case study: calculating capm beta in excel
DESCRIPTION
In this paper, we will look at the capital asset pricing model (CAPM), a simple but widely used factor model in finance. CAPM’s main strength – and its primary weakness – is that it assumes one single source of risk (i.e. market risk) and then buckets everything else as idiosyncratic (i.e. non-systematic). This paper will pave the way to more advanced factor modeling techniques in coming issues.We will begin by discussing the underlying assumptions, define systematic and idiosyncratic risk, and outline their influence on the covariance among assets. Next, using a simple regression model, we will attempt to compute the CAPM sensitivity factor (Beta) for two different tech stocks: Microsoft and IBM. Our coal in applying CAPM to these tech stocks is to compute each asset’s sensitivity (i.e. Beta) to non-diversifiable market risk. To do that, we will use a simple linear regression model, then a normal process to validate the model’s assumptions and ensure its stability over the data sample.for more information, or to download the spreadsheet file(s), http://bitly.com/136RRPjTRANSCRIPT
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CalculatingCAPMBetaTutorial 1 SpiderFinancialCorp,2013
CalculatingCAPMBetaInthispaper,wewilllookatthecapitalassetpricingmodel(CAPM),asimplebutwidelyusedfactormodelinfinance.CAPMsmainstrengthanditsprimaryweaknessisthatitassumesonesinglesourceofrisk(i.e.marketrisk)andthenbucketseverythingelseasidiosyncratic(i.e.nonsystematic).Thispaperwillpavethewaytomoreadvancedfactormodelingtechniquesincomingissues.Wewillbeginbydiscussingtheunderlyingassumptions,definesystematicandidiosyncraticrisk,andoutlinetheirinfluenceonthecovarianceamongassets.Next,usingasimpleregressionmodel,wewillattempttocomputetheCAPMsensitivityfactor(Beta)fortwodifferenttechstocks:MicrosoftandIBM.OurcoalinapplyingCAPMtothesetechstocksistocomputeeachassetssensitivity(i.e.Beta)tonondiversifiablemarketrisk.Todothat,wewilluseasimplelinearregressionmodel,thenanormalprocesstovalidatethemodelsassumptionsandensureitsstabilityoverthedatasample.Forsampledata,weusedthemonthlyreturnsbetweenJuly2001andMay2013(140observations).Forthemarketrisk,weselectedmonthlyreturnsoftheRussell3000Index,andforriskfree,weoptedforthe4weektreasurybills(TBILL)returns.
BackgroundInfinance,thecapitalassetpricingmodel(CAPM)isusedtodeterminetheappropriaterequiredrateofreturnofanasset(oraportfolio).TheCAPMtakesintoaccounttheassetssensitivitytothenondiversifiablerisk(akasystematicormarketrisk).
[ ] ( [ ] )
[ ][ ]
T T T Ti f i M f
T Ti f
i T TM f
E R R E R R
E R RE R R
Where
[ ]TiE R istheexpectedreturnofanassetIoveraholdingperiodT. TfR istheriskfreereturnovertheperiodT. i isthesensitivityoftheassetsexcessreturnovertheexpectedexcessmarketreturn. [ ]TME R istheexpectedmarketreturnoveraholdingperiodT. [ ]T TM fE R R isthemarketpremium(expectedexcessmarketreturn). [ ]T Ti fE R R isreferredtoastheriskpremium(expectedexcessassetsreturn).Inotherwords,
theassetsriskpremiumequalsthemarketpremiummultipliedbyitsbeta.
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CalculatingCAPMBetaTutorial 2 SpiderFinancialCorp,2013
Theequationabovedescribesasimplelinearregressionmodel(withzerointercept),betweentheassetsexcessreturnsandtheexcessmarketreturn.
2
( )
~ . . ~ (0, )
T T T Ti f i M f i
i
R R R R
i i d N
2 isoftenreferredtoastheidiosyncraticrisk(i.e.riskthatisspecifictotheassetitself,ratherthanthe
overallmarket).
