• DocumentCode
    3321057
  • Title

    Application of Artificial Neural Network to Predict Short-Term Capital Flow

  • Author

    Wang, Xiping

  • Author_Institution
    Dept. of Econ. & Manage., North China Electr. Power Univ., Baoding, China
  • fYear
    2009
  • fDate
    28-29 Dec. 2009
  • Firstpage
    124
  • Lastpage
    127
  • Abstract
    The last decade witnessed a significant increase in net private capital inflows in China. Some of them are short-term capital flows, which are typically considered to be highly volatile. For effectively forecasting the short-term capital flows, a three-layered neural feedforward network was employed in this paper. In light of the weakness of the conventional Back-Propagation algorithm, the Levenberg-Marquardt algorithm was used to train the neural network. The simulation results indicate that the predictive model can be used to carry out the prediction of short-term capital flow.
  • Keywords
    backpropagation; feedforward neural nets; finance; Levenberg-Marquardt algorithm; artificial neural network; backpropagation algorithm; short-term capital flow prediction; Application software; Artificial neural networks; Backpropagation algorithms; Biological neural networks; Biological system modeling; Computer network management; Computer science; Crisis management; Neural networks; Predictive models; Back-Propagation algorithm; Levenberg-Marquardt algorithm; artificial neural network; predicting; short-term capital flow;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Research Challenges in Computer Science, 2009. ICRCCS '09. International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-0-7695-3927-0
  • Electronic_ISBN
    978-1-4244-5410-5
  • Type

    conf

  • DOI
    10.1109/ICRCCS.2009.39
  • Filename
    5401311