Improving financial time series prediction using exogenous series and neural networks committees

@article{Neto2010ImprovingFT,
  title={Improving financial time series prediction using exogenous series and neural networks committees},
  author={Manoel C. Amorim Neto and Gustavo Tavares and Victor M. O. Alves and George D. C. Cavalcanti and Ing Ren Tsang},
  journal={The 2010 International Joint Conference on Neural Networks (IJCNN)},
  year={2010},
  pages={1-8}
}
Time series forecasting is useful in many researches areas. The use of models that provide a reliable prediction in financial time series may bring valuable profits for the investors. This paper proposes a methodology based on information obtained from exogenous series used in combination with neural networks to predict stock series. The best trained neural networks were used in combination to improve the prediction capacity of a single networks. To evaluate the proposed prediction models, some… CONTINUE READING

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