CFA一級百題預測-數(shù)量（打印版）

一級百題預測1.ETHICS2.3.ECONOMICS4.FINANCIAL5.FINANCE6.EQUITY7.FIXEDINCOME8.9.INVESTMENTS10.PORTFOLIOMANAGEMENT1-762.Quantitative2.1.Interest2.1.1.重要知識點.DecomposerequiredreturnInterest=risk+expected+premiumNominalriskfree=risk-free+2.1.2.基礎題Q-1.Comparingaacreditrisk,anothercompanyalowandhighdefaultmosttoofalowerthesameC.ahigherQ-2.WhichofhasimpactnominalExpectedinflationriskC.Creditrisk.Q-3.thenominalrisk-freecreditrisk,liquiditymaturityconstant,iftheincreases,therisk-freewillbe:Decrease.change.C.Increase.TheliquiditycanbebestdescribedtoforriskoflosstovalueiftocashincreasedsensitivityofthevalueofdebtachangeinmaturityisC.possibilitythatthewilltoapromisedpayment2-76inamount.Q-5.Whichofthefollowingpremiumsisinexplaininginyields20-yearthe20-yearbondsasmallprivateissuer?Inflation.C.2.2.CalculationofEAR2.2.1.重要知識點.HPY和的計算及轉化FVPVHPRPVannualof)365/t1rEAY)1mm性質：r，m，EAR；Whenm,EARmaxer1360365單利時用，復利時用tt2.2.2.基礎題Q-6.TheclosingpricesofMordiceDateClosingPrice1August8August15August112160120ThecompoundedofMordiceperiodAugust115closest6.90%.7.14%.C.8.95%.Q-7.commonofaa7%3-76Theadividendtothesaleof$48perThepricethatshareyearearlier$44.05.$45.09.C.$45.90.Q-8.Iftheannual4.5%andofcompoundingannualisclosestto:4.5940%.4.6025%.C.4.6028%.Q-9.AmanagerhasShehasalternativeone-yearcertificatesofdeposit(CD)shownbelow:CompoundingQuarterlyAnnualCD1CD24.10%4.00%ContinuouslyWhichCDhashighestannualmuchitearn?HighestEARCD1Interestearned$41,635C.CD2$40,811CD2$40,808Q-10.Iftheannualonais6%annualis6.1678%.Theofthecreditcardismostcompounded:C.2.3.Time2.3.1.重要知識點.Annuities年金：requiredpaymentN=numberofperiods4-76I/Y=periodPMT=ofperiodicpaymentFV=valuePV=value考察方法：計算——PV中任意給定四個，求另外一個.Ordinaryannuity后付年金Thecashflowofperiod.Annuitydue先付年金mode)Thecashflow(at).Aperpetuityasetoflevelnever-endingcashflows,withcashflowoccurringperiodAr計算：PV2.3.2.基礎題Q-11.winningahasoptionstogetbonus.Option1:ordinary20annualpaymentsof$2,000.Option2:20annualof$2,000.Option3:Awithannualpaymentsof$2,000.Assumingannualdiscountis5percent,optiononetochoose?OptionOptionC.OptionQ-12.Forplanningpurposes,individualtobeableto€pertheendof20inIntofundaccount,heannualdepositsof€11,606.56endofofhisworkingyears.Whatistheminimumnumberofsuchdepositsneedtotofund6%compoundedallcalculations.295-7630C.31Afinancialto€per8withmadeAssumingdiscountofcompoundedmonthlypresentvalueofclosest€84,484.€365,257.C.€367,083.Q-14.Aclient€inaofdeposit(CD)ofTheannualCDaseparateaannualof4%compoundedthevalueofassetisclosestto:€51,200.00.€51,903.24.C.€58,831.19.Q-15.Aperpetualitsquarterlydividendofquarters.Ifannualof6%compoundedthepresentvalueisclosestto:$31.$126.C.$133.2.4.Ratio,NominalScales2.4.1.重要知識點.Nominal,ordinal,scalesNominalscales:ofmeasurement,them,Ordinalscales(>,<):ofmeasurement,sortdatathatorderedwithsomeHasmodeIntervalscales(>,+,providenotonlyalsothat6-76scalevaluesequal,absolutecanadddeduct.Ratioscales(>,+,-,/):thestrongestofmeasurement.candoallkindsofcalculations.Notes:一般協(xié)會會給出具體場景，讓考生判斷屬于哪種類型。