Code covered by the BSD License
Highlights from
Risk and Asset Allocation
- ...
- Addition(x,y);
- Adendotd(dense, d, sparAd, Ab...
- Amul(At,dense,x,transp)
- BivStandardTPDF(x,y,r,nu)
- ChoiceGeneric(Market,Investor... little perturbation to the right of the frontier
- ChoiceOptimal(Market,Investor...
- ChoiceOptimal(Market,Investor...
- ChoiceOptimal(Market,Investor...
- ChoiceOptimal(Market,Investor...
- ChoiceOptimal(Market,Investor...
- ChoiceSubOptimal(Market,Inves... this is the equally weighted allocation ....
- Constraints(x,P)
- Cost(Allocation,Market,Invest...
- Cost(Allocation,Market,Invest...
- Cost(Allocation,Market,Invest...
- Cost(Allocation,Market,Invest...
- DecisionBayesParameters(Marke... % estimate market parameters
- DecisionBestPerfomer(Market,I... % find index of best performer
- DecisionPrior(Market,Investor... prior is the equally weighted allocation
- DecisionSample(Market,Investo... % estimate market parameters
- E=TwoDimEllipsoid(Location,Sq...
- E=TwoDimEllipsoid(Location,Sq...
- E=TwoDimEllipsoid(Location,Sq...
- EMforT(x,Nu,Tolerance)
- EfficientFrontier(NumPortf, C... This function returns the NumPortf x 1 vector expected returns,
- EfficientFrontier(NumPortf, C... This function returns the NumPortf x 1 vector expected returns,
- EfficientFrontier(NumPortf, C... This function returns the NumPortf x 1 vector expected returns,
- EfficientFrontier(NumPortf, C... This function returns the NumPortf x 1 vector expected returns,
- EfficientFrontier(NumPortf, C... % determine exp value of minimum-variance portfolio
- EfficientFrontier(NumPortf, E... This function returns the NumPortf x 1 vector expected returns,
- EfficientFrontier(NumPortf, E... This function returns the NumPortf x 1 vector expected returns,
- EfficientFrontierNoConstr(Tar... determine exp value of minimum-variance portfolio
- G_Hat_1(X)
- G_Hat_2(X)
- InvWishCorr(S,Nu,NumCases)
- L=Lklhd(Theta,X,T,N,VecIndex) this function computes the likelihood of an N-variate normal sample of length T
- LogLik(x,Nu,Mu,Sigma)
- LogLik(x,Nu,Mu,Sigma)
- LogTCopulaPDF(u,nu,Mu,Sigma) this function computes the pdf of the copula of the log-t distribution
- LogTPDF(x,nu,Mu,Sigma) this function computes the pdf of the N-variate log-t distribution
- LognormalCopulaPDF(u,Mu,Sigma... this function computes the pdf of the copula of the lognormal distribution
- LognormalPDF(x,Mu,Sigma) this function computes the pdf of the N-variate lognormal distribution
- MktProjection(Exp_Yr_Comp_Ret...
- MleRecursionForT(x,Nu,Toleran... this function computes recursively the ML estimators of location and scatter
- NormalCopulaCDF(u,Mu,Sigma)
- NormalCopulaCDF(u,Mu,Sigma)
- NormalCopulaPDF(u,Mu,Sigma) this function computes the pdf of the copula of the normal distribution
- NormalPDF(x,Mu,Sigma) this function computes the pdf of the N-variate normal distribution
- OutlierCutoff(d,d_0)
- PlotFrontier(Portfolios)
- PlotFrontier(Portfolios)
- PlotNIWMarginals(Mu_Simul,Inv... this function plots numerically and analytically the marginal pdf of
- PopK(d,x,K,lpq)
- PriorPDF(Theta,Theta_0,c_0,N,... This function computes the joint pdf of the normal-inverse-Wishart distribution. For notation and theory
- ProcessNPlotFrontier(T_0,Nu_0...
- Q=QuantileNormalMixture(c,ps,... this function computes the quantile for a mixture of normals
- Rejected=RejectOutlier(Sample... this function finds the "worst" outlier in a time series.
- RunAnalysis(Dates,Data) this function performs simple invariance (i.i.d.) tests on a time series
- Satisfaction(Allocation,Marke...
- Satisfaction(Allocation,Marke...
- Satisfaction(Allocation,Marke...
- Satisfaction(Allocation,Marke...
