Technical and Fundamental Analysis for the Forecast of Financial Scrip Quotation: An Approach Employing Artificial Neural Networks and Wavelet Transform

Authors:
Anderson Silva Soares;Maria Stela Veludo De Paiva;Clarimar José Coelho
Affiliations:
São Carlos Engineering School, Departament of Electric Engineer - University of São Paulo - Av. Trabalhador São Carlense 4000, São Carlos, Brazil;São Carlos Engineering School, Departament of Electric Engineer - University of São Paulo - Av. Trabalhador São Carlense 4000, São Carlos, Brazil;Departament of Computer Science - Catolic University of Goiás - Av. Universitária 1440, Goiânia, Brazil
Venue:
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
Year:
2007

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Abstract

This paper presents a method for predicting nonlinear time series. It is based on the multiscale filtering, fundamental and technical model and artificial neural networks. In the technical model we used wavelet transform for disjoin the time series trends then to smooth the economic time series by multiscale filtering. We used too the fundamental analysis, that is, financial and macroeconomics variables to improve the network forecasting. The results were compared with the technical analysis showing that the multiscale filtering and addition of the fundamental variables increase the network forecasting ability.