Stock Price Trend Analysis based on BP Neural Network

DOI

10.2991/ssmi-19.2019.42How to use a DOI?

Keywords

BP Neural Network; Python; Stock Prediction.

Abstract

Stock price prediction is important for investors to make investment decisions. This paper applies artificial neural network to stock forecasting, establishing a five-layer BP neural network model to predict the closing price of two stocks, the Shanghai Pudong Development Bank and China Fortune Land Development, in the empirical analysis. The results show that the model can effectively make prediction on the stock closing price and the BP neural network with three layers is feasible and effective to assist making investment decisions.

Copyright

© 2019, 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/).

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TY  - CONF
AU  - Jinke Li
PY  - 2019/12
DA  - 2019/12
TI  - Stock Price Trend Analysis based on BP Neural Network
BT  - Proceedings of the 2nd International Symposium on Social Science and Management Innovation (SSMI 2019)
PB  - Atlantis Press
SP  - 106
EP  - 114
SN  - 2352-5398
UR  - https://doi.org/10.2991/ssmi-19.2019.42
DO  - 10.2991/ssmi-19.2019.42
ID  - Li2019/12
ER  -