Credit Risk Evaluation for Listed Company Based on Adaboost-LVQ
To protect the investors interest and risk management of credit agency,conducting credit risk evaluation for listed company is very important.A new model based on Adaboost-LVQ neural network was proposed for credit risk evaluation.By defining credit risk as a listed company was special treated,the credit risk evaluation was changed into a pattern recognition problem and AdaBoost-LVQ neural network was introduced.99 samples from the Shanghai and Shenzhen A-share stock market in 2004 to 2010 was used to test the classification effect of the new model.70 in them were used as train set while the rest of them being used as test set.As a result,it was found that the new model had a good classification effect that 86.21% of test samples can be correctly classified.
AdaBoost algorithm Credit Risk Evaluation Learning Vector Quantization
XIAO Lei LI Li XIAO Jia-wen
Institute of Teaching and Reasearch of Ideological and Political Theory,Kunming University,P.R.China School of Mathematics,Yunnan Normal University,P.R.China,650504;School of Economics and Management o School of Economics and Management of UESTC,P.R.China,610054
国际会议
北京
英文
173-177
2012-10-17（万方平台首次上网日期，不代表论文的发表时间）