Multiple Change-Point Detection for High-Dimensional GARCH Processes
A regression-based test to backtest VaR models proposed by Engle and M...
An S4 method to detect the change-points in a high-dimensional GARCH p...
A method to generate piecewise constant coefficients
Method to backtest VaR violation using the Kupiec statistics
A method to simulate nonstationary high-dimensional CCC GARCH models.
Method to simulate correlated variables with change-points
Multiple Change-Point Detection for High-Dimensional GARCH Processes
An S4 class for a nonstationary CCC model.
Method to backtest VaR violation using the Traffic Light (TL) approach...
An S4 class for a nonstationary multivariate class model.
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.