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

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  • Malcolm J. Beynon
  • Mark A. Clatworthy
  • Michael John Jones

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.

Suggested Citation

  • Malcolm J. Beynon & Mark A. Clatworthy & Michael John Jones, 2004. "The prediction of profitability using accounting narratives: a variable‐precision rough set approach," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 12(4), pages 227-242, October.
    • Handle: RePEc:wly:isacfm:v:12:y:2004:i:4:p:227-242
    DOI: 10.1002/isaf.256
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    References listed on IDEAS

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    1. Beynon, Malcolm J. & Peel, Michael J., 2001. "Variable precision rough set theory and data discretisation: an application to corporate failure prediction," Omega, Elsevier, vol. 29(6), pages 561-576, December.
    2. R. Slowinski & C. Zopounidis, 1995. "Application of the Rough Set Approach to Evaluation of Bankruptcy Risk," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 4(1), pages 27-41, March.
    3. Ingram, Rw & Frazier, Kb, 1980. "Environmental Performance And Corporate Disclosure," Journal of Accounting Research, Wiley Blackwell, vol. 18(2), pages 614-622.
    4. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    5. L. Lin & J. Piesse, 2004. "Identification of corporate distress in UK industrials: a conditional probability analysis approach," Applied Financial Economics, Taylor & Francis Journals, vol. 14(2), pages 73-82.
    6. Frazier, Kb & Ingram, Rw & Tennyson, Bm, 1984. "A Methodology For The Analysis Of Narrative Accounting Disclosures," Journal of Accounting Research, Wiley Blackwell, vol. 22(1), pages 318-331.
    7. Mark Clatworthy & Michael Jones, 2003. "Financial reporting of good news and bad news: evidence from accounting narratives," Accounting and Business Research, Taylor & Francis Journals, vol. 33(3), pages 171-185.
    8. Beynon, Malcolm, 2001. "Reducts within the variable precision rough sets model: A further investigation," European Journal of Operational Research, Elsevier, vol. 134(3), pages 592-605, November.
    9. Dimitras, A. I. & Slowinski, R. & Susmaga, R. & Zopounidis, C., 1999. "Business failure prediction using rough sets," European Journal of Operational Research, Elsevier, vol. 114(2), pages 263-280, April.
    10. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    11. Aerts, Walter, 1994. "On the use of accounting logic as an explanatory category in narrative accounting disclosures," Accounting, Organizations and Society, Elsevier, vol. 19(4-5), pages 337-353.
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    Cited by:

    1. Zubin R. Mulla & R. K. Premarajan, 2008. "Strategic Human Rfesource Management in Indian it Companies: Development and Validation of a Scale," Vision, , vol. 12(2), pages 35-46, April.

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