Quantmodel · Strategy research

Pinwheel

Pinwheel receives a research grade of F (composite 39 / 100) on Paper-to-Profit robustness tests run against published monthly ours versus SPY. On these tests the published path does not currently support a constructive allocation case.

F score 39 BF 172.0 months 2012-04 → 2026-07

Factor grades

Statistical edge · 20% F 16
Bootstrap vs SPY · 18% F 12
Alpha decay · 16% F 3
Overfit / stability · 16% A 89
Cost robustness · 15% A 96
Regime / stress · 15% F 32

Published CAGR 7.66% / Sharpe 0.81 / max DD -19.6% over 172 months. Those headline stats are context only; the grade is the robustness tests above.

Assessment

Statistical edge

The path makes money vs zero (p=0.003) but is not a significant edge versus SPY (p=0.001, excess -0.54% per month). Same failure mode as a strategy that only rides beta.

Bootstrap versus SPY

Block bootstrap of consecutive months (400 paths): P(beat SPY) over 6.0 months is 21%; over 24.0 months is 2%. This is the Paper-to-Profit 'realistic path' test, not a reshuffled iid sample.

Alpha decay

1% of 12-month OLS windows have a significantly positive slope and 64% are significantly negative. Terminal strategy/SPY wealth ratio is 0.43. A steadily rising log-relative-wealth line is the decay test from the tutorial; a late collapse is a warning.

Overfit / stability

70/30 OOS/IS Sharpe ratio is 0.93; second/first-half Sharpe ratio is 1.16. Walk-forward parameter search is not estimable on a frozen catalog snapshot; this split is the overfit proxy. Return-space noise did not halve Sharpe on the tested grid.

Transaction costs

Average daily turnover is 0.013%. Additional one-way costs through 24 bps did not cut Sharpe in half. That is the tutorial's cost-robust case.

Regimes and crises

The path beats SPY in 5% of classified months (1.0/5.0 regimes). In bear/strong-bear/vol-down months it beats SPY 0% of the time. Crisis windows: COVID crash: strategy -14.3% vs SPY -19.4%; 2022 inflation shock: strategy -19.6% vs SPY -23.9%.

Limitations

Tests use published monthly ours, already lagged one bar in the engine, versus SPY. t-tests assume roughly comparable monthly means; Wilcoxon is shown as a non-normal check. Bootstrap paths are overlapping consecutive months (not iid reshuffles). Noise is added to monthly returns, not to OHLC, because this producer does not rerun backtests. Walk-forward parameter optimization, SPA, and PBO are not estimable without a trial ledger. Fee drag is extra one-way bps on catalog average daily turnover, on top of the published costed path.

Edge tests

Test Statistic p-value Significant?
t-test vs zero 3.07 0.0025 yes
t-test vs SPY (paired) -3.45 0.0007 no
Wilcoxon vs zero 9778.0 0.0002 p<0.05

Part 1: a strategy that only beats zero but not SPY has no statistically significant edge versus the market.

Monthly return distributions

Strategy versus SPY on the shared window. Input to the t-tests above.

Block bootstrap — 6 months

400 overlapping consecutive-month paths. P(beat SPY) = 21% . Fan is p10 / p50 / p90 of terminal wealth from $1.

Block bootstrap — 24 months

Same construction at a two-year horizon. P(beat SPY) = 2% .

Bootstrap excess CDF

Sorted 24-month strategy minus SPY terminal wealth. Fraction above zero is P(beat SPY).

Relative wealth versus SPY

Strategy equity divided by SPY equity. A rising line is persistent outperformance; a late roll-over is decay.

Rolling OLS slope of log relative wealth

12-month window on ln(strategy/SPY). Positive significant slopes are the tutorial's "edge is still there" test.

70/30 chronological split

Train through 2022-04. OOS/IS Sharpe ratio 0.93 . Walk-forward parameter search is not estimable here; this is the overfit proxy.

Transaction-cost sensitivity

Extra one-way bps applied to average daily turnover, on top of the published (~10 bps) path. Half-Sharpe at beyond 24 bps.

Return-space noise

Gaussian noise scaled by 12-month rolling vol. Not an OHLC re-backtest. Critical multiplier (Sharpe halves): not reached.

SPY regimes

Seven trend/vol states on a 12-month SPY window. Mean monthly return of strategy versus SPY in each state.

RegimeMonthsStrategy meanSPY meanBeats SPY?
Strong bull 89.0 0.84% 1.62% no
Bull 35.0 0.54% 0.89% no
Sideways 8.0 -0.76% -1.94% yes
Bear 2.0 — — —
Strong bear 0.0 — — —
Volatility up 27.0 1.43% 2.38% no
Volatility down 11.0 -0.93% -0.86% no

Named crisis windows

EpisodeStatusStrategySPY
Dot-com bust not_estimable — strategy history does not cover this episode — —
Global Financial Crisis not_estimable — strategy history does not cover this episode — —
COVID crash ok -14.3% -19.4%
2022 inflation shock ok -19.6% -23.9%

Growth of $1

Published path versus SPY, 60/40 when present, and a leave-one-out catalog mix. Context only — not a scoring factor.

Drawdown

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