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 …

We compare the ability of dictionary-based and machine-learning methods to capture
disclosure sentiment at 10-K filing and conference-call dates. Like Loughran and McDonald …

This paper conducts a textual analysis of earnings call transcripts to quantify climate risk
exposure at the firm level. We construct dictionaries that measure physical and transition …

Our paper relies on stock price reactions to colour words, in order to provide new
dictionaries of positive and negative words in a finance context. We extend the machine …

Summary Advances in Deep Learning have drastically improved the abilities of Natural
Language Processing (NLP) research, creating new state‐of‐the‐art benchmarks. Two …

Purpose This paper aims to examine whether firms meeting or just beating an earnings
benchmark engage in tone management in earnings conference calls to complement …

Conversation—a verbal interaction between two or more people—is a complex, pervasive,
and consequential human behavior. Conversations have been studied across many …

We empirically study how collusion in product markets affects firms' financial disclosure
strategies. We find that after a rise in cartel enforcement, US firms start sharing more detailed …

We use machine learning methods to create a comprehensive measure of credit risk based
on qualitative information disclosed in conference calls and in management's discussion …

Purpose Drawing on signalling and impression management theories, this study aims to
examine a bidirectional association between managerial tone in earnings conference calls …