Sell in May and Go Away: Does the Old Market Saying Hold Up?

Every year around late April, someone on a trading desk or a WhatsApp group dusts off the line: sell in May and go away. The idea is simple. Stocks supposedly do much better from November to April than from May to October, so you sell at the start of May, park the money somewhere safe, and come back around Halloween. It sounds like a tidy rule. The question we want to answer here is whether the evidence actually backs it, and whether it makes sense for someone trading or investing in Indian markets.

Short version: the pattern is real in a lot of historical data, but it is noisy, it fails badly in some years, and once you add costs and taxes, the edge gets thin. Let’s go through it properly.

What “sell in May and go away” actually means

As Wikipedia’s entry on the strategy describes it, the theory (also called the Halloween indicator) says the November-to-April stretch has significantly stronger stock market growth on average than the other six months. In practice, followers sell or cut their equity holdings around the start of May, hold the proceeds in cash or something like a money market fund, and buy stocks back in the autumn, typically around Halloween, which is October 31.

So it isn’t really about May alone. It’s a six-month switch: equities for the “winter” half, cash or bonds for the “summer” half.

Investopedia’s explainer on the adage credits the Stock Trader’s Almanac with popularising it. The Almanac’s version used the Dow Jones Industrial Average: hold stocks from November to April, switch to fixed income for the other six months, and, in the Almanac’s words, the approach “produced reliable returns with reduced risk since 1950.”

What the research found

This isn’t just folklore. It has been tested in academic work, and the results are more interesting than most market sayings.

Bouman and Jacobsen (2002)

The best-known study is Sven Bouman and Ben Jacobsen’s 2002 paper in the American Economic Review, titled “The Halloween Indicator, ‘Sell in May and Go Away’: Another Puzzle.” According to Wikipedia’s summary, they found the effect in 36 of the 37 countries they examined, and in the United Kingdom they traced it back to 1694. The effect was strongest in Europe.

That’s a big claim. A pattern that shows up across dozens of countries and over three centuries is hard to wave away as a fluke in one dataset.

The pushback: Maberly and Pierce

Not everyone bought it. Edwin Maberly and Raylene Pierce extended the US data to April 2003 and tested the strategy from April 1982 to April 2003. They left out two months when markets crashed, October 1987 and August 1998. With those excluded, they found the strategy did not work well in any of the three sub-periods they looked at: April 1982 to September 1987, November 1987 to July 1998, and September 1998 to April 2003.

Their point was that a couple of extreme months can do a lot of the heavy lifting. Remove the crashes and the “summer is bad” story weakens.

But the debate didn’t end there. Wikipedia also notes that other regression models using the same data, but controlling for extreme outliers rather than simply dropping them, found the effect to be significant.

The follow-up: Andrade, Chhaochharia and Fuerst (2012)

The most useful test is an out-of-sample one, data the original authors never saw. Sandro Andrade, Vidhi Chhaochharia and Michael Fuerst did exactly that in a 2012 paper with the memorable title “‘Sell in May and Go Away’ Just Won’t Go Away.” Looking at 1998 to 2012, they found November-to-April returns were larger than May-to-October returns, on average, in all 37 markets they studied. The average gap was about 10 percentage points, roughly the same size as in the original study.

A seasonal pattern that survives in fresh data is unusual. A seasonal pattern that survives costs, taxes and your own nerves is rarer still.

What the US index data shows

Investopedia’s analysis adds a few numbers worth knowing, all for the S&P 500:

• From 1990, the S&P 500 averaged a gain of about 3% in the May-to-October half, against about 6.3% in the November-to-April half.
• Going back to 1930, those averages change to about 3% for the summer months and 4.5% for the winter months.
• In the 1930s and 1940s the pattern ran the other way. Investopedia’s own analysis found summer returns were 11.23% and 4.51% higher than winter returns in those two decades respectively.

That last point matters. Investopedia says that if you used the S&P 500, which dates to 1927, instead of the Dow series the Almanac used, you’d find the summers almost always beat the winters in those early decades. The pattern depends on which index you pick and which years you start from. That’s a warning sign for any rule.

And the bad years for the strategy can be very bad. Investopedia points to 2020, when summer returns were about 24% while the winter half was negative at -7.7%. In 2009, summer returns were 21.9% against -9.4% for the winter. Anyone who sat in cash from May to October in those years missed the best part of the year.

Why might the pattern exist at all?

Nobody has a settled answer. The explanations people offer fall into a few buckets.

• Holidays and lower volumes. Summer vacations in Western markets mean thinner trading. Investopedia calls this the easy explanation but notes that the percentage change in prices doesn’t correlate with the drop in trading volume, so it doesn’t fully explain the gap.
• Institutional behaviour. Investopedia mentions that many US mutual funds end their fiscal year in October, and rebalancing or “window dressing” around that date can push certain sectors around.
• Statistics, not economics. Wikipedia lists small sample size and time variation in expected returns as alternative explanations. In plain words: maybe there’s no deep cause, and the gap is partly luck in the data.

There’s also the efficient-market argument. If the pattern were reliable and widely known, traders would front-run it, selling in April and buying back in October, until the edge disappeared. Investopedia makes exactly this point: once a pattern is recognised, people trying to exploit it tend to erase it.

A worked example: what the switch costs you

Let’s put rupees on it. The figures below are hypothetical, chosen only to show the mechanics. They are not historical Nifty or Sensex returns.