- Satisfaction(Allocation,Marke...
- TCopulaCDF(u,nu,Mu,Sigma)
- TCopulaPDF(u,nu,Mu,Sigma) this function computes the pdf of the copula of the t distribution
- TPDF(x,nu,Mu,Sigma) this function computes the pdf of the N-variate t distribution
- TwoDimEllipsoid(Location,Squa... this function computes the location-dispersion ellipsoid
- TwoDimEllipsoid(Location,Squa... this function computes the location-dispersion ellipsoid
- TwoDimEllipsoid(Location,Squa... this function computes the location-dispersion ellipsoid
- UniformEllipticalPDF(x,Mu,Sig... this function computes the pdf of the N-variate
- WishartPDF(W,nu,S) this function computes the pdf of the NxN-variate Wishart distribution
- [Dates,ZeroPrices]=ProcessDB(... fixed-income invariance quest from
- [E,V,MV_ExpectedValue,MV_Vari... compute useful parameters
- [E,V,MV_ExpectedValue,MV_Vari... compute useful parameters
- [E,V,MV_ExpectedValue,MV_Vari... compute useful parameters
- [E_EM, S_EM, Y, CountLoop]=EM... this function implements the Expectation-Maximization (EM) algorithm to recover
- [E_hat,V_hat]=UnevenSeriesEst... this function estimates the parameters of a multivariate normal distribution
- [Expected_Value,Covariance,St... this function computes analytically the summary statistics of a lognormal variable
- [M,S]=Log2Lin(Mu,Sigma)
- [M,S]=Log2Lin(Mu,Sigma)
- [MVE_Location,MVE_Dispersion]... this function computes the minimum volume ellipsoid for a given time series.
- [Mu,Sigma,InvSigma]=randNIW(M... this function generates a multivariate i.i.d. sample of lenght J from the
- [Mu,Sigma]=HubertM(x) this function computes the location and scatter parameters
- [Mu,Sigma]=NormalMLE(X)
- [Mu_shr, Sigma_shr]=ShrinkLoc... % standard sample estimate
- [Nu,Mu,Sigma]=FitT(x)
- [Nu,Mu,Sigma]=StudentMLE(x) This function computes the maximum-likelihood estimate of the
- [newAt,newb,newc,newK,prepinf... [newAt,newb,newc,newK,prepinfo]=preprocessSDP(At,b,c,K)
- [x,info]=RobSocpMVPortf(m,q,T... this function transforms the SOCP mean-variance problem in SeDuMi format
- [x,y,K]=postprocessSDP(newx,n... [x,y,K]=postprocessSDP(newx,newy,prepinfo,newK)
- a2=PlotEstimatorStressTest(Lo... plot loss
- a2=PlotEstimatorStressTest(Lo... plot loss
- a2=PlotEstimatorStressTest(Lo... plot loss
- a2=PlotEstimatorStressTest(Lo... plot loss
- a2=PlotEstimatorStressTest(Lo... plot loss
- a2=PlotEstimatorStressTest(Lo... plot loss
- asmDxq(d, x, K, ddotx)
- blkchol(L,X,pars,absd)
- bwblkslv(L,b) BWBLKSLV Solves block sparse upper-triangular system.
- bwdpr1(Lden, b)
- cellK(x,K)
- checkpars(pars,lponly) pars = checkpars(pars,lponly)
- ddot(d,X,blkstart, Xblkjc)
- deninfac(symLden, L,dense,DAt...
- dpr1fact(x, d, Lsym, smult, m...
- e=FitError(gamma,X,Y,Correlat...
- eigK(x,K)
- extractA(At,Ajc,blk0,blk1,blk... Apart = extractA(At,Ajc,blk0,blk1,blkstart[,blkstart2])
- eyeK(K)
- findblks(At,Ablkjc,blk0,blk1,... Ablk = findblks(At,Ablkjc,blk0,blk1,blkstart)
- finsymbden(LAD,perm,dz,firstq... Lden = finsymbden(LAD,perm,dz,firstq)
- frameit(lab,frmq,frms,K)
- fwblkslv(L,b) FWBLKSLV Solves block sparse upper-triangular system.
- fwdpr1(Lden, b)
- getDAt(At,Ablk,colsel, d,ud,K...
- getDAtm(A,Ablkjc,dense,DAtden...
- getada1(ADA, A,Ajc2,perm, d, ...
