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Soares, A.S. A Technique of Economic Time Series Prediction by Arti cial Neural Network and Wavelet Transform: Joining Technical and Fundamental Model. 2007. Thesis (Masters Thesis) São Carlos Engineer School, University of São Paulo, São Carlos, 2007. This work presents a method for predicting nonlinear economic time series. The method is based on fundamental and technical analysis of script quotation, a multiscale wavelet ltering, pattern selection and arti cial neural networks. In the technical model is used the wavelet transform in order to lter the economic time series from random or not economic behaviors. After the data ltering, the successive projections algorithm was used for the training pattern selection to the arti cial neural network. In the fundamentalist model is used nancial and macroeconomics variables that is correlated with the time serie in order to improve the network forecasting. For the evaluation of the proposed method are used temporal series data related to scrips prices quotation of São Paulo stock market. It presents a comparison of the results between technical model, mathematical model and proposed method. The mathematical model (ARIMA) presented better results in series with few variance, however have low performance when compared with the technical model and with the proposed method. The prediction error evaluation shows that the proposed method has better results than the other methods.

Predição de séries temporais econômicas por meio de redes neurais artificiais e transformada Wavelet: combinando modelo técnico e fundamentalista