DeployQuantFirst-to-Last Day of Month
Buy the first session of each month and sell the last, as a calendar-seasonality test.
The First-to-Last Day of Month template has no indicator. It buys at the open of the first session of a month, sells at the open of the last session, and waits for the next month. The test asks one question: how much of a fund's return was earned inside the month, and how much came from the days that cross a month boundary.
Over 2021-01-04 to 2026-10-02 the median result across 59 funds was 5.5% a year with a median maximum drawdown of 36.6%. It beat buy-and-hold of the same fund on 14 funds and had a shallower drawdown on 23. Exposure was 95.2% at the median, so the strategy behaves like a slightly smaller version of buy-and-hold. The cash days are few, and what they cost or saved shows up in the table as small gaps between the strategy and the fund.
The page is a research template, not a trading system. It is useful as a control. Any template that stays out of the market for long stretches can be compared with this one to see how much of its edge comes from timing and how much from simply holding less. The RSI(2) snapback template, which is invested only part of the time, is the opposite case, and its median of 4.7% is a little below this page's median of 5.5%.
The rules
- WHEN the first session of the month opens · IF not invested · THEN buy with 98% of the sleeve (once per month)
- WHEN the last session of the month opens · IF invested · THEN sell the whole position
This template uses no indicators. It tests the turn-of-the-month effect by holding from each month's first open to its last. Whatever it earns or loses comes from calendar seasonality alone, so it is a useful comparison against buy-and-hold on the same page.
Good for: measuring how much of an asset's return accrues inside the month versus across month boundaries.
Watch out: this is a research template. It holds ~95% of all sessions, so results usually track buy-and-hold minus the boundary days.
How the rules hold a fund
The entry fires once a month, on the first session, when the strategy is flat. It buys with 98% of the sleeve. The exit fires on the last session of the month and sells everything. Between those two opens the position is untouched, with no stop and no target.
The strategy is therefore out of the fund for the final session of every month and through the overnight gap into the next month's first open. Every other session is held. That is why exposure is 95.2% on almost every fund in the table. The exceptions come from funds with shorter histories: CLSE is at 94.8%, CTA at 93.7% and KMLM at 94.3%. UST shows 95.1%.
The round trip count follows the calendar. Nearly every fund shows 69 trades, one per month for the window. CLSE shows 55, CTA 54 and KMLM 68, because those three funds start trading after the window opens and have fewer months of price history inside the test. SOXS and UVXY also show 69 trades and 95.2% exposure, the same as every other fund.
Because trade count and exposure barely vary, the differences between funds are almost entirely about the fund. The table below is closer to a ranking of how each fund behaved from the first to the last session of the month than to a comparison of strategy designs. The monthly cycle on QQQ page shows what that looks like for a single fund, with the month-by-month results.
