一级前导班-数量分析

1、TopicWeightingsinCFALevelStudyEthics&alStudy2-StudyTopicWeightingsinCFALevelStudyEthics&alStudy2-Study4-Study7-lReportingStudyCorporate7StudyPortfolio Management and Wealth 7Study13-EquityStudy15-Study5StudyAlternative32-iveTimeValueR5TheTimeiveTimeValueR5TheTimeValueofR6DiscountedCashFlowProbabilit

2、y&R7isticalConceptsandMarketR8ProbabilityR9CommonProbabilityR10lingandR11Hypothesis3-Time4-Time4- TimeValueofRequiredrateofreturnaffectedbythesupplyanddemandof TimeValueofRequiredrateofreturnaffectedbythesupplyanddemandofhethetinvestorsandsaversrequiretogetthemtolendtheirusuallyforparticularDiscount

3、rateerestrateweusetodiscountpaymentstobeusuallyerchangeablywitherestOpportunitycostalsounderstoodasaformerestrate.Itisthetinvestorsobychoosingaparticularcourseof5- TimeValueofe TimeValueoferequiredrateofNominalrisk-freerate=realrisk-freerate+expectedinflationerestrateona=nominalrisk-freerate+default

4、riskpremium+liquiditypremium+maturityrisk6-TimeValueofEARm1EARr TimeValueofEARm1EARr m那么如果是semi, m=2; 如果是quarterly, -如果是连续复利，公式则变为=e定性（EAR和计息次数有关Thegreaterthecompoundingfrequency,thegreatertheEARwillincomparisontotheed7-m TimeValueofFuturevalue(FV):Amount TimeValueofFuturevalue(FV):Amounttowhichinve

5、stmentgrowsafteroneorcompounding Presentvalue(PV):CurrentvalueofsomefuturecashAnnuities:isastreamofequalcashgiventoccursatervalsover内容N=numberofI/YerestratePV=presentPMT=amountofeachperiodicFV=future8- TimeValueofAnleof TimeValueofAnleofordinaryannuities（后付年金le:WhatstheFVofanordinaryyearat tpays100o

6、feachof thenext3years,giventhediscountrateSolutions:enterrelevantdatafor N=3,I/Y=10,PMT=-100,PV=0,9-TimeValueofTimeValueofDefinition:anannuitywheretheannuitypaymentsoccuratbeginningofeachcompoundingMeasure1:puttherelevantheBGNmodeandMeasure2:treatasanordinaryannuityandsimplymultipleresultingPVby10-l

7、e:TimeValueofAcompanyplanstoborrow$50,000le:TimeValueofAcompanyplanstoborrow$50,000forfiveyears.Thecompanyslendthemoneyatarateof9%andttheloanbepaidoffinequal end-of-year payments. Calculate the amount of the payment companymustmakeinordertofullyamortizethisloaninfiveyears.N=5,I/Y=9,PV=50,000,FV=0;CP

8、T:PMT=-tUsingtheloanheprecedingle,determinetheamountiftherequiresthecompanytomakequarterlyN=54=20,I/Y=9/4=2.25,PV=50,000,FV=0;CPT:PMT=-房贷月供问题买了一套价值100万的房子，首付比例30%，她70房贷月供问题买了一套价值100万的房子，首付比例30%，她70万，？款的年利率为6.2%，期限为20年。她每月月末需还利用TVM功能N=20*12=240, I/Y=6.2/12, PV=700,000, CPTPMT=-还完第一个月以后，还有多少本金余额没有还？第一

9、个月中本金还了多利息还了多少利用AMORT功能：（2ND P1=1，P2=1，BAL=698,520.5485，PRN=-=-12-le今年60岁，她从今天开始即将退休。如果从退休开始每le今年60岁，她从今天开始即将退休。如果从退休开始每年初都要支取10万块钱的话，假设回报率为现需要准来支持她未来20BGN模式：(2NDBGN2NDSET2ND利用TVM功能N=20, I/Y=4, 13-教育金的女儿今年要上大学，她现在开始每年年初都要教育金的女儿今年要上大学，她现在开始每年年初都要给女儿支付万块钱的教育金，一直持续到女儿大学毕业，为期4年，如市场利率为现在需要为女儿准备多少教育金BGN模式

