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

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install.packages("tawny")

2.1.7 by Brian Lee Yung Rowe, a year ago


Browse source code at https://github.com/cran/tawny


Authors: Brian Lee Yung Rowe


Documentation:   PDF Manual  


Task views: Empirical Finance


GPL-3 license


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

Suggests testit


See at CRAN