## Negative resid(-1)^2 coefficient in Garch variance equation

For econometric discussions not necessarily related to EViews.

Moderators: EViews Gareth, EViews Moderator

J&P masters
Posts: 4
Joined: Fri Apr 01, 2016 4:28 am

### Negative resid(-1)^2 coefficient in Garch variance equation

Hi!

We are wondering why we get a negative resid(-1)^2 coefficient in Garch variance equation. If anyone could shed some light on this, we would be most thankful. Please see the attachment.
Attachments
Garch.PNG (23.64 KiB) Viewed 8676 times

Did you use forum search?
Posts: 1518
Joined: Thu Nov 20, 2008 12:04 pm

### Re: Negative resid(-1)^2 coefficient in Garch variance equat

Your output reads: "Failure to improve likelihood (non-zero gradients) after 26 iterations". In other words, you are experiencing a convergence problem. It also seems you have a very weak GARCH effect in the residuals. Either there is really no significant GARCH effect, or the mean equation is not stationary.

J&P masters
Posts: 4
Joined: Fri Apr 01, 2016 4:28 am

### Re: Negative resid(-1)^2 coefficient in Garch variance equat

We thank you kindly for the reply.

We have done unit root tests of data series, as well as ADF and KPSS test. The result from ADF showed that data series was stationary, while KPSS test showed that it was not stationary. We also found that it was no ARCH effect in the model. See picture. We are also wondering how we find out if the GARCH effect is significant?

Kind regards
Eager Norwegian students
Attachments
ARCH test.PNG (12.77 KiB) Viewed 8629 times

Did you use forum search?
Posts: 1518
Joined: Thu Nov 20, 2008 12:04 pm

### Re: Negative resid(-1)^2 coefficient in Garch variance equat

Try modeling your variables in first differences (i.e. d() or dlog()). Check the correlogram of residuals to see if there is any serial correlation left in your mean equation. If there is not, you are good to go. Otherwise, you need to add AR() and/or MA() lags to capture that effect. And keep in mind that there may not be any significant (G)ARCH behavior in the residuals to begin with. Sum of ARCH and GARCH coefficients close to (but smaller than) 1 indicates a strong effect.

J&P masters
Posts: 4
Joined: Fri Apr 01, 2016 4:28 am

### Re: Negative resid(-1)^2 coefficient in Garch variance equat

Thanks again.

Our variables are in first differences. Our depended variable is (Spot [t+1]-Spot[t])/Spot[t], and our independent variable is (F[t]- Spot[t])/Spot[t]. We have checked the correlogram of the residuals and there is no serial correlation, see the attachment. So that means there is no significant GARCH effect?

Kind regards
Eager Norwegian students
Attachments
Correlogram.PNG (32.19 KiB) Viewed 8615 times

Did you use forum search?
Posts: 1518
Joined: Thu Nov 20, 2008 12:04 pm

### Re: Negative resid(-1)^2 coefficient in Garch variance equat

Q-stats (and the related p-values) disagree with you. There are some significant lags indicating a possible serial correlation. As for the GARCH effect, you should look at the correlogram of squared residuals and then formally test for heteroscedasticity. It is hard to detect the source of the problem (if any) without seeing the actual data.

Jakem
Posts: 3
Joined: Wed May 23, 2018 4:26 am

### Re: Negative resid(-1)^2 coefficient in Garch variance equation

Dear Eviews,

I am using the dependent variable: LN(Returns) and independent variables: Standardized Announcements.
My time series range from 2000-2017 thus volatility clustering is observed.
When first performing an OLS it became clear that there was hetereoscedasticity.

Ultimately performing a GARCH(1,1) equation.
My squared residuals are oke (all p values >0.05)
My correlogram of Q statistics of standardized errors certainly not (only 1st and 2nd >0.05 because of two lags of returns).
What does this mean?

When adding another ARCH effect GARCH (2,1) then the coefficient is negative but significant.
How can this coefficient be negative?

Greetings,
Jake