library(fGarch)

# garch data with normal innovations
spec.norm <- garchSpec(model = list(omega = 0.02, alpha = 0.2, beta = 0.7,
  mu = 0.1), cond.dist="norm", rseed = 2008)
garch.norm <- garchSim(spec = spec.norm, n = 2000, n.start = 1000)

# garch data with student innovations with degree of freedom = 8
spec.std <- garchSpec(model = list(omega = 0.02, alpha = 0.2, beta = 0.7,
  mu = 0.1, shape = 8), cond.dist = "std", rseed = 2008)
garch.std <- garchSim(spec = spec.std, n = 2000, n.start = 1000)

# estimation of the normal garch
model.norm.hess <- garchFit(~ garch(1,1), garch.norm, cond.dist = "norm",
	algorithm = "nlminb", hessian = "rcd")
summary(model.norm.hess)

model.norm.QMLE <- garchFit(~ garch(1,1), garch.norm, cond.dist = "QMLE",
	algorithm = "nlminb", hessian = "rcd")
summary(model.norm.QMLE)

# estimation of the student garch
model.std.hess <- garchFit(~ garch(1,1), garch.std, cond.dist = "norm",
	algorithm = "nlminb", hessian = "rcd")
summary(model.std.hess)

model.std.QMLE <- garchFit(~ garch(1,1), garch.std, cond.dist = "QMLE",
	algorithm = "nlminb", hessian = "rcd")
summary(model.std.QMLE)