{"title":"新闻暗示的公司网络","authors":"G. Schwenkler, Hannan Zheng","doi":"10.2139/ssrn.3320859","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":11837,"journal":{"name":"ERN: Other IO: Empirical Studies of Firms & Markets (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"The Network of Firms Implied by the News\",\"authors\":\"G. Schwenkler, Hannan Zheng\",\"doi\":\"10.2139/ssrn.3320859\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":11837,\"journal\":{\"name\":\"ERN: Other IO: Empirical Studies of Firms & Markets (Topic)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-02-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ERN: Other IO: Empirical Studies of Firms & Markets (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3320859\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Other IO: Empirical Studies of Firms & Markets (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3320859","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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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