alexios alexios at 4dscape.com
Tue Aug 2 18:01:47 CEST 2011

```Dear Zoe,

The study of volatility spillover effects between markets is usually
studied using multivariate GARCH models, which take into account lagged
as well as own shocks and volatility. See for example the BEKK, VEK and
Generalized DCC models. For bivariate modelling this 'should' be
computationally feasible/straightforward, but you should look outside
the rgarch package at present for these type of multivariate GARCH
models (hint: mgarchBEKK, ccgarch).

Regards,

Alexios

On 02/08/2011 15:55, XI ZHANG wrote:
> sorry to bother all,
> I am recently doing a topic about spillover effect between two markets.
> And I want to use AR(1)-GJR-GARCH(1,1)-M Model. I find that rgarch
> package has *functions* for univariate GARCH model, including GJR.
> My GJR model is in the attachment.
>
>
>
> where Ɛ_(j,t-1)^2 is the squared volitility of counterpart market,
> Ɛ_(i,t-1)^2  is the squared volitility of domestic market. S represent
> good news (S=0)or bad news(S=1). and i write the R code as followings,
>
>>variance.model=list(model="gjrGARCH",garchOrder=c(1,1),
> external.regressors=lagvoljp)
>>mean.model=list(armaOrder=c(1,0),include.mean=TRUE,garchInMean=TRUE,inMeanType=2,arfima=FALSE,external.regressors=ljp)
>
>>spec=ugarchspec(variance.model=variance.model,mean.model=mean.model,
> distribution.model="norm")
>>fit3.sh=ugarchfit(data=shl,spec=spec,out.sample=0,solver="solnp")
>
> But then I figure out that in normal GJR model, the fomula is
> and the function written in rgarch package is also based on it
> which means it catches news from domestic market.
>
> But in my model, it should catch news from counterpart market,
> I was thinking of taking S part as an another external regressors
> since if Ɛ<0,S=1 elseS=0,so I write codes as
>
>>resjp[resjp>0]<-0
>
>>voljpgjr<-resjp^2
>
>>variance.model3sh=list(model="fGARCH",garchOrder=c(1,1),
> submodel="GARCH", external.regressors=cbind(lagvoljp,voljpgjr))
>
>>mean.model3sh=list(armaOrder=c(1,0),include.mean=TRUE,garchInMean=TRUE,inMeanType=2,arfima=FALSE,external.regressors=lagsh)
>
>>spec3sh=ugarchspec(variance.model=variance.model3sh,mean.model=mean.model3sh,
> distribution.model="norm")
>
>>fit3.sh=ugarchfit(data=shl,spec=spec3sh,out.sample=0,solver="solnp")
>
>>fit3.sh
>
>
> But the result is still disappointed that the coefficient which reflect
> volatility spillover effect is always not significant and almost 0. I
> tried other dataset, but the result is the same.
>
>
> Here is my question,
> How could i change the code to let the S reflects the effect from
> counterpart market? Are there any codes I write have problems and
> un-reasonable part?
>
> Thisi is important for me!
> Thank you so much!
>
> Sincerely,
> Zoe
>
>
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