fSeries_221.10065 and garchFit+sqp makes R lock up

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fSeries_221.10065 and garchFit+sqp makes R lock up

Monty B.
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

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Re: fSeries_221.10065 and garchFit+sqp makes R lock up

Monty B.
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]]

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Re: fSeries_221.10065 and garchFit+sqp makes R lock up

Diethelm Wuertz
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
>
>  
>

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Re: fSeries_221.10065 and garchFit+sqp makes R lock up

Monty B.
Diethelm,

Thank you very much for your time. I will look into using the updated code,
or I might
just use something similar to the code in the garchOxFit function for
problem runs.
Does there exist a zipped version of the latest version, or do I have to set
up a toolkit for
building the package from the latest sources?

Many thanks,

Monty


On 4/16/06, Diethelm Wuertz <[hidden email]> wrote:

>
> 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
> >
> >
> >
>
>

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