MV-EGARCH with spillovers

Discussions of ARCH, GARCH, and related models

Re: MV-EGARCH with spillovers

The asymptotic standard error for a correlation (under the null that the correlation is zero) is 1/sqrt(# of observations). So the t-statistics can be computed with:

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`cmom(corr)# variablescompute %cmom=%cmom*sqrt(%nobs)*disp %cmom`
TomDoan

Posts: 2725
Joined: Wed Nov 01, 2006 5:36 pm

Re: MV-EGARCH with spillovers

Tom,
After running the code, I got an estimate.
I want to know whether the estimate as per code is the standard errors OR
the square root of the number of observation which I should use to calculate the t-stats.

Thanks
gorgorm

Posts: 4
Joined: Mon Apr 05, 2010 9:19 am

Re: MV-EGARCH with spillovers

That produces the t-statistics. The diagonal elements are nonsense, of course, but all the off-diagonals are the asymptotic t-statistics.
TomDoan

Posts: 2725
Joined: Wed Nov 01, 2006 5:36 pm

Re: MV-EGARCH with spillovers

Dear Friends,

I have tried to estimate the restricted model as done by Koutmos (1996) Table 2. It does not give same results. Is there any simple way to modify the full-model code to become the restricted model. I have tried to put A(1)(3)==A(2)(3)==A(3)(3)==0.0 immediately after " nonlin b a g d rr " but it does not work.

and How to automatically calculate the impact of symmetric Innovations on volatility using RATS as shown in Table 4. Thanks.
turkhanali

Posts: 16
Joined: Fri Jul 17, 2009 1:47 am

Re: MV-EGARCH with spillovers

Hi Tom,
I tried to adjust your four variable code to a bivariate system. And just changed the below codes as seen. After I run the code, I have the below results. Is something wrong here? I am confused about the results.
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`compute n=2** Define the return series*dec vect[series] r(n)compute start=1, end=750set r(1) = 100*log(fra/fra{1})set r(2) = 100*log(ger/ger{1})** Template for mean equation. This is a VAR(1)*equation meaneq *# constant r(1){1} r(2){1}`

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`    Variable                        Coeff      Std Error      T-Stat      Signif************************************************************************************1.  B(1)(1)                       0.049233484  0.031080586      1.58406  0.113180282.  B(1)(2)                      -0.029537994  0.038492409     -0.76737  0.442860423.  B(1)(3)                       0.003853134  0.035468663      0.10863  0.913492094.  B(1)(4)                      -0.011483730  0.020734891     -0.55384  0.579691045.  B(1)(5)                      -0.014403906  0.021419092     -0.67248  0.501278306.  B(2)(1)                       0.069453165  0.051687750      1.34371  0.179043327.  B(2)(2)                       0.168135839  0.047800982      3.51741  0.000435778.  B(2)(3)                       0.023231342  0.053341768      0.43552  0.663185909.  B(2)(4)                      -0.015210762  0.037747528     -0.40296  0.6869773010. B(2)(5)                      -0.010654883  0.035051930     -0.30397  0.7611475411. A(1)(1)                       0.002922546  0.008504550      0.34365  0.7311132612. A(1)(2)                       0.146621640  0.034872157      4.20455  0.0000261613. A(1)(3)                      -0.009506499  0.023067570     -0.41212  0.6802549214. A(2)(1)                       0.037589459  0.016418051      2.28952  0.0220491515. A(2)(2)                       0.033118479  0.015117959      2.19067  0.0284755816. A(2)(3)                       0.103180374  0.038044773      2.71208  0.0066863017. D(1)                         -1.332757517  0.398151163     -3.34737  0.0008158418. D(2)                         -0.541204025  0.302098755     -1.79148  0.0732162219. G(1)                          0.947575690  0.009841957     96.27919  0.0000000020. G(2)                          0.952638476  0.019601947     48.59918  0.0000000021. RR(1,1)                       0.362829658  0.028700696     12.64184  0.00000000`

Thanks,
Ibrahim
ibrahim

Posts: 15
Joined: Wed Mar 20, 2013 10:50 am

Re: MV-EGARCH with spillovers

Tom,
Please ignore the results at my last post. I solved the results error and got new results as seen below for a bivariate egarch model.
For this model, "B" coefficients reflect return spillover and "A" coefficients reflect volatility spillover, right!
And B(1)(2) means own lagged retuns effect and B(1)(3) means the other variables' lagged return effect, right!
I am confused about interpreting the results!
Thank you very much.

