Does the NASDAQ-100 have good days, good months and good hours? We processed 14.5 years of M1 tick data (4,179,799 candles between February 2012 and July 2026) and aggregated them by day of week, month of year and trading session. Spoiler: the NASDAQ has the strongest "Monday rally" of the six assets in this series — the effect is large and it clears significance by a wide margin.
The dataset in numbers
4.2M candles
M1 candles (UTC)
14.5 years
2012-02 → 2026-07-29
Best day
Monday
+0.169% · 59.4% win · p=0.0001 ⭐⭐⭐
Best month
November
+3.42% · 85.7% win · p=0.005 ⭐⭐
Best session
NY 12-17
+0.032% drift · 54.3% win · p=0.016 ⭐
1. Seasonality by day of the week
For every trading day from Monday to Friday we computed the close-to-close return in % and aggregated the 3,733 days in the dataset. The test is a one-sample t-test against zero. ⭐ marks days with p < 0.05.
📅 Table 1 · Daily return by day of week (2012–2026)n=3,733 trading days
| Day | n | Mean % | Median % | Std % | Win rate | t-stat | p-value |
|---|---|---|---|---|---|---|---|
| Monday | 744 | +0.169% | +0.152% | 1.1977% | 59.4% | 3.86 | 0.0001 ⭐⭐⭐ |
| Tuesday | 750 | +0.078% | +0.092% | 1.1474% | 54.9% | 1.87 | 0.063 |
| Wednesday | 751 | +0.115% | +0.121% | 1.3579% | 56.1% | 2.32 | 0.021 ⭐ |
| Thursday | 751 | +0.016% | +0.054% | 1.3423% | 53.7% | 0.33 | 0.743 |
| Friday | 736 | +0.009% | +0.053% | 1.2934% | 52.0% | 0.19 | 0.847 |
Headline finding: Monday is strongly bullish and highly significant (+0.169%, 59.4% win rate, p=0.0001 ⭐⭐⭐). It is the strongest Monday effect of the six assets tested — about 60% larger than the Dow Jones (+0.107%, p=0.002). Wednesday clears significance too (+0.115%, p=0.021). The NASDAQ's weekly shape is clear: Monday and Wednesday bullish, Thursday and Friday flat.
2. Seasonality by month of the year
📆 Table 2 · Average monthly return by calendar monthn=174 months · 2012-2026
| Month | n | Mean % | Median % | Std % | Win rate | t-stat | p-value |
|---|---|---|---|---|---|---|---|
| January | 14 | +1.517% | +2.075% | 5.688% | 64.3% | 1.00 | 0.336 |
| February | 14 | +0.552% | -0.057% | 3.868% | 46.7% | 0.53 | 0.602 |
| March | 15 | +0.518% | +1.977% | 5.485% | 60.0% | 0.37 | 0.720 |
| April | 15 | +1.904% | +1.914% | 7.050% | 66.7% | 1.05 | 0.313 |
| May | 15 | +2.916% | +3.999% | 5.572% | 73.3% | 2.03 | 0.062 |
| June | 15 | +1.963% | +3.352% | 5.096% | 60.0% | 1.49 | 0.158 |
| July | 15 | +3.070% | +2.965% | 4.787% | 86.7% | 2.48 | 0.026 ⭐ |
| August | 14 | +1.282% | +1.128% | 4.722% | 64.3% | 1.02 | 0.328 |
| September | 14 | -0.916% | -0.098% | 4.179% | 42.9% | -0.82 | 0.427 |
| October | 14 | +1.594% | +3.179% | 5.501% | 57.1% | 1.08 | 0.298 |
| November | 14 | +3.423% | +2.666% | 3.850% | 85.7% | 3.33 | 0.005 ⭐⭐ |
| December | 14 | -0.110% | +0.532% | 4.295% | 57.1% | -0.10 | 0.925 |
Findings:
- November is the standout month: +3.42% mean, 85.7% win rate (12 of 14 Novembers closed green), p=0.005 ⭐⭐. The year-end rally in tech is robust.
- July is significant too: +3.07%, 86.7% win rate (13 of 15 Julys green), p=0.026 ⭐. The NASDAQ has the strongest summer rally of the six assets tested.
- September is the worst month: -0.92%, 42.9% win rate (8 of 14 Septembers red). The September effect is visible, though p=0.427 keeps it short of significance.
- May is borderline: +2.92%, 73.3% win rate, p=0.062 — close to the 5% threshold without clearing it.
3. Seasonality by trading session (UTC)
🌍 Table 3 · Drift, range and gap by session (UTC)n=16,394 session observations
| Session | n | Mean drift % | Win rate | p-value | Mean range % | |Gap| % |
|---|---|---|---|---|---|---|
| Asian (00–07 UTC) | 3,100 | +0.0224% | 55.3% | 0.002 ⭐⭐ | 0.490% | 0.049% |
| London (07–12 UTC) | 3,366 | +0.0071% | 54.2% | 0.321 | 0.582% | 0.278% |
| NY (12–17 UTC) | 3,716 | +0.0322% | 54.3% | 0.016 ⭐ | 1.151% | 0.402% |
| NY late (17–22 UTC) | 3,651 | +0.0113% | 54.4% | 0.312 | 0.843% | 0.717% |
| Weekend gap (22–24 UTC) | 2,561 | +0.0137% | 52.6% | 0.005 ⭐⭐ | 0.293% | 0.815% |
Findings for the NASDAQ-100:
- Asian session bullish and highly significant: +0.022%, p=0.002 ⭐⭐. Twice the Dow's Asian drift (+0.011%).
