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A Moving Average is a process where each value is a function of the noise in the past observations. These are the random error terms which follow a white noise process. The general form is MA(q), where xt depends on q past values.
Just like AR models, this also has a regression like structure, however, instead of the actual values, we are regressing each value on the noise/error in the previous observations.
