IndianAssociationofAlternativeInvestmentFunds(IAAIF)

PortfolioConstructionwithAlternativeInvestments

RohanMisra,CFA,FRMPartner&CEO

Transparency.Safety.Performance.

FINDINGTHEEQUILIBRIUM

1.ASSETALLOCATION2.ACTIVEVSPASSIVEBALANCE3.MANAGER/FUNDSELECTION

PART1:PORTFOLIOCREATION

AGENDA

PART2:PORTFOLIOPERFORMANCEEVALUATIONANDREBALANCING

3

Part1:PortfolioCreation

…Bymixinganumberofpoorlycorrelatedassets,and-

• Maximizetargetreturnforagivenlevelofrisk

• Minimizeriskforatargetedlevelofreturn

Findingtheequilibrium…

5

2waystoconstructportfolios

FINDINGTHEEQUILIBRIUMAssetAllocation

ActiveVsPassiveMix

Manager/FundSelection

BottomUp Topdown

• Usedbyprivateinvestors

• Adhoc–objectivesandrisknotfactored

• Susceptibleto“buyhighselllow”behaviour

• Favouredbyprofessionalinvestors

• Beginsbyexploringinvestmentrisk

• Createsaframeworktodecideinvestmentsbasedoninvestor’sobjectives

6

TypicalObjectives:• Maximizereturnforagivenlevelofrisk• Minimizeriskforatargetedlevelofreturn

SettingobjectivesILLUSTRATIVEEXAMPLEReturnTarget:5%plusinflation;afterfeesRiskBudgetandRiskDefinition:Maxloss20%TimeHorizon:5 years

Return

TimeRiskBudget

Examplesofotherconsiderations1. Interim/TerminalGoals:financingasecondhomepurchase2. Constraints: dedicatedassets(residentialhome),assetclass

restrictions,shortsellingrestrictions

7

FINDINGTHEEQUILIBRIUM

1.ASSETALLOCATION2.ACTIVEVSPASSIVEBALANCE3.MANAGER/FUNDSELECTION

PART1:PORTFOLIOCREATION

8

Whatisanassetallocation(AA)

9

Portfolio strategy that involves setting target allocations forvarious asset classes and attempts to balance risk versusreward, according to the investor’s risk budget, goals and timehorizon

Strategic Asset Allocation (SAA)Driven by the long-term investmentobjectives of the investor, with atypical time frame of > 1Y

Tactical Asset Allocation (TAA)Represents short-term tilts away fromthe SAA that are driven by visibleopportunities and risks

WhybeginwithAA?

-50

0

50

100

150

BHBEquityFunds BHBBalancedFunds

HEI&IKEquityFunds

HEI&IKBalancedFunds

Rsquare%

DecompositionofTime-SeriesTotalReturnVariations

ActiveManagement AssetAllocationPolicy

MarketMovement InteractionEffect

BHB: Brinson,Hood,Beebower, DeterminantsofPortfolioperformance,1986IK: Ibbotson&Kaplan,DoesAAexplain40,90or100%ofperformance?,2000HEI: Henzel,Ezra,Ilkiw,TheimportanceoftheAAdecision,1991

10

Choiceofassetclassesandtheirmixiskey• Forportfolioswithmarketexposures,e.g.longonlyportfolios,

marketmovement andassetallocationpolicymainlydrivereturnvariability

• Marketmovementisafunctionofthechosenassetclasses

• Assetallocationpolicydefineshowwehavemixedthechosenassetclasses

• CanweimproveanassetallocationbyincludingalternativeslikeHedgeFunds,PE,RealEstateandCommodities??

11

AssetclasschoicesAssetClass ProxyIndex Currency Freq.

