Hi everyone
I'm running a T-GARCH model (i.e. a GJR-GARCH model) using the package fGARCH.
A sample code for my model looks like this:
Modell1=garchFit(formula=~1+aparch(1,1), data="T-Bill", delta=2,
include.delta=F)
summary(m1)
Here's the issue. I need to indicate the adjusted R-squared value
Hi
Rt<-garchFit(formula=~garch(1,1),include.mean=FALSE,data=
X2,cond.dist=c("std")) # Student-t Garch.
I got the this output
omega alpha1 beta1 shape
0.0001027529 0.05195144470.88871366025.6843302645
I use above formulation
Hello,
The function garchFit in the package fGarch allows for choosing a
conditional distribution, one of which is the t-distribution. The function
allows specification of the shape parameter of the distribution (equal to
the degrees of freedom for the t-distribution), for which the default is set
The (maximum) limit for shape is set on 10 for the function garchfit. Hence
it is impossible to estimate data for a student-t distributed error term
with a higher degrees of freedom than 10. I wonder how to change this
parameter. I hope someone could give me the answer. Thank you verry much in
adva
Hi there,
an answer from someone who's not an expert in the field but used to
play around with time series:
The action of simulating a process using with input parameters then
estimating the parameters is not an invariant, especially when the
process involves nonlinearities.
Did you try increasing
Hi there,
I'm trying to fit a GJR-GARCH Model using fGarch. I wanted to try that by
fitting an APARCH model with a fixed delta of 2 and a non-fixed gamma. So I
was simply trying to use:
spec <- garchFit(~aparch(1,1),data=garchSim(),delta=2)
coef(spec)
And sometimes, it's working like a charm and
Hi Paul,
I suggest that you should send us commented, minimal, self-contained,
reproducible code.
That means, in essence, developing the simplest possible
representation of your problem. In the process of developing the
simplest possible representation, you may learn more about the
problem. May
Hi,
I am attempting to fit a ARMA/GARCH regression model without success.
### ARIMA-GARCH model with regressor ###
### Time series data: A multivariate data set.
cov.ts.dq = cov.ts[1:4,"dq1"][!is.na(cov.ts[,"dq1"])]
cov.ts.day = ts.intersect(dq = diff(q.ts), day = lag(q.t
On Aug 15, 2010, at 11:14 PM, Marius Hofert wrote:
> Dear David,
>
> thanks for the quick response. Yes, I tried "formula", but this gives the
> error "Multivariate data inputs require lhs for the formula."
>
> library(fGarch)
> spec <- garchSpec(model = list(alpha = 0.1, beta = c(0.4, 0.4)))
Dear David,
thanks for the quick response. Yes, I tried "formula", but this gives the error
"Multivariate data inputs require lhs for the formula."
library(fGarch)
spec <- garchSpec(model = list(alpha = 0.1, beta = c(0.4, 0.4)))
data <- garchSim(spec, n = 100)
x <- list()
for(q in 1:3){
On Aug 15, 2010, at 4:26 PM, Marius Hofert wrote:
Dear expeRts,
How can I specify the order p,q of a GARCH(p,q) model within a loop?
Here's a minimal example showing that an "Formula and data units do
not match"-error appears:
library(fGarch)
spec <- garchSpec(model = list(alpha = 0.1, b
Dear expeRts,
How can I specify the order p,q of a GARCH(p,q) model within a loop? Here's a
minimal example showing that an "Formula and data units do not match"-error
appears:
library(fGarch)
spec <- garchSpec(model = list(alpha = 0.1, beta = c(0.4, 0.4)))
data <- garchSim(spec, n = 100)
x <-
hello everybody,
I would like to fit a model to a times series (testing set) for out of
sample predictions using garchFit(). I would like to keep the coefficients
of ARMA/GARCH model fixed (as found by fitting the model to my training
set). The arima fitting function has such an option for that
Is the likelihood returned by fGarch the negative of the likelihood - so
we're minimizing the negative of the max likelihood function?
Thx,
John
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R-help@r-project.org mailing list
https://stat.ethz.ch/mai
Thanks for the report,
the problem boils down to the call of "methods:::bind_activation(TRUE)"
in one of the depended package.
I can reproduce the problem with
> methods:::bind_activation(TRUE)
> dfr <- data.frame(matrix(0, nrow = 1 , ncol = 1000))
> dfr2 <- is.na(dfr)
I will forward you remar
Hello,
after loading package "fGarch" the function is.na.data.frame() is behaving
different:
> sessionInfo()
R version 2.8.0 (2008-10-20)
i386-pc-mingw32
locale:
LC_COLLATE=English_United States.1252;LC_CTYPE=English_United
States.1252;LC_MONETARY=English_United
States.1252;LC_NUMERIC=C;LC_
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