《CFA三级写作课后题（2020.12）4.docx》由会员分享，可在线阅读，更多相关《CFA三级写作课后题（2020.12）4.docx（9页珍藏版）》请在第壹文秘上搜索。
1、2020年12月CFA三级写作题ASSETALLOCATIONANDRELATEDDECISIONSINPORTFOLIOMANAGEMENT今年由于疫情的缘故，CFA考试被迫延期。虽然给了大家更多的复习时间，但也不可掉以轻心。近年来，CFA考试的难度在逐步提高，并且在三级中更偏向实务与理论结合的考察。相比2019年考纲，2020年考纲发生了较多的变化。其中关于经济学的部分，更名为资本市场预期，并进行了重大改变；衍生产品与资产配置中的外汇管理合并在一起，并进行了较大的改写；另类投资的内容完全重新改写；交易与业绩评估合并在一起.并重新编写。而一向是考试重点的私人财富管理和机构组合管理也发生了较大
2、变化，其中私人财富管理的第一个RCading重新编写，而机构组合管理也进行了重新编写，这些变化需引起考生重视。为了全面应对考试，我们全面推出了的各种学习平台，如金程网校、手机APP、金程CFA答疑等活动，请各位充分利用。如有学术问题，请登录至金程网校提问。祝大家好运，顺利通过CFA三级考试，加油！AssetAllocationandRelatedDecisionsinPortfolioManagementCaseIzJohnTombJohnTombisaninvestmentadvisoratanassetmanagementfirm.Heisdevelopinganassetallocati
3、onforJamesYoungmall,aclientofthefirm.TombconsiderstwopossibleallocationsforYoungmall.AllocationAconsistsoffourassetclasses:cash,USbonds,USequities,andglobalequities.AllocationBincludesthesesamefourassetclasses,aswellasglobalbonds.Youngmallhasarelativelylowrisktolerancewithariskaversioncoefficient()o
4、f7.Tombrunsmean-varianceoptimization(MVO)tomaximizethefollowingutilityfunctiontodeterminethepreferredallocationforYoungmall:UIH=(/U-Ooo5TheresultingMVOstatisticsforthetwoassetallocationsarepresentedinExhibit1.Exhibit1MVOPortfolioStatisticsAllocationAAllocationBExpectedreturn6.7%5.9%Expectedstandardd
5、eviation11.9%10.7%DeterminewhichallocationinExhibit1TombshouldrecommendtoYoungmall.Justifyyourresponse.DeterminewhichallocationinExhibit1TombshouldrecommendtoYoungmall.(circleone)AllocationAAllocationBJustifyyourresponse.Solution:DeterminewhichallocationinExhibit1TombshouldrecommendtoYoungmaIL(circl
6、eone)AllocationAAllocationBJustifyyourresponse.TombshouldrecommendAllocationB.TheexpectedutilityofAllocationBis1.89%,whichishigherthanAllocationA,sexpectedutilityof1.74%.MVOprovidesaframeworktodeterminehowmuchtoallocatetoeachassetclassortocreatetheoptimalassetmix.Thegivenobjectivefunctionis:U.=(仆)-0
7、.005UsingthegivenobjectivefunctionandtheexpectedreturnsandexpectedstandarddeviationsforAllocationsAandBztheexpectedutilities(certainty-equivalentreturns)forthetwoallocationsarecalculatedas:AllocationA:6.7%-AllocationB:5.9%-0.005(7)(10.7%)2=1.89%Therefore,TombshouldrecommendAllocationBbecauseitresult
8、sinhigherexpectedutilitythanAllocationA.Case2:WalkerPatelWalkerPatelisaportfoliomanagerataninvestmentmanagementfirm.Aftersuccessfullyimplementingmean-varianceoptimization(MVO),hewantstoapplyreverseoptimizationtohisportfolio.Foreachassetclassintheportfolio,Patelobtainsmarketcapitalizationdata,betasco
9、mputedrelativetoaglobalmarketportfolio,andexpectedreturns.Thisinformation,alongwiththeMVOassetallocationresults,arepresentedinExhibit1.Exhibit1AssetClassDataandMVOAssetAllocationResultsAssetClassMarketCap(trillions)BetaExpectedReturnsMVOAssetAllocationCash$4.20.02.0%10%USbonds$26.80.54.5%20%USequiti
10、es$22.21.48.6%35%Globalequities$27.51.710.5%20%Globalbonds$27.10.64.7%15%Total$107.8Therisk-freerateis2.0%,andtheglobalmarketriskpremiumis5.5%.Contrast,usingtheinformationprovidedabove,theresultsofareverseoptimizationapproachwiththatoftheMVOapproachforeachofthefollowing:i.Theassetallocationmixii.The
11、valuesoftheexpectedreturnsforUSequitiesandglobalbondsJustifyyourresponse.Solution:Contrast,usingtheinformationprovidedabove,theresultsofareverseoptimizationapproachwiththatoftheMVOapproachforeachofthefollowing:i.TheassetallocationmixTheassetallocationweightsforthereverseoptimizationmethodareinputsin
12、totheoptimizationandaredeterminedbythemarketcapitalizationweightsoftheglobalmarketportfolio.TheassetallocationweightsfortheMVOmethodareoutputsoftheoptimizationwiththeexpectedreturns,covariances,andariskaversioncoefficientusedasinputs.Thetwomethodsresultinsignificantlydifferentassetallocationmixes.In
13、contrasttoMVOzthereverseoptimizationmethodresultsinahigherpercentagepointallocationtoglobalbonds,USbonds,andglobalequitiesaswellasalowerpercentagepointallocationtocashandUSequities.Thereverseoptimizationmethodtakestheassetallocationweightsasitsinputsthatareassumedtobeoptimal.Theseweightsarecalculate
14、dasthemarketcapitalizationweightsofaglobalmarketportfolio.Incontrast,theoutputsofanMVOaretheassetallocationweights,whicharebasedon(1)expectedreturnsandcovariancesthatareforecastedusinghistoricaldataand(2)ariskaversioncoefficient.Thetwomethodsresultinsignificantlydifferentassetallocationmixes.Incontr
15、asttoMVO,thereverseoptimizationmethodresultsina4.9,5.5,and10.1higherpercentagepointallocationtoUSbonds,globalequities,andglobalbonds,respectively,anda6.1and14.4lowerpercentagepointallocationtocashandUSequities,respectively.Theassetallocationunderthetwomethodsisasfollows:AssetAllocationWeightsAssetClassMarketCap(trillions)ReverseOptimizationMVOApproachDifferenceCash$4,23.9%10%-6.1%USbonds$26.824.9%20%4.9%USequities$22.220.6%35%-144%Globalequities$27.525.5%20%5.5%Globalbonds$27.125.1%15%10.1%Total$107.8100.0%100.0%ii.The