Equities MSCI AllCountry WorldNetTotalReturnIndex USD Monthly

Bonds BloombergBarclaysUSGovtTotalReturnIndexUnhedgedUSD USD Monthly

Commodities BloombergCMCITotalReturnIndex USD Monthly

HedgeFunds HFRIFundOfHedgeFundsCompositeIndex USD Monthly

RealEstate FTSEEPRANARIETDevelopedTotalReturnIndex USD Monthly

PrivateEquity CambridgeAssociatesUSPrivateEquityIndex USD Quarterly

Allindicesareassumedforillustrationpurposesonly,AlldatastartingJan-2000

12

Summarystatistics

Equity Bonds Com Hedge Funds

Real Estate

Private Equity

Ann. Return 3.5% 4.8% 6.4% 3.2% 9.5% 9.7%

Ann. Volatility 16.0% 4.2% 16.2% 5.1% 19.1% 10.4%

Max DrawDown 54.9% 4.6% 57.1% 22.2% 67.2% 25.2%

Return/Volatility 0.22 1.16 0.40 0.64 0.50 1.01

EquityreturnsbiaseddownwardsassamplebeginsinTechbubble,Source:B&BAnalytics

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Risk/ReturnProfiles

Note! :Profilesmaybepotentiallybiasedduetothechosensamplesince2000Source:B&BAnalytics

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

0.0% 5.0% 10.0% 15.0% 20.0% 25.0%

Bonds

HF

PE RE

COM

EQ

14

In-samplecorrelations

Source:B&BAnalytics

Equity Bonds Com HedgeFunds

RealEstate

PrivateEquity

Equity 1.00

Bonds -0.28 1.00

Com 0.56 -0.17 1.00

HedgeFunds 0.67 -0.13 0.58 1.00

RealEstate 0.80 -0.03 0.49 0.58 1.00

PrivateEquity 0.52 -0.29 0.35 0.41 0.40 1.00

AverageCorrelations 0.45 -0.18 0.36 0.42 0.45 0.28

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ImpactofintroducingAltsina50Eq/50bondsportfolio

Source:B&BAnalytics,portfoliosrebalancedmonthly

50Eq;50Bonds

45Eq;45Bonds;10Com

45Eq;45Bonds;10HF

45Eq;45Bonds;10RE

45Eq;45Bonds;10PE

AnnReturn 3.9% 4.1% 3.8% 4.3% 4.4%

VolatilityAnn. 7.7% 7.9% 7.3% 8.6% 7.2%

Return/Vol 0.50 0.51 0.52 0.50 0.61

MaxDrawDown 30% 31% 29% 35% 29%

Returns adjustedtothevollevelof50Eq/50BondsPortoflio

Ann.Return 3.9% 4.0% 4.0% 3.9% 4.7%

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Databiasesandothervagariescommontoalternatives

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1.Survivorshipbias• Generallyacceptednotion: Indices,inparticularhedgefunds

ones,aredistortedbecause‘closed’fundsnolongercontribute– andremainingfundsoverstatetheaverage

• Somenuancedstudieslookatreasonforclosureandfindtheindexunderstatesactualperformance1. ‘Closures’duetonegativeperformance2. ‘Closures’tonewinvestorsduetostrongperformance

• Juryisstilloutthere!• Partialremedy– UseaHedgeFundFoF IndexReturns 1Y 2Y 3Y

HFRGlobalAssetWtd Composite 5.38% 8.31% 23.68%

HFRFundofFundsComposite 4.16% 4.94% 17.25%

Source:B&BAnalytics,HFRI 18

2.Smoothed&staleprices• Esp.Relevantinthecontextofprivateequityandrealestate• Appraiserlacksconfidenceinthenewevidenceregarding

valuation- insteadattachestoomuchweightonthemostrecentempiricalevidence

• Reportedvaluationlagstruemarketvaluation• Positiveserialcorrelationisintroducedintoreturns

REDUCEDVARIABILITYINRETURNSACROSSTIMEà UNDERSTATESRISK

NEEDSTOBECORRECTED!

19

Correctingforsmoothedprices• Vastbodyofacademicwork

exists• FGW1993isaonewidely

adoptedapproach• Removesserialautocorrelation

tounsmooththetimeseries• Timeseriesisregressedagainst

laggedvaluestoidentifystatisticallysignificantvariables.

• Unsmoothedseriesisobtainedbyremovingthesevariables.

