Develop and stress-test long/short equity theses with catalyst timing and Kelly-based sizing.
npx skills add https://github.com/tmcga/alpha-stack --skill long-short
Please help me install this Agent Skill. Skill: long-short Source: https://github.com/tmcga/alpha-stack/tree/main/skills/long-short Command: npx skills add https://github.com/tmcga/alpha-stack --skill long-short
This Skill provides a rigorous framework for building, validating, and sizing long/short equity theses with explicit edge versus consensus and catalyst-driven timing.
Provide a ticker and baseline view, and I will generate a complete edge, catalyst plan, and Kelly-sized position for a long or short idea.
High-intent search queries and answers about installing and using this skill.
To build a long/short equity thesis, you provide a ticker and baseline view to develop variant perception. The framework generates a catalyst plan, explicit risk/reward analysis, and Kelly-sized positions to guide execution against consensus.
Kelly criterion position sizing calculates optimal trade allocation based on your estimated edge and odds. It applies to portfolio construction here by integrating correlation checks and risk controls to optimize long/short equity positions.
Catalyst mapping identifies upcoming events that can close the gap between your variant perception and consensus pricing. It structures idea generation by linking these events to explicit risk/reward analysis and risk budgeting controls.
Yes, you can stress-test long/short equity ideas using built-in scenario testing. The framework supports factor-neutral construction and framework-driven decision gates to validate execution and manage risk budgeting.
The best way to size a long/short position is using Kelly-based sizing integrated with correlation checks. This optimizes portfolio construction by ensuring risk controls account for asset relationships before executing the trade.
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