Serial correlation, non-stationarity, and dynamic performance of business failures prediction models

Emel Kahya, Arav S. Ouandlous, Panayiotis Theodossiou

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

This article examines the implications of serial correlation of the financial variables on the dynamic performance and robustness of the business failure prediction models based on the linear discriminant analysis, Logit, and Cumulative Sums (CUSUM)methods. Statistical tests show that most of the financial variables included in business failure prediction models exhibit strong positive serial correlation over time and in many cases a unit root. As a result, the predictive ability of these types of models deteriorates over time.

Original languageEnglish (US)
Pages (from-to)1-15
Number of pages15
JournalManagerial Finance
Volume27
Issue number8
DOIs
StatePublished - 2001

All Science Journal Classification (ASJC) codes

  • Business, Management and Accounting (miscellaneous)
  • Finance

Keywords

  • Accounting research
  • Company failures
  • Modelling
  • Predictive validity
  • USA

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