An algebraic approach to integer portfolio problems

Integer variables allow the treatment of some portfolio optimization problems in a more realistic way and introduce the possibility of adding some natural features to the model. We propose an algebraic approach to maximize the expected return under a given admissible level of risk measured by the co...

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Bibliographic Details
Published in:European journal of operational research Vol. 210; no. 3; pp. 647 - 659
Main Authors: Castro, F., Gago, J., Hartillo, I., Puerto, J., Ucha, J.M.
Format: Journal Article
Language:English
Published: Amsterdam Elsevier B.V 01.05.2011
Elsevier
Elsevier Sequoia S.A
Series:European Journal of Operational Research
Subjects:
Algebra
Applied sciences
Exact sciences and technology
Expected returns
Finance
Finance Portfolio Non-linear integer programming Grobner bases
Gröbner bases
Integer programming
Integers
Mathematical analysis
Mathematical models
Non-linear integer programming
Operational research
Operational research and scientific management
Operational research. Management science
Optimization
Portfolio
Portfolio theory
Risk assessment
Strategy
Studies
Test sets
Gröbner bases
Non-linear integer programming
Finance
Portfolio
Search strategy
Gröbner basis
Stock exchange
Algebraic method
Non linear programming
Covariance matrix
Portfolio management
Modeling
ISSN:0377-2217, 1872-6860
Online Access:Get full text
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Summary:Integer variables allow the treatment of some portfolio optimization problems in a more realistic way and introduce the possibility of adding some natural features to the model. We propose an algebraic approach to maximize the expected return under a given admissible level of risk measured by the covariance matrix. To reach an optimal portfolio it is an essential ingredient the computation of different test sets (via Gröbner basis) of linear subproblems that are used in a dual search strategy.
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ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2010.11.007