covmat: Covariance Matrix Estimation
Version 1.0

We implement a collection of techniques for estimating covariance matrices. Covariance matrices can be built using missing data. Stambaugh Estimation and FMMC methods can be used to construct such matrices. Covariance matrices can be built by denoising or shrinking the eigenvalues of a sample covariance matrix. Such techniques work by exploiting the tools in Random Matrix Theory to analyse the distribution of eigenvalues. Covariance matrices can also be built assuming that data has many underlying regimes. Each regime is allowed to follow a Dynamic Conditional Correlation model. Robust covariance matrices can be constructed by multivariate cleaning and smoothing of noisy data.

Browse man pages Browse package API and functions Browse package files

AuthorRohit Arora
Date of publication2015-09-28 18:46:22
MaintainerRohit Arora <emailrohitarora@gmail.com>
LicenseArtistic-2.0
Version1.0
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("covmat")

Man pages

compareCov: This is a utility function to compare two covariance matrices
dow30data: Symbol Data
estRMT: Denoising of Covariance matrix using Random Matrix Theory
estSpikedCovariance: (Donoho, Gavish, and Johnstone, 2013)
etfdata: Symbol Data
factor.data: Factor Data
isdccfit: Fit an Independent Regime Switching Model
missingdata: Symbol Data
plot.isdcc: Implied State plot
plotmissing: Plot data to visualize missing values
plot.RMT: Eigenvalue plot
plotSpikedCovariance: Eigenvalue plot. Similar to figure 1 in the paper
rmtdata: Simulated data for Spiked Covarianve Model
robustMultExpSmoothing: Robust Multivariate Exponential Smoothing
smoothing.matrix: Optimal Smoothing Matrix

Functions

TransitionProb Source code
biweight Source code
c.ell Source code
compareCov Man page Source code
detectSpikes Source code
dow30data Man page
ell.lambda Source code
estRMT Man page Source code
estSpikedCovariance Man page Source code
etfdata Man page
factor.data Man page
gamma_cp Source code
getMPfit Source code
givens.rotation Source code
helper.loglik Source code
huber Source code
isdccfit Man page Source code
missingdata Man page
mp.obj Source code
nitFilterProb Source code
nitQ Source code
obj Source code
obj.helper Source code
optim.params Source code
orthogonal.matrix Source code
plot.RMT Man page Source code
plot.isdcc Man page Source code
plot.spikedCovariance Source code
plotSpikedCovariance Man page Source code
plotmissing Man page Source code
rmtdata Man page
robustMultExpSmoothing Man page Source code
s.ell Source code
sdcc.loglik Source code
shrink.eigen Source code
shrink.eigen2 Source code
sigma.sq.est Source code
smoothing.matrix Man page Source code Source code

Files

inst
inst/scripts
inst/scripts/getFactorData.R
inst/scripts/getSymbolData.R
inst/doc
inst/doc/CovarianceEstimation.pdf
inst/doc/CovarianceEstimation.R
inst/doc/CovarianceEstimation.Rmd
NAMESPACE
data
data/dow30data.RData
data/rmtdata.RData
data/etfdata.RData
data/factordata.RData
data/missingdata.RData
R
R/spikedCovariance.R
R/covUitls.R
R/robustCoux.R
R/randomMatrix.R
R/datasets.R
R/independentSwitchingDCC.R
vignettes
vignettes/CovarianceEstimation_cache
vignettes/CovarianceEstimation_cache/rmt_strategy_rets.RData
vignettes/CovarianceEstimation_cache/croux_smoothfit.RData
vignettes/CovarianceEstimation_cache/Thumbs.db
vignettes/CovarianceEstimation_cache/Shrinkage.png
vignettes/CovarianceEstimation_cache/isdcc_model.RData
vignettes/CovarianceEstimation_cache/isdcc_strategy_rets.RData
vignettes/Thumbs.db
vignettes/references.bib
vignettes/CovarianceEstimation.Rmd
README.md
MD5
build
build/vignette.rds
DESCRIPTION
man
man/compareCov.Rd
man/factor.data.Rd
man/dow30data.Rd
man/missingdata.Rd
man/plotSpikedCovariance.Rd
man/robustMultExpSmoothing.Rd
man/plot.isdcc.Rd
man/etfdata.Rd
man/plot.RMT.Rd
man/estRMT.Rd
man/estSpikedCovariance.Rd
man/smoothing.matrix.Rd
man/plotmissing.Rd
man/isdccfit.Rd
man/rmtdata.Rd
covmat documentation built on May 20, 2017, 2:16 a.m.