Ranking of bankruptcy prediction models under multiple criteria

Jamal Ouenniche, Mohammad M. Mousavi, Bing Xu, Kaoru Tone

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)

Abstract

Prediction of corporate failure is one of the major activities in auditing firms’ risks and uncertainties. In practice, the design of reliable models to predict bankruptcy is crucial in many decision-making processes. In this chapter we address two research questions related to the design of bankruptcy prediction models: namely, do some modelling frameworks perform better than others by design? and to what extent do the choice and/or the design of explanatory variables and their nature affect the performance of modelling frameworks? Elements of answers to these questions are devised through an exhaustive comparative analysis of the most popular bankruptcy-modelling frameworks, including our own models. Our comparative analysis is performed using a multicriteria performance evaluation framework based on data envelopment analysis, namely, an orientation-free super-efficiency slacks-based measure model. The proposed performance evaluation framework delivers a multicriteria ranking of bankruptcy prediction models, which overcomes the methodological issues related to the commonly used monocriterion framework. The performance of bankruptcy prediction models is assessed under a set of commonly used criteria and is tested on a sample that consists of all UK firms listed on the London Stock Exchange during an 18 year period.
Original languageEnglish
Title of host publicationAdvances in DEA Theory and Applications
Subtitle of host publicationWith Extensions to Forecasting Models
EditorsKaoru Tone
PublisherJohn Wiley and Sons Ltd
Pages357-380
ISBN (Electronic)9781118946688
ISBN (Print)9781118945629
DOIs
Publication statusPublished - 6 May 2017

Fingerprint

Ranking
Multiple criteria
Prediction model
Bankruptcy prediction
Modeling
Performance evaluation
Comparative analysis
Bankruptcy
Multi-criteria
Corporate failure
Slacks-based measure
Decision-making process
Auditing
London Stock Exchange
Risk and uncertainty
Data envelopment analysis
Firm risk
Super-efficiency
Prediction

Keywords

  • Performance evaluation
  • Data Envelopment Analysis
  • super-efficiency
  • Bankruptcy prediction;
  • performance criteria and measures

Cite this

Ouenniche, J., Mousavi, M. M., Xu, B., & Tone, K. (2017). Ranking of bankruptcy prediction models under multiple criteria. In K. Tone (Ed.), Advances in DEA Theory and Applications: With Extensions to Forecasting Models (pp. 357-380). John Wiley and Sons Ltd. https://doi.org/10.1002/9781118946688.ch24
Ouenniche, Jamal ; Mousavi, Mohammad M. ; Xu, Bing ; Tone, Kaoru. / Ranking of bankruptcy prediction models under multiple criteria. Advances in DEA Theory and Applications: With Extensions to Forecasting Models. editor / Kaoru Tone. John Wiley and Sons Ltd, 2017. pp. 357-380
@inbook{ea8495cf28d2415fa56f7e59a5fb5687,
title = "Ranking of bankruptcy prediction models under multiple criteria",
abstract = "Prediction of corporate failure is one of the major activities in auditing firms’ risks and uncertainties. In practice, the design of reliable models to predict bankruptcy is crucial in many decision-making processes. In this chapter we address two research questions related to the design of bankruptcy prediction models: namely, do some modelling frameworks perform better than others by design? and to what extent do the choice and/or the design of explanatory variables and their nature affect the performance of modelling frameworks? Elements of answers to these questions are devised through an exhaustive comparative analysis of the most popular bankruptcy-modelling frameworks, including our own models. Our comparative analysis is performed using a multicriteria performance evaluation framework based on data envelopment analysis, namely, an orientation-free super-efficiency slacks-based measure model. The proposed performance evaluation framework delivers a multicriteria ranking of bankruptcy prediction models, which overcomes the methodological issues related to the commonly used monocriterion framework. The performance of bankruptcy prediction models is assessed under a set of commonly used criteria and is tested on a sample that consists of all UK firms listed on the London Stock Exchange during an 18 year period.",
keywords = "Performance evaluation, Data Envelopment Analysis, super-efficiency, Bankruptcy prediction; , performance criteria and measures",
author = "Jamal Ouenniche and Mousavi, {Mohammad M.} and Bing Xu and Kaoru Tone",
year = "2017",
month = "5",
day = "6",
doi = "10.1002/9781118946688.ch24",
language = "English",
isbn = "9781118945629",
pages = "357--380",
editor = "Kaoru Tone",
booktitle = "Advances in DEA Theory and Applications",
publisher = "John Wiley and Sons Ltd",
address = "United Kingdom",