Say you have ₹10,00,000 in an index fund at the start of November. We’ll assume:

• Every switch out of or into equities costs 0.3% of the amount moved (brokerage, transaction charges, any exit load and the bid-ask spread lumped together, as an assumption).
• Cash parked in a liquid or money market fund earns 2.5% over the six summer months.
• We ignore tax for now and come back to it below.

Scenario A: the pattern works (winter +6%, summer +3%)

Buy and hold: ₹10,00,000 grows 6% to ₹10,60,000 by end-April, then 3% to ₹10,91,800 by end-October.

Sell in May: you also reach ₹10,60,000 by end-April. Selling costs 0.3%, or ₹3,180, leaving ₹10,56,820. Six months in a liquid fund at 2.5% takes it to ₹10,83,240. Buying back in at Halloween costs another 0.3%, about ₹3,250, leaving about ₹10,79,991.

Look at that. In the year the pattern “worked”, with the summer half weaker than the winter, the switcher still ended about ₹11,809 behind, because summer equity returns (3%) were still higher than cash (2.5%) and the costs ate the rest. The strategy only wins when the summer half is weaker than your cash return plus your costs, not merely weaker than the winter.

Scenario B: a 2020-style year (winter -5%, summer +15%)

Buy and hold: ₹10,00,000 falls 5% to ₹9,50,000, then rises 15% to ₹10,92,500.

Sell in May: you sit through the same fall to ₹9,50,000, pay ₹2,850 to exit (₹9,47,150 left), earn 2.5% in cash to reach about ₹9,70,829, and pay about ₹2,912 to get back in, ending at about ₹9,67,916.

That’s roughly ₹1,24,584 behind buy-and-hold in a single year. One bad year like this can wipe out many years of small seasonal gains.

The rule doesn’t need the summer to be worse than the winter. It needs the summer to be worse than cash plus your costs, every time you act on it.

The Indian angle: tax and costs change the maths

For an Indian investor, there’s another drag the US figures above don’t capture. Selling your equity holdings every May means realising gains every year, which can create a tax bill each year instead of letting gains compound untouched. How much it costs depends on how long you held the units and the capital gains rules in force at the time, so run the numbers with your tax adviser before you model this. The post-tax result can look quite different from the gross figures in our example.

We also haven’t seen a study on Indian indices in the sources we checked for this article, so we won’t claim the effect does or doesn’t hold for the Nifty 50 or Sensex. If you want to test it, the honest way is to pull long-run index data, split each year into the two halves, and compare each half’s return against what a liquid fund paid over the same months, after costs and tax.

Smarter ways to use the seasonal idea

If you believe there’s something to the pattern but don’t want to go fully to cash, there are milder versions.

Sector rotation instead of exit

Investopedia cites a CFRA report arguing that cyclical sectors such as consumer discretionary, industrials, materials and technology have tended to do better from November to April, while defensive sectors like consumer staples and healthcare have done better in the summer half. Since 1990, it says, the S&P 500’s consumer staples and healthcare sectors rose 4.1% on average from May to October, which beat the broader market’s summer average.

There’s a catch, though. Investopedia notes that a US ETF built around this rotation idea charges 0.60% a year against 0.05% for a typical S&P 500 index fund, and that the S&P 500 has outperformed the ETF consistently since 2022. Even a clever version of the rule has to beat its own costs.

Rebalance on a calendar, not on a hunch

A more practical use is to pick a fixed date for rebalancing your asset mix, and May is as good as any. You trim what has run up, top up what has lagged, and get back to your target. That gives you discipline without betting the whole portfolio on a six-month forecast. Our risk management in trading guide covers how to size positions so that any single call, seasonal or otherwise, can’t do too much damage.

Treat it as context, not a signal

Seasonal patterns are best used as background. If your own setup says buy in June, the calendar alone shouldn’t stop you. If you already had doubts, a weak seasonal stretch is one more reason to keep position size modest. We’ve looked at other calendar patterns too, including the January effect and the turn-of-the-month effect, and the lesson is the same each time: averages hide big year-to-year swings.

Time in the market vs timing it

Investopedia points to a Charles Schwab scenario that’s worth keeping in mind. Five hypothetical investors each got $2,000 a year for 20 years, from 2003 to 2022, to put into the S&P 500. The one with perfect timing, buying at each year’s low, ended with $138,044. The one who invested immediately at the start of every year ended with $127,506. Dollar-cost averaging gave $124,248, and the one with the worst timing, buying at each year’s high, still ended with $112,292.

Notice the spread. Perfect timing beat simply investing on day one by about $10,500 over two decades. Even the worst possible timing ended only about $15,200 behind the investor who simply put the money in on day one. Staying invested did most of the work.

So, should you sell in May and go away?

Here’s how we’d sum it up:

• The seasonal gap is real in a lot of historical data across many countries, and it even showed up in later, out-of-sample tests.
• It is an average. Individual years swing hard both ways, and a single strong summer can undo years of small gains from switching.
• To profit, summer equity returns must fall below your cash return plus costs, not just below winter returns.
• For Indian investors, switching every year means realising gains every year, so tax can eat into whatever edge is left.
• Milder uses, like a fixed rebalancing date or slightly smaller positions in the weaker half, keep the idea without betting everything on it.

Old market sayings stick around because they’re easy to remember. This one has more evidence behind it than most. But “more evidence than most” is still a long way from a rule you can follow blindly with your savings.

Disclaimer: This article is for education only and is not investment advice. Past patterns in market returns do not guarantee future results. The worked example uses hypothetical figures. Consult a SEBI-registered adviser before making investment decisions.