Nasdaq Mid-Week Momentum Test

Conclusion: Rejected

Out-of-sample Sharpe was -0.91, versus -0.38 in-sample. A bootstrap test returned p = 0.953 (not significant).

The headline 76% figure does not replicate; the real conditional hit rate is ~55% and does not survive costs or payoff asymmetry. A classic case of a screenshot-friendly statistic that evaporates under out-of-sample, cost-aware testing.

Method

Rule / pseudocode

DATA ← adjusted observations for the stated instrument and horizon

RULE ← On the Nasdaq-100, the side of Monday's opening price that the index sits on by Wednesday's close predicts the direction of Friday's weekly close, giving a tradeable mid-week directional edge.

METHOD ← Instrument: QQQ · Entry: At Wednesday close take direction = sign(Wed close - Monday open) · Exit: Friday close

FIT ← estimate or select parameters on each training window only

TEST ← apply the frozen rule to the next unseen window after stated costs

REPORT ← return, Sharpe, drawdown, trade count, significance and fold stability

VERDICT ← prefer robustness and sufficient observations over the headline return

_Weekly return autocorrelation / drift persistence: once a directional bias is established early in the week (price holding above or below Monday's open), trend-following behaviour tends to carry it into the weekly close. The original poster claimed ~76% hit rate on 16y of NQ; the credible core is a modest positive conditional drift, not a coin-flip beater._

Out-of-sample equity curve

Growth of $1 over the held-out test data the strategy never saw while it was being built, after 10 bps round-trip costs.

Out-of-sample performance

OOS Sharpe

-0.91

Ann. return

-23%

Max drawdown

-48%

Win rate

50%

p-value

0.953

not significant

WF folds +

2/5

Measured on held-out data. A high Sharpe with a non-significant p-value means the result could still be luck — read them together.

Hypothesis

On the Nasdaq-100, the side of Monday's opening price that the index sits on by Wednesday's close predicts the direction of Friday's weekly close, giving a tradeable mid-week directional edge.

Method

Instrument: QQQ · Entry: At Wednesday close take direction = sign(Wed close - Monday open) · Exit: Friday close

Results

Out-of-sample Sharpe was -0.91, versus -0.38 in-sample. A bootstrap test returned p = 0.953 (not significant). Walk-forward Sharpe stayed positive in 2 of 5 folds. Worst out-of-sample drawdown was -47.69%.

Analysis

This tests a popular r/algotrading claim that on 16 years of NQ, whichever side of Monday's open price sits on by Wednesday calls the weekly close ~76% of the time. Reproduced honestly on QQQ daily bars with a fixed rule (no fitted parameters), the edge does not exist. In-sample Sharpe is already negative at -0.39 (-35.1% total return); out of sample it is worse at -0.91 (-46.1% total return, -47.7% max drawdown) over 303 independent weekly trades.

The measured out-of-sample directional hit rate is 55.1% — genuinely above a coin flip, and probably the grain of truth behind the Reddit post — but it is economically worthless here. Mean per-trade return after costs is negative because payoff is asymmetric: the weeks the rule gets wrong move further than the weeks it gets right, so 55% accuracy still bleeds money. Directional hit rate is not profitability.

Walk-forward validation is unstable: fold Sharpes [0.98, -1.57, 2.55, -0.47, -1.68] give only 40% positive folds and a combined walk-forward Sharpe of -0.70. There is no consistent regime in which the signal works; the positive folds are noise.

The block-bootstrap test on non-overlapping OOS trades returns p = 0.953 under the zero-edge null — the strategy is, if anything, significantly worse than random, consistent with buying strength/selling weakness into a two-day mean-reverting horizon after costs. The 10 bps round-trip cost (charged once per trade) is modest and not the primary driver; the raw directional bet has no positive expectancy.

Verdict: REJECTED. The headline 76% figure does not replicate; the real conditional hit rate is ~55% and does not survive costs or payoff asymmetry. A classic case of a screenshot-friendly statistic that evaporates under out-of-sample, cost-aware testing.

Source

Originated from discussion on r/manual.

Evidence

Walk-forward Sharpe by fold

Each fold retrains on past data then tests on the next unseen window. Staying positive across folds is the real test of an edge.

---

_Generated by labs-algo-trading. Automated research — not financial advice. Backtests overfit; treat verdicts as hypotheses._