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GARCHM_VOL
Returns an array for the model fitted conditional volatilities/standard deviations.
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 GARCHM^{i} 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^{i}).
betas
are the parameters of the GARCH(q) component model (starting with the lowest lag).
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:
A  B  C  D  E  

1  Date  Data 
GARCHM_VOL "=GARCHM_VOL($B$2:$B$32,1,$E$3,$E$4,$E$5:$E$6,$E$7)" 

2  January 10, 2008  2.827  0.9966 
GARCHM(1,1) 

3  January 11, 2008  0.947  0.9966  Mean  0.076 
4  January 12, 2008  0.877  0.9966  Lambda  0.145 
5  January 13, 2008  1.209  0.9966  Alpha_0  0.593 
6  January 14, 2008  1.669  0.9966  Alpha_1  0.000 
7  January 15, 2008  0.835  0.9966  Beta_1  0.403 
8  January 16, 2008  0.266  0.9966  
9  January 17, 2008  1.361  0.9966  
10  January 18, 2008  0.343  0.9966  
11  January 19, 2008  0.475  0.9966  
12  January 20, 2008  1.153  0.9966  
13  January 21, 2008  1.144  0.9966  
14  January 22, 2008  1.070  0.9966  
15  January 23, 2008  1.491  0.9966  
16  January 24, 2008  0.686  0.9966  
17  January 25, 2008  0.975  0.9966  
18  January 26, 2008  1.316  0.9966  
19  January 27, 2008  0.125  0.9966  
20  January 28, 2008  0.712  0.9966  
21  January 29, 2008  1.530  0.9966  
22  January 30, 2008  0.918  0.9966  
23  January 31, 2008  0.365  0.9966  
24  February 1, 2008  0.997  0.9966  
25  February 2, 2008  0.360  0.9966  
26  February 3, 2008  1.347  0.9966  
27  February 4, 2008  1.339  0.9966  
28  February 5, 2008  0.481  0.9966  
29  February 6, 2008  1.270  0.9966  
30  February 7, 2008  1.710  0.9966  
31  February 8, 2008  0.125  0.9966  
32  February 9, 2008  0.940  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