PE Beta P-Value SignificantIntercept 1.66 0.01 YesLag1 0.32 0.00 YesLag2 0.17 0.09 NoLag3 -0.02 0.87 NoLag4 0.02 0.80 No

Beta P-Value SignificantIntercept 2.04 0.00 YesLag1 0.38 0.00 Yes

r(t) = (r*(t) – 0.38r*(t-1))/wUSPrivateEquity* VolatilitySmoothedSeries 9.4%UnsmoothedSeries 15.7%Return 9.7%Return/NewVol 0.62

*Source: Cambridge Associate, FGW : Fisher Geltner Webb 20

• Mostmodelsassumethatreturnsfollowa“normaldistribution”– Chanceofmove>3s.d.<1/300– Skewness=0;returnsymmetry– Kurtosis=3

• Inrealitymostassetclassesexhibitnegativeskewandexcesskurtosis…i.elefttailrisk

3.Non-normalityandtailrisk

21

ThiscanbeseeninourdataEquity Bonds Com Hedge

FundsReal

EstatePrivate Equity

Skewness -0.89 -0.20 -1.08 -1.15 -1.54 -0.57

Excess Kurtosis 2.47 1.36 4.07 4.26 7.15 1.94

Directlyincorporatingvolatilityintomodelswillunderestimateriskandleadtoincorrectallocations

0

20

40

60

-30%

-28%

-25%

-23%

-20%

-18%

-15%

-13%

-10% -8%

-5%

-3% 0% 3% 5% 8% 10%

13%

15%

18%

20%

23%

RealEstateMonthlyReturnDistribution

Source:B&BAnalytics 22

Adjustingfornon-normality

Source:B&BAnalytics

Twoapproaches:

• Adjusttherisk(std.deviation)ofeachassetclassorinvestmenttocapturethehighermomentsofskewnessandkurtosisbeforedeterminingtheoptimalportfolioweights

• Directlyadjusttheportfolioriskmeasureintheassetweightingprocess(i.etheoptimizationprocess)toincorporatetheskewnessandkurtosisoftheportfolioforagivencombinationofweights

• Secondapproachisconvenient

• Bothapproachesareappropriateonlyifthehistoricaldistributionappropriatelycaptureshighermoments

23

PortfolioMath

24

Recap:essenceofportfolioconstruction

• Maximizetargetreturnforagivenlevelofrisk

• Minimizeriskforatargetedlevelofreturn

Howtomeasureportfolioreturn andwhatisportfoliorisk?

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PortfolioReturnWeightedaverageoftheexpectedreturns ofportfoliocomponents

Example:2assetclassportfolio

26

Varianceasportfoliorisk• Notasimpleweightedaverageofindividualcomponentrisks.• Requiresanestimateofexpectedcovariancesbetweenassets–

whichfirstrequiresanestimateofthevolatilitiesofallassetsandthecorrelations betweenthem

Example:2assetclassportfolio

PortfolioVolatility:√0.0504=22.4%

(wi)’COV(wi)or

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• Investor’sdon’tthinkinvolatilityterms!• Focusisondownsiderisk• Valueatrisk(VaR)focusesonthelefttailofthereturndistribution• Interpretation:95%chancethatportfoliolosswillnotexceed

X%overagiventimehorizon;95%representsconfidence

VaRasaportfolioriskmeasure

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ParametricVaR• Assumesnormaldistribution– requiresonlymeanand

standarddeviationofreturnstocalculateVaR

• VaR (confidence)=Mean- Std.Dev*z

• ‘z’isthenormalz-scorecorrespondingtotheconfidencelevel(e.g.1.65for95%,1.96for99%)

• Simplebutpracticallylimited– doesnotincludenegativeskewandfattails!

29

ModifiedParametricVaR• FormulaicadjustmenttoparametricVaRfortheempirically

observedskewandkurtosisoftheportfolioreturndistribution

• Somewhatbetteratcapturingnon-normalitybytransformingthenormal‘z’toamodified‘Z’incorporatinghighermoments

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Drawdown

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• MaxDDmeasurespeaktotroughloss– veryconservative• Difficulttoimplementinpracticeandneedstobesimplifiedtoan

eitherinceptiontodatedrawdownsorrollingdrawdowns

OptimalPortfolioMixTraditionalMarkowitzApproachesbasedonModernPortfolioTheory

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OptimizationSetup

• MaximizeExpectedPortfolioReturn subjecttoanabsoluteconstraintonrisk<=10%

• Riskcanbemeasuredbyeithervariance,VaR(valueatrisk),m-VaR(modifiedvalueatrisk),drawdownsignoredtoretainsimplicity

