[R-SIG-Finance] Simulating paths in rmgarch

[Josh Segal]

Alexios,

Thanks again for your help.
I'm getting some counterintuitive results with the seriesSim output.  When
I run your exact example above and then compute cor(sim at msim$seriesSim[[1]]),
I get a correlation matrix that has non-diagonal values close to zero
(ranging from -0.10 to 0.08).
When I measure the correlation of the original data (cor(dji30ret[,1:5])) I
get values from 0.33 to 0.66.
Shouldn't the simulation demonstrate higher unconditional correlations?  Am
I misunderstanding something about the package, or does this indicate a
problem?

Thanks,
Josh

On Wed, Mar 22, 2017 at 4:06 PM, alexios galanos <alexios at 4dscape.com>
wrote:

> library(rmgarch)
> data("dji30ret")
> spec<-gogarchspec(mean.model=list(model="AR"),ica = "radical")
> fit=gogarchfit(spec,dji30ret[,1:5])
> sim=gogarchsim(fit,n.sim = 1000,m.sim=1,startMethod = "sample",rseed = 10)
>
> head(sim at msim$seriesSim[[1]])
> str(sim at msim)
>
> There are lots of examples and demos in the /inst/rmgarch.tests/ folder of
> the source package.
>
> Alexios
>
>
> On 3/22/2017 2:54 PM, Josh Segal wrote:
>
>> Hi everyone,
>>
>> I'm trying to use the rmgarch package to estimate a multivariate GARCH
>> model and then use those parameters to simulate paths forward.  I've
>> gotten
>> as far as creating a goGARCHsim object (for example), but can't figure out
>> how to access the simulated returns.  I've looked through all the methods
>> described in the documentation (page 58) but don't see anything relevant.
>> I believe I am able to do this in the univariate case with rugarch - is it
>> not possible in rmgarch?
>>
>> Thanks for your help!
>>
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>>
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