Build it from blocks (or type it in English), backtest it on 5.7 years of minute data in seconds, tweak any parameter, then paper trade it on live data. No card, no broker needed to start.
Results on every ETF
| ETF | CAGR | buy & hold | max DD | Sharpe | trades | win rate |
|---|---|---|---|---|---|---|
| TECL | 36.0% | 38.2% | −78.0% | 0.80 | 69 | 52% (+1 open) |
| SOXL | 32.9% | 33.3% | −90.2% | 0.81 | 69 | 57% (+1 open) |
| SOXX | 29.2% | 31.1% | −44.5% | 0.90 | 69 | 62% (+1 open) |
| ROM | 27.0% | 30.2% | −69.4% | 0.74 | 69 | 57% (+1 open) |
| TQQQ | 21.5% | 25.4% | −82.5% | 0.64 | 69 | 59% (+1 open) |
| XLK | 20.9% | 22.1% | −32.0% | 0.93 | 69 | 64% (+1 open) |
| QLD | 20.6% | 23.6% | −65.0% | 0.67 | 69 | 61% (+1 open) |
| SPUU | 19.5% | 22.5% | −44.1% | 0.75 | 69 | 65% (+1 open) |
| CLSE | 18.9% | 19.5% | −17.4% | 1.39 | 55 | 64% (+1 open) |
| SSO | 18.8% | 21.9% | −43.9% | 0.73 | 69 | 65% (+1 open) |
| FAS | 17.0% | 18.3% | −66.7% | 0.58 | 69 | 57% (+1 open) |
| IOO | 15.8% | 16.7% | −21.1% | 1.02 | 69 | 68% (+1 open) |
| QQQM | 14.9% | 16.7% | −36.6% | 0.78 | 69 | 61% (+1 open) |
| QQQ | 14.7% | 16.7% | −36.1% | 0.77 | 69 | 61% (+1 open) |
| VOOG | 13.9% | 15.7% | −33.9% | 0.77 | 69 | 64% (+1 open) |
| CTA | 13.3% | 8.9% | −21.2% | 0.83 | 54 | 65% (+1 open) |
| SPY | 12.8% | 14.6% | −22.4% | 0.88 | 69 | 70% (+1 open) |
| VOO | 12.8% | 14.4% | −22.4% | 0.88 | 69 | 70% (+1 open) |
| VV | 12.4% | 14.3% | −23.7% | 0.84 | 69 | 68% (+1 open) |
| VTV | 12.1% | 13.4% | −15.4% | 0.97 | 69 | 65% (+1 open) |
| TBF | 11.9% | 12.2% | −17.6% | 0.86 | 69 | 59% (+1 open) |
| IAU | 11.8% | 13.7% | −26.1% | 0.74 | 69 | 54% (+1 open) |
| XLF | 11.6% | 12.6% | −23.5% | 0.73 | 69 | 58% (+1 open) |
| VOOV | 10.9% | 12.6% | −17.8% | 0.87 | 69 | 65% (+1 open) |
| KMLM | 8.1% | 7.1% | −24.0% | 0.66 | 68 | 56% (+1 open) |
| QQQE | 8.0% | 9.8% | −29.1% | 0.51 | 69 | 61% (+1 open) |
| ALTY | 7.2% | 7.6% | −18.5% | 0.77 | 69 | 65% (+1 open) |
| IWM | 6.5% | 7.5% | −36.9% | 0.42 | 69 | 57% (+1 open) |
| VOX | 6.0% | 9.1% | −46.2% | 0.41 | 69 | 61% (+1 open) |
| XLP | 5.5% | 5.8% | −13.4% | 0.50 | 69 | 54% (+1 open) |
| USDU | 5.4% | 5.2% | −7.6% | 0.87 | 69 | 51% (+1 open) |
| RINF | 5.2% | 6.6% | −14.9% | 0.49 | 69 | 57% (+1 open) |
| XLY | 3.7% | 6.3% | −43.8% | 0.28 | 69 | 52% (+1 open) |
| QAI | 3.3% | 3.9% | −16.1% | 0.52 | 69 | 52% (+1 open) |
| EEM | 3.1% | 6.6% | −44.4% | 0.27 | 69 | 54% (+1 open) |
| SGOV | 3.0% | 3.2% | −0.1% | 13.00 | 69 | 90% (+1 open) |
| IGIB | −0.3% | 0.2% | −20.9% | -0.02 | 69 | 58% (+1 open) |
| FXE | −0.3% | −0.9% | −22.4% | -0.00 | 69 | 52% (+1 open) |
| UDN | −0.7% | −1.1% | −22.6% | -0.06 | 69 | 51% (+1 open) |
| IEI | −0.8% | −0.4% | −15.0% | -0.18 | 69 | 49% (+1 open) |
| AGG | −0.9% | −0.8% | −18.9% | -0.14 | 69 | 54% (+1 open) |
| BND | −0.9% | −0.8% | −18.9% | -0.15 | 69 | 54% (+1 open) |
| IEF | −2.7% | −2.3% | −24.7% | -0.36 | 69 | 46% (+1 open) |
| TLT | −8.1% | −8.2% | −46.2% | -0.52 | 69 | 43% (+1 open) |
| SPDN | −8.6% | −9.7% | −41.8% | -0.52 | 69 | 35% (+1 open) |
| UST | −8.9% | −8.5% | −47.8% | -0.60 | 69 | 46% (+1 open) |
| SH | −8.9% | −10.0% | −42.9% | -0.54 | 69 | 35% (+1 open) |
| EEV | −10.0% | −16.1% | −75.0% | -0.09 | 69 | 42% (+1 open) |
| VXZ | −12.5% | −15.1% | −62.0% | -0.37 | 69 | 45% (+1 open) |
| PSQ | −12.7% | −13.8% | −60.3% | -0.54 | 69 | 36% (+1 open) |
| VIXM | −14.8% | −16.1% | −66.0% | -0.43 | 69 | 43% (+1 open) |
