可读性
相似性(几何)
会计
多样性(政治)
词汇多样性
私人信息检索
收益
ARCH模型
业务
精算学
财务
计算机科学
政治学
词汇
语言学
波动性(金融)
人工智能
哲学
程序设计语言
法学
图像(数学)
计算机安全
作者
Zahn Bozanic,Maya Thevenot
标识
DOI:10.1111/1911-3846.12123
摘要
Abstract We examine a routine and timely disclosure, earnings press releases, to determine the extent to which several novel qualitative elements of such disclosures are associated with changes in sell‐side financial analysts' information environment. Using a comprehensive set of GARCH‐based (generalized autoregressive conditional heteroscedasticity) proxies, we examine how disclosure readability's components, across‐document textual similarity, and within‐document lexical diversity alter analysts' information environment. We find that readability in the form of shorter sentences, textual similarity, and lexical diversity are strongly related to decreases in analysts' uncertainty. Further, shorter sentences and lexical diversity improve both public and private information precision, whereas similarity affects solely analysts' private information precision. While the GARCH ‐based proxies allow us to alleviate concerns regarding potentially spurious inferences (Sheng and Thevenot 2012), we note as a caveat that such an estimation restricts our inferences to large, stable, and heavily followed firms. These findings should be of interest to analysts who may wish to explore the latent information contained within the qualitative elements of disclosure, regulators who direct the form and content of disclosure, and academics who study the use (and possible misuse) of various forms of information and its presentation.
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