Sell in May and go away: does it still work?

By Raemin Kang · Nov 11, 2026 · Data through October 2026
A beach umbrella and lounger on an empty beach under a clear summer sky
Photo: Joe Desousa, CC0, via Wikimedia Commons

The short answer

  • No. In the US, selling in May grew 6.5% a year vs 8.7% for buy-and-hold (1999–2026).
  • Winter beat summer in 40 of 41 market series after 1998, but about half of that gap came from three summers.
  • Before 1970 the US gap was about 0.7 points a year, too small to tell apart from zero.
Annual growth, S&P 500 total return, 1999–2026
Source: S&P 500 total return, daily, 0.15% cost per trade. Tested Markets.

Sell in May and go away means holding stocks from November to April and sitting in cash from May to October. In the US, this earned less than simply holding the market. A $10,000 investment at the start of 1999 grew to about $58,000 with the rule, against about $102,000 for buy-and-hold.

Sven Bouman and Ben Jacobsen made the rule famous in 2002. Their paper found that the winter half beat the summer half in 36 of 37 countries, using data from 1970 to 1998. The saying is much older: London traders used to sell in May and come back on St Leger Day in September.

We asked whether the pattern survived after that paper, and whether anyone could have made money from it.

How we tested it

The rule

Winter means November to April. Summer means May to October. The rule sells at the close on the last trading day of April and buys back at the close on the last trading day of October. The calendar is known in advance, so the rule never uses information it could not have had. That is about two trades a year.

Every switch costs 0.15%. Money out of stocks earns the Treasury bill rate, 3.35% a year on average. Leveraged versions pay the bill rate plus 0.4% to borrow, plus a 0.95% yearly fee. We ignore taxes.

The data

For the US we used the S&P 500 with dividends reinvested, daily, from 1928 to October 2026. Before 1993 dividends are estimated from Robert Shiller’s yield data; from 1993 we use the SPY fund. Cash returns come from Ibbotson’s Treasury bill series until 1933, the Federal Reserve’s 3-month bill rate until 1959, and the 13-week bill yield after that.

For earlier years we also checked Shiller’s monthly series, which starts in 1871. It uses monthly average prices, so it is blurry around month ends.

Outside the US we used 41 data series covering 23 countries: 20 stock indexes (four of them US indexes) and 21 country ETFs. The indexes are price indexes in local currency, so they exclude dividends. European companies pay most dividends in spring, which can make the winter–summer gap look bigger than it is. The ETFs include dividends and are priced in US dollars. They start in 1996.

Three periods

We split the US history into three parts and read each one separately.

  • 1928–1969, before the paper’s data. A real pattern should show up here too.
  • 1970–1998, the years the 2002 paper used.
  • 1999–2026, after the paper. This is a clean test, because nobody could have fitted the rule to these years.

How we checked for luck

A few huge crashes can make a seasonal rule look brilliant. So we ran four checks on the main results:

  • Drop the best years. We removed the 1, 3 and 5 years that helped the rule most, then measured again.
  • Count years, not markets. Markets fall together, so 41 series in the same year are not 41 separate results. We averaged across markets each year and treated each year as one result.
  • Shift the calendar. We moved the six-month “winter” window to each of the 12 possible starting months. A real effect should rank near the top among those 12 windows.
  • Same exposure, no timing. The rule holds stocks only half the year. We compared it with a fixed mix that holds the same average amount of stock all year, with no timing.

We also resampled whole years at random to see how wide the range of luck was. When a result fell inside that range, we say so in the text.

The pattern survived abroad, but it rests on a few years

From 1999, winter beat summer in 40 of the 41 series. Because markets crash together, as almost every country did in autumn 2008, 41 series are not 41 independent results. The real sample is 28 years.

To see whether a few lucky years did the work, we dropped the best ones. About half the gap came from three summers with sharp falls: 2002, 2008 and 2011. Without them the evidence went from borderline to indistinguishable from chance.

US S&P 500: winter half minus summer half, each year
Points. Above zero means winter did better. Green: 2002, 2008 and 2011, the three summer falls named above.
−30
−15
0
+15
+30
1999
+21.5
2004
+24
2009
+22.4
2014
2019
2024
Source: S&P 500 total return, daily, returns above Treasury bills. Average +3.4 points. Tested Markets.

In the US it barely existed before 1970

From 1929 to 1969 the US winter–summer gap was about 0.7 points a year. That is too small to tell apart from normal year-to-year noise. In the paper’s period, 1970 to 1998, it was 5.0 points. Shiller’s data from 1872 to 1969 also shows almost no gap.