• Sumofportfolioweights=100%

• Individualweightsshouldbe>0%and<35%(thelattertoensurediversification)

33

0.0%1.0%2.0%3.0%4.0%5.0%6.0%7.0%8.0%9.0%10.0%11.0%

0.0% 5.0% 10.0% 15.0% 20.0% 25.0%

ExpectedReturnadjustments

AdjustmentsdonelargelytoreflectcurrentthinkingaroundcapitalmarketassumptionsSource:B&BAnalytics,forillustrativepurposesonly

Bonds HF

PE

RE

COMEQ

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Capitalconstraints(0,35%)

34.8%10.5% 7.4%

30.2%

35.0% 35.0%

19.5% 22.6%

35.0% 35.0% 35.0%

0%

20%

40%

60%

80%

100%

MeanVariance(Parametric)

MeanVaR(Parametric)

MeanmVaR(Parametric)

Equity Bonds CommoditiesHedgeFunds RealEstate PrivateEquity

• Allocationtobondsandhedgefundsincreasesasmoreconservativeapproaches(VaRandmVaR)areused

35

PortfolioMetrics

MeanVariance(Parametric)

MeanVaR(Parametric)

MeanmVaR(Parametric)

AnnualizedReturn 6.8% 6.1% 6.0%

AnnualizedRisk 10.0% 10.0% 10.0%

Return/Risk 0.68 0.61 0.60

Drawdown 30.3% 20.3% 19.2%

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Unconstrainedefficientfrontiers

4.0%

6.0%

8.0%

10.0%

12.0%

ReturnVsVolatility(Parametric) ReturnVsVaR(Parametric) ReturnVsmVaR(Parametric)

37

OptimalPortfolioMixOtherApproaches

38

CapitalAllocation

Bonds Equities

PracticalissueswithtraditionalapproachesEstimatingmanyinputsforNassetclasses• Nexpectedreturns• Nexpectedvolatilities• N(N-1)/2expectedcorrelations

RiskAllocation

Bonds Equities

Vs

39

Practicalissueswithtraditionalapproaches

5.0%18.3%

30.5% 41.2% 50.3%32.8% 32.8% 32.8% 32.8% 32.0%

30.6%30.1%

30.5%31.5%67.2% 67.2% 67.2% 67.2% 63.0% 51.1% 39.4% 28.3% 18.3%

0%

20%

40%

60%

80%

100%

7.00% 7.50% 8.00% 8.50% 9.00% 9.50% 10.00% 10.50% 11.00%

Uncon

strained

Weights

EquityReturnAssumption

Sensitivityofweightstochangingequityreturnassumptions

Equity Bonds Commodities HedgeFunds RealEstate PrivateEquity

40

RiskParity• Letsthrowsomedarts!• Riskdrivenapproaches– expected

returnsnotrequiredtobeestimated• Basedonpremisethatarangeof

outcomes(risk)iseasiertoestimatethantheoutcome(return)

• Optimizecapitalweightssothat“riskcontributions”ofallassetclassesareequal

• RiskContribution(RC) ofasseti=W(i)XStd.Dev(p)XBeta(i,p)

• Ifanasset’sweight=20%,itsbetawithportfolio=2,thenassumingportoliovol=10%,theRC=4%=>or40%ofriskcomesfromtheasset

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RiskParity5.8%

57.5%6.8%

18.0%

4.7%7.2%

AssetAllocation

Equity

Bonds

Commodities

HedgeFunds

RealEstate

PrivateEquity

20.0%

20.0%

20.0%20.0%

20.0%

20.0%

RiskContribution

Risk Parity

Annualized Return 4.1%

Annualized Risk 4.1%

Return/Risk 0.99Drawdown 12.8%

100

200

300

2000 2003 2006 2009 2012 2015

PortfolioEvolution

RiskParity

Criticism: Too much weight to fixed income, requires leverage to scale to traditional portfolio risk budgets 42

RiskBudgeting

• Optimizecapitalweightssothat”riskcontribution”ofeachassetclassfallswithinthemaxriskcontributionallocatedtoit

