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m a processThe m a process, referred to as MA(q), is the general finite-order procedure that happens to be an autoregressive representation of a covariance stationary series. It is a stationary process in the sense that the conditional expectation for the present is based solely on the function of the lagged and current unobserved https://oneonlineco.com/step-by-step-guide-to-choosing-a-virtual-data-room-in-2024/ shocks. This function is referred to as partial autocorrelation.

MA(q) MA(q) does not possess a unique MA polynomial like AR processes. In fact, there are many possible MA(q) polynomials for lag operators that could be stationary and possess the same asymptotic properties.

It is therefore conventional to impose invertibility constraints on the MA polynomial to guarantee that the process is causal. This guarantees that only past events (not future ones) will be able to predict current events.