To be covariance stationary, a time series has to satisfy the following three conditions:

1. Constant and finite expected value: The expected value of the time series should be constant over time.
2. Constant and finite variance: The time series volatility around its mean (i.e., the distribution of the individual observations around the mean) should not change over time.
3. Constant and finite covariance between values at any given lag: The covariance of the time series with leading or lagged values of itself is constant.

All three conditions (I, II, and III) must be satisfied for a time series to be covariance stationary. Therefore, option B is correct.