Did you expect them to have the same values? This is first and foremost a GARCH 
model augmented with the realized measure. Did you read the blog post and 
vignette first? 

Beyond that, it is difficult to comment without looking at your data 
(reproducible code). 
Did you first try a (1,1)-Normal model (to compare the likelihoods in case the 
model converged to a non-global optimum)?

-Alexios

On 17 Feb 2014, at 10:30, Duco van Rossem <[email protected]> wrote:

> Dear list,
> I am trying to compare the fitted sigma of the realGARCH model with my 
> realized volatility input. However these two time series have completely 
> different values. My realizedVol input has a values of around 0.004-0.010, 
> while the fitted sigma output has values of around 0.001-0.003 and I am 
> trying to understand why.
> Below I walk through my code:
> My model specification fitting below, where,return_c2casxts - daily 
> close-to-close return object (an xts object)RVar_BN2008 - Daily realized 
> variance measure (using realized kernel of Bandorff Nielsen 2008)
> spec.realGARCH21 <- ugarchspec(variance.model = list(model = "realGARCH", 
> garchOrder = c(2,1)),                       mean.model = list(armaOrder = 
> c(1,1)),                  distribution.model = 
> "std")garch_model<-ugarchfit(spec.realGARCH21, return_c2casxts, solver = 
> 'hybrid', realizedVol=sqrt(RVar_BN2008))
> RVolfitted<-garch_model@fit$sigma
> 
> Now comparing RVolfitted and sqrt(RVar_BN2008)below I have completely 
> different values throughput the series (3500 days in total). 
> RVolfitted:"       0.0020383691   0.0018783530    0.0020688548    
> 0.0015357892    0.0016052453     0.0016191145sqrt(RVar_BN2008): 0.006596078   
>  0.008683373     0.004344591     0.006393453     0.006223041      0.008463817
> Is this a conceptual issue on my part on what sigma signifies here? How can I 
> obtain fitted values corresponding to the realizedVol input?
> Best Regards,Duco                                       
>       [[alternative HTML version deleted]]
> 
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