When AI Trading Shook Nvidia Valuation

On Monday, Nvidia Corp. suffered the largest single-day loss in U.S. stock market history, shedding $593 billion in market value, according to Dow Jones Market Data. The catalyst? A breakthrough attributed to Liang Wenfeng, co-founder of High-Flyer Quant and its AI-focused subsidiary, DeepSeek.

DeepSeek, an advanced AI model, was developed by High-Flyer Quant, one of China’s largest quantitative trading firms. While it’s common for Wall Street quant veterans to explore the tech sector, DeepSeek’s debut marks a pivotal moment in AI innovation.

High-Flyer, a major player in Chinese financial markets, uses algorithms and mathematical models for trading. Over the weekend, DeepSeek’s AI model achieved global recognition after its release on a mobile app available to U.S. users. By late Sunday, the app had climbed to the top of Apple’s download charts. Social media was abuzz with comparisons between DeepSeek’s model and leading Western AI systems from OpenAI and Anthropic.

What set DeepSeek apart was its ability to compete with top-tier AI models while operating on a fraction of their budgets. The company claims it trained its models with fewer than 10,000 Nvidia A100 GPUs—a claim met with skepticism by figures like Tesla CEO Elon Musk. This efficiency sent shockwaves through the market as investors questioned the U.S.’s AI dominance and Nvidia’s role as the backbone of AI innovation. Nvidia’s stock plummeted 16.9%, erasing nearly $589 billion in market capitalization.

The market reaction also impacted shares of Microsoft, Alphabet, and Amazon, as doubts emerged about whether their massive AI infrastructure investments would deliver returns. Analysts, including those at Goldman Sachs, estimate that U.S. tech companies will spend over $1 trillion on AI development in the coming year. However, Sequoia’s David Cahn predicts a $600 billion gap between AI spending and revenue by late 2024.

Who Is Liang Wenfeng?

Liang Wenfeng, 40, grew up in Guangdong province and studied electronics and computer vision at Zhejiang University, one of China’s top institutions. In 2015, he co-founded High-Flyer Quant with two university friends. His increasing prominence in China’s AI sector was highlighted by his recent participation in a symposium hosted by Premier Li Qiang.

High-Flyer, which manages an estimated $8 billion in assets, began developing its AI capabilities by building a cluster of Nvidia GPUs. Liang joins a storied tradition of finance professionals leveraging their quantitative expertise to drive technological breakthroughs. Visionaries like Jeff Bezos, David Siegel, and David E. Shaw have similarly bridged the gap between finance and tech, creating transformative innovations in both industries.

The Intersection of Quant and AI

The fields of quantitative finance and AI research share significant overlap. According to Gareth Shepherd, co-head of Voya Machine Learning Intelligence, techniques such as reinforcement learning, deep learning, and Bayesian networks are foundational to both.

For years, hedge funds dominated the recruitment of top tech talent, offering some of the most lucrative opportunities in data science and machine learning. However, as the AI revolution gains momentum, tech giants like OpenAI are now luring talent with competitive compensation and the promise of groundbreaking projects.

Liang’s transition from quantitative trading to AI reflects the immense opportunities in the field. His success with DeepSeek highlights the rising competition in AI development and the sector’s potential to reshape global markets and challenge established leaders.