2.4.2.基礎題Q-16.Whichofscalesapoint?Ordinal.Ratio.C.Interval.Q-17.price-earningsintheS&P500thenfirmshighesttolowestShethenumber1tothewiththelowestthenumber2totheThemeasurementscaleusedordinal.C.2.5.RelativeFrequenciesRelativeFrequencies2.5.1.重要知識點.Relativefrequenciesandcumulativefrequencies:Relativeofobservationsinnumberof(theabsolutefrequency)dividedbynumberobservations.Cumulativefrequencies2.5.2.基礎題Q-18.Frequencydistributionssummarizein:atabularoverlappingC.alargenumberof7-76Q-19.theaboutprice-earningthecommonstocksheldaportfolio:Interval7.00-15.0015.00-23.0023.00-31.0031.00-39.00FrequencyI1224118IIIIIIVThecumulativeIIIclosestto:Relative20.00%CumulativeC.85.45%36.00%36.00%22.00%20.00%2.6.Measures2.6.1.重要知識點.MeasuresNXiThearithmeticmean:XinnThemean:XwXwXwXwX)Wii1122nni1NiGXXX...X(X1/NThemean:N123Ni1nTheharmonicmean:XHn(1/X)ii1Harmonicmean≤mean≤mean.PerformancemeasurementThegeometricmeanofannualofperformance.Thearithmeticisbestofnext2.6.2.基礎題Q-20.8-76AssetEquities(70%)Bonds(30%)TimeyearSecondyearThirdyear13%11%12%-5.6%15%-14.86%Theonisclosestto:3.9834%.3.5697%.C.4.5361%.Q-21.Whenanalyzingwhichofcorrect?ThemeanaseriesThemeancompoundofmultipleperiods.C.Themeanterminalvaluemultipleperiods.Q-22.Amanager€ina5pricesinfollowingtable.PurchasePrice12345124.00152.00168.00180.00184.00Thepricepaidtheclosest€134.1841.€158.2971.C.€161.6000.2.7.Describe,CalculateandQuartiles,Quintiles,Decilesand2.7.1.重要知識點.Quantiles9-76Quartile/Quintile/Deciles/PercentileThequintile:60%,orthree-fifthsofobservationslbelowthatvalue.Calculationformula:L=(n+1)y/100,yWhereLpositionexpressediny2.7.2.基礎題Q-23.Whichofmost?Thequintilemedian.Thequintiledecile.C.Thequintilequartile.Q-24.ThefollowingexhibitshowsannualMSCIa10-yearperiod:1234515.25%610.02%720.65%89.57%930.79%12.34%-5.02%16.54%27.37%-40.33%10ThequintileMSCIisclosestto:20.65%.26.03%.C.27.37%.2.8.Measure2.8.1.重要知識點.Measuredispersion:Range=highestvalue-lowestvalue∑?|?MAD=?=1??∑?(???)2?2=?=1?population)sample)??(?2?∑?2=?=.MAD和variance掌握計算和比較：10-76理解：比MAD要好，因為variance是連續(xù)的，處處可導。MAD計算的是絕對值，相對比較繁瑣。但是variance和MAD都是表示風險的。注意MAD≤σ2.8.2.基礎題Q-25.Theaboutofadistributionisthe:providesabouttheshapeofdatadistribution.arithmeticofequaltoone.C.meaneitherlessorequaltostandardQ-26.In2017,ananalystfollowingannualaboutasinceon1January2013:20132014201520162017Portfolio17.00%22.20%25.60%30.40%-19.00%Thedeviationandvarianceofannualtheperiodclosestto:Meanabsolutedeviation13.70%Populationvariance3.12%C.13.70%1.92%15.24%1.54%Q-27.Thefollowingtenobservationsasamplepopulation:Observation1234456789310-2-10-171921-610-15Thesample11.97.12.55.11-76C..Chebyshev’s2.9.1.