## garchFit -
# Parameter Estimation of Default GARCH(1,1) Model:
set.seed(123)
fit = garchFit(~ garch(1, 1), data = garchSim(), trace = FALSE)
fit
## predict -
predict(fit, n.ahead = 10)
predict(fit, n.ahead = 10, mse="uncond")
## predict with plotting: critical values = +/- 2
predict(fit, n.ahead = 10, plot=TRUE, crit_val = 2)
## predict with plotting: automatic critical values
## for different conditional distributions
set.seed(321)
fit2 = garchFit(~ garch(1, 1), data = garchSim(), trace=FALSE, cond.dist="sged")
## 95% confidence level
predict(fit2, n.ahead=20, plot=TRUE)
set.seed(444)
fit3 = garchFit(~ garch(1, 1), data = garchSim(), trace=FALSE, cond.dist="QMLE")
## 90% confidence level and nx=100 :
predict(fit3, n.ahead=20, plot=TRUE, conf=.9, nx=100)
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