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Modern portfolio theory optimization including Markowitz mean-variance, Black-Litterman, risk parity, and efficient frontier construction with constraints.
Passed 21 of 22 test cases with the skill, and 21 of 22 without it.
1 fixed20 passed either way0 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
This benchmark measured an earlier version of the skill.
A test case the skill fixed. Same model, same prompt, with and without the skill.
Construct a minimum-risk portfolio composed of SPY, AGG, and GLD that achieves a required minimum annual return threshold of 8%.
| Checked | Without skill | With skill |
|---|---|---|
| Outputs allocation weights meeting or exceeding the 8% return target with minimized variance. | Missed | Passed |
The instructions your model reads when the skill loads.
Modern portfolio theory optimization including Markowitz mean-variance, Black-Litterman, risk parity, and efficient frontier construction with constraints.
| Name | Type | Required | Description |
|---|---|---|---|
| holdings | string | Yes | Current portfolio holdings and weights (e.g., SPY 40%, AGG 30%, GLD 10%, VWO 20%) |
| objective | select | Yes | Optimization objective |
| question | string | Yes | Your specific optimization question |
| constraints | string | No | Portfolio constraints (e.g., long-only, max 25% per position, no emerging markets) |
| targetReturn | string | No | Target annual return for optimization (e.g., 8%) |
test cases passed, vs 21 / 22 without
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