# GARCH_GUESS - Initial Values for Model's Parameters

Returns the initial guess of a given model's parameters.

## Syntax

GARCH_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)).
Order Description
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 component of the variance model order.
q
is the GARCH component order of the model.
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)

## Remarks

1. The underlying model is described here.
2. The time series is homogeneous or equally spaced.
3. The time series may include missing values (e.g. #N/A) at either end.
4. GARCH_GUESS returns the model's parameters in the following order:
1. $\mu$
2. $\alpha_o,\phi_1,...,\phi_p$
3. $\beta_1,\beta_2,...,\theta_q$
4. $\nu$

## References

### Comments

Article is closed for comments.

Was this article helpful?
0 out of 0 found this helpful