Examines the model's parameters for stability constraints (e.g. stationarity, invertibility, causality, etc.).
Syntax
ARMAX_CHECK(mean, sigma, phi, theta)
- mean
- is the ARMA long run mean (mu) or the regression intercept.
- 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).
Remarks
- The underlying model is described here.
- The time series is homogeneous or equally spaced.
- ARMAX_CHECK examines the model for stability: stationarity, invertibility, and causality.
- Using the Solver add-in in Excel, you can specify the return value of ARMAX_CHECK as a constraint to ensure a stationary ARMA model.
- The long-run mean can take any value or be omitted, in which case a zero value is assumed.
- The residuals/innovations standard deviation (sigma) must be greater than zero.
- For the input argument (beta):
- The input argument is optional and can be omitted, in which case no regression component is included (i.e. plain ARMA).
- The order of the parameters defines how the exogenous factor input arguments are passed.
- One or more parameters may have missing values or error codes (i.e. #NUM!, #VALUE!, etc.).
- 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 values or error codes (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).
- 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).
- The function was added in version 1.63 SHAMROCK.
Files Examples
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
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