A Review of Bankruptcy Prediction Studies: 1930 to Present

One of the most well-known bankruptcy prediction models was developed by Altman [1968] using multivariate discriminant analysis. Since Altman's model, a multitude of bankruptcy prediction models have flooded the literature. The primary goal of this paper is to summarize and analyze existing research on bankruptcy prediction studies in order to facilitate more productive future research in this area. This paper traces the literature on bankruptcy prediction from the 1930's, when studies focused on the use of simple ratio analysis to predict future bankruptcy, to present. The authors discuss how bankruptcy prediction studies have evolved, highlighting the different methods, number and variety of factors, and specific uses of models. Analysis of 165 bankruptcy prediction studies published from 1965 to present reveals trends in model development. For example, discriminant analysis was the primary method used to develop models in the 1960's and 1970's. Investigation of model type by decade shows that the primary method began to shift to logit analysis and neural networks in the 1980's and 1990's. The number of factors utilized in models is also analyzed by decade, showing that the average has varied over time but remains around 10 overall. Analysis of accuracy of the models suggests that multivariate discriminant analysis and neural networks are the most promising methods for bankruptcy prediction models. The findings also suggest that higher model accuracy is not guaranteed with a greater number of factors. Some models with two factors are just as capable of accurate prediction as models with 21 factors.

[1]  Marc Blum.  FAILING COMPANY DISCRIMINANT-ANALYSIS , 1974 .

[2]  Erkki K. Laitinen,et al.  Survival analysis as a tool for company failure prediction , 1991 .

[3]  E. Altman,et al.  ZETATM analysis A new model to identify bankruptcy risk of corporations , 1977 .

[4]  Constantin Zopounidis,et al.  A survey of business failures with an emphasis on prediction methods and industrial applications , 1996 .

[5]  Kenth Skogsvik,et al.  CURRENT COST ACCOUNTING RATIOS AS PREDICTORS OF BUSINESS FAILURE: THE SWEDISH CASE , 1990 .

[6]  J. D. Vinso,et al.  Estimating the probability of failure for commercial banks and the banking system , 1977 .

[7]  Kimmo Kiviluoto,et al.  Predicting bankruptcies with the self-organizing map , 1998, Neurocomputing.

[8]  Osama El-Temtamy.  Bankruptcy prediction : a comparative study of logit and neural networks , 1995 .

[9]  Moshe Leshno,et al.  Neural network prediction analysis: The bankruptcy case , 1996, Neurocomputing.

[10]  Luyuan Gao,et al.  Study of business failure in the hospitality industry from both microeconomic and macroeconomic perspectives , 1999 .

[11]  R.H.A. Hennawy,et al.  THE SIGNIFICANCE OF BASE YEAR IN DEVELOPING FAILURE PREDICTION MODELS , 1983 .

[12]  Panayiotis Theodossiou,et al.  ALTERNATIVE MODELS FOR ASSESSING THE FINANCIAL CONDITION OF BUSINESS IN GREECE , 1991 .

[13]  Paul Newbold,et al.  CLASSIFYING BANKRUPT FIRMS WITH FUNDS FLOW COMPONENTS , 1985 .

[14]  J. Wilcox.  PREDICTION OF BUSINESS FAILURE USING ACCOUNTING DATA , 1973 .

[15]  R. Moyer.  Forecasting Financial Failure: A Re-Examination , 1977 .

[16]  Kevin Keasey,et al.  The Prediction of Small Company Failure: Some Behavioural Evidence for the UK , 1986 .

[17]  Geoff Meeks,et al.  THE EXCHANGE RATE AND COMPANY FAILURE IN A MACRO-MICRO MODEL OF THE UK COMPANY SECTOR* , 1991 .

[18]  Larry George Gru.  Financial ratios, multiple discriminant analysis and the prediction of small corporate failure , 1973 .

[19]  Gordon V. Karels,et al.  Multivariate Normality and Forecasting of Business Bankruptcy , 1987 .

[20]  F. T. Magiera.  Forecasting Bankruptcy More Accurately: A Simple Hazard Model , 2001 .

[21]  G. V. Henderson,et al.  A Brief Review of Catastrophe Theory and a Test in a Corporate Failure Context , 1991 .

[22]  Kung H. Chen,et al.  An Empirical Analysis of Useful Financial Ratios , 1981 .

[23]  Kathleen L. Henebry.  Do cash flow variables improve the predictive accuracy of a Cox proportional hazards model for bank failure , 1996 .

[24]  Yong Jiang,et al.  Bankruptcy prediction : a nonparametrick approach , 1993 .

