The performance of AI operation hedge funds has gradually surpassed that of humans

    In recent years, the integration of artificial intelligence (AI) into hedge fund operations has gained significant momentum. According to Eurekahedge, a leading hedge fund index, the average return of 13 AI-driven hedge funds since 2010 has been 10.6%. Major asset management firms like Two Sigma and Goldman Sachs have increasingly adopted AI as a core research tool or strategic component in their investment processes. Luke Ellis, CEO of Man Group, one of the largest hedge fund groups, has predicted that if AI computing power continues to grow at its current pace, it could manage 99% of global investments within 25 years. Man Group has already invested approximately $13 billion in AI-powered hedge funds, signaling a strong belief in the technology's potential. A recent image illustrates how AI-driven hedge funds are gradually outperforming traditional human-managed ones, showcasing the growing influence of machine learning in financial markets. The ability of AI to process vast amounts of unstructured data—such as social media activity and smartphone usage—has proven to be more efficient than human analysts in identifying trends and predicting company performance. According to consulting firm Opimas, by 2025, around 300,000 professionals in the finance sector—including fund managers, analysts, and back-office staff—could be affected by AI automation, with 90,000 positions at risk. This shift is being driven by the underperformance of many traditional hedge funds over the past decade, prompting investors to seek out AI-based alternatives. Hedge Fund Research reports that Quant Funds, which rely heavily on algorithmic strategies, have seen their assets under management increase by 86% to $94 billion since 2010. In 2016, while most hedge funds lost $83 billion, quantitative funds generated $13 billion in profits—a trend that continued through September 2017. Vasant Dhar, who launched the first AI-powered hedge fund two decades ago, believes that AI can not only analyze data but also generate hypotheses, test them, and provide insights that fundamentally change how humans approach work. His firm, SCT Capital Management, manages about $350 million and operates entirely on AI-driven models. As AI becomes more prevalent, human analysts may need to adapt by learning coding skills to remain competitive. MarTIn Taylor, who closed his non-AI hedge fund Nevsky Capital in 2016, noted that when fund returns decline, companies often invest more in engineers while reducing human roles to maintain profitability. Acadian Asset Management, another major player in AI-driven hedge funds, has grown by 79% over the past five years, reaching $93 billion in assets. Its team consists of individuals with diverse backgrounds, including strong statistical knowledge and programming skills, along with real-world market experience. Juergen Schmidhuber, an AI expert and hedge fund adviser, predicts that neural networks will become powerful indicators across all industries. He envisions a future where most transactions are executed through autonomous learning algorithms, with human decision-making playing a more occasional role.

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