Clean Covariance Matrices Using Random Matrix Theory and Shrinkage Estimators for Portfolio Optimization

Portfolio optimization typically requires an estimate of a covariance matrix of asset returns. There are many approaches for constructing such a covariance matrix, some using the sample covariance matrix as a starting point. This package provides implementations for two such methods: random matrix theory and shrinkage estimation. Each method attempts to clean or remove noise related to the sampling process from the sample covariance matrix.

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Tools for denoising covariance and correlation matrices


Reference manual

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2.1.7 by Brian Lee Yung Rowe, a year ago

Browse source code at

Authors: Brian Lee Yung Rowe

Documentation:   PDF Manual  

Task views: Empirical Finance

GPL-3 license

Imports lambda.r,, futile.logger, futile.matrix, tawny.types, zoo, xts, PerformanceAnalytics, quantmod

Suggests testit

See at CRAN