Hello, Yuhan:
If I wanted to get something sensible today, I'd do ordinary least
squares using lm(y~x), the garchFit on the residuals. This will give
you a reasonable answer except that the confidence intervals from "lm"
will not be accurate. I'd want to do normal probability plots of the
residuals and whitened residuals. Then I might also do a Monte Carlo to
evaluate the distribution of paramter estim
If I wanted to go beyond this, I might write my own likelihood
function and use, e.g., the maxLik package to get the MLEs, etc.
However before I did that, I would do a more careful search of
capabilities in contributed packages, something like the following:
library(RSiteSearch) # to search help pages of contributed packagee
gar <- RSiteSearch.function('GARCH') # for GARCH
HTML(gar) # to display the results in a web browser
ar <- RSiteSearch.function('ARMA') # Search for ARMA
ari <- RSiteSearch.function('ARIMA') # or ARIMA
ar. <- ar|ari # for help pages containing either ARMA or ARIMA
ar.gar <- ar.&gar # for help pages containing both ARMA / ARIMA and GARCH
summary(ar.gar) # to display the packages
ArG <- PackageSum2(ar.gar) # for a summary with more detail on installed
packages
write.csv(ArG, 'ArG.csv') # written to a CSV file where it can more
easily be displayed and modified, e.g., in MS Excel
HTML(ar.gar) # To display the results in a web browser.
This search did not produce much for me, which is part of the
reason I suggested maxLik.
Hope this helps.
Spencer Graves
Zhang, Yuhan wrote:
Hello -
Here's what I'm trying to do. I want to fit a time series y with
ARMA(1,1) + GARCH(1,1), there are also an exogeneous variable x which I
wish to include, so the whole equation looks like:
y_t - \phi y_{t-1} = \sigma_t \epsilon_t + \theta \sigma_{t-1}
\epsilon_{t-1} + c x_t where \epsilon_t are i.i.d. random
variables
\sigma_t^2 = omega + \alpha \sigma_{t-1}^2 + \beta y_{t-1}^2
I looked through documentation of garchFit() from the fGarch library but
didn't find a way to include exogeneous variables like x_t. How do I do
that? Thank you very much in advance!
Yuhan Zhang
Morgan Stanley | Fixed Income
1585 Broadway, 3rd Floor | New York, NY 10036
Phone: +1 212 761-2313
yuhan.zh...@morganstanley.com
--------------------------------------------------------------------------
This is not an offer (or solicitation of an offer) to bu...{{dropped:24}}
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
