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Apply the Fama-French three-factor model to decompose asset returns into market, size, and value factors.
Passed 19 of 22 test cases with the skill, and 7 of 22 without it.
and 12 more in the full report
12 fixed7 passed either way3 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 12 test cases the skill fixed. Same model, same prompt, with and without the skill.
Run a Fama-French 3-factor breakdown for the Endurance Small Cap Fund (Market 1.05, SMB 0.75, HML 0.30, Alpha 0.15%, t-stat 0.50, CAPM R² = 72%, 3-Factor R² = 91%). Format in markdown standard structure.
| Checked | Without skill | With skill |
|---|---|---|
| Formats R-squared text line using `- Three-factor R2: 91% vs CAPM R2: 72%` | Missed | Passed |
| Concludes that size and value factors explain additional return variance compared to CAPM | Passed | Passed |
The instructions your model reads when the skill loads.
Fama and French (1993) extended CAPM by adding two factors — size (SMB) and value (HML) — to explain cross-sectional variation in stock returns that CAPM alone cannot capture. The model shows that small-cap and high book-to-market stocks earn systematic premiums.
IRON LAW: Single-factor models (CAPM) underestimate expected returns
for small-cap and value stocks. Size and value represent systematic
risk factors that command their own premia.
Key assumptions:
test cases passed, vs 7 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.