Proceedings of the 2015 4th International Conference on Computer, Mechatronics, Control and Electronic Engineering

Research on the Application of Data Mining Technology in Stock Market Development Prediction

Authors
WenJing Gong
Corresponding Author
WenJing Gong
Available Online November 2015.
DOI
10.2991/iccmcee-15.2015.260How to use a DOI?
Keywords
Data Mining, Stock Prediction, Clustering, Neural Network
Abstract

The stock market is an important part of the securities industry and financial industry essential, universal attention by investors. Effective stock prediction plays an important role in the field of financial investment, so on the stock price of analysis and prediction has a very important theoretical significance and practical value. Based on data mining technology, this paper analyzes and predicts the trend of stock market. The goal is to establish a forecasting model using neural network in data mining, and to seek the combination of data mining algorithm and stock forecast through the analysis of the forecast process and the forecast results.

Copyright
© 2015, 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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Volume Title
Proceedings of the 2015 4th International Conference on Computer, Mechatronics, Control and Electronic Engineering
Series
Advances in Engineering Research
Publication Date
November 2015
ISBN
978-94-6252-110-0
ISSN
2352-5401
DOI
10.2991/iccmcee-15.2015.260How to use a DOI?
Copyright
© 2015, 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/).

Cite this article

TY  - CONF
AU  - WenJing Gong
PY  - 2015/11
DA  - 2015/11
TI  - Research on the Application of Data Mining Technology in Stock Market Development Prediction
BT  - Proceedings of the 2015 4th International Conference on Computer, Mechatronics, Control and Electronic Engineering
PB  - Atlantis Press
SP  - 1383
EP  - 1386
SN  - 2352-5401
UR  - https://doi.org/10.2991/iccmcee-15.2015.260
DO  - 10.2991/iccmcee-15.2015.260
ID  - Gong2015/11
ER  -