{"title":"中国企业财务困境诊断:基于信用评分模型的实证分析","authors":"Q. Liang","doi":"10.15057/4854","DOIUrl":null,"url":null,"abstract":"Corporate performance is undoubtedly of great interests to the owners, managers, creditors and regulatory institutions. This study attempts to extend and improve upon the prior studies in China, particularly in its greater sample size and comparative analysis between MDA and logistic regression analysis in the financial distress prediction. Empirical results show that logistic regression analysis has relatively higher prediction accuracy and lower Type I & II errors. Together with its great flexibilities and e$cient combination of data from both financial statements and capital market prices, logistic regression analysis is considered as the best technique to classify and predict financial distress of listed companies in nowadays China.","PeriodicalId":154016,"journal":{"name":"Hitotsubashi journal of commerce and management","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Corporate Financial Distress Diagnosis in China : Empirical Analysis Using Credit Scoring Models\",\"authors\":\"Q. Liang\",\"doi\":\"10.15057/4854\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Corporate performance is undoubtedly of great interests to the owners, managers, creditors and regulatory institutions. This study attempts to extend and improve upon the prior studies in China, particularly in its greater sample size and comparative analysis between MDA and logistic regression analysis in the financial distress prediction. Empirical results show that logistic regression analysis has relatively higher prediction accuracy and lower Type I & II errors. Together with its great flexibilities and e$cient combination of data from both financial statements and capital market prices, logistic regression analysis is considered as the best technique to classify and predict financial distress of listed companies in nowadays China.\",\"PeriodicalId\":154016,\"journal\":{\"name\":\"Hitotsubashi journal of commerce and management\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Hitotsubashi journal of commerce and management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15057/4854\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hitotsubashi journal of commerce and management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15057/4854","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Corporate Financial Distress Diagnosis in China : Empirical Analysis Using Credit Scoring Models
Corporate performance is undoubtedly of great interests to the owners, managers, creditors and regulatory institutions. This study attempts to extend and improve upon the prior studies in China, particularly in its greater sample size and comparative analysis between MDA and logistic regression analysis in the financial distress prediction. Empirical results show that logistic regression analysis has relatively higher prediction accuracy and lower Type I & II errors. Together with its great flexibilities and e$cient combination of data from both financial statements and capital market prices, logistic regression analysis is considered as the best technique to classify and predict financial distress of listed companies in nowadays China.