Forget the AI Trading Bot Hype — A New Trading Model Debate Is Shaking the Industry
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Crypto quants and prediction market traders, led by Joao Wedson (founder and CEO of Alphractal), warn that LLMs are not trading engines and can amplify losses without proper risk controls. They urge quantitative, backtested strategies across market cycles and researchers caution that AI's pattern reliance limits adaptation to new markets, posing risks for automated trading, DeFi and CEX strategies.
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- Joao Wedson warns LLMs are not built for trading and can amplify losses without risk controls.
- Wedson advocates a quantitative trading approach with strategies backtested across market cycles.
- Researchers say AI relies heavily on patterns, raising concerns about its ability to adapt to new markets.
A new debate across crypto and prediction markets is challenging the idea that large language models (LLMs) can safely run trading strategies on their own.
Quants, researchers, and Polymarket traders are pushing back against the narrative. Their argument is that LLMs may sound intelligent, but they were not designed to trade financial markets.
“LLMs Are Not Trading Engines,” Says Joao Wedson
In a tweet, Joao Wedson, founder and CEO of Alphractal, warned traders against relying on LLMs to automate trading.
According to Wedson, LLMs are built to understand la…
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