- getada2(ADA, DAt,Aord, K)
- getada3(ADA, A,Ajc1,Aord, uds...
- getdense(At,Ablkjc,K,pars)
- getsymbada(At,Ablkjc,DAt,psdb... SYMBADA = getsymbada(At,Ajc,DAt,psdblkstart)
- givensrot(gjc,g,x,K)
- h_ellips=TwoDimEllipsoid(Loca... this function computes the location-dispersion ellipsoid
- incorder(At,Ajc1,ifirst)
- invcholfac(u,K, perm)
- iswnbr(w,thetaSQR)
- loopPcg(L,Lden,At,dense,d, DA...
- makereal(x,K,cpx)
- mat(x,n)
- maxstep(dx,x,auxx,K)
- my_fprintf(fid, varargin) This function is needed because Matlab R2006B does not support fprintf with
- optstep(A,b,c, y0,y,d,v,dxmdz...
- ordmmdmex(adjncy) perm = ordmmdmex(adjncy)
- partitA(At,blkstart) Ablkjc = partitA(At,blkstart)
- posttransfo(x,y,prep,K,pars)
- pretransfo(At,b,c,K,pars)
- psdeig(x,K)
- psdfactor(x,K)
- psdinvjmul(xlab,xfrm, y, K)
- psdmul(x,y, K)
- psdscale(ud,x,K [,transp])
- qblkmul(mu,d,blkstart)
- qframeit(lab,frmq,K)
- qinvjmul(labx,frmx,b,K)
- qjmul(x,y,K)
- qreshape(x,flag, K)
- quadadd(xhi,xlo,y)
- r2=R2(I_k,Cov_XX,Cov_XF,Cov_F...
- rotlorentz(c,K)
- sddir(L,Lden,Lsd,pv,...
- sdfactor(L,Lden, dense,DAt, d...
- sdinit(At,b,c,dense,K,pars)
- sedumi(A,b,c,K,pars)
- sortnnz(At,Ajc1,Ajc2)
- sparbwslv(L,b) SPARBWSLV Solves block sparse upper-triangular system.
- sparfwslv(L,b, ysymb) SPARFWSLV Solves block sparse upper-triangular system.
- sparsity=spars(x) Returns the sparsity of the matrix/vector x. It works for sparse and dense
- sqrtinv(q,vlab,K)
- statsK(K)
- stepdif(d,R,y0,x,y,z,dy0,dx,d...
- symbchol(X,cachsz)
- symbcholden(L,dense,DAt) Lden = symbcholden(L,dense,DAt)
- symfctmex(adjncy, perm, cachs...
- tdet(x,K)
- triumtriu(r,u,K)
- trydif(t,wrIN,wIN, x,z, pars,...
- updtransfo(x,z,w, dIN,K)
- urotorder(u,K, maxu,permIN)
- vec(X)
- veccomplex(x,cpx,K)
- vecsym(x,K)
- vectril(x,K)
- whichcpx(K)
- widelen(xc,zc,y0, dx,dz,dy0,d...
- wrapPcg(L,Lden,At,dense,d, DA...
- Contents.m
- EstimateNGeneratePrior.m
- PlotBlackLittAllocation.m
- PlotDeceptionInMV.m
- PlotEvaluationBayesian.m
- PlotEvaluationGeneric.m
- PlotEvaluationPrior.m
- PlotEvaluationSample.m
- PlotSampleInMV.m
- PlotTotalRetsVsRelativeRets.m
- S_AffineConstraint.m
- S_AnalyzeLognormalCorrelation...
- S_AnalyzeNIWPriorPosterior.m
- S_AnalyzeNormalCorrelation.m
- S_AssessNModifyViews.m
- S_BlackLitterman.m
- S_BlackLittermanVsBruteForce.m
- S_BondPrices.m
- S_COP.m
- S_CaseStudy.m
- S_CaseStudyPCAEmprical.m
- S_CaseStudyPCALimitContinuum.m
- S_CaseStudySwapDistribution.m
- S_CopulaMarginalDecomposition...
