怎么来区分划线部分分类

NO.PZ202207040100001004 问题如下 Baseon Exhibit 2, the excess return of MultiFarising from active factor weighting is closest to: A.0.04%. B.0.25%. C.0.28%. SolutionA is correct. The excess return arising from active factor weights is 0.04%. Compare the weights between the portfolio anthe inx: The only two thffer are the weights for Low Volatility anMomentum. From the following table, the totcontribution to the return causeactive sector weighting is the sum of0.28% Overweighting Low Volatility + (–0.24%) Unrweighting Momentum = 0.04% rounNote thMultiFusefewer holngs for the Quality segment an therefore, incurreactive security selection risk—but not active factor risk sinthe Quality segment weight is the same thof the inx. Here is the full calculation:0.036% roun to 0.04%.B is incorrect. Results of all active management are shown the bottom of the TotActive fferencolumn of the table. This is the full attribution of the active segment overweights plus the result of the active security selection on the Quality segment.C is incorrect. This is the value of the active overweight to the Low Volatility segment, but it exclus the active unrweight to Momentum. See the Low Volatility row in the Factor Weight column of the table. 按照上一题的提问，采取的是risk rection策略，因为over weight了low volitility因子。那这一题，看到问active factor weighting，而不是直接问factor weighing，就自然想到了 low volitility因子是主动高配的，那另外一个因子就是被动低配了。所以算active factor weighting时，就只考虑low volitility因子，结果是0.28%。请问这么想哪里有问题

NO.PZ202207040100001004问题如下Baseon Exhibit 2, the excess return of MultiFarising from active factor weighting is closest to:A.0.04%.B.0.25%.C.0.28%. SolutionA is correct. The excess return arising from active factor weights is 0.04%. Compare the weights between the portfolio anthe inx: The only two thffer are the weights for Low Volatility anMomentum. From the following table, the totcontribution to the return causeactive sector weighting is the sum of0.28% Overweighting Low Volatility + (–0.24%) Unrweighting Momentum = 0.04% rounNote thMultiFusefewer holngs for the Quality segment an therefore, incurreactive security selection risk—but not active factor risk sinthe Quality segment weight is the same thof the inx. Here is the full calculation:0.036% roun to 0.04%.B is incorrect. Results of all active management are shown the bottom of the TotActive fferencolumn of the table. This is the full attribution of the active segment overweights plus the result of the active security selection on the Quality segment.C is incorrect. This is the value of the active overweight to the Low Volatility segment, but it exclus the active unrweight to Momentum. See the Low Volatility row in the Factor Weight column of the table. 如果factor portfolio和benchmark 的return不一样，是不是就不能按答案这样算了？factor weighting就用benchmark？

