MEANREVERSION:UNIVERSAL
TRUTHORDANGEROUS
DELUSION!
Historyrepeatsitself,untilitdoesnot!
TheEssenceofMeanReversion
¨
¨
Instatistics,meanreversionisthetermusedtodescribethe
phenomenonthatifyougetanextremevalue(relativetothe
average)inadrawofavariable,theseconddrawfromthe
samedistributionislikelytobeclosertotheaverage.
Inmarketsandininvesting,meanreversionhasnotonly
takenonamuchbiggerrolebuthasarguablyhadagreater
impactthaninanyotherdiscipline.
¤
¤
JeremySiegel'sargumentforwhy"stockswininthelongterm"is
baseduponhisobservationthatoveraverylongtimeperiod(more
than200years),stockshaveearnedhigherreturnsthanotherasset
classesandthatthereisno20-yeartimeperiodinhishistorywhere
stockshavenotoutperformedthecompetition.
Many“value”investingstrategies(buylowPEstocks,lowPBVstocks
etc.)arebaseduponthepresumptionofmeanreversion.
2
TheCountertoMeanReversion
¨
¨
¨
Justasthereareaplethoraofstrategiesbuiltaroundmean
reversion,therearealmostasmanybuiltonthepresumption
thatitwillnothappen,atleastduringaspecifiedtime
horizon.
Manymomentum-basedstrategies,suchasbuyingstocks
withhighrelativestrength(thathavegoneupthemostover
arecenttimeperiod)orhavehadthehighestearnings
growthinthelastfewyears,areeffectivelystrategiesthatare
bettingagainstmeanreversioninthenearterm.
Whileitiseasytobeanabsolutistonthisissue,theironyis
thatnotonlycanbothsidesberight,eventhoughtheir
beliefsseemfundamentallyopposed,butworse,bothsides
canbeandoftenarewrong.
3
Formsofmeanreversion
¨
¨
¨
In timeseriesmeanreversion,youassumethatthevalueofa
variablerevertsbacktoahistoricalaverage.This,inasense,is
whatyouareusingwhenlookingattheCAPEtodayat27.27(in
August2016)andarguethatstocksareoverpricedbecausethe
averageCAPEbetween1871and2016iscloserto16.
In crosssectionalmeanreversion,youassumethatthevalueofa
variablerevertsbacktoacrosssectionalaverage.Thisisthebasis
forconcludingthatanoilstockwitha PEratioof30isoverpriced,
becausetheaveragePEacrossoilstocksiscloserto15.
Attheriskofovergeneralizing,markettimingstrategiesaremore
likelytobebuiltontimeseriesmeanreversionwhereasstock
pickingstrategiesoftenrevolvearoundcrosssectionalmean
reversion.
4
MeanReversion:TheQuestions
MeasurementQuestions
1.
TheMeancanbeverydifferentdependingnotonlyonthe
timeperiodthatyoulookatbutalsoonhowyoucomputeit
¤
OnReversion,therecanbedifferencesaboutwhenitwill
happenandhow.
¤
2.
FundamentalQuestions
¤
¤
Meanreversionisbuiltonthepresumptionthattheunderlying
processisstable(andthereforerevertsbacktohistoricnorms)
Ifthereisorhasbeenalargestructuralchangeintheunderlying
process,meanreversionwillnolongerwork.
5
TheCausesforStructuralChange
¨
Withtimeseriesmeanreversion,structuralchange
cancomefrom
Agingofeitheracompany,asectorortheentiremarket,
changingitscharacteristics.
¤ Technology
¤ Investorpreferences
¤
¨
Withcrosssectionalmeanreversion,structural
changecancome
Changesinindustrystructure
¤ Disruption
¤
6
TheUSEquityMarket
7
The2008WakeUpCall
1.
2.
3.
Globalizationisheretostay andwhileithasbroughtpluses,ithasalready
broughtsomeminuses.AsInotedinmypostoncountryrisk,noinvestoror
companycanaffordtostaylocalizedanymore,sincenotonlydomarketcrisisin
onecountryquicklybecomeglobalepidemics,butacompanythatdependson
justitsdomesticmarketforoperations(revenuesandproduction)isnowmore
theexceptionthantherule.