重要知識點.Chebyshev’s掌握計算及理解：Foroforpopulation),proportionofvaluesthatwithinkstandarddeviationsoftheisleast1–wherekthan1.1P(kXk)1k21k2k個標準差之內(nèi)的概率不小于1，任意k>1）Thisofshapeofthe2.9.2.基礎題Q-28.hadameanofwithaofmonthlyofOver60months,54monthlyawhatisandupperlimitof-2.9315%to4.5315%-2.9395%to4.5315%C.-2.9315%to4.5395%Q-29.whatisofadistributionliesonthat3.16belowmean?44.9928%10.0144%C.5.0072%Q-30.Overthe60months,portfoliohadameanof0.withastandarddeviationofmonthlyof1.18minimumnumberof60monthlyreturnsof-1.00%to2.60%closest20.27.12-76C.34.2.10.Coefficientof&Sharpe2.10.1.重要知識點.Coefficientvariation(CV)theofdeviation)unitofSXXCV100%.TheSharpemeasuresreward,intermsofunitrisk,measuredstandardofRRfPPSharpe沒有實在含義；當小于零時，可能會得到錯誤的結論。2.10.2.基礎題Q-31.Ifrisk-freeisequaltheislessthestandarddeviation,comparedwithSharpethecoefficientofvariationis:GreaterSameC.LessQ-32.thefollowingPortfolioMean(%)Standardof(%)12391820321012Iftheofis5.0percent,thethathadbestperformancebasedontheSharpePortfolioPortfolioC.Portfolio13-76Q-33.thefollowingPortfolioMean(%)Sharpe(%)1210103437Ifrisk-freeof5.0percent,whichcoefficientofvlarger?Portfolio1Portfolio2C.Thesame2.11.and2.11.1.重要知識點.掌握概念：概念：Adistributioniscalled種類：Positively–Adistributionhassmallandaextremegains,(longrighttail)>(mean>median>–Adistributionsmallaextremelosses.(longtail)<0)<median<mode).Kurtosis掌握概念：概念：Itwhetheroradistributionisorlanormaldistribution.種類：LeptokurticNormaldistributionPlatykurticSamplekurtosisExcesskurtosis>3>0=3=0<3<0理解：Adistributionhastails14-76可能在考試中會和合并考核綜合知識2.11.2.基礎題Q-34.Adistributionwithmodemedian4.4,4,distributioncanbedescribedas:longtailinleftpositivelylongtailinpositivelyC.longtailinleftQ-35.ThereaofWhichofdescriptionisOrderData123244546-4-212MeanModeMedianMeanMedianModeC.MeanMedianModeQ-36.Oneexpectedhisyearwouldanormaldistribution.theactualdistributionofonehadkurtosis.giveninformation,whichofbeundervaluedbytheago?ThemeanofoneThemedianoftheyearC.TheextremeQ-37.Areturndistributionwithsmallaextremeismosttobecalled:leptokurtic.positivelyC.Q-38.followingaboutdistributionportfoliosduringtheperiod:Portfolio-0.7kurtosis2.1AB0.85.015-76ThedistributionAmorethanadistributionanddistributionBalongsideofthedistribution.Isthecorrectto:PortfolioPortfolioC.Q-39.Whenadistribtion,thepoweroftheandkurtosisrespectively?4,3.2,4.C.3,4.Q-40.seriesbestdescribedas,mostpart:platykurtoticanormaldistribution).leptokurtoticanormaldistribution).C.mesokurtotictonormaldistributionpeakedness).2.12.Empirical,PrioriSubjective2.12.1.重要知識點.Empirical,Objective客觀概率Empirical經(jīng)驗概率（分析過去歷史，得到將來）e.g.theDowJonesIndustrialclosedhigherthepreviousofeveryTherefore,probabilityofDowgoinguptomorrowtwo-thirds,or66.7%.Priori先驗概率（分析過去歷史，得到過去）e.g.24of30DJIAstocksincreasedvalue.Thus,if1ofstocksisselectedrandom,is80%(24/30)probabilitythatvalueSubjective主觀概率16-76e.g.thatprobabilitytheDowwillclosehigheris90%.2.12.2.