Hello all,

Over a year ago I wrote a blog post about the problems I was having 
estimating the parameters of GARCH models via fGarch. I got a lot of 
feedback and I've now followed up with another article taking that 
feedback into account: 
https://ntguardian.wordpress.com/2019/01/28/problems-estimating-garch-parameters-r-part-2-rugarch/

First, I switched from fGarch to rugarch, which is supposedly still 
maintained. I also looked at other parameter combinations in simulation 
experiments that others requested.

It seems that rugarch isn't necessarily better when it comes to 
parameter accuracy and one needs a lot of data (in the order of 
thousands) to get good estimates of the parameter values. That said, CIs 
computed are highly unreliable even at large sample sizes and there is 
certainly no "silver bullet" optimization algorithm.

I'd like feedback if I'm not doing things right. I heard once that 
others could not replicate my results; that is, they have reliable 
estimates for GARCH parameters. But I never found out who those people 
were and they did not give me their code to see what I was doing wrong.

If the community is aware of better approaches, I would like to hear 
them as well.

Thank you all,

Curtis Miller

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