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Business Failure Prediction: An emperical study based on Survival Analysis and Generalized Linear Modelling (GLM) Techniques

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  • Alhassan Bunyaminu

Abstract

This study investigated business failure using financial (ratios) and non-financial factors of listed companies on Ghana Stock Exchange. A combination of quantitative and qualitative variables have been used to predict corporate failure. Quantitatively, the study used 19 corporate determinants as predictors of business failure of listed companies on the Ghana Stock Exchange. The qualitative analysis used managerial (non-financial) factors to determine the success or otherwise of a business. An initial sample of 22 companies was divided into 70% estimation sample, 30% holdout sample and the overall prediction for a cumulative three-year data set.The study used the Cox proportional Hazard of Survival analysis technique and Generalised Linear Modelling (GLM) to predict business failure with an appreciable degree of accuracy. To reduce the dimentionality of the initial data space, the study initially used Factor Analysis(FA) by transforming a number of possibly correlated variables into a smaller number of uncorrelated variables called factor components. The study further employed Generalised Linear Modelling (GLM) with its three link functions-the Logit model, the Probit model and the Complementary log-log (Clog-log) function. Among the three link functions of GLM, the logit model provides the highest overall accuracy with the lowest Akaike Information Criteria (AIC): 46.456. The study reveals that among corporate determinants, the most significant variables that appear as consistent indicators of financial distressed companies in the superior model (logit model) are Profitability ratio (Return on total assets) and Leverage ratio (Solvency, Gearing and Interest cover). In connection with non-financial (managerial) factors used in the study, the study finds age and years of experience of managers as significant factors contributing to survival. The study recommends that future research should focus on business failure prediction that is based on tri-dimensional approach instead of the binary classification approach.

Suggested Citation

  • Alhassan Bunyaminu, 2015. "Business Failure Prediction: An emperical study based on Survival Analysis and Generalized Linear Modelling (GLM) Techniques," International Journal of Financial Economics, Research Academy of Social Sciences, vol. 4(3), pages 135-149.
    • Handle: RePEc:rss:jnljfe:v4i3p2
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    References listed on IDEAS

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    3. 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.
    4. Pamela K. Coats & L. Franklin Fant, 1993. "Recognizing Financial Distress Patterns Using a Neural Network Tool," Financial Management, Financial Management Association, vol. 22(3), Fall.
    5. 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.
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    1. Richard Oduro & Michael Amoh Aseidu, 2017. "A Model to Predict Corporate Failure in the Developing Economies: A Case of Listed Companies on the Ghana Stock Exchange," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 7(4), pages 1-5.

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