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REVIEW OF STRATEGIC ASSET ALLOCATION TOOLS

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Contents

Section Content Page 1. Executive Summary & Conclusions 3

2. Aim of Paper 5 Scope of Paper 6

3. TheDifferencesBetweenDeterministicandStochasticModellingApproaches 7

4. FurtherBackgroundInformationontheModels 9

5. TheMainProviders 11 - Distribution Technology (DT) 12 -EValue 17 -Moody’sAnalytics(MA) 21 -Morningstar 25 -WillisTowersWatson(WTW) 29 - AKG 33 -The“TraditionalApproach” 34 6. CommonLimitationsofModels 35 7. SummaryTableDetailingSomeDifferencesBetweentheMainProviders 38 8. EvaluatingModelPerformanceRecords 43 9. Appendix 45 -RiskProfilers 46 -FinaMetrica 46 -OxfordRisk 46 -RiskProfileBoundaries 48 -PlatformsandtheToolsEmbeddedWithinThem 50


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1. Executive Summary & Conclusions


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• The primary value of the strategic asset allocation (SAA)modelsappearstobeasanobjectivetoolthatcanbeusedwithinasuiteoffinancialplanningproducts.Such afinancialplanningsuitemayincludetoolstodetermine:

-attitudetoriskassessment-riskmapping- strategic asset allocation - savings programme assessment -riskillustrationtools

InouropiniontheSAAmodelsthatwehavereviewedwillperformasatisfactoryroleinmeetingtheneedsofinvestorsthoughadvisersshouldbeawareofthepossiblelimitationsoftheapproach.

• Thesearemodelsthatrelyuponadvancedstatisticaltechniquesandasophisticatedassessmentoffinancialmarkets.Thesemodelscannotanddonotpredictthefuture.Theymaybeastepupfromadvisers’traditional‘rulesofthumb’intheirfinancialplanningbuttheyact asnopanacea.Thesemodelscanonlyeverapproximatethelikelybehaviouroffinancialproductsandcanonly actasaguide.Careshouldbetakentoensurethattheydonotcreateafalsesenseofsecurityforadvisersandtheirclients.

• Anumberofthemodelsassumethatreturnsarenormallydistributedandthatcorrelationcoefficientsremainconstant.Empiricalevidencedemonstratesthattheseassumptionsarefalse.Asaresult,theunderlyingrisksdescribedbysomeSAAmodelsmaynotbefullyrepresentedandcaremayberequiredininterpreting theoutputsofsomemodels.


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2. Aim of Paper


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ToreviewtheSAAmodelscurrentlywidelyusedby retailadvisersandtohelpadvisersunderstandtheoptionsavailable,whatdifferentiatestheproductsandtohelp adviserfirmsidentifywhichproductmaybestsuittheir clients’requirements.

ToquotefromtheFSA’s2011GuidancePaper ‘AssessingSuitability’:

“Ifafirmusesathird-partytooltohelpmakesuitabilityassessmentsfortheircustomers,weexpectthatfirmto:

• ensure that the tool is suitable for use with its customer base;

• understandhowthetoolworks,soitcan interpretandevaluatetheresultswhenitis appliedtoindividualcustomers;

• understandtowhatextentthetoolwillhelpmeet its regulatory requirements;

• have a robust process to mitigate shortcomings orlimitationsofthetool;and

• whereatool(suchasanasset-allocationorfund-selectiontool)suggestsinvestmentselections,tounderstandtheproduct,marketandassetrisksfortheseinvestments.”

Weexpectthispapertohelpadviserfirmsmeet theserequirements.

Scope of Paper This paper focuses on the main strategic asset allocation toolsthatareavailableintheadvisermarket.Thesetoolssitwithinawidersetofadvisertoolsthatareusedintheplanningprocess.Thiswidersetcanbesummarisedas:

AttitudetoriskprofilingtoolsareoftenusedinconjunctionwiththeSAAmodelsandthetwomainproviders,OxfordRiskandFinaMetricaarebrieflyconsideredintheappendix.

Risk Profiling Tools

Risk Mapping Tools

Strategic Asset Allocation

Goal Validation


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3. The Differences Between Deterministic and Stochastic Modelling Approaches


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Oneoftheimportantunderlyingdistinctionsbetweenthevariousmodelsavailableiswhethertheunderlyingmodelengineis‘deterministic’or‘stochastic’inapproach.Thewordstochasticisusedtodescribesomethinghavingarandomprobabilitydistributionorpatternthatmaybeanalysedstatisticallybutmaynotbepredictedprecisely.Put simply, a deterministic approach is likely to be simpler than a stochastic approach but is possibly less refined in the results that it generates.

Definitions Deterministic Model

• Considersafixedstateusingalimitednumber ofdefinedinputs

• Theuser/modellerselectstheinputassumptions andtheseassumptions“determine”theresults

• The results will only change if the input assumptions (ortheequationsinsidethemodel)arechanged

Stochastic Model

• Anelementofrandomnessisintroducedwithinthe model.Thereforeeachtimethemodelisrun,adifferentresultisgenerated.Thesemodelscanberunnumeroustimesandtheresultscanbeaveragedtoproducea‘steadystate’(whererunningthemodelfurthermakesnegligibleimpactontheresults).Suchmodelsproduce arangeofoutcomesthatcanbeusedtoanalyseand tocomputearangeoflikelyoutcomes.

• Stochasticmodelscaninvolvesimulatingmultiplescenarios.Monte-Carlo(MC)simulationtechniques canbeusedtogenerateverylargenumbersof scenariosinordertounderstandthepotential behaviouroffinancialproductsinadiverserange ofpossiblefinancialconditions.

• Stochasticmodelsmaybe‘termcentric’.Thisisperhapsbestexplainedviaanexample:

I. Investingwithatwo-yearhorizon,ashorttermgilt-edgedstrategywillprovideaverycertainoutcome.Alternativelyanequitystrategywillgenerateahighlyuncertainoutcome.

II. Investingwithatwentyyearperiod,aninvestmentstrategyfocusingonshortdatedgilts will have a higher level of uncertainty attached.Conversely,anequitystrategywillproduceamorecertainoutcomesincestockmarketreturnsaremorereliableover 20yearperiods.

Deterministicmodelsaregenerallysimplerandarelikely toassumethatoutcomesarenormallydistributed[seetailrisks].Stochasticmodelsbetterdealwiththeuncertaintythatisprevalentinfinancialmarkets.Suchmodelscanincorporateboththelikelihoodofaneventoccurring,thetimingimpact ontheportfolioandthemagnitudeoftheimpactthattheeventcreates.

Arguably,astochasticmodelmayprovideabetterapproximationoftheoutcomesthanadeterministicapproach,althoughamoreimportantfactorinfluencingtheresultsmaybethequalityofthecapitalmarketassumptionssupportingthemodelandtheapproachtakentocalibrate themodel.


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4. Further Background


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CapitalMarketAssumptions Thecapitalmarketsassumptionsusedwithinthemodelhaveamaterialimpactontheoutputs.Atthehighestlevel,therearethreekeyvariables.

• Expectedreturns• Risk(volatility)• Covariance-describinghowoneassetperforms

in relation with another

The calculation of these variables may rest upon multiple capitalmarketassumptions,suchas,theoutlookforinterestrates,inflationrates,growthrates,exchangerates,dividendyieldsetc.

Theassumptionsdrawnwillbelargelybasedupon historicalanalysis.Adjustmentsmaybemadetoreflectcurrentvaluationsandsomemodelprovidersincorporate aqualitativeoverlay.Astochasticapproachpermitsmultiplescenarioanalysestobeincorporatedintoamodelandthesehelpstresstesttheoutputsunderdifferentconditions andassumptions.

QualityofInputs Stochasticmodelsareconstitutedusingavariety ofscenariosandarangeofdifferentassumptions.Anyfancifulassumptionsmadewithinthisarrayareunlikelytohave amaterialimpactontheoutput.

Deterministicmodelsmaybemorereliantonasingleset ofassumptions.Iftheseassumptionsprovetobeerroneous,itmayhaveamaterialimpactontheoutput.Theoldsaying ofgarbagein,garbageoutcomestomind.

Invariablythereisanecessitytostrikeabalancebetweenmakingthemodelasrealisticaspossibleandkeepingthemodelsimple.

Sensitivity of Output Thegreaternumberofassetclassesandsubassetclassesused,thegreaterthesensitivityoftheoutputtotheinputs.This will have implications on the practical application of theresultingassetallocationoutputs.Modelsconsideringawiderangeofassettypesarelikelytosufferregularandwidespreadchangestotheresultingassetallocationoutput. Aportfoliofollowingsuchmodelswillhavehighturnoverlevelsandsufferhighaggregatetransactioncostsasaresult.

A common solution to this is to limit the number of sub-asset classesmodelled.Forexample,theequitiescomponentofthemodelmaybesimplifiedintotwofactors:domesticequitiesandinternationalequities.Suchstepswillgreatlyreducethevariability of the output with only a minor compromise to the efficiencyoftheportfolio.

ModelConstraints Modelsmayberunwithvariousconstraints.Technically anyconstraintreducestheeffectivenessofamodel(thoughthe constraint may be put in place to overcome a potential weaknessintheunderlyingmodelassumptions).Forexample,propertyexposuremightbelimitedto10%toreflectthepotentialilliquidityintheassetclass.

Otherconstraints,suchasensuringthatasterling basedinvestorispredominatelyinvestedinsterlingassetsmayhelptoactasasanitychecktokeeptheoutputwithinrationalbounds.


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5. The Main Providers


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Distribution TechnologyWho they are and what they offer

Foundedin2003,DistributionTechnology(DT)isaprivatecompanylocatedinReadingandprincipallyownedbyitsfoundersanddirectors.DTisbestknownforitsDynamicPlanner(DP)software,whichisafinancialplanningtoolthathelpsadvisersprofile,planandmanagetheirclients.Around6,000advisersregularlyusethissoftware.Theirclientsincludeadvisers;assetmanagersandwealthconnectpartners,whichencompassesWrapPlatformsandLifeCompanies.

DTalsooffersrisk-profilingservicesforinvestmentfunds,whichfeedintotheirDPsoftware.Thisserviceattempts tomakeiteasierforadviserstofindfundsthatmatchinvestors’risktolerances.Currentlytheyriskratearound 800fundsfromsome80investmentorganisations.Thishasbeen a growth area for the business over the last few years withtheinvestmentcompaniespayingafeeforeachfund thatisriskrated.

WithinDynamicPlannersoftware,ariskprofilerisalsoavailable.ThishasbeenbuiltinconjunctionwithOxford Risk,withtheadviserhavingthechoiceofeithera10or 20questionversions.DTrecommendsthatthe20-questionversionbeused.DTunderstandsthatthisisonlythestart ofanyclientdiscussionandthatanadvisershouldmakefurtherinvestigationstofullyunderstandaclients’capacitytoacceptrisk.DynamicPlannerallowsanadvisertodothisthroughindividualcash-flowassessmentinaddition toshowingtheexpectedvolatility(5th,95thpercentile) ofagivenallocation.Definitionshaveallbeensignedoff bythePlainEnglishcampaign.

Their Model

DT’ssolutionsarebasedonmeanvarianceoptimisation (MVO)techniques.Usingassumptionsforexpectedreturns,volatilityandcorrelationasinputstotheMVOprocess,DTaimstoproduceoptimisedassetallocationsacrossawiderangeofriskprofiles.Thisassetallocationisreliantontheinputstothemodel.

HowevertheMVO-derivedassetallocationsarequalitativelyassessedtoensurethattheresultsarereasonableandpassacommonsensetest.Themodelsarecreatedusingbothforwardlookingandhistoricaldata;however,itismuchmoreheavilyskewedtowardsquantitativeanalysis.ThequalitativeoversightisprovidedbytheDTInvestmentCommittee (seevalidation).

Time Frame

DT’sCapitalMarketAssumptionsarebasedonalong termoutlook,althoughnoprecisetimeframeisspecified.Theyarereviewedandupdatedeachquarterasnewinformationbecomesavailable.DTdoesnotlooktocreatetacticalshorttermviewsonindividualmarketswhensettingallocationsandthereforetheirassetallocationsareseen asbeingprimarilystrategicinnature.

Underlying Capital Market Assumptions

Asof1stJanuary2015theprocessforcalculatingcorrelationshaschanged.Previouslycorrelationswerebasedondifferenttimeframes,reflectingthedifferentassetclassdatasets.Ithasnowmovedtoamoreconsistentapproach,basedonrolling15yearcorrelationsacrossallassetclasses.Thisstrikesusasamorelogicalapproach.A15yeartimeframeshouldensurestabilityofthecorrelations.

