I’ve seen quite a few projects advertising AI-powered trading and fully automated money management, claiming exceptionally high win rates.
But the actual research tells a different story.
In one AI-Trader experiment, all 6 AI models lost money in crypto. Even the best model recorded a -12.18% return, while none managed to beat the market benchmark.
In StockBench, 5 out of 13 AI models failed to outperform Buy & Hold.
A high win rate doesn’t necessarily mean consistent profitability. Real performance depends on execution, risk management, drawdowns, and long-term results.
I believe the most interesting direction is Hybrid AI, combining Machine Learning, LLM Agents, Reinforcement Learning, and robust risk management.
AI has potential, but fully automated trading with consistently high returns is a different story.
The real question isn’t how often AI wins, but how consistently it can make money.
But the actual research tells a different story.
In one AI-Trader experiment, all 6 AI models lost money in crypto. Even the best model recorded a -12.18% return, while none managed to beat the market benchmark.
In StockBench, 5 out of 13 AI models failed to outperform Buy & Hold.
A high win rate doesn’t necessarily mean consistent profitability. Real performance depends on execution, risk management, drawdowns, and long-term results.
I believe the most interesting direction is Hybrid AI, combining Machine Learning, LLM Agents, Reinforcement Learning, and robust risk management.
AI has potential, but fully automated trading with consistently high returns is a different story.
The real question isn’t how often AI wins, but how consistently it can make money.