基礎題Q-41.Afundmanagertoprobabilityofalosshigher5%onthefundheausestheofoccurrencebasedhistoricaldata.ThesubjectiveaprioriC.empiricalQ-42.Whichprobabilitymostvariespeople?aprioriempiricalC.Asubjective2.13.Properties2.13.1.重要知識點.Properties掌握基本公式：“×”rule:P(AB)=P(B)×P(A|B)=P(A)×P(B|A);“+”rule:P(Aor=P(A)+P(B)-P(AB).MutuallyindependentFormutuallyevents:P(AB)=0,P(Aor=P(A)+P(B)Forindependentevents:P(A|B)=P(A),P(B|A)=P(B),P(AB)=P(A)×P(B)注意：不獨立未必互斥，互斥一定不獨立。.OddsforaneventOddsforevent:P(E)/(1-P(E))Oddsagainstevent:(1-P(E))/P(E)2.13.2.基礎題Q-43.Afterestimatingthethatmanagerwillhisreturninofnextquarters,tothatthemanagerwillbenchmarkovertwo-quarterperiodinAssumingperformanceisindependentofthe17-76whichshouldtheselect?Additionrule.Multiplicationrule.C.probabilityrule.Q-44.TheofpriceisPricechangePrice0.90.6Whatisthesimultaneously?0.540.6C.0.9Q-45.findsthatofAis65%.WhattheofthestockA0.53850.4615C.1.8571Q-46.TheofX0.3=0.3]andprobabilityofYis0.6[P(Y)=ThejointofXY[P(XY)]isXYmostlikely:mutuallyexclusiveevents.independentC.dependentevents.IftwoAandindependenttheprobabilityofAdoesequalprobabilityofB[i.e.,P(A)≠P(B)],probabilityofAthatBhas[i.e.,P(A│B)]isbestdescribedas:P(A).P(B│A).C.P(B).Q-48.Giventhefollowinginthe18-76Portfolio1of3%0.3Either1or2of3%Portfolio1of3%2doeseitherWhattheprobabilitythatof2will0.80.250.520.67C.0.75Q-49.AssumeapriceovernexttwoperiodsisTime=0Time=1Time=2S=242S=2000S=220uS=184dS,=S=169.28TheinitialvalueofisTheprobabilityofupmovegivenperiod30%andtheprobabilityofadownmovegivenperiod70%.Usingthebinomialmodel,theprobabilitythatstock’sprice$202.40oftwoclosestto:14%.21%.C.42%.2.14.Expected2.14.1.重要知識點.ExpectedvalueE(X)Theexpectedvalueofavariableisprobability-weightedthepossibleoftherandomvariable.E(X)PXii.orσThevalueprobability-weightedofsquaredfromexpectedvalue.N2P(XEX)2iii119-762.14.2.基礎題Q-50.analystfollowingofis80%,theofis20%.ais85%ofEPS15%oftheEPSisrecession,10%ofthatEPSis$9.0and90%ofprobabilitythatEPSWhatisvarianceofthisEPS,recession?6.544.28C.3.242.15.Correlation2.15.1.重要知識點.Covariance:Covarianceisameasureofco-movementbetweenrandomvariables.X與Y同向變化，covariance>0.X與Y反向變化，covariance<.,CovariancefromtoCov(X,Y)XE(XYEYTheofarandomvariableitselfisitsownvariance.Cov(X,X)E[(XE(X))(XE(X))](X).Correlation:Correlationmeasuresco-movement(linearassociation)variables.YXCorrelationisanumberbetween?1+1.理解：Ifρx,y=0,aof0variables)linear(straight-line)variables.20-76linearto1,whichalinearIncreasinglystrong(inverse)linearto-1,alinear.Expectedreturn,variancedeviationanE(r)wE(R)piii1nn2wwR,R)ijijpi1j.plot&ofAscatterisathatshowsthebetweenobservationstwoseriesintwodimensions.chartsThreeofcorrelationanalysis.Nonlinearrelationships:variablescanastrongnonlinearandstillaverylowOutliers:smallofeitherextremeorlarge)ofasample.Spuriouscorrelation:Correlationscanspuriousinmisleadinglypointingbetweenvariables.2.15.2.