Working Paper
News versus Sentiment : Predicting Stock Returns from News Stories
Abstract: This paper uses a dataset of more than 900,000 news stories to test whether news can predict stock returns. We measure sentiment with a proprietary Thomson-Reuters neural network. We find that daily news predicts stock returns for only 1 to 2 days, confirming previous research. Weekly news, however, predicts stock returns for one quarter. Positive news stories increase stock returns quickly, but negative stories have a long delayed reaction. Much of the delayed response to news occurs around the subsequent earnings announcement.
Keywords: News; Text Analysis;
https://doi.org/10.17016/FEDS.2016.048
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File(s): File format is application/pdf http://www.federalreserve.gov/econresdata/feds/2016/files/2016048pap.pdf
Authors
Bibliographic Information
Provider: Board of Governors of the Federal Reserve System (U.S.)
Part of Series: Finance and Economics Discussion Series
Publication Date: 2016-06
Number: 2016-048
Pages: 35 pages