Comparing Prediction Methods

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Details

The aim of this study was to compare three methods of bankruptcy prediction, which were Multivariate Discriminant Analysis, Logit Analysis and Artificial Neural Networks. The methods were compared based on their ability to correctly classify and predict bankruptcy on American public listed companies one year prior to the year of failure. The window of interest in this study was the ten year period from 1984 to 1994. Eleven financial ratios, based on a study by Karels & Prakash (1987), were used in the three prediction methods. It was expected, based on previous literature, that the Artificial Neural Network would be the superior method. This study used a more robust testing technique, incorporating different proportions of bankrupt and financially stable companies as well as different sample mixes between the classification and holdout sample. Overall, it was Multivariate Discriminant Analysis which proved to be the best method of prediction in this study.

Autorentext

Ashvin is a chartered accountant based in New Zealand. He has worked in industry in senior roles involved with management and financial accounting. He now works as a commercial manager with Fonterra Co-Operative Group Ltd involved with the business management and strategic organisation of Fonterra's biotech subsidiary.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783639013795
    • Sprache Englisch
    • Größe H6mm x B220mm x T150mm
    • Jahr 2014
    • EAN 9783639013795
    • Format Kartonierter Einband (Kt)
    • ISBN 978-3-639-01379-5
    • Titel Comparing Prediction Methods
    • Autor Ashvin Sood
    • Untertitel The Case of Bankruptcy Predictions
    • Gewicht 174g
    • Herausgeber VDM Verlag Dr. Müller e.K.
    • Anzahl Seiten 104
    • Genre Wirtschaft

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