residualsdcc: Residuals for MGARCH(1,1) DCC models

In TaoussD/EbEEMGARCH: Estimating MGARCH(1,1) model equation by equation

Description

Compute the residuals from the estimation of a MGARCH(1,1) DCC on data

Usage

residuals_DCC(Omega,A,B,alpha,beta,S,eps,r=10,type)

Arguments

With usual notations

Omega	Estimation of Omega
A	Estimation of A
B	Estimation of B
alpha	Estimation of alpha
beta	Estimation of beta
S	Estimation of S
eps	Data used
r	Number of observations for the initial conditions
type	type="Engle" for Engle-DCC type="Aielli" for Aielli-DCC

Details

Residuals are necessary to compute quantile for the estimation of the VaR of financial series

Value

With usual notations

Ht	List of Ht
Rt	List or Rt
eta	Residuals

Author(s)

D. Taouss & C. Francq

References

C. Francq & J.M. Zakoian, Estimating multivariate GARCH and Stochastic Correlation models equation by equation, October 2014
G.P. Aielli, Dynamic Conditional Correlation: on Properties and Estimation, July 2011

See Also

EbEEMGARCH Homepage of the documentation

Examples

#Simulation of the yield of 2 assets
m<-2
n <- 800
Omega <- c(0.001, 0.001);
A <- matrix(c(0.03, 0.01, 0.01, 0.03), nrow = 2)
B <- c(0.1, 0.1);
S <- matrix(c(1, 0.4, 0.4, 1), nrow = 2)
alpha <- 0.05;
beta <- 0.97 - alpha
nu <- 14

yield <- GarchDCC.sim(n, Omega, A, B, alpha, beta, S, nu = nu, noise = "student", model = "Aielli")

#Estimation of the parameters (3-steps method)
EbEE<-estimDCC.EbEE(Omega,A,B,S,alpha,beta,yield$sim,type="Aielli")

var <- residuals_DCC(EbEE$Omega, EbEE$A, EbEE$B, EbEE$alpha, EbEE$beta, EbEE$S, yield$sim, type="Aielli")

TaoussD/EbEEMGARCH documentation built on May 9, 2019, 4:18 p.m.