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Predicting Corporate Failure in the UK: A Multidimensional Scaling Approach

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  • Evi Neophytou
  • Cecilio Mar Molinero

Abstract

Scaling techniques are proposed as a tool for the analysis and prediction of corporate failure. This approach, while keeping a strong theoretical basis, has the advantage of visualising the main features of the data in the form of statistical maps that lend themselves to intuitive interpretation. The maps contain directional statistics to help with interpretation. The methodology is demonstrated using a sample of UK industrial companies. A future‐dated holdout sample is also employed to illustrate how the Multidimensional Scaling technique can aid practitioners when assessing the financial health of a company.

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  • Evi Neophytou & Cecilio Mar Molinero, 2004. "Predicting Corporate Failure in the UK: A Multidimensional Scaling Approach," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 31(5‐6), pages 677-710, June.
    • Handle: RePEc:bla:jbfnac:v:31:y:2004:i:5-6:p:677-710
    DOI: 10.1111/j.0306-686X.2004.00553.x
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    1. Casey, C & Bartczak, N, 1985. "Using Operating Cash Flow Data To Predict Financial Distress - Some Extensions," Journal of Accounting Research, Wiley Blackwell, vol. 23(1), pages 384-401.
    2. Libby, R, 1979. "Bankers And Auditors Perceptions Of The Message Communicated By The Audit Report," Journal of Accounting Research, Wiley Blackwell, vol. 17(1), pages 99-122.
    3. Belkaoui, A, 1980. "The Interprofessional Linguistic Communication Of Accounting Concepts - An Experiment In Sociolinguistics," Journal of Accounting Research, Wiley Blackwell, vol. 18(2), pages 362-374.
    4. Deakin, Eb, 1972. "Discriminant Analysis Of Predictors Of Business Failure," Journal of Accounting Research, Wiley Blackwell, vol. 10(1), pages 167-179.
    5. Haggstrom, Gus W, 1983. "Logistic Regression and Discriminant Analysis by Ordinary Least Squares," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(3), pages 229-238, July.
    6. 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.
    7. Brown, Pr, 1981. "A Descriptive Analysis Of Select Input Bases Of The Financial-Accounting-Standards-Board," Journal of Accounting Research, Wiley Blackwell, vol. 19(1), pages 232-246.
    8. Mensah, Ym, 1984. "An Examination Of The Stationarity Of Multivariate Bankruptcy Prediction Models - A Methodological Study," Journal of Accounting Research, Wiley Blackwell, vol. 22(1), pages 380-395.
    9. Green, Paul E & Maheshwari, Arun, 1969. "Common Stock Perception and Preference: An Application of Multidimensional Scaling," The Journal of Business, University of Chicago Press, vol. 42(4), pages 439-457, October.
    10. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    11. Johnsen, Thomajean & Melicher, Ronald W., 1994. "Predicting corporate bankruptcy and financial distress: Information value added by multinomial logit models," Journal of Economics and Business, Elsevier, vol. 46(4), pages 269-286, October.
    12. Eisenbeis, Robert A, 1977. "Pitfalls in the Application of Discriminant Analysis in Business, Finance, and Economics," Journal of Finance, American Finance Association, vol. 32(3), pages 875-900, June.
    13. Pratt, J, 1982. "Post-Cognitive Structure - Its Determinants And Relationship To Perceived Information Use And Predictive Accuracy," Journal of Accounting Research, Wiley Blackwell, vol. 20(1), pages 189-209.
    14. I. T. Jolliffe, 1972. "Discarding Variables in a Principal Component Analysis. I: Artificial Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 21(2), pages 160-173, June.
    15. Frank, Wg, 1979. "Empirical-Analysis Of International Accounting Principles," Journal of Accounting Research, Wiley Blackwell, vol. 17(2), pages 593-605.
    16. Bailey, Ke & Bylinski, Jh & Shields, Md, 1983. "Effects Of Audit Report Wording Changes On The Perceived Message," Journal of Accounting Research, Wiley Blackwell, vol. 21(2), pages 355-370.
