moving_cov: Moving Covariance model

In dccmidas: DCC Models with GARCH and GARCH-MIDAS Specifications in the Univariate Step, RiskMetrics, Moving Covariance and Scalar and Diagonal BEKK Models

Moving Covariance model

Description

Obtains the matrix H_t, under the Moving Covariance model.

Usage

moving_cov(r_t, V = 22)

Arguments

r_t	List of daily returns
V	Length of the rolling window adopted. By default, V is 22

Value

A list with the H_t matrix, for each t.

Examples

require(xts)
# close to close daily log-returns
r_t_s<-diff(log(sp500['2010/2019'][,3]))
r_t_s[1]<-0
r_t_n<-diff(log(nasdaq['2010/2019'][,3]))
r_t_n[1]<-0
r_t_f<-diff(log(ftse100['2010/2019'][,3]))
r_t_f[1]<-0
db_m<-merge.xts(r_t_s,r_t_n,r_t_f)
db_m<-db_m[complete.cases(db_m),]
colnames(db_m)<-c("S&P500","NASDAQ","FTSE100")
# list of returns
r_t<-list(db_m[,1],db_m[,2],db_m[,3])
MC<-moving_cov(r_t,V=60)

dccmidas documentation built on May 29, 2024, 5:26 a.m.