assetsMeanCov {fAssets} | R Documentation |
Estimates the mean and/or covariance matrix of a time series of assets by traditional and robust methods.
assetsMeanCov(x, method = c("cov", "mve", "mcd", "MCD", "OGK", "nnve", "shrink", "bagged"), check = TRUE, force = TRUE, baggedR = 100, sigmamu = scaleTau2, alpha = 1/2, ...) getCenterRob(object) getCovRob(object)
x |
any rectangular time series object which can be converted by the
function as.matrix() into a matrix object, e.g. like an
object of class timeSeries , data.frame , or mts .
|
method |
a character string, whicht determines how to compute the covariance
matix. If method="cov" is selected then the standard
covariance will be computed by R's base function cov , if
method="shrink" is selected then the covariance will be
computed using the shrinkage approach as suggested in Schaefer and
Strimmer [2005], if method="bagged" is selected then the
covariance will be calculated from the bootstrap aggregated (bagged)
version of the covariance estimator.
|
check |
a logical flag. Should the covariance matrix be tested to be
positive definite? By default TRUE .
|
force |
a logical flag. Should the covariance matrix be forced to be
positive definite? By default TRUE .
|
baggedR |
when methode="bagged" , an integer value, the number of
bootstrap replicates, by default 100.
|
sigmamu |
when methode="OGK" , a function that computes univariate robust
location and scale estimates. By default it should return a single
numeric value containing the robust scale (standard deviation)
estimate. When mu.too is true (the default), sigmamu()
should return a numeric vector of length 2 containing robust location
and scale estimates. See scaleTau2 , s_Qn , s_Sn ,
s_mad or s_IQR for examples to be used as sigmamu
argument.
For details we refer to the help pages of the R-package
robustbase .
|
object |
a list as returned by the function assetsMeanCov .
|
alpha |
when methode="MCD" , a numeric parameter controlling the size
of the subsets over which the determinant is minimized, i.e.,
alpha*n observations are used for computing the determinant.
Allowed values are between 0.5 and 1 and the default is 0.5.
For details we refer to the help pages of the R-package
robustbase .
|
... |
optional arguments to be passed to the underlying estimators.
For details we refer to the manual pages of the functions
cov.rob for arguments "mve" and "mcd" in
the R package MASS , to the functions
covMcd and covOGK in the R package robustbase .
|
assetsMeanCov
returns a list with for entries named center
cov
,
mu
and Sigma
. The list may have a character vector
attributed with additional control parameters.
getCenterRob
extracts the center from an object as returned by the function
assetsMeanCov
.
getCovRob
extracts the covariance from an object as returned by the function
assetsMeanCov
.
Juliane Schaefer and Korbinian Strimmer for R's corpcov
package,
Diethelm Wuertz for the Rmetrics port.
Breiman L. (1996); Bagging Predictors, Machine Learning 24, 123–140.
Ledoit O., Wolf. M. (2003); ImprovedEestimation of the Covariance Matrix of Stock Returns with an Application to Portfolio Selection, Journal of Empirical Finance 10, 503–621.
Schaefer J., Strimmer K. (2005); A Shrinkage Approach to Large-Scale Covariance Estimation and Implications for Functional Genomics, Statist. Appl. Genet. Mol. Biol. 4, 32.
Wuertz, D., Chalabi, Y., Chen W., Ellis A. (2009); Portfolio Optimization with R/Rmetrics, Rmetrics eBook, Rmetrics Association and Finance Online, Zurich.
## LPP - LPP = as.timeSeries(data(LPP2005REC))[, 1:6] colnames(LPP) ## Sample Covariance Estimation: assetsMeanCov(LPP) ## Shrinked Estimation: shrink = assetsMeanCov(LPP, "shrink") shrink ## Extract Covariance Matrix: getCovRob(shrink)