Winter minus summer, US stocks, points per year
Source: S&P 500 total return, daily, returns above Treasury bills. Full summers only. Tested Markets.

A pattern that is missing before the years in which it was discovered is a warning sign. From 1999 the US gap came back at about 3.4 points a year (counting full summers only, through 2025), but without the five best years it turned slightly negative.

Cash in summer cost more than it saved

Strategy, US 1999–2026 Growth / yr Worst drop*
Buy and hold 8.7% −55.2%
Winter only, cash in summer 6.5% −35.8%
Winter 2x, cash in summer 8.4% −64.0%
Winter 2x, summer 1x 10.6% −74.9%
Skip September only 10.0% −51.8%

*Largest fall from a peak to a later low.

Growth vs worst drop, US 1999–2026
Growth per year ↑ better
6%
8%
10%
12%
−80%
−60%
−40%
−20%
Buy and hold
Winter only
Winter 2x
2x winter, 1x summer
Skip September
Worst drop → smaller is better
Source: the table above. Tested Markets.

Selling for the summer cut the worst drop from −55% to −36%. But it grew about 2.2 points a year slower on average, and over 28 years that became the gap between $58,000 and $102,000.

What $10,000 became, January 1999 to October 2026
Buy and holdWinter only, cash in summer
$0
$25k
$50k
$75k
$100k
$102k
$58k
1998
2008
2018
2026
Show the numbers
Buy and holdWinter only, cash in summer
1998$10,000$10,000
1999$12,039$11,881
2000$10,866$11,131
2001$9,588$11,830
2002$7,519$11,275
2003$9,638$12,544
2004$10,669$13,560
2005$11,184$13,768
2006$12,956$15,417
2007$13,623$15,702
2008$8,610$14,079
2009$10,879$14,827
2010$12,517$16,895
2011$12,754$18,472
2012$14,794$20,927
2013$19,573$24,826
2014$22,209$25,981
2015$22,483$26,030
2016$25,180$27,967
2017$30,646$31,271
2018$29,246$29,117
2019$38,377$36,954
2020$45,413$38,481
2021$58,459$44,595
2022$47,834$38,935
2023$60,355$49,665
2024$75,375$55,637
2025$88,731$53,894
2026$101,607$57,783
Source: S&P 500 total return, daily, 0.15% cost per trade. Tested Markets. 1998 = starting value. Year-end values.
How far each was below its last peak, month by month
Buy and holdWinter only, cash in summer
−60%
−40%
−20%
0%
Jan 2000
Jan 2010
Jan 2020
Show the numbers
Buy and holdWinter only, cash in summer
Jan 1999−5.1%−5.1%
Feb 1999−4.9%−4.9%
Mar 1999−4.4%−4.4%
Apr 1999−5%−5%
May 1999−6.4%−3%
Jun 1999−5.5%−2.7%
Jul 1999−6.4%−2.3%
Aug 1999−9.3%−1.9%
Sep 1999−10.3%−1.5%
Oct 1999−11.7%−1.1%
Nov 1999−4.8%−2.7%
Dec 1999−2.2%−2.2%
Jan 2000−7.6%−7.6%
Feb 2000−9.3%−9.3%
Mar 2000−7.1%−7.1%
Apr 2000−11.4%−11.4%
May 2000−10.2%−5.6%
Jun 2000−5.9%−5.2%
Jul 2000−7.3%−4.7%
Aug 2000−6.1%−4.2%
Sep 2000−6.8%−3.7%
Oct 2000−12.9%−3.2%
Nov 2000−13.5%−10.2%
Dec 2000−17.1%−14%
Jan 2001−15.4%−12.2%
Feb 2001−18.6%−15.5%
Mar 2001−26.9%−24.1%
Apr 2001−27.3%−24.6%
May 2001−17.6%−13.6%
Jun 2001−20%−13.3%
Jul 2001−22.2%−13.1%
Aug 2001−25.2%−12.8%
Sep 2001−35.6%−12.5%
Oct 2001−30.9%−12.4%
Nov 2001−28.1%−10.1%
Dec 2001−25.8%−7.2%
