LEAST SQUARE SUPPORT VECTOR MACHINE BASED ON GENETIC ALGORITHM FOR CREDIT RISK EVALUATION

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POUYANFAR A.; FALLAHPOUR S.; AZIZI M.

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Paper Information

Journal: FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT) Year:2014 | Volume:4 | Issue:17 Page(s): 133-158

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Information Journal Paper

Title

LEAST SQUARE SUPPORT VECTOR MACHINE BASED ON GENETIC ALGORITHM FOR CREDIT RISK EVALUATION

Author(s)

POUYANFAR A. | FALLAHPOUR S. | AZIZI M. | Issue Writer Certificate

Keywords

CREDIT RISKQ1

LEAST SQUARE SUPPORT VECTOR MACHINEQ2

GENETIC ALGORITHMQ2

FEATURE SELECTIONQ2

Abstract

One of the most important problems that banks and financial institutions always deal with is CREDIT RISK or the uncertainty in counterparty’s ability to meet its financial obligations. The significant amount of bank’s outstanding claims in all over the world shows the importance of this issue. Hence recently so much effort has been taken to develop an efficient model for the credit admission decisions. This study tries to apply a LEAST SQUARE SUPPORT VECTOR MACHINE based on GENETIC ALGORITHM (Ga-LSSVM) to evaluate CREDIT RISK of obligators. A German dataset in UCI database is used as an experimental data to demonstrate the effectiveness and accuracy of Ga-LSSVM classifier. The results of the proposed method is compared with statistical methods including logistic and probit models and also with results of other studies which had been used the same dataset. The experimental results show that the proposed LSSVM classifier based on Ga for parameter and FEATURE SELECTION can produce promising classification results in CREDIT RISK evaluation, relative to other classifiers listed in this study.

Cites

USE OF A HYBRID APPROACH BASED ON ARTIFICIAL BEE COLONY AND NEURAL NETWORK FOR CREDIT RISK ASSESSMENT

References

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APA: Copy

POUYANFAR, A., FALLAHPOUR, S., & AZIZI, M.. (2014). LEAST SQUARE SUPPORT VECTOR MACHINE BASED ON GENETIC ALGORITHM FOR CREDIT RISK EVALUATION. FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT), 4(17), 133-158. SID. https://sid.ir/paper/197768/en

Vancouver: Copy

POUYANFAR A., FALLAHPOUR S., AZIZI M.. LEAST SQUARE SUPPORT VECTOR MACHINE BASED ON GENETIC ALGORITHM FOR CREDIT RISK EVALUATION. FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT)[Internet]. 2014;4(17):133-158. Available from: https://sid.ir/paper/197768/en

IEEE: Copy

A. POUYANFAR, S. FALLAHPOUR, and M. AZIZI, “LEAST SQUARE SUPPORT VECTOR MACHINE BASED ON GENETIC ALGORITHM FOR CREDIT RISK EVALUATION,” FINANCIAL ENGINEERING AND SECURITIES MANAGEMENT (PORTFOLIO MANAGEMENT), vol. 4, no. 17, pp. 133–158, 2014, [Online]. Available: https://sid.ir/paper/197768/en

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