Al-Najjar, D. and Al-Najjar, Basil (2014) Developing a multi stage predicting system for corporate credit rating in emerging markets : Jordanian case. Journal of Enterprise Information Management 27 (4), pp. 475-487. ISSN 1741-0398.
Abstract
Purpose The purpose of this paper is to build a neural network system to predict corporate credit rating in Jordanian non-financial firms, using 19 different financial characteristics such as profitability, leverage ratios, liquidity, bankruptcy, and sales performance. Design/methodology/approach The study adopts two neural network techniques namely, Kohonen network and Back Propagation Neural Network (BPNN). Our sample includes the manufacturing firms that have provided the required financial information for the period from 2000 to 2007. Findings BPNN has successfully predicted firms with high performance gaining A rating and the bankrupted firms with D rating for the period from 2005 to 2007. Originality/value This study is the first study to investigate credit rating in Jordan using Neural Network technique.
Metadata
| Item Type: | Article |
|---|---|
| Keyword(s) / Subject(s): | neural network, Jordan, credit ratings, default risk |
| School: | Birkbeck Faculties and Schools > Faculty of Business and Law > Birkbeck Business School |
| Depositing User: | Sarah Hall |
| Date Deposited: | 18 Aug 2014 14:53 |
| Last Modified: | 02 Aug 2023 17:12 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/10428 |
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