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🎰 AI agents for stock trading show ambiguous results — Bloomberg.
Developer Jake Nesler trained an agent based on Claude with his own trading logic and launched it on a simulated account with $100,000. Over 30 days, the bot yielded about 7% compared to approximately 4.5% for the S&P 500, but with drawdowns up to 22%. The author does not recommend investing real money.
Structural problem: language models default to conservative positions — blue-chip stocks and defensive assets. Traders are forced to manually reconfigure agents for a more risky profile.
Former quant trader Annanay Kapila believes that LLMs are fundamentally unsuitable for short-term price forecasting.