Compute optimal Kelly fractions and position sizes from win probability and payoff ratio.
npx skills add https://github.com/cubexch/ai-fund --skill ed-thorp
Please help me install this Agent Skill. Skill: ed-thorp Source: https://github.com/cubexch/ai-fund/tree/main/skills/ed-thorp Command: npx skills add https://github.com/cubexch/ai-fund --skill ed-thorp
Provides a disciplined, math-driven framework for identifying and sizing edge in trading strategies using Kelly criterion, with explicit risk controls and bankroll management.
Provide the win probability and payoff ratio for a trade to compute the optimal Kelly fraction and determine the recommended position size.
High-intent search queries and answers about installing and using this skill.
To calculate optimal bet sizing for quant trading, you provide the win probability and payoff ratio of a trade. The framework then computes the recommended Kelly fraction to determine your exact position size.
Full Kelly sizing maximizes long-term bankroll growth by allocating the exact mathematical edge, while half Kelly reduces the fraction to lower drawdown risk. This framework supports both sizing methods to match your risk tolerance.
You backtest a trading strategy by applying historical inputs to the edge estimation framework. This process models your bankroll trajectory to forecast expected growth and potential drawdowns before live execution.
Yes, you can apply this risk management framework across multiple crypto exchanges. It processes standard API data inputs to calculate edge-aware sizing and track performance consistently across different venues.
The framework enforces explicit safety guardrails and edge verification protocols to prevent account ruin. These rules restrict overexposure and validate strategy health before executing risk-aware position sizes.
You track quantitative trading edge by using the built-in performance tracking and self-evaluation tools. These metrics monitor your strategy health over time to ensure your calculated edge remains valid.
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