[R-SIG-Finance] Simulating paths in rmgarch

[Alexios Ghalanos]

Yes...will check this weekend to see whether something may have gone amiss in the AR/Constant simulation. Check my bitbucket repo by next week to see if any changes were committed and reinstall from there if so.


Alexios

> On Mar 24, 2017, at 3:40 PM, Josh Segal <joshua.segal at gmail.com> wrote:
> 
> VAR seems ok, while AR and constant are not
> 
> Should I only use VAR with GOGARCH?
> 
>> On Fri, Mar 24, 2017 at 3:43 PM, alexios galanos <alexios at 4dscape.com> wrote:
>> Try using model="VAR" instead of "AR"....will check to see if something
>> is amiss otherwise.
>> 
>> A.
>> 
>> On 24/03/2017 13:42, Josh Segal wrote:
>> > 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$seriesSim[[1]]), I get a correlation matrix that has
>> > non-diagonal values close to zero (ranging from -0.10 to 0.08).
>> > When I measure the correlation of the original data
>> > (cor(dji30ret[,1:5])) I get values from 0.33 to 0.66.
>> > Shouldn't the simulation demonstrate higher unconditional
>> > correlations?  Am I misunderstanding something about the package, or
>> > does this indicate a problem?
>> >
>> > Thanks,
>> > Josh
>> >
>> > On Wed, Mar 22, 2017 at 4:06 PM, alexios galanos <alexios at 4dscape.com
>> > <mailto:alexios at 4dscape.com>> wrote:
>> >
>> >     library(rmgarch)
>> >     data("dji30ret")
>> >     spec<-gogarchspec(mean.model=list(model="AR"),ica = "radical")
>> >     fit=gogarchfit(spec,dji30ret[,1:5])
>> >     sim=gogarchsim(fit,n.sim = 1000,m.sim=1,startMethod =
>> >     "sample",rseed = 10)
>> >
>> >     head(sim at msim$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!
>> >
>> >                 [[alternative HTML version deleted]]
>> >
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> 

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