- S_CornishFisher.m
- S_DeceptionInMV.m
- S_DifferentHorizons.m
- S_DisplayCopulaCDF.m
- S_DisplayCopulaPDF.m
- S_DisplayLogTPDF.m
- S_DisplayLognormalPDF.m
- S_DisplayMleRecursionForT.m
- S_DisplayNormalPDF.m
- S_DisplayRobustness.m
- S_DisplayRobustness.m
- S_DisplayTPDF.m
- S_DisplayUniformPDF.m
- S_DisplayWishartPDF.m
- S_DiversificationCorrelation.m
- S_DiversificationNumAssets.m
- S_ES_Contributions.m
- S_ES_is_HomogConcave.m
- S_EVT.m
- S_EigenvalueDispersion.m
- S_EllipsoidGeometryVsStatisti...
- S_EllipsoidLogNormal.m
- S_EllipsoidNormal.m
- S_Elliptical2Dim.m
- S_Elliptical3Dim.m
- S_EllipticalNDim.m
- S_EquitiesInvariants.m
- S_EquivarianceLogNormal.m
- S_EquivarianceNormal.m
- S_EstimateExpectedValueEvalua...
- S_EvaluationBayesian.m
- S_EvaluationGeneric.m
- S_EvaluationPrior.m
- S_EvaluationSample.m
- S_ExponentialUtil_is_TranslIn...
- S_FixedIncomeInvariants.m
- S_Gamma.m
- S_GammaCdf.m
- S_GenericCopula.m
- S_Grades.m
- S_HighBreakdownMVE.m
- S_Introduction.m
- S_KendallTau.m
- S_KernelQuantile.m
- S_LeadingExample.m
- S_LogNormal.m
- S_LogT.m
- S_LogTCopulaSimul.m
- S_Lognormal.m
- S_LognormalCopulaSimul.m
- S_MCMC.m
- S_MissingValuesEM.m
- S_Motivation.m
- S_MotivationsBL.m
- S_NoEquivarianceMedian.m
- S_Normal.m
- S_Normal.m
- S_NormalCDF.m
- S_NormalCopulaSimul.m
- S_NormalMatrix.m
- S_OLS.m
- S_OptionsInvariants.m
- S_OrderStatistics.m
- S_OrderStatisticsPDFCentralGa...
- S_OrderStatisticsPDFLogn.m
- S_OrderStatisticsPDFStudentT.m
- S_PCA2Dim.m
- S_PCA3Dim.m
- S_PCAvsRegression.m
- S_PowerUtil_ContributionsToSa...
- S_PowerUtil_is_Homogeneous.m
- S_PricesVsReturns.m
- S_PricingAnyOrder.m
- S_PricingCallOption.m
- S_PriorCorrelationParametric.m
- S_PriorCorrelationUniform.m
- S_Projection_Beta.m
- S_Projection_Gamma.m
- S_Projection_Lognormal.m
- S_Projection_NonParam.m
- S_Projection_T.m
- S_ProspectTheory_isnot_Concav...
- S_Regression2Dim.m
- S_Regression3Dim.m
- S_Regularization.m
- S_RobustBayesMV.m
- S_RobustBayesMVSimulations.m
- S_RobustBayesSnP.m
- S_RobustMV.m
- S_SampleMVCoordinates.m
- S_SampleMeanCov.m
- S_SatisfactionVsCorrelation.m
- S_SelectFactors.m
- S_ShrinkageEstimators.m
- S_SimulationsVsAnalytical.m
- S_SimulationsVsAnalytical.m
- S_SpearmanRho.m
- S_SphericallySymmetric.m
- S_StochasticDominanceNormNorm...
- S_StochasticDominanceNormT.m
- S_StochasticDominanceUniBiMod...
- S_StressCorrelation.m
- S_StressCorrelation.m
- S_StressCorrelation.m
- S_StressCorrelation.m
- S_StressLognormalMu.m
- S_StressLognormalSigma.m
- S_StressNormalMu.m
- S_StressNormalSigma.m
- S_StudentT.m
- S_StudentT.m
- S_SwaptionsInvariants.m
- S_TCDF.m
- S_TCopulaSimul.m
- S_TotalRetsVsRelativeRets.m
- S_UnevenSeries.m
- S_Uniform.m
- S_Uniform.m
- S_UniformEllipsoid.m
- S_UniformEllipsoid2.m
- S_VaRContributions.m
- S_VaRContributions_TdistrMark...
- S_VaR_is_HomogNotConcave.m
- S_Wishart.m
- S_WishartCopulaSimul.m
- ada_pcg.m
- install_sedumi.m
- View all files
from
Risk and Asset Allocation
by Attilio Meucci
Software for quantitative portfolio and risk management |
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