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segMGarch (version 1.2)

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

193

Version

1.2

License

GPL (>= 2)

Maintainer

Karolos Korkas

Last Published

January 17th, 2019

Functions in segMGarch (1.2)

segMGarch-package

Multiple Change-Point Detection for High-Dimensional GARCH Processes
gen_pc_coef-class

A method to generate piecewise constant coefficients
garch.seg-class

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

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

Method to backtest VaR violation using the Kupiec statistics
TL

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

Method to simulate correlated variables with change-points
simMGarch-class

An S4 class for a nonstationary CCC model.
tvMGarch-class

An S4 class for a nonstationary multivariate class model.
pc_cccsim-class

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