Jan 2002−26.7%−8.3%
Feb 2002−28.2%−10.2%
Mar 2002−24.4%−5.5%
Apr 2002−28.8%−10.9%
May 2002−29.9%−10.2%
Jun 2002−34.7%−10.1%
Jul 2002−46.5%−10%
Aug 2002−44%−9.8%
Sep 2002−45%−9.7%
Oct 2002−47.5%−9.6%
Nov 2002−40.7%−9.9%
Dec 2002−41%−10.3%
Jan 2003−43%−13.4%
Feb 2003−44.6%−15.8%
Mar 2003−45.6%−17.4%
Apr 2003−41.7%−11.4%
May 2003−37.7%−5.4%
Jun 2003−34%−5.4%
Jul 2003−33.1%−5.3%
Aug 2003−34.4%−5.2%
Sep 2003−31.7%−5.1%
Oct 2003−30.3%−5.1%
Nov 2003−29.1%−6.5%
Dec 2003−27.1%−3.8%
Jan 2004−23.7%−2.2%
Feb 2004−22.5%−2.6%
Mar 2004−24.6%−5.6%
Apr 2004−23.6%−4.3%
May 2004−25%−4.5%
Jun 2004−22.8%−4.4%
Jul 2004−24.8%−4.3%
Aug 2004−26.1%−4.2%
Sep 2004−23.1%−4.1%
Oct 2004−23.7%−3.9%
Nov 2004−21.2%−3.7%
Dec 2004−17.8%−1%
Jan 2005−18.5%−4%
Feb 2005−17%−2.3%
Mar 2005−18.2%−4.7%
Apr 2005−20.1%−7%
May 2005−18.7%−5.5%
Jun 2005−16.1%−5.3%
Jul 2005−15.8%−5%
Aug 2005−14.9%−4.8%
Sep 2005−14.4%−4.5%
Oct 2005−16.9%−4.2%
Nov 2005−14.7%−3.8%
Dec 2005−11.4%−2.1%
Jan 2006−10.3%−2.6%
Feb 2006−10.7%−3%
Mar 2006−9.3%−1.6%
Apr 2006−8.1%−1.8%
May 2006−10.5%−0.1%
Jun 2006−12.4%0%
Jul 2006−11.5%0%
Aug 2006−8.9%0%
Sep 2006−6.8%0%
Oct 2006−4.1%0%
Nov 2006−1.8%−1.8%
Dec 2006−1.1%−1.1%
Jan 2007−1.4%−1.4%
Feb 2007−4.5%−4.5%
Mar 2007−6%−6%
Apr 2007−2.3%−2.3%
May 2007−1%−1%
Jun 2007−3.4%−0.6%
Jul 2007−6.4%−0.2%
Aug 2007−9%0%
Sep 2007−6%0%
Oct 2007−4.4%0%
Nov 2007−9.9%−9%
Dec 2007−7.3%−6.3%
Jan 2008−16%−15.2%
Feb 2008−14.5%−13.6%
Mar 2008−17.8%−16.9%
Apr 2008−14.2%−13.3%
May 2008−11.1%−9.9%
Jun 2008−17.3%−9.8%
Jul 2008−21.5%−9.7%
Aug 2008−18.9%−9.6%
Sep 2008−27.3%−9.4%
Oct 2008−45.2%−9.3%
Nov 2008−50.8%−29.4%
Dec 2008−46.4%−23.2%
Jan 2009−47%−24%
Feb 2009−51.4%−30.3%
Mar 2009−55.2%−35.8%
Apr 2009−46.3%−23%
May 2009−41.8%−17.1%
Jun 2009−40.5%−17.1%
Jul 2009−41.4%−17.1%
Aug 2009−34.5%−17.1%
Sep 2009−33.5%−17.1%
Oct 2009−31.4%−17.1%
Nov 2009−30.2%−16.6%
Dec 2009−26.6%−12.3%
Jan 2010−27.7%−13.6%
Feb 2010−28.7%−14.9%
Mar 2010−24.7%−10%
Apr 2010−20.4%−4.9%
May 2010−27.6%−4.2%
Jun 2010−29.9%−4.2%
Jul 2010−30.6%−4.2%
Aug 2010−28.5%−4.2%
Sep 2010−26.3%−4.2%
Oct 2010−22.3%−4.2%
Nov 2010−19.3%−4.6%
Dec 2010−17.4%−2.3%
Jan 2011−12.8%−1.7%
Feb 2011−10.4%−2.7%
Mar 2011−13.4%−6.2%
Apr 2011−10%−2.5%
May 2011−9%−0.1%
Jun 2011−12.4%−0.1%
Jul 2011−10.4%−0.1%
Aug 2011−22.2%−0.1%
Sep 2011−21.4%−0.1%
Oct 2011−23.5%−0.1%
Nov 2011−19%−9%
Dec 2011−15.7%−5.3%
Jan 2012−10.7%−0.9%
Feb 2012−7.2%−0.7%
Mar 2012−5.6%−2.2%
Apr 2012−4.3%−4.2%
May 2012−8.7%−1.5%
Jun 2012−9.8%−1.5%
Jul 2012−5.5%−1.5%
Aug 2012−3.3%−1.5%
Sep 2012−2.2%−1.5%
Oct 2012−3.7%−1.5%
Nov 2012−7.3%−5.6%
Dec 2012−3.7%−3%
Jan 2013−0.6%−0.6%
Feb 2013−2.8%−2.8%
Mar 2013−1.1%−1.1%
Apr 2013−3.2%−3.2%
May 2013−2.2%−0.1%
Jun 2013−5.6%−0.1%
Jul 2013−3.1%−0.1%
Aug 2013−4.5%−0.1%
Sep 2013−3.8%−0.1%
Oct 2013−3.9%−0.1%
Nov 2013−1.3%−1.3%
Dec 2013−1.8%−1.8%
Jan 2014−4%−4%
Feb 2014−5.7%−5.7%
Mar 2014−1.9%−1.9%
Apr 2014−3.9%−3.9%
May 2014−1.3%−0.5%
Jun 2014−1.1%−0.4%
