应用财务比率预警财务危机外文翻译

外文翻译原文Title:FinancialRatiosandtheProbabilisticPredictionofBankruptcyMaterialSource:Author:JamesOhlson1IntroductionThispaperpresentssomeempiricalresultsofastudypredictingcorporatefailureasevidencedbytheeventofbankruptcy.Therehavebeenafairnumberofpreviousstudiesin this field ofresearch;the more notable publishedcontributionsareBeaver(1966;1968a;1968b),Altman(1968;1973)andsoon.TwounpublishedpapersbyWhiteandTurnbuli(1975a;1975b)andapaperbySantomeroandVinso(1977)areofparticularinterestastheyappeartobethefirststudieswhichlogicallyandsystematicallydevelopprobabilisticestimatesoffailure.Thepresentstudyissimilartothelatterstudies,inthatthemethodologyisoneofmaximumlikelihoodestimationoftheso-calledconditionallogitmodel.Thedatasetusedinthisstudyisfromtheseventies(1970-76).Iknowofonlythreecorporatefailureresearchstudieswhichhaveexamineddatafromthisperiod.OneisalimitedstudybyAltmanandMcGough(1974])inwhichonlyfailedfirmsweredrawnfromtheperiod1970-73aonlyonetypeofclassificationerror(misclassificationoffailedfirms)wasanalyzed.Moyer(1977)consideredtheperiod1965-75,butthesampleofbankruptfirmswasunusuallysmall(twenty-sevenfirms).Thethirdstudy,byAltman,Haldeman,andNarayanan(1977),which"updates"theoriginalAltman(1968)study,basicallyconsidersdatafromtheperiod1969to1975.Theirsamplewasbasedonfifty-threefailedfirmsandaboutthesamenumberofnonfailedfirms.Incontrast,mystudyreliesonobservationsfrom105bankruptfirmsand2,058nonbankruptfirms.Althoughtheotherthreestudiesdifferfromthepresentonesofarasmethodologyandobjectivesareconcerned,itis,nevertheless,interestingandusefultocomparetheirretswiththosepresentedinthispaper.AnotherdistinguishingfeatureofthepresentstudywhichIshouldstressisthat,contrarytoalmostallpreviousstudies,thedataforfailedfirmswerenotderivedfromMoody'sManual.Thedatawereobtainedinsteadfrom10-Kfinancialstatementsasreportedatthetime.Thisprocedurehasoneimportantadvantage:thereportsindicateatwhatpointintimetheywerereleasedtothepublic,andonecanthereforecheckwhetherthecompanyenteredbankruptcypriortoorafterthedateofrelease.Previousstudieshavenotexplicitlyconsideredthistimingissue.SomeCommentsRegardingMethodologyandDataCollection Thefundamentalestimationproblemcanbe reduced simply to thefollowingstatement:giventhatafirmbelongstosomeprespecifiedpopulation,what istheprobabilitythatthefirmfailswithinsomeprespecifiedtimeperiod?Noassumptionshavetobemaderegardingpriorprobabilitiesofbankruptcyand/orthedistributionofpredictors.Thesearethemadvantages.Thestatisticalsignificanceofthedifferentpredictorsareobtainedfromasymptotic(largesample)theory.Clearly,muchcanbegainedbyimprovingthedatabase.Theevaluationofthepredictiveclassificationpowerofamodelshouldbemorerealistic,and,moreimportanthere,thesameshouldapplyforstandardtestsofstatisticalsignificance.Thisisnottosuggestthatitisimportanttohave"superaccurate"dataforpurposesofdeveloping(asopposedtoevaluating)adiscriminatorydevice.Itmightwellbethatthepredictivequalityofanymodelisreasonablyrobustacrossavarietyofdatagatheringandestimatingprocedures.CollectionofFinancialStatementDataThenextphasewasoneofactuallycollectingfinancialdataforthebankruptfirms.Theobjectivewastoobtainthreeyearsofdatapriortothedateofbankruptcy.Eachreporthadtoincludethebalancesheet,incomestatement,fundsstatement,andtheaccountants'report.Incasethelastavailableaccountants'reportexplicitlystatedthatthecompany had filedfor bankruptcy,then a fourthreportwascollected.AllreportswereretrievedfromtheStanfordUniversityBusinessSchoolLibrary,whichhasanextensivemicrofilmfileof10-Kreports.Therelevantpartsofthe10Kreportswerephotocopiedandsubsequentlycoded.Somefirmshadtobedeletedfromthesamplebecausenoreportwhatsoeverwasavailable,butthesewerefew.Otherfirms,againveryfew,weredeletedbecausetheywerecorporateshellsandhadnosales.Ontheotherhand,nofirmwasdeletedbecauseofitsyoung(exchange)age,andsomefirmshaonlyonesetofreports.Thefinalsamplewasmadeupof105bankruptfirms.Inotedthatwhileeighteenofthe105firm(17percent)hadaccountants'reportswhichdisclosedthatthecompanyhadenteredbankruptcy,thefiscalyear-endwaspriortothedateofbankruptcy.Thesereportsweredeletedandreportsfromthepreviousfiscalyearweresubstituted.AProbabilisticModelofBankruptcyLetX,denoteavectorofpredictorsfortheithobservation;βbeavectorofunknownparameters,andletP(X,p)denotetheprobabilityofbankruptcyforanygivenX,andβ.Pissomeprobabilityfunction,0≤P≤1.Thelogarithmofthelikelihoodofanyspecificoutcomes,asreflectedbythebinarysamplespaceofbankruptcyversusnonbankruptcy,L(β)=∑log(X,β)+∑log(1-P(X,β))isthengivenby:whereS1,isthe(index)setofbankruptfirmsandSnonbankruptfirms.ForanyspecifiedfunctionP,themaximumlikelihoodestimatesofβ1，β2…,areobtainedbysolving:maxl(β)Intheabsenceofapositivetheoryofbankruptcy,thereisnoeasysolutiontotheproblemofselectinganappropriateclassoffunctionsP.Asapracticalmatter,allonecandoistochooseonthebasisofcomputationalandinterpretativesimplicity.RatiosandBasicResultsForpurposesofthepresentreport,noattemptwasmadetodevelopanenyworexotic"ratios.Thecriterionforchoosingamongdifferentpredictorswassimplicity.(1).SIZE=log(totalassets/GNPprice-levelindex).Theindexassumesabasevalueof101968.Totalassetsareasreportedindollars.Theindexyearisasoftheyyearofthebalancesheetdate.Theprocedureassuresareal-timeimplementationofthemodel.Thelogtransformhasanimportantimplication.Supposetwofirms,AandB,haveabalancesheetdateinthesameyear,thenthesignofPA—PBisindependentoftheprice-levelindex.(Thiswillnotfollowunlessthelogtransformisapplied.)Thelatteris,ofcourse,adesirableproperty.(2).TLTA=Totalliabilitiesdividedbytotalassets.(3).CLCA=Currentliabilitiesdividedbycurrentassets.(4).OENEG=Oneiftotalliabilitiesexceedstotalassets,zerootherwise.