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name: brain-improve-alpha-performance
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description: >-
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Provides a systematic 5-step workflow for improving WorldQuant BRAIN alphas.
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Includes steps for gathering alpha info, evaluating datafields, proposing idea-focused improvements (using arXiv), simulating variants, and validating.
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Use when the user wants to improve an existing alpha or fix failing submission tests.
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---
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# Alpha Improvement Workflow
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This repeatable workflow enhances alphas by focusing on core idea refinements rather than just mechanical tweaks.
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For the detailed steps, analysis techniques, and best practices, see [reference.md](reference.md).
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## Step 1: Gather Alpha Information (5-10 mins)
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**Goal**: Identify weaknesses (low Sharpe, high correlation, etc.).
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- Fetch alpha details (`get_alpha_details`).
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- Check PnL, Sharpe, Fitness, Turnover.
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- Run submission checks (`get_submission_check`) and correlation checks (`check_correlation`).
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## Step 2: Evaluate Core Datafield(s) (5-10 mins)
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**Goal**: Understand data properties (sparsity, frequency).
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- Run 6 evaluation simulations (Coverage, Non-Zero, Update Frequency, Bounds, Central Tendency, Distribution) using `brain-datafield-exploration` skill methods.
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## Step 3: Propose Idea-Focused Improvements (10-15 mins)
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**Goal**: Evolve the signal with theory-backed concepts.
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- Review docs for tips (ATOM principle, flipping negatives).
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- Search arXiv for concepts (e.g., "persistence", "momentum").
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- Brainstorm 4-6 variants (e.g., add decay, change normalization).
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## Step 4: Simulate and Test Variants (10-20 mins)
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**Goal**: Compare ideas via metrics.
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- Use `create_multiSim` to test variants.
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- Compare Fitness, Sharpe, and Sub-universe performance.
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## Step 5: Validate and Iterate (5-10 mins)
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**Goal**: Confirm submittability.
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- Run final checks.
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- If failing, repeat from Step 3 with new ideas.
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- If passing, submit!
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## Best Practices
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- **Cycle Limit**: 3-5 iterations per alpha.
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- **Focus**: 70% on ideas, 30% on parameter tweaks.
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- **Goal**: Passing checks + stable yearly stats.
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