Jul 2014−2.8%−0.4%
Aug 2014−3.8%−0.4%
Sep 2014−2.3%−0.4%
Oct 2014−7.3%−0.4%
Nov 2014−0.3%−0.9%
Dec 2014−4.9%−4.9%
Jan 2015−4.6%−4.6%
Feb 2015−3.3%−3.3%
Mar 2015−3.5%−3.5%
Apr 2015−2.5%−2.5%
May 2015−1.7%−1.7%
Jun 2015−3.3%−1.7%
Jul 2015−3.7%−1.7%
Aug 2015−11.9%−1.7%
Sep 2015−11.1%−1.6%
Oct 2015−9.2%−1.6%
Nov 2015−4.2%−4.3%
Dec 2015−4.9%−5%
Jan 2016−11.7%−11.8%
Feb 2016−13%−13.1%
Mar 2016−5.8%−5.9%
Apr 2016−2.5%−2.6%
May 2016−2.8%−1.9%
Jun 2016−5.5%−1.9%
Jul 2016−1.4%−1.9%
Aug 2016−0.8%−1.9%
Sep 2016−2.7%−1.9%
Oct 2016−2.6%−1.8%
Nov 2016−4.3%−3.8%
Dec 2016−1.3%−1.3%
Jan 2017−0.9%−0.9%
Feb 2017−0.8%−0.8%
Mar 2017−2.1%−2.1%
Apr 2017−2.6%−2.6%
May 2017−1.9%−0.4%
Jun 2017−1.4%−0.3%
Jul 2017−1.7%−0.3%
Aug 2017−2.1%−0.2%
Sep 2017−0.7%−0.1%
Oct 2017−0.7%0%
Nov 2017−1%−1%
Dec 2017−0.7%−0.7%
Jan 2018−1.7%−1.7%
Feb 2018−10.1%−10.1%
Mar 2018−9.6%−9.6%
Apr 2018−9.8%−9.8%
May 2018−8%−7.5%
Jun 2018−5.2%−7.3%
Jul 2018−4.7%−7.2%
Aug 2018−1.3%−7%
Sep 2018−1.3%−6.8%
Oct 2018−9.7%−6.7%
Nov 2018−9.9%−9.2%
Dec 2018−19.3%−18.7%
Jan 2019−16%−15.3%
Feb 2019−7.1%−6.3%
Mar 2019−5.5%−4.8%
Apr 2019−1.2%−0.5%
May 2019−6.4%−0.1%
Jun 2019−6.6%0%
Jul 2019−1.5%0%
Aug 2019−6%0%
Sep 2019−3.7%0%
Oct 2019−4.2%0%
Nov 2019−0.6%−0.6%
Dec 2019−1.9%−1.9%
Jan 2020−3.1%−3.1%
Feb 2020−12.4%−12.4%
Mar 2020−33.7%−33.7%
Apr 2020−26.8%−26.8%
May 2020−16.3%−13.8%
Jun 2020−10.6%−13.8%
Jul 2020−7.3%−13.8%
Aug 2020−1.8%−13.7%
Sep 2020−9.4%−13.7%
Oct 2020−8.3%−13.7%
Nov 2020−7.3%−12.9%
Dec 2020−1.5%−3.8%
Jan 2021−3.7%−3.7%
Feb 2021−3.1%−3.1%
Mar 2021−4.1%−4.1%
Apr 2021−1.2%−1.2%
May 2021−4%−0.8%
Jun 2021−2.1%−0.8%
Jul 2021−2.8%−0.8%
Aug 2021−1.7%−0.8%
Sep 2021−5%−0.8%
Oct 2021−5.1%−0.8%
Nov 2021−3%−3%
Dec 2021−4.1%−4.1%
Jan 2022−9.7%−9.7%
Feb 2022−11.7%−11.7%
Mar 2022−12.9%−12.9%
Apr 2022−13.5%−13.5%
May 2022−18.2%−13.6%
Jun 2022−23%−13.5%
Jul 2022−20.3%−13.4%
Aug 2022−16.7%−13.3%
Sep 2022−24.4%−13.1%
Oct 2022−24.5%−12.9%
Nov 2022−21.4%−16.2%
Dec 2022−19.9%−14.5%
Jan 2023−19.3%−13.9%
Feb 2023−15.7%−10.1%
Mar 2023−18%−12.5%
Apr 2023−13.7%−7.9%
May 2023−13.5%−5.4%
Jun 2023−9.9%−4.9%
Jul 2023−6%−4.5%
Aug 2023−6.5%−4.1%
Sep 2023−8.4%−3.7%
Oct 2023−11.7%−3.3%
Nov 2023−9.1%−1.9%
Dec 2023−2.2%−1.4%
Jan 2024−2%−2%
Feb 2024−1.4%−1.4%
Mar 2024−1.1%−1.1%
Apr 2024−5.4%−5.4%
May 2024−4.4%−4.2%
Jun 2024−0.7%−3.7%
Jul 2024−4.7%−3.4%
Aug 2024−8.4%−2.9%
Sep 2024−4.3%−2.5%
Oct 2024−2.7%−2.1%
Nov 2024−2.5%−2.2%
Dec 2024−3.6%−3.6%
Jan 2025−4.2%−4.2%
Feb 2025−4.5%−4.5%
Mar 2025−10%−10%
Apr 2025−18.8%−18.8%
May 2025−8.6%−9.4%
Jun 2025−3%−9.1%
Jul 2025−0.8%−8.7%
Aug 2025−2.4%−8.4%
Sep 2025−1.3%−8.1%
Oct 2025−3%−7.8%
Nov 2025−5.1%−11.6%
Dec 2025−2.6%−9.1%
Jan 2026−2.5%−8%
Feb 2026−2.6%−8%
Mar 2026−8.9%−13.9%
Apr 2026−5.5%−10.8%
May 2026−1.9%−2.3%
Jun 2026−4.5%−2%
Jul 2026−3.7%−1.7%
Aug 2026−2%−1.4%
Sep 2026−3.1%−1%
Oct 2026−1.5%−0.7%
Source: S&P 500 total return, daily, lowest point of each month. Tested Markets.