[25]  Marjorie B. Platt,et al.  Predicting commercial bank failure since deregulation , 1987 .

[26]  Thomas E. McKee.  Predicting bankruptcy via induction , 1995, J. Inf. Technol..

[27]  Chavalit Arkaradejdachachai.  Study of corporate turnaround : using a probability of bankruptcy , 1993 .

[28]  Mohamed A. Nour.  Improved clustering and classification algorithms for the Kohonen self-organizing neural network , 1994 .

[29]  G. William Glezen,et al.  Bankruptcy Prediction Using Quarterly Financial Statement Data , 1992 .

[30]  Desmond Fletcher,et al.  Forecasting with neural networks: An application using bankruptcy data , 1993, Inf. Manag..

[31]  Anthony Joseph Zordan.  Cash flow ratios as predictors of business failure , 1998 .

[32]  W. R. Lane,et al.  An application of the cox proportional hazards model to bank failure , 1986 .

[33]  G. E. Pinches,et al.  The hierarchical classification of financial ratios , 1975 .

[34]  J. Efrim Boritz,et al.  Effectiveness of neural network types for prediction of business failure , 1995 .

[35]  E. Mine Cinar,et al.  Neural Networks: A New Tool for Predicting Thrift Failures , 1992 .

[36]  Paul L. Foster,et al.  Judgmental Approach to Forecasting Bankruptcy , 1997 .

[37]  Marjorie B. Platt,et al.  Predicting Failure of Savings & Loan Associations , 1987 .

[38]  R. Taffler.  Empirical models for the monitoring of UK corporations , 1984 .

[39]  David E. Booth,et al.  The use of fuzzy clustering algorithm and self-organizing neural networks for identifying potentially failing banks: an experimental study , 2000 .

[40]  H. Frydman,et al.  Introducing Recursive Partitioning for Financial Classification: The Case of Financial Distress , 1985 .

[41]  J. Swart,et al.  Financial Aspects of Corporate Net Worth.@@@Changes in the Financial Structure of Unsuccessful Industrial Corporations. , 1936 .

[42]  Raymond McNamara,et al.  PREDICTING PRIVATE COMPANY FAILURE , 1988 .

[43]  Cornelius J. Casey,et al.  Using Operating Cash Flow Data to Predict Financial Distress: Some Extensions , 1985 .

[44]  Ian Zimmer,et al.  A LENS STUDY OF THE PREDICTION OF CORPORATE FAILURE BY BANK LOAN OFFICERS , 1980 .

[45]  Ramesh Sharda,et al.  Bankruptcy prediction using neural networks , 1994, Decis. Support Syst..

[46]  F Jones,et al.  CURRENT TECHNIQUES IN BANKRUPTCY PREDICTION , 1987 .

[47]  Paul Thomas McGurr.  Failure prediction of retail firms through use of financial ratios , 1998 .

[48]  E. Altman.  Predicting Railroad Bankruptcies in America , 1973 .

[49]  J. Edward Ketz,et al.  The Effect of General Price-Level Adjustments on the Predictive Ability of Financial Ratios , 1978 .

[50]  Murugan Anandarajan,et al.  Bankruptcy Prediction Using Neural Networks , 2004 .

[51]  David D. Williams,et al.  Cash Flow in Bankruptcy Prediction , 1987 .

[52]  Abdul Aziz,et al.  Cash Flow Reporting and Financial Distress Models: Testing of Hypotheses , 1989 .

[53]  Daniel Martin,et al.  Early warning of bank failure: A logit regression approach , 1977 .

[54]  Panayiotis Theodossiou.  Predicting Shifts in the Mean of a Multivariate Time Series Process: An Application in Predicting Business Failures , 1993 .

[55]  Marjorie B. Platt,et al.  Probabilistic Neural Networks in Bankruptcy Prediction , 1999 .

[56]  Mo Adam Mahmood,et al.  A PREFORMANCE ANALYSIS OF PARAMETRIC AND NONPARAMETRIC DISCRIMINANT APPROACHES TO BUSINESS DECISION MAKING , 1987 .

[57]  Anurag Agarwal.  Neural networks and their extensions for business decision making , 1993 .

[58]  A. Lau.  A 5-State Financial Distress Prediction Model , 1987 .

[59]  Charles P. Jones,et al.  An Analysis of Risk and Return Characteristics of Corporate Bankruptcy Using Capital Market Data , 1980 .

[60]  Gerald A. Hanweck,et al.  Predicting bank failure , 1977 .

