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.
| 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 |
| Published: | 2018-04-20 |
| Author: | Brian Lee Yung Rowe |
| Maintainer: | Brian Lee Yung Rowe <r at zatonovo.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Materials: | README |
| In views: | Finance |
| CRAN checks: | tawny results |
| Reference manual: | tawny.pdf |
| Package source: | tawny_2.1.7.tar.gz |
| Windows binaries: | r-devel: tawny_2.1.7.zip, r-devel-gcc8: tawny_2.1.7.zip, r-release: tawny_2.1.7.zip, r-oldrel: tawny_2.1.7.zip |
| OS X binaries: | r-release: tawny_2.1.7.tgz, r-oldrel: tawny_2.1.7.tgz |
| Old sources: | tawny archive |
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