10、：(2NDBGN2NDSET2ND利用TVM功能N=4, I/Y=4, 14-TimeValueofAboutofmoneyatrpetuityisaltpaysafixedervalsoveran infiniteperiodofAAAATimeValueofAboutofmoneyatrpetuityisaltpaysafixedervalsoveran infiniteperiodofAAAAAAA0PV1 = A/(1+r) PV2=A/(1+r)2 PV3=A/(1+r)3 PV4 =1234567AAAAAPV (1r)PV A1 (1(11 (1ArrPV APV (2)15-D

11、iscountedCashFlowernalRateofWhenDiscountedCashFlowernalRateofWhenNPV=0,thediscount16-NPV 0CF0 1 2 .(1(1(1(1tNPV CF0 1 1 22 .NN t (1r(1r(1r(1rtle:DiscountedCashFlow花了10万块钱买了一le:DiscountedCashFlow花了10万块钱买了一品在这5年里每年年末分别可以产品，期限为5年。这产带来的收益为：3万、2万赚？17-le:DiscountedCashFlow18-按解显CF2NDCLR 3 2le:DiscountedCa

12、shFlow18-按解显CF2NDCLR 3 2 2 3 4NPV5折现率 计算IRR计算DiscountedCashFlowDefine:theDiscountedCashFlowDefine:theholdingperiodreturnissimplythehevalueofaninvestmentovertheperioditis19-HPR1 P0le:DiscountedCashFlowAstockisle:DiscountedCashFlowAstockispurchasedfor$30andissoldfor$33sixmonthslater,during which time

13、it paid $0.50 in dividends. Calculate the holding periodHPRP0 33300.5 20-Sistical21-Sistical21- isticalSummarizetheimportantcharacteristicsoflargedataInferential isticalSummarizetheimportantcharacteristicsoflargedataInferentialMakeforecasts,estimates,orjudgmentsaboutalargesetdataonthebasisoftheistic

14、alcharacteristicsofasmaller(a22- isticalAmeasureusedtodescribe isticalAmeasureusedtodescribeacharacteristicofapopulationreferredtoasahesame taparametermaybeusedtodescribecharacteristicofapopulation,aleisticisusedtoacharacteristicofa23- isticalMeasures isticalMeasuresofcentraltendency:mode,median,24-

15、SisticalThearithmeticTheweightedThegeometricSisticalThearithmeticTheweightedThegeometricTheharmonic25-XH n(1/ XiiNGN X1X2X3.XN (Xi)1/inXW wiXi (w1X1w2X2 wnXn iN Xi X i 1n isticalStandardXYZCorp.AnnualStockAtthedistributionofXYZ stockreturnsisapopulation,what ispopulation isticalStandardXYZCorp.Annua

16、lStockAtthedistributionofXYZ stockreturnsisapopulation,what ispopulationA.B.C.AtthedistributionofXYZ stockreturnsisale,thele varianceclosetA.B.C.26-N(X iForpopulation:2 NNXi MAD inn(X XiFor le:s2 nRangeumvalue minimum isticalCoefficientofvariationmeasurestheamount isticalCoefficientofvariationmeasur

17、estheamountofindistributionrelativetothedistributionsmean.(relative)Thesharpratiomeasuressreturnperunitof27-Sharp ratio= RP -CV=X isticalNegative(left)itive(right) itiveskewed：Modemedianmean,having isticalNegative(left)itive(right) itiveskewed：Modemedianmediamean,havingaleftfat28- isticalLeptokurtic

18、vs.Itdealswith isticalLeptokurticvs.Itdealswithwhetherornotadistributionismoreorlessnanormal29-Normalle isticalFatA isticalFatAleptokurticreturndistributionhasmorefrequentextremelylargedeviationsfromn anormal 30-31-31-32-32-33-33-34-34- BasicRandomvariableiseis BasicRandomvariableiseisanobservedvalu

19、eofarandomMutuallyexclusiveeventscannotbothhappenatthesameExhaustive eventsinclude TwoDefiningPropertiesof0P(E)P(E1)+P(E2)+35-UnconditionalProbability(marginalUnconditionalProbability(marginalprobability):Conditionalprobability:36-probability:P(AB) Multiplication rule:probability:P(AB) Multiplicatio

