EGARCH_SIM - Simulated values of an EGARCH Model

Returns an array of cells for the model simulated values.

Syntax

EGARCH_SIM(X, Sigmas, Order, mean, alphas, gammas, betas, innovation, Nu, T, seed)
X
is the univariate time series data (a one dimensional array of cells (e.g. rows or columns)).
Sigmas
is the univariate time series data (a one dimensional array of cells (e.g. rows or columns)) of the last q realized volatilities.
Order
is the time order in the data series (i.e. the first data point's corresponding date (earliest date=1 (default), latest date=0)).
Order Description
1 ascending (the first data point corresponds to the earliest date) (default)
0 descending (the first data point corresponds to the latest date)
mean
is the E-GARCH model marginal (unconditional) mean (i.e. mu).
alphas
are the parameters of the ARCH(p) component model (starting with the lowest lag).
gammas
are the leverage parameters (starting with the lowest lag). If missing, leverage parameters (i.e. gammas) are assumed zeroes.
betas
are the parameters of the GARCH(q) component model (starting with the lowest lag).
innovation
is the probability distribution function of the innovations/residuals (1=Gaussian (default), 2=t-Distribution, 3=GED).
value Description
1 Gaussian or Normal Distribution (default)
2 Student's t-Distribution
3 Generalized Error Distribution (GED)
Nu
is the shape parameter (or degrees of freedom) of the innovations/residuals probability distribution function.
T
is the simulation path time/horizon (expressed in terms of steps beyond end of the time series).
seed
is an unsigned integer for setting up the random number generator(s).

Remarks

1. The underlying model is described here.
2. The time series is homogeneous or equally spaced.
3. The time series may include missing values (e.g. #N/A) at either end.
4. The number of gamma-coefficients must match the number of alpha-coefficients.
5. The number of parameters in the input argument - alpha - determines the order of the ARCH component model.
6. The number of parameters in the input argument - beta - determines the order of the GARCH component model.
7. By definition, the EGARCH_FORE function returns a constant value equal to the model mean (i.e. $\mu$) for all horizons.
8. The function EGARCH_SIM was added in version 1.63 SHAMROCK.