Using Neutral Network in Predicting Corporate Failure. Using Neutral Network in Predicting Corporate Failure.

Using Neutral Network in Predicting Corporate Failure‪.‬

Journal of Social Sciences 2005, Oct, 1, 4

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Publisher Description

Abstract: This study investigates the predictive power of three neutral network models: Multi-layer neural network, probabilistic neural network, and logistic regression model in predicting corporate failure. Basing on the database provided by The Corporate Scorecard Group (CSG), we combine financial ratios which deem to be significant predictors of corporate bankruptcy in many previous empirical studies to build our predictive models and test it against the holdout sample. On comparison of the results, we find that three models are good at predicting probability of corporate failure. Moreover, probabilistic neural network model outperforms the others. Therefore, neutral networks are useful and probabilistic neutral network is a promising tool for the prediction of corporate failure. Key words: Corporate failure, default risk, credit risk, neutral network

GENRE
Nonfiction
RELEASED
2005
October 1
LANGUAGE
EN
English
LENGTH
12
Pages
PUBLISHER
Science Publications
SELLER
The Gale Group, Inc., a Delaware corporation and an affiliate of Cengage Learning, Inc.
SIZE
174.4
KB
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