MTS: comVol – R documentation

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MTS

comVol

Common Volatility

Description

Compute the principal volatility components based on the residuals of a VAR(p) model.

Usage

comVol(rtn, m = 10, p = 1, stand = FALSE)

Arguments

`rtn`	A T-by-k data matrix of k-dimensional asset returns
`m`	The number of lags used to compute generalized cross-Kurtosis matrix
`p`	VAR order for the mean equation
`stand`	A logical switch to standardize the returns

Details

Perform a VAR(p) fit, if any. Then, use the residual series to perform principal volatility component analysis. The ARCH test statistics are also computed for the sample principal components

Value

`residuals`	The residuals of a VAR(p) fit
`values`	Eigenvalues of the principal volatility component analysis
`vectors`	Eigenvectors of the principal volatility component analysis
`M`	The transformation matrix

Author(s)

Ruey S. Tsay and Y.B. Hu

References

Tsay (2014, Chapter 7)

Examples

data("mts-examples",package="MTS")
zt=diffM(log(qgdp[,3:5]))
m1=comVol(zt,p=2)
names(m1)

MTS

All-Purpose Toolkit for Analyzing Multivariate Time Series (MTS) and Estimating Multivariate Volatility Models

v1.0

Artistic License 2.0

Authors

Ruey S. Tsay and David Wood

Initial release

2018-10-8