I would fit the data with various (r,p) arma models with the
the desired garch assumption on the evolution of the variance
and consider both the likelihood ratios and autocorrelation
of the standardized residuals to determine the best model
to fit the data. I have code for this if you want (althou
Daan Taks <[EMAIL PROTECTED]> wrote:
>I have a question about my residuals. When testing for autocorrelation
>I come to the conclusion that the models (garch, Egarch, GJR a.k.a.
>Tarch) remove the correlation from the squared standardized residuals
>but not from the standardized residuals.
Jus
That stock market returns follow a Martingale in general has been pretty
well disproved. See the survey literature in The Econometrics of Financial
Markets by Campbell, Lo and MacKinlay and A Non-Random Walk down wall street
by Andrew Lo. Index returns show quite significant lag correlations which
Stock market returns usually satisfy martingale property, and are
uncorrelated. I think you should check your calculations again for errors.
Are you sure that you are working with returns and not prices? I guess
that by "heavy correlation" you mean that estimated autoregressive
coefficient is clos
I have a question about my residuals. When testing for autocorrelation
I come to the conclusion that the models (garch, Egarch, GJR a.k.a.
Tarch) remove the correlation from the squared standardized residuals
but not from the standardized residuals. Are my models misspecified??
I use returns from
