Explanation:
For a time series to be stationary, the expected value of the series must be not only finite but also constant across time. This also applies to the variance, which must be finite and constant across time. Time series that are not covariance stationary have linear regression estimates that have no economic meaning.
Section: Quantitative Analysis
Chapter: Stationary Time Series
Learning Objective: Describe the requirements for a series to be covariance stationary.
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Q.77 A time series is said to be stationary if:
A
Its statistical properties including the mean and variance do not change over time.
B
Its mean, variance, and covariances with lagged and leading values change over time.
C
Its mean remains constant but variance and covariances with lagged and leading values change over time.
D
Its mean and variance are variables but covariances with lagged and leading values do not change over time.