The present paper studies the evolution of a set of USA firms during the years 1993–2002. The firms that faced a difficult economic and financial situation in 1993 were considered to be in a distress situation. The aim of this study is to explore if the evolution of this situation depends on the initial features of the distress or if it concerns certain firms' characteristics. If the evolution is independent from the above, the management decisions become crucial in critical times. For the analysis we used a Multidimensional Scaling methodology where the firms are represented in a consensus map according to symptom variables, reaction variables, and recovering variables. 1. Introduction The research on financial distress has been closely tied to the determination of failure prediction models. Failure is considered to be the result of an evolutionary process, where the underlying idea is the possibility that the crisis can indeed be anticipated [1]. Pioneer prediction models such as the one proposed by Altman [2] built the basics of the research based on prediction. Those researches were mainly centered on minimizing classification errors and maximizing goodness of fit measures using certain variables throughout a wide period of time. In this context, prediction models were evaluated based on their percentage of success in the classification of the control sample companies [3]. The existence of an error in the classification of those companies, which did not fail even though were being described as failed, was considered as a failure of the proposed model. Nevertheless, these results leave an open door to consider the possibility that the companies can indeed survive a difficult situation or even subsist in a permanent crisis situation. This approach would allow considering the possibility that the failure process can sometimes not be an evolutionary-degenerative process, but it can revert so that the companies are able to subsist, even though still indicating certain situations that can determine their survival. In this sense, prediction models not only provide some essential information in order to take actions against the given default probability, but also warn about a future outcome which, in many cases, may not even take place. This “passive” use of the models has been highlighted by Altman and Hotchkiss [4] who affirm that stakeholders should have a more active participation instead of being simple onlookers of a given “probability of default”. Basically, this default probability should be considered as vital information by the managers not only
References
[1]
S. Balcaen and H. Ooghe, “35 years of studies on business failure: an overview of the classic statistical methodologies and their related problems,” British Accounting Review, vol. 38, no. 1, pp. 63–93, 2006.
[2]
E. I. Altman, “Financial ratios, discriminant analysis and the prediction of corporate failure,” Journal of Finance, vol. 23, no. 4, pp. 589–609, 1968.
[3]
M. Smith and C. Graves, “Corporate turnaround and financial distress,” Managerial Auditing Journal, vol. 20, no. 3, pp. 304–320, 2005.
[4]
E. Altman and E. Hotchkiss, Corporate Financial Distress and Bankcrupty, Wiley, Hoboken, NJ, USA, 2006.
[5]
R. Barniv, A. Agarwal, and R. Leach, “Predicting bankruptcy resolution,” Journal of Business Finance and Accounting, vol. 29, no. 3–4, pp. 497–520, 2002.
[6]
K. Robbins and J. A. Pearce, “Turnaround: retrenchment and recovery,” Strategic Management Journal, vol. 13, no. 4, pp. 287–309, 1992.
[7]
J. A. Pearce and K. Robbins, “Toward improved theory and research on business turnaround,” Journal of Management, vol. 19, no. 3, pp. 613–636, 1993.
[8]
J. A. Pearce and K. Robbins, “Retrenchment remains the foundations of business turnaround,” Strategic Management Journal, vol. 15, pp. 407–417, 1994.
[9]
V. L. Barker III and I. M. Duhaime, “Strategic change in the turnaround process: theory and empirical evidence,” Strategic Management Journal, vol. 18, no. 1, pp. 13–38, 1997.
[10]
W. F. Cascio, C. E. Young, and J. R. Morris, “Financial consequences of employment-change decisions in major U.S. corporations,” Academy of Management Journal, vol. 40, no. 5, pp. 1175–1189, 1997.
[11]
J. Morris, W. Cascio, and C. Young, “Downsizing after all these years: questions and answers about who did it, how many did it, and who benefited from it,” Organizational Dynamics, vol. 27, pp. 78–87, 1999.
