tawny (version 2.0.2)

denoise: Filter noise from a correlation matrix using RMT to identify the noise

Description

Used to filter out all eigenvalues below k*. At a later date this will become pluggable so other people can use their own functions and/or provide their own parameters to this function.

Usage

denoise(...)
cor.empirical(h)
cor.clean(es, lambda.plus=1.6, h=NULL)
normalize(...)

Arguments

h

A returns object

es

Eigenvalues and vectors

lambda.plus

Eigenvalue cutoff for cleaning

...

Arguments

Value

• A cleaned correlation matrix.

Details

denoise(p, estimator) normalize(h)

These are different implementations of the denoise function based on the estimator provided.

See Also

tawny, optimizePortfolio

Examples

# This is autorun outside of examples
tawny:::.init()
data(sp500.subset)

h <- sp500.subset
p <- create(TawnyPortfolio, h, 150)
r1 <- denoise(p, create(SampleFilter))

r2 <- denoise(p, create(EmpiricalFilter))

r3 <- denoise(p, create(ShrinkageFilter))

r4 <- denoise(p, create(RandomMatrixFilter))