plotVol function

Plotting volatilities of time series

Plotting method for volatilities of time series.

plotVol(mY, vol, ts.names=paste("TS_", 1:ncol(mY), sep=""), colors = c("grey","red"), ...)

Arguments

• mY: a matrix of the data ($n \times k$).
• vol: a matrix ($n \times k$) with the volatility estimates.
• ts.names: a vector of length $k$ with the names of the time series.
• colors: a vector with name of the colors for plotting the returns and volatilities.
• ...: additional arguments for plot function

Returns

No return value

References

Fioruci, J.A., Ehlers, R.S., Andrade Filho, M.G. Bayesian multivariate GARCH models with dynamic correlations and asymmetric error distributions, Journal of Applied Statistics, 41(2), 320--331, 2014a. doi:10.1080/02664763.2013.839635

Fioruci, J.A., Ehlers, R.S., Louzada, F. BayesDccGarch - An Implementation of Multivariate GARCH DCC Models, ArXiv e-prints, 2014b. https://ui.adsabs.harvard.edu/abs/2014arXiv1412.2967F/abstract.

Author(s)

Ricardo Sandes Ehlers, Jose Augusto Fiorucci and Francisco Louzada

See Also

bayesDccGarch-package, bayesDccGarch, plot.bayesDccGarch

Examples

data(DaxCacNik)

mY = DaxCacNik

out = bayesDccGarch(mY)

## The code
plotVol(mY, out$H[,c("H_1,1","H_2,2","H_3,3")], c("DAX","CAC40","NIKKEI"))

## gives the result of ##
plot(out)