Search results for "correlation matrice"

showing 2 items of 2 documents

Cluster analysis for portfolio optimization

2005

We consider the problem of the statistical uncertainty of the correlation matrix in the optimization of a financial portfolio. We show that the use of clustering algorithms can improve the reliability of the portfolio in terms of the ratio between predicted and realized risk. Bootstrap analysis indicates that this improvement is obtained in a wide range of the parameters N (number of assets) and T (investment horizon). The predicted and realized risk level and the relative portfolio composition of the selected portfolio for a given value of the portfolio return are also investigated for each considered filtering method.

Physics - Physics and SocietyEconomics and EconometricsControl and OptimizationMathematics::Optimization and ControlFOS: Physical sciencesStatistics::Other StatisticsPhysics and Society (physics.soc-ph)random matrix theoryportfolio optimizationcorrelation matriceRate of return on a portfolioFOS: Economics and businessComputer Science::Computational Engineering Finance and ScienceEconometricsEconomicsCluster analysisModern portfolio theoryStatistical Finance (q-fin.ST)Covariance matrixApplied MathematicsQuantitative Finance - Statistical FinanceCondensed Matter - Other Condensed MatterPortfolioPortfolio optimizationVolatility (finance)clustering methodRandom matrixOther Condensed Matter (cond-mat.other)
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The affine equivariant sign covariance matrix: asymptotic behavior and efficiencies

2003

We consider the affine equivariant sign covariance matrix (SCM) introduced by Visuri et al. (J. Statist. Plann. Inference 91 (2000) 557). The population SCM is shown to be proportional to the inverse of the regular covariance matrix. The eigenvectors and standardized eigenvalues of the covariance, matrix can thus be derived from the SCM. We also construct an estimate of the covariance and correlation matrix based on the SCM. The influence functions and limiting distributions of the SCM and its eigenvectors and eigenvalues are found. Limiting efficiencies are given in multivariate normal and t-distribution cases. The estimates are highly efficient in the multivariate normal case and perform …

Statistics and ProbabilityCovariance functionaffine equivarianceinfluence functionMultivariate normal distributionrobustnessComputer Science::Human-Computer InteractionEfficiencyestimatorsEstimation of covariance matricesScatter matrixStatisticsAffine equivarianceApplied mathematicsCMA-ESMultivariate signCovariance and correlation matricesRobustnessmultivariate medianMathematicsprincipal componentsInfluence functionNumerical AnalysisMultivariate medianCovariance matrixcovariance and correlation matricesdiscriminant-analysisCovarianceComputer Science::Otherdispersion matricesefficiencyLaw of total covariancemultivariate locationtestsStatistics Probability and Uncertaintyeigenvectors and eigenvaluesEigenvectors and eigenvaluesmultivariate signJournal of Multivariate Analysis
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