1、1本科毕业论文外文翻译外文文献译文标题EVA和市场价值资料来源WWW点VALUEADVISORS点COM/ATTACHMENTS/OBYRNEJACF91点PDF作者斯蒂芬楼奥伯恩价值评估理论主要关注于未来现金流量的现值,但事实上,投资在很大程度上还是依赖于现金流量,收益甚至是账面价值等各方面的增值。像出具“一个公司以高于其内在价值12倍被定价”或“一个公司以账面价值的90被评估”这样的报告,在投资者和分析师眼中是很平常的事。有时,出现这些报表是因为不重视现金流分析,但是更多的是因为他们的报告只分析了交易活动中的现金流或净资产变化,并无考虑到其他信息对企业价值的影响。想把各个因素整合起来是很困
2、难的。因为我们很少知道预测会导致销售,当然就更不会知道买方和卖方会如何发展他们的预测。贴现现金流量在预测一项交易中买方会愿意的支付多少价,或卖方能够接受多少价格不是很有用。即使我们对于公司未来业绩有自己的预测,在我们最后的预测范围内,也还是需要一个报价来决定公司的价值。为了能够更有意义的评估一个公司的价值,我们需要一个与折现现金流相符,能够高度的预测公共的市场价值的价值评估方法来评估公司价值。本文的目标是显示经济增值(EVA)就是税后净营业利润NOPAT减去公司的资本成本。它是用于测量经营绩效和评估企业价值的方法。我最近的研究发现EVA足以解释投资者回报的差异。例如,在一个被广泛引用的题为“总
3、会计收益可以解释大部分的安全返还”的研究报告中,彼得伊斯顿,特雷弗哈里斯,和詹姆斯奥尔森说到,随着时间的增长,盈利对股票收益的解释力渐强。它们显示,例如,虽然当年的收入只能解释当年股票收益变化的5,但五年的公司盈利可以解释这五年同期的股票收益变化的33,十年的公司盈利可以解释这十年的股票收益变化的63。基于这些发现,伊斯顿等人假设总利润和股票收益之间的相关性会随着时间渐长而渐近。方法一然而我的研究表明,十年的EVA在十年股票价值变化上的解释力上,比十年的利润要好,相对的,十年的EVA也比五年的EVA更具解释力。更具体的说,我的研究发现,在五年里,EVA的变化解释了市场价值变化的55,而利润变化
4、只能解释市场价值变化的24。而在十年里,EVA的变化解释了市场价值变化的274,而利润变化只能解释市场价值变化的64。我的调查也显示了EVA的市场价值解释力水平比利润的解释力水平要高。我尝试着揭示,到目前为止,其他研究者在证实EVA比利润有更强大的解释力上失败的原因是因为在很大程度上,他们对公司市场价值的两个重要特点缺乏认识。EVA的回归模型为了测试EVA相对于税后净营业利润(或NOPAT)和自由现金流(FCF)的预测能力,我们们设计了一种的回归模型捕捉公司的市场价值和当前经营业绩之间的关系。最简单的EVA模型是基于刚才所描述的框架,表达了公司的市场价值作为资本的线性函数和EVA之间的关系市值
5、A资本B(EVA/C)4为了使这种模式更加适用于回归分析,我再除以等式两边资本。这使得市场价值的回归模型的构成为市值/资本AB(EVA/C)/资本在测试中的其他变量,例如税后净营业利润(NOPAT)和自由现金流(FCF)的预测能力时,我们用下面的模型市值/资本AB(NOPAT/资本)市值/资本AB(FCF/资本)。如前所述,NOPAT是企业税后净营业利润。自由现金流是等于NOPAT减去资本性支出(包括留存收益)。对EVA,NOPAT,和自由现金流这三个变量中的每一个变量,我的回归分析都尝试着去发现他们和与市场价值/资本比率的强度相关性。我也研究了EVA、NOPAT和资本的变化与市场价值变化的相
6、关性。为什么盈利模式是真的EVA模型为了评估NOPAT模型的解释力,我们需要建立数学回归模型。如果我们的模型是标准的单回归趋势线,则市值/资本AB(NOPAT/资本),如果常数项不为零,那么我们真的有一个可以被称为“资本和税后净营业利润”的模型市值A资本BNOPAT。“资本和税后净营业利润”模式是一个有效的EVA模型(包含资本成本),其等于(1A)/B如果考虑了实际的回归,从我们的样本中可得出的方程为市值/资本08089878NOPAT/资本双方同时乘以资本,可转换为以下方程市场价值0808资本9878NOPAT如果我们在等式的左右两边同时加上(10808)资本0192资本,则公式变为3市场价
