The Use of Word Lists in Textual Analysis

Tim Loughran and Bill McDonald

Journal of Behavioral Finance, 2015, vol. 16, issue 1, 1-11

Abstract: A commonly used platform to assess the tone of business documents in the extant accounting and finance literature is Diction. We argue that Diction is inappropriate for gauging the tone of financial disclosures. About 83% of the Diction optimistic words and 70% of the Diction pessimistic words appearing in a large 10-K sample are likely misclassified. Frequently occurring Diction optimistic words like respect, security, power, and authority will not be considered positive by readers of business documents. Similarly, over 45% of the Diction pessimistic 10-K word-counts are not and no. The Loughran-McDonald [2011] dictionary appears better at capturing tone in business text than Diction.

Date: 2015
References: Add references at CitEc
Citations: View citations in EconPapers (56)

Downloads: (external link)
http://hdl.handle.net/10.1080/15427560.2015.1000335 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:hbhfxx:v:16:y:2015:i:1:p:1-11

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/hbhf20

DOI: 10.1080/15427560.2015.1000335

Access Statistics for this article

Journal of Behavioral Finance is currently edited by Brian Bruce

More articles in Journal of Behavioral Finance from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().