Box-Jenkins Model

Box-Jenkins Model

A methodology that makes forecasts of future economic behavior by applying a best fit model to past behavior. In using the model, one applies an autoregressive moving average to past data. In order to do this accurately, one must identify the data being measured and ensure it is independent of other variables, define the parameters of investigation, and check the model. The model is used in econometrics.
References in periodicals archive ?
Data obtained through the Box-Jenkins model, which were applied to develop index forecasting for trading volume of options on futures contracts, tend to show a decrease in the value question.
5]; Appendix) was formulated for the Box-Jenkins model developed in step 2.
This technique was found to be optimal for the Box-Jenkins model (Eq.
The documented step-by-step algorithm procedures for moving averages, exponential smoothing, Winter's model, multiplicative decomposition, Box-Jenkins model, cycle regression, and multiple regression have successfully avoided computerese and forecasting jargon.
Still, it's nice to sit down and watch your computer do most of the thinking for you, spitting out solutions to complex Box-Jenkins models every two seconds (if you have a built-in math coprocessor) or every thirty seconds (if you don't).
A quick skim through the manual left me with only one minor quibble: The authors apparently do not believe in parsimonious parameterization of Box-Jenkins models.