Volatilityisalsoderivedfrom15yearhistoricaldataand iscalculatedinsterling.

Expectedreturnfiguresarecalculatedusingavariety ofindexandmarketdatawithinformationfromindices beingusedfromasfarbackaspossible.Moredetailsof howthereturnexpectationforeachassetclassiscalculated isprovidedbelow.

Forinflation,DTcurrentlyassumea0.5%factorontop oftheBankofEnglandlongertermtargetof2%togiveaninflationexpectationof2.5%.Note,DTcalculateboththenominalandrealreturnexpectationforeachassetclass.


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TheInvestmentCommitteeisresponsibleforagreeing andapprovingtheCMA’sthatareproducedbytheFinancialAnalyticsTeam.

UpdatestotheCMAsareundertakenonaquarterlybasis andfinalassetallocationsaregenerallyupdatedwithinthe DPsoftwareonanannualbasis.ThisusuallygoesliveattheendofQ3eachyear,basedontheQ1CMA’s.TheQ1CMA’saresignedoffinMayandsoareasonableleadintimeisgiven.TheAll-returnfiguresarequotedgrossofmanagementfeesandtaxes. Portfolio Optimisation

Theexpectedreturn,riskandcorrelationfiguresarethen fedintoanoptimiser(covariancematrix),whichcreatesasetofportfolios,whichfallclosetothemidpointforeachofthe10riskprofilesalongtheefficientfrontier.

Asetofassetclassconstraintsisthenoverlaid. Theconstraintsarelistedbelow:

1. Portfolio1is100%cashfornominalcapitalpreservationpurposes.

Asset Class Return Assumptions

Cash Interpolated2.5%yieldon5-15yearindexlinkedgilts.

Conventional Gilts BarclaysAllMaturityGiltsindexgrossredemptionyield.

IndexLinkedGilts Interpolated2.5%yieldbasedonAllUKindexlinkedgilts.

UKcorporatebonds iBoxxCorporateBondindexyieldandanallowanceforthedefaultriskpremium(0.2%currently).

InternationalBonds BoAMerrillLynchGlobalBondMarketIndexyields.ThisislargelyUSTreasuries, UKGiltsandGermanBunds.

GlobalHighYieldBondsBarCapGlobalHighYieldBondIndexyieldandanallowancefordefaultprobability (1.7%currently).

EquitiesAllgeographicalequityregionsusetheMSCIindicesforreturnexpectations.Inputstothefinalfiguresincludeanappreciationoftheearningsyieldviathepayoutratio,dividendyieldandGDPforecastsplusinflationforeachregion,basedonconsensusforecasts.

Property ExcessreturnofIPDindexovergilts.

Commodities InlinewiththeglobalgrowthforecastfromtheIMF.

HedgeFunds RiskPremiumoverGilts(around1.2%).

2. Theminimumallocationperassetclasswhenutilisedintheportfoliois5%.Thereisnomaximumallocationperassetclass,otherthanproperty,whichshallnotexceed10%inanyallocation,reflectingitspotentialilliquidity.

3. Assetclasschangeswillnotgenerallyexceed5%betweenperiods,althoughthecommitteereservestherighttoexceedthisinextremecircumstances.

4. Portfolios3to7representthemostdiversifiedandwellusedportfolios.Theywillbeconstitutedusingatleasttwobroadassetclasses.Abroadassetclassisconsidered:Cash,Equity,BondorProperty.

5. Portfolios8to10arethehighestriskportfoliosandwillbedominatedbyequityassets.

6. Thereshouldbeasmoothprogressionacrossthebroadassetclasssplitastheriskparametersincrease.Forexample,theyexpectatransitionfromapredominanceofbondstohigherequityweightings.

7. Thechangeinefficiency(expectedreturnperunitofrisk)fromtheunconstrainedtotheproposedallocationwillbeminimali.e.theportfoliosshouldcontinuetositonorveryclosetotheefficientfrontier.


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TheInvestmentCommitteehassomediscretionon howtheseconstraintsareapplied.Whenapplyingtheseconstraints,theCommitteeissensitivetotherequirementssetoutbytheunconstrainedmodelandanyrevisionsmadewillbeconsistentwiththeunconstrainedmodel.

Validation

TheprimaryroleoftheInvestmentCommitteeistoensuretheconsistencyofthemodelsonanongoingbasisbybringingamorequalitativeapproachtotheprocessandensuringanumberofconstraintsarereferenced.Detailsofthecurrentmembers of the committee are as follows:

Chris Fleming (Chairman)-Chrisisthehead ofDistributionTechnology’sFinancialAnalyticsTeam andmemberoftheExecutiveManagementTeam.HejoinedDistributionTechnologyfromAonHewittinMarch2012wherehewasaseniorinvestmentconsultantprovidingadvicetotheTrusteesoflargeUKpensionschemes.Thisinvolvedrecommendingassetallocationsandtheappropriatefundmanagerinthecontextoftheprevalentmarketconditions,whilstconsideringascheme’suniquecircumstances.Priortothis,ChrisspentfouryearswithDeutscheAssetManagement,whereheheldaroleinfundanalysis.ChrisholdsadegreeinMathematicsfromtheUniversityofCanterbury,NewZealandandhascompletedtheCharteredFinancialAnalyst(CFA)andtheInvestmentManagementCertificate(IMC)qualifications.

Clive Hale-CliveisanexternalCommitteememberandhasover30yearsofexperienceincludingInvestmentDirectorandChiefInvestmentOfficerrolesatseveralleadingorganisations,suchasTowryandSkandiaInvestmentGroup.Heiscurrentlya partner at the Albemarle Street Partners LLP as well as directorofFundCalibire.

Jim Henning-JimholdsaBSCinEconomicsfromtheUniversityofBirminghamandholdstheInvestmentManagementCertificate.Jimhasaccumulatedover25years’experience specialising in investment platform proposition design,fundgovernancemechanismsandpromotionalsupport.Thishasencompassedawidevarietyofroles,mostrecentlyintheoffshoreinvestmentmarketforFriendsProvidentInternational(FPI).

Chris Brooks -ChrisisProfessorofFinance,DeputyHeadofSchoolandDirectorofResearchattheICMACentre.HewasformerlyProfessorofFinanceattheCassBusinessSchool,London.HeholdsaPhDandaBAinEconomicsandEconometrics,bothfromtheUniversityofReading.Hisareasofresearchinterestincludeassetpricing,fundmanagement,behaviouralfinance,financialhistory,andeconometricanalysisandmodellinginfinanceandrealestate.Chrisacts asconsultantforvariousbanks,corporationsandprofessionalbodiesinthefieldsoffinance,realestate,andeconometrics.HeisCourseConvenoroftheSecurities,FuturesandOptions,andIntroductoryFinancemodulesandalsoteachesonthePhDprogramme.

Jason Dewar - Jason has over 25 years investment experiencehavingheldpositionsatZurich,AEGON,MarlboroughInvestmentManagersandPrudential.PriortojoiningDTinAugust2015hewasheadofResearchandTechnicalServicesatSesameBankhallGroupmanaging ateamof11peopledeliveringfund,platformandDiscretionaryFundManagementresearch.

Graham Bentley -Grahamisthesecondexternalcommitteemember who has a wealth of experience in the investment industryhavingworkedatHenderson,M&GInvestmentsandOldMutual.Grahamisfounderandmanagingdirectorofgbi2,whoadvisesassetmanagers,distributorsandadvisersonInvestmentPropositionformation,AssetManagementMarketingandDistributionStrategy,anInvestmenttraining.AswellasbeingontheInvestmentCommittee,GrahamisalsoontheadvisoryboardatDT,aswellastheadvisoryboardsofHilbertInvestmentSolutionsandAlexanderBeardGroup. Overthelast12months,RajHallen,BarryMillerandPareshShahhaveleftthecommitteewhileJasonDewarandGrahamBentleyhavejoined.


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ThetwoassetclassesinitalicsarenotincludedasstandardintheDTmodelsbutareavailableforadviserstoaddshouldtheywish.*addedinQ12015

Asset Classes

WithinDynamicPlannerthestandardassetallocationcovers15-assetclassCMAs.Ofthese15,13areincludedinthe10Models.

Asset Class Index Inception Date

Cash BankofEngland,MonthlyAverageofUKbanksbaserates Jan1978

UKGilts BarclaysCapitalUKGovernmentAllMaturitiesGiltIndex Dec1980

UKIndexLinkedGilts BarclaysCapitalUKGovernmentInflationLinkedBondIndex May1981

UKCorporateBonds iBoxx£CorporateIndex Dec1997

InternationalBonds BoAMerrillLynchGlobalBroadMarketIndex Dec1996

GlobalHighYieldBonds* BarclaysGlobalHighYieldIndex June1990

UKEquity MSCIUKTotalReturnIndex Dec1969

EuropeexUKEquity MSCIEurope(exUK)TotalReturnIndex Dec1969

NorthAmericanEquity MSCINorthAmericaTotalReturnIndex Dec1969

Japanese Equity MSCIJapanTotalReturnIndex Dec1969

PacificexJapanEquity MSCIPacific(exJapan)TotalReturnIndex Dec1969

EmergingMarketEquity MSCIEmergingMarketsTotalReturnIndex Dec1987

UKCommercialProperty IPDUKMonthlyPropertyIndex Dec1986

Commodities S&P GSCI Total Return Index Jan 1970

Hedge Funds HFRI Fund Weighted Composite Index Dec 1989

AnumberofotherCMA’sarealsocalculatedbyDTwhichsitoutsideofDynamicPlannerandareusedwithclientsonamorebespokebasis.Theseinclude,inadditiontotheabove,UKEquitySmallCap,UKEquityMidCap,UKEquityLargeCap,EuropeexUKEquitySmallCap,EuropeExUKEquityMidCap,EuropeExUKEquityLargeCap,NorthAmericanEquitySmallCap,NorthAmericanEquityMidCap,NorthAmericanEquityLargeCap,JapaneseEquitySmallCap,JapaneseEquityMidCap,JapaneseEquityLargeCap,UKGiltShortDuration,UKGiltMidDuration,UKGiltLongDuration,UKIndexLinkedGiltsShortDuration,UKIndexLinkedGiltsMidDuration,UKIndexLinkedGiltsLongDuration,GlobalInvestmentGradeBonds,

GlobalInvestmentGradeSovereignBonds,GlobalInvestmentGradeCorporateBonds,GlobalHighYieldSovereignBonds,GlobalHighYieldCorporateBonds.EmergingMarketBonds.Theseareallcalculatedonasimilarbasishoweversomeoftheindicesdonothaveparticularlylongtrackrecords.

What is the experience and resources of the team?

Financial Analytic Team – The team currently consists of7individualsfromanarrayofacademicandmarketbackgroundsincludingactuaries,PhDgraduatesandstrongfinancedbaseddegrees.


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What services are offered as standard?

WithinDynamicPlannerCMA’sforeach ofthe15assetclasses.Theseareupdatedonaquarterlybasis.Theassetallocationisupdatedonanannualbasis.Ariskprofilesummaryisalsogeneratedwhichprovides forecasting in terms of probability of returns basedonthetargetassetallocation. Performance

DThaveprovideduswiththereturns andstandarddeviationsoftheir10riskprofilesover3yearand5yearperiodsaswellassinceinception(31/08/2005)to31stAugust2016(seegraphs).ThereturnsdonotassumeanOCFhasbeenappliedandfortheDTportfolios,theallocationtoeachassetclasshasbeeninvestedintheindicesmentionedinthetableabove.

16.0%14.0%12.0%10.0%8.0%6.0%4.0%2.0%0.0%0.0%

2.0%

4.0%

Perf

orm

ance

(% p

.a.)

Volatility (% p.a.)

DT 10 Portfolios Risk and Reward, 3 Years (p.a.) to 31st August 2016

6.0%

8.0%

10.0%

12.0%

18.0%16.0%14.0%12.0%10.0%8.0%6.0%4.0%2.0%0.0%0.0%

2.0%

4.0%

Perf

orm

ance

(% p

.a.)

Volatility (% p.a.)

DT 10 Portfolios Risk and Reward, 5 Years (p.a.) to 31st August 2016

6.0%

8.0%

10.0%

12.0%

20.0%18.0%16.0%14.0%12.0%10.0%8.0%6.0%4.0%2.0%0.0%0.0%

2.0%

4.0%

Perf

orm

ance

(% p

.a.)

Volatility (% p.a.)

