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from a plethora of raw news articles. We showcase how the latest development in NLP (i.e. the BERT model) can be applied to …
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We find that an increase in the ``unusualness'' of news with negative sentiment predicts an increase in stock market volatility. Similarly, unusual positive news forecasts lower volatility. Our analysis is based on more than 360,000 articles on 50 large financial companies, published in...
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The purpose of this research is to examine the impact of sentiment derived from news headlines on the direction of stock price changes. The study examines stocks listed on the WIG-banking sub-sector index on the Warsaw Stock Exchange. Two types of data were used: textual and market data. The...
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We classify the sentiment of a large sample of StockTwits messages as bullish,bearish or neutral, and create a stock-aggregate daily sentiment polarity measure.Polarity is positively associated with contemporaneous stock returns. On average,polarity is not able to predict next-day stock returns....
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