Proceedings of the 2021 International Conference on Financial Management and Economic Transition (FMET 2021)

Application of SVM, Decision Tree and Logistic Regression Algorithm in Stock Classification and Prediction

Authors
Liu Xiaojie, Liao Aihong
Corresponding Author
Liao Aihong
Available Online 18 September 2021.
DOI
10.2991/aebmr.k.210917.011How to use a DOI?
Keywords
A-share market, data mining, SVM, decision tree, logistic regression
Abstract

This paper uses three data mining algorithms, support vector machine, decision tree and logical regression, to establish the stock classification prediction model. The paper compares and analyzes the prediction effect of the three models, and summarizes the relationship between the financial indicators of listed companies and their stock intrinsic investment value.The results show that: (1) among the three prediction models, logistic regression model has the best performance, followed by support vector machine model, and decision tree model has the worst performance.(2) The significant influencing factors of stock intrinsic investment value include the actual operation ability, profitability and the continuity and stability of operation. The conclusion of this paper can provide a basis for stock investors to make investment decisions.

Copyright
© 2021, 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 2021 International Conference on Financial Management and Economic Transition (FMET 2021)
Series
Advances in Economics, Business and Management Research
Publication Date
18 September 2021
ISBN
10.2991/aebmr.k.210917.011
ISSN
2352-5428
DOI
10.2991/aebmr.k.210917.011How to use a DOI?
Copyright
© 2021, 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  - Liu Xiaojie
AU  - Liao Aihong
PY  - 2021
DA  - 2021/09/18
TI  - Application of SVM, Decision Tree and Logistic Regression Algorithm in Stock Classification and Prediction
BT  - Proceedings of the 2021 International Conference on Financial Management and Economic Transition (FMET 2021)
PB  - Atlantis Press
SP  - 64
EP  - 68
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.210917.011
DO  - 10.2991/aebmr.k.210917.011
ID  - Xiaojie2021
ER  -