Stock Market Prediction: A Big Data Approach

Attigeri, Girija V and Pai, Manohara M.M. and Pai, Radhika M and Nayak, Aparna (2016) Stock Market Prediction: A Big Data Approach. In: TENCON 2015 - 2015 IEEE Region Conference, 01/11/2015, Macau.

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Abstract

The Stock market process is full of uncertainty and is affected by many factors. Hence the Stock market prediction is one of the important exertions in finance and business. There are two types of analysis possible for prediction, technical and fundamental. In this paper both technical and fundamental analysis are considered. Technical analysis is done using historical data of stock prices by applying machine learning and fundamental analysis is done using social media data by applying sentiment analysis. Social media data has high impact today than ever, it can aide in predicting the trend of the stock market. The method involves collecting news and social media data and extracting sentiments expressed by individual. Then the correlation between the sentiments and the stock values is analyzed. The learned model can then be used to make future predictions about stock values. It can be shown that this method is able to predict the sentiment and the stock performance and its recent news and social data are also closely correlated

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