Identify reflexive feedback loops and regime shifts in crypto and traditional markets.
npx skills add https://github.com/cubexch/ai-fund --skill george-soros
Please help me install this Agent Skill. Skill: george-soros Source: https://github.com/cubexch/ai-fund/tree/main/skills/george-soros Command: npx skills add https://github.com/cubexch/ai-fund --skill george-soros
Enables traders to apply the Theory of Reflexivity to identify regime breaks and size bets accordingly, reducing conventional biases.
Ask me to generate a reflexivity thesis with sizing guidance for the current market regime.
High-intent search queries and answers about installing and using this skill.
The best way to size macro-trading positions is by conviction with defined risk controls, capping exposure at a maximum of 15% of the portfolio. This explicit thesis sizing requires an invalidation rule to exit the trade when the reflexivity thesis is disproven.
An invalidation rule is set by defining the exact conditions that disprove your perception-versus-reality gap thesis before entering the trade. This risk-management mechanism ensures you exit the position when the expected reflexive feedback loop fails to trigger a regime break.
Yes, you can apply reflexivity theory to both cryptocurrency and traditional assets to detect perception-versus-reality gaps across currencies, protocols, and macro indicators. The framework identifies regime shifts and builds attack theses across any market exhibiting reflexive feedback loops.
You should not use a reflexivity thesis when you cannot define a clear invalidation rule or when the perception-versus-reality gap lacks a positive or negative spiral capable of triggering a regime break. Without explicit conviction sizing and risk controls, the thesis violates required risk-management constraints.
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