DT 10 Portfolios Risk and Reward, 31/08/05 - 31/08/16

6.0%

8.0%

10.0%

12.0%

Source: Distribution Technology SinceInception:31stAugust2005


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EValue Who they are and what they offer

EValueprovideanalysis,forecastingandplanningtoolstoenableadvisersandconsumerstounderstandthepotentialriskandreturnfromdifferentinvestmentchoices.EValue’soriginsstartin1993whenTowersPerrincreatedaglobaleconomicmodelthatgeneratedstatisticalforecastsforfutureinvestmentreturns.FollowingthemergerofTowersPerrinandWatsonWyattin2010,EValuewasformedusingtheTowersPerrinmodel.ThebusinessnowoperatesasanassociatecompanyofFinancialExpress.

EValueclaimthatmorethan90%ofUKproductprovidersandbanksandover50%oftheadvisermarkethaveaccesstotheirtoolsandsolutions.Thisequatesto15,000advisersand250,000consumers.ThesesolutionsareprovidedtoAccenture,Aviva,Axa,BBC,BlackRock,GE,HSBC,IrishLife,Legal&General,Lloyds,RBS,StandardLife,Santander,ScottishWidowsandZurich.HoweverEValueultimatelyseetheirendconsumerbeingprivateinvestorsmakingdecisionson long-term investments through collective investment schemes.

AdvisaCentaisEValue’sadvisoryofferingwhichprovidesariskprofilersolutionthroughthreestandardquestionnaires,whichmeettherequirementsofdifferentdistributionchannels.AdvisaCentaalsooffersfinancialplanningtoolsfordifferentinvestorcircumstances,aswellas,portfolioanalysisandfundriskassessment. Thesuiteoftoolsincludes:

• RiskProfiler–apsychometricquestionnairethat’sallowsassessmentofaclients’attitudetoinvestmentrisk.

• InvestmentPlanner–amodulethatcomparespotentialoutcomesovertimefromthedifferentinvestmentstrategiesavailable;graphicallyillustratingthetrade-offsbetweenriskandrewardbasedontheproposedamounttobeinvestedandthespecificgoalsoutlinedbythecustomer.

• RetirementPlanner – helps communicate the potential sizeoftheclient’sretirementpotbasedonhis/herpensionandinvestmentarrangements.Thetoolhelpsshowaholisticretirementplanandshowsthechanceofreaching an income target given the levels of investments andcontributions.

• Protection Planner–enablesadviserstoquicklyseetheimpactofprovidingprotectionforaclient’scashflowneeds.Keyfactorssuchasdebts,assetsandexistingcovercanbetakenintoaccount.

• Lifetime Planner–helpsadvisersandclientsreviewtheirfinancialpositionthroughoutlife.

• Portfolio Optimiser–enablesadviserstoanalyseclientsexistingassetsataproductandfundleveltakingintoaccountfundperformance,theclientsriskprofile,chargesandtaxationallowingrecommendationofdifferentproductsolutions,ifappropriate.

• AtRetirement–helpsadvisersrecommendincomestrategiesfortheirclientsatthepointofandintoretirement.

• PensionsFreedomPlanner–specificallydesignedtofocusonpensionsfreedomsandtheoptionsnowavailabletoconsumers

• FundsRiskAssessor–Supportstherecommendationsofindividualfundstakingintoaccounttheclientsoverallportfoliotoensuretheyarealignedtotheclients’riskprofile.

Their Model EValue’ssolutionsarebasedonastochasticapproach, whichmodelsarangeofpossibleoutcomesforaninvestmentproposition.EValueusetheirowneconomicscenariogenerator(ESG)model,Insight,whichreflectsbothshortandlong-termforecastsinitsoutputs.InsightgeneratesfuturescenariosratherthanusinghistoricaldataandasimpleMVCmodel to illustrate how an investment strategy or asset will perform inthefuture.TheESGisbuilttobeself-consistentandforbothassetallocationandprojection.Self-consistencymeansthatupdatesareconsistentwithmarketdevelopmentsandeconomicchangesovertimeandresponsesmatchthoseassumedinthemodel.

EValuerunsapproximately10,000scenariostoestablish theirkeyassetallocationsandasubsetof1,000scenarios areusedforthecalculationsintheon-lineplanningtools.

EValue’sstochasticassetmodelisbasedondatafromeachmajoreconomicmarketcurrentlycoveringtheUK,Japan,the US,theEurozone,Asia-PacificexJapanandEmergingMarkets.Itisdesignedtoproviderealisticsimulationsofcurrenciesensuringthattheriskofinvestmentsheldinothercurrencies isnotunderstated.

EValueclaimtofollowasystematicandquantitativeupdateprocesswithintheirmodelwhichminimisesanydiscretionthey


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exerciseduringupdates.Themodelisupdatedquarterlytoensureassetallocationsremainuptodate.Additionalreviewsoftheassetmodelmayalsobeconsideredifmarketconditionshavechangedtosuchanextentthatsignificantportfoliochangesarelikely.Forexample,followingtherecentBrexitvote,EValuecarriedoutanacceleratedupdateofitsassetallocationsandoptimumportfoliostoreflectthechangedeconomicconditions,inparticularreducingyieldsonGovernmentbonds.

Time Frame

EValueuse4,8,13,18and25yearsasaproxyforarangeofinvestmentperiods.Theseareapplicabletoinvestmentperiodsof3-5,6-10,11-15,16–20and21+yearsrespectively.Themodelwillbeupdatedonaquarterlybasisandportfoliosareassumedtoberebalancedonayearlybasis.

EValue’smodelisbasedontheprinciplethatthelong run behavior of an asset class will be in line with its historic behaviour.Theselongrunconditionsreverttoafixedterm,whichisreferredtoasa“steadystate”.However,atanyonetime,returnscanbequitedifferentfromthoseinthe“steadystate”andthesedependheavilyonmarketconditions.Ingeneral,therateofreturndriftsbacktothe“steadystate”buttherateatwhichitdoessovariesandsometimesitcanbeveryslow.EValuewilldeterminethe“steadystate”throughempiricalanalysisanditwillnotchangeuntilitisrevisited.

EValuecommentedthat“thereisatrendtowardsasteadystateinthelongertermbutsincethemodelisarealworldeconomicscenariogenerator,thescenarioswemodelwill notnecessarilyeverreachtheselongtermassumptions. Weseeatrendoveraround20yearswherethoselonger termsituationstendtosettledown.Youshouldnote,however,thatauniquefeatureofourassetmodelisthat,unlikeothereconomicscenariogenerators,wedonot assumethatnormalitywillresumeintheshortterm.Forexample,allUKpre-creditcrunchESGmodelswillassume thatlowyieldswillrevertwithinaround5yearsto‘normality’.Giventhisnotonlyunderestimatesbutcompletelyignores thepossibilityoflongtermlowyieldssuchasinJapan,wehavereviewedandrevisedourmodeltoensurethatthis iscorrectlytakenintoaccount.”

Underlying Capital Market Assumptions

Thestructureofthemodelbeginswiththemodelling ofinterestrates,asEValuebelievetheyhaveadirectimpactoncashandfixedincomereturns,whileallotherassetclasseshavesomedependencyoninterestrates.Forexamplewheninterestratesarehigh,itisexpectedthatgrowthrateswillbehigher,whichimpactsequitydividendgrowthratesandpropertyrentgrowthrates.

EValueemployasmuchhistoricdataaspossible,andmanycasesthiswillgobacktotheendofWorldWarII.EValuewillsimulatescenarios,whichareindividuallyrealistic.

TheEValueassetmodelincludesmodelsofthetermstructureofUK,US,EurozoneandJapanesegovernmentbondyields.Inordertoproviderealisticforecastsoftherisksinherentwithininternationalgovernmentbondportfolios,EValue’sassetmodeltakesintoaccounttheinternationaldependencestructureofinterestrates.Thisisachievedbymodellingcommonfactorsdrivingthesingle-economyresiduals.

TheEValuemodelalsoincorporatespriceinflation,whichisusedtocalculatereturnsonrealassetandinflation-linkedbonds.Asaresult,themodeltakesintoaccountlong-termexpectationsoninflation.

TheEValueequitymodeldescribesthejointreal-worlddynamicsofthemajorequitymarkets,whichcoverstheUK,US,Eurozone,Japan,Asia-PacificexJapanandEmergingMarkets.Theequitymodelprojectscrediblelevelsofrisk,for instance by attaching a realistic probability of a large short-termloss,aswellasmodelingtherealisticlevelsoffuturereturns.Theseassumptionsarederivedfromhistoricobservations,sothatafteraperiodofrisingequityvaluations,futureexpectedreturnsarelower.Themodelalsoproducesassetallocations,whicharecounter-cyclicalwithrespecttoequity“bubbles”.Thereforetheoptimalassetallocationwillshiftawayfromequitymarketsthathavebecomeovervaluedandtowardsequitymarketsthatareunder-valued.Toensurethatthereductioninriskduetointernationaldiversificationismodelledaccurately,themodelwillincorporateaninternationaldependencebetweendividendyields,growthratesandvolatilityindifferenteconomies.


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Themodelalsoconsidersunhedgedinvestments inforeignassets,byprovidingrealisticsimulationsofcurrencies,toensurethattheriskofinvestmentsdenominatedinothercurrenciesisnotunderstated. Themodel,whichobeysuncoveredinterestrateparity, alsoincorporatesadependencestructurebetween ifferentcurrencies,toensurethattheriskofinternationallydiversifiedportfolioscanbeaccuratelyforecasted.

TheEValuecorporatebondmodelisdesignedtoaccuratelyreflectthepropertiesofatypicalcorporatebondfundwith acreditratingof“A”.Commoditiesaremodelledlikeanequitywithoutadividendyield.Thepropertymodelassumesthatforcurrentinterestrates,valuationsintermsofrentalyieldwilltendtoreverttothesteady-statelevelgivenbythecurrentcostofmortgagefinance. Validation

Theoverallleveloftheequityriskpremiumischosentobeconsistentwitharangeofacademicandmarketconsensusestimates,includingthePricewaterhouseCoopersreportcommissionedbytheFCA.

Team EValuecurrentlyemploy60people,whichincludes ateamof6actuariesandPhDswhoworkonupdating andmaintainingthemodel.

EValueoperatesonanindependentbasisasanassociatecompanyofFinancialExpresswhoacquiredasignificantequitystakein2011fromTowersWatson.EValuecommentedthat“strongrelationsremaininplacebetweenEValueandTowersWatson,withthesamemanagementteamand EValueemployeesretainedtodrivethenextstageofthe ompany’sdevelopment”.

Asset Class EValuehavemodelsforover60assetclassesin4currenciesandcanextendthatrangesystematically.Fortheirstandardallocationstheyhaveusedthefollowingassetclasses:

• UKMoneyMarket• UKGovernmentBond• UKCorporateBond• UKIndexLinkedBond• UKEquity

• USEquity• European Equity• Japanese Equity • EmergingMarketEquity• UKProperty

Forpracticalpurposes,EValuebelievethatitissensible forassetallocationtoberelativelystableovertimeandnottobeundulyaffectedbysmallchangeseachquarter.Assets,whichhavesimilarpropertiesandarestronglycorrelated,maypromptrelativelylargechangesintheproposedportfolio.Asaresult,EValuegroupcertainassetsinordertoreducethesensitivityoftheoutputandtoreduceturnoverinportfolios.Forexamplefortheirstandardallocations,developedmarketequitieshavebeengroupedtogetherandassumethefollowingstaticratios:65%USEquity,20%EuropeanEquityand15%JapaneseEquity.

Portfolio Optimisation

Taxisnottakenintoaccountintheportfolio optimisation,butforthecalculationofassetallocations,EValueincludechargesthatarelevieddirectlyoneach asset class but not charges that apply to the investmentproductasawhole.Thereforetheyrepresentfundchargesbutnotproductcharges.

Theresultofaproposedassetallocationmaynotbedesirableorachievableforpracticablepurposes. Hence,toensureaportfoliohasareasonablelevel ofliquidityanddiversification,constraintstotheportfolio canbeimposed.Forexample,foreachassetclasstheminimum weighting as a percentage of the portfolio can besetatzero,toavoidshortselling.Alternatively,amaximumweightingof10%canbeappliedtoavoidhighallocations toilliquidassetclassessuchasProperty.

Funds Risk Assessor

EValuewillmaptheriskprofileofafundoraportfoliooffunds,andwilldosobyobjectivelyassessingthedegreeofinvestmentmarketriskbyanalyzingtheunderlyingassetallocation.Thisensuresthatnosubjectivejudgmentismade.EValuehaveadoptedthisapproachastheywanttolookintothefutureandnotthepast.Theybelievethatanalysingafund’spastperformancecanbemisleading.Afundthathasasteadyreturnisnotnecessarilylowrisk.EValuealsoclaimtobeabletomapanynumberofriskcategoriesoruseanybenchmarkallocation.