• Thisinvolvessettingriskcontributionbudgetse.g.RC(1)=X,RC(2)=Y…

• Sum[RC(i)]=PortfolioStandardDeviation

• Robustalternativetousingexpectedreturns->Increaseriskbudgetsifviewonassetclassispositive,decreaseriskbudgetiftheviewisnegative

43

FINDINGTHEEQUILIBRIUM

1.ASSETALLOCATION2.ACTIVEVSPASSIVEBALANCE3.MANAGER/FUNDSELECTION

PART1:PORTFOLIOCREATION

44

Arealternativebetasinvestable?AssetClass DevelopedMarkets India

Equities(EQ) Thousands ofETFsavailablebyregion,market,sectorandstyle

Few ETFs,butmanyMFstochoosefrom

FixedIncome(FI)

Largenumber ofETFsavailablebyFX,Duration,Rating,Riskcountry

ETFspracticallynon-existent;butseveralMFstochoosefrom

Commodities(COM)

Many ETFandETNoptionsonmostcommodities Few,largelylimitedtoGold

RealEstate(RE) REIT&CEF/FoF optionsavailable 1st REITexpected in2017;REPEFundsexisting

Hedge Funds(HF)

SeveralHF Indexreplication &FoFavailable

PMS, AIFfunds,Largelysinglemanagers

PrivateEquity(PE) DiversifiedFoFoptionsavailable Largelysinglemanagers

45

Unfortunatelynot

• Traditionalbetas(EQ,FI,COM)cheaplyavailable

• Altmanagers(HF,PE,RE)mainlyseektodeliveralpha

• Altbetasnoteasilyavailable(atleastforHF,PE,RE)

• HighdispersionofAltreturnsmakesitdifficulttoreplicatebenchmarks,FoFinvestmentroutesolvesthisproblemonlypartially

Solution: TreatAlts(espHF,PE,RE)asapartofanactivemanagementmandate

46

Core&SatelliteApproach

• Core:long-term,low-costinvestmentsincludingETFs,MFsetcseekingmarketreturns(EQandFIandpossiblyCOMbetas)

• Satellite:activelymanagedalphaproducinginvestmentsseekingtodeliverabsolutereturn(HF,PE,RE)

• Abestofboth(active&passive)worldsapproach• Optimizecosts(inexpensivecore)• Potentialtooutperformtheasset

allocation• Diversifyriskthroughgreaternumberof

holdings

Core

Satellite

AssetClass

Passive(Core)

Active(Satellite)

EQ ✔ ✔

FI ✔ ✔

COM ✔ ✔

RE ✔

HF ✔

PE ✔

47

ButthisshouldbeconsistentwithAssetAllocation

1. E[RC(core+satellite)]<=E[RC(assetclassinSAA)]

2. E[R(core+satellite)]>=E[R(assetclassinSAA)]

WhereE[R]isexpectedreturnandE[RC]isexpectedriskcontribution.

Niceintheory,difficulttoachieveinpractice!

48

FINDINGTHEEQUILIBRIUM

1.ASSETALLOCATION2.ACTIVEVSPASSIVEBALANCE3.INVESTMENT/MANAGERSELECTION

PART1:PORTFOLIOCREATION

49

DiversificationwithinassetclassHowmanyinvestmentsshouldwemakewithinHF,withinPE..?

Risk

123 6 10 20 25…#investments

• Diversifyviaafundoffundstructure– lowinvestmentsize,buthigherfeetrade-off– anoutsourcingdecision

• Cultivatesuperiormanagerselectioncapabilities,i.e.identifyingtrulyuncorrelatedalphageneratingstreams

Altstypicallyrequirehighinvestmentsizes

Traditionaldiversificationmethodsarenotpracticalforallinvestors

ManagerselectionbecomesKEY

50

TheThreePs

Canamanagerbetrusted?

• Trackrecord• Background• Education• Philosophy• Attitude

People Process Performance

Whatsetsthemanagerapart?

• Investmentstrategy

• Risks• Restrictions• Rigor&

Repeatability

Isthereactualskill?

• Sustainedoutperformance

• Benign&adverseenvironments

• Adaptability• Peergroup

analysis

Isthemanageranaturalfit?

• Correlation• Quantitative

analysisandmisfitrisk

• Willthestrategycontinuetoworkatscale?