[61]  James A. Ohlson.  FINANCIAL RATIOS AND THE PROBABILISTIC PREDICTION OF BANKRUPTCY , 1980 .

[62]  Constantin Zopounidis,et al.  Business failure prediction using the UTADIS multicriteria analysis method , 1999, J. Oper. Res. Soc..

[63]  Michael Y. Hu,et al.  Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis , 1999, Eur. J. Oper. Res..

[64]  Ann Gaeremynck,et al.  The endogenous relationship between audit-report type and business termination: evidence on private firms in a non-litigious environment , 2003 .

[65]  Paul L. Foster.  Judgmental Approach to Forecasting , 1996 .

[66]  H. S. Diamond,et al.  Pattern recognition and the detection of corporate failure , 1976 .

[67]  Edward I. Altman,et al.  Bankruptcy, Credit Risk, and High Yield Junk Bonds , 2002 .

[68]  R. O. Edmister,et al.  JOURNAL OF FINANCIAL AND QUANTITATIVE ANALYSIS March 1972 AN EMPIRICAL TEST OF FINANCIAL RATIO ANALYSIS FOR SMALL BUSINESS FAILURE PREDICTION , 2009 .

[69]  Sandro Appetiti,et al.  Identifying unsound firms in Italy: An attempt to use trend variables , 1984 .

[70]  Charles Lewis Merwin,et al.  Financing small corporations in five manufacturing industries, 1926-1936 : a dissertation in economics , 1942 .

[71]  C. Zavgren.  ASSESSING THE VULNERABILITY TO FAILURE OF AMERICAN INDUSTRIAL FIRMS: A LOGISTIC ANALYSIS , 1985 .

[72]  Cornelius J. Casey.  The Usefulness Of Accounting Ratios For Subjects Predictions Of Corporate Failure - Replication And Extensions , 1980 .

[73]  C. Lennox.  The Accuracy and Incremental Information Content of Audit Reports in Predicting Bankruptcy , 1999 .

[74]  E. Deakin.  Discriminant Analysis Of Predictors Of Business Failure , 1972 .

[75]  Andrew W. Lo.  Essays in financial and quantitative economics , 1984 .

[76]  Walter A. Chudson,et al.  The Pattern of Corporate Financial Structure. , 1945 .

[77]  Ingoo Han,et al.  Hybrid neural network models for bankruptcy predictions , 1996, Decis. Support Syst..

[78]  Mark Eugene Zmijewski.  Essays on corporate bankruptcy , 1983 .

[79]  M. Peel,et al.  Neural Network Simulation and the Prediction of Corporate Outcomes: Some Empirical Findings , 1995 .

[80]  Hian Chye Koh,et al.  Prediction of going-concern status : a probit model for the auditors , 1987 .

[81]  Ramesh Sharda,et al.  A neural network model for bankruptcy prediction , 1990, 1990 IJCNN International Joint Conference on Neural Networks.

[82]  E. Laitinen.  FINANCIAL RATIOS AND DIFFERENT FAILURE PROCESSES , 1991 .

[83]  P. Meyer,et al.  PREDICTION OF BANK FAILURES , 1970 .

[84]  James C. Flagg,et al.  PREDICTING CORPORATE BANKRUPTCY USING FAILING FIRMS , 1991 .

[85]  Abdul Aziz,et al.  BANKRUPTCY PREDICTION ‐ AN INVESTIGATION OF CASH FLOW BASED MODELS[1] , 1988 .

[86]  James V. Hansen,et al.  Inducing rules for expert system development: an example using default and bankruptcy data , 1988 .

[87]  Pouran Espahbodi,et al.  Identification of problem banks and binary choice models , 1991 .

[88]  I. G. Dambolena,et al.  Ratio Stability and Corporate Failure , 1980 .

[89]  R. Libby.  Accounting Ratios and the Prediction of Failure: Some Behavioral Evidence , 1975 .

[90]  Kar Yan Tam,et al.  Neural network models and the prediction of bank bankruptcy , 1991 .

[91]  Panayiotis Theodossiou,et al.  Predicting Corporate Financial Distress: A Time-Series CUSUM Methodology , 1998 .

[92]  H. Izan.  Corporate distress in Australia , 1984 .

[93]  Namsik Chang,et al.  Dynamics of Modeling in Data Mining: Interpretive Approach to Bankruptcy Prediction , 1999, J. Manag. Inf. Syst..

[94]  Terry J. Ward,et al.  AN EMPIRICAL STUDY OF THE INCREMENTAL PREDICTIVE ABILITY OF BEAVER'S NAIVE OPERATING FLOW MEASURE USING FOUR-STATE ORDINAL MODELS OF FINANCIAL DISTRESS , 1994 .

