Description Usage Arguments Details Value Author(s) See Also Examples
Method for forecasting from a variety of univariate GARCH models.
1 2 |
fitORspec |
Either a univariate GARCH fit object of class |
data |
Required if a specification rather than a fit object is supplied. |
n.ahead |
The forecast horizon. |
n.roll |
The no. of rolling forecasts to create beyond the first one (see details). |
out.sample |
Optional. If a specification object is supplied, indicates how many data points to keep for out of sample testing. |
external.forecasts |
A list with forecasts for the external regressors in the mean and/or variance equations if specified. |
... |
. |
The forecast function has two dispatch methods allowing the user to call it with either
a fitted object (in which case the data argument is ignored), or a specification object
(in which case the data is required) with the parameters entered via the fixed.pars
argument in the ugarchspec
function.
The forecast is based on the expected value of the innovations and hence the density
chosen. One step ahead forecasts are based on the value of the previous data, while
n-step ahead (n>1) are based on the unconditional expectation of the models.
The ability to roll the forecast 1 step at a time is implemented with the
n.roll
argument which controls how many times to roll the n.ahead forecast.
The default argument of n.roll = 0 denotes no rolling and returns the standard
n.ahead forecast. Critically, since n.roll depends on data being available from which
to base the rolling forecast, the ugarchfit
function needs to be called
with the argument out.sample
being at least as large as the n.roll argument, or
in the case of a specification being used instead of a fit object, the out.sample
argument directly in the forecast function.
A uGARCHforecast
object containing details of the GARCH forecast.
See the class for details on the returned object and methods for accessing it and
performing some tests.
Alexios Ghalanos
For filtering ugarchfilter
,simulation ugarchsim
, rolling forecast
and estimation ugarchroll
, parameter distribution and uncertainty
ugarchdistribution
, bootstrap forecast ugarchboot
.
1 2 3 4 5 6 7 8 9 10 11 | ## Not run:
# Basic GARCH(1,1) Spec
data(dmbp)
spec = ugarchspec()
fit = ugarchfit(data = dmbp[,1], spec = spec)
forc = ugarchforecast(fit, n.ahead=20)
forc
head(as.data.frame(forc))
#plot(forc,which="all")
## End(Not run)
|
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