(5).NITA=Netincomedividedbytotalassets.(6).FUTL=Fundsprovidedbyoperationsdividedbytotalliabilities. Afteraseriesofresearch,this paperanalyzesthechoiceanddividingpointtwocategories,therelationshipbetweentheafrwithdividingpointnumericalincreases,thebankruptompanydiscriminantaccuracylower,withthebankruptcyofthecompanydiscriminantrateishighandhigher.By50%asdividingpointinbankruptcy,modeltothebankruptcompanyyearbeforethediscriminant99.37%,butforcorrectness criterionaccuracy is bankrupt company, if by 6% 32.4%asdividingpoint(initssamples,bankruptcompanyproportionof105/(105+2058)=4.85%,accordingtotheinformationprovided6%weretheauthorsprovidethemostcloseto4.85%asegmentationpoint),Thecorrespondingtothebankruptcompanydiscriminant88.2%oftheaccuracyandcorrectnessofthecorrespondingdiscriminantinsolventcorporationis80%.6ConclusionsTherearetwoconclusionswhichshouldberestated.First,thepredictivepowerofanymodeldependsuponwhentheinformation(financialreport)isassumedtobeavailable.Somepreviousstudieshavenotbeencarefulinthisregard.Second,thepredictivepowersoflineartransformsofavratiosseemtoberobustacross(largesample)estimationprocedures.Hence,morethananythingelse,significantimprovementprobablyrequiresadditionalpredictors. 译文应用财务比率预警财务危机资料来源: 作者：奥尔逊1引言本文通过对财务危机进行防范，但最终仍导致破产的公司实例，从实证上得到一些分析结果。在这个领域，之前已经有相当一部分研究，更值得注意并已经发表文章有Beaver（1966;1968a;1986b）,Altman（1968;1973）等等。White和Turnbull（1975a;1975b）和Santomero和Vinso（1977）写的两篇未发表的论文，让我们看起来他们似乎是第一次系统而有逻辑性地发展了预测财务危机，本文类似于后面这篇文章的研究，采用的这种方法是利用logistic模型，最大可能地预测财务危机。该数据集应用于该研究是在70年代（1970-1976），在这个时期，我知道的只有三个公司进行过数据检查。一个是由Altman和McGough（1974）创作的有限制性的研究，文中只有失败的公司是来自1970-1973，而且只有一种分类错误（失败公司的错误分类）进行了分析。Moyer（1977）认为在1965-1975，破产公司的例子不同寻常地很小（27个公司）。三分之一的研究，是由Altman,Haldeman,andNarayanan（1977）,更新了Altman（1968）最初的研究，基本上的数据都是从1969-1975来的。他们的样本引用了53家破产公司和相同数量的绩效优异的公司。而对比之下，本文的研究是通过观察105家破产公司和2058家没有破产的公司。尽管就方法和客观性而言，其他的三项研究不同于目前的这一项，确实如此，但是，在本文中，很有意义并且很有实际效用地用现在的数据比较了他们的结果。本文研究的另一个显著的特点我应该强调的是，与以前几乎所有的研究相反的是失败公司的数据并不是来自穆迪手册，这些数据是间接地从10-K财务报表上得到的。这个过程有一个很重要的优点：这些报告及时地显示了他们向公众开放的重点，因此可以检查这个公司是在公开财务报表之前还是之后产生破产。之前的研究并没有确切地考虑时间上的问题。一些关于方法和数据收集的评论基本的估计问题可以被简化到以下状态：由于公司属于一些指定的人员，那么公司在特定的时期发生财务失败的可能性是多少呢？之前没有假设关于公司破产的可能性或者发生财务失败的概率分布。这些都是主要优势。不同预警系统的数据意义在于数据都是从渐进的理论（大样本）中得到的。显然，提高数据库，加大数据库的容量能收获很多。对于预测模型的评估应该更加现实一点，而且，更重要的是，在这里，同样地应该应用到具有统计学意义的标准测试中。这并不是说，为了发展一项有识别能力的装置而要以拥有“超级精确”的数据为宗旨（相对于评估）。他可能意味着，财务预警模型通过一系列的数据收集和预测过程会很合理地变得更加强大。财务数据的收集下一阶段的其中一个任务是为破产公司收集财务数据。我们的目标是获得公司破产前3年的数据。每一份报告都必须包括资产负债表、利润表、现金流量表和会计人员的报告。如果在会计师最后的有效的报告中明确声明该公司已申请破产，那么第四份报告应该被收集。AU报告是来自斯坦福大学商学院图书馆里，里面有一个容量很大、涵盖面很广的缩微胶片10-K文件的报告。相关部分被复印并且随后编码。一些公司因为没有报告可以使用而从这个样本中被删除，但是这些也很少。少数的一些其他的公司因为共同销售但是没有销售而被删除。另外一方面，没有公司由于还在起步阶段或者只有一系列的报告而被删除。最后的样本是由破产的105家公司组成的。我注意到105家中的18家公司（17%）的会计人员透露公司已经进入破产，是在破产日期前的一个财政年度。这些报告被删除了，而且被以前年度的报告替代了。4一种财务危机预警模型让X，指示一个预测i的向量，