Claim check: The turn-of-the-month effect
“The best days for stocks are around the turn of the month.”
What the data says
Does not hold Not supported by the data: The turn-of-month window (the last trading day plus the first three of the next month) returned +0.07% a day on average against +0.05% for all other days in S&P 500 (n = 203 windows, 2010-01-04 to 2026-11-10; t = 0.5, likely noise). The direction points the claimed way, but the result cannot be told apart from chance.
No effect we can tell from chance, or the opposite effect.
Who says it
Documented by Ariel (1987) and Lakonishok and Smidt (1988); popular with Quantpedia and r/algotrading.
Origins are as commonly cited and were not independently verified.
How we tested it
The window is the last trading day of a month plus the first three trading days of the next. We compare the average daily return inside the window with all other days (Welch t-stat), in the full history and in both halves.
Results
| Market | Windows | Mean/day inside | Mean/day outside | Difference | Window return | Windows up | t-stat | Reading |
|---|---|---|---|---|---|---|---|---|
| S&P 500 | 203 | +0.07% | +0.05% | +0.020% | +0.3% | 59% | 0.5 (likely noise) | Right way, likely noise |
Average daily return inside the window and outside it
Stability across the two halves of history
A saying that only works in one half of the history is not much of a rule. Each row shows the effect in the full history, the first half and the second half; green means the claimed effect was present.
| Market | Full history | First half | Second half |
|---|---|---|---|
| S&P 500 | +0.02% | 0.00% (406) | +0.04% (404) |
Context and cross-checks
Shown for context; not part of the verdict.
Other markets (context, not part of the verdict)
| Market | Windows | Mean/day inside | Mean/day outside | Difference | Window return | Windows up | t-stat | Reading |
|---|---|---|---|---|---|---|---|---|
| Gold | 203 | +0.10% | +0.02% | +0.077% | +0.4% | 57% | 1.7 (likely noise) | Right way, likely noise |
| Silver | 203 | +0.07% | +0.04% | +0.028% | +0.3% | 52% | 0.3 (likely noise) | Right way, likely noise |
| Commodities | 203 | +0.01% | +0.02% | -0.006% | 0.0% | 50% | -0.1 (likely noise) | No effect |
| Agriculture | 203 | 0.00% | +0.01% | -0.011% | 0.0% | 49% | -0.3 (likely noise) | No effect |
| EUR/USD | 203 | 0.00% | -0.01% | +0.004% | 0.0% | 52% | 0.2 (likely noise) | Right way, likely noise |
| Bitcoin | 147 | +0.34% | +0.15% | +0.195% | +1.4% | 59% | 1.4 (likely noise) | Right way, likely noise |
| Ether | 109 | +0.48% | +0.10% | +0.376% | +1.9% | 58% | 1.7 (likely noise) | Right way, likely noise |
Average daily return inside the window and outside it
The site's own strategies
| Strategy | Market | Sharpe, 5 years | Benchmark, 5 years | Sharpe, full | Benchmark, full | CAGR, full | Benchmark, full | Max DD, full | Benchmark, full | Reading |
|---|---|---|---|---|---|---|---|---|---|---|
| CAL-01 Turn of Month | SPY | 0.47 | 0.72 | 0.53 | 0.85 | +4.5% | +13.8% | -17% | -34% | No effect |
Sharpe ratio minus benchmark, full history · Benchmark = the buy-and-hold shown on the strategy pages.
The honest caveat
Without flow or cash-timing data we cannot tell why it works or whether it survives costs.
Descriptive statistics from historical data, before costs. Not a forecast and not investment advice.
Questions
The best days for stocks are around the turn of the month.
Not supported by the data: The turn-of-month window (the last trading day plus the first three of the next month) returned +0.07% a day on average against +0.05% for all other days in S&P 500 (n = 203 windows, 2010-01-04 to 2026-11-10; t = 0.5, likely noise). The direction points the claimed way, but the result cannot be told apart from chance.
How was this claim tested?
The window is the last trading day of a month plus the first three trading days of the next. We compare the average daily return inside the window with all other days (Welch t-stat), in the full history and in both halves.
Related strategies on Quant Arena
Markets used
S&P 500 · Gold · Silver · Commodities · Agriculture · EUR/USD · Bitcoin · Ether