  This paper offers a general and comprehensive definition of the
day-of-the-week effect. Using symbolic dynamics, we develop a unique test based
on ordinal patterns in order to detect it. This test uncovers the fact that the
so-called "day-of-the-week" effect is partly an artifact of the hidden
correlation structure of the data. We present simulations based on artificial
time series as well. Whereas time series generated with long memory are prone
to exhibit daily seasonality, pure white noise signals exhibit no pattern
preference. Since ours is a non parametric test, it requires no assumptions
about the distribution of returns so that it could be a practical alternative
to conventional econometric tests. We made also an exhaustive application of
the here proposed technique to 83 stock indices around the world. Finally, the
paper highlights the relevance of symbolic analysis in economic time series
studies.
