Dynamic analysis of different business failure process
-
DOIhttp://dx.doi.org/10.21511/ppm.15(si).2017.02
-
Article InfoVolume 15 2017, Issue #2 (cont. 3), pp. 486-499
- Cited by
- 1696 Views
-
395 Downloads
This work is licensed under a
Creative Commons Attribution 4.0 International License
This work is framed in the research of business failure. We examine a method of analyzing the dynamics of financial failure. The authors examine a method of analyzing the dynamics of financial failure, because our goal is to analyze how the economic and financial indicators show the risk of failure in a group of companies.
Using a sample of 163 companies declared bankrupt or dissolved, the authors show how to depict company trajectories of behavior and movement to terminal failure. They analyze these trajectories to find and describe empirical evidence of the different dynamics of bankruptcy. The authors also show that the estimation of failure risk is more accurate when these different failure trajectories are defined.
In conclusion, the authors can see that there are different failure trajectories. One can use these different trajectories to identify more efficiently the indicators warning of the failure risk of the companies analyzed.
- Keywords
-
JEL Classification (Paper profile tab)G32, G33
-
References52
-
Tables9
-
Figures0
-
- Table 1. Description of Laitinen (1991) research ratios
- Table 2. Frequencies by cluster
- Table 3. Summary contrast K-W by ratios described in Laitinen (1991)
- Table 4. Kruskal-Wallis contrast with the ratios described by Laitinen (1991)
- Table 5. Contrast of independent sub-samples. Groups taken two by two
- Table 6. Summary contrast independent grouping (K-W)
- Table 7. Groups of companies that follow different failure processes
- Table 8. Proportional risk function for all companies of the sample (like these following the same failure process)
- Table 9. Proportional risks function for each processes failure detected in the sample
-
- Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), 589-609.
- Altman, E., Iwanicz-Drozdowska, M., Laitinen, E., Suvas, A. (2015). Financial and Non-Financial Variables as Long-Horizon Predictors of Bankruptcy.
- Altman, E., Sabato, G. (2007). Modelling credit risk for SMEs evidence from the US market. Abacus, 43(3), 332-356.
- Argenti, J. (1976). Corporate Collapse the causes and symptoms. Ed. John Wiley and Sons. New York.
- Arquero, J. L., Abad, M. C., & Jimйnez, S. M. (2009). Procesos de Fracaso Empresarial en Pymes. Identificaciуn y Contrastaciуn Empнrica. Revista Internacional de la Pequeсa y Mediana Empresas, 1(2).
- Еstebro, T., & Winter, J. K. (2012). More than a dummy: The probability of failure, survival and acquisition of firms in financial distress. European Management Review, 9(1), 1-17.
- Bal, J., Cheung, Y., & Wu, H. C. (2013). Entropy for business failure prediction: an improved prediction model for the construction industry. Advances in Decision Sciences.
- Balcaen, S., & Ooghe, H. (2006). 35 years of studies on business failure: an overview of the classic statistical methodologies and their related problems. The British Accounting Review, 38(1), 63-93.
- Beaver, W. H. (1966). Financial ratios as predictors of failure. Journal of Accounting Research, 5(suplement), 123-127.
- Bercovitz, J., & Mitchell, W. (2007). When is more better? The impact of business scale and scope on long‐term business survival, while controlling for profitability. Strategic Management Journal, 28(1), 61-79.
- Burnham, K. P., & Anderson, D. R. (2004). Multimodel inference understanding AIC and BIC in model selection. Sociological methods & research, 33(2), 261-304.
- Chancharat, N., Davy, P., McCrae, M., & Tian, G. (2007). Firms in financial distress, a survival model analysis. Working Paper. 20th Australasian Finance & Banking Conference, August.
- Chava, S., & Jarrow, R. A. (2004). Bankruptcy prediction with industry effects. Review of Finance, 8(4), 537-569.
- Christidis, A. C., & Gregory A. (2010). Some New Models for Financial Distress Prediction in the UK (Working Paper). XFi Centre for Finance & Investment, University of Exeter.
- Cox, D. R. (1972). Regression Models and Life Tables. Journal of the Royal Statistical Society, Series B, 34, 187-220.
- Cox, D. R. (1975). Partial likelihood. Biometrika, 62(2), 269-276.
- Deakin, E. (1972). A Discriminant Analysis of Predictors of Business Failure. Journal of Accounting Research, 167-179.
- Dimitras, A. I., Zanakis, S. H., & Zopounidis, C. (1996). A survey of business failure with an emphasis on prediction methods and industrial applications. European Journal of Operational Research, 90(3), 487-513.
- Du Jardin, P. (2015). Bankruptcy prediction using terminal failure processes. European Journal of Operational Research, 242(1), 286-303.
- Du Jardin, P. (2016). A two-stage classification technique for bankruptcy prediction. European Journal of Operational Research, 254(1), 236-252.
- Edminster, R. O. (1972). An Empirical Test of Financial Ratio Analysis for Small Business Failure Prediction. Journal of Financial and Quantitative Analysis, March, 1477-1493.
- Frydman, H., Altman, E. I., & Kao, D. (1985). Introducing Recursive Partitioning for Financial Classification: The Case of Financial Distress. The Journal of Finance, 40(1), 269-291.
- Garcнa, D., Arquйs, A. y Calvo-Flores, A. (1995). Un modelo discriminante para evaluar el riesgo bancario en los crйditos a empresas. Revista Espaсola de Financiaciуn y Contabilidad, XXIV(82), 175-200.
