(deprecated) Calculates the estimated error/standard deviation of the conditional mean forecast.
Syntax
GARCHM_FORESD(X, Sigmas, Order, mean, lambda, alphas, betas, T, Local)
 X
 is the univariate time series data (a one dimensional array of cells (e.g. rows or columns)) of the last p observations.
 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).
 T
 is the forecast time horizon (expressed in terms of steps beyond the end of the time series X). If missing, t=1 is assumed.
 Local
 is the type of desired volatility output (0=Term Structure, 1=Local Volatility). If missing, local volatility is assumed.
Warning
GARCHM_FORESD() 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 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_FORESD($B$2:$B$32,1,$D$3,$D$4,$D$5:$D$6,$D$7,1)  Forecasted conditional volatility at T+1, February 10, 2008 (0.9966) 
=GARCHM_FORESD($B$2:$B$32,1,$D$3,$D$4,$D$5:$D$6,$D$7,2)  Forecasted conditional volatility at T+2, February 11, 2008 (0.9966) 
=GARCHM_FORESD($B$2:$B$32,1,$D$3,$D$4,$D$5:$D$6,$D$7,3)  Forecasted conditional volatility at T+3, February 12, 2008 (0.9966) 
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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