Neural Networks in Bankruptcy Prediction - A Comparative Study on the Basis of the First Hungarian Bankruptcy Model

The article attempts to answer the question whether or not the latest bankruptcy prediction techniques are more reliable than traditional mathematical–statistical ones in Hungary. Simulation experiments carried out on the database of the first Hungarian bankruptcy prediction model clearly prove that bankruptcy models built using artificial neural networks have higher classification accuracy than models created in the 1990s based on discriminant analysis and logistic regression analysis. The article presents the main results, analyses the reasons for the differences and presents constructive proposals concerning the further development of Hungarian bankruptcy prediction

Aggregate economy risk and company failure: An examination of UK quoted firms in the early 1990s

Considerable attention has been directed in the recent finance and economics literature to issues concerning the effects on company failure risk of changes in the macroeconomic environment. This paper examines the accounting ratio-based and macroeconomic determinants of insolvency exit of UK large industrials during the early 1990s with a view to improve understanding of company failure risk. Failure determinants are revealed from estimates based on a cross-section of 369 quoted firms, which is followed by an assessment of predictive performance based on a series of time-to-failure-specific logit functions, as is typical in the literature. Within the traditional for cross-sectional data studies framework, a more complete model of failure risk is developed by adding to a set of traditional financial statement-based inputs, the two variables capturing aggregate economy risk - one-year lagged, unanticipated changes in the nominal interest rate and in the real exchange rate. Alternative estimates of prediction error are obtained, first, by analytically adjusting the apparent error rate for the downward bias and, second, by generating holdout predictions. More complete, augmented with the two macroeconomic variables models demonstrate improved out-ofestimation- sample classificatory accuracy at risk horizons ranging from one to four years prior to failure, with the results being quite robust across a wide range of cutoff probability values, for both failing and nonfailed firms. Although in terms of the individual ratio significance and overall predictive accuracy, the findings of the present study may not be directly comparable with the evidence from prior research due to differing data sets and model specifications, the results are intuitively appealing. First, the results affirm the important explanatory role of liquidity, gearing, and profitability in the company failure process. Second, the findings for the failure probability appear to demonstrate that shocks from unanticipated changes in interest and exchange rates may matter as much as the underlying changes in firm-specific characteristics of liquidity, gearing, and profitability. Obtained empirical determinants suggest that during the 1990s recession, shifts in the real exchange rate and rises in the nominal interest rate, were associated with a higher propensity of industrial company to exit via insolvency, thus indicating links to a loss in competitiveness and to the effects of high gearing. The results provide policy implications for reducing the company sector vulnerability to financial distress and failure while highlighting that changes in macroeconomic conditions should be an important ingredient of possible extensions of company failure prediction models

Aggregate economy risk and company failure: An examination of UK quoted firms

Considerable attention has been directed in the recent finance and economics literature to issues concerning the effects on company failure risk of changes in the macroeconomic environment. This paper examines the accounting ratio-based and macroeconomic determinants of insolvency exit of UK large industrials during the early 1990s with a view to improve understanding of company failure risk. Failure determinants are revealed from estimates based on a cross-section of 369 quoted firms, which is followed by an assessment of predictive performance based on a series of time-to-failure-specific logit functions, as is typical in the literature. Within the traditional for cross-sectional data studies framework, a more complete model of failure risk is developed by adding to a set of traditional financial statement-based inputs, the two variables capturing aggregate economy risk - one-year lagged, unanticipated changes in the nominal interest rate and in the real exchange rate. Alternative estimates of prediction error are obtained, first, by analytically adjusting the apparent error rate for the downward bias and, second, by generating holdout predictions. More complete, augmented with the two macroeconomic variables models demonstrate improved out-ofestimation- sample classificatory accuracy at risk horizons ranging from one to four years prior to failure, with the results being quite robust across a wide range of cut-off probability values, for both failing and non-failed firms. Although in terms of the individual ratio significance and overall predictive accuracy, the findings of the present study may not be directly comparable with the evidence from prior research due to differing data sets and model specifications, the results are intuitively appealing. First, the results affirm the important explanatory role of liquidity, gearing, and profitability in the company failure process. Second, the findings for the failure probability appear to demonstrate that shocks from unanticipated changes in interest and exchange rates may matter as much as the underlying changes in firm-specific characteristics of liquidity, gearing, and profitability. Obtained empirical determinants suggest that during the 1990s recession, shifts in the real exchange rate and rises in the nominal interest rate, were associated with a higher propensity of industrial company to exit via insolvency, thus indicating links to a loss in competitiveness and to the effects of high gearing. The results provide policy implications for reducing the company sector vulnerability to financial distress and failure while highlighting that changes in macroeconomic conditions should be an important ingredient of possible extensions of company failure prediction models