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Risk Targets EValueusevolatilitybaseduponthestandarddeviation ofthelogarithmofthefinalportfoliovalue,todetermineriskandsetrisktargets[seeappendixfortherationalebehind thisapproach].Thelevelsofrisktargetsaresetatregularintervalsonthevolatilityscaletoprovideasensiblerange ofoutcomestomeetinvestorrequirements.(Notethattheriskstargetswillchangewitheachquarterlycalibration). Thecurrentbenchmarkportfoliosstatethelowestriskcategoryisaportfolioof100%cashwhilethehighestriskcategoryisaportfolioof100%UKequities.


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Moody’sAnalytics(MA)–FormerlyknownasBarrie & Hibbert Who they are and what they offer

Moody’sAnalyticsofferanumberofservicesincludingInvestment,RiskManagementandWorkforceSolutions.WithintheInvestmentSolutionsarenatheyarealeadingproviderofinvestmentresearchandanalyticsfordebtcapitalmarketsandriskmanagementprofessionals.AstheexclusivedistributorofallcontentproducedbyMoody’sInvestorsServiceanddeveloperofthemarket-leadingEDFTM(ExpectedDefaultFrequency)creditmeasures,theyprovidethemarketwithinformationandtoolsthatsupportbetterdecisionmaking.Thescopeoftheirexpertiserangesfromcreditresearchtomacroeconomicforecastsandstructuredmarkets.

Moody’shaverelationshipswithalargenumberoffinancialinstitutionstoprovideriskmanagementservicesforthebusiness,aswellaswithintheirretailproductarea,thisincludesStandardLifeandLloyds.Theyofferafullend-to-endpropositionforproductproviders,distributorsandadviserstohelpdevelopinvestmentpropositionsinlinewithnewregulations.Theservicecombinessolutionsforattitudetoriskandfinancialprojectionwithinaninvestmentgovernanceframeworkthatallowsevaluation,monitoringandreviewoftheriskandreturnofinvestmentsolutions.Itdoesthisbyusingaseriesofquantitativeandindependentlyvalidatedriskmetrics.

Moody’sbelievethatinvestmentsolutionsshould bespecificallytailoredtomeettherequirementsofthe clientandtheirinvestmentcustomers.Theyhavedevelopedananalyticalframeworkthatsupportsthedesignandgovernanceofinvestmentsolutions,configuredtothedesiredinvestmentoutcomesandrisktargetsforeachclient.Moody’sdonotbelieveitisappropriatetoofferastandardsetof“offtheshelf”riskgradesorSAAs.Oncetheyhaveestablishedthedesiredoutcomesandrisktargets,theyusethecashflowprojectionengine,theWealthScenarioGenerator,toidentifysuitableinvestmentsolutions,andtoillustrateinvestmentoutcomesinrelationtoclientneeds.Moody’sAnalyticseconomicandcapitalmarketmodellingplatform,orEconomicScenarioGenerator(ESG),sitsatthecoreofalltheirproductsandservices.Moody’semployalargeteamofspecialists,builtupoverthelast20years,whichisdedicatedtotheresearch &development,maintenanceandregularre-calibration oftheESG.

History

Barrie&Hibbert(B&H)wasacquiredbytheMoody’sCorporationin2011andformspartoftheMoody’sAnalyticsEnterpriseRiskManagementsolutions.TheacquisitionbroadensMoody’sAnalyticssuiteofsoftwaresolutions fortheinsuranceandpensionsectors.

Thebusinessdatesbackto1995,whenAndrewBarrie andJohnHibbertstartedasconsultantstohelpcompaniesmanagemarketrisk.Overthenexteightyears,B&Hundertookawiderangeofclientengagementsandresearchsupportingthedevelopmentofadiversearrayofmodels.Detailsofsignificantmilestonesarebelow:

1995 Firstclientengagementsinformingmodel developmentandresearch

1996 Regime-switchingequitymodel1997 Fullyieldcurvemodelforactuarialuse1998 FTSEoption-implieddistributions1999 Stochasticvolatilitymodel2000 Corporatebondmodel2000 LaunchofDecisionAnalyserToolbox(DAT)cashflow

engineforfinancialplanning2001 Stochasticmortalitymodel,firstclientsusing

stochasticmodellinginfinancialplanningtools2002 Equitymean-reversionmodel2003 FirststandaloneEconomicScenarioGenerator

(ESG)launched2004 TwoFactorBlack-Karasinskimodelforinterestrates2007 ExtendedTwo-FactorBlack-Karasinskimodelfor

interest rates2008 FullStochasticVolatilityJumpDiffusionEquitymodel2009 Time-varyingtermpremiumintroducedtoTwo-

FactorBlack-Karasinskimodelforinterestrates2011 Secondgenerationcreditandcorporatebondmodel2012 DynamicEquilibriumcalibrationdesignedfor

StrategicAssetAllocationandOptimisation2013 Enhancementofstandardmulti-year“BestViews”

calibrationforassetportfolioprojection2014 LaunchofWealthScenarioGeneratorproductand

cashflowengineforretirementplanning

Withmorethan150customersaroundtheworld,the ESGiswidelyrecognizedasanindustrystandardforvaluinginsuranceassetsandliabilities.BasedinEdinburgh,theyexpandedintoAmericain2007withanofficeinNewYork andintoAsiain2009withanofficeinHongKong.


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MAhasexpandedbeyondlifeinsurance,applyingitsexpertisetoassetmanagement,retaildistribution,pensions,andProperty&Casualtyinsurance.Theirmodelsarenowintegratedintoenterpriseriskmanagementplatforms,consumeradvicetoolsandvaluationprocessesaroundtheworld.ItisestimatedthatintheUKalone,70%ofinsurersrelyontheirmodels.Around30UKproductprovidersandassetmanagershaverisk-gradedinvestmentpropositions,whicharesupportedbyMoody’sinvestmentgovernanceservicesincludingStandardLife(Myfolio),RoyalLondon(GlobalMultiAssetPortfolios)andIntrinsic(CiriliumFunds).

The Model

Themodellooksat40economiesacrossvariousfundamentalsincludinginterestrates,inflation,currenciesandassetpriceprojections.Themainchangesaregenerallytointerestratesandimpliedvolatility.Themodelisupdatedquarterly,andaftereachupdateassumptionsaretestedbeforemodelsgolivetoensuretheyadequatelyreflecttheviewsoftheteam.Anychangestothemodels,alongwithanexplanation,areprovidedwithclearrationale.

Themodelisintegratedwithassetpriceandeconomic riskfactordynamics.Itcapturesfundamentalfinancialeconomicdynamicsandrelationshipsandensureseconomicallycoherentprojectionsforpathsofassetprices,inflationandinterestrates.Itprovidesforward-lookingprojectionsconsistentwithcurrenteconomicconditions, incontrasttoanumberofmodelswheresimple distributionsarefittedtohistoricassetreturndata

Importantlythemodelcapturescomplexmarketfeatureswhichimpactclientoutcomesforexamplemarketfattails,time-varyingvolatility,taildependence,realisticyieldcurvebehaviourimpactingassetprices,cashflowsandclientoutcomes.TheirStochasticVolatilityJumpDiffusionmodel isdesignedspecificallytoincorporatescenarioswherevolatilitiesandcorrelationsincreasesignificantlyabove the‘average’levels.

Asset and Modeling Coverage

TheMAEconomicScenarioGeneratorcanproject awiderangeofassetsandriskfactors,including:

• Equityindices• Nominalandrealinterestrates• Nominalandindex-linkedbonds

• Inflation(RPI,CPI,wages,)• Exchange rates• Realestateandalternativeassets(hedgefunds,private

equity,commodities)• Creditspreadsandcreditriskybonds(financialandnon-

financialcorporatebonds,sovereignbonds)• Municipalbonds• Structuredproducts(MBSetc)• Derivatives(options,swaps,forwards)• Impliedvolatilities• Multi-assetportfolios(witharangeofrebalancingoptions)

TheMAEconomicScenarioGeneratorincludesarange ofmodelingoptionsforthemajorrisksandassettypes.Typicallytheywillrunbetween1000and5000scenarios.Theymaintainstandardcalibrationtointerestrates,inflation,creditriskandawiderangeofrelatedassetprices(includingequities,fixedincome,realestateandarangeofalternativeassets)across31globaleconomies.

Whereamorebespokecalibrationsolutionoradditionalassetsarerequired,clientsmaychoosethebestmodelfortheirrequirementsconsideringthenatureoftheirliabilitiesandthesophisticationlevelofusers.Examplesofthevariousmodelsincludeconstantvolatility;creditandequitymeanreversion,amongstothers.

Optimisation

Theyprovideastandardmulti-yearrealworldcalibration ofassetmodels,specificallytosupportportfoliooptimisationandstrategicassetallocationexercises.

StrategicAssetAllocationsarecreatedforeachclient,accordingtospecificclientrequirementsinrespectof:investmentorcashflowobjectives(e.g.wealthaccumulation,retirementsaving,decumulation),assetexposurepreferencesandassetallocationconstraints.Thesestandardcalibrationsareupdatedonaquarterlybasis. Validation

Moody’soperateaquarterlyCalibrationSteeringGroup, whichhasresponsibilityforvalidatingthat,themodelcalibrationandoutputsareinlinewithexpectations,givenchangesinmarketpricesandeconomicindicators.Theyalsoassesstheimpactanymodelchangesarelikelytohaveonclient’sportfoliosandliabilities.


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Support

Clientsaresuppliedwithcalibrationreportsthatdocumentthefeaturesofthecalibration.ThisincludesarangeofinformationandvalidationsofESGoutputsincluding:

• Parameter values• Qualityoffitvs.marketortargetdata(tabular

andgraphical)• Distributionandpercentilesvalidations• Summarymethodologiesformodelsandcalibrations• Referencestotheirknowledgebaseforin-depth

documentation

Manyclientsusethesecalibrationreportsasthebasisfordiscussionswiththeirauditorsandregulators.TheoutputfromMoody’sanalyticframeworkistypicallyusedwithintheclients’owninvestmentgovernancecommittees.

Time Frame

TheMAmodelismultiperiodandsimulationscanberunoveranytimeframe.Intheirexperiencegenerally,retirementprojectionsupto50+yearshavebeenrequired,buttypicallyretailprojectionswillbemuchshorter(e.g.10years).

Underlying Capital Market Assumptions (CMAs)

Moody’smaintainastandardsetofCapitalMarketAssumptionsandusethesetoproduceastandardmodelcalibration,whichtheytermtheir“BestViewsCalibration”.Theseassumptionsandtheassociatedmodelcalibration areupdatedonaquarterlybasis.

Risk Profilers

MAworkswithanumberofriskprofilers.Theyhave astandardintegrationwithA2Risk,thebusinesswhere DavidBlakeofCassBusinessSchoolisaDirector.However,theyhavealsodevelopedassetallocations,whichhave beenintegratedwithFinaMetrica,OxfordRiskandEValue, forspecificclients.

Resources

Intermsofstaffdirectlyinvolvedinsupportingthecoremodellingplatform,andbasedinthegroupsEdinburghandLondonoffices,thistotals60plus.ThisisreinforcedbythewiderresourceofMoody’sandthecommitmenttothecontinuousdevelopmentoftheircoremodellingcapability.Furtherdetails oftheirstrengthanddepthofresourceisprovidedbelow.

Overview of Modelling Operations Number

StaffresponsibleforESGresearch,development,maintenance 63

Staffresponsibleforquarterlycalibrationupdate 15

Approx.quarterlyoperationaleffort(man-daysperquarter)todeliverquarterlycalibrationupdates 30-50

SpecialistEmployeeQualifications(relatingtothe63employeesidentifiedabove)

Actuaries(qualified) 11

Actuaries (trainee) 7

CFA(qualified) 7

CFA (trainee) 3

FRM(qualified) 5

FRM(trainee) 1

QuantitativePhDs:Maths,Physics 15

Economists(postgraduateeconomicsqualification,includingPhD) 9


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BeingpartofthewiderMoody’sAnalyticsgrouphelps thecapitalmarketsandriskmanagementprofessionalsworldwiderespondtotheevolvingmarketplacewithconfidence.Moody’sAnalyticsprovidesuniquetoolsandbestpracticesformeasuringandmanagingriskthroughexpertiseandexperienceincreditanalysis,economicresearchandfinancialriskmanagement.Aspartofthis globalanalyticsbusiness,theybenefitfromaccessto amuchbroadergroupofriskmodellingandeconomicresearchexperts,whichencompassesaround1600 creditanalystsand70economists.


