(**Deprecated**) Returns the confidence interval limits of the conditional mean forecast.

## Syntax

**GARCH_FORECI** (**[x]**, [σ], order, µ, **[α]**, [β], f, ν, t, α, **upper**)

**[X]**- Required. Is the univariate time series data (a one-dimensional array of cells (e.g., rows or columns)).
**[σ]**- Optional. Is the univariate time series data (a one-dimensional array of cells (e.g., rows or columns)) of the last q realized volatilities.
**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). **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).
**[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.
**T**- Optional. Is the forecast time/horizon (expressed in terms of steps beyond the end of the time series X). If missing, t = 1 is assumed.
**α**- Optional. Is the statistical significance level (i.e., alpha). If missing or omitted, an alpha value of 5% is assumed.
**Upper**- Required. If true, function returns the upper confidence interval limit. Otherwise, it returns the lower limit.
Value Upper 0 Returns the lower limit. 1 Returns the upper limit.

* *Warning

GARCH_FORECI(.) function is deprecated as of version 1.63; use the GARCH_FORE(.) function instead.

## 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 significance level (α) must be greater than zero and less than one. Otherwise, a #VALUE! is returned.
- The number of steps must be greater than zero. Otherwise, a #VALUE! is returned.

## 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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