Core Insights - The article discusses a unique competition where AI models are tested in real-time trading of cryptocurrencies, aiming to determine which model can generate the highest returns without human intervention [1][2]. Group 1: AI Trading Competition - The competition involves six AI models, each with a capital of $10,000, trading major cryptocurrencies like BTC, ETH, and others [1]. - The event has generated significant interest, surpassing traditional stock trading discussions among participants [1][2]. - The performance of the models is evaluated based on their ability to analyze market data and sentiment, akin to human traders [2]. Group 2: Performance of AI Models - After six days, the leading model, DeepSeek Chat v3.1, initially achieved a return of nearly 40%, but has since stabilized around 10% due to market fluctuations [3]. - The most well-known model, GPT-5, has suffered a loss of 68.9%, indicating a poor performance compared to its peers [4]. - Qwen3 Max has outperformed DeepSeek Chat v3.1 with a return of 13.41% by employing a more aggressive trading strategy [7]. Group 3: Insights on AI Models - DeepSeek's strong performance may be attributed to its quantitative background, although initial tests showed mixed results for various models [7]. - The competition highlights the unpredictability of the market and the need for models to adapt to changing conditions [9]. - Observing the trading strategies and decisions of the models provides valuable insights beyond just the final returns [11]. Group 4: AI in Stock Trading - The article emphasizes the importance of selecting the right AI model for stock trading, as many retail investors are beginning to rely on AI tools for investment decisions [12]. - The development of financial AI models has evolved significantly, with notable examples like BloombergGPT, which faced challenges due to its high costs and closed systems [14]. - Despite the potential of AI in trading, many users report dissatisfaction with the outputs, indicating a need for better data quality and model customization [15][18]. Group 5: Challenges and Limitations of AI - AI models often struggle with understanding complex market dynamics and may produce similar strategies, limiting their effectiveness against larger, more sophisticated quantitative firms [16]. - The article warns that relying solely on AI without a solid understanding of investment principles can lead to significant losses [19][23]. - AI's limitations in predicting "black swan" events and its reliance on historical data highlight the need for human oversight in investment decisions [24][26].
中国AI模型超美国模型，靠AI炒股的时代来了吗？
3 6 Ke·2025-10-26 09:20