Markov chain portfolio liquidity optimization model

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Published: May 1, 2014
DOI: https://doi.org/10.14807/ijmp.v5i2.156
Keywords:
Portfolio Optimization Markov chain Genetic Algorithms

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Eder Oliveira Abensur
Universidade Federal do ABC (UFABC)

Abstract

The international financial crisis of September 2008 and May 2010 showed the importance of liquidity as an attribute to be considered in portfolio decisions. This study proposes an optimization model based on available public data, using Markov chain and Genetic Algorithms concepts as it considers the classic duality of risk versus return and incorporating liquidity costs. The work intends to propose a multi-criterion non-linear optimization model using liquidity based on a Markov chain. The non-linear model was tested using Genetic Algorithms with twenty five Brazilian stocks from 2007 to 2009. The results suggest that this is an innovative development methodology and useful for developing an efficient and realistic financial portfolio, as it considers many attributes such as risk, return and liquidity.

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Article Details

Issue
Vol. 5 No. 2 (2014): Independent Journal of Management & Production
Section
Articles

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Author Biography

Eder Oliveira Abensur, Universidade Federal do ABC (UFABC)

Eder Oliveira Abensur, PHD, Universidade Federal do ABC (UFABC), Santo André, SP, Brazil

Currently professor of Operations Research and Economics Engineering of the course of Production Engineering

email: eder.abensur@ufabc.edu.br

Tel: 55 11 99239-5021
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