NO.PZ202207040100001004 问题如下 Arthur Camme Case ScenarioArthur Camme, founr of Camme Consulting, Inc., aises enwment fun anprivate fountions regarng equity manager selection. Because of the poor relative performananhigh fees of active management over the past severyears, Camme hbeen fielng increasing number of inquiries from clients about the best ways to use passive solutions for equity exposure. Camme meets with client Sylvia Parker, who seeks guinin establishing passive exposure for her $400 million family fountion. For a portion of equities, Parker wants to use inx approaaugmentefactor-basesolutions. She comments, “I hethfactor-baseapproaches cusewhen pursuing risk-austereturns superior to thof a comparable market cap-weighteinx. In aition,funmentweighting cenhanreturn, but when comparewith intrinsic values, it hthe saantages of overweighting overpricestocks anunrweighting unrpricestocks;value factor fun seek to lower wnsi risk; anrelative to cweighting, single-factor fun tento concentrate risk exposure.”Camme suggests to Parker ththe first priority in moving to a passive solution is to consir the choices available for inx exposure. Owing to the large size of the fun Camme recommen choosing a replication manager in orr to minimize totcosts. He explains the fferences between full replication, stratifiesampling, anoptimization when constructing the portfolio. Parker likes the ia of blenng stratifiesampling with optimization anasks Camme to intify the appropriate manager baseon the ta in Exhibit 1. Exhibit 1 Equity Replication ManagersIn reviewing the relative performanof Manager B from Exhibit 1, Parker makes the following statements:He facemore volatile markets ththe others baseon the tracking errors. He usecurrenoverlays to lever the returns of securities helin foreign currency. His excess return looks like it is more a matter of luthskill. Another client is Ken she, the new chairmof the investment committee of the ventown Arts Enwment. He wants Camme to help him unrstanthe primary investment strategy being followethe MultiFfun whiuses severfactors to structure anmaintain its large-cactive portfolio. The funuses benchmark segments of four mutually exclusive sub-categories shown in Exhibit 2. Exhibit 2 Attribution ta for MultiFFunanBenchmarkshe’s request, Camme calculates the amount of the excess return of MultiFtharose from active factor weighting cisions. e to a recent funraising campaign, ventown experiencesizable cash inflows anthe fun were appliein accornwith poliweights.Exhibit 3 Excerpts from ventown Arts Enwment Investment PoliStatementSevermonths later, she anCamme meet again. she nee aion how to hane a new pressing issue. A significant market correction hresultein a current asset allocation of 51% equities, 2% cash, an47% fixeincome. These values are now inconsistent with the investment polistatement guilines. In aition, the tracking error with equity benchmarks hincreasebecause of a sproportioncline in values of some of the actively managefun. Camme recommen a cost-efficient strategy to aress the situation thwill put the portfolio bain line with allocation guilines anrethe tracking error. Question Baseon Exhibit 2, the excess return of MultiFarising from active factor weighting is closest to: A.0.04%. B.0.25%. C.0.28%. SolutionA is correct. The excess return arising from active factor weights is 0.04%. Compare the weights between the portfolio anthe inx: The only two thffer are the weights for Low Volatility anMomentum. From the following table, the totcontribution to the return causeactive sector weighting is the sum of0.28% Overweighting Low Volatility + (–0.24%) Unrweighting Momentum = 0.04% rounNote thMultiFusefewer holngs for the Quality segment an therefore, incurreactive security selection risk—but not active factor risk sinthe Quality segment weight is the same thof the inx. Here is the full calculation:0.036% roun to 0.04%.B is incorrect. Results of all active management are shown the bottom of the TotActive fferencolumn of the table. This is the full attribution of the active segment overweights plus the result of the active security selection on the Quality segment.C is incorrect. This is the value of the active overweight to the Low Volatility segment, but it exclus the active unrweight to Momentum. See the Low Volatility row in the Factor Weight column of the table. 如题

NO.PZ202207040100001004问题如下Baseon Exhibit 2, the excess return of MultiFarising from active factor weighting is closest to:A.0.04%.B.0.25%.C.0.28%. SolutionA is correct. The excess return arising from active factor weights is 0.04%. Compare the weights between the portfolio anthe inx: The only two thffer are the weights for Low Volatility anMomentum. From the following table, the totcontribution to the return causeactive sector weighting is the sum of0.28% Overweighting Low Volatility + (–0.24%) Unrweighting Momentum = 0.04% rounNote thMultiFusefewer holngs for the Quality segment an therefore, incurreactive security selection risk—but not active factor risk sinthe Quality segment weight is the same thof the inx. Here is the full calculation:0.036% roun to 0.04%.B is incorrect. Results of all active management are shown the bottom of the TotActive fferencolumn of the table. This is the full attribution of the active segment overweights plus the result of the active security selection on the Quality segment.C is incorrect. This is the value of the active overweight to the Low Volatility segment, but it exclus the active unrweight to Momentum. See the Low Volatility row in the Factor Weight column of the table. 如果这两个factor portfolio和benchmark 的return不一样，是不是就不能按答案这样算了