brfut3 <- da[1:84,5]
brfut4 <- da[1:84,6]
brfut5 <- da[1:84,7]
brfut6 <- da[1:84,8]
brfut7 <- da[1:84,9]
brfut8 <- da[1:84,10]
brfut9 <- da[1:84,11]
brfut10 <- da[1:84,12]
brfut11 <- da[1:84,13]
brfut12 <- da[1:84,14]
germango <- da[1:84,28]
# Monthly gross return grossreturn <- da[,7]
grossreturnM <- matrix(grossreturn,95,1) basicStats(grossreturnM)
# First we need to test for ARCH-effects,
# we use the package "arch.test"
ones <- rep(1,95)
ols <- lm(ts(grossreturnM)~ones);ols residuals<-ols$residuals
# ARCH LM-test; Null hypothesis: no ARCH effects ArchTest(residuals,lags=1)
ArchTest(residuals,lags=5) ArchTest(residuals,lags=12)
# There definitely are ARCH-effects. We continue with a
# GARCH-M(1,1) specification.
pacf(grossreturnM)
# Fitting a GARCH-M(1,1)-model to the data
gr.fit <- garchFit(~garch(1,1),data=grossreturnM, include.mean=TRUE)
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