基礎題21-76Q-51.Havingtwohigh-riskinvestmentproducts,investmentarisk-freeofThevalueofcorrelationbetweenthesetwohigh-riskinvestmentproductswillmostbe:-10C.+1Q-52.Thejointprobabilityofreturns,securitiesAandfollows:JointProbabilityFunctionofAandBprobabilities)ReturnonsecurityB=32%ReturnonsecurityB=24%Returnonsecurity24%Returnonsecurity18%0.70000.30ThecovarianceofbetweensecuritiesABclosestto:0.0005.0.0010.C.0.0032.Q-53.analystgatheredinformationaboutthreeeconomicvariables,HenotedwhenevervariableAincreasedbyunit,variableBincreased0.6unitsbutvariableCdecreasedby0.6ThecorrelationbetweenvariablesABandcorrelationvariablesAandCrespectively,areclosestCorrelationbetweenCorrelationbetweenvariablesABvariablesACC.-1.0-0.6-1.0Q-54.individual$300,000inproductsStockExpected6%WeightsStandarddeviation25%Correlation0.280%20%Fund8%30%Whatwillbeofstandarddeviationonexpectedportfolio?6.4%and4.84%.6.2%and4.84%.C.6.4%and22%.22-76Q-55.followingmatrixofreturns:HedgeFundMarketHedgefund225909064MarketTheofhedgeisclosest0.005.0.00625.C.0.75Q-56.Allelsebeingequal,thecorrelationbetweenassets+1.0,benefits:decrease.thesame.C.increase.Q-57.Givenaofsixstocks,uniqueterms,excludingvariances,variance?10.15.C.25.2.16.Bayes’Formula2.16.1.重要知識點.Bayes’formula掌握計算：UpdatedGivenasetofpriorprobabilitiesofifyounewinformation,ruleupdatingyourprobabilityoftheUpdatedofnew=ofinformationunconditionalprobabilityofnewinformation)×priorprobabilityofPPB|APAPA|BPBB)=Posteriorprobability（后驗概率）23-76P(B)P()P(B)P(B)P()P(AB)P(BW)PW)P(BW)PW)1122nPB(B|W)W)(B|W)W)P(B|W)W)1122n2.16.2.基礎題Q-58.WithitispossiblesomenewWhichofmost?(???????????|?????)==C.=?(???????????)?(???????????)?(???????????|?????)?(???????????|?????)?(?????)P(Information)Q-59.theofandpass-throughofIis30%,andthepass-throughof40%.ledbytheinstitutes,amongpeoplewhohaspassedtheFRM,thepass-throughof150%.Sopass-throughofhasalsopassed148%60%C.67%2.17.Principalsof2.17.1.重要知識點.PrincipalsofMultiplicationrule:n12kFactorial:n!n!nn...n!LabelingMultinomial):12knCombination:n!(nr)!r!Cnrrn!Permutation:Prn(nr)!2.17.2.基礎題24-76Q-60.AfirmdecidedtosellofinHowpossible?10.60.C.120.2.18.DiscreteandContinuousRandom2.18.1.重要知識點.DiscreteandcontinuousvariablesDiscretevariables:mostanumberofoutcomesbutdonotnecessarilybelimited.Continuousvariables:cannotdescribepossibleofacontinuousvariableZwithaz,z,...because(z+121z)/2,list,bepossible.2P(x)=0xcanhappen.P(x<X<x)12Probabilityfunction:p(x)=P(X=x)Fordiscretevariables0≤p(x)≤1Σp(x)=1Probabilitydensityf(x)ForcontinuousrandomvariableCumulativeprobabilityfunction(c.p.f):F(x)=P(X<=x)2.18.2.基礎題Q-61.Whichofavariable?Probabilitiesofadice.Pricesofastock.C.Arandomvariableanormaldistribution.Q-62.ThevalueofcumulativedistributionF(x),wherexaparticular25-76adiscreteuniformdistribution:sumsliesbetween0C.decreasesxQ-63.ForacontiuousvaiableX,probabilityXequalsto0is:0.1/n.C.1/x.Q-64.Forabinomialrandomvariablewithfivetrials,andaprobabilityofsuccessoneachtrialof0.50,thedistributionwillbe:C.symmetric.2.19.DiscreteRandomDistribution2.19.1.