- NY session bullish and significant: +0.032%, p=0.016 ⭐. The most volatile session by far (1.15% average range) and it has upward direction.
- Weekend gap bullish and significant: +0.014%, p=0.005 ⭐⭐. Unlike the Dow, the NASDAQ closes the week with positive momentum.
- London and NY late are neutral: no reliable direction.
4. Day × session heatmap
📅 Table 4 · Day × session heatmap (mean drift %)Mon-Fri × 4 sessions
| Day | Asian (00–07) | London (07–12) | NY (12–17) | NY late (17–22) |
|---|---|---|---|---|
| Monday | +0.033% | +0.026% | +0.080% | +0.039% |
| Tuesday | +0.030% | +0.004% | +0.018% | +0.014% |
| Wednesday | +0.031% | +0.030% | +0.038% | +0.026% |
| Thursday | +0.002% | -0.012% | +0.033% | -0.028% |
| Friday | +0.017% | -0.013% | -0.008% | +0.006% |
Heatmap findings:
- Monday is bullish everywhere: all four sessions positive (+0.033%, +0.026%, +0.080%, +0.039%). The Monday × NY cell (+0.080%) is the strongest in the whole NASDAQ table.
- Wednesday is bullish everywhere too: four positive sessions, making it the most consistent day of the week.
- Thursday splits: NY is positive (+0.033%) while NY late is the weakest cell on the board (-0.028%) — a rally-then-fade pattern.
- Friday is the weakest day: only Asian and NY late are positive; London and NY are negative.
5. Most volatile hours (UTC)
⏰ Table 5 · Top 6 most volatile hours (UTC, Mon-Fri)14.5 years of M1 bars
| Hour UTC | Mean range % | Std % | Session |
|---|---|---|---|
| 14:00 | 0.891% | 0.540 | NY mid |
| 15:00 | 0.853% | 0.521 | NY mid |
| 13:00 | 0.801% | 0.506 | NY open |
| 19:00 | 0.747% | 0.478 | NY late |
| 18:00 | 0.706% | 0.460 | NY late |
| 20:00 | 0.683% | 0.438 | NY late |
The NASDAQ is meaningfully more volatile than the Dow: NY mid (14:00-15:00 UTC) ranges 0.85-0.89% against the Dow's 0.62-0.65%. The hot window is 13:00-15:00 UTC (NY open plus two hours). Like the Dow, the NASDAQ is entirely NY-dependent — no London peak.
---6. Three practical NASDAQ-100 setups
Setup 1 · Long bias on Monday during NY
- When: Monday 12-17 UTC (NY session).
- Why: +0.080% drift, the strongest cell in the table, backed by the significant Monday aggregate (+0.169%, p=0.0001).
- How to use it: discretionary traders can open longs at the Monday NY open (13:00 UTC) and take profit at the daily close.
Setup 2 · Long bias in November and July
- When: the whole of November and the whole of July.
- Why: November +3.42%, 85.7% win rate, p=0.005 ⭐⭐. July +3.07%, 86.7% win rate, p=0.026 ⭐.
- How to use it: a strong seasonal filter for trend-following systems on tech.
Setup 3 · Long bias on Wednesdays, all sessions
- When: Wednesday 00-22 UTC.
- Why: all four Wednesday sessions are positive (+0.031%, +0.030%, +0.038%, +0.026%), and the daily aggregate clears significance (+0.115%, p=0.021).
- How to use it: the cleanest of the three — longs on Wednesday with a tight stop.
What this data does not tell you
- The sample includes the AI era: 2023-2024 was an exceptional NASDAQ rally (10,000 to 18,000). That inflates every positive statistic here.
- The bullish Monday is mostly post-COVID: pre-2020 Monday averaged +0.021% (not significant). From 2020 onward it averages +0.342%.
- September stays weak: p=0.427 keeps it out of significance, but a 42.9% win rate (8 of 14 Septembers red) is worth noting.
- CFD data: USATECHIDXUSD is a Dukascopy CFD, not the E-mini NASDAQ-100 futures contract (NQ). Behaviour can differ.
- Rate sensitivity: the NASDAQ-100 reacts hard to Fed policy. The 2022 hiking cycle produced the bear market and the 2024 cuts produced the rally, so seasonal patterns here overlap heavily with the macro cycle.
Methodology
- Source: M1 tick data (Dukascopy) for USATECHIDXUSD between February 2012 and July 2026.
- Total: 4,179,799 M1 UTC candles, aggregated into 3,733 trading days and 174 months.
- Daily return: (close_22UTC[t] − close_22UTC[t−1]) / close_22UTC[t−1] × 100.
- Monthly return: (close_lastDay − close_lastDayPrevMonth) / close_lastDayPrevMonth × 100.
- Session drift: (close_last_bar − open_first_bar) / open × 100.
- Statistical test: one-sample t-test against zero. ⭐ = p < 0.05.
- Software: Python 3.14, pandas 3.x, pyarrow, scipy, matplotlib.
For position sizes matched to NASDAQ-100 volatility, use the position size calculator. For more on US indices, read strategies for US futures.
The full seasonality series
This study is part of a series applying the same methodology to six assets. The NASDAQ's bullish Monday is the strongest of the set; in gold and the FX majors that pattern does not exist at all.
- Dow Jones (USA30) — the same weekly pattern, about 60% weaker.
- XAUUSD (gold) — 23 years of data, best day Friday and best month January.
- XAGUSD (silver) — gold's more volatile sibling.
- EURUSD — the world's most traded pair, 23 years.
- GBPUSD — the London session and its intraday bias.