Which of the following best describes a stationary time series?

A stationary time series is characterized by having both a constant mean and constant variance over time. This means that the statistical properties of the series remain stable, and it does not exhibit any long-term trends or seasonal effects. In essence, when you analyze a stationary time series, you should see fluctuations around a consistent average level without increasing or decreasing patterns that could skew your interpretation.

The other options do not align with the definition of a stationary time series. A fluctuating mean would imply that the series is not stable over time, and trends can indicate changes in the mean or variance, which go against the concept of stationarity. A series that is entirely random may have a constant mean, but if it lacks structure entirely, it may not be considered stationary in the typical sense. Lastly, a series with only upward or downward trends cannot be stationary because the presence of trends indicates that the mean is changing over time, which contradicts the fundamental requirement for stationarity.