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2015 | OriginalPaper | Chapter

Improving Financial Time Series Prediction Through Output Classification by a Neural Network Ensemble

Authors : Felipe Giacomel, Adriano C. M. Pereira, Renata Galante

Published in: Database and Expert Systems Applications

Publisher: Springer International Publishing

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Abstract

One topic of great interest in the literature is time series prediction. This kind of prediction, however, does not have to provide the exact future values every time: in some cases, knowing only time series future tendency is enough. In this paper, we propose a neural network ensemble that receives as input the last values from a time series and returns not its future values, but a prediction that indicates whether the next value will raise or fall down. We perform exhaustive experiments to analyze our method by using time series extracted from the North American stock market, and evaluate the hit rate and amount of profit that could be obtained by performing the operations recommended by the system. Evaluation results show capital increases up to 56 %.

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Metadata
Title
Improving Financial Time Series Prediction Through Output Classification by a Neural Network Ensemble
Authors
Felipe Giacomel
Adriano C. M. Pereira
Renata Galante
Copyright Year
2015
DOI
https://doi.org/10.1007/978-3-319-22852-5_28

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