What it means
Calendar anomalies are patterns tied to a time of year, and the September effect is one of the best known. Investopedia says that from 1928 through 2023 the S&P 500 averaged a decline in September, though September was not the worst month every year.
The average can mislead. A few very bad Septembers can pull the mean below zero while most Septembers are flat or positive, and Investopedia notes that the median September return has turned positive, which means a typical year was not a loss.
Period choice matters a lot too. Investopedia says that betting against September over the last 100 years would have made a profit, but betting against it only since 2014 would have lost money.
A pattern that flips with the start date is weak evidence. A fair test compares September with the average of the other months over the same years, then asks whether the gap is bigger than normal random variation.
With one observation a year, a century of data gives only about 100 points, which is a small sample for such a claim. Several explanations are offered: investors return from summer holidays and may sell to lock in gains or tax losses, some individuals sell to pay school costs, and funds may rebalance at quarter end.
Expecting weakness can itself make traders cautious. These are theories, and Investopedia says much of the case is anecdotal.
The effect violates the efficient-market idea because a known pattern should be traded away, and economists and professionals have largely discounted it as a reliable indicator. If it ever was real, publicity and arbitrage may have reduced it.
It is related to, but separate from, the Halloween effect, which Bouman and Jacobsen studied in the American Economic Review in 2002 by comparing winter and summer half-years across many countries, whereas the September effect is about a single month and has much thinner support. An investor who tries to avoid September pays trading costs and may miss a rebound.
Taxes can apply to gains from selling. Results differ across markets and years, and past patterns do not predict future returns.
In practice
Real-world examples.
Example
A fictional market has five Septembers with returns of -8%, -5%, +2%, +3% and +4%. The mean is -0.8% (sum of -4 divided by 5), which looks like a weak month. The median is +2%, so the typical September was positive.
Example
An investor holds $100,000 and sits out one September in cash. If the market falls 4%, avoiding it saves $4,000. If it rises 5%, the investor misses $5,000 of gain.
Example
A fictional trader sells and buys back $100,000 around September, paying 0.2% each way, a total of 0.4% or $400. The expected saving from an average 0.8% fall is $800. If September is flat, the trader is down $400 from costs alone.
Formula
Calculation
Mean return = Sum of returns / Number of years. With -4 / 5 = -0.8%.
Median return = Middle value of the sorted returns. With -8, -5, 2, 3, 4 the median is 2%.
Net gain from avoiding a month = Avoided loss - Trading costs. With $800 - $400 = $400 only if the average repeats.
Significance check with assumed figures. Suppose 100 Septembers have a mean return of -0.5% and a standard deviation of 5.0%. The standard error is 5.0% / the square root of 100 = 5.0% / 10 = 0.5%, so the mean sits 0.5% / 0.5% = 1.0 standard error below zero. A gap that small is well within ordinary random variation, which is why a negative average alone is weak evidence.Case study
Seen in the real world.
This case study is fictional and illustrative. Isla, 45, in Edinburgh, reads that September is a weak month and wonders whether to move her 60,000 pension to cash for four weeks. She looks up the history and sees that results depend on the years chosen. She checks the cost of selling and buying back, and the possible tax. She also remembers the risk of missing a sharp rise.
She decides not to time the month. She keeps her regular monthly contribution going instead. September ends slightly up. She notes that she would have paid costs and missed the gain, so she leaves her plan unchanged.
Watch out
Common mistakes.
- Treating a long-run average as a rule that holds each year.
- Ignoring trading costs and taxes when moving out of the market for one month.
- Forgetting that the result flips with the start date of the data.
Questions
People also ask.
What is the September effect?
It is the belief that stocks tend to do poorly in September, based on weak average returns in long US data.
Is the September effect reliable?
No. Economists largely discount it, and the result changes with the period studied.
How is it different from sell in May?
Sell in May covers a six-month period, while the September effect is about a single month.
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