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Morningstar–FormerlyIbbotson Who they are and what they offer MorningstarisaglobalindependentinvestmentresearchcompanybasedinChicago,operatingin27countries.Itcurrentlyemploys(asat30thJune2016)over4,000peopleacrossNorthAmerica,Europe,AustraliaandAsia.ManywillknowMorningstarasadataproviderwhoprovidedataonapproximately530,000investmentofferings,includingstocks,mutualfundsandsimilarvehicles,alongwithreal-timeglobalmarketdataonnearly18millionequities,indexes,futures,options,commoditiesandpreciousmetals,inadditiontoforeignexchangeandTreasurymarkets.

Howeverthecompany’sproductsandservicesalsoincludeawiderangeofinvestmentconsultingservices,suchasrisktolerancequestionnaires,assetclassmodels,capitalmarketassumptions;andfund-of-fundsservices.Itsservicesincludeassetallocation,momentumstrategies,activeandpassivestrategies,andcustomstrategies,aswellasincome,tax-efficient,alternative,targetmaturity,andrisk-basedportfolios.Theycurrentlyalsoofferassetallocationresearchandservicestomutualfundfirms,banks,financialadvisers,insurancecompanies,assetmanagers,andretirementplanprovidersintheUnitedStatesandinternationally.

TheoriginsofMorningstar’sSAAapproachgobackto1977whenRogerIbbotsonfoundedIbbotsonAssociates.Duringthe1980s,IbbotsonAssociatesmadenumerouscontributionstothefinancialindustrythrough:

• Theintroductionofbuildingblocksmethodology to forecast asset class returns

• Assetallocationandbusinessvaluationconsulting• TheintroductionoftheMean-VarianceOptimizerallowing

institutionalinvestorstoexamineriskandreturntrade-offsamongassetclasses

• Asset allocation training to investors

Overthenexttwodecades,IbbotsonAssociatescontinuedtobuilditsassetallocationexpertisethroughvariousworksincludingresearchinretirementincomeplanningandmutualfundreturns,thedevelopmentofrisktolerancequestionnairesandassetallocationmodelportfolios.Asof1stMarch2006,IbbotsonAssociates,Incbecame aMorningstarcompany.

Resources and Asset Classes Covered

Morningstarclaimthatallofthe120-investment managementteambasedinChicago,Londonand Sydneycontributetothestrategicassetallocationprocess.Morningstarhassplittheinvestmentuniverseinto12assetgroups,withteamsworkingindividuallyoneachgroup.Therearesixassetgroupswithinequities,whichareAmericas,Europe,theMiddleEastandAfrica(EMEA),AsiaPacific,GlobalSectors,EmergingMarketsandREITs/Infrastructure.TheremainingsixassetgroupsarereferredtoasFixedGroups,whichareAmericas,EMEA,AsiaPacific,G5&GlobalCredit,EmergingMarketDebtandCurrency. Valuation Driven Investing

ComparedtootherSAAproviderswhoanchortheircapitalmarketassumptionsontheexpectationofoneorafewassetclassesandthenextrapolateoutforotherassetclassesbasedontheirriskpremia.Morningstarhasadoptedacompletebottom-upapproachwithanindependentviewformedoneachassetclass.

Valuationdriveninvestingisprimarilyfocussedonsettingassumptionsastheyseekoutassetsthatareunderpricedrelativetothewidermarketandwaitforthemtoreturntofairvalue.Valuationdriveninvestingisbasedontwoclearprinciples.Firstly,thebeliefthatanassethasa“fairvalue”thatcanbeestimatedthroughcarefulanalysis.Secondly,anassetwillreturntoitsfairvalueoverthelongterm,butintheshorttermanassetmaydeviateawayfromitsfairvalue.

Withtheaboveinmind,Morningstarwillformtwosets ofassumptionsforeachassetclass;thefairreturns,which arewhataninvestorwouldexpecttoearnfromanasset classoverthelongterm,whichisindependentofcurrentmarketprices;thevaluationimpliedreturn,whichisspecific totheassetclass’currentvaluationandcouldbeexpected torevertoverthemediumtolongterm,whichtheyhavedefinedastenyears. How do they estimate an asset class’ fair value?

Morningstarhasdevelopeddifferentmethodologies forcalculatingEquitiesandFixedIncomeinstruments.


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Equities-Morningstardefinethevaluationimpliedreturn of an equity asset class by the following formula:

Valuation Implied Return = Change in valuation + Growth + Total Yield + Inflation

Changeinvaluationrepresentstheassetclass’expectedreturnbasedonitsreversiontofairvalue.Soifanassetpricewerehigherthanfairvaluewewouldexpectthepricetofallovertime.Thefairvaluecalculationsarebasedonthefollowing metrics:

• Profit margin normalisation.Profitmarginsareknown tobeameanrevertingseries,whichcreatesopportunities.Sowhenprofitmarginsareabnormallylowaninvestormaylooktobeoverweightthatassetclassandviceversawhenprofitmarginsareabnormallyhigh.

• Return to book-equity normalisation. Similar toprofitmargins,opportunitiesarecreatedwhen ROEisabnormallyhighorlow.Morningstarareaware forbothROEandprofitmargins,the“normal”level canstructurallychangedependingonthemarketinquestionandsoitrequirescontinualinvestigation.

• Cyclically adjusted price to earnings ratio (CAPE). Manyinvestorsbelievethatthepricetoearningsratio is helpful in assessing whether a price is abnormally high orlow.Howeverreal-timeearningsaretoovolatiletoassess,soalong-termearningsfigurethatisadjusted forinflationcanbemorereliable.

Morningstardeterminetheirlongrungrowthexpectationsonforecastsforbothlong-runproductivitygrowthandequitysectorcashflowgrowth.Thisisbasedonacademicresearch,whichshowedthatlong-runcorporatefundamentalgrowth isinlinewitheconomicproductivity.

Theyieldiscalculatedastheexpectedshareholderdistributionsfromdividendsandsharebuybacks.WhilstMorningstardeterminesinflationastheexpectedincrease inconsumerpriceswhichwillbereflectedinfutureequityprices.Thelong-terminflationexpectationsarebasedonseverallong-terminflationforecasts,aswellasCentral Bank’smediumtolong-termexplicitinflationtargets.

Fixed Income-Morningstardefinesthevaluationimpliedreturnofafixedincomeassetclassbythefollowingformula:

Valuation Implied Return = Income Return + Shift Return + Roll Return + Credit Migration Cost + Default Loss

Morningstardefineincomereturnastheexpectedincome tobereceivedovera10-yearperiod.Whichisthestartingyieldalongwithanexpectationforyieldstonormaliseovertimeto“fair”yield.Thefairyieldiscalculatedbyforecastinginflation,therealrateofreturn,termspreadandcreditspread.

Shiftreturnisthepricechangethatwouldberequired fortheyieldtoreverttonormallevelsovera10-yearperiod.Soifyieldswerecurrentlybelowfairvalue,thenoverthe long-termyieldswouldbeexpectedtorisecausingthe priceofthebondtofall.

Thepriceimpactofabondgettingclosertotheirmaturity andmovingfromlongertermratestoshortertermratesistherollreturn.Thedefaultlosswillbeadragontheexpectedreturnandisbasedontheestimateddefaultrisk.Finally,thecreditmigrationcostisthereturnattributabletotheimpact ofratingupgradesanddowngradesoncreditbondprices.

Morningstarbelievesthatdeterminingthefairvalue ofcurrencyisconsiderablyharderthanforequitiesand fixedincome,howevertheydon’tbelievethatit’simpossible.Themethodologyemployedisbasedonthetheorythatinthelongrun,theinflationdifferentialisthesoledriverofchangesinthespotrate.Thereforethecurrencyvaluationimpliedreturnisbasedontheinflationdifferentialbetweenthelocalcurrencyandthereferencecurrency,aswellasthe reversionofrealexchangeratestofairvalue.


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Forming an SAA

TheSAAthatisconstructedbyMorningstarisnotthe outputfromahighlysophisticatedmachinebuttheranking oftheirconvictionsandriskmanagement.Theyseek togainthelargestexposuretotheirbestideasthatare mostunderpriced,whilebuildingassetallocationsdesigned tostanduptochallenginginvestmentenvironments.

Morningstarareawarethatasimpleapproach todiversificationmaynotalwaysbethemosteffectivemethodinreducingcapitallossasthemajorityofassetscouldbeovervaluedatthesametime.Therefore,duringcertainperiodsassetclassesthatarehistoricallyuncorrelatedmayhaveacorrelationthatconvergesto1.Therefore,Morningstarlookintofuturerisks,notjusthistoric.Sobyunderstandingforwardlookingriskdrivers,Morningstarcanbuildportfolioswhichtheybelievearediversifiedforthefutureratherthanthepast.

Inadditiontovaluation,whichformsamajorpartoftheSAA,Morningstarlooktoalsounderstandmarketsentimentbetweendifferingassets.Thisallowsthemtoseehowthemarketconsensusviewsaninvestmentideatheyareconsidering.Theywouldliketogoagainsttheconsensus as that is the only way they believe they can outperform themarket.

AnimportantthingtonoteaboutMorningstar’sSAAisthatit’saslowevolvingprocessandisunlikelytoconsiderablychange.Giventhelong-termtimehorizontheydonotbelieveinconstantlychangingtheassetallocation,evenifasignificantmarketchangetakesplace.Forinstance,afterBrexit,theSAAchangedslightlywithareductionintheportfolio’sgiltallocation.However,acrosstheboardthiswasbyapproximately1-2%. Optimisation

Asdiscussedintheappendixofthisreport,assetclass returnsarenotnormallydistributedduetotheexistence offattails.ThereforeMorningstarincorporateSkewness andKurtosisintotheassetallocationprocess.Alsogiven theweaknessesinassumingthatassetclassreturnsarenormallydistributed,MorningstarbelievethattheTruncatedLevyFlight(TLF)distributionisparticularlywellsuitedforfinancialmodellingbecauseithasafinitevariance,fattailsthatempiricallybetterfitthedataanditscalesappropriatelyovertime.

Validation

Morningstarhaveformedanumberofworking groupsandsub-committeestoensurethattheassetallocationprocessisbeingadheredtoandevolving. Thecommitteesinclude:

• Global Investment Policy Committee - This over-arching committeeensuresthegroupisproducingoutcomesthatarealignedwiththecompany’sprinciplesandareinlinewithregulatorystandards.

• Regional Asset Allocation Committee - This committee utilisestheinformationfromtheworkinggroupsandsector analysis research to ensure full alignment of the assetallocationprocess.

• Global Capital Market and Asset Allocation Working Group - The group comprises of senior investment professionalsacrossNorthAmerica,EuropeandAsia.The group is responsible for the ongoing review of the firmscapitalmarketassumptionsanddevelopingnewforecastingmethodologies.

• Regional Risk Committees-Thisischairedbytheregionalmanagingdirectorandtheintentionistoensureadherencetoriskstandardsandtheregulatoryframeworkforthatregion.

• Regional Portfolio Committee-Thefinalcommitteewillprovideapeerreviewandapprovalforumfortheproposedchangestoportfolios.

Performance

Morningstarhasprovideduswiththereturnandvolatilityfiguresoffiveoftheirportfolioswhicharepurelybasedonassetallocation(seechartonnextpage).


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0.0% 4.0% 6.0% 8.0%2.0% 14.0%10.0% 12.0%0.0%

4.0%

4.0%

6.0%

8.0%

10.0%

12.0%

Perf

orm

ance

(% p

.a.)

Volatility (% p.a.)

Morningstar 5 Portfolio Risk and Reward Chart - 31/12/08 - 31/08/16 p.a.

Source:MorningstarReturnsareannualisedfrom31stDecember2008to31stAugust2016.


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Willis Towers Watson (WTW) Who they are and what they offer

WillisTowersWatson(WTW)isaUS-listedglobal professional services company that helps organisations improveperformancethrougheffectivepeople,riskandfinancialmanagement.Theoriginsofthefirm’slegacyorganisationsdatebacktothe19thcentury.WTWasan entitywasformedfollowingthemergerofWillisGroup HoldingsandTowersWatsoninJune2015.Whilein2010,TowersWatsonwasformed,asTowersPerinandWatson Wyattmerged.GloballyWTWemploys39,000associates and900withintheirinvestmentbusiness.Thebusiness advisesmorethan1,200pensionfundsandinstitutionalinvestorswhichamountstoover$2.3trillionofassets underadvisory(asat1January2015).WTWisalso responsibleforover$78.2billionofdelegatedand fiduciaryassetsworldwide(asatJune2016).

A large proportion of the WTW client base is pension funds,whileitalsohasendowments,sovereignwealthfundsandinsurancecompaniesasclients.WTWcurrentlyprovidesstrategicassetallocationtoOldMutualWealth,whichinturnisusedbyitsmulti-assetteamaswellasitswealthselectplatform.WTWhaspreviouslydesignedmodelportfolios forretailcustomersofaUKBuildingSociety.

