Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/14509
Title: Serial correlation, non-stationarity, and dynamic performance of business failures prediction models
Authors: Theodossiou, Panayiotis 
Kahya, Eyup 
Ouandlous, A.S 
metadata.dc.contributor.other: Θεοδοσίου, Παναγιώτης
Major Field of Science: Social Sciences
Field Category: Economics and Business
Keywords: Accounting research;Predictive validity USA;Modelling;Company failures
Issue Date: 1-Aug-2001
Source: Managerial Finance, 2001, vol. 27 no. 8, pp. 1-15
Volume: 27
Issue: 8
Start page: 1
End page: 15
Journal: Managerial Finance 
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. © Emerald Group Publishing Limited. SciVal Topic Prominence
URI: https://hdl.handle.net/20.500.14279/14509
ISSN: 03074358
DOI: 10.1108/03074350110767303
Rights: © Emerald
Type: Article
Affiliation : Rutgers University-Camden campus 
Savannah State University 
Publication Type: Peer Reviewed
Appears in Collections:Άρθρα/Articles

CORE Recommender
Show full item record

SCOPUSTM   
Citations

1
checked on Nov 9, 2023

Page view(s)

283
Last Week
2
Last month
0
checked on Nov 12, 2024

Google ScholarTM

Check

Altmetric


This item is licensed under a Creative Commons License Creative Commons