Stocks tend to perform unusually well around the end of one month and the beginning of the next. At first glance, the explanation appears almost absurdly simple: the calendar changes.

That basic pattern has been documented for decades and across many countries. In “Infrequent rebalancing, risk deferral, and equity returns at the turn of the month”, Nuri Volkan Kayaçetin examines 30 developed and emerging stock markets over roughly 30 years. The result is striking: a narrow period around month-end accounts for essentially all of the positive average equity return in most of the markets he studies. That is an extraordinary concentration of returns in a very small part of the calendar.

But describing the effect is not the same as explaining it. Saying that stocks rise at the turn of the month because it is the turn of the month is just restating the observation. A more interesting question is why returns should cluster there in the first place.

The traditional explanation is institutional cash flow. Salaries, pension contributions, dividends and other payments often arrive around month-end, and some of that money finds its way into equities. There is an obvious intuitive appeal to this story: money arrives, funds invest it, and the resulting demand pushes prices higher. But Kayacetin’s paper asks whether the effect may reflect something deeper than simple calendar-driven inflows.

The alternative is that the turn of the month is partly a risk event.

Most investors do not rebalance continuously. A pension fund does not restore its target allocation every time the market moves 20 basis points, and neither does a mutual fund, an insurance company or a private investor. Portfolio weights drift during the month, and month-end is a natural point at which those accumulated deviations are corrected.

Suppose equities fall sharply during the month. A portfolio that began at 60% equities might now be at 57% or 58%. If the investor wants to restore the original allocation, the rebalance requires buying stocks. If equities have risen strongly, the reverse may be true. Month-end therefore becomes a natural point when investors respond to risks and portfolio imbalances that have accumulated over the previous several weeks.

That is a very different interpretation of the anomaly. The calendar itself may not be causing anything. It may simply identify the date when deferred portfolio decisions finally hit the market.

If that story is right, then market conditions leading into month-end should matter. The naive version of the trade is simply to buy because it is month-end. But a risk-based explanation implies that the size of the effect should depend on what happened beforehand. A weak month, elevated volatility or unusually large portfolio drift should matter more than the date by itself.

This is broadly where Kayacetin’s results become interesting. The turn-of-the-month premium appears related to market conditions such as preceding returns and volatility, which is more consistent with a state-dependent risk story than with a completely arbitrary seasonal anomaly. The effect is still tied to the calendar, but the calendar may be acting as a marker for when a particular kind of risk transfer takes place.

This sounds like a subtle distinction, but it changes how a trader should think about the signal. If the calendar itself contains the information, then December 31 should be December 31 regardless of whether stocks rose 8%, fell 8% or did nothing during the month. If the effect instead reflects accumulated risk and rebalancing pressure, then the path into month-end should matter enormously.

There is a broader lesson here about anomalies. We tend to name effects after the easiest variable to observe: the Monday effect, January effect, turn-of-the-month effect, post-earnings-announcement drift, 52-week-high effect. But the name of an anomaly is not necessarily its cause. The calendar may tell us when something happens without telling us why.

That distinction matters especially for calendar effects because they are “too easy”. If stocks reliably earn higher returns around month-end for no reason whatsoever, then markets are leaving an embarrassingly simple pattern on the table. No complicated model or machine learning system is required. You just need a calendar.

A persistent effect makes more sense if traders are not simply collecting free money. Perhaps they are being paid for supplying liquidity, absorbing temporary imbalances or bearing risk at a predictable time. In that case, the return premium can survive even after everyone knows about it, because knowing a trade exists is not the same as being willing to take the other side when conditions are unpleasant.

That is familiar in other areas of markets. The variance risk premium is well known, but selling volatility can still earn a premium because someone has to sell insurance during crashes. Carry is well known, yet carry strategies occasionally get hit very hard. Momentum is one of the best-known anomalies in finance, but its reversals can be vicious. An effect can be predictable without being free.

The turn-of-the-month effect may belong in the same category. The important question is not simply whether it exists. The more useful question is what kind of return it represents. Is it an inefficiency, predictable institutional demand, compensation for bearing risk, or some combination of all three?

For investors, that naturally suggests a better way to use the signal. Calendar effects are often treated as binary variables: either today is inside the turn-of-the-month window or it is not. But if the mechanism is state dependent, that throws away potentially useful information. A better model might condition the calendar effect on what happened beforehand.

Was the preceding month weak? Has realized or implied volatility risen? Have portfolios likely drifted significantly away from their target allocations? Are there reasons to expect unusually large institutional flows? Those variables may help identify the month-ends when the effect should be strongest.

That way of thinking generalizes beyond turn-of-the-month. Options-expiration effects may depend on dealer positioning. FOMC-day returns may depend on how much uncertainty has accumulated before the announcement. Index-rebalancing effects should depend on the size and predictability of the required flows. Even holiday effects may vary depending on market conditions going into the holiday.

The broader lesson is that simple anomalies can have complicated causes. Finding the pattern is only the first step. The danger comes when we confuse the label we gave the pattern with an explanation for why it exists. Stocks do not know what date it is, but investors do. If investors postpone decisions, rebalance portfolios and manage accumulated risk on predictable schedules, then the calendar can become a map of when those decisions hit the market.

The turn of the month may therefore be real without being mysterious. The calendar tells us when. Risk may tell us why.

Disclaimer

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