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
- The underlying model is described here.
- The time series is homogeneous or equally spaced.
- The number of gamma-coefficients must match the number of alpha-coefficients.
- The number of parameters in the input argument - alpha - determines the order of the ARCH component model.
- The number of parameters in the input argument - beta - determines the order of the GARCH component model.
- EGARCH_CHECK examines the model's coefficients for:
- The coefficients are all positive.
Files Examples
Related Links
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.
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