Chaotic Data Prediction and Its Applications in Stock Market Based on Embedding Theory and Neural Networks

Yi Wen YANG;Gui Zhong LIU;Zong Ping ZHANG

Systems Engineering - Theory & Practice ›› 2001, Vol. 21 ›› Issue (6) : 52-58.

PDF(203 KB)
PDF(203 KB)
Systems Engineering - Theory & Practice ›› 2001, Vol. 21 ›› Issue (6) : 52-58. DOI: 10.12011/1000-6788(2001)6-52
论文

Chaotic Data Prediction and Its Applications in Stock Market Based on Embedding Theory and Neural Networks

  • Yi Wen YANG,Gui Zhong LIU,Zong Ping ZHANG
Author information +
History +

Abstract

This paper provides a method for predicting chaotic data with combining embedding theory and artificial neural networks. We discuss methods for calculating embedding dimension and embedding time delay and, from the view of signal processing, analyze the relationship between phase space reconstruction and prediction, with which the structure of the input layer of neural networks can be determined.Stock market prediction is implemented with the method provided here.The result showed that this method is widely...

Key words

phase space reconstruction / neural networks / prediction

Cite this article

Download Citations
Yi Wen YANG , Gui Zhong LIU , Zong Ping ZHANG. Chaotic Data Prediction and Its Applications in Stock Market Based on Embedding Theory and Neural Networks. Systems Engineering - Theory & Practice, 2001, 21(6): 52-58 https://doi.org/10.12011/1000-6788(2001)6-52
PDF(203 KB)

391

Accesses

0

Citation

Detail

Sections
Recommended

/