plot.bayesDccGarch {bayesDccGarch} | R Documentation |
Produces a plot of time series and the volatilities. This is a particular case of plotVol
function.
## S3 method for class 'bayesDccGarch' plot(x, ts.names=NULL, colors = c("grey","red"), ...)
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 |
Ricardo Sandes Ehlers, Jose Augusto Fiorucci and Francisco Louzada
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.
bayesDccGarch-package
, bayesDccGarch
, plotVol
data(DaxCacNik) mY = DaxCacNik[1:10,] # more data is necessary out = bayesDccGarch(mY, nSim=1000) plot(out)