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 (µ, [α], [γ], [β], f, ν)

µ
Optional. Is the GARCH model long-run mean (i.e., mu). If missing, the process mean is assumed to be zero.
[α]
Required. Are the parameters of the ARCH(p) component model: [αo α1, α2 … αp] (starting with the lowest lag).
[γ]
Optional. Are the leverage parameters: [γ1, γ2 … γp] (starting with the lowest lag).
[β]
Optional. Are the parameters of the GARCH(q) component model: [β1, β2 … βq] (starting with the lowest lag).
F
Optional. Is the probability distribution function of the innovations/residuals (1 = Gaussian (default), 2 = t-Distribution, 3 = GED).
Value Probability Distribution
1 Gaussian or Normal Distribution (default).
2 Student's t-Distribution.
3 Generalized Error Distribution (GED).
ν
Optional. 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 (minus one).
  4. The number of parameters in the input argument - [αo α1, α2 … αp] - determines the order of the ARCH component model.
  5. The number of parameters in the input argument - [β1, β2 … βq] - determines the order of the GARCH component model.
  6. EGARCH_CHECK examines the model's coefficients for:
    • The coefficients are all positive.

Files Examples

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References

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