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Title: Time series with sentiment analysis for stock price prediction
Authors: Sharma, V.
Khemnar, R.
Kumari, R.
Mohan, B.R.
Issue Date: 2019
Citation: 2019 2nd International Conference on Intelligent Communication and Computational Techniques, ICCT 2019, 2019, Vol., , pp.178-181
Abstract: Stock price prediction has been a major area of research for many years. Accurate predictions can help investors take correct decisions about the selling/purchase of stocks. This paper aims to predict and gauge stock costs and patterns, utilizing the power of machine learning, content examination and fundamental analysis, to give traders a hands-on tool for keen speculations particularly for the volatile Indian Stock Market. We propose a technique to analyze and predict the stock price with the help of sentiment analysis and decomposable time series model along with multivariate-linear regression. � 2019 IEEE.
Appears in Collections:2. Conference Papers

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