Combining technical analysis with sentiment analysis for stock price prediction

Shangkun Deng, Takashi Mitsubuchi, Kei Shioda, Tatsuro Shimada, Akito Sakurai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

23 Citations (Scopus)

Abstract

This paper proposes a stock price prediction model, which extracts features from time series data and social networks for prediction of stock prices and evaluates its performance. In this research, we use the features such as numerical dynamics (frequency) of news and comments, overall sentiment analysis of news and comments, as well as technical analysis of historic price and volume. We model the stock price movements as a function of these input features and solve it as a regression problem in a Multiple Kernel Learning regression framework. Experimental results show that our proposed method outperforms other baseline methods in terms of magnitude prediction measures such as RMSE, MAE and MAPE for three famous Japan companies' stocks in US stock market. The results indicate that features other than mining from stock prices themselves improved the performance.

Original languageEnglish
Title of host publicationProceedings - IEEE 9th International Conference on Dependable, Autonomic and Secure Computing, DASC 2011
Pages800-807
Number of pages8
DOIs
Publication statusPublished - 2011
Event9th IEEE Int. Conf. on Dependable, Autonomic and Secure Comput., DASC 2011, incl. 9th Int. Conf. on Pervasive Intelligence and Computing, PICom 2011, 9th Int. Symp. on Embedded Computing, EmbeddedCom 2011, 1st Int. Conf. on Cloud and Green Comput.CGC - Sydney, NSW, Australia
Duration: 2011 Dec 122011 Dec 14

Other

Other9th IEEE Int. Conf. on Dependable, Autonomic and Secure Comput., DASC 2011, incl. 9th Int. Conf. on Pervasive Intelligence and Computing, PICom 2011, 9th Int. Symp. on Embedded Computing, EmbeddedCom 2011, 1st Int. Conf. on Cloud and Green Comput.CGC
CountryAustralia
CitySydney, NSW
Period11/12/1211/12/14

Fingerprint

Time series
Industry
Financial markets

Keywords

  • Human Sentiment Factors
  • Multiple Kernel Learning
  • Sentiment Analysis
  • Social Networks Mining
  • Stock Price Prediction
  • Technical Indicators
  • Text Mining

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Software

Cite this

Deng, S., Mitsubuchi, T., Shioda, K., Shimada, T., & Sakurai, A. (2011). Combining technical analysis with sentiment analysis for stock price prediction. In Proceedings - IEEE 9th International Conference on Dependable, Autonomic and Secure Computing, DASC 2011 (pp. 800-807). [6118898] https://doi.org/10.1109/DASC.2011.138

Combining technical analysis with sentiment analysis for stock price prediction. / Deng, Shangkun; Mitsubuchi, Takashi; Shioda, Kei; Shimada, Tatsuro; Sakurai, Akito.

Proceedings - IEEE 9th International Conference on Dependable, Autonomic and Secure Computing, DASC 2011. 2011. p. 800-807 6118898.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Deng, S, Mitsubuchi, T, Shioda, K, Shimada, T & Sakurai, A 2011, Combining technical analysis with sentiment analysis for stock price prediction. in Proceedings - IEEE 9th International Conference on Dependable, Autonomic and Secure Computing, DASC 2011., 6118898, pp. 800-807, 9th IEEE Int. Conf. on Dependable, Autonomic and Secure Comput., DASC 2011, incl. 9th Int. Conf. on Pervasive Intelligence and Computing, PICom 2011, 9th Int. Symp. on Embedded Computing, EmbeddedCom 2011, 1st Int. Conf. on Cloud and Green Comput.CGC, Sydney, NSW, Australia, 11/12/12. https://doi.org/10.1109/DASC.2011.138
Deng S, Mitsubuchi T, Shioda K, Shimada T, Sakurai A. Combining technical analysis with sentiment analysis for stock price prediction. In Proceedings - IEEE 9th International Conference on Dependable, Autonomic and Secure Computing, DASC 2011. 2011. p. 800-807. 6118898 https://doi.org/10.1109/DASC.2011.138
Deng, Shangkun ; Mitsubuchi, Takashi ; Shioda, Kei ; Shimada, Tatsuro ; Sakurai, Akito. / Combining technical analysis with sentiment analysis for stock price prediction. Proceedings - IEEE 9th International Conference on Dependable, Autonomic and Secure Computing, DASC 2011. 2011. pp. 800-807
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