| SDS | −20.5% | −21.6% | −74.3% | -0.60 | 69 | 32% (+1 open) |
| QID | −28.8% | −29.5% | −88.0% | -0.59 | 69 | 33% (+1 open) |
| TMF | −32.2% | −31.2% | −89.7% | -0.71 | 69 | 39% (+1 open) |
| REW | −37.2% | −36.1% | −93.4% | -0.70 | 69 | 32% (+1 open) |
| SQQQ | −44.6% | −42.3% | −97.0% | -0.60 | 69 | 32% (+1 open) |
| TECS | −55.6% | −46.7% | −99.1% | -0.78 | 69 | 32% (+1 open) |
| UVXY | −68.7% | −48.7% | −99.9% | -0.69 | 69 | 33% (+1 open) |
| SOXS | −77.5% | −48.3% | −100.0% | -0.81 | 69 | 29% (+1 open) |
How funds ranked and where the strategy lagged
TECL leads at 36.0% a year against 38.2% for holding it, with a 78.0% maximum drawdown. SOXL made 32.9% against 33.3%, with a 90.2% drawdown. SOXX made 29.2% against 31.1% at a 44.5% drawdown, and ROM made 27.0% against 30.2%. All of the top results are in funds that rose strongly in this window, and in each the strategy finished slightly behind holding.
That is the usual shape. The strategy holds 95.2% of the sessions and skips the rest, so on a fund that rises on most days it trails by a small margin. TQQQ is the clearest example among the large names, with 21.5% for the strategy against 25.4% for holding and an 82.5% drawdown. QQQ made 14.7% against 16.7%. SPY made 12.8% against 14.6%. VOO made 12.8% against 14.4%. None of the broad index funds beat holding.
The cases where the strategy came out ahead are few and small. CTA made 13.3% against 8.9% for holding. KMLM made 8.1% against 7.1%. CLSE made 18.9% against 19.5%, so it fell just short. USDU made 5.4% against 5.2%. These are alternative and currency funds with low volatility. A gain of a point or two on a fund that moves little is the size of the edge that month-boundary timing produced here.
The weak side of the table is inverse and volatility funds. SQQQ lost 44.6% a year against 42.3% for holding. TECS lost 55.6% against 46.7%. UVXY lost 68.7% against 48.7%, and SOXS lost 77.5% against 48.3%. The drawdowns on those four were 97.0%, 99.1%, 99.9% and 100.0%. In each case the strategy lost more than holding, so the one session a month it skipped was a net gain for the fund rather than a loss avoided. The cause of the losses is the decay of the funds themselves, and these are also the funds where the strategy trailed holding by the widest margin.
SGOV is a special case. It made 3.0% against 3.2% for holding, with a drawdown of 0.06% and a 90% win rate. The fund pays interest daily and barely moves, so almost every month is positive. The USDU page covers another low-volatility fund that held up in this test.
Limits of the test
The window is 2021-01-04 to 2026-10-02, one stretch of market with a bear year in 2022. The headline run has no fees or slippage. Since each fund trades about once a month, costs would be small for most funds, and the cost runs on each fund page add 5 and 10 basis points to check that.
Orders fill on minute bars at the open. Results use adjusted prices, and no margin is used. The strategy never shorts. The rule set is deliberately plain, so it does not claim any edge. It reports how much of each fund's return arrived between the first and last open of each month in this period, and the table shows that for most funds the number is slightly below buy-and-hold.
For a stronger comparison, the weekly 7% target template had the highest median of the templates at 6.6%, above this page's 5.5%.
