Re: garch residuals
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 (although it is for multivariate problems and so is inefficient for univariariate garch.) Dave 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 SP. 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. -- Dave Fournier, Otter Research Ltd PO Box 2040, Sidney, B.C. V8L 3S3, Canada 250-655-3364 email: [EMAIL PROTECTED] http://otter-rsch.com = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Re: garch residuals
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 SP. 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. = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Re: garch residuals
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 SP. 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. = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
Re: garch residuals
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. Just standardizing residuals should not remove the autocorrelation from them. That would require some kind of filtering. Even filtering might not remove all autocorrelation. For example, in an AR(1) model estimated with conditional ML, the filtered residual is e = u - rho*u(-1) . The numerator of the first order autocorrelation of the filtered residual is (u - rho*u(-1))'(u(-1) - rho*u(-2)). The first order condition for estimating rho is (u - rho*u(-1))'u(-1) = 0. This is not enough to make the numerator of the first order autocorrelation zero (it doesn't handle the rho*u(-2) part). Are my models misspecified?? It's not possible to say, just on the basis of this. I use returns from the FTSE, the DAX, and the SP. 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?? This is a different question (unless there are no RHS variables), since presumably you are talking about the dependent variable in the model, and not the residual. Clint Cummins TSP International = Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at http://jse.stat.ncsu.edu/ =
