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Focusing on online sentiment analysis, this book delves into its application for stock market predictions. It presents various tools and their historical research, alongside a Google Trend model to assess the predictive power of search volumes on the S&P 500 index. The effectiveness of this strategy is compared with a traditional buy and hold approach using historical data. Additionally, it tests the hypothesis that publicly released news can serve as a leading indicator for stock returns, while also evaluating the strengths and weaknesses of algorithmic sentiment analysis.
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Applicability of Online Sentiment Analysis for Stock Market Prediction, Petr Rýgr
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- Released
- 2016
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- (Paperback)
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