Predicting Bankruptcy: Evidence from Israel

Lifschutz, Shilo

doi:10.5539/ijbm.v5n4p133

Cited by 29 publications

(21 citation statements)

References 26 publications

(25 reference statements)

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“…Lifschutz and Jacobi (2010) showed that the Ingbar version of the Altman Model having a critical value of 1 was a preferable model for predicting financial failure. Using multiple discriminant analysis, Bhunia and Sarkar (2011) found 7 out of 16 financial ratios to be significant in discriminating power.…”

Section: Literature Reviewmentioning

confidence: 99%

Default risk modelling using macroeconomic variables

Agrawal

Maheshwari

2014

Journal of Indian Business Research

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2006),"Predicting probability of default of Indian corporate bonds: logistic and Z-score model approaches", If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -This paper aims to find out significant macroeconomic variables, incorporated as sensitivity variables (macroeconomic sensitivities), affecting financial distress for a sample of listed Indian firms. Design/methodology/approach -The study uses a matched pair sample of defaulting and non-defaulting listed Indian firms. It uses two alternative statistical techniques, viz., logistic regression and multiple discriminant analysis. The macroeconomic sensitivities are estimated by regressing the monthly stock return of the individual firm on the monthly changes in each macroeconomic variable. Findings -Sensitivity to changes in the stock market (stock market sensitivity) and sensitivity to changes in inflation [Consumer Price Index (CPI) sensitivity] have a significant impact on the default probability of a firm. Stock market sensitivity has a significant positive relationship with the probability of default, and CPI sensitivity has a significant negative relationship with the probability of default. Originality/value -The study links the developments in the external environment to the firm's susceptibility to default. Furthermore, it highlights the significance of sensitivity of a firm to uncertainties in the macroeconomic environment and its impact on default risk. This establishes the fact that each firm is uniquely affected by the changes in the overall macroeconomic environment. The findings could be valuable to lenders such as banks and financial institutions, investors and policymakers.

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Section: Literature Reviewmentioning

confidence: 99%

Default risk modelling using macroeconomic variables

Agrawal

Maheshwari

2014

Journal of Indian Business Research

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“…Bankruptcy is a state of insolvency in which an enterprise is unable to repay a creditor the amount of debt, whereby a situation will arise when the value of the debt is higher than the value of the property. The ability to predict bankruptcy is an important issue for many users of financial statements, such as banks, investors, rating agencies, auditors, insurance companies, and legislators (Lifschutz & Jacobi, 2010). Financial statements are one of the key sources of information for all users, so it is crucial that they are reviewed and analyzed in more detail (Mitrović & Vučić, 2015;Vasilev et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Bankruptcy forecasting of hotel companies in the Republic of Serbia using Altman's Z-score model

Milašinović

Knežević

Mitrović

2019

Menadž u hotelijerstvu i turiz

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Monitoring the financial health of a company to prevent bankruptcy is not only a matter of interest to owners, management and creditors as previously thought, but also a subject of interest to the wider community due to the consequences that bankruptcy may cause. There are numerous models for predicting bankruptcy, but one of the most commonly used is Altman's Z-score model. Over time, the model has been modified so that from its initial form that was intended solely for one enterprise model, today we have a model that can be applied to manufacturing, service, public and private enterprises, as well as to businesses operating in developing markets. The paper uses Altman's Z-score model for companies operating in developing markets to assess the financial health, that is, the possibility of bankruptcy in a sample of 7 hotel companies listed on the Belgrade Stock Exchange.

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“…Being the first person to successfully develop multiple discriminate analysis (MDA) prediction model with a degree of 95.0% rate of accuracy, he is considered the pioneer of insolvency predictors. Altman´s model has been applied successfully in many studies worldwide concerning the subjects of capital structure and strategic management, investment decisions, asset and credit risk estimation and financial failure of publicly traded companies (Lifschutz and Jacobi, 2010). For many years thereafter, MDA was the prevalent method applied to the default prediction models.…”

Section: Literature Reviewmentioning

confidence: 99%

Comparative Analysis of Credit Risk Models in Relation to SME Segment

Plíhal

Sponerová

Sponer

2018

FAI

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The importance of credit risk management is well known and was deeply investigated by the banking industry. There is a pressure on financial institutions to still improve their credit risk management systems, so the credit risk of a bank is an unflagging object of discussion. The aim of this article to compare the predicting abilities of several bankruptcy models to the SME segment in the Czech Republic and its subsegments-medium sized, small and micro enterprises. We have focused on small and medium sized enterprises (SMEs) considering their fundamental role played in the Czech economy and the considerable attention placed on SMEs. We have chosen popular bankruptcy models that are often applied, namely the Altman Z-score, Altman model developed especially for SMEs in 2007, the Ohlson O-score, the Zmijewski's model, the Taffler's model, and the IN05 model. The basic form of the models was used as proposed by their authors. The results were compared using the contingency table and ROC curve. We have found that the best prediction models are Zmijewski´s and Ohlson´s models which use probit and logit methodologies and according to our analysis, their prediction ability is better than that of models based on discriminant analysis. Surprisingly, model IN05 designed for Czech companies provides average results only. One of the worst performing models is Altman 2007, which was created specifically for SMEs, but according to our analysis it only provides subordinates results.

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Predicting Bankruptcy: Evidence from Israel

Cited by 29 publications

References 26 publications

Default risk modelling using macroeconomic variables

Default risk modelling using macroeconomic variables

Bankruptcy forecasting of hotel companies in the Republic of Serbia using Altman's Z-score model

Comparative Analysis of Credit Risk Models in Relation to SME Segment

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