search for: garch11

Displaying 4 results from an estimated 4 matches for "garch11".

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2009 Jun 23
1
Forecast GARCH model
...the residuals of my time serie (X). X is an ARMA(1,1) process. Now I want to do a n-step forecast for X, knowing these processes. How can I do this? I know that there's a command: predict() for ARIMA processes and so on, but what about GARCH? I've got: arma=arima(x, order=c(1,0,1)) (...) garch11<-garch(residuals(x),order = c(1, 1)) summary(garch11) How can I forecast the conditional variance and my serie X? Many thanks Ana [[alternative HTML version deleted]]
2017 Jun 07
0
Getting forecast values using DCC GARCH fit
...x vibration_x Speed 1 2017-05-16 17:53:00 -0.132 421.4189 2 2017-05-16 17:54:00 -0.296 1296.8882 3 2017-05-16 17:55:00 -0.572 0.0000 4 2017-05-16 17:56:00 -0.736 1254.2695 5 2017-05-16 17:57:00 0.000 0.0000 6 2017-05-16 17:58:00 0.000 0.0000 > garch11.spec = ugarchspec(mean.model = list(armaOrder = c(1,1)), variance.model = list(garchOrder = c(1,1), model = "sGARCH"), distribution.model = "norm") > dcc.garch11.spec = dccspec(uspec = multispec( replicate(2...
2017 Jun 07
0
Getting forecast values using DCC GARCH fit
...x vibration_x Speed 1 2017-05-16 17:53:00 -0.132 421.4189 2 2017-05-16 17:54:00 -0.296 1296.8882 3 2017-05-16 17:55:00 -0.572 0.0000 4 2017-05-16 17:56:00 -0.736 1254.2695 5 2017-05-16 17:57:00 0.000 0.0000 6 2017-05-16 17:58:00 0.000 0.0000 > garch11.spec = ugarchspec(mean.model = list(armaOrder = c(1,1)), variance.model = list(garchOrder = c(1,1), model = "sGARCH"), distribution.model = "norm") > dcc.garch11.spec = dccspec(uspec = multispec( replicate(2...
2011 Feb 15
1
Estimation of an GARCH model with conditional skewness and kurtosis
Hello, I'm quite new to R but tried to learn as much as possible in the last few months. My problem is that I would like to estimate the model of Leon et al. (2005). I have shortly summarised the most important equations in the following pdf file: http://hannes.fedorapeople.org/leon2005.pdf My main question is now how could I introduce these two additional terms into the Likelihood