Results by fund type
| Fund type | ETFs | Median CAGR | Median buy & hold | Median max DD | Beat holding |
|---|---|---|---|---|---|
| Broad index ETFs | 12 | 12.8% | 14.4% | −29.1% | 0 of 12 |
| Sector ETFs | 6 | 11.6% | 12.6% | −43.8% | 0 of 6 |
| Leveraged ETFs | 10 | 20.6% | 23.6% | −69.4% | 0 of 10 |
| Inverse ETFs | 11 | −20.5% | −21.6% | −75.0% | 6 of 11 |
| Bond ETFs | 7 | −0.9% | −0.8% | −18.9% | 1 of 7 |
| Commodity ETFs | 1 | 11.8% | 13.7% | −26.1% | 0 of 1 |
| Currency ETFs | 3 | −0.3% | −0.9% | −22.4% | 3 of 3 |
| Volatility products | 3 | −14.8% | −16.1% | −66.0% | 2 of 3 |
| Alternative-strategy ETFs | 6 | 8.1% | 7.6% | −18.5% | 2 of 6 |
What the fund types show
The category medians confirm the pattern.
Leveraged funds had a median of 20.6% against 23.6% for holding, with a median drawdown of 69.4%. The strategy beat holding on none of the 10. Sector funds had a median of 11.6% against 12.6% with none of 6 ahead. Broad index funds had 12.8% against 14.4% with none of 12 ahead, and a median drawdown of 29.1%. Commodity, with one fund, had 11.9% against 13.7%.
Alternative-strategy funds had 8.1% against 7.6%, ahead on 2 of 6, with a median drawdown of 18.5%. Currency funds had negative 0.3% against negative 0.9% and finished ahead on all 3. Bond funds had negative 0.9% against negative 0.8%, ahead on 1 of 7.
Inverse funds had negative 20.5% against negative 21.6%, ahead on 6 of 11, with a median drawdown of 75.0%. Volatility products had negative 14.8% against negative 16.1%, ahead on 2 of 3, with a drawdown of 66.0%. The medians sit close to holding, but the individual cases spread widely: some inverse funds beat holding by a few points while SQQQ, TECS, UVXY and SOXS fell behind.
The counts of funds ahead are 0, 0, 0 for the three equity groups that matter most, and that is the finding. A calendar rule that sits out two or so sessions a month does not add return on a rising equity fund. The cases that look better are funds where holding lost money and the skipped days happened to be down days.
The drawdown figures show that the strategy offers almost no protection. A median drawdown of 36.6% across the universe is the same order as holding. The RSI mean reversion template, with a lower median return of 3.0%, spends more time in cash and cuts drawdowns more, which is a different trade-off.
Year by year, median across all ETFs
| Year | monthly cycle | Buy & hold | ETFs with a gain |
|---|---|---|---|
| 2021 | 5.4% | 4.1% | 31 of 59 |
| 2022 | −13.8% | −12.7% | 20 of 59 |
| 2023 | 6.7% | 8.9% | 40 of 59 |
| 2024 | 11.4% | 9.7% | 38 of 59 |
| 2025 | 11.4% | 11.1% | 42 of 59 |
| 2026 | 2.3% | 3.7% | 32 of 59 |
The calendar years
The yearly medians follow the market with a small offset.
In 2021 the median strategy return was 5.4% against 4.1% for holding, and 31 funds finished positive. This was an up year for the strategy relative to holding. In 2022 the median was negative 13.8% against negative 12.7%, with 20 funds positive. The strategy lost slightly more than holding, because it was invested through the declines and the sessions it skipped did not help.
In 2023 the median was 6.7% against 8.9%, with 40 funds positive. In 2024 the median was 11.4% against 9.7%, with 38 positive. In 2025 it was 11.4% against 11.1%, with 42 positive. The 2026 figure of 2.3% against 3.7% covers a partial year to 2026-10-02, with 32 positive.
The strategy was ahead of holding at the median in 2021, 2024 and 2025, and behind in 2022, 2023 and 2026. That split of three and three is what a rule with no real edge looks like. The differences are small in every year, within a few points, and they change sign.
The funds-positive count follows the market more than the rule. 2022 had the fewest at 20 and 2025 had the most at 42. Because exposure is 95.2%, the strategy has little ability to avoid a bad year. It would be a mistake to read the 2024 result as evidence for a turn-of-the-month effect, since the same median is within a point of buy-and-hold in 2025 and below it in 2023.
The effect has appeared in long historical studies, according to the template description, and it depends on the market regime. This window of 5.74 years is short, and the test does not separate the boundary days from the rest, so it cannot confirm or reject the effect. It only measures what holding from the first open to the last open did on these 59 funds. The momentum breakout template, with a median of 0%, is another example of a rule set that did not improve on holding.
