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GARCH_CHECK
Examines the model's parameters for stability constraints (e.g. stationary, positive variance, etc.).
Syntax
GARCHi_CHECK(mean, alphas, betas, innovation, v)
mean
is the model mean (i.e. mu).
alphas
are the parameters of the ARCH(p) component model (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 of the innovations/shocks (1=Gaussian, 2=t-Distribution, 3=GEDi). If missing, a gaussian distribution is assumed
| value | Description |
|---|---|
| 1 | Gaussian or Normal Distribution (default) |
| 2 | Student's t-Distribution |
| 3 | Generalized Error Distribution (GED) |
v
is the shape factor (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 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.
-
GARCH_CHECK examines the model's coefficients for:
Examples
Example 1:
| A | B | |
|---|---|---|
| 1 |
GARCH(1,1) |
|
| 2 | Mean | -0.160 |
| 3 | Alpha_0 | 0.608 |
| 4 | Alpha_1 | 0.000 |
| 5 | Beta_1 | 0.391 |
| Formula | Description (Result) | |
|---|---|---|
| =GARCH_CHECK($B$2,$B$3:$B$4,$B$5) | The model is stable? (1) |
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