Prediction of Insolvency of Life Insurance through Neural Networks

Past research studies have documented the failure of the Insurance Regulatory Information System (IRIS) to provide adequate warning of insurer financial distress or insolvency. As a result, scholars have examined alternative parametric and nonparametric models to predict insurer insolvency. This study uses a neural network, a non-parametric alternative to past techniques, and shows how this methodology more effectively predicts insurer insolvency than parametric models

Small, alone and poor: a merciless portrait of insolvent French firms, 2007-2010

This empirical paper investigates the path to bankruptcy for a sample of French firms in default, in particular the decision to file a petition for bankruptcy, the arbitrage between rescuing and liquidation and the effective survival. The procedure is depicted as a sequence of three steps in which judges play a crucial role as they decide whether a company is insolvent or not and determine whether an insolvent company deserves to be rescued or, on the contrary, should be liquidated, the market having the last word since the effective success depends on the capability of the firm to recover from the judicial proceedings. We test different hypotheses about the variables influencing each possibility which include i) the role of the market in the firm's health, ii) the influence of financial structures, iii) the importance of corporate governance and iv) the inherent corporate factors of probable survival. Using three linked LOGIT models, our first finding is that the probability to default depends mainly on the market. Secondly the probability to be rescued depends essentially on the financial structure. Finally, the probability for the firm to remain in business in the long term is largely influenced by the market and profitability. Our results also support the idea that governance, size and resources are the main determinants of exit from the market or success of any company.Insolvency, bankruptcy, firm default, financial indicators, size, logit models.

Synthesis of research studies examining prediction of bankruptcy

The purpose of this study is to synthesize the findings of prior bankruptcy prediction research studies by compiling and classifying the independent variables used as predictor variables in the studies. The objective is to find out the popularity of the different types of the predictor variables by classifying the variables into the categories describing the fincancial function of the variables, and by assessing the popularity of the significant variables in the categories. This work studies elementary theories on firm failure and bankruptcy to discuss and seek justitication for what might be the reasons for using the most popular financial function measures in the bankruptcy prediction. Bankruptcy prediction research literature covers vast amount of studies in which various different predicton models are developed for predicting bankruptcy. Usually these studies use a prediction model with a set of some financial and/or non-financial variables that are presumed to be relevant proxies for financial distress and eventually business failure and bankrupcty. However, there seems to be no consensus or unified theory on how the variables predicting bankrupcty should be selected, thus the numerous bankruptcy prediction research studies include vast number and various different types of variables that are presumed to be applicable in predicting bankruptcy. This study includes a systematic literature review where 51 bankruptcy prediction research studies were collected from well-recognized scientific journals. The studies included into the review were such that included a single or multiple bankruptcy prediction models, the detailed description of the independent variables, and the information about the statistical significances of the independent variables. The variables were then classified according to their financial function and a meta-analysis were conducted on those variables which were significant in bankruptcy prediction, to find out the popularity of the different variable categories. The findings of this study suggest that the most popular predictor variables included into the banktuptcy predicton models are accounting-based financial ratios, particurarly ones measuring liquidity, profitability, and financial leverage, and that there exists also theoretical foundation for using these variables in the bankruptcy prediction

