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BUSINESS FAILURE PREDICTION MODELS BASED ON EXPERT KNOWLEDGE

100%
Situm M.
Czech Journal of Social Sciences, Business and Economics
|
2013
|
vol. Volume 2
|
issue 4
28-46
EN
This paper presents two business failure prediction models developed with multivariate linear discriminant analysis and multivariate logistic regression. The financial ratios as predictors for the models were selected based on results from previous empirical research. It was assumed that companies can be categorized into three classes – healthy (group 1), crisis-resistant (group 2) and insolvency endangered (group 3) – which are describing different economic conditions. Data for model building were obtained by a survey of 35 professionals from management consulting and banking industry. The results show consistency with findings of prior research. High values for equity-ratio, EBIT/total assets, operating cashflow/financial liabilities and percentage sales development are positively related to financial health. Within model building several problems occurred, which influenced classification accuracy. Non-normality of data had an impact on discriminant analysis, but also on logistic regression. Successful preliminary analyses of suitable predictors are not a guarantee that model fit including statistically significant variables will provide a superior prediction model. This indicates that model building is heavily dependent on the quality of metrics used. Logistic regression was less sensitive to outliers in terms of prediction sign within classification formula. It was also shown that crisis indicators used in practice are similar to those proposed by empirical research and literature.
2

Inability of Gearing-Ratio as Predictor for Early Warning Systems

100%
Situm M.
Business Systems Research Journal
|
2014
|
vol. 5
|
issue 2
23-45
EN
Background: Research in business failure and insolvency prediction provides numerous potential variables, which are in the position to differentiate between solvent and insolvent firms. Nevertheless, not all of them have the same discriminatory power, and therefore their general applicability as crisis indicators within early warning systems seems questionable. Objectives: The paper aims to demonstrate that gearing-ratio is not an appropriate predictor for firm failures/bankruptcies. Methods/Approach: The first and the second order derivatives for the gearing-ratio formula were computed and mathematically analysed. Based on these results an interpretation was given and the suitability of gearing-ratio as a discriminator within business failure prediction models was discussed. These theoretical findings were then empirically tested using financial figures from financial statements of Austrian companies for the observation period between 2008 and 2010. Results: The theoretical assumptions showed that gearing-ratio is not a suitable predictor for early warning systems. This finding was confirmed with empirical data. Conclusions: The inclusion of gearing-ratio within business failure prediction models is not able to provide early warning signals and should therefore be ignored in future model building attempts.
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