tegarchSim {betategarch} | R Documentation |
Simulate from a first order Beta-Skew-t-EGARCH model
Description
Simulate the y series (typically interpreted as a financial return or the error in a regression) from a first order Beta-Skew-t-EGARCH model. Optionally, the conditional scale (sigma), log-scale (lambda), conditional standard deviation (stdev), dynamic components (lambdadagger in the 1-component specification, lambda1dagger and lambda2dagger in the 2-component specification), score (u) and centred innovations (epsilon) are also returned.
Usage
tegarchSim(n, omega = 0, phi1 = 0.95, phi2 = 0, kappa1 = 0.01, kappa2 = 0,
kappastar = 0, df = 10, skew = 1, lambda.initial = NULL, verbose = FALSE)
Arguments
n |
integer, length of y (i.e. no of observations) |
omega |
numeric, the value of omega |
phi1 |
numeric, the value of phi1 |
phi2 |
numeric, the value of phi2 |
kappa1 |
numeric, the value of kappa1 |
kappa2 |
numeric, the value of kappa2 |
kappastar |
numeric, the value of kappastar |
df |
numeric, the value of df (degrees of freedom) |
skew |
numeric, the value of skew (skewness parameter |
lambda.initial |
NULL (default) or initial value(s) of the recursion for lambda or log-volatility. If NULL then the values are chosen automatically |
verbose |
logical, TRUE or FALSE (default). If TRUE then a matrix with n rows containing y, sigma, lambda, lambdadagger, u and epsilon is returned. If FALSE then only y is returned |
Details
Empty
Value
A zoo
vector of length n or a zoo
matrix with n rows, depending on the value of verbose.
Author(s)
Genaro Sucarrat, http://www.sucarrat.net/
References
Fernandez and Steel (1998), 'On Bayesian Modeling of Fat Tails and Skewness', Journal of the American Statistical Association 93, pp. 359-371.
Harvey and Sucarrat (2014), 'EGARCH models with fat tails, skewness and leverage'. Computational Statistics and Data Analysis 76, pp. 320-338.
Sucarrat (2013), 'betategarch: Simulation, Estimation and Forecasting of First-Order Beta-Skew-t-EGARCH models'. The R Journal (Volume 5/2), pp. 137-147.
See Also
Examples
##1-component specification: simulate series with 500 observations:
set.seed(123)
y <- tegarchSim(500, omega=0.01, phi1=0.9, kappa1=0.1, kappastar=0.05,
df=10, skew=0.8)
##simulate the same series, but with more output (volatility, log-volatility or
##lambda, lambdadagger, u and epsilon)
set.seed(123)
y <- tegarchSim(500, omega=0.01, phi1=0.9, kappa1=0.1, kappastar=0.05, df=10, skew=0.8,
verbose=TRUE)
##plot the simulated values:
plot(y)
##2-component specification: simulate series with 500 observations:
set.seed(123)
y <- tegarchSim(500, omega=0.01, phi1=0.95, phi2=0.9, kappa1=0.01, kappa2=0.05,
kappastar=0.03, df=10, skew=0.8)