Corporate Bankruptcy Prediction

Bankruptcy prediction is one of the most important research areas in corporate finance. Bankruptcies are an indispensable element of the functioning of the market economy, and at the same time generate significant losses for stakeholders. Hence, this book was established to collect the results of research on the latest trends in predicting the bankruptcy of enterprises. It suggests models developed for different countries using both traditional and more advanced methods. Problems connected with predicting bankruptcy during periods of prosperity and recession, the selection of appropriate explanatory variables, as well as the dynamization of models are presented. The reliability of financial data and the validity of the audit are also referenced. Thus, I hope that this book will inspire you to undertake new research in the field of forecasting the risk of bankruptcy

Analysing Financial Distress in Malaysian Islamic Banks: Exploring Integrative Predictive Methods

Against the background of global financial crisis, some argue in favour of the ‘resilience’ of Islamic finance, while others suggest that Islamic financial institutions are not more prone to distress and crisis than their conventional counterparts. However, there have been a number of cases of Islamic finance and banking distress in recent years, including instances in Malaysia. These cases, hence, motivated this study in terms of emphasising the importance of employing financial distress prediction models for analysing Islamic banks. This study aims at empirically exploring, examining and analysing the financial distress of the Malaysian Islamic banks. In doing so, the effectiveness of the existing early warning statistical insolvency prediction models that have been used in previous studies, and a particular model adapted by Islamic banks in Malaysia were critically evaluated. This study, hence, employed a number of models to predict the financial distress faced by Islamic banks in Malaysia. In addition, an attempt was made at the modification of the existing early warning insolvency prediction models in evaluating and analysing the financial distress of Malaysian Islamic banks. This research is constructed within four empirical chapters by employing three prediction models in assessing the financial distress of Islamic banks. The first empirical chapter analyses the secondary data collected from a sample of Islamic banks, based on selected ratios developed in the literature, whereby a comprehensive description of these selected financial ratios in terms of descriptive statistical analysis for the selected Islamic banks in Malaysia is provided. The second empirical chapter investigates the performance of the ‘emerging market Z-score’, introduced by Altman in predicting the performance of Islamic banks and conventional banks in Malaysia. The study aimed to introduce the EM Z-score as a valuable analytical tool in monitoring the deterioration of the performance of banks as well as looking at the impact of the global financial crisis on the performance of Islamic and conventional banks. This chapter examines thirteen Islamic banks and ten conventional banks during the period of 2005-2010. The results show that the EM Z-score for all banks is well above the cut-off point of 2.6, although for Islamic banks the EM Z-score showed a declining trend whilst for conventional banks it showed an increasing trend. This empirical evidence is important for the banks since it provides a warning signal to the banks’ management as well as the related parties involved in the planning, controlling and decision making process. The third empirical chapter presents the newly constructed integrated predictive model designed to evaluate and analyse the financial distress of Islamic banks in Malaysia, which can be used as an alternative model for regulators in monitoring the performance of Islamic banks that are experiencing any serious financial problems. This paper develops a preliminary model for the prediction of the performance level of Islamic financial institutions for the period of December 2005 to September 2010 by using quarterly data for ten selected Islamic banks in Malaysia. For this, factor analysis and three parametric models (discriminant analysis, logit analysis and probit analysis) are used. The results depict that the first few quarters before the benchmark quarter are the most important period for making a correct prediction and crucial decisions on the survival of Islamic banks. Thus, the results demonstrate the predictive ability of the integrated model to differentiate between the healthy and non-healthy Islamic banks, therefore reducing the expected cost of bank failure. The fourth empirical chapter conducts further exploration in predicting the financial distress position of Islamic banks by introducing new variables such as the funding structure, deposit composition, and macroeconomic variables. Using the same sample and data set for Islamic banks as in the previous chapter, this study shows the relationship between the banks’ funding profiles and other alternative variables, and the Islamic banks’ performance in Malaysia. For this, the logit model is used. Based on the results of all models, this study recommended two final models, which showed an excellent fit for predicting the Islamic banks’ performance. The results indicate that none of the macroeconomic variables included were significant, thus suggesting that the performance of Islamic banks in Malaysia was not affected by the economic conditions throughout the study period. This can perhaps be attributed to efficient regulation and supervision by the relevant authorities in the country