Their Model

WTW’ssolutionsarebasedonastochasticmodelcalledStarESG*,whichmodelsarangeofpossibleoutcomesforaninvestmentportfolio.WTWhasadoptedaneconomicscenariogenerator(ESG)model,whichreflectsbothshortandlong-termforecastsinitsoutputs.

StarESGisafullycoherentandintegratedstochasticMonte-Carlogeneratorcoveringawidearrayofeconomicandfinancialriskmetricsincludinginterestrates,creditspreads,equities,property,foreignexchangeandmanyalternativeseries.MonteCarlomethodsareabroadclassofcomputationalalgorithmsthatrelyonrepeatedrandomsamplingtoobtainnumericalresults.Thesemetricsarethenusedtodeterminethefulldistributionofreturnsatone-yearandmulti-yearprojectionsforawiderangeofassets(andatbothaggregateand/orindividualsecurityleveldetail).Theassumptionsthatgointobuildingthemodelareformedusingcurrentmarketinformation,historicaldata,viewsfromotherindustryparticipantsandanelementofeconomicoverlay.

TheWTWmodelincludes“fat-tailed”distributions.Thisfeatureattemptstoensurethatperiodsofseverenegativereturnsarenotunderestimated.TheWTWnowalsoallowsforthepossibilityofnegativecashratesandbondyields.

*CurrentlyWTW’sclientsuseoutputfrom3stochasticeconomicmodelsthatcome fromlegacyconsultingorganisations.WTWisintheprocessofcombiningthesemodelsintotheSTARESGplatform.

Time Frame

WTW’smodelisamulti-periodmodel,whichcanmodelreturnsforlong-termtimehorizons,forexample50yearsplus.Fromyear20onwards,WTWadoptsanormativelong-termassumption.ThenormativeassumptionsrepresentWTWexpectationsforassetclassreturnswhenmarketsarepricedat“equilibrium”levelsor,thereturnsWTWwouldexpect,onaverage,overafullmarketcycle(overwhichtheywouldexpectover/underpricingrelativetoequilibriumto“balanceout”).WTW’sbestestimatesintheearlieryearsoftheprojectionsdifferfromtheirviewsoflonger-termcentraloutcomesinanumberofareas.Thetransitionfromshorter-termtolonger-termassumptionsoperatesoverdifferentperiodsfordifferentvariables.

WTWisalsoabletoprovidedynamicassetallocationadvicebasedonviewsoverathreetofiveyeartimehorizon.

Underlying Capital Market Assumptions ThestartingpointforWTW’sstandardassumptions iscurrentmarketexpectations.Theextenttohowmuch theydependonthisinformationvariesfromassetclass,butit’sanimportantinputintotheprocess.WTWalsouseshistoricmarketdata,mainlytodeterminevolatilityandcorrelationassumptionsforeachassetclass.Judgment isusedtodecideifthedriversofhistoricalperformance willrecur.

WTWalsoincorporatestheviewsofothermarket participantsbyusinginformationfromcentralbanksandgovernmentguidesforregionalexpectationsonfutureinflationandeconomicgrowth.Theywillalsosensecheck their assumptions by surveying return expectations ofmanyinvestmentmanagers.

TheseinputsarethenusedtoframetheGlobalInvestmentCommittee(GIC)capitalmarketassumptions.TheGICaremadeupofnineInvestmentprofessionalswithanaverage of17yearsofinvestmentexperience.


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• Robert Brown-ManagingDirectorandChairman oftheGIC.RobertjoinedWTWin2002havingpreviouslyspent7yearsatFirstQuadrantwherehewasinvolvedinmanagingequitymarketneutralandGTAAstrategies,andlatterlyheadingitsEuropeanoperations.PriortothathespentelevenyearsatNatWestInvestmentManagement(Gartmore)wherehewasadirectorinchargeoftheirstructuredequitiesgroup.

• Alasdair Macdonald-HeadofAdvisoryPortfolioManagement.AlasdairjoinedWTWin1999.AparticularareaofAlasdair’sspecialisationisinstochasticmodellingandhasbeenheavilyinvolvedinthedevelopmentoftheWTWInvestmentModelandtheuseofriskbudgetingstatisticsforinstitutionalinvestors.

• Peter Ryan Kane–HeadofPortfolioAdvisoryAsia Pacific.Peterhasmorethan25yearsofexperienceinfinancialmarketsasanadviser,investor,borrowerandriskmanager.PriortoWTW,PeterheldpositionsincludingGlobalChiefInvestmentOfficer,HeadofInterestRateRiskManagement,CapitalMarketsresearcher,andFinancialMarketsTrader.

• Matt Stroud–HeadofInvestmentStrategy,NorthAmerica.MattisresponsibleforallaspectsofinvestmentstrategyadviceintheAmericasincludingdevelopingandmaintainingmodelportfoliosfordelegatedaccounts,completewithmanagersandweights,andoverseeingapplicationofmodelportfoliostoclientcontext.PriortoworkingatWTW,MattdevelopedandassessedtheNASD’sfirstformalactionagainstaNASDAQmarketmakerfortradingaheadofcustomerlimitordersandwasalsoaFinancialConsultantatMerrillLynch&Co.

• Craig Baker–GlobalChiefInvestmentOfficer.CraigisultimatelyresponsibleforallaspectsofWTW’sinvestmentphilosophyandprocess.PriortotheCIOroleCraigspentthreeyearsasHeadofInvestmentResearchand15yearsleadingtheManagerResearchteamatWTW.

• David Hoile–HeadoftheAssetResearchTeam. Davidisresponsibleforthefirm’scapitalmarkets researchanddevelopingmedium-termandstrategic assetclassviews.PriortojoiningWTW,Davidwas HeadofInvestmentResearchatAonConsulting.

• Luba Nikulina–GlobalHeadofManagerResearch. Priortoassumingthisrole,LubaledtheglobalprivatemarketsteamatWTWandhasover18years’industryexperience.LubaattendedtheAdvancedManagementProgramatHarvardBusinessSchoolandholdsanMBAdegreefromLondonBusinessSchool,MSinFinancefromtheFinanceAcademyinRussianandaBAinLinguistics.

• Chris Mansi–GlobalDelegatedCIO.InthisroleChris isresponsiblefortheinvestmentprocess,structureandresourcesWTWputinplacetobuildportfoliosdesigned tomeetdelegatedclients’objectives.ChrisjoinedWTW in1999andhasover20years’industryexperience.

• Chris Hemmer–ChrisjoinedWTWin1993an isaDirectorandSeniorConsultantintheChicago office.Chrisservesastheleadconsultantforanumberofclientsprovidingbothadvisoryanddelegatedservices.PriortohiscurrentrolehemanagedtheChicagoinvestmentpracticeforfiveyears

Overthelast12months,ChrisRedmondandTimHodgsonhavelefttheGICandCraigBaker,DavidHoile,LubaNikulina,ChrisMansiandChrisHemmerhavealljoined.

TheGIChasoverallresponsibilityforsettingWTW’sinvestmentreturnassumptions,whichtheyreviewonaquarterlybasistoreflectanychangestomarketconditions.Amoreextensivereviewisconductedonayearlybasis.TheproductionofquarterlymodelcalibrationsisdelegatedtotheESGTechnicalCommittee(TC),whichreportsintotheGIC. Asset Allocation TheESGTCalsodeterminesmodelportfoliosundertwodifferingrisklevelsthatreflectWTW’sbestinvestmentideasunderanunconstrainedmandate.Theywillusetheirreturn,volatilityandcorrelationassumptionsasavalidationcheck toensuretheyhavedesignedanoptimisedportfolio.

UsingtheGIC’smodelportfoliosasastartingpoint,WTW isabletoapplyclientspecificconstraintstoarriveatbespokeassetallocationsusingtheirin-housemodellingsystems.WTW’sassumptionscanalsobeusedinconjunctionwithitsclient’sownoptimisationmodelswhereappropriateandnecessary.Sensitivityanalysisistypicallyconductedtotest therobustnessofportfolioanalysis.


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Resources TheGICcompromisesnineinvestmentprofessionalwhoarebackedbytheassetresearchteamwhichcompromises10globalconsultantsanda140strongmodellingteamwhoworkontheassetmodellinganddevelopmentofthemodel.

Validation

WTWconductsanannualsensecheckofassumptionsbysurveyingmanyinvestmentmanagersandotherindustryparticipants.

Asset Classes TheassetclassesthatTWareabletomodelareshowninthetablebelow:

Optimisation

WTWisabletooverlaytheirstandardassumptionswithfactorsspecifictoclientsandisabletoconductthefollowing:

• MappingofWTWassetassumptionstoeachclient’sassetclass categories

• Includetheexpectedalphaandfeesforresearchedmanagers

• Providedifferentriskmeasuressuchasstandarddeviation,tailVaR(ValueatRisk)andprobabilityofloss.

WTW’s work with Old Mutual Wealth

WTWhasbeenworkingwithOldMutualsince2000anditcurrentlyprovidesthemwithassetallocationforOldMutual’swealthselectplatformandtheirSpectrumfunds.

Fixed Income Derivatives Equities Alternative Beta Others

GovernmentBondMBS(MortgageBackedSecurities)

Large Cap Reinsurance HedgeFunds

CorporateBondCMBS(CommercialMortgageBackedSecurities)

Small Cap Commodities Private Equity

FRN(FloatingRateNotes)

Swap EmergingMarket Loans Global Property

IndexLinkedGilts Equity Derivatives HighYield Infrastructure

MunicipalBondsEMD(EmergingMarketDebt)

Gold

EMCurrency

WTWprovidesOldMutualwithrisk/return/correlationassumptions for the following asset categories:

• UKEquities• Global Equities• UKCash• UKFixedIncome• InternationalFixedIncome• UKProperty

Propertyexposureisconstrainedtoamaximumof15% andtheInternationalequityweightsarecalculatedbasedonregionalGDPweighting(exceptfora15%subcomponentinGlobalSpecialist).

WTWthenrunstheassetassumptionsthoughOldMutualWealth’smeanvarianceoptimisationtoolandprovidesOldMutualwithasetofoptimisedassetallocations.


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Historic assumptions vs actual outcomes

Thechartbelowlooksattheassumedrealreturnsrelativetotheactualoutcomesforfivemajorassetclasses.Ofparticularimportanceistheequityriskpremium(UKequitiesrelativetoILG)andthisisalsoshownonthechart.

UKEquityreturnswerebetweenthelowerquartileandthemedianexpectedlevelreflectingtherelativelyhighstartingpointofmarketsasat30June2006,followedbythesignificantbearmarketseenin2007-9,andthesubsequentrecovery.

ILGreturnsbenefitedasBankofEnglandindependenceandafocusonliabilitymatchingbyUKpensionschemescausedrealyieldstodecline.Thishasresultedinarealisedriskpremiumatthelowendoftherangethatwasexpectedin2006.UKfixedinterestgiltsalsobenefitted,buttoasmallerextent,fromfallingyieldsovertheperiod.

UK Equities

Realised Return

Overseas Equities UK Gilts UK IndexLinked Gilts

UK Property Equity RiskPremium

5th percantile

95th percantile

LQ

Median

UQ

0.0%

-5.0%

5.0%

10.0%

15.0%

Source: WTW


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AKG Although AKG are involved in this market, their activities are limited in the retail space. Therefore we have not reviewed their product in detail. Who they are and what they offer AKGisanactuariallybasedorganisationspecialising intheprovisionofinformation,ratingsandconsultancy tothefinancialservicesindustry.Thisactuarialskill,settogetherwithmarketexperience,hasmeantAKGcanprovideanassetallocationcomponentandassistanceforintermediaryfirms,systemproviders,publishersandotherthirdpartiesinvolvedinthecreationofclientinvestmentsolutionsandsupport.TheirclientsincludeO&MSystems,DefaqtoandCapita.

AKGhaveconfirmedthattheirassetallocationoffering isnotacorepartoftheirbusiness.Theyarenotoverlyproactiveinseekingclients,butarehappytoassistexistingclientswhorequiretheirexpertiseinthisarea.

AKGcontinuetoprovideservicestoCitywire,Networks andWealthWizards.

Approach to Strategic Asset Allocation

AKGdonothaveaonesizefitsallmodelandinsteadtailortheirofferingtoeachindividualclient.Theprocessstartswithreviewingtheclient’sexistingsetofassumptions.AKGwillthenlookatthemarkets’recentperformancetodeterminewhetherthecurrentassumptionsforvolatilities,correlationsandreturnsneedtobeadjusted.Theadjustedassumptionsarethenusedtomodeltheclient’scurrentportfoliotochecktheirrobustnesstomeettheneedsofinvestorsbasedontheirattitudetorisk.Analysisofwhetherthevolatilitiesarestartingtoriseorfallisthenconsideredwithconsiderationofadjustmenttohigherorlowervaluesinthemodelling.

