The role of survival analysis in financial distress prediction

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Abstract

Accurate business failure prediction models would be extremely valuable to many industry sectors, particularly in financial investment and lending. The potential value of such models has been recently emphasised by the extremely costly failure of high profile businesses in both Australia and overseas, such as HIH (Australia) and Enron (USA). Consequently, there has been a significant increase in interest in business failure prediction from both industry and academia. Statistical business failure prediction models attempt to predict the failure or success of a business. Discriminant and logit analyses have been the most popular approaches, but there are also a large number of alternative techniques available. In this paper, a comparatively new technique known as survival analysis has been used for business failure prediction. In addition, hybrid models combining survival analysis with either discriminant analysis or logit analysis were trialled, but their empirical performance was poor. Overall, the results suggest that survival analysis techniques provide more information that can be used to further the understanding of the business failure process.
Original languageEnglish
Pages (from-to)13-34
Number of pages22
JournalInternational Research Journal of Finance and Economics
Volume16
Issue number16
Publication statusPublished - 1 Jun 2008

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Survival analysis
Prediction
Business failures
Financial distress
Failure prediction
Prediction model
Industry
Enron
Logit analysis
Hybrid model
Discriminant
Lending
Logit
Discriminant analysis

Cite this

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title = "The role of survival analysis in financial distress prediction",
abstract = "Accurate business failure prediction models would be extremely valuable to many industry sectors, particularly in financial investment and lending. The potential value of such models has been recently emphasised by the extremely costly failure of high profile businesses in both Australia and overseas, such as HIH (Australia) and Enron (USA). Consequently, there has been a significant increase in interest in business failure prediction from both industry and academia. Statistical business failure prediction models attempt to predict the failure or success of a business. Discriminant and logit analyses have been the most popular approaches, but there are also a large number of alternative techniques available. In this paper, a comparatively new technique known as survival analysis has been used for business failure prediction. In addition, hybrid models combining survival analysis with either discriminant analysis or logit analysis were trialled, but their empirical performance was poor. Overall, the results suggest that survival analysis techniques provide more information that can be used to further the understanding of the business failure process.",
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The role of survival analysis in financial distress prediction. / Gepp, Adrian; Kumar, Kuldeep.

In: International Research Journal of Finance and Economics, Vol. 16, No. 16, 01.06.2008, p. 13-34.

Research output: Contribution to journalArticleResearchpeer-review

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