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Title: Predicting corporate financial distress: a time-series CUSUM methodology
Authors: Kahya, Emel
Theodossiou, Panayiotis 
Keywords: Finance;Accounting;Statistical methods;Business
Issue Date: 1999
Publisher: Springer
Source: Review of quantitative finance and accounting, 1999, Volume 13, Issue 4, Pages 323-345
Abstract: The ability to predict corporate financial distress can be strengthened using models that account for serial correlation in the data, incorporate information from more than one period and include stationary explanatory variables. This paper develops a stationary financial distress model for AMEX and NYSE manufacturing and retailing firms based on the statistical methodology of time-series Cumulative Sums (CUSUM). The model has the ability to distinguish between changes in the financial variables of a firm that are the result of serial correlation and changes that are the result of permanent shifts in the mean structure of the variables due to financial distress. Tests performed show that the model is robust over time and outperforms similar models based on the popular statistical methods of Linear Discriminant Analysis and Logit
ISSN: 0924-865X (print)
1573-7179 (online)
DOI: 10.1023/A:1008326706404
Rights: © 1999 Kluwer Academic Publishers
Type: Article
Appears in Collections:Άρθρα/Articles

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