TheprocessusedbyAKGisasimpledeterministicquantitativedrivenapproachwithsomequalitativeoverlay.AKG’sofferingis purely strategic in nature with no tactical asset allocation overlayprovided.GenerallytheyupdatetheirCapitalMarketAssumptionsonasemiannualbasisandthesearepeerreviewedbyanexternalactuarialbusiness.


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The“TraditionalApproach” Priortotheintroductionofquantitativemodels,investmentprofessionalsconstructedprivateclientportfoliosinamannerthatwasconsistentwiththeprincipalsbackingmodernportfoliotheory.Itisassumedthatasensiblydiversifiedportfoliowouldapproximateapositionclosetotheefficientfrontier.Portfolioswereconstructedacrossanumberofassetclassesandportfolio’sriskgradationswereoftendeterminedinaqualitativefashion.Labelssuchas‘cautious’and‘balanced’arecommonlyappliedtodescribetheportfoliomix.

Typicallyportfolioswouldbeconstructedusingarbitraryallocations,whichapproximatedclients’riskbandings.Hencea“balancedrisk”portfoliomaybeconstructedusingabaseallocationof60%equities,30%bondsand10%cash.Theportfoliomaybemanagedwithintolerancesaroundthesebandstoensurethattheportfoliomettheclients’expectationsofriskandreturns.

Pros

• Thestaticbaseportfoliocanactasabenchmark• Theinvestmentmanagerretainsfullflexibilityover

the investment strategy• Precisecapitalmarketassumptionsarenotrequired• Clients may assume false levels of comfort from more

complexandseeminglymorerigorousapproaches

Cons

• Itmayrequireanexperiencedadvisertomatchthe client’srisktolerancewithanappropriateportfolio.

• Theportfoliosarenotoptimisedforriskandreturn• Risk/returncharacteristicsoftheportfoliomaybedifficult

todetermine• Risk/returncharacteristicsofotherassetsheldoutside

oftheportfoliomaybedifficulttoincorporateintotheoverallexposureoftheclient.

• Portfoliolabelswereappliedinconsistentlyacrosstheindustry–onefirm’s“cautious”portfoliomaybeanother’s“balanced”.(Thisproblemmaystillremainwithindifferentrisktargetedrangesbutatleastthereissomeunderlyingconsistency in the approach)


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6. Common Limitations of Models


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1.UseofHistoricVolatility toGaugeFutureRisk a)Themodelsusesomeformofvolatilitymeasure todenoterisk.Investorsmightconsiderriskasbeing moreasymmetricalinnature,withaspecificconcern beingapermanentlossofcapital.

b)Volatilitychangesovertime.Marketscanbecalmortheycanbeextremelyagitated.Mostofthemodelsuselong-termaveragevolatilitytogaugefuturerisk.Useoflongtimeseriesofdataensuresthatthemodelsarenotundulyinfluencedbyshort-termtrendsinmarkets.

Moresophisticatedmodels(egMoody’sAnalytics “volatilityjumpdiffusionmodel”)factorinbothcalm andagitatedmarketsintotheirstochasticassumptions. Inadditiontothedifferentvolatilityassumptionsineach‘regime’,differentreturnassumptionscanbeapplied. Suchanapproachdiminishestheimpactofsequencing inthemodelsoutputs.

2.TailRisks Manystatisticaltechniquesbasedonprobabilitytheoryassumethatobservationsaredrawnindependentlytoformanormaldistribution.Evidenceinfinancialliteraturedemonstratesthatreturnobservationsinfinancialmarketsonlyapproximateanormaldistribution.Extremeeventsaremorecommonthanthenormaldistributioncurvewouldsuggest,examplesofthesewouldinclude:

• May2010‘flashcrash’whentheDowJonesindex lost1,000pointsinminutes

• 2008financialcrisisandthecollapseincreditmarkets• 2000-2001collapseinTMTstocks• 1998LTCMhedgefundcrisis• Asianfinancialcrisisin1997• Stockmarketcollapsein1987

Thepresenceofeventssuchastheseproducesabellcurvethathas“fat”tails.Asaretypicallynegativeeventsforfinancialmarkets,fattailstendnottobesymmetricalandfeatureonthelefthandside.Belowisastylisedchartillustratingthephenomenon.

Putanotherway,theannualisedvolatility(SD)oftheUK equitymarketovertheTwentiethCenturywasapproximately18%.Ifweassumeanormaldistribution,wemightexpect to observe a single instance of a monthly return in excess of15%overthe100-yearperiod.Infacttherewere7-recordedinstances.

Deterministicmodelsassumingthatdistributionsare ‘normal’,failtofullyfactorinthelikelihoodofextreme events.Asaresult,therisksdescribedbythesemodels areprobablyunderstated.

Astochasticapproachislikelytobettermodelhow financialmarketsbehaveinpractice.Suchamodellingapproachcanconsiderhistoricaleventssuchasthe1987stockmarketcrashaspartoftheirscenarioanalysis. Thisshouldmoreaccuratelymodeltherisk-returnexpectationsofaparticularassetallocation.

3.BreakdownsinCorrelations Awell-diversifiedportfolioofassetsisconstructedusingadiversemixofassets,whichhaveindependentperformancedrivers.Thegreaterthediversityinthemixofperformancedrivers,thegreaterthediversificationbenefitstheportfolioprovides.

Historiccorrelationanalysisisusuallyemployedasaproxytodescribetheinterdependenceofdifferentassets.Ifthehistoriccorrelationrelationshipbreaksdown,thevolatilityofthereturnsfromaportfoliocouldrise.

Exhibit 1: International Equities - “Fat” left tails in historical returns

“Fat” left tails

Monthly return

Empirical Normal

-20% -15% -10% -5% 0% 5% 10% 15% 20%

Source:J.P.MorganAssetManagement.Forillustrativepurposesonly.

Den

sity

12

10

8

6

4

2

0


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Financialmarketsareinterrelated.Duringperiodsofmarketstress,assetsthatareseeminglyunrelatedcanbegintoperforminunison.Asaresultdiversificationbenefitscanmeltawayasassetsbecomeincreasinglycorrelated.

Someofthemoresophisticatedstochasticmodels(suchasBarrie&Hibbert)canfactorinchanging‘regimes’or‘marketstates’.Duringcalmstablemarkets,volatilityofindividualassetclassesislow,asarecorrelationsbetweenthem.Duringturbulent,stressedmarkets,thevolatilityofreturnsfromindividualassetclassesrise,aswillcorrelationsbetweenthem.Astochasticapproachpermitstheuseoftwo(ormore)volatilitytablesandcorrelationmatrices.Forexample,amodelcanbegeneratedwhichassumesthat80%ofthetimemarketsareinacalmstate,and20%inastressedstate.

Modelsthatignoresuchchangestothemarketdynamicsmayunderestimatetheriskswithintheproposedassetallocations.

4.AssumptionsofPositiveNominalInterestRates Overthelastyear,wehaveseeninterestratesacross thewesternworldturnnegativeandinmarketswhererateswhereexpectedtorise,theyhaveremainedathistoricallylowlevels.InthecaseoftheUK,interestrateshaveactuallyfallenfrom0.50%to0.25%(Asat4thAugust2016)andmanymarketanalystsexpectfurtherfalls.Howeveronlytwelvemonthsago,therewereadvertsontheradiowarningconsumersabouttheimpactofrisinginterestrates.

Mostretailinvestorsinwesterneconomieswillnothavetopaytoholdtheirmoneyinabasiscurrentaccountanditisunlikelythatthatthiswillhappen.Howeveroverthelastyear,thelikelihoodofthishappeninghasincreased.Thereforewequestionedtheprovidersinthisreporttoseehowtheywoulddealwithnegativeinterestrates.

Manyoftheprovidershavehadtorecalibratetheir modelsinordertoaddressanegativeinterestrateregime,howeveralloftheprovidersareabletodealwithanegativeratesenvironment.

5.SequencingRisks inDrawdown Itisnotjustlong-termaveragereturnsthatimpactthefinancialwellbeingofinvestors.Thetimingofhowthosereturnsariseiscritical.Whenretireesbeginwithdrawingmoneyfromtheirinvestments,thereturnsduringthefirst fewyearscanhaveamajorimpactontheirwealth.

Tworetireeswithidenticalwealthcanhaveentirelydifferentfinancialoutcomes,dependingonwhentheystartretirement.A retiree starting out an retirement plan at the bottom of abearmarketwillhaveafarhappierfinancialexperiencethananotherstartingoutatamarketpeak,evenifthelong-termaveragesreturnsmaybethesame.

Deterministicmodelsdonotfactorsuchtimingfactors andstochasticmodelsprovideamoreeffectivesolution.


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7. Summary Table Detailing Some Differences Between the Main Providers


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Question DT EValue MA Morningstar WTW

Isthemodelstochastic or deterministic?

Deterministic Stochastic Stochastic n/a Stochastic

Isaqualitativeoverlay in place postmodelresults?

Yes No No Yes Yes

How many scenarios are run intheESGModel

N/A 10,000scenarioswill be run for the main asset allocation.Asubsetof1,000isusedinthecalculation of planningtools.

From1000to5000

n/a From10,000to20,000

SizeofTeam BenGrossistheCEOandissupportedbyfourdirectors.One of which is Chris Fleming who leadstheanalyticsteam.Ateamof6analysts supports Chris.

EValue employ approximately 60people.ThisincludesateamofsixactuariesandPHD’swhoupdateandmaintainthemodel.

60plusemployees are responsible for ESGresearch,developmentandmaintenance.Of these 15 are also responsible for the quarterly calibration update.

The120stronginvestment management team all contribute with varying levels of input into the strategic asset allocationprocess.

The global investment committee consists of nine investment professionals who arebackedby10global consultants anda140plusstrong investment strategyteam.


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How many asset classes are modelled?

CashCorporateBondIndexLinkedGiltUKGiltsGlobalHighYieldBondsGlobal EquitiesPropertyCommoditiesHedgeFundsInflation

CashGovernmentBondCorporateBondIndexLinkedGiltGlobal EquitiesCommoditiesProperty

CashGovernment BondsCorporateBondsIndexLinkedGiltGlobal EquitiesPropertyEmergingMarketDebt CommoditiesHedgeFundsPrivate EquityInfrastructure

Where clients requireadditional/bespokeassetclasses,MAprovidesacustomcalibrationservice.

CashGovernment BondsCorporateBondsIndexLinkedGiltGlobalHighYieldBondEmergingMarketDebtGlobal EquitiesPropertyHedgeFundsCommoditiesRealEstateInfrastructure

CashGovernmentBondCorporateBondFRN(FloatingRateNotes)IndexLinkedGiltMunicipalBondsMBS(MortgageBackedSecurities)CMBS(Commercial MortgageBackedSecurities)SwaptionEquity DerivativesGlobal EquitiesReinsuarnceCommoditiesLoansHighYieldEmergingMarketDebtEMcurrencyHedgeFundsPrivate EquityGlobal PropertyInfrastructureGold

Over what time horizonsareinvestment periodsmodelled?

DT’sCMA’sarebasedonalong-termoutlookthough they donotspecifyprecisely the time frame.

EValue use 4,8,13,18and21+yearsasaproxy for a range of investment periods.Theproposedportfolios are applicable to investment periodsof3-5,6-10,11-15,16-20and21+.

TheMAmodelismultiperiodthatuses multiple time frames.

Assumptions are typicallybasedona10-yeartimehorizon.Howevertheydohavetheability to form SAA’sbasedona20yearhorizon.

WTW is a multi periodmodel,whichcanmodelreturns for long-term time horizons,forexample50yearsplus.



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Doesthemodelassumeasteadystate?Ifso,overwhattimeperiodisthesteadystateassumed?

Themodelalwaysassumes that returns,volatilitiesandcorrelationsare always in a steadystate.

Yes.EValuetendtoseeatrendover20yearswhen longer-term situationstendtosettledown.

Yes.MA’smodelassumes that interest rates reverttowardsa long-term averagelevel.The term over which asset price behaviourwouldbeexpectedtoreverttowardsthis equilibrium statewilldependon the current levelofrates,theassumedlongterm reversion levelandtheirassumptions regardingtherate of mean reversion.

n/a Yes.Aftertwenty years WTW assume a normative long-termassumption.

Doesthemodelassumetailrisk

No Yes Yes Yes Yes

Didtheeventsin2008,fallwithinthemodelspredictedrange?

