Using SVM to Predict Stock Price Changes from Online Financial News

被引：0
|
作者：
Dai, Shuyan [1 ]
Li, Ning [2 ]
机构：
[1] Beihua Univ, Dept Finance & Planning, Beihua 132000, Jilin, Peoples R China
[2] China Univ Petr, Sch Econ & Management, Qingdao 266555, Peoples R China
来源：
MECHATRONICS AND APPLIED MECHANICS, PTS 1 AND 2 | 2012年 / 157-158卷
关键词：
information retrieval; stock analysis; SVM classification; financial analysis;
D O I：
10.4028/www.scientific.net/AMM.157-158.1586
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Many technical analysis use financial indices to predict stock price changes. In this paper, we present a different approach for prediction stock price fluctuations using financial news. Our method approaches the stock price prediction problem from an information retrieval perspective. We apply both text analysis and pattern classification techniques to search for important online news that are relevant for stock price changes. First, the online financial news and the corresponding stocks are extracted. Then we apply Support Vector Machine (SVM) to construct a model that predicts the price changes for the stocks. Finally, the stock changes prediction model is used to classify and extract upcoming important financial news. The experimental results demonstrate our method is effective for seeking the important financial news for stock price changes.
引用
收藏
页码：1586 / +
页数：2
相关论文
共 50 条
  • [41] Spot Gold Price Prediction Using Financial News Sentiment Analysis
    Zhou Junjie
    Mengoni, Paolo
    [J]. 2020 IEEE/WIC/ACM INTERNATIONAL JOINT CONFERENCE ON WEB INTELLIGENCE AND INTELLIGENT AGENT TECHNOLOGY (WI-IAT 2020), 2020, : 758 - 763
  • [42] Deep learning for stock market prediction from financial news articles
    Vargas, Manuel R.
    de Lima, Beatriz S. L. P.
    Evsukoff, Alexandre G.
    [J]. 2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND VIRTUAL ENVIRONMENTS FOR MEASUREMENT SYSTEMS AND APPLICATIONS (CIVEMSA), 2017, : 60 - 65
  • [43] Financial Indicators and Stock Price Movements: The Evidence from the Finance of China
    Jiang, Qiang
    Wang, Xin
    Li, Yi
    Wang, Dong
    Huang, Qing
    [J]. PROCEEDINGS OF THE THIRTEENTH INTERNATIONAL CONFERENCE ON MANAGEMENT SCIENCE AND ENGINEERING MANAGEMENT, VOL 2, 2020, 1002 : 743 - 758
  • [44] Using news to predict Chinese medicinal material price index movements
    Yu, Miao
    Guo, Chonghui
    [J]. INDUSTRIAL MANAGEMENT & DATA SYSTEMS, 2018, 118 (05) : 998 - 1017
  • [45] Can interest rate changes help predict future stock price movements? Evidence from the German market
    Siddiqui, S
    [J]. APPLIED ECONOMICS LETTERS, 2003, 10 (04) : 209 - 211
  • [46] Improving Stock Price Forecasting Using a Large Volume of News Headline Text
    Zhang, Daxing
    Cai, Erguan
    [J]. CMC-COMPUTERS MATERIALS & CONTINUA, 2021, 69 (03): : 3931 - 3943
  • [47] Forecasting significant stock price changes using neural networks
    Firuz Kamalov
    [J]. Neural Computing and Applications, 2020, 32 : 17655 - 17667
  • [48] Forecasting significant stock price changes using neural networks
    Kamalov, Firuz
    [J]. NEURAL COMPUTING & APPLICATIONS, 2020, 32 (23): : 17655 - 17667
  • [49] Predicting stock market reactions to financial news using naive Bayesian classifiers
    Svangård, N
    Nordin, P
    Lloyd, S
    [J]. PROCEEDINGS OF THE 7TH JOINT CONFERENCE ON INFORMATION SCIENCES, 2003, : 1067 - 1070
  • [50] The impacts of online public opinions on stock price synchronicity in China: Evidence from stock forums
    Chang, Kai
    Yang, Mengfei
    Zhou, Shengqi
    Wei, Guangxi
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2024, 255
12345