重要知識點.Discreteuniformvariablewouldaknown,numberofequallytohappen.oneofnhasequalprobability.Bernoullivariable:p(1)==1)=p,p(0)==0)=1-p.BinomialrandomvariableXnumberofnBernoulliP(x)P(Xx)Cxnxp-p)n-x.ExpectationsandvariancesExpectationp(1-p)Bernoullivariable(Y)Binomialvariable(X)Pnpnp(1-p)2.19.2.基礎題Q-65.Whichofcanbeatrial?TheflipofaTheclosingpriceofastock.C.Thepickingofabetween1and10.26-76Q-66.Thefollowingtableshowsthediscreteuniformprobabilitydistributionofgrossprofitsfromthepurchaseofanoption.ProfitCumulativeProfitCumulativeFunction0.1Function0.6$0$2.5$3.0$3.5$4.0$4.5$0.5$1.0$1.5$2.00.51.0TheXwillavalueofeither2or40.2.0.4.C.0.6.Q-67.Iftheprobabilityaunderperformsbenchmarkquarter0.40,thebenchmarkorovertheofayearclosest34.56%.49.92%.C.52.48%.2.20.ContinuousUniformDistribution2.20.1.重要知識點.DefinitionAllofsametheContinuousDistribution'ssupport.PropertiesP(X<aorX>b)=0Foralla≤x<x≤b,P(x≤X≤x)=(x–x-1212212.20.2.基礎題Q-68.thepriceperbarrelofcrudeoilfromwillUSD$150Assumingacontinuousdistribution,thepricebeUSD$16027-76now5.8%.16.7%.C.43.4%.2.21.NormalDistribution2.21.1.重要知識點.PropertiesX~N(μ,σ2)Symmetricaldistribution:skewness=0,kurtosis=3Alinearcombinationoformorenormalvariablesdistributed.thevaluesofxfrommean,probabilitydensitysmallerandsmallerbutpositive..Confidence68%confidenceis-σ,μ+σ]90%confidenceis–1.65σ,μ+1.65σ]95%confidenceis–1.96σ,μ+1.96σ]99%confidenceis–2.58σ,μ+2.58σ].StandardizationIfX~N(μ,σ2),Z=(Xμ)/σ~.CumulativeforanormalF(-z)=1-F(z)P(Z>z)=1–2.21.2.基礎題Q-69.Thenumberofadistribution3.2.C.1.Q-70.Aadistribution,aof20%astandarddeviationofWhatiscriticalvalueprobabilitywillinof28-76+0.30C.-0.3Q-71.Theofaanormaldistribution,withmeanof13%anditsofGiventhez-table,theprobabilitybetween7%19%to:CumulativeaStandardNormalDistributionP(Z≤z)=N(z)z≥0z00.010.020.030.040.050.060.070.080.091.200.88490.88690.88880.89070.89250.89440.89620.89800.89970.90151.300.90320.90490.90660.90820.90990.91150.91310.91470.91620.91771.400.91920.92070.92220.92360.92510.92650.92790.92920.93060.93191.500.93320.93450.93570.93700.93820.93940.94060.94180.94290.94411.600.94520.94630.94740.94840.94950.95050.95150.95250.95350.95451.700.95540.95640.95730.95820.95910.95990.96080.96160.96250.96331.800.96410.96490.96560.96640.96710.96780.96860.96930.96990.970683.84%.76.98%.C.93.32%.Q-72.astandardnormaldistribution,theprobabilitythatarandomvariablewithin1to2P(1<?<2)?13.5%27%C.15.5%2.22.SafetyFirst2.22.1.重要知識點.SFR掌握計算及理解：E(R)-R/:thethepLpShortfallrisk:R=thresholdlevelminimumLsafetyoptimal29-76probabilitythatRbelowlevel,R.Lsymbols,objectiveistochooseaP(R<R).PL.SFR與Sharpe的區(qū)別E(R)-R/pLpPE(R)-R/PFSharpewillbeaspecialofifr=FL2.22.2.