7、值10资本9878NOPAT0192资本这个表达式可以重新写成市值10资本9878(NOPAT00194资本),这是一个资本费用支出占成本194的EVA模型。为了有一个“纯粹”的NOPAT模式,我们需要促使回归方程到最初始。当我们做到这一点时,回归方程为市值/资本015557NOPAT/资本,或者市值15557NOPAT结论EVA,不像NOPAT或其他收入的措施(例如净收益或每股收益),它是与系统挂钩的市场价值。它必须比其他经营业绩措施提供更好的市场价值预测。而且,正如我们已经表明,一旦我们了解和适应了EVA与市场价值之间的重要关系,它就能为我们提供一个更好的预测。首先,在评估价值时,投资者利
8、用正EVA评估出的结果要比用负EVA高出很多倍。正EVA是未来EVA改善的标志,因为越来越多公司可以通过维持其目前的回报率来改善EVA。负EVA降低了市场价值,如果业绩一直没有达到我们期望的,那么这一情况将一直延续下去。低整合的负EVA暗示,市场预期将会好转,无论是通过内部改进还是一些外部力量的纠正。第二,资本倍数随着企业规模的增大而下降。从这里的市场隐含的信息是,规模的大小最终带来了它的规模不经济。那些现在没有产生正EVA的大公司,随着他们规模的扩大,在未来是越来越没有可能进行EVA改善。EVA的改进提供了一个功能强大的工具,来了解投资者希望某家公司当前的股票价格是多少。预期EVA的改进(就
9、是在未来,EVA增加就有必要向投资者提供了一个正常公司的股份返还)是重要的,这不仅是为了便于证券分析师评估股票,同时也为便于公司薪酬委员会设定标准的激励补偿计划。4外文文献原文TITLEEVAANDMARKETVALUEMATERIALSOURCEWWW点VALUEADVISORS点COM/ATTACHMENTS/OBYRNEJACF91点PDFAUTHORSTEPHENFOBYRNEVALUATIONTHEORYISFOCUSEDONTHEPRESENTVALUEOFFUTURECASHFLOWS,BUTINVESTMENTPRACTICEFOCUSESLARGELYONMULTIPLESO
10、FCASHFLOW,EARNINGS,ANDEVENBOOKVALUESSTATEMENTSLIKETHISCOMPANYISOVERPRICEDAT12TIMESCASHFLOWORTHISCOMPANYISABARGAINAT90OFBOOKVALUEARECOMMONPLACEAMONGINVESTORSANDANALYSTSSOMETIMESTHESESTATEMENTSARESHORTHANDFORTHERESULTSOFDISCOUNTEDCASHFLOWANALYSIS,BUTOFTENTHEYAREJUSTSTATEMENTSABOUTTHEMULTIPLESOFCASHFLO
11、WSORNETASSETSPAIDINCOMPARABLETRANSACTIONSITISHARDTOMAKEMULTIPLESGOAWAYSINCEWERARELYKNOWTHEFORECASTSTHATLEDTOASALE,MUCHLESSHOWTHEBUYERANDSELLERDEVELOPEDTHEIRFORECASTS,DISCOUNTEDCASHFLOWANALYSISISNOTVERYUSEFULINPREDICTINGWHATTHEBUYERMIGHTBEWILLINGTOPAY,ORTHESELLERACCEPT,INANOTHERTRANSACTIONEVENWHENWEH
12、AVEOUROWNFORECASTOFFUTURECOMPANYPERFORMANCE,WENEEDAVALUATIONMULTIPLETODETERMINETHEVALUEOFTHECOMPANYATTHEENDOFOURFORECASTHORIZONTODEVELOPACCURATEVALUATIONSTHATMAKESENSEINTERMSOFCORPORATEFINANCETHEORY,WENEEDANOPERATINGPERFORMANCEMEASURETHATISCONSISTENTWITHDCFANDVALUATIONMULTIPLESTHATAREHIGHLYPREDICTIV
