PyPortfolioOpt
Task 30 / 47
robust_mvo_rebalance
Robust mean-variance portfolio rebalancing under estimation uncertainty plus sector/factor/turnover constraints to improve out-of-sample or worst-case risk-return trade-offs. Convex robustification meets practical trading limits; scoring uses benchmark return/covariance data and constraint slacks.
Model leaderboard
| # | Participant | Score |
|---|---|---|
| 1 | GPT-5.4 | 100.0 |
| 2 | Claude Opus 4.6 | 100.0 |
| 3 | Grok 4.20 | 99.9 |
| 4 | Qwen3 Coder Next | 36.6 |
| 5 | DeepSeek V3.2 | 34.1 |
| 6 | SEED 2.0 Pro | 25.9 |
| 7 | GLM-5 | 24.7 |
| 8 | Gemini 3.1 Pro Preview | 0.0 |
Framework leaderboard
| # | Participant | Score |
|---|---|---|
| 1 | Claude Opus 4.6 + OpenEvolve | 100.0 |
| 2 | Claude Opus 4.6 + ShinkaiEvolve | 100.0 |
| 3 | Claude Opus 4.6 + ABMCTS | 100.0 |
| 4 | GPT-OSS + OpenEvolve | 100.0 |
| 5 | GPT-OSS + ShinkaiEvolve | 40.0 |
| 6 | GPT-OSS + ABMCTS | 0.0 |
Score is the normalized score for this task (0–100, higher is better).