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alphagbm-etf-strategy

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Score ETF trend, risk, liquidity, cost and available tracking and theme signals while preserving data gaps. Use when the user asks to etf strategy with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.

skills/stocks/alphagbm-etf-strategy/SKILL.md

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Last checked
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Oct 6, 2026
License
MIT

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# ETF Strategy

Score ETF trend, risk, liquidity, cost and available tracking and theme signals while preserving data gaps.

Release preview: the matching backend has not been verified in production. Do not claim this structured workflow is live; unsupported servers must fail closed. Retained legacy runner commands remain compatible.

## Before running

Read [access and evidence rules](references/access.md). Python 3.9+ is the only runtime dependency; no separate CLI or sibling Skill installation is required. Resolve `<skill-dir>` to the directory containing this file.

Use a plain, non-leveraged ETF ticker. The workflow scores observed trend, risk, liquidity, cost, tracking, theme and event inputs only when supplied by the provider. Leveraged and inverse ETFs are rejected. Expense ratio may be available from the provider; tracking error, theme and event signals may remain missing. Preserve status and missingData, and never fill them from model memory or a demo. The strategy-workflows.v1 backend must be deployed; unsupported servers receive no paid request.

## Run
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