Improving Financial Time Series Prediction Using Exogenous Series and Neural Networks Committees

被引:0
作者
Amorim Neto, Manoel C.
Tavares, Gustavo
Alves, Victor M. O.
Cavalcanti, George D. C.
Ren, Tsang Ing
机构
来源
2010 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS IJCNN 2010 | 2010年
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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 known metrics were applied. Moreover, we also proposed one new metric called Prediction in Direction and Accuracy (PDA), which benefits models with great performance in prediction accuracy and trend. Addictionally, there was used an evolutionary algorithm to choose the best trained models that maximize PDA. Experiments with two of the most important Brazilian companies stock quotes have shown the usefulness of the proposed prediction system to generate profits in investments.
引用
收藏
页数:8
相关论文
共 10 条
  • [1] Neto MCA, 2009, IEEE IJCNN, P2578
  • [2] [Anonymous], 1982, THEORY EC DEV INQUIR
  • [3] Brockwell P.J., 1996, INTRO TIME SERIES FO
  • [4] Charkha Pritam Radheshyam, 2008, 2008 1st International Conference on Emerging Trends in Engineering and Technology (ICETET), P592, DOI 10.1109/ICETET.2008.223
  • [5] A comparative study of linear and nonlinear models for aggregate retail sales forecasting
    Chu, CW
    Zhang, GP
    [J]. INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2003, 86 (03) : 217 - 231
  • [6] De Gooijer, 1998, SOME RECENT DEV NONL
  • [7] A new intelligent system methodology for time series forecasting with artificial neural networks
    Ferreira, Tiago A. E.
    Vasconcelos, Germano C.
    Adeodato, Paulo J. L.
    [J]. NEURAL PROCESSING LETTERS, 2008, 28 (02) : 113 - 129
  • [8] Haykin S., 1992, INT J FORECASTING, V8, P135
  • [9] Reilly FrankK., 2008, INVESTMENT ANAL PORT, VNinth
  • [10] Smith, 2003, WEALTH NATIONS