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: | 2.1.6 |

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: | RUnit |

Published: | 2016-07-10 |

Author: | Brian Lee Yung Rowe |

Maintainer: | Brian Lee Yung Rowe <r at zatonovo.com> |

BugReports: | NA |

License: | GPL-3 |

URL: | NA |

NeedsCompilation: | no |

Materials: | README |

In views: | Finance |

CRAN checks: | tawny results |

Reference manual: | tawny.pdf |

Package source: | tawny_2.1.6.tar.gz |

Windows binaries: | r-devel: tawny_2.1.6.zip, r-release: tawny_2.1.6.zip, r-oldrel: tawny_2.1.6.zip |

OS X Mavericks binaries: | r-release: tawny_2.1.6.tgz, r-oldrel: tawny_2.1.6.tgz |

Old sources: | tawny archive |