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The Turn-of-the-Month Effect: When the Calendar Quietly Pays Traders

July 11, 2026 · 8 min read

The Turn-of-the-Month Effect: When the Calendar Quietly Pays Traders

Imagine being told that, on average, the entire long-run gain of the stock market happened in just four trading days each month — and the other fifteen or so days added up to roughly nothing. It sounds impossible. But that is exactly what careful, peer-reviewed research found. It is called the turn-of-the-month effect, and it is one of the cleanest, most testable calendar edges in finance.

Who found it, and where (the who / what / when)

The effect was first documented by Robert Ariel in "A Monthly Effect in Stock Returns," published in the Journal of Financial Economics in 1987. Two decades later, John McConnell and Wei Xu of Purdue University re-examined it in "Equity Returns at the Turn of the Month," published in the Financial Analysts Journal in 2008 — and their finding was even more striking.

What they found (the data points)

McConnell and Xu looked at U.S. stock returns from 1926 to 2005 — roughly 80 years. They found that, on average, all of the market's positive return occurred during a four-day window: the last trading day of the month plus the first three trading days of the next month. Across the other trading days of the month, the average return was essentially zero. They then checked 34 other countries and found the same turn-of-the-month pattern in the large majority of them. That is a rare thing in finance: a simple, calendar-based edge that repeats across 80 years and dozens of countries.

The "equation" is really just a window

There is no scary formula here — just a way to count days. We label trading days relative to the month's end:

  • TD−1 = the last trading day of the month (the close where you get in).
  • TD+1, TD+2, TD+3 = the first, second, and third trading days of the new month.

The whole strategy is: be in the market from the close of TD−1 through the close of TD+3, and be flat the rest of the month. "Trading days" means market-open days, so weekends and holidays are skipped when you count — a detail TapeScript handles for you automatically.

Why it should work (the why)

Money moves on a schedule. Paychecks, 401(k) and pension contributions, and automatic fund investments tend to land around month-end. Big funds also rebalance at month-end, buying to hit their target weights. All of that is predictable buying pressure arriving at roughly the same time every month, which nudges prices up during the turn window. It is not magic — it is the plumbing of how cash enters markets.

Does it still hold — honestly?

Be honest with yourself on three points. First, this is mainly an equity-index effect — it is strongest on stock index futures (like the E-mini S&P 500 or Nasdaq), and it is weaker and must be tested on forex, where the closest cousin is month-end currency-rebalancing flow around the "London fix." Second, well-known edges can decay as more traders pile in, so recent decades matter as much as the 1930s. Third — and this is the good news — because the rule is a pre-set calendar window with almost no knobs to twist, it is very hard to accidentally curve-fit. That makes it one of the safest ideas for a beginner to test properly.

Build and test it in TapeScript, step by step

  1. Create it in plain English. Type: "Build a seasonality strategy on daily ES: go long at the close of the last trading day of the month, exit at the close of the third trading day of the new month, and stay flat otherwise."
  2. Classify and baseline. Type: "Classify this and run the baseline backtest." You will see the equity curve built only from those four-day windows.
  3. See the calendar edge. Type: "Open the Time and Context view and show returns by trading-day-of-month." This is the visual heart of the study — you want to see the turn-window days glowing and the mid-month days flat.
  4. Prove it did not decay. Type: "Run a walk-forward test decade by decade — is the effect still there in the last 10 years?" Honest seasonality must survive recent data, not just old data.
  5. Compare markets. Type: "Clone this strategy onto EURUSD and Nasdaq futures and compare — is the turn-of-the-month edge stronger on the index or the currency?" This directly answers the futures-versus-forex question.
  6. Final exam. Type: "Run Monte-Carlo and spend the untouched holdout, then simulate it on a prop-firm account."

The bottom line

The calendar is the one thing in trading you know in advance. Eighty years of data say a specific four-day window around each month's end carried most of the market's gains — a rare edge that is simple, low-parameter, and hard to fake. The only question that matters is whether it still pays on your market, in recent years, after costs. TapeScript answers that in minutes, with no lookahead and an honest holdout. Test the turn-of-the-month edge →

Citation: McConnell, J. J., & Xu, W. (2008). "Equity Returns at the Turn of the Month." Financial Analysts Journal, 64(2), 49–64. Origin: Ariel, R. A. (1987), "A Monthly Effect in Stock Returns," Journal of Financial Economics, 18(1), 161–174. Free versions on SSRN.

Frequently asked questions

What is the turn-of-the-month effect?

It is a calendar pattern where stock returns concentrate in a short window around the month's end. A 2008 Financial Analysts Journal study found that, from 1926 to 2005, essentially all of the U.S. market's average return occurred over four days — the last trading day of the month and the first three of the next — with the rest of the month averaging near zero.

Why does the turn-of-the-month effect happen?

It is driven by predictable cash flows: paychecks, retirement contributions, automatic investments, and month-end fund rebalancing all tend to arrive around the same time each month, creating recurring buying pressure that nudges prices up during the turn window.

Does the turn-of-the-month effect work on futures and forex?

It is strongest on stock index futures like the E-mini S&P 500 and Nasdaq. On forex it is weaker and tied to month-end currency-rebalancing flows, so it should be tested separately per market. Because the rule is a fixed calendar window with almost no parameters, it is relatively hard to curve-fit.

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