整合财务比率与公司治理指标建构信用评等预测模型

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1、“育達學院學報,，第18期，民或98年3月，第45・74頁YuDaAcademicJournalNo.18.March2009,pp.45-74.IntegratingAccountingInformationandCorporateGovernanceIndicesforBuildingUpaCreditRatingForecastingModel-ComparisonofMultivariateDiscriminantAnalysisandGenetic-Algorithm-BasedNeuralNetworkChai-ChiaoLeeAbstractCreditratingsystems

2、haveexistedforalongtimeinmostfinancialmarketsandplayedamajorroleincorporatecapitalraising,providinginvestmentinformationforbothindividualinvestorsandinstitutionalinvestors,andcreditgrantinginbanks.Howtopredictenterprisecreditratingandeffectsofincorporatingcorporategovernanceindicesnowarethefocus.The

3、methodologiesusedareconventionalMDAmodelandartificialintelligencebasedtechniques-GAANNforbuildingupacreditratingforecastingmodeltotestthatwhichonehasbetterprecisenessandintegrity,andprovidebasisforenterprisestopredictcreditrating.Ourempiricalresultsrevealthataftercorporategovernanceindicesbeincorpor

4、atedintothemodelwhichisconstructedbymultivariatediscriminateanalysis,hitratioachieves89.52%muchbetterthanwhatwegetsimplybyusingfinancialratiowithoutincorporatingcorporategovernanceindicesandthatwouldboosttheprecisenessandintegrityweconsidered・Furthermore,byusingGeneticAlgorithm,weextractvariableshav

5、ingheavyimpacttocreditrattingresults,andfindthatmorethanhalfofvariablesbelongLecture,DepartmentofAccounting,YuDaCollegeofBusiness.tocorporategovernanceindicators,andthatmeanscorporategovernancereallyimportantinformationsourceofbusinessevaluation.Finally,wecomparetheforecastingabilityofMultivariateDi

6、scriminateAnalysismodelwiththatofArtificialNeuralNetworkModel.CreditratingmodelconstructedbyusingArtificialNeuralNetworkModelhaswholevalidity(90%hitratio),internalvalidity(89.29%hitratio)andexternalvalidity(88.57%hitratio),andallofthosethreeindictorsarebetterthanthosefromDiscriminantAnalysismodel.It

7、meansthatArtificialNeuralNetworkmodelhasbettergeneralitythatcanprovideexternalstakeholderstoapplydifferentbusinessestoforecastriskdegree.KeyWords:creditratingsmultivariatediscriminateanalysis(MDA)，cor