第七章效率市场(证券投资学北大)

第七章效率市场主要内容效率市场的定义效率市场的实证结果证券市场中的几种反常景象行为金融MauriceKendall,Theanalysisofeconomictimeseries,PartI:Prices,JournaloftheRoyalstatisticalsociety96,1953.Hecouldidentifynopredictablepatternsinstockprices.1.Whyarenotstockpricespredictable?例子：一种模型预测股票价钱三天后将从20元/股涨至23元/股Theforecastofafuturepriceincreasewillleadinsteadtoanimmediatepriceincreasethestockpricewillimmediatelyreflectthegoodnewsimplicitinthemodel’sforecast.例子：2001年10月21日晚，证监会宣布暂停国有股减持例子：2002年4月5日宣布，从5月1日起买卖佣金运用0.3%上限向下浮动制。例子：中国人民银行决议，从2004年10月29日起上调金融机构存贷款基准利率并放宽人民币贷款利率浮动区间和允许人民币存款利率下浮。金融机构一年期存款基准利率上调0.27个百分点，由现行的1.98%提高到2.25%，一年期贷款基准利率上调0.27个百分点，由现行的5.31%提高到5.58%。由于存在聪明的投资者的缘由，任何可以用来对股票价钱作预测的信息曾经反映在股票的价钱中。任何新信息，假设是可以预测的，那么曾经反映在价钱中；假设是不可预测的，那么导致的股票价钱变动也是不可预测的，即随机的信息导致随机的股票价钱变化。2.股票价钱的随机游走(randomwalk)股票价钱的变动服从随机游走的方式。随机游走的方式并不是阐明市场是非理性的，而恰恰阐明这是投资者真相寻求相关信息，以使得本人在别的投资者获得这种信息之前买或者卖股票而获得利润的结果。反之，假设股票价钱不是随机变动而是可以预测的，那么阐明一切的相关信息并没有完全反映在价钱中，这阐明市场是非有效的。股票价钱反映了一切可得信息称为有效性市场假设。有效资本市场指的是现时市场价钱可以反映可得信息的资本市场，在这个市场中，不存在利用可得信息获得超额利润的时机。资本市场的有效性这一概念对于金融投资者而言具有非常重要的意义。由于市场的有效性消除了许多可以提高收益的战略。MarketefficiencymeansPricesarecorrectTheyfullyreflectallavailableinformationPeopleuseallavailableinformationinformingexpectationsaboutfuturecashflows.Thediscountrateisrightfortherisknessofthecashflows.PricesreacttonewinformationquicklyandtotherightextentThereisnofreelunchTheonlywayyoucangethigherreturnsisbytakingonmoreriskThereisnoinformationouttherethatcanbeusedtoconstructstrategiesthatearnreturnshigherthanrequiredfortheirrisk.Whenwesay‘pricesarecorrect’,weareimplicitlystatementwhat‘correct’is(i.e.,weareassuminganassetpricingmodel)3.有效资本市场的描画例子：F-stopCameraCorporationisattemptingtodevelopacamerathatwilldoublethespeedoftheauto--focusingsystemnowavailable.在特定的价钱下，持有股票的缘由著名的光学专家加盟股价能否上涨股价上涨的缘由股价上涨的时间一个市场对于一个信息集来说称为有效的，假设不存在利用该信息获得超额利润的时机。有效和非有效市场中价钱对新信息的反响股票价钱0宣布前〔-〕或者后〔+〕的天数过激反响和回归延迟反响有效市场对新信息的反响三种有效市场(efficientcapitalmarket)不同的信息集对证券价钱产生影响的速度不一样。为了处置不同的反响速度，把信息集分成不同的类别。最常用的一种分类方法：过去价钱的信息，可得的公共信息，一切信息。针对这三种信息集，有三种方式的有效市场的定义弱有效市场(theweakform)半强有效市场(thesemistrongform)强有效市场(strongform)弱有效市场定义：一个资本市场称为弱有效的或者满足弱有效方式，假设证券价钱充分反响了包含在历史价钱中的信息。弱方式有效通常表示成下面的数学方式+Expectedreturn+Randomerror这里随机误差项的均值为0，且不同时间的随机误差项是不相关的。弱方式有效性是最弱类型的有效性。股票价钱的历史数据是可以免费得到的，假设这些数据里包含有用的数据，那么一切的投资者都会利用它，导致价风格整，最后，这些数据失去价值。‘technical’analysisusingpastpricepatternswillnotproduceprofits.假设一个市场是弱有效的，思索一个买卖战略假设某股票的价钱延续涨三天，就买进该股票；假设股票的价钱延续降三天，就卖出股票。问题：这个战略能否赚钱。FairlyconvincedthatmarketsareweakformefficientBut,newevidence(i.e.,momentum)haschallengedthis.半强方式有效市场定义：一个市场是半强方式有效的，假设价钱反响了一切公共可得的信息。这些信息包括：历史价钱数据、与公司消费有关的根本数据、管理的质量、资产负债表、专利情况、收益预测、会计处置‘fundamental’analysis(e.g.sortingthroughincomestatements)willnotproduceprofits.Ex.Formingportfoliosonaccountingratios,balancesheet,orincomestatementinformationwillnotgenerateabnormalprofits.NoevidenceofabnormalreturnsafterapublicannouncementProfessionalmoneymanagersdonotoutperformthemarketMarketseemtobesemi-strongefficientBut,B/MandE/Pstrategiesstillchallengethis.