Generate macro-driven crypto trading theses with risk controls and API integration.
npx skills add https://github.com/cubexch/ai-fund --skill arthur-hayes
Please help me install this Agent Skill. Skill: arthur-hayes Source: https://github.com/cubexch/ai-fund/tree/main/skills/arthur-hayes Command: npx skills add https://github.com/cubexch/ai-fund --skill arthur-hayes
Provide a macro-driven crypto trading framework that translates macro indicators into leveraged, conviction-based trades.
Describe a current macro thesis and request a Hayes-style leveraged crypto trade to execute.
High-intent search queries and answers about installing and using this skill.
This Skill generates a macro-driven crypto trading thesis by applying indicators like DXY, real yields, and the Fed balance sheet to map liquidity regimes to crypto positioning. It then defines conviction-based trades with risk controls and position sizing.
Mapping liquidity regimes to crypto positioning allows you to apply risk-managed leverage of 2-5x for position sizing. This framework pairs thesis-based stops with macro analysis to size conviction-based trades appropriately.
Yes, you can use perpetual funding rates as signals and carry to fine-tune crypto trade entries. This framework integrates funding rate analysis with macro event timing, like FOMC and CPI releases, to optimize execution for hedged spot and perp positions.
You build hedged crypto positions around FOMC and CPI macro events by constructing combined spot and perpetual trades timed to the release schedule. The framework uses liquidity regime shifts to define entries and apply thesis-based stops for risk governance.
Yes, the macro crypto trading framework supports API integration for execution and monitoring of leveraged trades. It includes explicit confirmation for orders and a staging mode to ensure governance over automated position management.
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