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ARMA_FORESD
Calculates the estimated error/standard deviation of the conditional mean forecast.
Syntax
X
is the univariate time series data (a one dimensional array of cells (e.g. rows or columns)).
Order
is the time order of the data series (i.e. whether the first data point corresponds to the earliest or latest date (earliest date=1 (default), latest date=0)).
Order  Description 

1  ascending (the first data point corresponds to the earliest date) 
0  descending (the first data point corresponds to the latest date) 
mean
is the ARMA model mean (i.e. mu).
sigma
is the standard deviation of the model's residuals/innovations.
phi
are the parameters of the AR(p) component model (starting with the lowest lag^{i}).
theta
are the parameters of the MA(q) component model (starting with the lowest lag).
T
is the forecast time/horizon (expressed in terms of steps beyond end of the time series).
Remarks
 The underlying model is described here.
 Warning: ARMA_FORESD() function is deprecated as of version 1.63: use ARMA_FORE function instead.
 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  phi  determines the order of the AR component.
 The number of parameters in the input argument  theta  determines the order of the MA component.
Examples
Example 1:
A  B  C  D  

1  Date  Data  
2  1/1/2008  0.30 
ARMA 

3  1/2/2008  1.28  Mean  0.00258 
4  1/3/2008  0.24  Sigma  0.14 
5  1/4/2008  1.28  Phi_1  0.236 
6  1/5/2008  1.20  Theta_1  5.60E05 
7  1/6/2008  1.73  
8  1/7/2008  2.18  
9  1/8/2008  0.23  
10  1/9/2008  1.10  
11  1/10/2008  1.09  
12  1/11/2008  0.69  
13  1/12/2008  1.69  
14  1/13/2008  1.85  
15  1/14/2008  0.98  
16  1/15/2008  0.77  
17  1/16/2008  0.30  
18  1/17/2008  1.28  
19  1/18/2008  0.24  
20  1/19/2008  1.28  
21  1/20/2008  1.20  
22  1/21/2008  1.73  
23  1/22/2008  2.18  
24  1/23/2008  0.23  
25  1/24/2008  1.10  
26  1/25/2008  1.09  
27  1/26/2008  0.69  
28  1/27/2008  1.69  
29  1/28/2008  1.85  
30  1/29/2008  0.98 
Formula  Description (Result)  

=ARMA_FORE($B$2:$B$30,1,$D$3,$D$4,$D$5,$D$6,1)  The conditional mean forecast value at T+1 (0.228)  
=ARMA_FORESD($B$2:$B$30,1,$D$3,$D$4,$D$5,$D$6,1)  The conditional mean forecast error at T+1 (0.140) 
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