iClick.GARCH: iClick Output GUI for Univariate GARCH Models

Description

This GUI makes GARCH estimation of comparison easy. With a pre-selected GARCH type, it automatically fits eight probability distributions and conducts all diagnostic tests with a Click.

Usage

iClick.GARCH(dat, meanEQ = meanEQ, garchEQ = garchEQ, n.ahead = 15)

Arguments

dat

Time series object, xts.

meanEQ

Specification of mean equation.

garchEQ

Specification of variance equation.

n.ahead

Number of out-of-sample forecasting period.

Value

Fitted GARCH regression output.

Details

This GUI fits 8 distributions for univariate GARCH with pre-selected GARCH types, and returns a 54-button GUI output. The outputs can be individually saved as .RData file for later use, the last row is the save button.The saved filename is automatically generated once clicked, in addition, corresponding .csv files will be generated also. The 54-button GUI is divided into 9 panes, and the last pane collects coefficient outputs and diagnostic tests together, which aims to make estimation comparison easy.

Examples

Run this code

# NOT RUN {
##==External data
data("world20")
y=na.omit(diff(log(world20[,1])))

##== Simulation data
#dat=rnorm(200,5,1)
#y=ts(dat, start = c(1970, 1), frequency = 12)

meanEQ=list(AR=1,MA=0,Exo=NULL, autoFitArma=FALSE,arfimaDiff=FALSE,archM=FALSE)
  # If there are external regressors X, put them as Exo=X
  # autoFitArma=TRUE, If you want to fit arma automatically.
  # arfimaDiff=TRUE,to take ARFIMA difference
  # archM=TRUE, to estimate GARCH-in-mean

garchEQ=list(Type="sGARCH",P=1,Q=1, exo=NULL)
  # Type: "sGARCH","eGARCH","gjrGARCH","iGARCH","apGARCH"
  # please check rugarch for details.
  # P is the ARCH order
  # Q is the GARCH order

#iClick.GARCH(y,meanEQ, garchEQ,  n.ahead=15)
# This computation takes more than 6 seconds, hence I added a # to block it.

# }