Abstract

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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