A hybrid model for s&p500 index forecasting

Authors:
Ricardo de A. Araújo;Adriano L. I. Oliveira;Silvio R. L. Meira
Affiliations:
Informatics Center, Federal University of Pernambuco, Recife, PE, Brazil,Informatics Department, Federal Institute of Sertão Pernambucano, Ouricuri, PE, Brazil;Informatics Center, Federal University of Pernambuco, Recife, PE, Brazil;Informatics Center, Federal University of Pernambuco, Recife, PE, Brazil
Venue:
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part II
Year:
2012

Citing 3
Cited 0

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Abstract

This paper presents a morphological-linear model, called the dilation-erosion-linear perceptron (DELP), for financial forecasting. It consists of a hybrid model composed of morphological operators under context of lattice theory and a linear operator. A gradient-based method is presented to design the proposed DELP (learning process). Also, it is included an automatic phase fix procedure to adjust time phase distortions observed in financial phenomena. Furthermore, an experimental analysis is conducted with the proposed model using the S&P500 Index, where five well-known performance metrics and an evaluation function are used to assess the forecasting performance.