Indian Stock Market Prediction using Machine Learning and Sentiment Analysis

Pathak, Ashish and Shetty, Nisha P (2017) Indian Stock Market Prediction using Machine Learning and Sentiment Analysis. In: ICCIDM, 11/11/2017, Odhisa.

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Stock market is a very volatile in-deterministic system with vast number of factors influencing the direction of trend on varying scales and multiple layers. Efficient Market Hypothesis (EMH) states that the market is unbeatable. This makes predicting the uptrend or downtrend a very challenging task. This research aims to combine multiple existing techniques into a much more robust prediction model which can handle various scenarios in which investment can be beneficial. Existing techniques like sentiment analysis or neural network techniques can be too narrow in their approach and can lead to erroneous outcomes for varying scenarios. By combing both techniques, this prediction model can provide more accurate and flexible recommendations. Embedding Technical indicators will guide the investor to minimize the risk and reap better returns.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Machine Learning; Sentiment Analysis; Stock Market; SVM
Subjects: Engineering > MIT Manipal > Information and Communication Technology
Depositing User: MIT Library
Date Deposited: 11 Feb 2019 04:29
Last Modified: 11 Feb 2019 04:29

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