}

Ouenniche, J, Mousavi, MM, Xu, B & Tone, K 2017, Ranking of bankruptcy prediction models under multiple criteria. in K Tone (ed.), Advances in DEA Theory and Applications: With Extensions to Forecasting Models. John Wiley and Sons Ltd, pp. 357-380. https://doi.org/10.1002/9781118946688.ch24

Ranking of bankruptcy prediction models under multiple criteria. / Ouenniche, Jamal; Mousavi, Mohammad M.; Xu, Bing; Tone, Kaoru.

Advances in DEA Theory and Applications: With Extensions to Forecasting Models. ed. / Kaoru Tone. John Wiley and Sons Ltd, 2017. p. 357-380.

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)

TY - CHAP

T1 - Ranking of bankruptcy prediction models under multiple criteria

AU - Ouenniche, Jamal

AU - Mousavi, Mohammad M.

AU - Xu, Bing

AU - Tone, Kaoru

PY - 2017/5/6

Y1 - 2017/5/6

N2 - Prediction of corporate failure is one of the major activities in auditing firms’ risks and uncertainties. In practice, the design of reliable models to predict bankruptcy is crucial in many decision-making processes. In this chapter we address two research questions related to the design of bankruptcy prediction models: namely, do some modelling frameworks perform better than others by design? and to what extent do the choice and/or the design of explanatory variables and their nature affect the performance of modelling frameworks? Elements of answers to these questions are devised through an exhaustive comparative analysis of the most popular bankruptcy-modelling frameworks, including our own models. Our comparative analysis is performed using a multicriteria performance evaluation framework based on data envelopment analysis, namely, an orientation-free super-efficiency slacks-based measure model. The proposed performance evaluation framework delivers a multicriteria ranking of bankruptcy prediction models, which overcomes the methodological issues related to the commonly used monocriterion framework. The performance of bankruptcy prediction models is assessed under a set of commonly used criteria and is tested on a sample that consists of all UK firms listed on the London Stock Exchange during an 18 year period.

AB - Prediction of corporate failure is one of the major activities in auditing firms’ risks and uncertainties. In practice, the design of reliable models to predict bankruptcy is crucial in many decision-making processes. In this chapter we address two research questions related to the design of bankruptcy prediction models: namely, do some modelling frameworks perform better than others by design? and to what extent do the choice and/or the design of explanatory variables and their nature affect the performance of modelling frameworks? Elements of answers to these questions are devised through an exhaustive comparative analysis of the most popular bankruptcy-modelling frameworks, including our own models. Our comparative analysis is performed using a multicriteria performance evaluation framework based on data envelopment analysis, namely, an orientation-free super-efficiency slacks-based measure model. The proposed performance evaluation framework delivers a multicriteria ranking of bankruptcy prediction models, which overcomes the methodological issues related to the commonly used monocriterion framework. The performance of bankruptcy prediction models is assessed under a set of commonly used criteria and is tested on a sample that consists of all UK firms listed on the London Stock Exchange during an 18 year period.

KW - Performance evaluation

KW - Data Envelopment Analysis

KW - super-efficiency

KW - Bankruptcy prediction;

KW - performance criteria and measures

U2 - 10.1002/9781118946688.ch24

DO - 10.1002/9781118946688.ch24

M3 - Chapter (peer-reviewed)

SN - 9781118945629

SP - 357

EP - 380

BT - Advances in DEA Theory and Applications

A2 - Tone, Kaoru

PB - John Wiley and Sons Ltd

ER -

Ouenniche J, Mousavi MM, Xu B, Tone K. Ranking of bankruptcy prediction models under multiple criteria. In Tone K, editor, Advances in DEA Theory and Applications: With Extensions to Forecasting Models. John Wiley and Sons Ltd. 2017. p. 357-380 https://doi.org/10.1002/9781118946688.ch24