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Mathematical Problems in Engineering
Volume 2015, Article ID 957893, 14 pages
http://dx.doi.org/10.1155/2015/957893
Research Article

Model to Estimate Monthly Time Horizons for Application of DEA in Selection of Stock Portfolio and for Maintenance of the Selected Portfolio

Institute of Production Engineering and Management, Federal University of Itajubá, 37500-903 Itajubá, MG, Brazil

Received 24 March 2015; Revised 10 June 2015; Accepted 25 June 2015

Academic Editor: Yan-Jun Liu

Copyright © 2015 José Claudio Isaias et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

In the selecting of stock portfolios, one type of analysis that has shown good results is Data Envelopment Analysis (DEA). It, however, has been shown to have gaps regarding its estimates of monthly time horizons of data collection for the selection of stock portfolios and of monthly time horizons for the maintenance of a selected portfolio. To better estimate these horizons, this study proposes a model of mathematical programming binary of minimization of square errors. This model is the paper’s main contribution. The model’s results are validated by simulating the estimated annual return indexes of a portfolio that uses both horizons estimated and of other portfolios that do not use these horizons. The simulation shows that portfolios with both horizons estimated have higher indexes, on average 6.99% per year. The hypothesis tests confirm the statistically significant superiority of the results of the proposed mathematical model’s indexes. The model’s indexes are also compared with portfolios that use just one of the horizons estimated; here the indexes of the dual-horizon portfolios outperform the single-horizon portfolios, though with a decrease in percentage of statistically significant superiority.