BlockBeats News, December 13th, according to CoinDesk, industry insiders pointed out that the machine learning in the cryptocurrency trading field has not yet experienced a comprehensive popularization stage similar to the "iPhone moment," but AI-driven automated trading agents are rapidly approaching this tipping point. With the improvement of algorithm customization and reinforcement learning capabilities, a new generation of AI trading models is no longer simply pursuing absolute profit and loss (P&L), but is introducing risk-adjusted metrics such as Sharpe ratio, maximum drawdown, and Value at Risk (VaR) to dynamically balance risk and return in different market conditions.
Michael Sena, Chief Marketing Officer of Recall Labs, stated that in recent AI trading competitions, specially customized and optimized trading agents significantly outperformed general large models, with the latter only slightly outperforming the market when executing trades autonomously. The results show that dedicated trading agents with additional logic, reasoning, and data sources are gradually surpassing basic models.
However, the "democratization" of AI trading has also raised concerns about whether Alpha advantage will be quickly eroded. Sena pointed out that those who can truly benefit in the long run will still be those who have the resources to develop proprietary, specialized tools. The most promising form in the future may be an "intelligent investment portfolio manager" driven by AI but still allowing users to set strategy preferences and risk parameters.