Summer was weaker than winter, but it was not bad. The US summer half still earned about 1.6% more than cash per year. Selling in May meant giving that up every year to dodge crashes that came only now and then.

The season does carry some information. After 1970 the rule beat a fixed mix of about half stocks and half cash, which has the same average exposure. Before 1970 it lost even that comparison. It never beat simply holding the market.

None of the wins in this table are large enough to rule out luck.

Leverage in winter: more growth, much deeper crashes

We tried borrowing to hold twice the stock position in winter. With a normal position in summer, it grew 10.6% a year, more than buy-and-hold. But its worst drop was −74.9%.

The problem is timing. The last leg of the 2008–09 bear market, from November 2008 to March 2009, fell in the winter half. So did the Covid crash of February and March 2020.

We also tried four real leveraged funds held only in winter. Only the 3x S&P 500 fund, UPRO, beat its plain index, at 18.3% a year against 15.2% from mid-2009. Its worst drop was −76.8%, no smaller than holding the 3x fund all year. The 2x S&P 500 fund and both Nasdaq funds lost to their plain index.

What about September?

From 1929 to 2026, September was the weakest month for the S&P 500 in each of the three periods we checked. In Shiller’s data from 1872 to 1927, though, it was one of the better months: 10th worst of 12. Since 1999 September has also been weaker than other months in all 40 index and ETF series we had, but those cover the same years as the US data, so they are not separate evidence.

