Predicting Corporate Failure of UK's Listed Companies

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Details

This study compares two corporate failure prediction models, namely; multiple discriminant analysis (MDA) and logistic regression (Logit) in an attempt to; identify whether or not financial ratios can be used as indicators of failure in the UK, to identify financial ratios that are most important for detecting potential insolvency of UK s public listed companies and also which model is better in predicting corporate failure. The study employed financial information for a group of 50 distressed and 50 non-distressed UK listed companies during the period 2000 2010. The initial sample of 100 companies was divided into a 70% estimation (training) sample and a 30% holdout (test) sample for the following 4 data sets: First-year data set to predict failure, a second-year data set for a 2 year-ahead prediction, third-year data for a 3 year-ahead prediction, as well as cumulative three-year data to predict distress 1 year ahead by letting the ratios vary in time. For each company, a set of 19 financial ratios reflecting the company s profitability, solvency, asset utilisation, growth ability and size, were calculated and then used in the study.

Autorentext

Mohammed Issah is a Chartered Accountant with over 10 years experience in the accounting and finance industry. He is currently the Financial Controller of European Care Group/Vendors Plus, London and Post-graduate student at Oxford University.He holds BSc from Oxford Brookes University and MSc from Unversity of West of England.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783848481842
    • Sprache Englisch
    • Auflage Aufl.
    • Größe H220mm x B150mm x T7mm
    • Jahr 2012
    • EAN 9783848481842
    • Format Kartonierter Einband
    • ISBN 3848481847
    • Veröffentlichung 27.04.2012
    • Titel Predicting Corporate Failure of UK's Listed Companies
    • Autor Mohammed Issah
    • Untertitel Comparing Multiple Discriminant Analysis and Logistic Regression
    • Gewicht 191g
    • Herausgeber LAP LAMBERT Academic Publishing
    • Anzahl Seiten 116
    • Genre Betriebswirtschaft

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