Computer Science ›› 2018, Vol. 45 ›› Issue (6A): 75-78.

• Intelligent Computing • Previous Articles     Next Articles

Modeling and Decision-making of Futures Market Price Prediction with DBN

CHEN Jun-hua, HAO Yan-hui,ZHENG Ding-wen, CHEN Si-yu   

  1. School of Management Science and Engineering,Central University of Finance and Economics,Beijing 100081,China
  • Online:2018-06-20 Published:2018-08-03

Abstract: The deep learning algorithm can realize the approximation of complex functions by learning the deep nonliner network structure,and it can learn the essential characterstics of data sets from a large number of unlabeled samples.Deep belief network (DBN) is a model of deep learning,which is a Bayesian probability generation model composed of multi-layer random hidden variables.DBN can be used as a pre-training link for deep neural networks,providing initial weight for the network.This learning algorithm not only solves the problem of slow training,but also produces very good initial parameters,greatly enhances the model's modeling capabilities.The financial market is a multi-variable and nonlinear system.The DBN model can solve the problems like initial weights and so on,that other prediction methods are difficult to analyze and predict.This paper used oil futures market price forecast as an example,to prove the feasibi-lity of using DBN model to predict futures market price.

Key words: DBN algorithm, Deep learning, Futures market

CLC Number: 

  • TP181
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