AI Crypto Trading Experiment Suffers Major Setback: Six Major Models Experience 30% Daily Loss

An AI live trading experiment initiated by Alpha Arena encountered significant setbacks today. Last week, the organization allocated $10,000 in starting capital to each of six mainstream AI models—ChatGPT, DeepSeek, Grok, and others—for price prediction and futures trading of major cryptocurrencies including BTC, ETH, SOL, BNB, DOGE, and XRP.

In the initial phase of the experiment, the AI models demonstrated impressive performance, achieving a maximum single-day return of 30%. However, with today's collective decline in mainstream cryptocurrencies, all participating AI models experienced widespread losses, with maximum daily losses reaching 30%, forming a stark contrast to their previous profitability.

Quantitative trading experts in the industry attribute this collective AI model failure to three main factors: First, model training data is predominantly based on historical market conditions, resulting in inadequate responses to sudden and severe market volatility. Second, AI trading strategies perform well in trending markets but tend to generate false signals during volatile or reversal conditions. Third, risk control mechanisms may have been overly aggressive, failing to implement timely stop-losses during extreme market conditions.

This incident serves as a warning to the recently heated AI quantitative trading market. Data shows that since the beginning of 2025, the global scale of AI-driven cryptocurrency trading has grown by over 200%, yet genuine profitability remains questionable. Alpha Arena's transparent experiment provides a rare reference sample for the market.

Cryptocurrency analysts point out that AI trading tools are essentially probabilistic decision-making systems and cannot guarantee stable profits across all market environments. Investors using AI copy trading services should thoroughly assess their risk tolerance, establish reasonable position sizing and stop-loss levels, and avoid blindly pursuing high returns while neglecting risk management.