On Sun, 25 Dec 2005, sudip mukherjee wrote:
Everytime I try to run the GARCH model from the menu
(model/time series/garch) it gives me an error message
"convergence criterion not met". I tried several
different data series but i get the same message
What do the data series look like? An important point about the
GARCH model is that the assumed error process handles _only_
conditional heteroskedasticity (a non-constant error variance,
varying in an autoregressive manner). If the series in question has
a definite trend, or is autoregressive in its level, then a simple
GARCH model will not be appropriate and the likely symptom is
non-convergence of the estimation procedure.
It may be possible to overcome this problem by including suitable
independent variables in the GARCH model (e.g. variables that have
the effect of "taking out" the trend in the dependent variable).
Alternatively, it may be necessary to use some transformation of the
variable of interest, such as percentage change or log-difference.
As a simple example, look at the data file djclose.gdt (supplied
with gretl). This contains daily closing values of the Dow Jones
index. If you try a simple GARCH model for djclose, the procedure
will not converge. This is, I would say, the "correct" result,
since the Dow has a strong upward trend and cannot reasonably be
represented as fluctuations of varying amplitude around a constant
mean. But if you form the log-difference of the dclose variable
and run a GARCH, you get sensible estimates.
I can't say with perfect confidence that gretl fails to produce
GARCH estimates _only_ when the GARCH model is clearly
inappropriate. Nonetheless, I think it's quite likely that
non-convergence in gretl is an indication of a problem with the
If you find a data series for which gretl will not produce GARCH
estimates, but (say) R succeeds in producing sensible estimates,
please let us know and we'll take a look at the case.