Yes Nearlyalloutcomes were withinthe95%confidencelevel.

Yes n/a Yes

Howdothemodelsaccommodateforamarketcrisis where the correlation of assetclassestendtomoveto1.

Theydon’t.DTmodelassumes that the correlation between asset classes remains constant throughout.

Conditionalcorrelation factors areusedwithinthemodeltoallow for these situations.Thishelps overcome the issues that fixedcorrelationfactorsusedbyanMVCmodelsufferintheeventofamajormarketupset.

Specificmodel,calledstochasticvolatilitydiffusionequitymodel.Themodelisusedto incorporate scenarios where volatilityandcorrelations increase significantlyabovemarketlevels.

Yes.Morningstartakeaforward-lookingapproachtoriskandunderstandthatthemajorityofasset classes can be over or undervaluedatthesametime.

WTW use scenario analysisandsensitivity testing extensively to provideapictureof asset class / portfolio returns undermarketstressscenarios.



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Are they willing toprovidelongterm examples of historic performance information?

Yes.PleaseseeDT’ssectionofthereport.

No.EValuearelookingintoprovidingfairandconsistentperformance measures of their portfolios.

As the SAA that MAprovideisspecifictoeachoftheir clients in line withclient-specificasset allocation constraints,investment objectivesorasset exposure preferences.MAwillonlyprovideperformance information to theirclients.

Yes.PleaseseeMorningstar’ssection of the report.

Yes.WTWhavenotprovidedus with historic performance of theirportfolios.However they haveprovidedhow their historic capitalmarketassumptions have differedtotheactual outcomes forfivemajorassetclasses.

Doesthemodelconsidernegativeinterest rates into theirscenarios?

Yes.DTdoesnotconductscenarioanalysis,howevertheirmodelcanassume the interest rates are negative.

Yes.Inlate2015,EValueallowedthe possibility of negative interest rates into their scenarios.

Yes.Postthe2008financialcrisisMAaddedavolatilitydisplacementfactor into their model.Thiswas to ensure thatthemodelwas capable of simulating negative nominal rates.

Yes Yes.TheWTWmodelnowallowsfor the possibility of negative cash ratesandbondyields.


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8. Evaluating Model Performance Records


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TheSAAmodelsaredesignedtoplacetheinvestors’portfoliosonorclosetotheefficientfrontier.

Intheoryitshouldbepossibletoexaminetheriskadjustedperformancetrackrecordofamodel.

Weacknowledgethatanyperformancecomparisonisfraughtwithdifficulty.

a) Therearetwooutcomevariablestoconsider–boththeriskandreturnb) Themodelsmaynothaveconsistenttimehorizonsc) Considerationshouldalsobemadetothemodelcalibrationand

constraintsusedd) Capitalmarketshavenotperformedastheorysuggestsoverthelast

15years.Certainhigh-riskassetssuchasdevelopedmarketequityhave beenoutshonebytheperformanceoflowerriskgilts.

Annualised 15 year Risk and Reward

Annu

alis

ed R

etur

n (%

p.a

.)

Volatility (% p.a.)

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

FTSE Actuaries UK Coventional Gilts MSCI WorldFTSE All Share MSCI Emerging MarketsLIBOR GBP 3m

Increasing Expected Deviation (Market Risk)

Bonds

The Efficient Frontier

Efficient Portfolios

Inefficient Portfolios

The Efficient Frontier

Incr

easi

ng E

xpec

ted

Retu

rn

Cash (Money Market Funds)

Stocks (S&P 500 Stock Index)

Small Company Stocks

Diversified Emerging Markets Stocks


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9. Appendix


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RiskProfilers FinaMetrica TheFinaMetricaRiskToleranceToolkitwaslaunched in1998.ItwasdevelopedandtrailedinAustraliaover fouryearswiththeassistanceoftheUniversityofNewSouthWales.ItsnowmaintainedwithexpertisefromtheLondonSchoolofEconomicsandhasgainedinternationalrecognitionasworld’sbestpractice.TheToolkit’sreliabilityandvalidityisbackedbyoveramillionusesbythousandsoffinancialadvisorsinover20countries. Thesystemprovidesascientificassessmentofan individual’spersonalfinancialrisktoleranceinplain English.Thesystemusespsychometricstoensurevalidityandreliability.FinaMetricaoffera12and25questionrisktolerancequestionnairethatcanbecompletedin15-20minutes.The25-questionquestionnairemeasuresfinancialrisktolerance,whilethe12-questionquestionnaireonlyasksinvestmentquestions.Ariskprofilereportisavailableafterthequestionnaireistakenandprovidesascoringscale from0to100.

FinaMetricahasregionalallianceswithfirmsinvolved inthefinancialservicesindustryinvariouscountries.FinaMetrica’sUKallianceiswithIdealsLabwhooffers supportforUKadvisersseekingmoreinformationon theFinaMetricariskprofilingsystem.

Mapping Services

FinaMetricamapanumberofriskratedfundsprovided byassetmanagersincluding7IM,Architas,Santander,SEI,Legal&GeneralandStandardLife.

FinaMetricawillmapeachofanassetmanger’srisk ratedfundstotheappropriaterangeofFinaMetricarisktolerancescores.FinaMetricaassetallocationmappinglinksrisktolerancescorestoinvestmentportfoliosenablinganapples-to-applescomparisonbetweenrisktoleranceandportfoliorisk.FinaMetricamonitorsthestrategicallocation ofeachfundonaregularbasistoensurethatthemappingsarestillappropriate.

Oxford Risk

OxfordRisk(OR)isaspinoutcompanyoftheUniversityofOxford,whohasretainedasignificantshareholdinginthecompany.ORwasfoundedbyProfessorLordJohnKrebs,ProfessorAlexKacelnikandDr.EdwardMitchellwhohavepublishedhundredsofscientificresearchpapersinbehaviouralecology,behaviouraleconomics,riskpsychologyanddecision-making.

TheOxfordRiskRating(ORR)PersonalInvestorassessestherisktolerancesofretailcustomerswhenconsideringthepurchaseofinvestmentproducts.ORRPersonalInvestorprovidesascientificallydefensiblemeasuretoaidtheadviceprocess,andiscurrentlyavailableto40,000advisers.TheirclientsincludeSesameBankhallGroup,PersonalTouchFinancialServices,StandardLife,Clarendon,HSBC,RBS,BrewinDolphin,RathbonesandLegal&General.

ORbelievethatthereareotherfactorsapartfromrisktolerancethatcanhelpdiscriminatebetweeninvestorandcustomertypes.Theseinclude:

• Composure–Thedegreeofshort-termanxietythananindividualwillfeel.

• Fear of Catastrophic Loss • PerceivedFinancialExpertise• Delegation • Beliefinskill• Theeffectofcircumstances

ORhavecreatedarisktoleranceassessmentspecificallyfortheUKmarket,whichwasestablishedthroughalistof140questions.Statisticalanalysiswasthenconductedtoseehowthequestionsperformandtoidentifypoorlyunderstoodorconfusingquestions.Acomponentanalysiswasthencompletedtoreducethenumberofquestionstotheminimumsetthatmeetstheirperformancecriteria.Thisledto18questions,whichequallycompromiseanassessmentofthe following factors:

• Riskfocus• Rewardfocus• Composure


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All18questionsareregularlyreviewedtoensuretheyare stillreliableandvalid.Afive-pointansweroptionscaleisusedformostquestions.ThescaleiscalledtheLikertscale,andlookslikethefollowing:

(1) Strongly Disagree(2) (3) (4) (5) Strongly Agree

Therefore higher scores from the questionnaire represent higherlevelsofrisktoleranceandlowerscoresrepresentlowerrisktolerance.

InOR’smethodologydocumenttheyalsomentioned the following:

• Measuresofassetriskarebasedonprobabilityratherthandeterministic.

• Volatilitytreatsoutcomesthatarebetterthanexpectedasbeingjustasriskyasoutcomesthatareworsethanexpected.

• Risktoleranceshouldbeenseeninthecontextoftheinvestmentobjectives,notobscuredbythem.

• Researchshowsthatattitudestoriskindomainsotherthanfinancialinvesting,suchashealthrisksandgamblingareunrelatedtofinancialriskattitudes.

• Neitherknowledgeoffinancenormathematicalabilityshouldfeatureinrisktolerance.

• Risktoleranceshouldreflectadeepseatedandstableaspectofpersonality.

• A sensible question can fail a statistical test because itdoesn’telicitsufficientdisagreementamongstrespondents.

• Higherwealthnormallymeanshigherrisktolerance.• Olderindividualstendtohavealowerrisktolerance,as

loss aversion becomes a more pressing concern at or approachingtheageofretirement.


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Risk Profile Boundaries Thispaperbrieflydiscussesthetwocommonly appliedapproachestodeterminingvolatilitybands forriskprofiles.Bothmethodsassumethatvolatility ismeasuredthoughaportfoliosstandarddeviation andeachcorrespondinginvestmentriskprofilehas beengivenitsownprescribedlevelofexpected volatilitydeemedappropriateforatypicalinvestor.

Uniform Volatility Bands

Thefirstmethoddividestheefficientfrontierasset strategyintoaspecificamountofuniformvolatilitybands.Undertheuniformvolatilitybandmethodanincreaseordecreaseinriskprofilejustmeansanincreaseordecrease involatilitybyauniformamount.

Non-Linear Volatility Bands

Thismethodalsoconsiderstime,basedontheassumptionthataninvestor’swillingnesstoacceptriskisdependentupontheirtimehorizon.

Illustrative Example

Assumingthataninvestorholds£100,000andthatthereturnsofhisinvestmentsfollowanormaldistribution, wecancalculatetheinvestor’smaximumlosswitha95%confidencelevelusingthefollowingformula:

(1.96 x 100,000 x volatility)

Whilethe%Increaseinmaximumlossisjustthemaximumlossofthenewriskprofiledividedbythemaximumlossofthepreviousriskprofile.

Belowisatableshowingthelowerandupperriskbands fortheuniformmethod,aswellasthemaximumlossfrom theuppervolatilityband.

Risk Profile Lower Band Upper Band Maximum Loss% Increase in

Maximum Loss

1 0% 2% £3,920 n/a

2 2% 4% £7,840 100.0%

3 4% 6% £11,760 50.0%

4 6% 8% £15,680 33.3%

5 8% 10% £19,600 25.0%

6 10% 12% £23,520 20.0%

7 12% 14% £27,440 16.7%

8 14% 16% £31,360 14.3%

9 16% 18% £35,280 12.5%

10 18% 20% £39,200 11.1%


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Theexampleshowsforalowerriskprofileinvestor, movingupariskprofileissignificantlygreaterthanahigherriskprofileinvestormovingupariskprofile.Soeventhoughthevolatilitybandsareuniformsthedifferenceinriskprofilesarenotuniform.

Belowisatableshowingthelowerandupperriskbands forafouryeartimeperiodunderthenon-linearmethod, aswellasthemaximumlossfromtheuppervolatilityband.

Thisexampleshowsforalowerriskprofileinvestor,moving upariskprofileissimilartoahigherriskprofileinvestormovingupariskprofile.Soeventhoughthevolatilitybandsarenotuniformtheuniformityinriskprofilesisgreaterthanfortheuniformvolatilitybandmethod.

Risk Profile Lower Band Upper Band Maximum Loss% Increase in

Maximum Loss

1 0.0% 3.9% £7,644 n/a

2 3.9% 4.5% £8,820 15.4%

3 4.5% 5.3% £10,388 17.8%

4 5.3% 6.3% £12,348 18.9%

5 6.3% 7.6% £14,896 20.6%

6 7.6% 9.1% £17,836 19.7%

7 9.1% 10.9% £21,364 19.8%

8 10.9% 12.8% £25,088 17.4%

9 12.8% 15.3% £29,988 19.5%

10 15.3% 18.0% £35,280 17.6%


Page50of51

Platform Risk Profiling Tool Asset Allocation Tools

CoFunds OxfordRisk DT

FundsNetwork Ibbottson

OldMutualWealth Inhouse Towers

StandardLife OxfordRisk MA

Transact

SEI N/A

James Hay n/a

AJBellInvestment

Zurich EValue

Elevate EValue EValue

Ascentric

Nucleus FinaMetrica

SevenIM Ibbottson

Aviva

RaymondJames

Novia Inhouse EValue

Aegon EValue

Parmenion Inhouse/EdgecumbeConsulting Inhouse

Alliance Trust Savings

JamesBrearley&Sons

Wealthtime

Praemium OxfordRisk MA

Avalon

HSBCPrivateBank OxfordRisk

Platforms and the Tools Embedded Within Them

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