13、EOFPUBLICMARKETVALUESMYOBJECTIVEINTHISPAPERISTOSHOWTHATECONOMICVALUEADDEDOREVA,WHICHISNETOPERATINGPROFITAFTERTAXNOPATMINUSACHARGEFORALLCAPITALINVESTEDINTHEBUSINESS,PROVIDESTHEOPERATINGPERFORMANCEMEASUREANDTHEVALUATIONMULTIPLESWENEEDTOLINKTHEORYANDPRACTICETHEFINDINGSOFMYRECENTRESEARCHCHALLENGETHESUGG
14、ESTIONOFOTHERRESEARCHERSTHATEARNINGS,WITHOUTREGARDTOTHEAMOUNTOFCAPITALEMPLOYEDTOGENERATETHOSEEARNINGS,ARESUFFICIENTTOEXPLAINDIFFERENCESININVESTORRETURNSFOREXAMPLE,INONEWIDELYCITEDSTUDYENTITLEDAGGREGATEACCOUNTINGEARNINGSCANEXPLAINMOSTOFSECURITYRETURNS,PETEREASTON,TREVORHARRIS,ANDJAMESOHLSONREPORTTHAT
15、ACOMPANYSTOTALEARNINGSOVERAGIVENPERIODEXPLAINANINCREASINGPROPORTIONOFTHEVARIATIONINSHAREHOLDERRETURNASTHEMEASUREMENTPERIODISEXTENDEDTOLONGERANDLONGER5PERIODSTHEYSHOW,OREXAMPLE,THATALTHOUGHTHECURRENTYEARSEARNINGSEXPLAINONLY5OFTHEVARIATIONINTHATYEARSSTOCKRETURNS,FIVEYEARSOFCORPORATEEARNINGSEXPLAIN33OF
16、THEVARIATIONINSTOCKRETURNSOVERTHESAMEFIVEYEARPERIODANDTENYEARSOFCORPORATEEARNINGSEXPLAIN63OFTHEVARIATIONINTENYEARRETURNSBASEDONTHESEFINDINGS,MOREOVER,EASTONETALHYPOTHESIZETHATTHELONGRUNCORRELATIONBETWEENAGGREGATEEARNINGSANDSHAREHOLDERRETURNWILLASYMPTOTICALLYAPPROACHONE1MYOWNRESEARCH,HOWEVER,SHOWSTHA
17、TCHANGESINEVAEXPLAINMOREOFTHEVARIATIONINTENYEARSTOCKRETURNSTHANDOCHANGESINEARNINGS,ANDDRAMATICALLYMOREOFTHEVARIATIONINFIVEYEARRETURNSMORESPECIFICALLY,MYSTUDYFINDSTHATFIVEYEARCHANGESINEVAEXPLAIN55OFFIVEYEARCHANGESINMARKETVALUE,WHEREASFIVEYEAREARNINGSCHANGESEXPLAINONLY24ANDTENYEARCHANGESINEVAACCOUNTED
18、FOR74OFVARIATIONINMARKETVALUE,ASCOMPAREDTOTHE64EXPLAINEDBYTENYEARCHANGESINEARNINGSMYRESEARCHALSOSHOWSTHATTHELEVELOFEVAEXPLAINSMOREOFTHEVARIATIONINMARKETVALUESTHANTHELEVELOFEARNINGSASIATTEMPTTOSHOWINTHISPAPER,HEFAILUREOFOTHERRESEARCHERSTODATETOSUBSTANTIATETHEGREATEREXPLANATORYPOWEROFEVARELATIVETOEARN
19、INGSISDUE,INLARGEPART,TOTHEIRFAILURETORECOGNIZETWOIMPORTANTCHARACTERISTICSOFTHEMARKETSVALUATIONOFCOMPANIESTHEEVAREGRESSIONMODELSTOTESTTHEPREDICTIVEPOWEROFEVARELATIVETOEARNINGSORNOPATANDFREECASHFLOWFCF,WEDEVISEDANUMBEROFREGRESSIONMODELSDESIGNEDTOCAPTURETHERELATIONSHIPBETWEENACOMPANYSMARKETVALUEANDTHE
