Stock market reaction to news: Do tense and horizon matter?

Marie Briere, Karen Huynh, Olav Laudy,Sebastien Pouget

Finance Research Letters(2023)

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摘要
Using textual data extracted from a large variety of news sources (news stories, call transcripts, broker research, etc.), we build a daily aggregate news signal that takes into account the tone and tense of various news statements about a given firm. We test the informational content of this signal and examine how news about events happening in different tenses or at different horizons is incorporated into stock prices. We document large and significant market reactions around news publication. News' tense and horizon matter a lot. News about the future drives much larger reactions than those about the present or the past. Additionally, the market reaction to future news is mainly driven by near rather than distant future news.
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关键词
Natural language processing,Textual analysis,Efficient market hypothesis
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