Executive verdict (before clearing-lag adjustment)

We tested whether S&P 500 returns are systematically higher around paydays, using the methodology described on the previous page. The short answer: the theory as stated is not supported.

When we align the payday calendar directly to market dates — treating the paycheck date as the date of market impact — we find no consistent evidence of elevated returns in the run-up window. In fact, the only coefficient that survives multiple-testing correction points in the wrong direction.

At this point in the investigation, the payday effect hypothesis appears to be dead in the water.

Prediction scorecard

In the hypothesis page, we translated the payday effect theory into five testable predictions (P1 through P5). Here is how each one fared against the data:

ID Prediction Result Verdict
P1 Run-up returns (T-5 to T-1) should be positive and significant Run-up coefficient is negative in most windows. Semi-monthly run-up = -0.001%/day (full period), with no significance. Rejected
P2 Post-payday returns (T+1 to T+3) should be flat or slightly positive from actual fund purchases Post-payday coefficients are inconsistent across windows and pay types. No clear pattern emerges. No support
P3 Semi-monthly pay should show the strongest signal (concentrated flow from salaried workers) Semi-monthly actually shows the weakest signal of all pay types tested. Mid-month shows the largest coefficient, but it's negative. Reversed
P4 The effect should be visible on payday (T=0) itself There are some positive T=0 coefficients, but they appear on the wrong days and do not survive FDR correction. Partial, wrong day
P5 The effect should be stronger in recent decades (as 401(k) assets grew) Some windows show larger magnitudes in recent data, but the signs are inconsistent — sometimes positive, sometimes negative. Mixed

Zero out of five predictions are cleanly confirmed. The scorecard reads like a failed experiment.

Coefficient estimates by bucket

The chart below shows the regression coefficients (in percent per day) for each timing bucket — run-up, payday, and post-payday — across all tested time windows and payday types, filtered to the S&P 500 with semi-monthly pay. Error bars show the 95% bootstrap confidence interval.

S&P 500 semi-monthly payday coefficients by bucket and time window
Grouped bar chart of beta coefficients (% per day) with 95% bootstrap confidence intervals. Filter: asset = sp500, payday_type = semi.
The only coefficient surviving FDR correction points the wrong way: semi-monthly run-up = -0.48%/day in the recent 12-month window. If anything, the market goes down before paydays, not up.

But wait...

Before we file this under "debunked," consider a fundamental assumption baked into every test above:

The theory assumed payday = market impact date. But your 401(k) money doesn't hit the market the day you get paid.

Think about what actually happens when you receive a paycheck with a 401(k) deduction:

  1. Your employer issues the paycheck (payday)
  2. The payroll provider batches 401(k) contributions and sends them to the plan recordkeeper (1-2 business days)
  3. The recordkeeper (Fidelity, Vanguard, etc.) processes the contribution and places trade orders (1-2 business days)
  4. Mutual fund shares are purchased at the next available NAV price (1 business day)
  5. The trade settles (T+1 for mutual funds, T+2 for equities)

That entire chain takes roughly 3 to 7 business days. So when we test "does the market go up before payday?" we're asking the wrong question. The market can't react to money that hasn't arrived yet.

The initial "failure" was actually a clue. If the payday effect is real, it wouldn't show up around the paycheck date itself — it would show up around the date the money actually arrives in the market. We were looking in the right place, but at the wrong time. The next page explores what happens when we shift the calendar forward to account for this clearing lag.

What if we shift the calendar forward? →