[12]
E. Neophytou and C. M. Molinero, “Financial ratios, size, industry and interest rate issues in company failure: an extended multidimensional scaling approach,” Working Paper 100, Kent Business School, 2005.
[13]
L. R. Gilbert, K. I. Menon, and K. B. Schwarz, “Predicting bankruptcy for firms in financial distress,” Journal of Business Finance and Accounting, vol. 17, no. 1, pp. 161–171, 1990.
[14]
K. M. Poston, W. K. Harmon, and J. D. Gramlich, “A test of financial ratios as predictors of turnaround versus failure among financially distressed firms,” Journal of Applied Business Research, vol. 10, no. 1, pp. 41–57, 1994.
[15]
C. M. Molinero and M. Ezzamel, “Multidimensional scaling applied to corporate failure,” Omega, vol. 19, no. 4, pp. 259–274, 1991.
[16]
C. M. Molinero and C. Serrano-Cinca, “Bank failure: a multidimensional scaling approach,” The European Journal of Finance, vol. 7, pp. 165–183, 2001.
[17]
E. Neophytou and C. M. Molinero, “Predicting corporate failure in the UK: a multidimensional scaling approach,” Journal of Business Finance and Accounting, vol. 31, no. 5, pp. 677–709, 2004.
[18]
W. Beaver, “Financial ratios predictors of failure. Empirical research in accounting: selected studies 1966,” Journal of Accounting Research, vol. 4, pp. 71–111, 1967.
[19]
E. I. Altman, R. G. Haldeman, and P. Narayanan, “ZETA analysis a new model to identify bankruptcy risk of corporations,” Journal of Banking and Finance, vol. 1, no. 1, pp. 29–54, 1977.
[20]
E. I. Altman, “The success of business failure prediction models: an international survey,” Journal of Banking and Finance, vol. 8, no. 2, pp. 171–198, 1984.
[21]
A. I. Dimitras, S. H. Zanakis, and C. Zopounidis, “A survey of business failures with an emphasis on prediction methods and industrial applications,” European Journal of Operational Research, vol. 90, no. 3, pp. 487–513, 1996.
[22]
P. Cybinski, “Description, explanation, prediction the evolution of bankruptcy studies?” Managerial Finance, vol. 27, no. 4, pp. 29–44, 2001.
[23]
P. R. Kumar and V. Ravi, “Bankruptcy prediction in banks and firms via statistical and intelligent techniques—a review,” European Journal of Operational Research, vol. 180, no. 1, pp. 1–28, 2007.
[24]
E. K. Laitinen, “Financial ratios and different failure processes,” Journal of Business Finance and Accounting, vol. 18, no. 3, pp. 649–673, 1991.
[25]
M. Luoma and E. Laitinen, “Survival analysis as a tool for company failure prediction,” Omega, vol. 19, no. 6, pp. 673–678, 1991.
[26]
A. H. Catanach and S. E. Perry, “An evaluation of the survival model`s contribution to thrift institution distress prediction,” Journal of Managerial Issues, vol. 12, no. 4, pp. 401–417, 2001.
[27]
T. Shumway, “Forecasting bankruptcy more accurately: a simple hazard model,” Journal of Business, vol. 74, no. 1, pp. 101–124, 2001.
[28]
H. F. Turetsky and R. A. Mcewen, “An empirical investigation of firm longevity: a model of the Ex Ante predictors of financial distress,” Review of Quantitative Finance and Accounting, vol. 16, no. 4, pp. 323–343, 2001.
[29]
M. Bardos, “Développements récents de la méthode des scores de la banque de France,” Bulletin de la Banque de France, no. 90, 2001.
[30]
E. K. Laitinen, “Survival analysis and financial distress prediction: finnish evidence,” Review of Accounting & Finance, vol. 4, pp. 75–90, 2005.
[31]
J. Argenti, Corporate Collapse. The causes and Symptoms, MacGraw-Hill, London, 1976.
[32]
E. Laitinen, “Financial predictors for different phases of the failure process,” Omega, vol. 21, no. 2, pp. 215–228, 1993.
