GARCH.X (version 1.0)

simulate: Simulate GARCHX model

Description

Simulates Time series data from GARCH model with exogenous covariates

Usage

simulate(n, omega, alpha, beta, delta = 2, X, pi, shock.distr = "Normal", valinit = 200)

Value

A named list containing vector of Time Series data and X covariates used

Arguments

n

Desired length of simulated time series data

omega

Coefficient value for omega, required to be $$\omega_0 > 0$$

alpha

ARCH Coefficient value, required to be $$\alpha_0 \geq 0$$

beta

GARCH Coefficient value, required to be $$\beta_0 \geq 0$$

delta

Value of the power of the time series to allow for Power GARCHX, default is 2 for GARCHX

X

Matrix with exogenous covariates where the number of rows is equal to the length of n + valinit

pi

Vector containing coefficients for exogenous covariates.

shock.distr

Distribution of the shock eta_t that multiply w_t in the GARCH-X model eps_ = w_t*eta_t.

valinit

Initialization value, default value is 200

Examples

n <- 200
d <- 4
valinit <- 100
n2 <- n + d + 1
omega <- 0.05
alpha <- 0.05
beta <- 0.05
delta <- 2
pi <- rep(0.05, d)
e<-rnorm(n2+valinit)
Y<-e
for (t in 2:n2)
 Y[t]<- 0.2*Y[t-1]+e[t]
x<-exp(Y)
X <- matrix(0, nrow = (n+valinit), ncol = length(pi))
for(j in 1:d)
 X[, j] <- x[(d+2-j):(n+d+1-j+valinit)]
data <- simulate(n, omega, alpha, beta, delta, X, pi, valinit = valinit)