51

Managingmisfitrisk• Startbyidentifyinginvestments

withineachAltassetclassthatareexpectedtobeatAAhurdlerate(HF1,HF2,PE1,PE2etc..)– keepaneyeoncorrelations,esp.tailones

• PoolselectedAltinvestmentswithotherinvestmentsandestimateanextendedcovariancematrix

• Optimizeweightstominimizetrackingerror(wp – wsaa)’COV(wp – wsaa)subjecttoconstraints• Sumofweightstoinvestmentswithin

assetclass≅ SAAwt.toassetclass• Portfoliorisk=SAArisk

HF1 HF2… PE1 PE2… RE1 RE2… EQ FI COM

HF1

HF2…

PE1

PE2…

RE1

RE2…

EQ

FI

COM

Note:ThiscovarmatrixassumesthatthereisonlyonepassiveinvestmentwithinEQ,FI,COMthatperfectlyreplicatestheindexusedintheSAA

Simpleandstraightforwardapproach,especiallywhennumberofinvestmentsarenottoolarge

52

Identifyingsourcesofreturn• A simple approach to analyze the sources of excess return for a

fund relative to a comparable style benchmark

• Define a peer group of hedge funds with similar style and size

• Calculate average peer return over time – benchmark

• Calculate fund β w.r.t to benchmark over time via rollingregressions. Then– Style Returns = β* Rb– Timing alpha = Rb *(β - 1)– Selection alpha = Rp - β* Rb– Timing alpha + Selection alpha = Excess Return = Rp - Rb

• Analyze stability and superiority of timing and selectionreturns

Implicitassumptionisthatanappropriatepeergroupexists! 53

Peergroupstyleattributions

54

FINDINGTHEEQUILIBRIUMPART2:PERFORMANCEEVALUATIONANDREBALANCING

55

Whatmakesavalidbenchmark?

56

• Investable: abilitytobuyandholdthebenchmark

• Unambiguous: namesandweightsofholdingsareclearlystated

• Measurable: transparentw.r.tcalculation

• Independent: notbedesignedbymanager– removesconflict

• Relevant: shouldreflecttheinvestmentstrategy

HowdoesthislookinthecaseofAltindices

57

• Investable: NOTREALLY,EXCEPTCOMMODITIES

• Unambiguous: YES

• Measurable: YES

• Independent: YES

• Relevant: MAYBE

Peergroupanalysis

58

Peergroupsagoodbenchmark?

59

Convenient- showstheedge,orlackthereof!

• Investable: NO• Unambiguous:NO• Measurable:YES• Independent: NO• Relevant: MAYBE

Issues: classificationbias,survivorshipbias,pronetosnapshotassessments– endpointbias,canbegamed…

Endpointbias

60

Thesamefundrankedinthetopquartilewhenlookingattrailingperiods

Onlyonebenchmarkplease!

61

AssetClass Cash/Hurdle Index PeerGroup

Equities(EQ) ✔

Useasasecondarytooltoassessperformance

versuscompetition,andattribute

returns

FixedIncome(FI) ✔

Commodities(COM) ✔

RealEstate(RE) ✔(REPE/REFs)

✔(REITS)

Hedge Funds(HF) ✔

PrivateEquity(PE) ✔

BasicPerformanceComparisonMeasures

62

TimeWeightedReturn

• Cumulatesreturnsovertime

• Givesanequalweighttoeachresult,regardlessofthedollaramountinvested

• Returnsarecalculateddailyandgeometricallylinkedovertime

• Time-weightedmethodsdonotconsidertheeffectofcontributionsorwithdrawalsontheportfolio

63

TimeWeightedReturn

Investor 1 invests $1M on Dec 31. On Aug 15 of the followingyear, his portfolio is valued at $1,162,484. At that point, he adds$100,000, bringing total value to $1,262,484. By the end of theyear, portfolio has decreased in value to $1,192,328.

