商业新闻和商业周期

IF 7.6 1区经济学 Q1 BUSINESS, FINANCE

Journal of Finance Pub Date : 2024-08-09 DOI:10.1111/jofi.13377

LELAND BYBEE, BRYAN KELLY, ASAF MANELA, DACHENG XIU

{"title":"商业新闻和商业周期","authors":"LELAND BYBEE, BRYAN KELLY, ASAF MANELA, DACHENG XIU","doi":"10.1111/jofi.13377","DOIUrl":null,"url":null,"abstract":"We propose an approach to measuring the state of the economy via textual analysis of business news. From the full text of 800,000 Wall Street Journal articles for 1984 to 2017, we estimate a topic model that summarizes business news into interpretable topical themes and quantifies the proportion of news attention allocated to each theme over time. News attention closely tracks a wide range of economic activities and can forecast aggregate stock market returns. A text-augmented vector autoregression demonstrates the large incremental role of news text in forecasting macroeconomic dynamics. We retrieve the narratives that underlie these improvements in market and business cycle forecasts.","PeriodicalId":15753,"journal":{"name":"Journal of Finance","volume":"79 5","pages":"3105-3147"},"PeriodicalIF":7.6000,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jofi.13377","citationCount":"0","resultStr":"{\"title\":\"Business News and Business Cycles\",\"authors\":\"LELAND BYBEE, BRYAN KELLY, ASAF MANELA, DACHENG XIU\",\"doi\":\"10.1111/jofi.13377\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose an approach to measuring the state of the economy via textual analysis of business news. From the full text of 800,000 Wall Street Journal articles for 1984 to 2017, we estimate a topic model that summarizes business news into interpretable topical themes and quantifies the proportion of news attention allocated to each theme over time. News attention closely tracks a wide range of economic activities and can forecast aggregate stock market returns. A text-augmented vector autoregression demonstrates the large incremental role of news text in forecasting macroeconomic dynamics. We retrieve the narratives that underlie these improvements in market and business cycle forecasts.\",\"PeriodicalId\":15753,\"journal\":{\"name\":\"Journal of Finance\",\"volume\":\"79 5\",\"pages\":\"3105-3147\"},\"PeriodicalIF\":7.6000,\"publicationDate\":\"2024-08-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jofi.13377\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Finance\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/jofi.13377\",\"RegionNum\":1,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Finance","FirstCategoryId":"96","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/jofi.13377","RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}

引用次数: 0

摘要

我们提出了一种通过商业新闻文本分析来衡量经济状况的方法。我们从《华尔街日报》1984 年至 2017 年的 80 万篇文章全文中估算出一个主题模型，该模型将商业新闻概括为可解释的主题，并量化了随着时间推移分配给每个主题的新闻关注比例。新闻关注密切跟踪各种经济活动，并能预测股市的总体回报。文本增强向量自回归证明了新闻文本在预测宏观经济动态方面的巨大增量作用。我们检索了市场和商业周期预测得以改善的原因。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Business News and Business Cycles

查看原文本刊更多论文

Business News and Business Cycles

We propose an approach to measuring the state of the economy via textual analysis of business news. From the full text of 800,000 Wall Street Journal articles for 1984 to 2017, we estimate a topic model that summarizes business news into interpretable topical themes and quantifies the proportion of news attention allocated to each theme over time. News attention closely tracks a wide range of economic activities and can forecast aggregate stock market returns. A text-augmented vector autoregression demonstrates the large incremental role of news text in forecasting macroeconomic dynamics. We retrieve the narratives that underlie these improvements in market and business cycle forecasts.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Journal of Finance Multiple-

CiteScore

12.90

自引率

2.50%

发文量

期刊介绍： The Journal of Finance is a renowned publication that disseminates cutting-edge research across all major fields of financial inquiry. Widely regarded as the most cited academic journal in finance, each issue reaches over 8,000 academics, finance professionals, libraries, government entities, and financial institutions worldwide. Published bi-monthly, the journal serves as the official publication of The American Finance Association, the premier academic organization dedicated to advancing knowledge and understanding in financial economics. Join us in exploring the forefront of financial research and scholarship.