[R-SIG-Finance] To obtain the t student of each rolling window with EGARCH model

Sandrine Boulerne sandrine.boulerne at univ-tours.fr
Tue Sep 12 18:18:41 CEST 2017


Dear Alexios

That's wonderful. Thanks to you I got what I was looking for several weeks. you are right, the documentation is very clear, but sometimes we do not see what may seem obvious to an expert eye.

Thanks a lot


Sandrine BOULERNE 
Maitre de Conferences - Habilitation à Diriger des Recherches (HDR) 
Co-responsable du thème Finance Contrôle Audit du Laboratoire de recherche VALLOREM 
IAE de Tours - Faculté de Droit, Économie et Sciences Sociales 
50 av. Jean Portalis, BP 0607, 37206 TOURS Cedex 3 
Téléphone : 02 47 36 10 47 
www.iae.univ-tours.fr

----- Mail original -----
De: "alexios" <alexios at 4dscape.com>
À: "Sandrine Boulerne" <sandrine.boulerne at univ-tours.fr>
Cc: r-sig-finance at r-project.org
Envoyé: Mardi 12 Septembre 2017 06:27:33
Objet: Re: To obtain the t student of each rolling window with EGARCH model

Have you tried 'coef(roll1)'?

I think the documentation is reasonably clear (?ugarchroll).
It returns an object of class 'uGARCHroll' (which is clickable in the 
documentation and will take you to the class help page).
In the class help page you will see that one of the methods on the class
is:

"coef
signature(object = "uGARCHroll"): Extracts the list of coefficients for 
each estimated window in the rolling backtest."

Therefore, coef(roll1) will return the list of coefficient matrices
per roll window, from which you can extract the shape parameter of the
standardized Student distribution.

Similarly, please read the documentation for ugarchdistribution.


-Alexios

On 9/11/2017 9:03 AM, Sandrine Boulerne wrote:
> Good Morning,
> 
> I investigate the day-of –the-week of 11 indices in 11 countries using 
> EGARCH model and rolling sample method with one sample interval case of 
> 500 days. The main purpose of the empirical analysis is to determine 
> whether there exist calendar effects or not by observing whether the /t/ 
> values exceed the quantile of the standard normal distribution z = 1.96 
> for confidence level of 5%. I want to use the same method as Zhang, Lai, 
> Lin (2017), “the day-of-the-week effects of stocks markets in different 
> countries”, Finance Research Letters 20.
> 
> For the EGARCH model, I used Package “Rugarch”, and everything is good:
> 
> spec2b<-ugarchspec(variance.model=list(model="eGARCH",garchOrder=c(1,1), 
> external.regressors=L1),            
> mean.model=list(armaOrder=c(0,0),archm=TRUE,archpow=1,external.regressors=L2),
> 
> distribution.model = "std")
> 
> fit2b<-ugarchfit(spec=spec2b,solver="hybrid", data=RENT)
> 
> show(fit2b)
> 
> But for the rolling sample method, with EGARCH(1,1), I thought using 
>   “ugarchroll” or “ugarchdistribution*”, ** to calculate the student /t/ 
> for each rolling window*, *but **I do not get student /t/* :
> 
> dist <- ugarchdistribution(fit2b, n.sim = 500, n.start = 1, m.sim = 100, 
> solver = "solnp")
> 
> show(dist)
> 
> or
> 
> roll1=ugarchroll(spec1b,data = RENT,n.start = NULL,window.size = 
> 500,solver = "solnp" )
> 
> show(roll1)
> 
> Could you orient me to a solution ?
> 
> Thank you very much
> 
> 
> 
> Sandrine BOULERNE
> Maître de Conférences - Habilitation à Diriger des Recherches (HDR)
> IAE de Tours - Faculté de Droit, Économie et Sciences Sociales
> 50 av. Jean Portalis, BP 0607, 37206 TOURS Cedex 3
> Téléphone : 02 47 36 10 47
> www.iae.univ-tours.fr
>



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