20、SEMEASURESOFCURRENTOPERATINGPERFORMANCETHESIMPLESTEVAMODEL,BASEDONTHEFRAMEWORKJUSTDESCRIBED,WOULDEXPRESSACOMPANYSMARKETVALUEASALINEARFUNCTIONOFCAPITALANDCAPITALIZEDCURRENTEVAMARKETVALUEACAPITALBEVA/C4TOMAKETHISMODELMOREUSEFULFORREGRESSIONANALYSIS,ITHENDIVIDEDBOTHSIDESOFTHEEQUATIONBYCAPITALINSODOING,
21、OURAIMWASTOGIVEEQUALWEIGHTINGTOEQUALPERCENTAGEERRORSRATHERTHANEQUALDOLLARERRORS5THISMADETHEFORMOFTHEMARKETVALUEREGRESSIONMODELMARKETVALUE/CAPITALABEVA/C/CAPITALINTESTINGTHEPREDICTIVEPOWEROFTHEOTHERVARIABLES,OPERATINGEARNINGSNOPATANDFREECASHFLOWFCF,IUSEDTHEFOLLOWINGMODELSMARKETVALUE/CAPITALABNOPAT/CA
22、PITAL6MARKETVALUE/CAPITALABFCF/CAPITALNOPAT,ASNOTEDEARLIER,ISPREINTERESTBUTAFTERTAXCORPORATEEARNINGSFCFISEQUALTONOPATMINUSNETNEWCORPORATEINVESTMENTINCLUDINGRETAINEDEARNINGSFOREACHOFTHESETHREEVARIABLESEVA,NOPAT,ANDFCFMYREGRESSIONSATTEMPTEDTODISCOVERTHESTRENGTHOFTHECORRELATIONSWITHTHEMARKETVALUE/CAPIT
23、ALRATIOSIALSOEXAMINEDTHECORRELATIONSBETWEENCHANGESINEVA,NOPAT,ANDCAPITALANDCHANGESINMARKETVALUEWHYTHEEARNINGSMODELISREALLYANEVAMODELTOASSESSTHEEXPLANATORYPOWEROFANOPATMODEL,ONENEEDSTOBECAREFULABOUTTHEMATHEMATICALFORMOFTHEREGRESSIONMODELIFOURMODELISTHESTANDARDSINGLEREGRESSIONTRENDLINE,MARKETVALUE/CAP
24、ITALABNOPAT/CAPITAL,ANDTHECONSTANTTERMAISNOTZERO,THENWEREALLYHAVEWHATMIGHTBECALLEDACAPITALANDNOPATMODELMARKETVALUEACAPITALBNOPATANDACAPITALANDNOPATMODELISEFFECTIVELYANEVAMODELWITHACOSTOFCAPITALEQUALTO1A/BCONSIDER,FOREXAMPLE,THEACTUALREGRESSIONEQUATIONPRODUCEDBYOURSAMPLEMARKETVALUE/CAPITAL08089878NOP
25、AT/CAPITALMULTIPLYINGBOTHSIDESBYCAPITALTRANSFORMSTHISEQUATIONINTOTHEFOLLOWINGMARKETVALUE0808CAPITAL9878NOPATIFWEADDANDSUBTRACT10808CAPITAL0192CAPITALFROMTHERIGHTSIDEOFTHEEQUATION,THEEQUATIONBECOMESMARKETVALUE10CAPITAL9878NOPAT0192CAPITALTHISEXPRESSIONCANBEREWRITTENASMARKETVALUE10CAPITAL9878NOPAT0019