(mayberisk,maybenot)强方式有效市场定义：一个市场是强有效的，假设价钱反响了一切的信息，不论是公共的还是私有的。InsidertradingwillnotproduceprofitsEx.Knowingamergerisgoingtotakeplacebeforeitisannouncedpublicly.Althoughillegal,thereisevidencethatpricesmovebeforeannouncements,suggestinginsidertradestakeplaceInsidertradingappearsprofitable,indicatingmarketsarenotstrongformefficient.But,theseprofitsareshortlived,suggestingthemarketmaybeclosetoefficient.强方式有效性半强方式有效性弱方式有效性阐明三种有效性的例子：总是在股价上涨后卖出股票，能赚到钱投资者在一家公司宣布添加收益后买该公司股票，能赚到钱知道采矿公司能否开采到了金子的内部音讯后买该公司股票，能赚到钱4.Howcanwetellifmarketsareinefficient?Lookforstock-pickingstrategiesbasedonsomepastinformationwhichhaveearnedhighreturnswithlittlerisk.Unfortunately,wecanneverbesureofinefficiency.Itisalwayspossiblethatwearenotmeasuringriskproperly,i.e.,wedonotknowwhattherightdiscountrateisThisisthe‘Jointhypothesisproblem’5.Whywouldweexpectmarketstobeefficient?theforcesofarbitragesmartinvestorsexploitthemispricinginsecuritiesuntilitdisappearsToshowthatmarketsareineffcient,needtoshowthatpeoplemakeerrorsinsettingpricesthatarbitragefailstoeliminatetheseerrors一些例子GrossmanandStiglitz的结果不同市场的有效性不同：中国和美国的股市小股票和大股票的有效性不同RandomWalksandEfficientMarketsitisoftenthoughtthatefficientmarketspricesmoverandomlythisisnotnecessarilytrueStrictlyspeaking,weshouldcharacterizestockpriceasfollowingasubmartingale,meainngthattheexpectedchangeinthepricecanbepositive,presumablyascompensationforthetimevalueofthemoneyandsystematicrisk.Moreover,theexpectedreturnmaychangeovertimeasriskfactorschange.returnsaremean-revertingifthediscountrateforanassetdoesnotchangeovertime,thenitistruethatefficientmarketsrandomwalke.g.overshorttimeframes,returnsshouldlookrandom6.Evidenceformarketefficiencystockpricesappeartomoverandomlynewinformationappearstobequicklyincorporatedintopricese.g.announcementofatakeoverdoan‘eventstudy’tolookatthestockpricereactiontothenewsaverageovermanycompaniesProfessionalmoneymanagersdonotclearlybeatthemarketonaverage.7.EvidenceagainstmarketefficiencydidthevalueoftheU.S.economyreallydrop20%inOctober1987?thevolumeoftradingonstockexchangesistoohightobeconsistentwithrationalinvestorsthevolatilityofthemarketistoohigh(Shiller,1982).why?whyaretheresomanymutualfunds?thereareinvestmentstrategieswhichappeartohaveearnedhigheraveragereturnsthanisconsistentwiththeirriskThesearesocalled‘marketanomalies’suggeststhatnewinformationisnotalwaysimmediatelyincorporatedintopricesThisevidencereferstoweak/semi-strongversionsofmarketefficiencyHowaboutstrong-formefficiency?canyoumakemoneyusinginside,non-publicinformation?YES!stockpricesoftenmoveinadvanceofimportantcompanyannouncementsfromrecordsofinsidertrades,wefindthattheymakemoneyonaverageBUT:it'sillegalforcompanyinsiders(orpeopletippedbythem)totransactbasedonmaterialnon-publicinformationHowaboutinstitutionalinvestors?Wementionedmoneymanagersdonotexhibitabnormalperformanceonaverage,butmaybesomelocaladvantage.8.ThemarketanomaliesAnomaliescanbethoughtofasinvestmentstrategieswhichseemtoearnhighreturnswithoutbeingveryriskyThestrategiesarenormallybasedonsomefirmcharacteristic:sizeofthefirmitsprice-earningsratioRecipe:formaportfoliobasedonobservablecharacteristics,andmeasureitsreturnsovertimedoesthestrategygivehighreturnsonaverage?Whylookataveragereturns?IFYES:thestrategymayberiskyandthehighaveragereturnsarejustfaircompensationforthatriskhowdowemeasurerisk?