Forecasting variance/covariance Diagonal BEKK

[ErikH]

Hello, for my thesis I am trying to forecast the variance and covariance of two series (spot and futures series), both in- and out-sample (in-sample 85%). The code below was found on this forum, however when I try to run the forecast something goes wrong and the forecast is not produced. I believe there might be a mistake in the section where the dynamic series are formulated, however due to lack of eviews knowledge I am not sure. I hope someone is willing to help. In the attachements I added all the data, the workfile and the code I use.

Kind Regards, Erik Homan

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'First order model (BEKK-GARCH(1,1)) is assumed. sym(2) M vector(2) A1 vector(2) B1 'Create a system %sys = "sysbekk" system {%sys} '{%sys}.append duks = c(1) '{%sys}.append dukf = c(2) {%sys}.append logspot = c(1) {%sys}.append logfirst= c(2) 'Estimate the system as diagonal BEKK 'smpl @first @first+368 smpl @first @first+2440 {%sys}.arch @diagbekk c arch(1) garch(1) 'Save the conditional series {%sys}.makegarch 'Compute the in-sample hedge ratio 'series hr = garch_02/garch_01_02 series hr = garch_01_02 / garch_02 delete garch* 'Rolling forecasts 'for !i=1 to 154 for !i=1 to 10 'smpl @first @first+368+!i-1 smpl @first @first+2440+!i-1 {%sys}.arch @diagbekk c arch(1) garch(1) {%sys}.makegarch {%sys}.makeresids 'Generate new series for forecasted variables for %y GARCH_01 GARCH_02 GARCH_01_02 RESID01 RESID02 series {%y}f= {%y} next 'Organize the estimated coefficients into matrix form. 'Constant is assumed to be the only exogenous variable in each mean equation. 'Therefore coefficients of variance specification should start at c(3). M(1,1)={%sys}.@coefs(3) M(1,2)={%sys}.@coefs(4) M(2,2)={%sys}.@coefs(5) A1(1)={%sys}.@coefs(6) A1(2)={%sys}.@coefs(7) B1(1)={%sys}.@coefs(8) B1(2)={%sys}.@coefs(9) 'Number of observations used in the estimation !n={%sys}.@regobs 'Define out of sample forecast horizon !h = 1 'Perform dynamic forecasts via adjusting the sample (do not forget the missing value due to lag structure) for !j=1 to !h smpl @first+!n+!j @first+!n+!j+1 GARCH_01f = M(1,1) + A1(1)^2*RESID01f(-1)^2 + B1(1)^2*GARCH_01f(-1) GARCH_02f = M(2,2) + A1(2)^2*RESID02f(-1)^2 + B1(2)^2*GARCH_02f(-1) GARCH_01_02f= M(1,2) + A1(1)*A1(2)*RESID01f(-1)*RESID02f(-1) + B1(1)*B1(2)*GARCH_01_02f(-1) RESID01f = 0 RESID02f = 0 next 'Out-sample hedge ratios series hrf = garch_01_02f / garch_02f 'Combine in-sample and out-sample hedge ratios into one series hr = hrf delete garch* resid0* next smpl @all