GARCH_FORECI - Forecasting Confidence Interval of GARCH Model

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


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

Required. Is the univariate time series data (a one-dimensional array of cells (e.g., rows or columns)).
Optional. Is the univariate time series data (a one-dimensional array of cells (e.g., rows or columns)) of the last q realized volatilities.
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).
Optional. Is the GARCH model long-run mean (i.e., mu). If missing, the process mean is assumed to be zero.
Required. Are the parameters of the ARCH(p) component model: [αo α1, α2 … αp] (starting with the lowest lag).
Optional. Are the parameters of the GARCH(q) component model: [β1, β2 … βq] (starting with the lowest lag).
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).
Optional. Is the shape parameter (or degrees of freedom) of the innovations/residuals’ probability distribution function.
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.
Optional. Is the statistical significance level (i.e., alpha). If missing or omitted, an alpha value of 5% is assumed.
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.


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


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

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