1st period return = ($1,162,484 - $1,000,000) / $1,000,000 =16.25%2nd period return = ($1,192,328 - ($1,162,484 + $100,000)) /($1,162,484 + $100,000) = -5.56%Time-weighted over the two time periods = (1 + 16.25%) x (1 + (-5.56%)) - 1 = 9.79%

64

Howismyportfoliodoingonanabsolutereturnbasis?• An absolute return measure allows direct alignment with

investment objective• No comparison to a benchmark or peer• Relevant for goal based investing agnostic of market or

benchmark performance

50100150200250300

Jan-00 Jan-02 Jan-04 Jan-06 Jan-08 Jan-10 Jan-12 Jan-14 Jan-16

Portfolio AbsoluteReturnBenchmark

PortfolioAnn.TWR=6.45%

65

Howismyportfoliodoingonarelativereturnbasis?• Shows the portfolio is doing relative to SAA benchmark after

incorporating for drift and actively set tactical weights

50

100

150

200

250

300

Jan-00 Jan-02 Jan-04 Jan-06 Jan-08 Jan-10 Jan-12 Jan-14 Jan-16

Portfolio SAA

PortfolioAnn.TWR=6.45%SAAAnn.TWR=5.70%

66

SharpeRatio• Measures portfolio excess return generated over the risk free

rate per unit of risk taken• Implies that one is left with the premium that is independent

of total risk• Provides easy comparison of portfolios and best used as a

ranking metric

Sharpe Ratio = (Ra - Rf) / σaRa is the portfolio returnRf is the risk free rateσa is the standard deviation of the portfolio return

67

SharpeRatio

• Portfolio Sharpe = (6.45% - 0.60%) / 8.16% = 0.72• SAA Sharpe = (5.70% - 0.60%) / 7.46% = 0.68

• Pitfalls– It is a ranking criterion only– Negative Sharpe is meaningless– Does not incorporate higher moments– Upward movement is penalized via higher volatility– Doesn’t distinguish between active and passive return– Not so useful when comparing strategies with vastly different trading

frequencies (e.g. HFT versus low frequency)

68

TreynorMeasure

• Measures outperformance over market or benchmark (beta)• Independent of portfolio risk meaning one can compare two

portfolios even though they have different betas

Treynor Measure= (Ra - Rb) / βaRa is the portfolio returnRb is the risk free rateβa is the beta of the portfolio

69

TreynorMeasure

• Portfolio Treynor Measure = (6.45% - 0.60%) / 1.22 = 0.048

• Pitfalls– Doesn’t quantify value added by active portfolio management– It is a ranking criterion only– Unlike Sharpe which applicable to all portfolios, Treynor uses relative

market risk or beta and hence is applicable only to well diversifiedportfolios

70

Jensen’sAlpha

• Measure of a security’s excess return with respect to theexpected return given by Capital Asset Pricing Model

Jensen’s Alpha = Ra - [Rb + βa*(Rm - Rb)]= 6.45% - [0.60% + 1.22*(5.70% - 0.60%)]= -0.39%

Ra is the portfolio returnRb is the risk free rateRm is the market returnβa is the beta of the portfolio• Pitfalls: It only allows an absolute measurement of active

return71

SharpevsTreynorvsJensen

Return Beta Std.Dev SharpeRatio

TreynorMeasure

Jensen’sAlpha

ManagerA 10% 0.90 11% 0.91 0.11 0.03

ManagerB 14% 1.03 20% 0.70 0.14 0.06

ManagerC 15% 1.02 27% 0.56 0.15 0.07

Assuming risk free rate of 0% and benchmark return of 8%Don’t forget: this is a snap shot, analyzing across time is crucial to assessstability of these rankings 72

Therebalancingdecision

73

PortfolioSettingSAA

AllocationMin

AllocationMax

AllocationCurrent

AllocationEquity 25% 20% 30% 20.0%

Bonds 20% 15% 25% 12.6%

Commodities 5% 0% 10% 4.0%

HedgeFunds 15% 10% 20% 21.4%

RealEstate 10% 10% 20% 11.0%

PrivateEquity 25% 20% 30% 31.0%

74

Should we rebalance? - YES

Canwerebalanceeffectively?MOSTPROBABLYNOT

• Lowtradingliquidity(potentiallyduetoilliquidinvestments)• Subscription/Redemptionwindows:timetakento

subscribe/redeempostrequest• Lock-ins:investmentcan’tberedeemedatall• Investmentsize:accuraterebalancingsimplynotpossible

unlessportfolioisofsignificantsize• Hightransactioncostsandtaxation

Factorintheseconsiderations– setwiderSAAbands

75

Thankyou.

76