Early warning models against bankruptcy risk for Central European and Latin American enterprises

Korol, Tomasz

doi:10.1016/j.econmod.2012.11.017

Cited by 81 publications

(73 citation statements)

References 21 publications

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“…Studies (Korol, 2013;Sharma and Mahjan, 1980) have shown that failed businesses show sign of their hailing between a couple of (2-5) years before their failure and a year afterwards. This study therefore compares the rate of change in the pieces of information over these periods for each of the companies in this investigation.…”

Section: Methodsmentioning

confidence: 99%

Non-Financial Risk Disclosure: The Case of the UK’s Distressed Banks

Adelopo¹

2017

AABFJ

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This study investigates the narratives risk disclosures of the four British financial institutions that were adversely affected during the 2008 banking crisis. This investigation uses content analysis with the aid of Concordance software to explore the risk disclosure of these companies for the period 1998-2008. Risk disclosures in the Business Review sections of the annual reports of the banks were analysed into their historic and forward looking contents, and current firm performance was measured with respect to earnings per share (EPS) and dividend, while future performance was measured by growth in EPS, and positive time lag in EPS.Consistent with its predictions, the study found a significant negative relationship between the extent of historic narrative disclosures and current and future firm performance, and a significant positive relationship between forward looking narrative risk disclosures and both current and future firm performance. Additional analysis shows that optimistic and pessimistic narrative risk disclosures are not significant in explaining current and future firm performance for these firms.Findings from this study are important for users of the financial statements and regulators because they highlight an opportunity to detect warning signals for companies at risk of collapse. The study adds to the growing number of empirical investigations that provide alternative approaches to understanding business failures. AbstractThis study investigates the narratives risk disclosures of the four British financial institutions that were adversely affected during the 2008 banking crisis. This investigation uses content analysis with the aid of Concordance software to explore the risk disclosure of these companies for the period 1998-2008. Risk disclosures in the Business Review sections of the annual reports of the banks were analysed into their historic and forward looking contents, and current firm performance was measured with respect to earnings per share (EPS) and dividend, while future performance was measured by growth in EPS, and positive time lag in EPS. Consistent with its predictions, the study found a significant negative relationship between the extent of historic narrative disclosures and current and future firm performance, and a significant positive relationship between forward looking narrative risk disclosures and both current and future firm performance. Additional analysis shows that optimistic and pessimistic narrative risk disclosures are not significant in explaining current and future firm performance for these firms. Findings from this study are important for users of the financial statements and regulators because they highlight an opportunity to detect warning signals for companies at risk of collapse. The study adds to the growing number of empirical investigations that provide alternative approaches to understanding business failures. JEL Classification: M40

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Section: Methodsmentioning

confidence: 99%

Non-Financial Risk Disclosure: The Case of the UK’s Distressed Banks

Adelopo¹

2017

AABFJ

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“…The business failure is considered to be the result of an evolutionary process (González-Bravo & Mecaj, 2011; Korol, 2013). In fact, financial distress of a company is a dynamic ongoing process, and is the result of continuous abnormality of business operation for a period of time (Sun, Li, Huang, & He, 2014).…”

Section: Review Of the Literature And Hypothesesmentioning

confidence: 99%

Dynamic analysis of different business failure process

Flores-Jimeno¹,

García²

2017

Problems and Perspectives in Management

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This work is framed in the research of business failure. We examine a method of analyzing the dynamics of financial failure. The authors examine a method of analyzing the dynamics of financial failure, because our goal is to analyze how the economic and financial indicators show the risk of failure in a group of companies. Using a sample of 163 companies declared bankrupt or dissolved, the authors show how to depict company trajectories of behavior and movement to terminal failure. They analyze these trajectories to find and describe empirical evidence of the different dynamics of bankruptcy. The authors also show that the estimation of failure risk is more accurate when these different failure trajectories are defined. In conclusion, the authors can see that there are different failure trajectories. One can use these different trajectories to identify more efficiently the indicators warning of the failure risk of the companies analyzed.Rocío Flores-Jimeno (Spain), Inmaculada Jimeno-García (Spain)

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“…As these models can be applied in dynamic environments without the need of regular redesign (Tan, undated), they are prime candidates for use in the new environments. Finally, ANNs perform well with vaguely defined problems, unfinished data, inaccuracies and uncertainties (Korol, 2013). …”

Section: 3mentioning

confidence: 99%

“…ANNs have been applied in a number of areas in the financial markets, including fore casting forward interest rates (Bouqata, Bensaid & Palliam, 1999), estimating general insurance reserves (Braun & Lai, 2005), evaluating credit risk (Fei & Zhigang, 2008), detecting credit card fraud (Sahin & Duman, 2011), analysing stock exchange movements (Abhishek et al, 2012;O'Connor & Madden, 2006), forecasting commodity prices (Kohzadi et al, 1996) and foreign exchange rates (Tan, undated), and predicting credit union distress and bankruptcy (Korol, 2013;Tsai & Wu, 2008;Saha, 2009;Lacher et al, 1995;Tan, undated).…”

Section: 5mentioning

confidence: 99%

A method of parameterising a feed forward multi-layered perceptron artificial neural network, with reference to South African financial markets

2016

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No analytic procedures currently exist for determining optimal artificial neural network structures and parameters for any given application. Traditionally, when artificial neural networks have been applied to financial modelling problems, structure and parameter choices are often made a priori without sufficient consideration of the effect of such choices. A key aim of this study is to develop a general method that could be used to construct artificial neural networks by exploring the model structure and parameter space so that informed decisions could be made relating to the model design. In this study, a formal approach is followed to determine suitable structures and parameters for a Feed Forward Multi-layered Perceptron artificial neural network with a Resilient Propagation learning algorithm with a single hidden layer. This approach is demonstrated through the modelling of four South African economic variables, namely the average monthly returns on the money, bond and equity markets as well as monthly inflation. Artificial neural networks can be constructed on the aforementioned variables in isolation or, jointly, in an integrated model. The performance of a range of more traditional time series models is compared with that of the artificial neural network models. The results suggest that, on a statistical level, artificial neural networks perform as well as time series models at forecasting the returns for financial markets. Hybrid models, combining artificial neural networks with the time series models, are constructed, trained and tested for the money market and for the rate of inflation. They appear to add value to the time series models when forecasting inflation, but not for the money market.

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Early warning models against bankruptcy risk for Central European and Latin American enterprises

Cited by 81 publications

References 21 publications

Non-Financial Risk Disclosure: The Case of the UK’s Distressed Banks

Non-Financial Risk Disclosure: The Case of the UK’s Distressed Banks

Dynamic analysis of different business failure process

A method of parameterising a feed forward multi-layered perceptron artificial neural network, with reference to South African financial markets

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