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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/11427

Title: A Heuristic Crossover for Portfolio Selection
Authors: Ackora-Prah, Joseph
Gyamerah, Samuel Asante
Andam, Perpetual Saah
Keywords: Portfolio Selection
Genetic Algorithm
Heuristic Crossover
Issue Date: 2014
Publisher: Applied Mathematical Sciences
Citation: Applied Mathematical Sciences, Vol. 8, 2014, no. 65, 3215 - 3227; http://dx.doi.org/10.12988/ams.2014.43203
Abstract: We propose the suitability of Heuristic Crosover in Genetic Algo- rithm (GA) for the selection of an optimal portfolio of stocks from the Ghana Stock Exchange. The appropriate choice of an optimal port- folio is the principal problem of both the portfolio manager and the investor. In this paper, we formulate a model which includes practical constraints ( oor-ceil and cardinality constraints) which the Markowitz unconstrained Mean-Variance method does not consider in the selec- tion of optimal portfolio. We use heuristic crossover to optimize the risk-return trade-o and achieve an optimal solution for the portfolio selection and the allocation of weights to each portfolio.
Description: An article published in Applied Mathematical Sciences, Vol. 8, 2014, no. 65, 3215 - 3227; http://dx.doi.org/10.12988/ams.2014.43203
URI: http://hdl.handle.net/123456789/11427
Appears in Collections:College of Science

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