可读性
工具箱
光学(聚焦)
数据科学
计算机科学
度量(数据仓库)
政治
比例(比率)
财务
政治学
数据挖掘
经济
地理
物理
光学
程序设计语言
法学
地图学
作者
Tim Loughran,Bill McDonald
出处
期刊:Annual review of financial economics
[Annual Reviews]
日期:2020-11-30
卷期号:12 (1): 357-375
被引量:37
标识
DOI:10.1146/annurev-financial-012820-032249
摘要
Textual analysis, implemented at scale, has become an important addition to the methodological toolbox of finance. In this review, given the proliferation of papers now using this method, we first provide an updated survey of the literature while focusing on a few broad topics—social media, political bias, and detecting fraud. We do not attempt to survey the various statistical methods and instead initially focus on the construction and use of lexicons in finance. We then center the discussion on readability as an attribute frequently incorporated in contemporaneous research, arguing that its use begs the question of what we are measuring. Finally, we discuss how the literature might build on the intent of measuring readability to measure something more appropriate and more broadly relevant—complexity.
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