Emerging market corporate bonds — a scoring system

Altman, Edward I.; Hartzell, John W.; Peck, Matthew

doi:10.1007/978-1-4615-6197-2_25

Cited by 119 publications

(133 citation statements)

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“…It is not often possible to build a model specific to an emerging market country based on a sample from that country because of the lack of credit experience there. To deal with this problem, Altman, Hartzell, and Peck (1995) have modified the original Altman Z-Score model to create the emerging market scoring (EMS) model. This article is also included in this volume.…”

Section: Emerging Market Scoring Model and Processmentioning

confidence: 99%

Predicting financial distress of companies: revisiting the Z-Score and ZETA® models

Altman¹

Handbook of Research Methods and Applications in Empirical Finance

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Section: Emerging Market Scoring Model and Processmentioning

confidence: 99%

Predicting financial distress of companies: revisiting the Z-Score and ZETA® models

Altman¹

Handbook of Research Methods and Applications in Empirical Finance

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582

578

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“…This 'quality-junk' investment strategy can be shown in Figure 2, whereby higher yield bonds from companies in quadrants A and B, with relatively strong BREs, are particularly attractive candidates. The Z-score model referenced in Figure 2 is actually our Z"-score specification, developed for emerging market firms (Altman et al 1997) and also advocated for non-manufacturers. This model has been used in several academic studies, as well, (see for example, Altman et al 2014).…”

Section: Bond Investorsmentioning

confidence: 99%

Applications of Distress Prediction Models: What Have We Learned After 50 Years from the Z-Score Models?

Altman

2018

IJFS

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Fifty years ago, I published the initial, classic version of the Z-score bankruptcy prediction models. This multivariate statistical model has remained perhaps the most well-known, and more importantly, most used technique for providing an early warning signal of firm financial distress by academics and practitioners on a global basis. It also has been used by scholars as a benchmark of credit risk measurement in countless empirical studies. Practical applications of the Altman Z-score model have also been numerous and can be divided into two main categories: (1) from an external analytical standpoint, and (2) from an internal to the distressed firm viewpoint. This paper discusses a number of applications from the former's standpoint and in doing so, we hope, also provides a roadmap for extensions beyond those already identified.

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“…Using the above model, Altman's Z Score provided evidence to predict bankruptcy of 94% of the failed companies in his sample (Altman, 1968).One limitation that made the 'Z score' face criticism was that the model is industry specific, as it was formulated for operating manufacturing companies, noted by Grice and Ingram (2001). This was further developed and updated to create the ZScore model (Altman, 1995). This model is applied to predict corporate failures for developing countries firms, emerging market companies and for non-manufacturers.…”

Section: Literature Reviewmentioning

confidence: 99%

Prediction of Financial Distress of Non-Bank Financial Institutions of Bangladesh using Altman’s Z Score Model

Hamid¹,

Akter²,

Rab³

2016

IJBM

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The Non-Bank Financial Institutions (NBFIs) comprise a rapidly growing segment of the financial system in Bangladesh. They are gaining increased popularity in recent times. They play a vital role in the economy. This study attempts to predict the financial health of 15 publicly traded NBFIsof Bangladesh over five years ranging from 2011 to 2015 using Altman's Z Score Model (1965). The results show that most of the sampled NBFIs are in 'Distress' zone, Some of sample NBFIs are nationally and internationally acclaimed for their outstanding performances and contributions to the industrial as well as economic development of the country, but they fail to attain the minimum score. Most of the companies are lying on the bankruptcy level. Hence, the study suggests the stakeholders, including regulatory authorities and researchers to be more watchful of the operations of NBFIs.

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Emerging market corporate bonds — a scoring system

Cited by 119 publications

References 0 publications

Predicting financial distress of companies: revisiting the Z-Score and ZETA® models

Predicting financial distress of companies: revisiting the Z-Score and ZETA® models

Applications of Distress Prediction Models: What Have We Learned After 50 Years from the Z-Score Models?

Prediction of Financial Distress of Non-Bank Financial Institutions of Bangladesh using Altman’s Z Score Model

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