Hello all, I have encountered bad behavior in fGarch's garchFit() function used for estimating the parameters of a GARCH model. The estimates behave in highly erratic ways on simulated data. For example, when beta = 0.2 according to the simulation, the function sometimes estimates beta to be 0.0000001 even for sample sizes as large as 1000, and there are other irregularities. I believe this behavior is tied to how the numerical optimizers are computing the parameters. In my research I planned on using garchFit() from fGarch in a changepoint detection context. I was hoping to use it to detect structural change in GARCH parameters. (See, for example, Ling 2007 paper https://arxiv.org/abs/0708.2369 .) But with this behavior I don't know if such a test using garchFit() is possible; the estimates are too unreliable. Has anyone else observed this behavior? Is there a way to get around it? I'm hoping someone who knows more about this can offer guidance. I have written a blog post documenting the behavior I observed, with numerical experiments. Here is a link: https://ntguardian.wordpress.com/2017/11/02/problems-estimating-garch-parameters-r/ Curtis
Problems when estimating GARCH parameters with fGarch
2 messages · Curtis Miller, Bob
1 day later
Have you tried rugarch or just "garch" in the tseries package? Reproducible examples are always helpful as well.
On Nov 2, 2017, at 1:56 PM, Curtis Miller <cgmil at msn.com> wrote: Hello all, I have encountered bad behavior in fGarch's garchFit() function used for estimating the parameters of a GARCH model. The estimates behave in highly erratic ways on simulated data. For example, when beta = 0.2 according to the simulation, the function sometimes estimates beta to be 0.0000001 even for sample sizes as large as 1000, and there are other irregularities. I believe this behavior is tied to how the numerical optimizers are computing the parameters. In my research I planned on using garchFit() from fGarch in a changepoint detection context. I was hoping to use it to detect structural change in GARCH parameters. (See, for example, Ling 2007 paper https://arxiv.org/abs/0708.2369 .) But with this behavior I don't know if such a test using garchFit() is possible; the estimates are too unreliable. Has anyone else observed this behavior? Is there a way to get around it? I'm hoping someone who knows more about this can offer guidance. I have written a blog post documenting the behavior I observed, with numerical experiments. Here is a link: https://ntguardian.wordpress.com/2017/11/02/problems-estimating-garch-parameters-r/ Curtis
_______________________________________________ R-SIG-Finance at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-finance -- Subscriber-posting only. If you want to post, subscribe first. -- Also note that this is not the r-help list where general R questions should go.