Plotting volatilities for Bayesian DCC-GARCH model

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Description

Produces a plot of time series and the volatilities. This is a particular case of plotVol function.

Usage

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## S3 method for class 'bayesDccGarch'
plot(x, ts.names=NULL, colors = c("grey","red"), ...)

Arguments

x

Object of class “bayesDccGarch”.

ts.names

a vector of length k with the names of the time series.

colors

a vector with the colors for plotting the returns and volatilities.

...

additional arguments for plot function

Author(s)

Ricardo Sandes Ehlers, Jose Augusto Fiorucci and Francisco Louzada

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. http://dx.doi.org/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. http://adsabs.harvard.edu/abs/2014arXiv1412.2967F.

See Also

bayesDccGarch-package, bayesDccGarch, plotVol

Examples

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data(DaxCacNik)

mY = DaxCacNik[1:10,] # more data is necessary

out = bayesDccGarch(mY, nSim=1000)
plot(out)