Finally,the i istheslope(sensitivity)andcanbeexpressedasfollows: ( , )
( )
T Ti M
i TM
Cov R RVar R
Furthermore,fortwoassets,thecovariancecanbecomputedusingCAPMasfollows:
2
2
( , ) [ ] [( )( )]
( , ) [( ( ) )( ( ) )]
( , ) [ ( ) ( ) ( ) ]
( , ) [( ) ] ( )
i j i j i f j f
i j i M f i j M f j
i j i j M f i M f j j M f i i j
i j i j M f i j M
Cov R R E R R E R R R RCov R R E R R R R
Cov R R E R R R R R R
Cov R R E R R Var R
BasedontheCAPM,thevariance(orrisk)ofeachassetconsistsoftwocomponents:systematicandidiosyncraticrisk.
2 2( ) ( )T Ti i MVar R Var R Whydowecare?BasedontheCAPMtheory,wecancomputenotonlytheexpectedreturns,butalsoconstructacovariancematrixofthedifferentassets.Notethatthevarianceofeachassetconsistsoftwocomponents.Case1:MicrosoftMicrosoftCorporationdevelops,licenses,andsupportssoftwareproductsandservices,aswellasdesigningandsellinghardwareworldwide.Microsoftisapubliclytradedcompany,listedonNASDAQwithamarketcapitalof290B.LetsplotthemonthlyexcessreturnsofMicrosoftandRussell3000(marketproxy):
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CalculatingCAPMBetaTutorial 3 SpiderFinancialCorp,2013
Next,weplotthescatterplotforthetwodatasetsanddrawalineartrendlinetooutlinethecorrelationbetweenthetwo:
UsingthelinearregressionwizardinNumXL,designatethemonthlyexcessreturnsofMicrosoftasthedependentvariable(Y)andthoseofRussell3000astheindependentvariable(i.e.X).
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CalculatingCAPMBetaTutorial 4 SpiderFinancialCorp,2013
FromtheOptionstabintheregressiondialogbox,settheintercept/constantvaluetozero.
Note:Youmayleavetheintercept/constantfloating(i.e.unset)andtheregressionwillfinditinsignificant.Tryit.Whenwearefinished,clickOK.Theregressionwizardwillgenerateseveraloutputtables.
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CalculatingCAPMBetaTutorial 5 SpiderFinancialCorp,2013
Theregressionmodel(i.e.CAPM)isstatisticallysignificant(ANOVAtable)andcapturesabout40%ofMSFTmonthlyexcessreturnvariance.TheBeta(i.e.Russell3000coefficient)hasanaveragevalueof0.98withanerrorof0.10.Thisisgoodsofar,soletsexaminethestandardizedresidualsoftheregression(rightmosttable).Theresidualsexhibitapositiveskewandfattails,andthusitfailsthenormalitytest.Togetabetterideaabouttheresidualsdistribution,wecreatetheQQplotwithaGaussiantheoreticaldistribution:
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CalculatingCAPMBetaTutorial 6 SpiderFinancialCorp,2013
TheQQPlotshowsasmalldeviationfromnormalityatpositivevalues(i.e.skew)andafatlefttail(negative).BeforewestartusingtheCAPMandourregressionbetatodeterminetheappropriaterequiredreturnofMicrosoft,weshouldaskourselvesakeyfewquestionsfirst:Q:Istheregressionmodelstable?DoestheBetasvaluesignificantlydifferthroughoutthesampledata?A:Toanswerthisquestion,letsdividethesampledataintotwosubsets:dataset1includesallobservationspriorto2008(~70observations)anddataset2coversobservationsstartingfromJanuary2008toMay2013(~70observations).UsingtheRegressionStabilityTestWizardinNumXL,weconductthisimperativetest.Similartowhatwedidwiththeregressionwizard,theRussellsexcessreturnsaretheindependent(X)variable,andtheMSFTreturnsarethedependentvariable(Y).
IntheOptionstab,settheintercept/constanttozero.
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CalculatingCAPMBetaTutorial 7 SpiderFinancialCorp,2013
Now,ClickOK.TheWizardgeneratesthestatisticalstabilitytestoutputtable.
TheBetavalueisstablethroughoutoursampledataset(2001to2013).Letscomputeandplotthebetavaluethroughoutthedataset.Theshadedareaisour95%confidenceinterval.
