Returns an array of the fitted (insample) conditional mean values.
Syntax
GARCHM_MEAN(X, Order, mean, lambda, alphas, betas)
 X
 is the univariate time series data (a one dimensional array of cells (e.g. rows or columns)).
 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).
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 fitted conditonal mean is calculated as:
$$\hat x_t = \mu + \lambda \sigma_t$$
Where: $\hat x_t$ is the fitted conditional mean at time t.
 $\sigma_t$ is the fitted conditional volatility at time t.
 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:


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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