AI Trading Competition Pits LLMs Against Fixed Rules With $100K Simulated Portfolio

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A public experiment called the AI Trading Competition tests whether large language models can outperform a static, rule-based trading system using a simulated $100,000 portfolio. Multiple LLMs participate as active traders, making decisions autonomously, while the frozen rulebook serves as a benchmark opponent. Early results suggest the predefined rulebook strategy is leading over the AI-driven approaches. The project is openly accessible and appears designed to evaluate real-world decision-making capabilities of modern AI models in financial contexts. No specific timeframe or sponsoring organization has been disclosed in the available information.

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