anozman wrote:Hi everyone,
I am using garch procedure to estimate different models for my research. The focus is on the mean equation specifications and the garch part is only used to deal with the arch effect in the error term.
Could anyone help me to understand the following four issues:
1. What goodness of fit measures in RATS that can be used to compare nested garch models; and also compare models based on different datasets? Ideally, these measures should be adjusted for the number of parameters in a model, e.g. similar to adj R^2 in an OLS regression.
anozman wrote:2. Is the Wald joint test a valid test for testing some restrictions in the mean equation?
anozman wrote:3. And how valid is the Wald join test statistics when some variables are highly correlated, e.g. with their own lags?
anozman wrote:4. Would it be a problem if all the variables in the garch model are I(1) variables?
anozman wrote:Thanks Tom for your valuable feedback.
Could you please help me to clarify the following two points:
For point 3
With highly correlated variables in the mean equation, is t-test or Wald test statistic (it is essentially the same) on single parameter significance test still valid (the multicollinearity problem is not an issue here)?
anozman wrote:For point 4
When you say “… but the mean model has to reduce the residuals to being uncorrelated, …”
are the “residuals” mentioned above referring to the raw residuals from the mean equation or the standardised residual series coming out of the GARCH model has to pass some kind of autocorrelation tests such as LB test?
anozman wrote:Hi Tom,
I have read the Sims, Stock and Watson 1990 paper. I have one more question I hope you could help me to understand.
When I used OLS for intial analysis, the raw residauls coming out of most of the equations are I(0), impling these I(1) variables are cointegrated
anozman wrote:although the residuals are nonnormal and have some autocorrelation and arch effect. Does this result (I(0) residuals) have an implication on the validity of those t- and Wald-tests when I set up the models properly within a garch framework and estimate them by MLE?
thanks for your help!
anozman wrote:Hi Tom,
It seems Bruce Hansen (1994)'s skew-t-distribution can be used to deal with skewed t errors. Could you please tell me whethter the normal wald tests we discussed in this topic are still valid under the skew-t-distribution?
Thanks Tom, appreciate your help!
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