New GDP VAR model based on quarterly data.

New S&P 500 forecast is based upon quarterly data. Therefore new quarterly data based VAR model for GDP is required.

v_GPC_q_1992_2016 <- merge(GDPC96["1992::2016-04-01"],to.quarterly(UNDCONTSA["1992::2016-04-01"])[,4])
v_GPC_q_1992_2016 <- merge(v_GPC_q_1992_2016,to.quarterly(PAYEMS["1992::2016-04-01"])[,4])
names(v_GPC_q_1992_2016)[2] <- "UNDCONTSA"
names(v_GPC_q_1992_2016)[3] <- "PAYEMS"
VARselect(v_GPC_q_1992_2016)
$selection
AIC(n)  HQ(n)  SC(n) FPE(n) 
    10      2      2     10 

$criteria
                  1            2            3            4            5            6            7            8            9
AIC(n) 2.789256e+01 2.551374e+01 2.550815e+01 2.549235e+01 2.552063e+01 2.551927e+01 2.558270e+01 2.561892e+01 2.537707e+01
HQ(n)  2.802866e+01 2.575191e+01 2.584840e+01 2.593467e+01 2.606502e+01 2.616573e+01 2.633124e+01 2.646954e+01 2.632976e+01
SC(n)  2.823038e+01 2.610492e+01 2.635270e+01 2.659026e+01 2.687190e+01 2.712390e+01 2.744070e+01 2.773029e+01 2.774180e+01
FPE(n) 1.299168e+12 1.204798e+11 1.200424e+11 1.185840e+11 1.226860e+11 1.235582e+11 1.332081e+11 1.403119e+11 1.124435e+11
                 10
AIC(n) 2.525669e+01
HQ(n)  2.631145e+01
SC(n)  2.787478e+01
FPE(n) 1.023095e+11

Then "lag.max" parameter for the new model is 10.

predict(VAR(v_GPC_q_1992_2016,lag.max=10))
my_sp5(predict(VAR(v_GPC_q_1992_2016,lag.max=10))$fcst$GDPC96[,1],predict(VAR(v_GPC_q_1992_2016,lag.max=10))$fcst$PAYEMS[,1],predict(VAR(v_GPC_q_1992_2016,lag.max=10))$fcst$UNDCONTSA[,1])

private function "my_sp5" will be explained in the  future post .