The prediction of profitability using accounting narratives: A variable-precision rough set approach

Beynon, Malcolm James ORCID: https://orcid.org/0000-0002-5757-270X, Clatworthy, Mark A. and Jones, Michael John 2004. The prediction of profitability using accounting narratives: A variable-precision rough set approach. Intelligent Systems in Accounting, Finance and Management 12 (4) , pp. 227-242. 10.1002/isaf.256

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Abstract

This article utilizes a new method of data mining for the classification of companies as profitable or non-profitable, based on a textual analysis of the respective chairman's statement. The method used is a development of the rough set theory technique, namely the variable-precision rough sets (VPRS) model. A dichotomous sample of companies is used to construct a set of decision rules from a VPRS analysis using the textual characteristics of the chairman's statement in UK corporate annual reports. A number of descriptive measures are analyzed, including the predictive accuracy of the decision rules. Copyright © 2005 John Wiley & Sons, Ltd.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Business (Including Economics)
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management H Social Sciences > HF Commerce > HF5601 Accounting H Social Sciences > HG Finance
Publisher:	Wiley-Blackwell
ISSN:	1055-615X
Last Modified:	24 Oct 2022 09:52
URI:	https://orca.cardiff.ac.uk/id/eprint/42407

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