Neural network application in corporate bankruptcy prediction.
In today turbulent business climate, corporations have more exposure to bankruptcies than ever before. The recession in the early 1990s caused firms to experience severe cash flow problems that resulted in increased delinquency and failure rates.
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sg-ntu-dr.10356-201982024-01-12T10:31:53Z Neural network application in corporate bankruptcy prediction. Xu, Xu Wei. Das, Amit Nanyang Business School DRNTU::Business::Law::Bankruptcy In today turbulent business climate, corporations have more exposure to bankruptcies than ever before. The recession in the early 1990s caused firms to experience severe cash flow problems that resulted in increased delinquency and failure rates. Master of Business 2009-12-14T09:06:36Z 2009-12-14T09:06:36Z 1998 1998 Thesis http://hdl.handle.net/10356/20198 en NANYANG TECHNOLOGICAL UNIVERSITY 117 p. application/pdf |
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Nanyang Technological University |
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Singapore Singapore |
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NTU Library |
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DR-NTU |
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English |
topic |
DRNTU::Business::Law::Bankruptcy |
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DRNTU::Business::Law::Bankruptcy Xu, Xu Wei. Neural network application in corporate bankruptcy prediction. |
description |
In today turbulent business climate, corporations have more exposure to bankruptcies than ever before. The recession in the early 1990s caused firms to experience severe cash flow problems that resulted in increased delinquency and failure rates. |
author2 |
Das, Amit |
author_facet |
Das, Amit Xu, Xu Wei. |
format |
Theses and Dissertations |
author |
Xu, Xu Wei. |
author_sort |
Xu, Xu Wei. |
title |
Neural network application in corporate bankruptcy prediction. |
title_short |
Neural network application in corporate bankruptcy prediction. |
title_full |
Neural network application in corporate bankruptcy prediction. |
title_fullStr |
Neural network application in corporate bankruptcy prediction. |
title_full_unstemmed |
Neural network application in corporate bankruptcy prediction. |
title_sort |
neural network application in corporate bankruptcy prediction. |
publishDate |
2009 |
url |
http://hdl.handle.net/10356/20198 |
_version_ |
1789483207800913920 |