![](/images/graphics-bg.png)
Stock Price Change Rate Prediction by Utilizing Social Network Activities
Joint Authors
Deng, Shangkun
Mitsubuchi, Takashi
Sakurai, Akito
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-03-25
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Predicting stock price change rates for providing valuable information to investors is a challenging task.
Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities.
The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer.
In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA).
MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources.
GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators.
Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading.
Experimental results show that our proposed model performed better than other models including ones using state of the art techniques.
American Psychological Association (APA)
Deng, Shangkun& Mitsubuchi, Takashi& Sakurai, Akito. 2014. Stock Price Change Rate Prediction by Utilizing Social Network Activities. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-14.
https://search.emarefa.net/detail/BIM-1051384
Modern Language Association (MLA)
Deng, Shangkun…[et al.]. Stock Price Change Rate Prediction by Utilizing Social Network Activities. The Scientific World Journal No. 2014 (2014), pp.1-14.
https://search.emarefa.net/detail/BIM-1051384
American Medical Association (AMA)
Deng, Shangkun& Mitsubuchi, Takashi& Sakurai, Akito. Stock Price Change Rate Prediction by Utilizing Social Network Activities. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-14.
https://search.emarefa.net/detail/BIM-1051384
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1051384