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The key difference between a moving average representation and an autoregressive process is that:
A
An autoregressive process is never covariance stationary
B
An autoregressive process shows evidence of autocorrelation cutoff
C
Unlike the autoregressive process, a moving average representation shows evidence of gradual decay
D
A moving average representation shows evidence of autocorrelation cutoff
Explanation:
The main differentiator between a moving average (MA) representation and an autoregressive (AR) process is that while the AR process shows a gradual decay in autocorrelations, the MA process shows abrupt autocorrelation cutoff. This is a fundamental characteristic in time series analysis:
Option A is incorrect because AR processes can be covariance stationary under certain conditions. Option B is incorrect because AR processes show gradual decay, not cutoff. Option C is incorrect because it reverses the characteristics - MA shows cutoff, not gradual decay.