[33]
M. Bardos, “Détection précoce des défaillances d’entreprises à partir des documents comptables,” Bulletin de la Banque de France, Etudes, no. 3, pp. 57–75, 1995.
[34]
C. Abad, J. L. Arquero, and S. M. Jiménez, “El fracaso empresarial: características y tipos,” Accounting Review, vol. 38, pp. 63–93, 2007.
[35]
H. Ooghe and S. Prijcker, “Failure processes and causes of company bankruptcy: a typology,” Management Decision, vol. 46, no. 2, pp. 223–242, 2008.
[36]
V. Agarwal and R. Taffler, “Comparing the performance of market-based and accounting-based bankruptcy prediction models,” Journal of Banking and Finance, vol. 32, no. 8, pp. 1541–1551, 2008.
[37]
J. R. Aragonés and J. G. Sánchez, “Gestión continuada versus crisis financiera empresarial. Algunos criterios de previsión,” Revista Técnica del Instituto de Censores Jurados de Cuentas de Espa？a, vol. 23, pp. 37–45, 1991.
[38]
K. Raghunandan and D. V. Rama, “Audit reports for companies in financial distress: before and after SAS No 59,” Auditing, vol. 14, no. 1, pp. 50–63, 1995.
[39]
M. A. Geiger, K. Raghunandan, and D. V. Rama, “Reporting on going concern before and alter SAS n 59,” The CPA Journal Online, vol. 53, 1995.
[40]
J. F. Mutchler and D. D. Williams, “The relationship between audit technology, client risk profiles, and the going-concern opinion decision,” Auditing, vol. 9, no. 3, pp. 39–45, 1990.
[41]
J. F. Mutchler, “A multivariate analysis of the auditor’s going-concern opinion decision,” Journal of Accounting Research, vol. 23, no. 2, pp. 668–682, 1985.
[42]
A. Ponemon and A. G. Shich, “Financially distressed companies and auditor perceptions of the twelve characteristics of decline,” Auditing, vol. 10, no. 2, pp. 70–84, 1991.
[43]
R. D. Martin, “Going-concern uncertainty disclosures and conditions: a comparison of French, German, and U.S. practices,” Journal of International Accounting, Auditing and Taxation, vol. 9, no. 2, pp. 137–159, 2000.
[44]
P. Jostarndt, Financial Distress, Corporate Restructuring and Firm Survival: An Empirical Analysis of German Panel Data, Dissertation Universit？t München, 2006.
[45]
R. J. Taffler, “The assessment of company solvency and performance using a statistical model,” Accounting and Business Research, vol. 15, pp. 295–307, 1983.
[46]
A. V. Bruno, J. K. Leidecker, and J. W. Harder, “Why firms fail,” Business Horizons, vol. 30, no. 2, pp. 50–58, 1987.
[47]
M. Khal, “Financial distress as a selection mechanism: evidence from the United States,” Paper 16, UC Los Angeles, Anderson School of Management, 2001.
[48]
J. Routledge and D. Gadenne, “Financial distress, reorganization and corporate performance,” Accounting and Finance, vol. 40, no. 3, pp. 233–259, 2000.
[49]
J. B. Kruskal and M. Wish, Multidimensional Scaling, Sage, London, 1984.
[50]
D. Pe？a, Análisis de Datos Multivariantes, MacGraw Hill, 2002.
[51]
K. Arogyaswamy, V. L. Barker III, and M. Yasai-Ardekani, “Firm turnarounds: an integrative two-stage model,” Journal of Management Studies, vol. 32, no. 4, pp. 493–525, 1995.
[52]
P. Asquith, R. Gertner, and D. Scharfstein, “Anatomy of financial distress: an examination of junk-bond issuers,” The Quarterly Journal of Economics, vol. 109, pp. 625–658, 1994.
[53]
J. B. Kruskal, “Nonmetric multidimensional scaling: a numerical method,” Psychometrika, vol. 29, no. 2, pp. 115–129, 1964.
