EGARCH_CHECK - Check parameters' values for model stability

Examines the model's parameters for stability constraints (e.g., stationary, positive variance, etc.).

Syntax

EGARCH_CHECK(mean, alphas, gammas, betas, innovation, v)

mean

is the E-GARCH model 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).

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).

v

is the shape parameter (or degrees of freedom) of the innovations/residuals probability distribution function.

Remarks

1. The underlying model is described here.
2. The time series is homogeneous or equally spaced.
3. The number of gamma-coefficients must match the number of alpha-coefficients.
4. The number of parameters in the input argument - alpha - determines the order of the ARCH component model.
5. The number of parameters in the input argument - beta - determines the order of the GARCH component model.
6. EGARCH_CHECK examines the model's coefficients for:
   
   • The coefficients are all positive.

Files Examples

Related Links

• Wikipedia - Autoregressive conditional heteroskedasticity.

References

• Hamilton, J .D.; Time Series Analysis, Princeton University Press (1994), ISBN 0-691-04289-6.
• Tsay, Ruey S.; Analysis of Financial Time Series John Wiley & SONS. (2005), ISBN 0-471-690740.