Cash Management Behavior and Failure Prediction

Laitinen, Erkki K.; Laitinen, Teija

doi:10.1111/1468-5957.00218

Cited by 26 publications

(12 citation statements)

References 20 publications

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“…Apart from the aforementioned concepts, belonging to the most commonly used in the field of bankruptcy forecasting, the following approaches can be found in the literature of the subject: rough set theory (Slowinski and Zopounidis 1995), cash management methods (Laitinen and Laitinen 1998), catastrophe theory (Gregory-Allen and Henderson 1991), multicriteria decision aid methodology (Zopounidis and Doumpos 1999), Case-Based Reasoning (Park and Han 2002), Data Envelopment Analysis (Premachandra et al 2009), multidimensional scaling (Molinero and Ezzamel 1991), concepts based on the entropy theory (Bal et al 2013), pattern recognition method (Kolari et al 1996), the self-organizing map method (Kiviluoto 1998;Du Jardin and Séverin 2011), bankruptcy trajectories (Argenti 1976;Du Jardin and Séverin 2010) and opinions of auditors on the continuation of business activity of the surveyed companies (Carson et al 2013).…”

Section: Global Experience-literature Reviewmentioning

confidence: 99%

Review of Research into Enterprise Bankruptcy Prediction in Selected Central and Eastern European Countries

Prusak

2018

IJFS

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Abstract:In developed countries, the first studies on forecasting bankruptcy date to the early 20th century. In Central and Eastern Europe, due to, among other factors, the geopolitical situation and the introduced economic system, this issue became the subject of researcher interest only in the 1990s. Therefore, it is worthwhile to analyze whether these countries conduct bankruptcy risk assessments and what their level of advancement is. The main objective of the article is the review and assessment of the level of advancement of bankruptcy prediction research in countries of the former Eastern Bloc, in comparison to the latest global research trends in this area. For this purpose, the method of analyzing scientific literature was applied. The publications chosen as the basis for the research were mainly based on information from the Google Scholar and ResearchGate databases during the period Q4 2016-Q3 2017. According to the author's knowledge, this is the first such large-scale study involving the countries of the former Eastern Bloc-which includes the following states: Poland, Lithuania, Latvia, Estonia, Ukraine, Hungary, Russia, Slovakia, Czech Republic, Romania, Bulgaria, and Belarus. The results show that the most advanced research in this area is conducted in the Czech Republic, Poland, Slovakia, Estonia, Russia, and Hungary. Belarus Bulgaria and Latvia are on the other end. In the remaining countries, traditional approaches to predicting business insolvency are generally used.

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Section: Global Experience-literature Reviewmentioning

confidence: 99%

Review of Research into Enterprise Bankruptcy Prediction in Selected Central and Eastern European Countries

Prusak

2018

IJFS

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“…Lau (1987) and Ward (1994) develop, respectively, five-state and four-state models of financial distress prior to filing. Recently Laitnen and Laitnen (1998) and Dhumale (1998) use logistic regressions with cash management model and earning retention, respectively, to predict corporate failure. Lennox (1999) discusses the impact of the audit report on bankruptcy prediction.…”

Section: Prior Literature and Incremental Contributionmentioning

confidence: 99%

Predicting Bankruptcy Resolution

Barniv¹,

Agarwal²,

Leach³

2002

Business Fin & Account

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This study examines classification and prediction of the bankruptcy resolution event. Filing of bankruptcy is resolved through one of three alternative resolutions: acquisition, emergence or liquidation. Predicting the final bankruptcy resolution has not been examined in the prior accounting and finance literature. This post-bankruptcy classification and prediction of the final resolution is harder than discriminating between healthy and bankrupt firms because all filing firms are already in financial distress. Motivation for predicting the final resolution is developed and enhanced. A sample of 237 firms filing for bankruptcy is used. Classification and prediction accuracies are determined using a logit model. A ten-variable, three-group resolution logit model, which includes five accounting and five non-accounting variables is developed. The model correctly classifies 62 percent of the firms, significantly better than a random classification. We conclude that non-accounting data add relevant information to financial accounting data for predicting post bankruptcy resolution. Further, public policy implications for investors, researchers, bankruptcy judges, claimants and other stakeholders are discussed. Copyright Blackwell Publishers Ltd 2002.

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“…To reflect this, proxies of borrower quality using Dun and Bradstreet (D&B) scores have been proposed by Cavalluzzo et al (2002). Other proxies might be the variance of returns to equity (Booth and Booth, 2006) or cash management behaviour (Laitinen and Laitinen, 1998). None, however, are appropriate measures for the analysis of the effects of private information on financing choices because such information is publicly available and so will underestimate the effects of any information imperfections.…”

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confidence: 99%

The Role of Collateral in Entrepreneurial Finance

Han

Fraser

Storey

2009

Business Fin & Account

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Previous research has suggested collateral has the role of sorting entrepreneurs either by observed risk or by private information. In order to test these roles, this paper develops a model which incorporates a signalling process (sorting by observed risk) into the design of an incentive-compatible menu of loan contracts which works as a self-selection mechanism (sorting by private information). It then tests this Sorting by Signalling and Self-Selection Model, using the 1998 US Survey of Small Business Finances. It reports for the first time that: high type entrepreneurs are more likely to pledge collateral and pay a lower interest rate; and entrepreneurs who transfer good signals enjoy better contracts than those transferring bad signals. These findings suggest that the Sorting by Signalling and Self-Selection Model sheds more light on entrepreneurial debt finance than either the sorting-by-observed-risk or the sorting-by-private information paradigms on their own. Copyright (c) 2009 The Authors Journal compilation (c) 2009 Blackwell Publishing Ltd.

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Cash Management Behavior and Failure Prediction

Cited by 26 publications

References 20 publications

Review of Research into Enterprise Bankruptcy Prediction in Selected Central and Eastern European Countries

Review of Research into Enterprise Bankruptcy Prediction in Selected Central and Eastern European Countries

Predicting Bankruptcy Resolution

The Role of Collateral in Entrepreneurial Finance

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