Turn of the month effect
What it shows
The turn-of-month effect: the mean change over the last and first days of the month (the turn window) versus all remaining days, with n, the 95% confidence interval, the share of up days and the quality badges.
How to read it
Compare the turn row with the remaining-days row: the effect is interesting only when the difference is clear, FDR-significant and stable. On traditional markets the turn-of-month effect was linked to fund flows; in crypto it is purely a historical observation.
Parameters
- n (sample size)
- How many historical days back the group. A small n (the “low sample” badge) = a result too noisy to take seriously.
- Whiskers / 95% CI
- Whiskers are the 95% confidence interval of the mean: a realistic range for the true value. A narrow interval = a more confident reading.
- Positive reading: The whole interval on one side of zero: a clear tendency across the data window.
- Negative reading: Whiskers crossing zero: the interval contains 0, so it may just as well be noise.
- FDR-significant
- The green badge: the result passed the multiple-comparison correction (Benjamini–Hochberg). Without it, with ~30 tests per profile, a few “significant” results are pure chance.
- Stable over time (walk-forward)
- The stability badge: the effect keeps the same direction in both the earlier and the later half of the window. “Unstable” = the tendency may have already faded.