Average monthly return above cash, S&P 500, 1929–2026
−2%
−1%
0%
+1%
+2%
J
F
M
A
M
J
J
A
−1.31%
S
O
N
D
Source: S&P 500 total return, daily, returns above Treasury bills. Tested Markets.

Skipping only September grew 10.0% a year against 8.7% from 1999 to 2026. Moving the switch by a single day cut that to 9.5%, so much of the edge depends on the first trading day of October. It also edged out buy-and-hold in 1929–1969 and 1970–1998. But the 1999 result was within the range of luck, and removing the three worst Septembers (2002, 2008 and 2022) cut the advantage to almost nothing.

Annual growth, S&P 500 total return, 1999–2026
Source: S&P 500 total return, daily, 0.15% cost per trade. Tested Markets.

There is also a selection problem: we picked September because we already knew it was the worst month. When we let the data pick the worst month each year using only past years, the rule lost to buy-and-hold in 1950–1969 and in 1970–1998.

Other markets and crypto

An equal-weight basket of 21 country ETFs that sat in cash every summer did beat holding the basket from 1999: 9.1% a year against 8.2%, with a worst drop of −38% against −61%. But 2008 did most of the work. From 2009 the rule grew 7.9% a year against 9.6%.

Annual growth, equal-weight basket of 21 country ETFs
Source: 21 country ETFs with dividends, in US dollars. Tested Markets.

For Bitcoin (2011–2026), holding only from November to April grew about 51% a year, against about 81% for holding all year. The winter gap came almost entirely from two early years, 2011 and 2013. For Ethereum (2017–2026), the gap vanished in the second half of the data. Since 2022 the worst month for both has been June, not September.

What if you are waiting with spare cash?

Some people get money in summer and plan to wait until November to invest it. Compared three years later, waiting left them behind in about 6 of 10 cases, by about 1% at the median.

Money that arrived from mid-August to September and waited until the end of September did no harm. It also gained almost nothing: +0.2% at the median.

Does it help inside an uptrend?

We split S&P 500 days by season and by whether the index was above its 200-day average, the average closing price of the last 200 trading days. Winter days in an uptrend had the best return for the risk taken in every period.

A rule built on that, holding more in winter uptrends and going to cash in downtrends, added about one point a year from the season. But the trend filter cost more than that after 2009, and the rule fell −43% in 2022–23, when buy-and-hold fell −24.5%.

What this means for you

  • Don’t move to cash in May. In the US it cost about 2 points a year.
  • If money arrives in summer, invest it now. Waiting for November usually left you behind.
  • If money arrives in late August or September, waiting until the end of the month did no harm, but it gained almost nothing.

This test ignores taxes. Why a seasonal pattern might exist is still debated. Bouman and Jacobsen pointed to summer holidays. Other researchers have suggested that investors take less risk when the days get shorter.

Bottom line

Winter has beaten summer in many countries, but much of that comes from a handful of summer crashes, and in the US the pattern barely existed before 1970. Selling in May cut the worst losses, but it earned less than holding the market, because the summer half still paid you to stay invested.

Common questions

Does Sell in May and go away work?

Not as a way to beat the market in the US. From January 1999 to October 2026, holding the S&P 500 only from November to April and sitting in cash from May to October grew 6.5% a year, against 8.7% for buy-and-hold. A $10,000 investment became about $58,000 instead of about $102,000. The rule did cut the worst drop from −55% to −36%.

Is the Halloween effect real?

The pattern is real in many countries. From 1999, winter beat summer in 40 of 41 stock index and country ETF series. But about half of that gap came from three summers with sharp falls: 2002, 2008 and 2011. In the US the gap was only about 0.7 points a year from 1929 to 1969, too small to tell apart from zero.

Is September the worst month for stocks?

For the S&P 500, September was the weakest month in each of three periods from 1929 to 2026, but not in Shiller's data from 1872 to 1927. Skipping only September grew 10.0% a year against 8.7% from 1999 to 2026. Moving the switch by one day cut that to 9.5%, and removing the three worst Septembers (2002, 2008 and 2022) cut the advantage to almost nothing.

Should I wait until November to invest new money?

Usually not. For money that arrived in summer, waiting until November left investors behind in about 6 of 10 cases three years later, by about 1% at the median. Money that arrived from mid-August to September and waited until the end of September did no harm, but gained almost nothing: +0.2% at the median.

How this was tested
Markets
41
Period
1928–2026
Costs
0.15% per trade, one way
Benchmark
Buy and hold the same index
Details
Full method