[R-SIG-Finance] garch in R vs Matlab

[Spencer Graves]

      I now see things I didn't see before: 

           (1) With "garch11<-ret-res1", garch11 = mu.  Since the model 
is "~garch(1,1)", I'd be worried if it were otherwise, because the model 
for the 'mean' in this case is only the mean. 

           (2) Per Michal's suggestions, it looks like 'innovations' may 
be standardized residuals, which suggests we might want to compare 
'innovations' with (fit at residuals / fit at sigma.t). 

      In addition, you may wish to consider the following: 

           (3) Using 'garchSim{fGarch}, you could simulate anything you 
want in R, then export the numbers to Matlab and compare the estimates.  
If you made that comparison, I'm sure that other people would be 
interested in the answers.  [If you export from R to a csv file, I 
suggest you first round the numbers off to, say, 4 significant digits, 
then apply 'garchFit' to the rounded numbers, to ensure you are actually 
analyzing the same numbers in R and Matlab.] 

           (4) If you do very much with both R and Matlab, you may wish 
to investigate the R.matlab package if you haven't already.  It's not 
the easiest thing to use, but if you do very much with both R and 
Matlab, you may wish to look at it if you haven't already.   
    
     Spencer    

michal miklovic wrote:
> Hi
>
> I would suggest you to compare standardised residuals, defined as fit at residuals / fit at sigma.t, from garchFit estimation with innovations from matlab.
> Simulation results could be different because random numbers generated by the two programs are different.
>
> Regards
>
> Michal
>
>
>
> ----- Original Message ----
> From: "babel at centrum.sk" <babel at centrum.sk>
> To: R-SIG-Finance <r-sig-finance at stat.math.ethz.ch>
> Sent: Tuesday, February 26, 2008 11:29:39 PM
> Subject: [R-SIG-Finance] garch in R vs Matlab
>
> Hello guys
> Why residuals in R are different than in matlab. Here is example
> fit = garchFit(~garch(1, 1), data =ret)
> res1<-fit at residuals
> garch11<-ret-res1
> garch11 = 0.0001074985  0.0001074985   0.0001074985 ......     which is coefficient  mu  from garchFit
>
> in MATLAB
> [coeff,errors,LLF,innovations,sigmas,summary] = garchfit(ret);
>
> garch11<-ret-innovations =    3.066250e-04    1.075012e-04   -1.909928e-04   5.055000e-04 .. 
>
> Innovations (in help there is also use name "residuals") in Matlab should be the same residuals that those in R (fit at residuals) ? Even when coefficients alpha, beta, omega are same. Also simulation results are totally different. Does R count garch different than Matlab, or just additional mathematical operation are needed? 
> Regards Jano
>
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