Predicting Chinese Stock Market Price Trend Using Machine Learning Approach

被引：3

作者：

Zhang, Chongyang ^{[1
]}

Ji, Zhi ^{[1
]}

Zhang, Jixiang ^{[1
]}

Wang, Yanqing ^{[1
]}

Zhao, Xingzhi ^{[2
]}

Yang, Yiping ^{[1
]}

机构：

[1] Chinese Acad Sci, Inst Automat, Beijing, Peoples R China

[2] Governors Acad Massachusetts, Newbury, MA USA

来源：

PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND APPLICATION ENGINEERING (CSAE2018) | 2018年

关键词：

machine learning; stock prediction; SVM; neural network;

D O I：

10.1145/3207677.3277966

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The stock(1) market is dynamic, noisy and hard to predict. In this paper, we explored four machine learning models using technical indicators as input features to predict the price trend 30 days later. The experimental dataset is Shanghai Stock Exchange(SSE) 50 index stocks. The result demonstrates that ANN performs better than the other three models and is promising to find some profitable patterns.

引用

页数：5

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