20、n rule:IfAandBaremutuallyexclusiveevents,AdditionleastoneoftwoeventswillIfAandBaremutuallyexclusiveevents,then: P(A or B)=P(A)+P(B)37-TheoccurrenceofAhas noinfluenceTheoccurrenceofAhas noinfluenceofontheoccurrenceofP(A|B)=P(A)orP(AorB)=P(A)+P(B)-IndependenceandMutuallyExclusivearequiteIfexclusive,mu

21、stnotCauseexclusivemeansifAoccur,Bcannotoccur,Ainfluents38-E(X ) P(Xi ExpectedE(X ) P(Xi Expected*P(xi ) x1 *P(x1)*P(x2)*P(xn NP(X EX22ii39-40-40- ProbabilityDescribetheprobabilitiesofall ProbabilityDescribetheprobabilitiesofallthe esforaDiscreteandcontinuousrandomDiscreterandomvariables:thenumberes

22、cancounted,andforitivee,thereisameasurableContinuous variables: the number of eveniflowerandupperboundsexist.P(x)=0eventhoughxcanPesis41-ForFordiscreterandom0p(x)Probabilitydensityfunction(p.d.f):Forcontinuousrandomvariable42- DiscreteAdiscreteuniform DiscreteAdiscreteuniformrandomvariableisoneforwh

23、ichtheforesforadiscreterandomvariableareForle,considerthediscreteuniformprobabilitydefinedasX=1,2,3,4,5,Here,theprobabilityforeisequalto0.243- ContinuousUniform-isdefined ContinuousUniform-isdefinedoveratspansnsomelowerlimit,a,andupperb,whichserveastheparametersofthePropertiesofContinuousuniformFora

24、llax1x2P(Xb)=P(x1 X x2)(x2x1)/(b44-正态正态分布的前世今生45- The TheofthedensityxXN(,Thetailsgetthinandgotozerobutextend近yasympotic46- The68%90%95%99% The68%90%95%99%ervalis ervalis ervalerval , 1.65, 1.651.96,1.96U-U-U-U-47-StandardnormalN(0,1)or StandardnormalN(0,1)or X Standardization:ifXN( ,),ZP(Zz)=148-49

25、-49-Definition: IflnXisnormal,thenXDefinition: IflnXisnormal,thenXislognormal,whichisusedto describe the price of assetRightBoundedfrombelowbyzero,soitisusefulforingasset50-Slingand51-Slingand51- lingandSlingandSimplerandom lingandSlingandSimplerandomStratifiedrandomling:toseparatetheogroupsbasedono

26、neormoredistinguishingcharacteristics.andSlingerror:lingerrorofthemean=lemean-52- lingandTime-seriesconsistofobservationstaken lingandTime-seriesconsistofobservationstakenriodoftimeatspecificequallyspacedaleofobservationstakenatasingle53-Time-series Cross-sectional acollectionofdatarecordedovera per

27、iod of timea collection of daakenat asingle of time. lingandestimate:theistic, lingandestimate:theistic,computedfromleinformation,isusedtoestimatethepopulationervalestimate:arangeofvaluesconstructedfromledatasoparameteroccurshatrangeataspecified54- lingandData-mining Referstoresultswheretheisticalsi

28、gnificance lingandData-mining ReferstoresultswheretheisticalsignificanceofthepatternoverestimatedbecausetheresultswerefoundthroughdataleselectionSSomedataissystematicallyexcludedfromthe the lack of availability.Survivorship ysis,usuallybecauseUsuallyderivesfroms Look-ahead leselectionforonlytheexist

29、ingportfolioOccurswhenastudytestsarelationshipusings available on the test date.Time-period lehatwasnotTimeperiodoverwhich thedataisgatherediseithertooshortortoolong.If the time period istoo short, research results may reflect phenomena specificttimeperiod,orperhapsevendata55-56-56-HypothesisThestep

30、sofhypothesisStepHypothesisThestepsofhypothesisStepStepStepStepStep57-Formulate a Take a sarrive at DonotSelectalevelof Identifythetest enulland 58-58-aredeterminedbyeractionofsupplyandOnlyparticipantswhoaredeterminedbyeractionofsupplyandOnlyparticipantswhoactuallytradeaffect,andinformedparticipantstendtotradeingreaterPriceandvolumereflectthecollectivebehaviorofbuyersandAMarketreflectbothrationalandirrationalinvestorInvestorbehaviorisrendsandttrendtoandcanbeidentifiedand