Thank you very much for your time. I will look into using the updated code,

problem runs.

>

> GARCH-Modelling is not easy, and indeed for your dataset the default

> "Sequential Quadratic Programming" solver doesn't converge. I observed

> this also for some other time series. There is already an updated

> version on

> the server,

https://svn.r-project.org/Rmetrics/trunk/fSeries/ which uses

> improved

> control parameter settings as default values. With this version there

> exist

> no convergence problems. What can you do? Download the updated

> version from the repository, or just use the alternative optimization

> "nlminb"

> until the next version of "Rmetrics" becomes published.

>

> regards Diethelm Wuertz

>

>

> garchFit() # Update - Default Settings

> Estimate Std. Error t value Pr(>|t|)

> mu -0.016772 0.020792 -0.807 0.4199

> omega 0.008898 0.004055 2.194 0.0282 *

> alpha1 0.047233 0.011134 4.242 2.21e-05 ***

> beta1 0.936329 0.014828 63.146 < 2e-16 ***

> Log Likelihood:

> 1045.871 normalized: 1.045871

>

>

> garchFit(algorithm = "nlminb") # Current Version

> Estimate Std. Error t value Pr(>|t|)

> mu -0.016772 0.020793 - 0.807 0.4199

> omega 0.008898 0.004055 2.194 0.0282 *

> alpha1 0.047233 0.011134 4.242 2.21e-05 ***

> beta1 0.936329 0.014828 63.145 < 2e-16 ***

> Log Likelihood:

> 1045.871 normalized: 1.045871

>

>

> garchOxFit()

> Coefficient(s):

> Value Std.Error t.value

> Cst(M) -0.0166990 0.0207920 -0.80315

> Cst(V) 0.0089064 0.0040545 2.19670

> ARCH(1) 0.0472270 0.0111270 4.24430

> GARCH(1) 0.9362900 0.0148290 63.13900

>

>

>

>

> Monty B. wrote:

>

> >Thanks to Sean and Diethelm for pointing out that the link was not

> working.

> >

> >The data can be found here:

> >

> >

http://host-a.net/getfile.php?usern=upppload&file=fGARCH_crash.csv> >(click in the yellow box to receive file)

> >

> >Sorry about the quirky download site. It was the best I could do right

> now..

> >

> >

> >Many thanks,

> >

> >Monty

> >

> >

> >On 4/16/06, Monty B. <

[hidden email]> wrote:

> >

> >

> >>Dear all,

> >>

> >>I am fitting garch models to a sliding window of observations of the

> >>USD/NOK exchange rate. I've been provided with the Ox/G@RCH package,

> >>but I am not entirely happy with it's scriptability, so I thought I

> >>would give fSeries a go. The package seems to work well for some

> >>series, but for others, it locks up R.

> >>

> >>This code:

> >>

> >>library(fSeries)

> >>y <- read.table("fGARCH_crash.csv")

> >>fg <- garchFit(formula.mean =~ arma(0,0), formula.var =~ garch(1,1),

> >> cond.dist = "dnorm", y, trace=T, title="USD vs NOK")

> >>

> >>and the file:

> >>

> >>

> >>

http://us.f13.yahoofs.com/bc/44422dee_a419/bc/My+Documents/fGARCH_crash.csv?bfcOjQEBfGO1k9on> >>

> >>makes R crash giving no output when the default settings are used.

> >>Changing the algorithm to "nlminb" seems to provide estimates. BUT, I

> >>am a bit skeptical about changing defaults when I do not know what the

> >>difference between sqp and nlminb is.

> >>

> >>Any suggestions? Should I use the non-default optimization? Can anyone

> >>refer me to literature on what the difference is? Will the parameter

> >>estimates be of worse quality?

> >>

> >>BTW: I am using R for windows 2.2.1. I have tested both the standard

> >> 2.2.1 and the patched 2.2.1 versions with this code.

> >>

> >>Thanks for any input,

> >>

> >>cheers,

> >>

> >>Monty

> >>

> >>

> >>

> >

> > [[alternative HTML version deleted]]

> >

> >_______________________________________________

> >

[hidden email] mailing list

> >

https://stat.ethz.ch/mailman/listinfo/r-sig-finance> >

> >

> >

>

>