    17. Lo, Andrew W., 1986. "Logit versus discriminant analysis : A specification test and application to corporate bankruptcies," Journal of Econometrics, Elsevier, vol. 31(2), pages 151-178, March.
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    4. Katsafados, Apostolos G. & Leledakis, George N. & Pyrgiotakis, Emmanouil G. & Androutsopoulos, Ion & Fergadiotis, Manos, 2024. "Machine learning in bank merger prediction: A text-based approach," European Journal of Operational Research, Elsevier, vol. 312(2), pages 783-797.
    5. Josep Patau & Antonio Somoza & Salvador Torra, 2020. "Diagnosis of the Domino Effect in Bankruptcy Situations Through Positioning Maps and Their Evolution 10 Years Later," SAGE Open, , vol. 10(4), pages 21582440209, December.
    6. Beat Reber & Agnes Gold & Stefan Gold, 2022. "ESG Disclosure and Idiosyncratic Risk in Initial Public Offerings," Journal of Business Ethics, Springer, vol. 179(3), pages 867-886, September.
    7. Cohen, Sandra & Doumpos, Michael & Neofytou, Evi & Zopounidis, Constantin, 2012. "Assessing financial distress where bankruptcy is not an option: An alternative approach for local municipalities," European Journal of Operational Research, Elsevier, vol. 218(1), pages 270-279.
    8. du Jardin, Philippe, 2012. "The influence of variable selection methods on the accuracy of bankruptcy prediction models," MPRA Paper 44383, University Library of Munich, Germany.
    9. Hsu, Hwa-Hsien & Wu, Chloe Yu-Hsuan, 2014. "Board composition, grey directors and corporate failure in the UK," The British Accounting Review, Elsevier, vol. 46(3), pages 215-227.
    10. Layla Khoja & Maxwell Chipulu & Ranadeva Jayasekera, 2016. "Analysing corporate insolvency in the Gulf Cooperation Council using logistic regression and multidimensional scaling," Review of Quantitative Finance and Accounting, Springer, vol. 46(3), pages 483-518, April.
    11. Denis Kušter & Bojana Vuković & Sunčica Milutinović & Kristina Peštović & Teodora Tica & Dejan Jakšić, 2023. "Early Insolvency Prediction as a Key for Sustainable Business Growth," Sustainability, MDPI, vol. 15(21), pages 1-24, October.
    12. Jarmila Horváthová & Martina Mokrišová & Martin Bača, 2023. "Bankruptcy Prediction for Sustainability of Businesses: The Application of Graph Theoretical Modeling," Mathematics, MDPI, vol. 11(24), pages 1-20, December.
    13. Katsafados, Apostolos G. & Androutsopoulos, Ion & Chalkidis, Ilias & Fergadiotis, Manos & Leledakis, George N. & Pyrgiotakis, Emmanouil G., 2020. "Textual Information and IPO Underpricing: A Machine Learning Approach," MPRA Paper 103813, University Library of Munich, Germany.
    14. Wu, Chloe Yu-Hsuan & Hsu, Hwa-Hsien & Haslam, Jim, 2016. "Audit committees, non-audit services, and auditor reporting decisions prior to failure," The British Accounting Review, Elsevier, vol. 48(2), pages 240-256.
    15. Beattie, Vivien, 2005. "Moving the financial accounting research front forward: the UK contribution," The British Accounting Review, Elsevier, vol. 37(1), pages 85-114.
    16. Pasiouras, Fotios & Tanna, Sailesh & Zopounidis, Constantin, 2007. "The identification of acquisition targets in the EU banking industry: An application of multicriteria approaches," International Review of Financial Analysis, Elsevier, vol. 16(3), pages 262-281.
    17. du Jardin, Philippe & Séverin, Eric, 2010. "Dynamic analysis of the business failure process: A study of bankruptcy trajectories," MPRA Paper 44379, University Library of Munich, Germany.
    18. C Mar-Molinero & J Mingers, 2007. "An evaluation of the limitations of, and alternatives to, the Co-Plot methodology," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(7), pages 874-886, July.
    19. Juan García Lara & Beatriz Osma & Evi Neophytou, 2009. "Earnings quality in ex‐post failed firms," Accounting and Business Research, Taylor & Francis Journals, vol. 39(2), pages 119-138.
    20. Tamás Kristóf & Miklós Virág, 2020. "A Comprehensive Review of Corporate Bankruptcy Prediction in Hungary," JRFM, MDPI, vol. 13(2), pages 1-20, February.

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