- Gonzбlez-Bravo, M. I., & Mecaj, A. (2011). Structural and Evolutionary Patterns of Companies in a Financial Distress Situation. Advances in Decision Sciences.
- Gill de Albornoz, B. G., & Giner, B. (2013). Predicciуn del fracaso empresarial en los sectores de construcciуn e inmobiliario: Modelos generales versus especнficos. Universia Business Review, 39, 118-131.
- Gray, S., Mirkovic, A., Ragunathan, V. (2006). The determinants of credit ratings Australian evidence. Australian Journal of Management, 31(2), 333-353.
- Jimeno-Garcнa, I., Rodrнguez-Merayo, M. A., Vнdal-Blasco, M. A., (2015). The processes of failure and their relation to the business interruption. Proceedings of 1st International Virtual SBRLAB Conference “Finding solution for a post crisis society”, December, 9-11, 2015, Tarragona (pp. 384-395).
- Korol, T. (2013). Early warning models against bankruptcy risk for Central European and Latin American enterprises. Economic Modelling, 31, 22-30.
- Labatut, G., Pozuelo, J., & Veres, E. J., (2009). Modelizaciуn temporal de los ratios contables en la detecciуn del fracaso empresarial de la PYME espaсola. Revista Espaсola de Financiaciуn y Contabilidad, 38(143), 423-448.
- Laitinen, E. (1991). Financial ratios and different failure processes. Journal of Business Financial and Accounting, 18(5), 649-673.
- Laitinen, E., & Lukason, O. (2014). Do firm failure processes differ across countries: evidence from Finland and Estonia. Journal of Business Economics and Management, 15(5), 810-832.
- Laitinen, E., Lukason, O., & Suvas, A. (2014). Behavior of Financial Ratios in Firm Failure Process: An International Comparison. International Journal of Finance and Accounting, 3(2), 122-131.
- Lane, W. R., Looney, S. W., & Wansley, J. W. (1986). An application of the Cox proporcional risks model to bank failure. Journal of Banking and Finance, 10, 511-531.
- Lee, S. H., & Urritia, J. L. (1996). Analysis and Prediction of Insolvency in the Property-Liability Insurance Industry: A Comparison of Logit and Risk Models. The Journal of Risk and Insurance, 63(1), 121-130.
- Lukason, O. (2012). Firm failure patterns: The interconnection of failure reasons and financial data. Proceedings of 7th International Scientific Conference “Business and Management 2012”, May 10-11, 2012, Vilnius, Lithuania.
- Lukason, O., & Hoffman, R. C. (2014). Firm Bankruptcy Probability and Causes: An Integrated Study. International Journal of Business and Management, 9(11), 80.
- Lukason, O., & Laitinen, E. (2016). Failure processes of old manufacturing firms in different European countries. Investment Management and Financial Innovations, 13(2).
- Luoma, M., & Laitinen, E. (1991). Survival analysis as a tool for company failure prediction. Omega, 19(6), 673-678.
- Mдnnasoo, K., (2007). Determinants of firm sustainability in Estonia (Working Paper). Series Esti Pank Bank of Estonia.
- McKee, T. E. (2000). Developing a Bankruptcy Prediction Model via Rough Sets Theory. International Journal of Intelligent Systems in Accounting, Finance & Management, 9, 159-173.
- Mora, A. (1994). Los modelos de predicciуn del fracaso empresarial: Una aplicaciуn empнrica del Logit. Revista Espaсola de Financiaciуn y contabilidad, XXIV(78), 203-233.
- Nam, C., Kim, T., Park, N., & Lee, H. (2008). Bankruptcy Prediction Using a Discrete-Time Duration Model Incorporating Temporal and Macroeconomic Dependencies. Journal of Forecasting, 27, 493-506.
- Ohlson, J. A. (1980). Financial ratios and the probabilistic prediction of bankruptcy. Journal of Accounting Research, Spring, 109-131.
- Ooghe, H., & De Prijcker, S. (2008). Failure processes and causes of company bankruptcy: a typology. Management Decision, 46(2), 223-242.
- Pang-Tien, L., Ching-Wen, L., Hui-Fun, Y. (2008). Financial early-warning models on cross-holding groups. Journal of Industrial Management & Data Systems, 108(8), 1060-1080.
- Saridakis, G., Mole, K., & Storey, D. J. (2008). New small firm survival in England. Empirica, 35(1), 25-39.
- Sun, J., Li, H., Huang, Q. H., & He, K. Y. (2014). Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches. Knowledge-Based Systems, 57, 41-56.
- Shumway, T. (2001). Forecasting Bankruptcy More Accurately: A Simple Hazrad Model. Journal of Business, 74(1), 101-124.
- Taffler, R. J. (1984). Empirical models for the monitoring of UK corporations. Journal of banking and finance, 8(2), 199-227.
- Thorley, N., Perry, S. E. & Andes, S. (1996). Evaluating Firms in Financial Distress: An Event History Analysis. Journal of Applied Business Research, 12(3), 60-71.
- Volkov, A., & Van den Poel, D. (2012). Extracting information from sequences of financial ratios with Markov for Discrimination: an application to bankruptcy prediction. Proceedings of 2012 IEEE 12th International Conference on Data Mining Workshop (pp. 340-343).
- Zmijewski, M. E. (1984). Methodological Issues Related to the Estimation of Financial Distress Prediction Models. Journal of Accounting Research, Supplement, 22, 59-82.