Horse race
You are now asked to run a horse race in terms of forecasting accuracy between the two approaches for making rolling GARCH model predictions:
garchroll
: AR(1) standard GARCH model and student \(t\) distributiongjrgarchroll
: AR(1) GJR GARCH model and skewed student \(t\) distribution.
The rolling estimations are implemented using n.start = 2500, refit.window = "moving", refit.every = 500
.
The resulting ugarchroll objects are available in the console.
This exercise is part of the course
GARCH Models in R
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Inspect the first three rows of the dataframe with out of sample predictions
garchpreds <- as.data.frame(garchroll)
head(garchpreds, ___)