Q:Aretheregressionsstandardizedresidualsserially(akaauto)correlated?A:Thewhitenoisetestanswersthisspecificquestion,andisavailableintheNumXLstatisticalteststab.
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CalculatingCAPMBetaTutorial 8 SpiderFinancialCorp,2013
IntheOptionstab,setthemaximumlagorderto12(1year).ClickOK.
Theresidualstimeseriesexhibitsnosignificantserialcorrelation.Sofar,wefoundthefollowing:
ThemonthlyreturnsofMicrosoftstockhaveanaveragesensitivityof0.98withtheoverallmarket.
Theresidual(akaidiosyncratic)risk(i.e. )isaround5.54%.Q:Dowehaveobservation(s)thatsignificantlyaffecttheregressionmorethanothers(i.e.Influentialdata)?
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CalculatingCAPMBetaTutorial 9 SpiderFinancialCorp,2013
Toanswerthequestionabove,wecomputetheCooksdistanceforeachobservationinthesampledata.Furthermore,weusetheheuristicthresholdof 4
Ntoidentifythoseinfluentialpoints.Nisthe
numberofnonmissingvaluesinthedataset.
Tohandleinfluentialandatapoint,wedecidedtoremoveitbysettingtheMSFTreturnsto#N/A,thusremovingtheobservationfromanyanalysis.Weremoveoneobservation(theonewiththehighestCooksdistance)atatime,thenrecalculatetheCooksdistancefortheremainingdatapointsusingthereduceddataset.Notethatthethresholdslightlyincreasesaswedropobservations.Wecontinuewiththeprocessuntilnoapparentinfluentialdataisinsight.
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CalculatingCAPMBetaTutorial 10 SpiderFinancialCorp,2013
Notethatthe 4Nthresholdisaheuristic,soweaccepteddatapointswhoseCooksdistanceisslightly
higherthanthethreshold.Recalculatingtheregression(SHIFT+F9),weobservethenewBetavalue(1.21)andregressionerror(5.07%).
PlottingtheCAPMBetavaluethroughoutthesampledata,weobservethattheBetaslightlychangesovertimeandistrendinglowerovertime.OnemayconcludethatMSFTssensitivitytomarketriskisgoingdown,duetoitsmarketcaporthenatureofinvestmentthatthecompanyitselfisundertaking.
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CalculatingCAPMBetaTutorial 11 SpiderFinancialCorp,2013
Case2:IBMInternationalBusinessMachines(IBM)Corporationprovidesinformationtechnology(IT)productsandservicesworldwide.Thecompanyoperatesinfivesegments:GlobalTechnologyServices,GlobalBusinessServices,Software,SystemsandTechnology,andGlobalFinancing.IBMispubliclytraded,listedonNYSEwithamarketcapof233B.LetsplottheIBMmonthlyexcessreturnsalongwiththeRussell3000(marketproxy)excessreturns.
Next,weplotthescatterplotforthetwodatasetsanddrawalineartrendlinetooutlinethecorrelationbetweenthetwo.
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CalculatingCAPMBetaTutorial 12 SpiderFinancialCorp,2013
Thetwoseriesdemonstrateastrongcorrelationbetweenthem.Again,usingtheRegressionWizard,designateIBMexcessreturnsasthedependentvariableandtheRussell3000astheindependent,settingtheintercept/constanttozero.
TheoutputtablesshowsimilarresultstowhatwesawwiththeMicrosoftcase.LetsexaminetheresidualsdistributioncloserusingtheQQPlot.
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CalculatingCAPMBetaTutorial 13 SpiderFinancialCorp,2013
TheQQplotexhibitspositiveskew,withaheavyfattailontheleft(negative)side.BeforewestartusingtheCAPMandourregressionbetatodeterminetheappropriaterequiredreturnofMicrosoft,weoughttoaskourselvesakeyfewquestions:Q:Istheregressionmodelstable?DoestheBetasvaluesignificantlydifferthroughoutthesampledata?Again,welldividethedatasetinto2separatesubsets:dataset1includesallobservationspriorto2008,anddataset2includesallobservationsstartingfromJanuary2008todate.UsingtheNumXLregressionstabilitytest,wespecifytheindependent(X)anddependentvariable(Y)valuesforeachdataset,settheintercepttozero,andclickOK.
