Is Deepseek Going to Trigger a Bear Market?

The Chinese AI firm DeepSeek has significantly advanced artificial intelligence with a cheaper Language Learning Model (LLM), marking a pivotal moment in the industry. While this development is not an unforeseen “black swan” event, it can be classified as a “gray swan,” presenting both opportunities and challenges. The breakthrough promises to accelerate AI adoption and unlock productivity gains, though it also raises questions about its broader economic and market implications, including potential effects on the U.S. Federal Reserve’s policy considerations.

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DeepSeek has gained attention for developing a competitive LLM that reportedly surpasses ChatGPT’s capabilities but at a fraction of the cost. The company achieved this by using less powerful Nvidia GPUs and significantly reducing the training time for the model. Additionally, DeepSeek’s open-source approach has made the technology accessible to a wider audience, challenging the dominance of American AI companies that rely on exclusive access to cutting-edge hardware.

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This development has stirred debates about its potential impact on the U.S. stock market, particularly regarding high-growth technology companies. Historically, bear markets in the S&P 500 have been linked to recessions caused by monetary policy tightening, credit crunches, or financial crises. DeepSeek’s innovation is unlikely to cause such disruptions. However, it could affect capital expenditures on AI infrastructure by American companies and influence the wealth of shareholders in firms like Nvidia.

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DeepSeek’s emergence challenges the existing AI landscape but also highlights the potential for innovation to lower costs and democratize access to technology. Companies that adapt to this shift may still profit by integrating AI into their products and services. Additionally, increased competition in the AI sector is expected to benefit businesses and consumers by driving efficiency and affordability.

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AI’s evolution can be seen as a continuation of the digital revolution, which has focused on processing data faster and more cost-effectively. Language learning models like DeepSeek’s play a crucial role in making vast amounts of data usable, ultimately enhancing productivity.

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Despite concerns, the overall valuation of the U.S. stock market remains resilient. While some worry about high price-to-earnings (P/E) ratios in the S&P 500, particularly among the “Magnificent Seven” tech giants, analysts believe earnings growth could sustain these valuations. Historically, valuation multiples rise during economic expansions and decline during recessions. Currently, rising bond yields have raised questions about whether the S&P 500’s forward P/E ratio has peaked.

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The relationship between the S&P 500 forward earnings yield and the 10-year Treasury yield is returning to historical norms after years of divergence driven by the Federal Reserve’s low-interest-rate policies.

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Analysts argue that stocks are now fairly valued relative to bonds, supported by strong earnings growth expectations. Even if the P/E ratios of the Magnificent Seven decline, the remaining 493 companies in the S&P 500 are likely to see rising valuations, as earnings growth across various sectors supports the broader market.

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Earnings growth is expected to drive stock-market performance through the decade, with analysts forecasting an annual growth rate of 17.9% for S&P 500 companies over the next five years. While these expectations echo those seen during the dot-com boom, the current environment offers cheaper valuations and aligns with pre-pandemic trends. Companies, particularly the Magnificent Seven, may offset high capital expenditures on AI infrastructure by leveraging AI to reduce internal costs and improve operational efficiency.

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Moreover, as AI tools become more affordable and accessible, other companies in the S&P 500 are likely to benefit from productivity gains, potentially boosting their profit margins. This dynamic could maintain the overall market’s valuation even if tech giants experience a decline in their P/E ratios.

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The Federal Reserve may take notice of the market reactions to DeepSeek’s emergence, though its primary focus will likely remain on economic fundamentals. If stock prices fall significantly, the Fed might be concerned about reduced consumer spending due to a negative wealth effect. However, a more probable scenario involves the Fed examining the broader implications of AI-driven productivity gains.

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Cheaper AI tools could enable businesses to cut costs and enhance worker productivity, creating a disinflationary environment. This might lead the Fed to reassess its neutral rate of interest, potentially influencing future monetary policy decisions.

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An AI-fueled productivity surge could support real GDP growth while keeping inflation in check. However, lowering interest rates in such a scenario might risk inflating a speculative bubble in risk assets.

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Analysts are optimistic about the economic outlook, assigning a 55% probability to a “Roaring 2020s” scenario characterized by robust growth and innovation. A speculative market melt-up, similar to the 1990s, is seen as less likely, with a 25% probability.

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Conversely, a stagflationary environment akin to the 1970s is considered the least likely outcome, with a 20% probability.

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Ultimately, DeepSeek’s breakthrough represents a “gray swan” event rather than a catastrophic black swan. While it disrupts the status quo in AI, it also opens doors for further innovation, competition, and productivity gains. By reducing the cost of AI adoption, DeepSeek may catalyze broader economic benefits, balancing the challenges it poses to existing market leaders.

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