Developing a multi stage predicting system for corporate credit rating in emerging markets

Jordanian case

Dana Al-Najjar, Basil Al-Najjar

Research output: Contribution to journalArticle

1 Citation (Scopus)

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.
Original languageEnglish
Pages (from-to)475-487
Number of pages13
JournalJournal of Enterprise Information Management
Volume27
Issue number4
DOIs
Publication statusPublished - 2014
Externally publishedYes

Fingerprint

Neural networks
Backpropagation
Profitability
Sales
Credit rating
Emerging markets
Back-propagation neural network
Rating
Design methodology
Jordan
Leverage ratio
Manufacturing firms
Sales performance
Liquidity
High performance
Bankruptcy
Financial information

Cite this

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title = "Developing a multi stage predicting system for corporate credit rating in emerging markets: Jordanian case",
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.",
keywords = "Neural network, Jordan, Credit ratings, Default risk",
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AU - Al-Najjar, Dana

AU - Al-Najjar, Basil

PY - 2014

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N2 - 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.

AB - 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.

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KW - Credit ratings

KW - Default risk

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JO - Journal of Enterprise Information Management

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