26、4CAPITAL,WHICHISANEVAMODELWITHA194CAPITALCHARGEONENDINGCAPITALTOHAVEAPURENOPATMODEL,WENEEDTOFORCETHEREGRESSIONEQUATIONTHROUGHTHEORIGINWHENWEDOTHIS,THEREGRESSIONEQUATIONISMARKETVALUE/CAPITAL015557NOPAT/CAPITAL,ORMARKETVALUE15557NOPATTHISREGRESSIONHASASTANDARDERROROF102EXPRESSEDINTERMSOFMARKETVALUE/CA
27、PITALANDEXPLAINSONLY17OFTHEVARIATIONINMARKET/CAPITALCONCLUSION7EVA,UNLIKENOPATOROTHEREARNINGSMEASURESLIKENETINCOMEOREARNINGSPERSHARE,ISSYSTEMATICALLYLINKEDTOMARKETVALUEITSHOULDPROVIDEABETTERPREDICTOROFMARKETVALUETHANOTHERMEASURESOFOPERATINGPERFORMANCEAND,ASWEHAVESHOWN,ITDOESPROVIDEABETTERPREDICTORON
28、CEWEUNDERSTANDANDADJUSTFORTWOCRITICALRELATIONSHIPSBETWEENEVAANDMARKETVALUEFIRST,INVESTORSCAPITALIZEPOSITIVEEVAATMUCHHIGHERMULTIPLESTHANNEGATIVEEVAPOSITIVEEVAISASIGNOFFUTUREEVAIMPROVEMENTBECAUSEAGROWINGCOMPANYCANCREATEEVAIMPROVEMENTSIMPLYBYMAINTAININGITSCURRENTRATEOFRETURNNEGATIVEEVAREDUCESMARKETVALU
29、E,BUTBYSIGNIFICANTLYLESSTHANIFSUCHSUBSTANDARDPERFORMANCEWEREEXPECTEDTOCONTINUEFOREVERLOWERMULTIPLESONNEGATIVEEVAIMPLYTHATTHEMARKETEXPECTSATURNAROUND,WHETHERENGINEEREDINTERNALLYORTHROUGHSOMEEXTERNALCORRECTIVEFORCESECOND,CAPITALMULTIPLESDECLINEWITHSIZETHEIMPLICITMESSAGEFROMTHEMARKETHEREISTHATSIZEEVENT
30、UALLYBRINGSWITHITDISECONOMIESOFSCALEBIGCOMPANIESTHATDONTGENERATEPOSITIVEEVANOWARELESSANDLESSLIKELYASTHEYGETBIGGERTOGENERATEANYEVAIMPROVEMENTINTHEFUTUREEVAIMPROVEMENTPROVIDESAPOWERFULTOOLFORUNDERSTANDINGTHEINVESTOREXPECTATIONSTHATAREBUILTINTOACOMPANYSCURRENTSTOCKPRICEEXPECTEDEVAIMPROVEMENTTHATIS,THEINCREASEINFUTUREEVATHATISNECESSARYTOPROVIDEINVESTORSWITHANORMALRETURNONTHECOMPANYSSHARESISIMPORTANTNOTONLYFORSECURITIESANALYSTSINEVALUATINGSTOCKS,BUTALSOFORCORPORATECOMPENSATIONCOMMITTEESINSETTINGPERFORMANCESTANDARDSFORMANAGEMENTINCENTIVECOMPENSATIONPLANS