(deprecated) Returns the confidence interval limits of the conditional mean forecast.
Syntax
GARCHM_FORECI(X, Sigmas, Order, mean, lambda, alphas, betas, innovation, v, T, alphalevel, upper)
 X
 is the univariate time series data (a one dimensional array of cells (e.g. rows or columns)).
 Sigmas
 is the univariate time series data (a one dimensional array of cells (e.g. rows or columns)) of the last q realized volatilities.
 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)  mean
 is the GARCHM model mean (i.e. mu).
 lambda
 is the volatility coefficient for the mean. In finance, lambda is referenced as the risk premium.
 alphas
 are the parameters of the ARCH(p) component model (starting with the lowest lag).
 betas
 are the parameters of the GARCH(q) component model (starting with the lowest lag).
 innovation
 is the probability distribution model for the innovations/residuals (1=Gaussian (default), 2=tDistribution, 3=GED).
value Description 1 Gaussian or Normal Distribution (default) 2 Student's tDistribution 3 Generalized Error Distribution (GED)  v
 is the shape parameter (or degrees of freedom) of the innovations/residuals probability distribution function.
 T
 is the forecast time/horizon (expressed in terms of steps beyond end of the time series X).
 alphalevel
 is the statistical significance level. If missing, a default of 5% is assumed.
 upper
 If true, returns the upper confidence interval limit. Otherwise, returns lower limit.
upper description 0 return lower limit 1 return upper limit
Warning
GARCHM_FORECI() function is deprecated as of version 1.63: use GARCHM_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 (i.e. $\alpha$) must be greater than zero and less than one. Otherwise, the function returns #VALUE!
 The number of steps must be greater than zero. Otherwise, the function returns #VALUE!
 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.
Examples
Example 1:


Formula  Description (Result) 

=GARCHM_FORECI($B$2:$B$32,1,$D$3,$D$4,$D$5:$D$6,$D$7,1,0.05,1)  Upper confidence interval limit (2.0219) 
=GARCHM_FORECI($B$2:$B$32,1,$D$3,$D$4,$D$5:$D$6,$D$7,1,0.05,0)  Lower confidence interval limit (1.885) 
Files Examples
References
 Hamilton, J .D.; Time Series Analysis , Princeton University Press (1994), ISBN 0691042896
 Tsay, Ruey S.; Analysis of Financial Time Series John Wiley & SONS. (2005), ISBN 0471690740
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