolio selection problem. In the second part, we overview the exact algorithms proposed to solve the single‐objective single‐period portfolio selection problem with quadratic risk measure.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0969-6016
1475-3995
DOI:10.1111/itor.12541