新闻暗示的公司网络

G. Schwenkler, Hannan Zheng
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引用次数: 18

摘要

我们表明,新闻是一个丰富的数据来源,关于陷入困境的公司联系,推动公司层面和总体风险。新闻倾向于报道那些不太受欢迎的公司陷入困境并可能影响到更受欢迎的公司的联系。这构成了一个传染渠道,产生可预测的回报和评级下调。对新闻暗示的企业连通性程度的冲击预示着总波动率、信贷息差和违约率的增加,以及产出的下降。为了获得我们的结果,我们提出了一种机器学习方法,该方法将文本数据作为输入并输出数据隐含的公司网络。
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The Network of Firms Implied by the News
We show that the news is a rich source of data on distressed firm links that drive firm-level and aggregate risks. The news tends to report about links in which a less popular firm is distressed and may contaminate a more popular firm. This constitutes a contagion channel that yields predictable returns and downgrades. Shocks to the degree of news-implied firm connectivity predict increases in aggregate volatilities, credit spreads, and default rates, and declines in output. To obtain our results, we propose a machine learning methodology that takes text data as input and outputs a data-implied firm network.
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