Financialservicefirmswereatthecenterofthecrisis,hashadlongterm
consequences.Notonlyhasitledtoalossoffaithinbanksaswell-regulated
entities,runbysensible(andriskaverse)people,butithasincreasedtheroleof
centralbankersineconomies,withperverseconsequences.Intheirzealtobe
saviorsoftheeconomy,centralbankers(inmyview)havecontributedtoan
environmentofloweconomicgrowthandhigherriskpremiums.
Loweconomicgrowthandlowinflationhasresultedininterestrateslowerthan
theyhavebeenhistorically inmostcurrenciesandnegativeinterestratesin
some.IknowthattherearemanywhobelievethatIamoverreactingandthat
itonlyaquestionoftimebeforewerevertbacktomorenormalinterestrates,
highereconomicgrowthandtypicalinflationbutIamnotconvinced.
8
TheStatisticalBasisforMeanReversion–
TheCAPEIllustration
9
AMoreUsefulPicture?
10
MoreStatistics:Correlation
11
StatisticsDoublingDown:Regressions
Expected annualized return in next 10 years
= 16.24% - 0.0044 (27.27) = 4.30%
12
FromStatisticstoInvesting:MarketTiming
Choices
¨
¨
¨
¨
Timingthreshold:Ifyoudecidethatyouwilltimemarkets
usingametric,youhavetofollowthroughwithspecifics.
Assetclassalternatives:Ifyoudecidetomovemoneyoutof
stocks,youhavetoalsospecifywherethemoneywillgoand
youhavefourchoices.
Holdingperiod:Youwillhavetospecifyhowlongyouplanto
staywiththe"markettimed"allocationmix.
AllocationConstraints(ifany):Theallocationthatyouhave
foranassetclasscanbeflooredatzero,ifyouarealongonly
investor,butcanbenegative,ifyouarewillingtogoshort.
Thecaponwhatyoucanallocatetoanassetclassis100%,if
youcannotorchoosenottoborrowmoney,butcanbe
greaterthan100%,ifyoucan.
13
MarketTimingResults
14
GeneralConclusions
1.
2.
3.
4.
TimePeriod:TheCAPEdeliversapositivemarkettimingpayoffinthefirsthalf
oftheentiretimeperiod(from1917to1966)andanegativeoneinthesecond
half(1967-2016).
Choiceoftimeperiodformedian:Usingthelifetimemediandeliversbetter
resultsduringthe"good"period(1917-1966)butworseresultsduringthe"bad"
period(1967-2016).Usingashortertimeperiodsforthemedianreducesthe
outperformanceinthefirsthalfoftheanalysisperiodbutimprovesitinthe
secondhalf.
BuyandSell:TheCAPE'stimingpayoffisgreaterwhenitisusedasabuying
metricthanasasellingmetric.Infact,youmakeapositivepayofffromusinga
lowCAPEasabuyingindicatorovertheentireperiodbutusingitisasignalof
overpricedmarketscostsyoumoneyinbothtimeperiod.
Activity:Increasingthedegreetowhichyoutilttowardsorawayfromstocks,in
reactiontotheCAPE,justmagnifiesthereturndifference,positiveornegative.
Thus,inthefirsthalfofthecentury(1917-1966),changingyourequityexposure
moreincreasesthepayofftomarkettiming.Inthesecondhalf,itmakesthe
negativepayoffworse.
15
TheBottomLine
¨
¨
LongPeriodsofData:areablessingandacurse,a
blessingbecausewecanextractmoreinformation
fromthemandacursebecausethatinformation
maynolongerberelevant.
Statisticsoncall:Sincewecanstatisticspainlessly,
usingbuiltintools,bothacademicsandpractitioners
haveincreasinglyturnedtousingstatisticalevidence
asproofthatyoucanbeatmarkets.Correlationis
notcashinthebank.Convertingstatistical
significancetoinvestmentreturnsisfarmore
difficultthanitlooks.
16