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
can be attributed to significant lead/lag correlations between individual
stocks in the index. It is quite common in GARCH modeling to account for
short lag correlations by including MA terms in the mean equation before
fitting the variance.
ez
"Vadim and Oxana Marmer" <[EMAIL PROTECTED]> wrote in message
[EMAIL PROTECTED]">news:[EMAIL PROTECTED]...
> 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 close to 1, which holds for prices. Just a suggestion, hope
> it helps.
>
>
>
>
> On Tue, 19 Feb 2002, Daan Taks 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. Are my models misspecified??
> > I use returns from the FTSE, the DAX, and the S&P. These returns are
> > (heavily) correlated, should a garch model remove the correlation of
> > the returns? Or should it only remove the correlation of the squared
> > returns??
> > Thanks.
> >
> >
>
>
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