builtin {fAssets}

Estimation of Mean and Covariances of Asset Sets

Description

Helper functions for estimating the mean and/or covariance matrix of a time series of assets by traditional and robust methods.

Usage

.baggedMeanCov(x, baggedR = 100, ...)
.bayesSteinMeanCov(x, ...)
.cov.arw(x, center, cov, alpha = 0.025, pcrit = NULL)
.cov.nnve(datamat, k = 12, pnoise = 0.05, emconv = 0.001, bound = 1.5,
extension = TRUE, devsm = 0.01)
.cov.shrink(x, lambda, verbose = FALSE)
.donostahMeanCov(x, ...)
.ledoitWolfMeanCov(x, ...)
.rmtMeanCov(x, ...)
.studentMeanCov(x, ...)

Arguments

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.

baggedR

when methode="bagged", an integer value, the number of bootstrap replicates, by default 100.

center

specifies for a data set (n x p), the initial location estimator(1 x p).

cov

Initial scatter estimator (p x p).

alpha

Maximum thresholding proportion (optional scalar, default: alpha = 0.025).

pcrit

critical value for outlier probability (optional scalar, default values from simulations).

datamat

a matrix in which each row represents an observation or point and each column represents a variable.

k

desired number of nearest neighbors (default is 12).

pnoise

percent of added noise

emconv

convergence tolerance for EM.

bound

value used to identify surges in variance caused by outliers wrongly included as signal points (bound = 1.5 means a 50 percent increase).

extension

whether or not to continue after reaching the last chi-square distance. The default is to continue, which is indicated by setting extension= TRUE.

devsm

when extension = TRUE, the algorithm stops if the relative difference in variance is less than devsm (default is 0.01).

lambda

the correlation shrinkage intensity (range 0-1). If lambda is not specified (the default) it is estimated using an analytic formula from Schaefer and Strimmer (2005) - see details below. For lambda=0 the empirical correlations are recovered.

verbose

a logical indicating whether to print progress information to the stdout.

...

optional arguments to be passed to the underlying estimators. For details we refer to the manual pages of the functions cov.rob in the R package MASS, to the functions covMcd and covOGK in the R package robustbase.

Value

The functions return a list with elements containing the covariance and mean. The list may contain additional control parameters.