High Quality Content by WIKIPEDIA articles! In statistics, Wold's theorem or Wold representation theorem, named after Herman Wold, says that every covariance-stationary time series Yt can be written as an infinite moving average (MA(infty)) process of its innovation process. Such a formulation is known as a moving average representation for the time series. This is also known as the Wold decomposition theorem. The usefulness of the Wold Theorem is that it allows the dynamic evolution of a variable Yt to be approximated by a linear model. If the innovations varepsilon_{t} are independent, then the linear model is the only possible representation relating the observed value of Yt to its past evolution.

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