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    FRM一级培训项目:数量分析(学习笔记).docx

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    FRM一级培训项目:数量分析(学习笔记).docx

    FRM-级培训项目一.3T相比率非每件W雅住二2个工具FDFC斤三I,公为贝叩斯Terms>Ranomexperiment(gfl1Anobservationormeasurementprocesswithmultiplebutuncertainoutcomes.>Outcome(S®>Theresultofasingletrial.Forexample,ifwerolltwodices,anoutcomemightbe3and4;adifferentoutcomemightbe5and2>EVent停件)1表列CUtaPme(结果)的集台Theresultthatreflectsnone,one,ormoreoutcomesinthesamplespace.EventsCanbesimpleorcompound.Aneventisasubsetofthesample<ace.IfverolltwodicesiaexampleOfaneventmightberolling7in2【M1.Mutuallyexclusiveevents?件).Eventsthatcannotbothhappenatrhesametime/gg曲eegO15彘各事件)ThoseindudeMPGSSibgProbabilityrobAbrHfyE11-",*'”',.'*IT*lIMff".U,rm1lITlf',".,n,1»<»1flnhH11fpr11prH4f*4(口,l,hIljlyC口I,1IIMUhJj,ut?IrtltrEJ3H.fu,,JN火*中汜B片N,火*F=%二不=儿=4义勿工错题回饭,A%5pphaWy¥&mii$t出缪岳VProbabilityess-thanOri»tt七桃titc/rchoHttjcjje"Jir¾t Prybgbility 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令ProbabilityandProbabilityDistributions>PropertiesofCDFF-=andF+J=Q丹的耸我力皿eF(X)isaR11jf萩虱functionsuchthatifx?>x1thenF(x,)闵F(XJF、,P(X>k)=l-F(k)灾P(XIX42)=F(Xz)-F的);今 Probability and Probability Distributions> Ml4AttPrChnhililydEJiy functi” Pdj)Lw少Ie We lake X from 1 or 2 WlthIhUamenrQu)bity We take YP(Aft)-FlA)Y产'吗产7IQtJl Pl10254-A0.7S <20.25 I0 25n仁口and Y=9 50100hofn Xl vth tfe sn<' DrobabilHvEa>jSl rW<rtj尸 DefinitiOn 也> Properties Of HlQ bivariate or joint probability mass function_(PMF)r 引尸P(X=LaW)。卜PCY) Ve for all pairs of X and YThiS is because all probabilities are nonnegMiVa lf(,) =1PIXHI)=0 5令 Probability and Probability DistributionsMarginal probability distribution Of X and YVaIueofXfx)Value of Y电)10.501075205020.25Sum1.00 ILOO> MMgi“I Probability function> Definition of marginal probability functionKX) = Tf(X1Y)InrallXf(Y) = f(X,Y)furaljr令 Probability and Probability Distributions> Statistical Independence23fY)11/91/93/921/91/91/93/931/91/91/93/93/93/93/91 Definiti 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I uh' *. bw1M% I "f ' JJ M又无扬叶"B九d川Gi相 伸3 7出个同令 Kurtosis失小LeptokurtNormalDistributionA R口竺kurtjjjtbul2n has mofg frequent PxrtrPmeIY IdrgR deviatiom Qorii411gJI£3ii£KaD)a normal distribution.Q A2re 妨e true CkSVtm Oj retur右 t ItORUrtCC 弓 We %wne nwmtj.v帆We SlMote -the V>R. 7e / ½R. <s Mck/aFNb件 3F >Sf*K<. 但现晞l+令CoskewnessandCokurtosis"急IMeSS罩磁魄SThethirdcrosscennimomentisTef曰TedtoasCeSkeWness.eThefourthcrosscentralmomentisreferredtoascokurtosis.>Riskmodelswithtime-varyingvolatilityortime-varyingcorrelationcandisplayawiderangeofbehaviorsWIthveryfewfreeprmeters4ihi-tail8沱Hi5(庙豳联性)aCopulascanalsobeusedtodescribecomplexinteractionsbetweenvariablesthatgobeyondcovariances,andhavebecomePoPUlarinriskmanagementinrecentyears.3CoskewnessandCokurtosisExampleA«umcfourscriesofhindrclurn5(A.氏&D)whorethemean,standarddcvalin.skew,andku11oisarealltheampjbutonlytheordcfofctussdifferentUmeIAonr.DCDIilliriCA*日COIK3”153%I1<1、53".心3-72%2J3H-,/100%33Hj153%458%S3M,00%38,00%519%19%G77%72%72%67153、1M%153%38%T(1537»I95%Thetwoportfolios(A+BandC«D)havethesamemeanandstandarddeviation,buttheskewsoftheportfoliosaredifferent.令CoskewnessandCokurtosisSCaURfPloISshowthedifferencebetweenBversusAandDversusC:/AandB:theirbestpositivereturnsoccurduringthesametimeperiod,butIheirworstnegativeretf11soccurindifferentperiods.ThiscausesthedistributionOfpointstobeskev/edtowardthetop-rightofthechart.CandD.theirworstnegativereturnsoccurinthesameperiodbuttherbestpositivereturnsoccurindifferentperiods.Inthesecondchart,thepointsareskewedtowardrhebottom-leftof(hechart令CoskewnessandCokurtosisThereasontheabovechartslookdifferentorthe侔独曲t>ereturnsQflhetw。portfoliosaredifferent,isbecausetheCQSkCWne55betweentheportfoliosisdifferent.Notices,毛尸。GandF依andD)«碱,w一0S8”099Qf3ttWQVa11aDieS.)d!U/Forexample力灯=EK胃尸¾说明辞手无处游,9Ja)=EIX-讲IL()yS=日X-EX),疝ThenontrivialCpkurlgsisCrftwoVanaMes:(and玉,/ForexampleKXXxY二SmWn终=tyj令BestLinearUnbiasedEstimator(BLUE)川口3g""rBLUlnolhrrproprr1yof»»"<v"1p%hr114tr.h11r>1111(jfjlIhliphoui<i"«iHfrhr114tr(*,itc;“itjrus<das.lf"%Mh"Mhcn11ltl11r.a)erlata)Utheestimator«5theh,J.v<(ablrk(1.h%lh<,finrrnuu;WMlnrr>),(xhfl

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