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tawny (version 2.1.2)

denoise: Remove 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

Run this code
data(sp500.subset)

h <- sp500.subset
p <- TawnyPortfolio(h, 150)
r1 <- denoise(p, SampleDenoiser())
r2 <- denoise(p, EmpiricalDenoiser())
r3 <- denoise(p, ShrinkageDenoiser())
r4 <- denoise(p, RandomMatrixDenoiser())

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