Sentiment Analysis of News Headlines for Stock Price Prediction
Keywords:
Sentiment Analysis, Naive Bayes, SVM, KNNAbstract
Stock market data analysis needs the help of artificial intelligence and data mining techniques. The volatility of stock prices depends on gains or losses of certain companies. News articles are one of the most important factors which influence the stock market. This study basically shows the effect of emotion classification of financial news to the prediction of stock market prices. In order to find correlation between sentiment predicted from news and original stock price and to test efficient market hypothesis, we plot the sentiments of two companies (Infosys and Wipro) over a period of 10 years. For emotion classification, various classifiers such as Naive Bayes, Knn and SVM are evaluated. The comparison between positive sentiment curve and stock price trends reveals co-relation between them.
References
A Sheta, “Software Effort Estimation and Stock Market Prediction Using Takagi-Sugeno Fuzzy Models”, In Proceedings of the IEEE International Conference on Fuzzy Systems, pp.171-178, Vancouver, BC, 2006.
Ching Long Su, ChuenJyh Chen and Shih Ming Yang, “A self-organized neuro-fuzzy system for stock market dynamics modeling and forecasting”, WSEAS Transactions on Information Science and Applications,Vol7.8,No.9, September 2010 .
M.H. FazelZarandi, B. Rezaee, I.B. Turksen and E. Neshat, “A type-2 fuzzy rule-based expert system model for stock price analysis”, Expert Systems with Applications,Vol.36, No.1, pp. 139-154,January 2009.
Robert K. Lai, Chin-Yuan Fan, Wei-Hsiu Huang and Pei-Chann Chang, “Evolving and clustering fuzzy decision tree for financial time series data forecasting”, An International Journal of Expert Systems with Applications, Vol.36,No.2, pp. 3761-3773, March 2009.
Shyi-Ming Chen and Yu-Chuan Chang, “MultiVariable Fuzzy Forecasting Based On Fuzzy Clustering and Fuzzy Rule Interpolation Techniques”, Information Sciences, Vol.180, No.24, pp. 4772-4783,2010.
WengLuen Ho, Whye Loon Tung and Chai Quek, “Brain-Inspired Evolving Neuro-Fuzzy System for Financial Forecasting and Trading of the S&P500 Index”, Lecture Notes in Computer Science, Vol.6230, pp.601-607,2010
EsmaeilHadavandi, Hassan Shavandi and ArashGhanbari, “Integration of genetic fuzzy systems and artificial neural networks for stock price forecasting”, Knowledge-Based Systems, Vol.23, No.8, pp. 800-808,December 2010.
Kelvin Sim, VivekanandGopalkrishnan, Clifton Phua and Gao Cong, “3D Subspace Clustering for Value Investing”, IEEE Intelligent Systems, Vol. PP, No.99, pp. 1, 2012.
Anil Rajput , S.P. Saxena , Ramesh Prasad Aharwal and RituSoni, “Rule based Classification of BSE Stock Data with Data Mining”, International Journal of Information Sciences and Application, Volume 4, Number 1 (2012), pp. 1-9.
XianggaoCai, Su Hu, XiaolaLin,”Feature Extraction Using Restricted Boltzmann Machine for Stock Price Prediction”, 978-1-4673- 0089-6/12/$26.00 ©2012 IEEE.
http://www.moneycontrol.com/stocks/companydetails/hist_graph.php
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