Sentiment Based Stock Market Prediction

The Stock Market prophets focus on developing a efficient approach to predict the future stock prices. Apart from achieving best results in the successful stock market prediction it is also necessary to minimize the inaccurate forecast of stock prices. The project aims to design and implement a pred...

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Bibliographic Details
Published in2018 International Conference on Computational Techniques, Electronics and Mechanical Systems (CTEMS) pp. 12 - 17
Main Authors Pooja, B. L., Kanakaraddi, Suvarna, Raikar, Meenaxi .M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2018
Subjects
Classification algorithms
Companies
Google
investiture
Linear regression
predictive
Prophets
sentiment analysis
Stock markets
Support vector machines
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Summary:The Stock Market prophets focus on developing a efficient approach to predict the future stock prices. Apart from achieving best results in the successful stock market prediction it is also necessary to minimize the inaccurate forecast of stock prices. The project aims to design and implement a predictive system for guiding stock market investiture. As stock market is a very volatile environment, it can be influenced by positive or negative stock price releases. The research shows that there is an effect of prices on stock market and that the stocks can be predicted with the help of those prices. Automated data in general and company's distinct data of Apple, Microsoft, Google and Amazon are used to test the effect of the efficient prices on the stock market. A different procedure is experimented with sentiment analysis and the results display that it is able to predict the stock market with the help of stock prices for different companies, where the linear regression model is possible to predict more accurately than the sentiment analysis method.
DOI:10.1109/CTEMS.2018.8769159