Asset management using an extended Markowitz theorem

Markowitz theorem is one of the most popular techniques for asset management. The method has been widely used to solve many applications, successfully. In this paper, we present a multi objective Markowitz model to determine asset allocation by considering cardinality constraints. The resulted model...

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Main Author: Paria Karimi
Format: Article
Language:English
Published: Growing Science 2014-06-01
Series:Management Science Letters
Subjects:
Online Access:http://www.growingscience.com/msl/Vol4/msl_2014_114.pdf
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author Paria Karimi
author_facet Paria Karimi
author_sort Paria Karimi
collection DOAJ
description Markowitz theorem is one of the most popular techniques for asset management. The method has been widely used to solve many applications, successfully. In this paper, we present a multi objective Markowitz model to determine asset allocation by considering cardinality constraints. The resulted model is an NP-Hard problem and the proposed study uses two metaheuristics, namely genetic algorithm (GA) and particle swarm optimization (PSO) to find efficient solutions. The proposed study has been applied on some data collected from Tehran Stock Exchange over the period 2009-2011. The study considers four objectives including cash return, 12-month return, 36-month return and Lower Partial Moment (LPM). The results indicate that there was no statistical difference between the implementation of PSO and GA methods.
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series Management Science Letters
spelling doaj-art-5a324a4d94b34986bf6780181bf0e4e32025-08-20T01:57:25ZengGrowing ScienceManagement Science Letters1923-29341923-93432014-06-01461309131410.5267/j.msl.2014.4.011Asset management using an extended Markowitz theoremParia KarimiMarkowitz theorem is one of the most popular techniques for asset management. The method has been widely used to solve many applications, successfully. In this paper, we present a multi objective Markowitz model to determine asset allocation by considering cardinality constraints. The resulted model is an NP-Hard problem and the proposed study uses two metaheuristics, namely genetic algorithm (GA) and particle swarm optimization (PSO) to find efficient solutions. The proposed study has been applied on some data collected from Tehran Stock Exchange over the period 2009-2011. The study considers four objectives including cash return, 12-month return, 36-month return and Lower Partial Moment (LPM). The results indicate that there was no statistical difference between the implementation of PSO and GA methods.http://www.growingscience.com/msl/Vol4/msl_2014_114.pdfMarkowitz TheoremTehran Stock ExchangeGenetic algorithmParticle Swarm optimization
spellingShingle Paria Karimi
Asset management using an extended Markowitz theorem
Management Science Letters
Markowitz Theorem
Tehran Stock Exchange
Genetic algorithm
Particle Swarm optimization
title Asset management using an extended Markowitz theorem
title_full Asset management using an extended Markowitz theorem
title_fullStr Asset management using an extended Markowitz theorem
title_full_unstemmed Asset management using an extended Markowitz theorem
title_short Asset management using an extended Markowitz theorem
title_sort asset management using an extended markowitz theorem
topic Markowitz Theorem
Tehran Stock Exchange
Genetic algorithm
Particle Swarm optimization
url http://www.growingscience.com/msl/Vol4/msl_2014_114.pdf
work_keys_str_mv AT pariakarimi assetmanagementusinganextendedmarkowitztheorem