A Market-Based Framework for Bankruptcy Prediction

Reisz, Alexander S.; Perlich, Claudia

doi:10.2139/ssrn.531342

Cited by 28 publications

(38 citation statements)

References 61 publications

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“…Reisz and Perlich () developed a model incorporating barrier options for bankruptcy prediction and compared its discriminatory power with other market‐based models and Altman's Z‐ Score and Z ”‐Score. The dataset covered nearly 6000 industrial firms over the 1988–2002 period.…”

Section: Survey Of Literature Related To the Altman Z‐score Modelmentioning

confidence: 99%

“…Chava and Jarrow (2004) employed an extended bankruptcy database of U.S.A. listed firms to test the superiority of Shumway's model (2001) over Altman's (1968) and Zmijewski's (1984) models. The authors re-estimated the models over the Reisz and Perlich (2007) developed a model incorporating barrier options for bankruptcy prediction and compared its discriminatory power with other market-based models and Altman's Z-Score and Z"-Score. The dataset covered nearly 6000 industrial firms over the 1988-2002 period.…”

Section: Survey Of Literature Related To the Altman Z-score Modelmentioning

confidence: 99%

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Financial Distress Prediction in an International Context: A Review and Empirical Analysis of Altman's Z‐Score Model

Altman¹,

Iwanicz-Drozdowska

Laitinen

et al. 2016

Financ Manag Account

583

377

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This paper assesses the classification performance of the Z-Score model in predicting bankruptcy and other types of firm distress, with the goal of examining the model's usefulness for all parties, especially banks that operate internationally and need to assess the failure risk of firms. We analyze the performance of the Z-Score model for firms from 31 European and three non-European countries using different modifications of the original model. This study is the first to offer such a comprehensive international analysis. Except for the United States and China, the firms in the sample are primarily private, and include non-financial companies across all industrial sectors. We use the original Z 00 -Score model developed by Altman, Corporate Financial Distress: A Complete Guide to Predicting, Avoiding, and Dealing with Bankruptcy (1983) for private and public manufacturing and non-manufacturing firms. While there is some evidence that Z-Score models of bankruptcy prediction have been outperformed by competing market-based or hazard models, in other studies, Z-Score models perform very well. WithThe authors are grateful to the Editor, Richard Levich, and to the anonymous referees for many helpful comments and suggestions. We also wish to thank participants at the 2014 Inter- out a comprehensive international comparison, however, the results of competing models are difficult to generalize. This study offers evidence that the general Z-Score model works reasonably well for most countries (the prediction accuracy is approximately 0.75) and classification accuracy can be improved further (above 0.90) by using country-specific estimation that incorporates additional variables.

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Section: Survey Of Literature Related To the Altman Z‐score Modelmentioning

confidence: 99%

Section: Survey Of Literature Related To the Altman Z-score Modelmentioning

confidence: 99%

Financial Distress Prediction in an International Context: A Review and Empirical Analysis of Altman's Z‐Score Model

Altman¹,

Iwanicz-Drozdowska

Laitinen

et al. 2016

Financ Manag Account

583

377

View full text Add to dashboard Cite

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“…2. See Brockman and Turtle (2003), Reisz and Perlich (2004), and Merton (1973) for a more detailed explanation of barrier options applied to equities and for the derivation of the relevant valuation formulas.…”

Section: Introductionmentioning

confidence: 99%

Investigating the Performance of Alternative Default-Risk Models: Option-Based Versus Accounting-Based Approaches

Gharghori

Chan

Faff

2006

Australian Journal of Management

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In this paper we evaluate the performance of three alternate default-risk models, seeking to find that measure which performs best, using a comprehensive sample drawn from the Australian equities market. The first two models are option-based models and are derived from Merton's (1974) insight that equity can be viewed as a call option on a firm's assets. In the first model, equity is modelled as a standard call option. In the second model, equity is modelled as a path-dependent barrier option. The third model is created using accounting ratios and is similar to Altman's (1968) Z-Score. To assess which of the models is superior, we consider variations of each model and then rely on prediction-oriented tests that focus on whether a firm subsequently defaults. Our results show that the option-based models clearly outperform their accounting ratio counterparts. Furthermore, our analysis suggests that the option-based models are very successful at ranking firms by default probability. It is noteworthy that the performances of the option-based models are difficult to distinguish from each other. The financial assistance provided by an ARC Linkage grant (LP0453913) and the helpful comments of an anonymous referee are gratefully acknowledged.-209 -(1974) that equity can be viewed as a call option on the firm's assets leads to a measure of default-risk that is derived from theory and is economically justifiable.In spite of the theoretical justification for the Merton model, Moody's-KMV, who are one of the leading providers of credit-risk measurement in the US, find that the Normal distribution underlying the Merton model understates the actual DP of firms. Using their own propriety dataset, collected over 20 years, Moody's-KMV observe that defaulted firms have a leptokurtic distribution. 1 Based on this finding, they have created their own propriety distribution, the EDF, to calculate DPs for firms. Researchers have latched onto this claim and argue that it is inconsistent to derive a formula for calculating DPs based on an underlying Normal distribution and then depart from this distribution in the final calculation of the DPs.Brockman and Turtle (2003) argue that path-dependent options rather than path-independent options, such as a standard call option, should be used to model equities and infer DPs for firms. The Merton model is path-independent because default can only occur if the asset value falls below liabilities at maturity. The asset value prior to maturity, or the 'path' followed by the asset value, does not affect the probability of default. Conversely, path-dependent options do take into consideration the asset value prior to maturity. One can argue that the path followed by the market value of assets prior to maturity is an important determinant of a firm's DP and hence that a barrier option is a more appropriate choice than a standard option for modelling equities. The relevant barrier option for equities is a down-and-out call (DOC) option on the firm's assets. With a DOC, the value of equity is zero if t...

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“…10 Real world probabilities can be determined using the methodology outlined in Arnold and Crack (2004). 11 Brockman and Turtle (2003) considered path dependence in a continuous-time context; see also Reisz and Perlich (2004), and Episcopos (2008). 12 Alternatively, junior debt can be modelled as the difference between two call options, as in Freydefont (2001).…”

Section: Intermediate Path-dependent Cash Flows 11mentioning

confidence: 99%

“…1111Brockman and Turtle (2003) considered path dependence in a continuous‐time context; see also Reisz and Perlich (2004), and Episcopos (2008).…”

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confidence: 99%

An overview of project finance binomial loan valuation

Winsen

2009

Rev Financ Econ

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Setting project financing parameters, such as the loan to valuation ratio, loan interest rate, repayment schedules, and fees, requires detailed modelling of the resulting credit risk in a non‐recourse setting. Structured credit risk models, based on the early work of Merton, have been developed in continuous time which can assist with project financing structuring. These models require a level of mathematical sophistication that may not always be available to those undertaking project financing analysis. This note provides an overview of a discrete time binomial approach to structural credit risk modelling, which enables project financing analysts a more accessible tool to evaluate project loan structures.

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A Market-Based Framework for Bankruptcy Prediction

Cited by 28 publications

References 61 publications

Financial Distress Prediction in an International Context: A Review and Empirical Analysis of Altman's Z‐Score Model

Financial Distress Prediction in an International Context: A Review and Empirical Analysis of Altman's Z‐Score Model

Investigating the Performance of Alternative Default-Risk Models: Option-Based Versus Accounting-Based Approaches

An overview of project finance binomial loan valuation

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