Textual Analysis in Accounting and Finance: A Survey

By Tim Loughran, Bill McDonald. 2016

229 citations recorded by the source corpus.

Subfields: Accounting, Artificial Intelligence, Management Science and Operations Research

Citations in the corpus

• Decision support from financial disclosures with deep neural networks and transfer learning (2017, neutral): “Recent literature surveys [2, 3, 4, 5] provide a detailed overview of explanatory works, finding that these commonly count the instances of polarity cues, predefined by manually created dictionaries.”
• It Pays to Write Well (2017, unknown): “Another challenge facing the literature is that the readability of a document is intimately linked with the structural complexity of the entity it is intended to describe, in this case a company (e.g., Bloomfield, 2008; Loughran and McDonald, 2014, 2016).”
• Natural language processing (NLP) in management research: A literature review (2020, unknown): “The meaning of some indexes or measures in NLP, such as readability, is still not well defined in management research (Loughran and McDonald, 2016).”
• Readability of Narrative Disclosures in 10-K Reports: Does Managerial Ability Matter? (2018, unknown): “Prior studies use linguistic analysis tools to examine the causes and consequences of the readability of narrative disclosures (Ertugrul, Lei, Qiu, & Wan, 2017; Li, 2008; Lo, Ramos, & Rogo, 2017; Loughran & McDonald, 2016).”
• Analyst Information Discovery and Interpretation Roles: A Topic Modeling Approach (2018, unknown): “Finally, our study contributes to the emerging area of textual analysis by introducing the topic modeling approach to the accounting and finance literature and validating the approach for financial documents (see a recent review by Loughran and McDonald 2016).”
• Informational Content and Assurance of Textual Disclosures: Evidence on Integrated Reporting (2019, unknown): “…group, concept, or event, or highlighting 13Before computing all the indexes, removing tables, graphs, titles, and headings, we convert the pdf into text; we also remove numbers, symbols, URLs, special characters and stop words (Lewis, Yang, Rose, & Li, 2004; Li, 2008; Loughran & McDonald, 2016).”
• Saying more with less? Disclosure conciseness, completeness and balance in Integrated Reports (2017, unknown): “…by developing a measurement approach that draws on both the IIRC Framework (IIRC, 2013) and extant accounting studies applying textual analysis of narrative disclosures in financial reporting (cf. De Franco et al., 2015; Lang and Stice-Lawrence, 2015; Li, 2008, 2010; Loughran and McDonald, 2016).”
• Female Audit Partners and Extended Audit Reporting: UK Evidence (2020, unknown): “Though the fuzziness of textual analysis is not obstructing its use, nonetheless it is an attribute that may be provoked in constructing future empirical findings that are anticipated to have reliable influence and can be rationally reproduced (Loughran and McDonald 2016; Melloni et al. 2017).”