December rate cut odds jump to 90%

Key Concepts

• Metaverse Moment Analogy: Comparing the current AI capital expenditure narrative to the metaverse bubble of 2021, where excessive spending led to investor punishment and subsequent spending cuts.
• AI Capital Expenditure Skepticism: Growing investor doubt regarding the profitability and sustainability of current AI-related capital spending.
• Monetization Challenges: Difficulty in translating AI efficiency gains into tangible profits for companies.
• Hyperscaler Spending: Significant investments by major tech companies (Microsoft, Meta, Google, Amazon, Oracle) in AI infrastructure.
• Depreciation Expense: The annual cost associated with the decline in value of AI assets.
• Unprofitable Investment: The scenario where AI investments do not generate sufficient returns to cover their costs.
• Investor Disillusionment: A potential shift in investor sentiment away from AI stocks due to concerns about profitability.
• Economic Drag: The risk that a downturn in AI spending could negatively impact the broader economy.
• Recession Risk: The possibility of an economic downturn, potentially triggered by a stock market correction.
• Rate Cuts: The Federal Reserve lowering interest rates to stimulate the economy.
• Economic Weakness Indicators: Signs of a struggling economy, such as stalled job growth and declining wage growth.

AI Capital Expenditure and Investor Sentiment

The discussion highlights a growing skepticism surrounding the narrative of Artificial Intelligence (AI) capital expenditure, with tech stocks currently leading market gains. Peter Barrison, Chief Global Investment Strategist and Director of Research at BCA Research, draws a parallel to the "metaverse moment" of 2021. In 2021, Meta faced investor backlash for excessive metaverse spending, leading to a reduction in their investment. Barrison anticipates a similar scenario for AI, where a major AI company announcing increased capital spending might see its stock price decline. This, he suggests, could deter further announcements and create a "bust" in AI capital spending, potentially dragging down the entire economy due to its current reliance on such investments.

The "Rubber Hits the Road" for AI Monetization

Barrison believes that the upcoming year will be critical for the AI narrative, as investors are likely to become disillusioned. While acknowledging that AI will undoubtedly lead to efficiency gains and is "super useful," the primary concern is the difficulty in monetizing these advancements. As investors shift their focus to this monetization challenge, a significant sell-off in AI-related stocks is anticipated. This sell-off could be substantial enough to negatively impact the economy and potentially trigger a recession, reminiscent of the 2001 recession, which was more a consequence of a stock market crash than its cause.

Profitability of Large Language Models (LLMs)

A key point of contention is the profitability of Large Language Models (LLMs). While these models are profitable for companies like Nvidia, they are not generally profitable for other entities. Barrison points to the substantial capital expenditure announced by hyperscalers. If these figures are taken seriously, they are projected to hold approximately $2 trillion in AI assets by 2030. With a depreciation rate of around 20% on these assets, this translates to an annual depreciation expense of $400 billion. This figure is nearly equivalent to the combined profits of hyperscalers like Microsoft, Meta, Google, Amazon, and Oracle, which were slightly less than $400 billion in the current year. Barrison argues that unless these companies can significantly grow their revenues and profits, they are facing a scenario of unprofitable investment, which investors will eventually penalize.

Investment Advice for Investors

For the end of the year, Barrison advises investors to "take some profits." While not advocating for a complete shift to defensive positions due to the absence of imminent recession risk, he suggests moving "a little bit to the sidelines." He emphasizes that at current valuation levels, even if one fully embraces the AI narrative, future returns over a five-year horizon are historically very low. This means investors are "not really getting paid to be in this market" and there is limited upside. Conversely, there is significant downside risk if the AI narrative begins to "crater."

Federal Reserve Rate Cuts and Economic Conditions

Barrison anticipates that the Federal Reserve will cut rates in December. He attributes this decision partly to political pressure but more significantly to the economy's need for rate cuts. He cites several indicators of economic weakness:

• Stalled Job Growth: No job growth for approximately three months.
• Private Sector Job Losses: Latest ADP numbers point to job losses in the private sector.
• Wage Growth Stalled: Stagnation in wage increases.
• Declining Job Openings: A downward trend in available job positions.
• Weak Perceptions of Job Availability: Low confidence in job availability from surveys by the Conference Board and the University of Michigan.

Barrison concludes that the economy is struggling despite the stock market and AI booms. Without these factors, the economy would likely already be in a recession. Therefore, he believes the Fed "should be cutting rates" and expects them to do so in December.

Conclusion

The core takeaway from the discussion is a cautionary outlook on the current AI investment boom. While AI's potential for efficiency is undeniable, the ability to translate these gains into profitability for a broad range of companies remains a significant challenge. Investors are advised to be prudent, take profits, and consider reducing their exposure to highly valued tech stocks, as the risk of a significant market correction and its potential economic repercussions is substantial. The current economic indicators suggest a weakening economy that may necessitate Federal Reserve intervention through interest rate cuts.