We survey the textual sentiment literature, comparing and contrasting the various
information sources, content analysis methods, and empirical models that have been used …

Natural language processing (NLP) is a part of the artificial intelligence domain focused on
communication between humans and computers. NLP attempts to address the inherent …

The financial technologies (FinTech) revolution is in full swing globally. In this paper, we
review the burgeoning literature on FinTech and FinTech-enabled services, focusing on the …

We develop FinBERT, a state‐of‐the‐art large language model that adapts to the finance
domain. We show that FinBERT incorporates finance knowledge and can better summarize …

Natural language is a key form of business communication. Textual analysis is the
application of natural language processing (NLP) to textual data for automated information …

Contextual pretrained language models, such as BERT (Devlin et al., 2019), have made
significant breakthrough in various NLP tasks by training on large scale of unlabeled text re …

Abstract Information, which can arrive in multiple forms, is a fundamental component of all
financial transactions and markets. We define hard and soft information and describe the …

Relative to quantitative methods traditionally used in accounting and finance, textual
analysis is substantially less precise. Thus, understanding the art is of equal importance to …

This study examines analyst information intermediary roles using a textual analysis of
analyst reports and corporate disclosures. We employ a topic modeling methodology from …

We investigate whether and when firms manage the tone of words in earnings press
releases, and how investors react to tone management. We estimate abnormal positive tone …