{"title":"New News is Bad News","authors":"Paul Glasserman, Harry Mamaysky, Jimmy Qin","doi":"arxiv-2309.05560","DOIUrl":null,"url":null,"abstract":"An increase in the novelty of news predicts negative stock market returns and\nnegative macroeconomic outcomes over the next year. We quantify news novelty -\nchanges in the distribution of news text - through an entropy measure,\ncalculated using a recurrent neural network applied to a large news corpus.\nEntropy is a better out-of-sample predictor of market returns than a collection\nof standard measures. Cross-sectional entropy exposure carries a negative risk\npremium, suggesting that assets that positively covary with entropy hedge the\naggregate risk associated with shifting news language. Entropy risk cannot be\nexplained by existing long-short factors.","PeriodicalId":501372,"journal":{"name":"arXiv - QuantFin - General Finance","volume":"87 ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuantFin - General Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2309.05560","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
An increase in the novelty of news predicts negative stock market returns and
negative macroeconomic outcomes over the next year. We quantify news novelty -
changes in the distribution of news text - through an entropy measure,
calculated using a recurrent neural network applied to a large news corpus.
Entropy is a better out-of-sample predictor of market returns than a collection
of standard measures. Cross-sectional entropy exposure carries a negative risk
premium, suggesting that assets that positively covary with entropy hedge the
aggregate risk associated with shifting news language. Entropy risk cannot be
explained by existing long-short factors.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