(seebelow)ifriskdoesnotexplainthehighreturns,isitevidenceofmarketinefficiency?itmaybespurious,theresultofdata-miningifyoutrymanystrategies,someofthemwilldogreatinhistoricaldatadoesn'ttellyouanythingaboutfutureperformancepoorriskmeasurementfrictionstotradingandexploitingtheanomaly(bid-askspread,transactionscosts,liquidity,taxes,etc.)Measuringtheriskofastrategystandarddeviationdownsideriskdoesthestrategysometimesperformverypoorly?betalooksatstrategy'spayoffrelativetothemarket'spayoffahighcovarianceisunattractive(risky)lookatcovarianceofstrategy'spayoffwithvariableslikeGNPgrowth(factormodels)astrategywhichdoeswellingoodstatesoftheworldandpoorlyinbadstatesisriskyNote:evenifnoneoftheaboveturnupameasureofrisk,efficientmarketsenthusiastswillsay:theriskispresent,butjusthasn'tsurfacedwithinthesampleanalyzedOR:we'rejustnotlookingattherightmeasureofriskSmallvs.LargestocksSmallstockshaveoutperformedlargestocksbyabout12%ayearover1929-1979timeperiodShouldwebuylotsofsmallstocks?DependsonwhethertheyareriskiersmallstockshavehigherstandarddeviationsandbetasbutnothighenoughtoexplaintheirreturnsSo,smallstocksmaybemispricedBUT:althoughsmallstockreturnsarehigh,thismayonlybebasedonafewextraordinaryyearsWemaybemissingsomedimensionofriskTheJanuaryEffectMuchofthesmallfirmeffectseemstooccurinJanuaryMuchofsmallfirmpremiumoccursinfirstfivedaysofJanuaryoftenexplainedbytax-losssellinghowever,effectiswidespreadininternationalmarketsalso,evenwhenthere'snocapitalgainstaxand,therestillseemstobeasizeeffectaftercontrollingforthis.IfthepositiveJanuaryeffectisamanifestationofbuyingpressure,itshouldbematchedbyasymmetricnegativeDecembereffect.maynotaccordwithefficientmarketswhydon'tpeoplebuyinDecemberinanticipation?andthepredictableJanuaryeffectfliesinthefaceofefficientmarkettheory.‘Windowdressing'byinstitutionalinvestorsinfusionofcapitalatbeginningofyearOverreactionstudiessomestudiessuggestthatthereareinefficienciesduetopeopleoverreactingtoinformation〔1〕LosersandWinners----Longtermreversaltakeathreeyearperiodandrankstocksonthebasisoftheirperformanceoverthatperiodforma‘winner"portfolioofthetop10%best-performingstocksforma‘loser"portfolioofthebottom10%worst-performingstocksthisiscalledacontrarianstrategylookattheirreturnsoverthenextfewyearstheloserportfolioseemstooutperformthewinnerportfolio(DeBondtandThaler(1985))Twoexplanations:overreaction:thewinnersarefirmsthatpeoplehavebecometooexcitedaboutsubsequently,theyrealizethattheyweretoooptimisticpricefallsandreturnsarelowrisk:thelosersareriskierfirmstheirhigherreturnsarejustcompensationforriskbutlosersdonotappearriskieronstandardmeasuresofriskHowdoweaccountforrisk?VarianceUseregressionanalysisandapricingmodelCAPMFF3-factormodelExaminewhenthestrategyexhibitsthehighestandlowestpayoffs(i.e.,doesthestrategydowellwhenthemarketdoes?whenweareinthepeakofabusinesscycle?arecession?,etc.)Catastropherisk〔2〕ValueandGrowthformportfoliosofvaluestocksavaluestockisonewithlowpricerelativetosomemeasureoffundamentals,i.e.highbooktomarket(B/M)ratioscashflowtoprice(C/P)ratiosearningstoprice(E/P)ratiosalsoformportfoliosofgrowthstocks,i.e.withlowvaluesoftheseratiosWhygrowthvs.value?findthatvaluestocksdramaticallyoutperformgrowthstocksWhy?rational:Representsadistressfactorintheeconomy.Valuestocksaremorepronetothissourceofriskthangrowthstocks.higheraveragereturns.Valuestocksaretypically`fallenangels'irrational:Growthstocksare`glamorous'.Peopletendtowanttobuytheseandstampedetowardsthem,pushinguptheprice,anddepressingfuturereturns.Valuestockshavebeenneglected,causingtheirpricetofall,andexpectedreturnstorise.Thisisanoverreactionstory.Also,valuestocksdonotappearriskier,however.theydon'thavehighervariancetheydon'thavehighdownsiderisk(i.e.,donotunderperformoftenorbythatmuch)theydon'thavehigherbetastheydon'tunderperforminbadstatesoftheworldLakonishok,Shleifer,andVishny(1994)somaybeit'saninefficiency,drivenagainbyoverreactionPsychologicalfoundationsforoverreaction:representativenessheuristicsmallsamplebiasbutofcourse,itcouldstillberisk!TheFama-FrenchdebatesmallstocksandhighB/Mstocksearnreturnsthatarehigherthanisrequiredfortheirrisk,accordingtotheCAPMmeasureofrisktwopossibilities:smallstocksandhighB/MstocksaremispricedOR:theCAPMisn'tmeasuringriskproperlyFamaandFrench(1993)constructanewasset-pricingmodel,the‘’3-factormodel"whichmakessmallandhighB/Mstockslookriskierstartwiththemarketfactor,andaddtwonewfactors,F(small)(=SMB)andF(B/M)(=HML)theysupposedlytrackgoodandbadstatesoftheworldsmallstockshavehighcovariancewithF(small)highB/MstockshavehighcovariancewithF(B/M)theyareriskier!EvidenceinfavorofFF:Adjustingthelong-runcontrarianprofitsfoundbyDeBondtandThaler(1985)usingthe3-factormodel,theprofitsdisappear(i.e.,alpha=0.).pastlong-termlosersloadhigheronSMBandHMLthanpastwinners,eventhoughtheyhavethesamemarketbeta.long-termlosersmoreriskythanlong-termwinners.The3-factormodelcapturesahostofotheranomaliesaswell!EvidenceagainstFF:LSV(1994):HMLandotherbook-to-priceratiosperformwellinpoortimes.DanielandTitman(1997):characteristicsratherthanfactorloadingspriceassetsbettercontrolforsizeandB/Mcharacteristics,SMBandHMLnolongerexplainaveragereturnsex:twostockswithsamesizebutdifferentbetasonSMBhavethesameaveragereturn.twostockswithsamebetaonSMBbutdifferentsizeshavedifferentaveragereturns.DoesthisnecessarilyimplysizeandBE/MEareirrationalanomalies?No,couldproxyforsometrueunknownfactor,bettercapturedbythecharacteristic.Measurementofbetasarepronetoestimationerror,whichincreasesnoiseintherelationbetweenthebetasandaveragereturns.Underreactionstudiesotherstudiessuggestthatthereareinefficienciesduetopeopleunderreactingtoinformation〔1〕Momentumformportfoliosofstocksthatperformedverywellinrecentpast(`winners')i.e.overthepast3monthstooneyearsimilarly,formaportfolioof`loser'stocksthewinnersoutperformtheloserse.g.buythewinnersandselltheloserse.g.azero-costportfoliowhichbuyswinnersandsellslosersfromthepast6monthsearns12%(annually)overthenext6months!contrasttothemean-reversionresultsourceofinefficiency:underreactiontoinformation?Or,isitrisk?〔2〕EarningsAnnouncementsslowpriceresponsetoearningsannouncements(post-earningsannouncementdrift)eachquarter,rankstocksonthesizeofthesurpriseintheirearningsannouncement(surprise=actual-expected)formaportfolioofstockswithlargestpositivesurprises(portfolioA)andaportfolioofstockswiththelargestnegativesurprises(portfolioB)AoutperformsBisitrisk?beta,factormodeltypechecksdon'tfindanyover50quartersfrom1974-1986,strategyearnedpositiveabnormalreturns46timesManyexamplesofunderreactiontoinformation:tochangesindividendpolicystrategy:buycompaniesthathavejustannouncedadividendincrease;sellthosethathavejustannouncedacutindividendstorepurchasesofsharesstrategy:buycompaniesthathavejustannouncedasharerepurchasePsychologicalFoundationsforUnderreaction:conservatism,pessimismOtheranomaliesThenewissuespuzzleHotoffering

Iftheseanomaliesareinefficiencies,whydoesn'tarbitrageeliminatethem?inpractice,arbitrageislimiteddonothaveinfinitenumberofstocks,thereforethereissomerisksometimesthestrategycandoverypoorly,andyoulosealotofmoneymoneymanagersandindividualsmayhaveshorthorizons(duetoregularevaluationsorpsychologicalpreferences)amispricingcantakeawhiletocloseinfactitmaynotclosewithintheinvestor'shorizoninvestorwillrestrictthesizeofpositiontakentherecanbehightransactionsandtradingcostsduetoturnoverinthesestrategiesliquiditycanbelowattimeswhenyouneeditmostmonitoringcanbehighthereareshortsalesconstraintsMeasurementissues:Theseanomaliesaremarket-basedmeasurese.g.,theyincludepricesize,BE/ME,pastreturns(contrarianandmomentum),E/P,etc.,allcontainpriceinthem.soanythingmissedbythepricingmodelwillshowupinoneofthesevariablese.g.,appearsonbothsidesoftheregressionequationthiswasnotedbyBall(1978)andformalizedinBerk(1995)wemayneverknowifpickingupmispricingorinadequacyofpricingmodel.Dataminingtechniquesoffindinganomaliesareoftensubjecttothedataminingcritiqueifyoutryenoughvariables,somethingwilleventuallyappeartopredictreturnsbut,theforecastpowerofthisvariablewillbecompletelyspurious(i.e.,itwon'tworkoutofsample)e.g.,generate100differentdataseriesofcompletelyrandomnumbersrunaregressionofactualstockreturnsoneachofthe100randomdataseries.someoftheregressionswillproducesignificantresults:doesthismeanyoucanmakemoney?NO!thedataminingcritiqueisverypowerful:bearitinmindwhenpeopletrytoimpressyouwithstrategiesthatworkedgreatinthepast.theyprobablywon'tworkinthefuture!ResponsetoDataMiningCritique:Manyoftheseanomaliesappearinother(international)markets(seeHawawinian