Artikel

Industry specific financial distress modeling

This study investigates uncertainty levels of various industries and tries to determine financial ratios having the greatest information content in determining the set of industry characteristics. It then uses these ratios to develop industry specific financial distress models. First, we employ factor analysis to determine the set of ratios that are most informative in specified industries. Second, we use a method based on the concept of entropy to measure the level of uncertainty in industries and also to single out the ratios that best reflect the uncertainty levels in specific industries. Finally, we conduct a logistic regression analysis and derive industry specific financial distress models which can be used to judge the predictive ability of selected financial ratios for each industry. The results show that financial ratios do indeed echo industry characteristics and that information content of specific ratios varies among different industries. Our findings show diverging impact of industry characteristics on companies; and thus the necessity of constructing industry specific financial distress models."

Language
Englisch

Bibliographic citation
Journal: BRQ Business Research Quarterly ; ISSN: 2340-9436 ; Volume: 20 ; Year: 2017 ; Issue: 1 ; Pages: 45-62 ; Barcelona: Elsevier España

Classification
Management
Subject
Uncertainty
Information theory
Financial ratios
Financial distress modeling

Event
Geistige Schöpfung
(who)
Sayari, Naz
Simga-Mugan, Can
Event
Veröffentlichung
(who)
Elsevier España
(where)
Barcelona
(when)
2017

DOI
doi:10.1016/j.brq.2016.03.003
Handle
Last update
10.03.2025, 11:41 AM CET

Data provider

This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.

Object type

  • Artikel

Associated

  • Sayari, Naz
  • Simga-Mugan, Can
  • Elsevier España

Time of origin

  • 2017

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