A Meta-heuristic Algorithm for Portfolio Selection Problem under Cardinality and Bounding Constraints

The focus of this paper is on standard Markowitz mean–variance model and its traditional approach to solve portfolio selection problem (Quadratic Planning). For this goal we have applied a meta-heuristic method based on genetic algorithms (GA) in order to trace out the efficient frontier associated...

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Bibliographic Details
Main Authors: mohammad taghi Taqavi Fard, taha Mansouri, mohsen Khosh Tinat
Format: Article
Language:fas
Published: Tarbiat Modares University 2008-01-01
Series:پژوهشهای اقتصادی
Subjects:
Online Access:http://ecor.modares.ac.ir/article-18-273-en.pdf
Description
Summary:The focus of this paper is on standard Markowitz mean–variance model and its traditional approach to solve portfolio selection problem (Quadratic Planning). For this goal we have applied a meta-heuristic method based on genetic algorithms (GA) in order to trace out the efficient frontier associated with the portfolio selection problem under cardinality and bounding constraints. These constraints ensure the investment in a given number of different assets and limit the amount of capital to be invested in each asset. We have presented some experimental results in two samples from Iranian stock market and overseas ones and compare the GA result with unconstrained quadratic results. Finally, we have found out which proposed GA can optimize portfolio selection problem under cardinality and bounded constrains
ISSN:1735-6768
2980-7832