A Review of Using Support Vector Machine Theory to Do Stock Forecasting

DOI

10.2991/ncce-18.2018.184How to use a DOI?

Keywords

statistical learning theory; Support vector machine (SVM); Stock prediction.

Abstract

support vector machine (SVM) is developed based on statistical learning theory new method, its training algorithm is essentially a problem of solving the quadratic programming. This paper summarizes the basic principle of SVM, and then use SVM to stock prediction research status at home and abroad were reviewed, analyzed using SVM analysis, stock price, stock index also simple analysis of financial condition, finally, the existing problems and development trend in this field were discussed.

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  - Meizhen Liu
AU  - Chunmei Duan
PY  - 2018/05
DA  - 2018/05
TI  - A Review of Using Support Vector Machine Theory to Do Stock Forecasting
BT  - Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)
PB  - Atlantis Press
SP  - 1094
EP  - 1096
SN  - 1951-6851
UR  - https://doi.org/10.2991/ncce-18.2018.184
DO  - 10.2991/ncce-18.2018.184
ID  - Liu2018/05
ER  -