Research on Stock Price Prediction Based on BP Wavelet Neural Network with Mexico Hat Wavelet Basis

DOI

10.2991/iceemr-17.2017.25How to use a DOI?

Keywords

Wavelet Neural Network, BP algorithm, Stock Price, Prediction

Abstract

In order to improve the prediction ability of stock price, a prediction method based on Wavelet Neural Network (WNN) is proposed. First BP algorithm is used to optimize the parameters of WNN with Mexico Hat wavelet basis for the establishment of the stock price prediction model, and then the built model is applied to predict the stock price movement on the basis of 15 features. The simulations on daily closing price index of SSE Composite Index indicate that, the proposed method has the advantages of simple structure, strong implementation and good prediction accuracy, and gets better stock price prediction in contrast with single neural network and genetic neural network. This verifies the feasibility and effectiveness of the method in the application of stock price prediction.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Pingan Wang
AU  - Yuanwei Lou
AU  - Lei Lei
PY  - 2017/05
DA  - 2017/05
TI  - Research on Stock Price Prediction Based on BP Wavelet Neural Network with Mexico Hat Wavelet Basis
BT  - Proceedings of the 2017 International Conference on Education, Economics and Management Research (ICEEMR 2017)
PB  - Atlantis Press
SP  - 99
EP  - 102
SN  - 2352-5398
UR  - https://doi.org/10.2991/iceemr-17.2017.25
DO  - 10.2991/iceemr-17.2017.25
ID  - Wang2017/05
ER  -