tvMGarch-class: An S4 class for a nonstationary multivariate class model.

In segMGarch: Multiple Change-Point Detection for High-Dimensional GARCH Processes

An S4 class for a nonstationary multivariate class model.

Description

A specification class to create an object of a nonstationary multivariate class model reserved for real (empirical) applications. It inherits from simMGarch.

Slots

out_of_sample_prop

Proportion of y to keep for out-of-sample forecasting expressed in %.

out_of_sample_y

The out of sample y matrix reserved for forecasting and backtesting exercises.

in_sample_y

The in-sample y matrix reserved for estimation (calibration) and change-point detection.

References

Cho, H. and Korkas, K.K., 2022. High-dimensional GARCH process segmentation with an application to Value-at-Risk. Econometrics and Statistics, 23, pp.187-203.

Examples

simObj <- new("simMGarch")
simObj@d <- 10
simObj@n <- 1000
simObj@changepoints <- c(250,750)
simObj <- pc_cccsim(simObj)
empirObj <- new("tvMGarch") #simulated, but treated as a real dataset for illustration
empirObj@y <- simObj@y
empirObj@out_of_sample_prop <- 0.1
#empirObj=garch.seg(object=empirObj,do.parallel = 4)##Not run

segMGarch documentation built on Aug. 8, 2025, 6:07 p.m.