A stochastic process 
is strictly stationary if, for every positive integer
,
every collection of times 
, and every shift 
, the random vectors
 |
have the same joint distribution. Thus all finite-dimensional distributions are invariant under a shift of time.
Strict stationarity need not imply weak stationarity unless the required moments exist, and weak stationarity need not imply strict stationarity.
