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tawny (version 2.1.2)

Provides various portfolio optimization strategies including random matrix theory and shrinkage estimators

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.

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Version

Install

install.packages('tawny')

Monthly Downloads

12

Version

2.1.2

License

GPL-3

Maintainer

Brian Lee Yung Rowe

Last Published

May 7th, 2014

Functions in tawny (2.1.2)

sp500

A (mostly complete) subset of the SP500 with 250 data points
tawny-package

Provides various portfolio optimization strategies including random matrix theory and shrinkage estimators
denoise

Remove noise from a correlation matrix using RMT to identify the noise
divergence

Measure the divergence and stability between two correlation matrices
sp500.subset

A subset of the SP500 with 200 data points
optimizePortfolio

Optimize a portfolio using the specified correlation filter
getPortfolioReturns

Utility functions for creating portfolios of returns and other functions
cov_shrink

Shrink the covariance matrix towards some global mean