Paper Info
Title
An iterative method for solving a bi-objective constrained portfolio optimization problem.
Abstract
In this work, we consider the problem of portfolio optimization under cardinality and quantity constraints. We use the standard model of mean-variance in its bi-objective form which is presented here as a bi-objective quadratic programming problem under cardinality and quantity constraints. This problem is NP-hard, which is why the majority of methods proposed in the literature use metaheuristics for its resolution. In this paper, we propose an iterative method for solving constrained portfolio optimization problems. Experiments are performed with major market indices, such as the Hang Seng, DAX, FTSE, S&P 100, Nikkei, S&P 500 and Nasdaq using real-world datasets involving up to 2196 assets. Comparisons with two exact methods and a metaheuristic are performed. These results show that the new method allows to find efficient portfolio fronts in reasonable time.
Year
DOI
Venue
2019
10.1007/s10589-018-0052-9
Comp. Opt. and Appl.
Keywords
Field
DocType
Cardinality and quantity constraints, Cardinality portfolio selection, Bi-objective programming, Mixed integer programming, Steepest descent method, Pascoletti–Serafini method, 90C29, 90C90, 90C11, 90B50, 91B28
Mathematical optimization,Method of steepest descent,Iterative method,Cardinality,Portfolio,Integer programming,Portfolio optimization,Quadratic programming,Mathematics,Metaheuristic
Journal
Volume
Issue
ISSN
72
2
1573-2894
Citations 
PageRank 
References 
0
0.34
15
Authors
4
Name
Order
Citations
PageRank
Madani Bezoui183.56
Mustapha Moulaï2123.11
Ahcène Bounceur330635.05
Reinhardt Euler49528.50