| Author: | Tsang, Shu-fung |
| Title: | Bankruptcy prediction and credit evaluation for small and medium size enterprises : a neural networks-expert system hybrid approach |
| Degree: | M.Sc. |
| Year: | 1998 |
| Subject: | Hong Kong Polytechnic University -- Dissertations Small business -- China -- Hong Kong Bankruptcy -- Forecasting -- Mathematical models Business failures -- Forecasting -- Mathematical models Credit ratings -- China -- Hong Kong Neural networks (Computer science) -- Mathematical models |
| Department: | Department of Computing |
| Pages: | 153, [50] leaves : ill. ; 30 cm |
| Language: | English |
| Abstract: | Bankruptcy has long been an issue that arouse great concerns. Altman is one of the pioneers in the study of bankruptcy prediction. He has developed the Z-score model and the Zeta model which are widely adopted by financial institutions for evaluation of financial risk. Altman employed multiple discriminant analysis (MDA) in development of the models. Although Altman's models attain quite good prediction accuracy, the models are not targeted for environment as Hong Kong where significant proportion of the companies are small and medium size enterprises (SMEs). After the introduction of neural networks (NN), many researches have been conducted which aimed at using NN to obtain a better solution. The objective of this study are to develop a NN bankruptcy prediction model for SMEs in Hong Kong. The NN model so developed will be compared with the Altman's models and the MDA result. Finally, a front end expert system prototype for the support of loan application for financial institutions will be developed. |
| Rights: | All rights reserved |
| Access: | restricted access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b14391569.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 5.85 MB | Adobe PDF | View/Open |
Copyright Undertaking
As a bona fide Library user, I declare that:
- I will abide by the rules and legal ordinances governing copyright regarding the use of the Database.
- I will use the Database for the purpose of my research or private study only and not for circulation or further reproduction or any other purpose.
- I agree to indemnify and hold the University harmless from and against any loss, damage, cost, liability or expenses arising from copyright infringement or unauthorized usage.
By downloading any item(s) listed above, you acknowledge that you have read and understood the copyright undertaking as stated above, and agree to be bound by all of its terms.
Please use this identifier to cite or link to this item:
https://theses.lib.polyu.edu.hk/handle/200/4883