[95]  Kazunori Watase,et al.  Corporate bankruptcy prediction in Japan , 1984 .

[96]  D. Patterson,et al.  Bankruptcy prediction: A model for the casino industry , 2000 .

[97]  David E. Booth,et al.  Pattern classification and clustering algorithms with supervised and unsupervised neural networks in financial applications , 2001 .

[98]  Edward I. Altman,et al.  FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY , 1968 .

[99]  Carlos Serrano-Cinca,et al.  Self organizing neural networks for financial diagnosis , 1996, Decision Support Systems.

[100]  TamKar Yan,et al.  Predicting bank failures , 1990 .

[101]  S. Oswald,et al.  Prediction of hospital failure: a post-PPS analysis. , 1996, Hospital & health services administration.

[102]  Qing Guan.  Development of optimal network structures for back -propagation-trained neural networks , 1993 .

[103]  Doris M. Cook,et al.  Using Cash Flow Ratios to Predict Business Failures , 1995 .

[104]  Stephanie M. Bryant,et al.  A case-based reasoning approach to bankruptcy prediction modeling , 1997, Intell. Syst. Account. Finance Manag..

[105]  Edward I. Altman,et al.  A FINANCIAL EARLY WARNING SYSTEM FOR OVER-THE-COUNTER BROKER-DEALERS , 1976 .

[106]  Larry N. Killough,et al.  The USE OF MULTIPLE DISCRIMINANT ANALYSIS IN THE ASSESSMENT OF THE GOING-CONCERN STATUS OF AN AUDIT CLIENT , 1990 .

[107]  Kenneth B. Schwartz,et al.  PREDICTING BANKRUPTCY FOR FIRMS IN FINANCIAL DISTRESS , 1990 .

[108]  David Martin Bukovinsky.  Cash flow and cash position measures in the prediction of business failure : an empirical study , 1993 .

[109]  E. Altman.  The success of business failure prediction models: An international survey , 1984 .

[110]  Vijay Mahajan,et al.  Early Warning Indicators of Business Failure , 1980 .

[111]  Constantin Zopounidis,et al.  Business failure prediction using rough sets , 1999, Eur. J. Oper. Res..

[112]  W. Beaver.  Financial Ratios As Predictors Of Failure , 1966 .

[113]  J. Sinkey.  A MULTIVARIATE STATISTICAL ANALYSIS OF THE CHARACTERISTICS OF PROBLEM BANKS , 1975 .

[114]  Gottfried Rudorfer.  Early bankruptcy detection using neural networks , 1995 .

[115]  Zoltan Matolcsy,et al.  The Prediction of Corporate Failure: Testing the Australian Experience , 1981 .

[116]  Monty L. Lynn,et al.  Development of a Prediction Model for Hospital Closure Using Financial Accounting Data , 1993 .

[117]  Ismael G. Dambolena,et al.  A Primary Rule for Detecting Bankruptcy: Watch the Cash , 1988 .

[118]  Ingoo Han,et al.  Bankruptcy prediction using case-based reasoning, neural networks, and discriminant analysis , 1997 .

[119]  Margaret Mary Devine Dwyer.  A comparison of statistical techniques and artificial neural network models in corporate bankruptcy prediction , 1992 .

[120]  B. Yegnanarayana,et al.  Artificial Neural Networks , 2004 .

[121]  D. Hensher,et al.  Predicting Firm Financial Distress: A Mixed Logit Model , 2004 .

[122]  Nathaniel Jackendoff,et al.  A study of published industry financial and operating ratios , 1962 .

[123]  D. T. Cadden.  Neural networks and the mathematics of chaos-an investigation of these methodologies as accurate predictors of corporate bankruptcy , 1991, Proceedings First International Conference on Artificial Intelligence Applications on Wall Street.

[124]  Marjorie B. Platt,et al.  BANKRUPTCY DISCRIMINATION WITH REAL VARIABLES , 1994 .

[125]  Bin Wang,et al.  Strategy changes and internet firm survival , 2004 .

[126]  J. Sinkey,et al.  Establishing On‐Site Bank Examination Priorities: An Early‐Warning System Using Accounting and Market Information , 1980 .

[127]  Melody Y. Kiang,et al.  Managerial Applications of Neural Networks: The Case of Bank Failure Predictions , 1992 .

[128]  Junsei Tsukuda,et al.  Predicting Japanese corporate bankruptcy in terms of financial data using neural network , 1994 .