varcov {LFUrmutils}R Documentation

Variance-covariance matrix

Description

Function to extract the variance-covariance matrix of multivariate volatility models. Currently only implemented for models of class MultiEWMA.

Usage

varcov(object, ...)
## S3 method for class 'MultiEWMA'
varcov(object, offdiagonal = TRUE, duplicates = TRUE, ...)

Arguments

object

Output of a multivariate volatility model.

offdiagonal

Whether diagonal elements should be kept or not. TRUE (the default) or FALSE.

duplicates

Whether duplicate off-diagonal elements should be kept or not. TRUE (the default) or FALSE.

...

Arguments passed to methods.

Details

Returns the variance-covariance matrix of a multivariate volatility model.

Value

A multivariate zoo object. Each row of the output objects represents the correlation matrix (or elements thereof) of the corresponding day.

Note

If the full conditional variance-covariance matrices are needed, users can also use link{fitted}, which is slightly faster. However, in comparison to fitted, varcov gives the user more control over the extracted elements of the conditional variance-covariance matrices. Moreover, in future releases of this package, varcov may be defined for other multivariate volatility models as well. In this case, the function will provide a convenient infrastructure to better compare the output of these models.

Author(s)

Bernhard Eder

References

Danielsson (2011). Financial Risk Forecasting. Wiley. Chichester. Jorion (2007). Value at Risk, 3rd. McGraw-Hill. New York. Ruppert and Matteson (2015). Statistics and Data Analysis for Financial Engineering, 2nd. Springer. New York.

See Also

MultiEWMA, ccor

Examples

# Load returns
data("CRSPday_zoo")
y <- CRSPday_zoo

# Compute multivariate EWMA model
ewma <- MultiEWMA(y, center = TRUE)

# Extract variance covariance matrix
EWMAvc <- varcov(ewma)
plot(EWMAvc)

[Package LFUrmutils version 0.1-2 Index]