The original theory

"Did you notice that the stock market takes massive jumps on the days leading up to the influx of institutional money from 401(k)s, etc. for people that get paid on the 15th/end of month and every two-week cycles? Seems like collusion to drive up prices for regular people."

This is the claim we set out to test. Before we can run any statistics, we need to unpack the assumptions baked into it and turn them into concrete, measurable predictions.

Embedded premises

The theory contains four implicit claims, each of which must be true for the overall argument to hold:

  1. Predictable calendar: Semi-monthly (15th and end-of-month) and biweekly paydays create a known, repeating schedule of money flowing into the stock market via 401(k) contributions.
  2. Measurable price impact: The volume of money flowing in on these dates is large enough to move prices in a statistically detectable way.
  3. Anticipatory run-up: Prices rise before the money arrives, not just when it lands — implying that someone is buying ahead of the known flow.
  4. Intentional front-running: The anticipatory price movement is not random — it reflects deliberate action by institutional traders who know the calendar and trade ahead of it to profit at the expense of 401(k) participants.

Testable predictions

We translated the theory into five specific, falsifiable predictions. Each one maps directly to a statistical test:

ID Prediction What we measure "Supports theory" if...
P1 Prices rise in the 5 trading days before paydays (T-5 to T-1) Mean daily return in the run-up window vs. all other days Run-up returns are significantly positive after controlling for known calendar effects (p < 0.05)
P2 Prices rise on payday (T) and the 3 days after (T+1 to T+3) Mean daily return on payday and post-payday days vs. all other days Payday and post-payday returns are significantly positive
P3 Volatility is elevated around paydays Parkinson volatility in payday windows vs. non-payday days Intraday range is wider around paydays than on ordinary days
P4 Volume is elevated around paydays Trading volume on payday-window days vs. non-payday days Volume is significantly higher in the payday window
P5 The price moves happen overnight, not during the trading session Overnight return (prior close to open) vs. intraday return (open to close) Overnight returns account for most of the excess return in the payday window
We are going to check whether the stock market behaves differently around paydays compared to ordinary days. Specifically, we will look at whether prices go up more than usual in the days before and around paydays, whether the market is choppier or busier on those days, and whether any price gains happen overnight (when regular people are not trading) rather than during the day.

What would DISprove the theory

A hypothesis is only useful if we can specify what evidence would cause us to reject it. The theory would be disproven if:

Possible alternate explanations

Even if we find a statistically significant pattern, it does not automatically mean the theory is correct. We must consider alternative explanations:

Turn-of-month effect

The turn-of-month effect is a well-documented anomaly (Ariel 1987, Lakonishok & Smidt 1988) where stock returns are disproportionately concentrated in the last trading day of each month and the first three days of the next month. Because end-of-month paydays overlap with this window, any payday signal could simply be the turn-of-month effect wearing a different label. Our regression controls explicitly for this.

No signal at all

The most parsimonious explanation is that there is no payday effect — that daily returns around paydays are indistinguishable from any other trading days once known calendar effects are removed. This is our null hypothesis, and the burden of proof is on the theory to disprove it.

Volatility compression

It is possible that what looks like a payday "bump" is actually reduced volatility around paydays creating an illusion of smoother upward drift, while the magnitude of returns is unchanged. Our GARCH analysis helps disentangle return effects from volatility effects.

Prediction scorecard: what actually happened

After completing the full investigation, here's how each prediction fared. The verdicts reflect ALL findings, including the Friday revelation and structural flow reframing.

IDPredictionVerdictWhat we found
P1Prices rise T-5..T-1 REVISED Yes, but only at lag+7-8 (not lag+0), only for semi-monthly pay, only on Fridays, and only post-1978. The effect is real but far more specific than predicted.
P2Rise at T and T+1..T+3 NOT SUPPORTED No consistent positive signal at T or T+1..T+3 after controlling for calendar effects and clearing lag.
P3Volatility elevated REVERSED Volatility is actually lower in the run-up window — consistent with "flow absorbed smoothly," not with manipulation.
P4Volume elevated PARTIALLY Volume is +10% on month-end paydays (the classic turn-of-month). Biweekly shows highly significant volume spikes (p<0.001) but NO return signal — the money is flowing but too diffuse to move prices.
P5Moves happen overnight MIXED Some post-month-end overnight return elevation (marginal), but not conclusive. The bigger finding is the intraday directional ratio: the market systematically closes near the high before month-end (p=0.001).
Scorecard summary: 0 of 5 predictions fully confirmed as originally stated. 2 revised (the pattern exists but is more specific than predicted). 2 failed. 1 mixed. The theory's core intuition — that predictable money flow creates a detectable market pattern — survived. The mechanism (intentional front-running / collusion) did not.

How the theory evolved

Science doesn't often end where it started. Here's how each discovery reshaped our understanding:

April 16: "The pattern is at lag+7-8, not lag+0"

The naive test (lag+0) found nothing. Shifting by 7-8 trading days to account for the clearing lag revealed a statistically significant pattern. Theory revised: money doesn't impact the market on payday — it takes a week to arrive.

April 16: "It emerged with 401(k) adoption"

The clearing-lag pattern didn't exist before 1978 (when 401(k) plans were created). It emerged in the 1990s, peaked in the 2000s, faded in the 2010s. This timeline matches 401(k) adoption precisely — powerful evidence for the flow mechanism.

April 18: "The signal is 100% Friday-dependent"

Removing all Fridays from the dataset eliminates every significant result. The effect isn't about "lag+7-8" in general — it's about what happens on Fridays that fall in that window. Theory revised: the mechanism is Friday settlement clustering (payroll batching, biweekly overlap, options expiration interaction).

April 18: "Structural flow, not manipulation"

The combination of Friday dependency, biweekly volume-without-returns, component decomposition (neither 15th nor EOM alone is significant), and the Sabbatucci cross-sectional challenge points to structural settlement mechanics rather than intentional manipulation. The cost to investors is real but the cause is infrastructure, not adversarial intent.

The bottom line: The original theory asked the right question — does predictable 401(k) money flow leave a fingerprint in the stock market? The answer is yes. But the fingerprint is subtler, more specific, and more structural than "collusion to drive up prices." It's concentrated on Fridays, tied to settlement infrastructure, and represents one component of the broader turn-of-month phenomenon rather than a standalone manipulation scheme.
Revision log:
  • April 16: Original hypothesis stated. Clearing-lag discovery (lag+7-8). Historical emergence confirmed (post-1978). Alternative explanations tested (FOMC, OpEx, CPI — all survived).
  • April 18: Friday isolation test — signal vanishes without Fridays. Biweekly deep-dive — volume without returns. Component decomposition — neither 15th nor EOM alone significant at lag+7-8. Settlement timing research — DOL regulations, recordkeeper data. Theory reframed from "manipulation" to "structural flow."