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segMGarch (version 1.3)

Multiple Change-Point Detection for High-Dimensional GARCH Processes

Description

Implements a segmentation algorithm for multiple change-point detection in high-dimensional GARCH processes. It simultaneously segments GARCH processes by identifying 'common' change-points, each of which can be shared by a subset or all of the component time series as a change-point in their within-series and/or cross-sectional correlation structure.

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Version

Install

install.packages('segMGarch')

Monthly Downloads

204

Version

1.3

License

GPL (>= 2)

Maintainer

Karolos Korkas

Last Published

July 6th, 2025

Functions in segMGarch (1.3)

pc_cccsim-class

A method to simulate nonstationary high-dimensional CCC GARCH models.
tvMGarch-class

An S4 class for a nonstationary multivariate class model.
TL

Method to backtest VaR violation using the Traffic Light (TL) approach of Basel
DQtest

A regression-based test to backtest VaR models proposed by Engle and Manganelli (2004)
gen_pc_coef-class

A method to generate piecewise constant coefficients
segMGarch-package

Multiple Change-Point Detection for High-Dimensional GARCH Processes
garch.seg-class

An S4 method to detect the change-points in a high-dimensional GARCH process.
simMGarch-class

An S4 class for a nonstationary CCC model.
pc_Sigma

Method to simulate correlated variables with change-points
kupiec

Method to backtest VaR violation using the Kupiec statistics