Y is the response or the dependent variable time series data array (one dimensional array of cells (e.g. rows or columns)).

X is the independent variables (exogenous factors) time series data matrix, such that each column represents one variable.

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)).

Beta are the coefficients array of the exogenous factors.

mean is the ARMA long-run mean (i.e. mu).

sigma is the standard deviation of the model's residuals.

phi are the parameters of the AR(p) component model (starting with the lowest lag).

theta are the parameters of the MA(q) component model (starting with the lowest lag).

T is the simulation time/horizon (expressed in terms of steps beyond end of the time series).

seed is an unsigned integer for setting up the random number generator(s)

1. The underlying model is described here.
2. The Log-Likelihood Function (LLF) is described here.
3. ARMAX_SIM returns an array of one simulation path starting from the end of the input data.
4. The response input data argument (i.e. latest observations) is optional. If omitted, an array of zeroes is assumed.
5. The number of observations in the factors (exogenous variables) input data must be greater than or equal to the size of response input data plus horizon.
6. The time series (response and factors) are homogeneous or equally spaced.
7. The time series may include missing values (e.g. #N/A) at either end.
8. The observation at any given time is examined using the response and factors value, so a missing values (e.g. #N/A) in any of the input time series, deem the whole observation as missing.
9. The long-run mean can take any value or omitted, in which case a zero value is assumed.
10. The residuals/innovations standard deviation (sigma) must greater than zero.
11. For the input argument - phi:
    • The input argument is optional and can be omitted, in which case no AR component is included.
    • The order of the parameters starts with the lowest lag
    • One or more parameters may have missing value or an error code(i.e. #NUM!, #VALUE!, etc.).
    • The order of the AR component model is solely determined by the order of the last value in the array with a numeric value (vs. missing, or error).
12. For the input argument - theta:
    • The input argument is optional and can be omitted, in which case no MA component is included.
    • The order of the parameters starts with the lowest lag
    • One or more values in the input argument can be missing or an error code(i.e. #NUM!, #VALUE!, etc.).
    • The order of the MA component model is solely determined by the order of the last value in the array with a numeric value (vs. missing, or error).
13. The function ARMAX_SIM is available starting with version 1.63 SHAMROCK.

Files Examples

Related Links

• Wikipedia - Likelihood function
• Wikipedia - Likelihood principle
• Wikipedia - Autoregressive moving average model

References

• Hamilton, J .D.; Time Series Analysis , Princeton University Press (1994), ISBN 0-691-04289-6
• Tsay, Ruey S.; Analysis of Financial Time Series John Wiley & SONS. (2005), ISBN 0-471-690740