Changing the parameters
| Version | Median CAGR | Median max DD | Median round trips |
|---|---|---|---|
| Published rules | 5.5% | −36.6% | 69 |
| Only after a positive month | 1.2% | −29.8% | 38 |
| Only above the 200-day SMA | 2.9% | −24.7% | 40 |
| With a 5% profit target | 3.8% | −29.5% | 69 |
What the three variants add
Each fund page runs three variants. They test whether a filter on the monthly entry improves on the plain version.
Buying only after a positive month gave a median of 1.2% a year with a 29.8% median drawdown and 38 round trips. This is the weakest of the three. The filter skipped months that followed a decline, and in a window where dips were followed by recoveries that cost return. The trade count fell, so exposure fell with it.
Buying only when the fund is above its 200-day average gave 2.9% with a 24.7% median drawdown and 40 round trips. The filter cut the drawdown more than the previous variant, from 36.6% in the base rule to 24.7%, but it also cut the return from 5.5% to 2.9%. That trade-off is the same one the 200-day regime filter template makes, and that template had a median of 1.8% on its own.
Adding a 5% profit target gave 3.8% with a 29.5% median drawdown and 69 round trips. The target did not change the number of trades, since the monthly entry is already once per month. It did exit early on winning months, and the fund then sat in cash until the next first session. It lowered the return from the base figure of 5.5%, so on the median fund the early exits left more behind than they protected.
All three variants have a lower median than the base rule. No filter improved the return. Two reduced the drawdown. A reader who wants lower risk on this template gets it only by holding less, which is a trade that cuts return in this window.
The variants are median figures, so they hide large differences by fund. For leveraged and inverse funds, a trend filter changes the result far more than it does for a bond fund. The fund pages, such as QQQ and SOXL, show the variants for one fund at a time.
Frequently asked questions
What is the monthly cycle strategy?
Buy the first session of each month and sell the last, as a calendar-seasonality test. This template uses no indicators. It tests the turn-of-the-month effect by holding from each month's first open to its last. Whatever it earns or loses comes from calendar seasonality alone, so it is a useful comparison against buy-and-hold on the same page.
Does monthly cycle beat buy-and-hold?
Across 59 ETFs backtested 2021-01-04 to 2026-10-02, it beat same-ETF buy-and-hold on 14 of 59 (24%). Median CAGR was 5.5% with a median max drawdown of 36.6%. Per-ETF results vary widely; the table lists every one.
Is the turn-of-the-month effect real?
It has appeared in long historical studies, but it depends on the market regime and is small. These pages show the recent five and a half years per ETF.
Does the turn-of-the-month effect show up in this backtest?
Not in a way that beats holding. The strategy had a median of 5.5% a year and beat buy-and-hold on 14 of 59 funds. None of the 12 broad index funds finished ahead, so the test does not confirm a calendar edge.
How many trades does the monthly cycle make?
One round trip per month, which is 69 on most funds over 2021-01-04 to 2026-10-02. CLSE, CTA and KMLM have fewer because their price history in the window is shorter.
How much of the time is the monthly cycle invested?
The median exposure is 95.2%. The strategy is in cash for the last session of each month and the overnight gap to the next open. That is why its results track buy-and-hold closely.
Which funds did the monthly cycle beat buy-and-hold on?
CTA made 13.3% against 8.9%, KMLM made 8.1% against 7.1%, and USDU made 5.4% against 5.2%. All three are low-volatility alternative or currency funds. The gains are small.
Does a 200-day filter help the monthly cycle?
It cut the median drawdown to 24.7% from 36.6%, and it cut the median return to 2.9% from 5.5%. The strategy held fewer months, with 40 round trips at the median.
How did the monthly cycle do in 2022?
The median return was negative 13.8% against negative 12.7% for holding, and 20 of 59 funds finished positive. The strategy was invested for most sessions, so it had little protection.
Compare with other strategies
Backtests are hypothetical, computed by DeployQuant's engine on minute-resolution consolidated US market data (2021-01-04 to 2026-10-02, $10,000 starting capital, no margin, no fees or slippage in the headline run; buy-and-hold puts 98% of the account in at the first open, as the templates do) and do not guarantee future results. Nothing on this page is investment advice. Live trading involves risk of loss.