Title :
Intelligent System for Portfolio Selection
Author :
Hermenegildo Costa Silva, Andre ; Soares Lacerda, Wilian
Author_Institution :
Univ. Fed. de Minas Gerais (UFMG), Belo Horizonte, Brazil
Abstract :
The aim of this paper was to develop an intelligent system for portfolio selection that assists the investor in selecting assets for the composition of an optimal portfolio of investments. It was built a variation of the Markowitz Model, where the forecast price is reported by a predictor, using the Support Vector Machines (SVM) technique. The SVMs obtained an average prediction error of 7.13% and a standard deviation of 2.88%, which shows that most of SVMs performed good predictions about the data set.
Keywords :
economic forecasting; investment; pricing; support vector machines; Markowitz Model; SVM technique; asset selection; forecast price; intelligent system; investments; portfolio selection; support vector machines technique; Intelligent systems; Kernel; Media; Portfolios; Predictive models; RNA; Support vector machines; forecasting financial series; markowitz model; portfolio selection; support vector machines;
Journal_Title :
Latin America Transactions, IEEE (Revista IEEE America Latina)
DOI :
10.1109/TLA.2014.7014526
