tvMGarch-class

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

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.

Karolos Korkas

segMGarch

Multiple Change-Point Detection for High-Dimensional GARCH
Processes

Haeran Cho

tvMGarch-class function

<dl>
<dt><code>out_of_sample_prop</code></dt>
<dd>Proportion of y to keep for out-of-sample forecasting expressed in %.</dd></dl>
<dt><code>out_of_sample_y</code></dt>
<dd>The out of sample y matrix reserved for forecasting and backtesting exercises.</dd>
<dt><code>in_sample_y</code></dt>
<dd>The in-sample y matrix reserved for estimation (calibration) and change-point detection.</dd>

Slots

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

<dl>
<dt><code>out_of_sample_prop</code></dt>
<dd>Proportion of y to keep for out-of-sample forecasting expressed in %.</dd>


<dt><code>out_of_sample_y</code></dt>
<dd>The out of sample y matrix reserved for forecasting and backtesting exercises.</dd>


<dt><code>in_sample_y</code></dt>
<dd>The in-sample y matrix reserved for estimation (calibration) and change-point detection.</dd>


</dl>

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

Description

Arguments

Slots

References

Examples