Returns the initial guess of the model's parameters.

## Syntax

**GARCHM_GUESS** (**[x]**, order, **p**, **q**, f)

**[X]**- Required. Is the univariate time series data (a one-dimensional array of cells (e.g., rows or columns)).
**Order**- Optional. 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**- Required. Is the ARCH model component order.
**q**- Required. Is the GARCH model component order.
**F**- Optional. Is the probability distribution function of the innovations/residuals.
Value Probability Distribution 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.
- GARCHM_GUESS returns the model's parameters in the following order:
- $\mu$.
- $\lambda$.
- $\alpha_o,\phi_1,...,\phi_p$.
- $\beta_1,\beta_2,...,\theta_q$.
- $\nu$.

## Files Examples

## Related Links

## References

- James Douglas Hamilton; Time Series Analysis, Princeton University Press; 1st edition(Jan 11, 1994), ISBN: 691042896.
- Tsay, Ruey S.; Analysis of Financial Time Series, John Wiley & SONS; 2nd edition(Aug 30, 2005), ISBN: 0-471-690740.

## Comments

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