The prediction of profitability using accounting narratives: a variable‐precision rough set approach

Malcolm J. Beynon, Mark Clatworthy () and Michael John Jones

Intelligent Systems in Accounting, Finance and Management, 2004, vol. 12, issue 4, 227-242

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.

Date: 2004
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