基礎題Q-73.On1January2014,thevalueofis$90,000.Theplansdonatetocharityinsuranceaccounton31December2014,meanwhilehedoesyear-endvaluebebelow$90,000.Ifexpectedontheexistingis14%avarianceof0.0225,thethatbeusedthebasedonclosest0.193.0.465.C.0.415.Q-74.totheofearningleast6%hereachUsingsafetycriterion,whichoffollowingportfoliosismostappropriatechoice?ExpectedreturnStandarddeviationPortfoliovalue1230.450.7424%42%PortfolioPortfolioC.Portfolio30-762.23.LognormalDistribution2.23.1.重要知識點.LognormaldistributionDefinition:Ifisnormal,Xislognormal,whichistodescribepriceofBoundedfrombelowbytheofvariablesthatlognormaldistributionpositive,soitmodelingprices.XRightStockpricedistributionl,whileofnormaldistribution.2.23.2.基礎題Q-75.Intonormaldistributions,lognormaldistributions:havecannotbeC.describingassetthanassetprices.2.24.MonteCarloandHistorical2.24.1.重要知識點.LognormaldistributionMonteCarlotoanumberofspecifiedprobabilitydistribution(s)totheofItisusedinplanning,management,andinvaluingcomplexsecurities;Limitations:TheofCarlosimulationverycomplexassumeaparameterdistributioninadvance.MonteCarlosimulationprovidesonlystatisticalnotresults.HistoricalsimulationistosamplingadataHistoricalsimulationisbutonlysample31-76Limitations:ComparedwithCarlosimulation,historicaldoesnotitselftoifanalyses.2.24.2.基礎題Q-76.ACarlosimulationuseddirectlyprovidevaluationsofcalloptions.simulateafromofC.testsensitivityofamodeltoassumptions.2.25.Cross-SectionalvsTime2.25.1.重要知識點.Time-seriesAtimeseriesisasequenceofintervalsoftime(suchahistoricalseriesofmonthlystock.Cross-sectionalCross-sectionalsomeofindividuals,geographicalorcompaniesasinglepointin2.25.2.基礎題collectsrelatingtocommonlyusedofandachosenof300Thedatacomethoseyear2013annualdatabesttimeseries.longitudinal.C.crosssectional.2.26.CentralLimitTheorem2.26.1.重要知識點.CentraltheoremDefinition:Thesamplingdistributionofsampleapproachesadistributionsamplebecomeslarge30);Theofsamplemeandistribution=μ;Thevarianceofsample32-762distribution=σ/n..StandardofsampleKnownvariance:/nxss/nxUnknownvariance:2.26.2.基礎題Q-78.WhichofbestdescribeofasampleSamplingStandardofsampleC.Standarddeviationof2Q-79.Ahasanormaldistributionwithμandvarianceσ.Thesamplingdistributionofcomputedsamplesofpopulationhave:thesamedistributiontheitsequalpopulationmean.C.itsvarianceequalpopulationvariance.Q-80.Thelimitisbestdescribedthesamplingdistributionofthesamplenormallarge-sizesamples:ifthedistributionissymmetrical.populationsdescribeddistribution.C.ifthedistributionisnormal.Q-81.Thefollowingsampleof10isselectedapopulation.Thevariance1121-73-860-7422Theofsampleclosest10.89.3.44.C.7.SamplingandEstimation33-762.27.1.