In one line: near-index return at roughly
half the worst-case drawdown — and ahead of buy-and-hold in every 12-month window where the index
fell more than 20%.
Same rules, two large-cap universes — the matching shape is the point.
| Metric | Nasdaq-100 | S&P 500 |
|---|---|---|
| Portfolio CAGR ($100k, 0% on cash) | 11.4%/yr | 9.3%/yr |
| Exposure-adj. CAGR (in-market only) | 11.4%/yr | 9.3%/yr |
| Concurrent symbols | ≤20 (~20 held) | ≤20 (~20 held) |
| Max drawdown | −30% | −23% |
| vs. buy & hold the index (CAGR / max DD) | 15.3%/yr · −53% | 10.9%/yr · −55% |
Portfolio CAGR and exposure-adjusted CAGR coincide here because the book is near-fully invested. Window 2005–2026 (21.4 yrs).
| Kind of system | Momentum rotation — rank large-caps by trend strength each week, hold the strongest, rotate as the ranking shifts. |
|---|---|
| Universe | Nasdaq-100 and S&P 500, run as two separate variants. |
| Average period | Weekly — ranked from Tuesday’s close, rebalanced once a week. Positions ride for multiple weeks until the trend, a gap, or a rank drop ends them. |
| Exposure | Mostly in the market — holds a position on ~100% of trading days (~85% of capital deployed), cut to ~38–52% only in 2008 and 2022. |
| Distinguishing feature | Index-like return at roughly half the max drawdown (−30% vs −53% on the Nasdaq-100; −23% vs −55% on the S&P 500), with Sharpe equal to or above buy-and-hold. The edge concentrates in down markets. |
| Who it’s for | A portfolio manager whose first job is to protect capital through the cycle — a defensive equity allocation or drawdown-aware sleeve, not a pure maximum-growth mandate. |
| Out-of-sample | Tested 2005–2026 (21.4 yrs). The rules are an externally specified book recipe (Clenow, Stocks on the Move 2015 / Trading Evolved 2019), not fitted here; a conservative post-publication pivot at 2021 leaves ~5.4 yrs strictly out-of-sample. |
→ Details for the plain-English walk-through, the bear-market record, and how it was tested — or the full Deep Dive with methodology, the monkey baseline, the sizing ablation, and the risk-adjusted tables.
See if it fits your mandate. We can re-run this on your own universe
and risk limits, or send you the Python, daily trade logs, and data behind every number.
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