Package: tawny
Type: Package
Title: Clean Covariance Matrices Using Random Matrix Theory and
        Shrinkage Estimators for Portfolio Optimization
Version: 2.1.7
Depends: R (>= 3.0.0)
Imports: lambda.r (>= 1.1.6), lambda.tools, futile.logger (>= 1.3.7),
        futile.matrix (>= 1.2.1), tawny.types (>= 1.1.2), zoo, xts,
        PerformanceAnalytics, quantmod
Suggests: testit
Date: 2018-04-20
Author: Brian Lee Yung Rowe
Maintainer: Brian Lee Yung Rowe <r@zatonovo.com>
Description: 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.
License: GPL-3
NeedsCompilation: no
Packaged: 2018-04-20 19:20:33 UTC; brian
Repository: CRAN
Date/Publication: 2018-04-20 19:35:55 UTC