重要知識點.ConceptofsamplingestimationMethodssimplerandomsampling,samplingsampling.DefinitionofSamplingofaThesamplingofadistributionofdistinctvaluescomputedsamplesofthesamepopulation.Sampleitselfavariable,thusspecificSamplingerror:samplingerrorofmean=samplemean-populationmean..ThepropertiesofanUnbiasedness:theexpectedvalueofestimatorequalsEfficiency:unbiasedestimatorefficientifotherunbiasedthesameparameterasamplingdistributionsmallervariance.Consistency:Aestimatorisonewhichprobabilityofclosethevalueoftheparametersampleincreases(thedeviationofdecreasessampleincreases).thesamplesizeincreases,standarderrorofthesamplemean.Pointstatistic,fromusedestimatethe.Intervalestimation:Levelofsignificance(alpha)DegreeofConfidence(1-alpha)Confidence=Estimate+/-×Standard.BiasessamplingData-miningbias:comesfindingsearchingbias,out-of-sampleandsignificanceSamplebias:dataleadsanalysis,callresultingsampleselectionbias.Survivorshipbias:usuallysampleselectiononlyportfolioLook-aheadbias:biasiftheusesdata34-76participantstheparticipantsmodel.Time-periodbias:time-periodbiasispresentifperiodusedresultstime-periodspecificoriftheperiodincludesaIflong,cannotthe2.27.2.基礎題Q-82.Whichofbestdescribesasamplemean?C.parameterQ-83.allsampledaconcentratingintailsofsamplingdistribution.Whichofthefollowingsamplingused?StratifiedsamplingsamplingC.SimplesamplingQ-84.Asampleof64hasameanof8.Thedeviationofsample15.Whichofbestofthe95%confidencesample?4.32511.675.4.90611.094.C.3.03112.969Q-85.AllelseheldofaconfidenceameanmosttobesmallerifsamplelargerandtheofconfidencelargerandtheofconfidenceC.smallerdegreeofconfidenceisQ-86.IfestimatorissamplesizewillincreaseaccuracyofefficiencyofC.unbiasednessof35-76Q-87.analystallelseequal,increasingsamplesizewilldecreasebothstandardandtheoftheconfidenceThestatementiscorrectto:boththeerrorandconfidencethestandardbutincorrecttoconfidenceC.theconfidencebutincorrecttotheQ-88.Areportlong-termallpubliclyfirmsindustrysusceptibleto:look-aheadbias.survivorshipbias.C.intergenerationalmining.2.28.Student’s-distribution2.28.1.重要知識點.-distributionSymmetricalDegreesofn-1Lessanormaldistributiontails”)thedegreesofincrease,t-distributionstandardnormal2.28.2.基礎題Q-89.UsefollowingvaluesaStudent'st-distributiontoa95%confidenceintervalmeanasamplesizeof10,asampleofasamplestandarddeviationof12.thatthesampleisnormallydistributedandvarianceisnottProbabilities)DegreesFreedomp=0.101.383p=0.051.833p=0.0252.262p=0.012.821910111.3721.8122.2282.7641.3631.7962.2012.718The95%confidenceclosestlowerof–upperboundof36-76lowerof–upperboundofC.lowerof–upperboundofQ-90.Compareddistribution,whichoffollowingaboutt-distributionisifthesignificanceofthesethesame?ItwithnormalItstailstailsofnormaldistribution.C.Itlessprobabilityinnormaldistribution.Q-91.analystdegreesoffreedomincrease,at-distributionwillbecomemoretailsoft-distributionbecomelessstatementcorrecttot-distribution:Becomingmorepeaked?Tailsbecominglessfat?C.YesYesYesYes2.29.Hypothesis2.29.1.重要知識點.StepsStep1:HypothesisStep2:ChooseandStep3:FindCriticalvalueStep4:FormDecisionStep5:a.HypothesisX0;T-Statistic=0XT-=/nsnSqua