Code: Select all
`MAXIMIZE - Estimation by BFGSConvergence in    27 Iterations. Final criterion was  0.0000095 <=  0.0000100Usable Observations                       746Function Value                     -2340.3786    Variable                        Coeff      Std Error      T-Stat      Signif************************************************************************************1.  B(1)(1)                       0.043866259  0.030047126      1.45992  0.144313362.  B(1)(2)                      -0.028237331  0.032342501     -0.87307  0.382623843.  B(1)(3)                      -0.009105750  0.019289191     -0.47206  0.636880474.  B(2)(1)                       0.068639510  0.052417456      1.30948  0.190372455.  B(2)(2)                       0.166320047  0.038417338      4.32930  0.000014966.  B(2)(3)                      -0.012156675  0.013639290     -0.89130  0.372769227.  A(1)(1)                       0.003478053  0.009199481      0.37807  0.705378168.  A(1)(2)                       0.143448536  0.036151163      3.96802  0.000072479.  A(1)(3)                      -0.006822461  0.024400134     -0.27961  0.7797786310. A(2)(1)                       0.037727871  0.015439911      2.44353  0.0145444011. A(2)(2)                       0.032639706  0.015393948      2.12029  0.0339812012. A(2)(3)                       0.103701708  0.037852261      2.73964  0.0061505813. D(1)                         -1.375944773  0.412245282     -3.33768  0.0008448014. D(2)                         -0.538287971  0.352336195     -1.52777  0.1265701415. G(1)                          0.947938662  0.011011507     86.08619  0.0000000016. G(2)                          0.952677816  0.018517041     51.44871  0.0000000017. RR(1,1)                       0.362829054  0.040470315      8.96531  0.00000000`
ibrahim

Posts: 15
Joined: Wed Mar 20, 2013 10:50 am

Re: MV-EGARCH with spillovers

ibrahim wrote:Tom,
Please ignore the results at my last post. I solved the results error and got new results as seen below for a bivariate egarch model.
For this model, "B" coefficients reflect return spillover and "A" coefficients reflect volatility spillover, right!
And B(1)(2) means own lagged retuns effect and B(1)(3) means the other variables' lagged return effect, right!
I am confused about interpreting the results!
Thank you very much.

The B's are the mean model coefficients. As it's written, B(x)(1) is the intercept. B(x)(2) is the coefficient on the lag of the 1st variable and B(x)(3) is on the second, so B(1)(3) is the spillover in the first equation and B(2)(2) is the spillover in the second.

The A's have a similar pattern--A(x)(1) is the intercept, ...
TomDoan

Posts: 2725
Joined: Wed Nov 01, 2006 5:36 pm

Re: MV-EGARCH with spillovers

Thank you so much Tom,

One more question about bivariate VAR(1) EGARCH results. After checking diagnostic tests, LBQ for u(1) is insignificant but LB-Q for u(2) is significant. Although I specified different VAR models, diagnostis test has never changed. Actually, I don't know what to do?

Thank you very much.
Ibrahim
ibrahim

Posts: 15
Joined: Wed Mar 20, 2013 10:50 am

Re: MV-EGARCH with spillovers

ibrahim wrote:Thank you so much Tom,

One more question about bivariate VAR(1) EGARCH results. After checking diagnostic tests, LBQ for u(1) is insignificant but LB-Q for u(2) is significant. Although I specified different VAR models, diagnostis test has never changed. Actually, I don't know what to do?

Thank you very much.
Ibrahim

I'm not sure what you mean by "I specified different VAR models". Did you increase the number of lags? That would be the only thing likely to fix the Q statistic. And how significant is it?
TomDoan

Posts: 2725
Joined: Wed Nov 01, 2006 5:36 pm

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