BEKK11: BEKK Model

In d-/MTS: All-Purpose Toolkit for Analyzing Multivariate Time Series (MTS) and Estimating Multivariate Volatility Models

BEKK Model

Description

Estimation of a BEKK(1,1) Model for a k-dimensional time series. Only k = 2 or 3 is available

Usage

BEKK11(rt, include.mean = T, cond.dist = "normal", ini.estimates = NULL)

Arguments

rt	A T-by-k data matrix of k-dimensional asset returns
include.mean	A logical switch to include a constant vector in the mean equation. Default is with a constant vector.
cond.dist	Conditional innovation distribution. Only Gaussian innovations are used in the current version.
ini.estimates	Optional initial estimates.

Value

estimates	Parameter estimates
HessianMtx	Hessian matrix of the estimates
Sigma.t	The multivariate volatilities, each row contains k-by-k elements of the volatility matrix Sigma(t)

Author(s)

Ruey S. Tsay

References

Tsay (2014, Chapter 7)

Examples

 #data("mts-examples",package="MTS")
 #da=ibmspko
 #rtn=log(da[,2:3]+1)
 #m1=BEKK11(rtn)

d-/MTS documentation built on June 12, 2022, 12:50 a.m.