Multi Criteria Credit Rating Model for Small Enterprise Using a Nonparametric Method
A small enterprise’s credit rating is employed to measure its probability of defaulting on a debt, but, for small enterprises, financial data are insufficient or even unreliable. Thus, building a multi criteria credit rating model based on the qualitative and quantitative criteria is of importance t...
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Online Access: | https://www.mdpi.com/2071-1050/9/10/1834 |
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doaj-ac2ca51063a945ab925ed2e76c8f79602020-11-25T00:22:25ZengMDPI AGSustainability2071-10502017-10-01910183410.3390/su9101834su9101834Multi Criteria Credit Rating Model for Small Enterprise Using a Nonparametric MethodGuotai Chi0Zhipeng Zhang1Faculty of Management and Economics, Dalian University of Technology, Dalian 116024, ChinaFaculty of Management and Economics, Dalian University of Technology, Dalian 116024, ChinaA small enterprise’s credit rating is employed to measure its probability of defaulting on a debt, but, for small enterprises, financial data are insufficient or even unreliable. Thus, building a multi criteria credit rating model based on the qualitative and quantitative criteria is of importance to finance small enterprises’ activities. Till now, there has not been a multicriteria credit risk model based on the rank sum test and entropy weighting method. In this paper, we try to fill this gap by offering three innovative contributions. First, the rank sum test shows significant differences in the average ranks associated with index data for the default and entire sample, ensuring that an index makes an effective differentiation between the default and non-default sample. Second, the rating equation’s capacity is tested to identify the potential defaults by verifying a clear difference between the average ranks of samples with default ratings (i.e., not index values) and the entire sample. Third, in our nonparametric test, the rank sum test is used with rank correlation analysis made to screen for indices, thereby avoiding the assumption of normality associated with more common credit rating methods.https://www.mdpi.com/2071-1050/9/10/1834financesmall enterprise creditcredit ratingnonparametric test |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Guotai Chi Zhipeng Zhang |
spellingShingle |
Guotai Chi Zhipeng Zhang Multi Criteria Credit Rating Model for Small Enterprise Using a Nonparametric Method Sustainability finance small enterprise credit credit rating nonparametric test |
author_facet |
Guotai Chi Zhipeng Zhang |
author_sort |
Guotai Chi |
title |
Multi Criteria Credit Rating Model for Small Enterprise Using a Nonparametric Method |
title_short |
Multi Criteria Credit Rating Model for Small Enterprise Using a Nonparametric Method |
title_full |
Multi Criteria Credit Rating Model for Small Enterprise Using a Nonparametric Method |
title_fullStr |
Multi Criteria Credit Rating Model for Small Enterprise Using a Nonparametric Method |
title_full_unstemmed |
Multi Criteria Credit Rating Model for Small Enterprise Using a Nonparametric Method |
title_sort |
multi criteria credit rating model for small enterprise using a nonparametric method |
publisher |
MDPI AG |
series |
Sustainability |
issn |
2071-1050 |
publishDate |
2017-10-01 |
description |
A small enterprise’s credit rating is employed to measure its probability of defaulting on a debt, but, for small enterprises, financial data are insufficient or even unreliable. Thus, building a multi criteria credit rating model based on the qualitative and quantitative criteria is of importance to finance small enterprises’ activities. Till now, there has not been a multicriteria credit risk model based on the rank sum test and entropy weighting method. In this paper, we try to fill this gap by offering three innovative contributions. First, the rank sum test shows significant differences in the average ranks associated with index data for the default and entire sample, ensuring that an index makes an effective differentiation between the default and non-default sample. Second, the rating equation’s capacity is tested to identify the potential defaults by verifying a clear difference between the average ranks of samples with default ratings (i.e., not index values) and the entire sample. Third, in our nonparametric test, the rank sum test is used with rank correlation analysis made to screen for indices, thereby avoiding the assumption of normality associated with more common credit rating methods. |
topic |
finance small enterprise credit credit rating nonparametric test |
url |
https://www.mdpi.com/2071-1050/9/10/1834 |
work_keys_str_mv |
AT guotaichi multicriteriacreditratingmodelforsmallenterpriseusinganonparametricmethod AT zhipengzhang multicriteriacreditratingmodelforsmallenterpriseusinganonparametricmethod |
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1725359929382928384 |