Financial Analysts Journal·VOL73,NO.3·July/August 2016.

新闻vs情绪：从新闻报道中预测股票收益

作者：Steven L. Heston (Robert H. Smith School of Business, University of Maryland), Nitish Ranjan Sinha (Board of Governors of the Federal Reserve System)

摘要：作者使用了超过90万条新闻的数据集来测试新闻是否可以预测股票收益。他们用专有的Thomson Reuters神经网络测量情绪，发现每日新闻只能预测未来一到两天的股票收益，这证实了以前的研究。然而，每周新闻只能预测未来股价回报的四分之一。积极的新闻报道迅速增加股票收益，但负面报道反应迟缓。大部分对新闻的延迟响应出现在随后的盈利公告期间。

News vs. Sentiment: Predicting Stock Returns from News Stories

Steven L. Heston (Robert H. Smith School of Business, University of Maryland), Nitish Ranjan Sinha (Board of Governors of the Federal Reserve System)

ABSTRACT

The authors used a dataset of more than 900,000 news stories to test whether news can predict stock returns. They measured sentiment with a proprietary Thomson Reuters neural network and found that daily news predicts stock returns for only one to two days, confirming previous research. Weekly news, however, predicts stock returns for one quarter. Positive news stories increase stock returns quickly, but negative stories receive a long-delayed reaction. Much of the delayed response to news occurs around the subsequent earnings announcement.

原文链接： https://doi.org/10.2469/faj.v73.n3.3

翻译：赵胜旺