Returns an initial/quick guess of a given model's parameters.
Syntax
EGARCH_GUESS(X, Order, p, q, Innovation)
- X
- is the univariate time series data (a one-dimensional array of cells (e.g., rows or columns)).
- 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)).
Value Order 1 Ascending (the first data point corresponds to the earliest date) (default). 0 Descending (the first data point corresponds to the latest date). - p
- is the ARCH model component order.
- q
- is the GARCH model component order.
- Innovation
- is the probability distribution function of the innovations/residuals (1 = Gaussian (default), 2 = t-Distribution, 3 = GED).
Value Innovation 1 Gaussian or Normal Distribution (default). 2 Student's t-Distribution. 3 Generalized Error Distribution (GED).
Remarks
- The underlying model is described here.
- The time series is homogeneous or equally spaced.
- The time series may include missing values (e.g., #N/A) at either end.
- 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_GUESS returns the model's parameters in the following order:
- $\mu$.
- $\alpha_o,\phi_1,...,\phi_p$.
- $\gamma_1,\gamma_2,...,\gamma_p$.
- $\beta_1,\beta_2,...,\beta_q$.
- $\nu$.
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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