Research on Stock Prediction in China based on Social Network and SVM Algorithm

DOI

10.2991/icedem-18.2018.108How to use a DOI?

Keywords

Social Network; Stock Prediction; Support Vector Machine (SVM); Regression

Abstract

To some extent, the information from social network can have an impact on the investment decisions of people. Based on behavioral finance theory, this thesis focuses on the influence of social networks on the stock market and forecast the stock price. Firstly, it collects data from the social network platform, and explores the relationship between social network information and stock trading volume and stock fluctuations. Secondly by means of SVM algorithm, then a stock price forecasting model is established to predict the stock price, which verifies that there is a positive correlation between stock market and social network information. Finally, the experimental results prove that the accuracy of SVM algorithm is high.

Copyright

© 2018, 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  - Li Tang
AU  - Shuhua Zhang
AU  - Li He
AU  - Huiyu Fan
PY  - 2018/12
DA  - 2018/12
TI  - Research on Stock Prediction in China based on Social Network and SVM Algorithm
BT  - Proceedings of the 2018 2nd International Conference on Economic Development and Education Management (ICEDEM 2018)
PB  - Atlantis Press
SP  - 435
EP  - 438
SN  - 2352-5398
UR  - https://doi.org/10.2991/icedem-18.2018.108
DO  - 10.2991/icedem-18.2018.108
ID  - Tang2018/12
ER  -