Thetestfailed!Wehaveastructuralbreakinthedataset.ThiscanbeinterpretedastheBetavaluechangedsignificantly.
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CalculatingCAPMBetaTutorial 14 SpiderFinancialCorp,2013
Whatcanwedonow?LetsfirstplottheBetavalueovertimeinanattempttoidentifythepoint(s)wherestructuralchangecommenced.
TheIBMstockhasundergoneaBetastartingin2008.Thiscanbeduetointernalcompanypolicychange:typeofinvestment,particularmarketexposure,etc.TheimportantfacthereisthattheidentityoftheIBMstockmorphed(withrespecttoCAPM).Insum,weneedtotossawaytheobservationspriorto2008andusethelaterobservations(i.e.2008toMay2013)toestimatetheCAPMBeta.
Examiningtheregressionoutputs(usingpost2008observations),theBetahasameanvalueof0.66.Furthermore,theresidualdiagnosistestsallpassed.Additionally,thenonsystematicrisk(i.e.regressionstandarderror)isaround4%.Inshort,theIBMstockmorphedfrombeingahighbetavalueabove1toavaluelowerthanone.
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CalculatingCAPMBetaTutorial 15 SpiderFinancialCorp,2013
Q:Aretheregressionsstandardizedresidualsserially(akaauto)correlated?A:Thewhitenoisetestanswersthisspecificquestion,andisavailableinNumXLsstatisticalteststab.
Theresidualstimeseriesexhibitsnosignificantserialcorrelation.Q:Dowehaveobservation(s)thatsignificantlyaffecttheregressionmorethanothers(i.e.influentialdata)?Toanswerthequestionabove,wecomputetheCooksdistanceforeachobservationinthesampledatapost2008.
SimilartowhatwedidintheMicrosoftcase,weremovedinfluentialdatabysettingtheMSFTreturnsto#N/A,thusremovingtheobservationfromanyanalysis.Weremoveoneobservation(onewiththehighestcooksdistance)atatime,thenrecalculatetheCooksdistancefortheremainingdatapoints
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CalculatingCAPMBetaTutorial 16 SpiderFinancialCorp,2013
usingthereduceddataset.Notethatthresholdslightlyincreasesaswedropobservations.Wecontinuewiththeprocess,untilnoapparentinfluentialdataisinsight.
Recalculatingtheregressionmodel:
Thenonsystematicerrordroppedto3.42%(from4.27%earlier),andalltheresidualsdiagnosistestsarepassed.
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CalculatingCAPMBetaTutorial 17 SpiderFinancialCorp,2013
PlottingtheCAPMbetavaluethroughoutthesampledata,weobservethattheBetaslightlychangesovertimeandistrendingupwardovertime.OnemayconcludethatMSFTssensitivitytomarketriskisgoingup,duetothenatureofnewinvestmentthatthecompanyisundertaking.
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CalculatingCAPMBetaTutorial 18 SpiderFinancialCorp,2013
ConclusionInthispaper,wedemonstratedtheprocessforcomputingtheCAPMBetafortwotechstock:IBMandMSFT.Inbothcases,weproposedasimplelinearregressionmodelforthestocksmonthlyexcessreturnsversusthemonthlyexcessreturnsoftheRussell3000Index(marketproxy).TheregressionslopeistheempiricalCAPMBetaandtheregressionstandarderrorisviewedasthestocksnonsystematic(idiosyncratic)error.Afterward,wecarriedonaplainregressionanalysisprocess:ANOVA,coefficientsvaluetest,residualsdiagnosis,regressionstabilitytest,andinfluentialdataanalysis.ThecomputedCAPMBetasignificantlyimprovedaswecarriedourthoroughanalysistotheregressionresults.AlltoolsyouneedtocarryonthisexercisearepartofNumXL1.60Pro.TheCAPMisarelativelysimpleonefactormodel.Inlaterissues,welltacklemultifactors(e.g.FamaFrenchthree(3)factormodel(FFM),etc.),whichmayaddsomenumericalcomplexitywhilethebasicstepsandintuitionremainthesame.