Publication Type : Journal Article
Publisher : Journal of Chemical and Pharmaceutical Sciences
Source : Journal of Chemical and Pharmaceutical Sciences , Volume 9, Issue 1, p.533 - 536 (2016)
Url : http://www.jchps.com/issues/Volume%209_Issue%201/jchps%209(1)%20112%20Binoy%20B%20Nair%20533-536.pdf
Keywords : Artificial neural networks, Forecasting, Sentiment, Stock
Campus : Coimbatore
School : School of Engineering
Center : Amrita Innovation & Research, Electronics Communication and Instrumentation Forum (ECIF)
Department : Computer Science, Electronics and Communication
Verified : Yes
Year : 2016
Abstract : Short-term fluctuations in stock prices are generally considered to be extremely difficult to predict, primarily due to their nonlinear nature. The authors believe that one of the reasons for such seemingly unpredictable fluctuations is the type of sentiment prevailing amongst traders at that point in time. An attempt has been made in this study to forecast the stock returns using the sentiments expressed on social media and Artificial Neural Networks. The proposed system is validated on stocks drawn from the Indian stock markets. Results indicate that the proposed technique can indeed be successfully used for short-term forecasting of stock prices.
Cite this Research Publication : Dr. Binoy B. Nair, “Forecasting short-term stock prices using sentiment analysis and Artificial Neural Networks”, Journal of Chemical and Pharmaceutical Sciences , vol. 9, no. 1, pp. 533 - 536, 2016.