20% Market Crash By Year-End Is Just ‘Tip Of The Iceberg’ | David Woo

Key Concepts

• US Technology Strategy: Control of technological choke points, requiring other nations to rent technology from American companies.
• Midterm Elections Incentive: President Trump's strong motivation to retain Republican majorities in Congress to avoid becoming a "lame duck" and facing legal challenges.
• Inflation and Consumer Sentiment: Declining consumer confidence, its impact on pricing power, and its correlation with layoffs.
• Tariffs and Economic Impact: The negative effects of tariffs on US companies' operating margins, leading to cost-cutting and layoffs, particularly in manufacturing sectors like automotive and furniture.
• AI Bubble: The rapid rise in AI valuations, the significant investment required, and the potential for a market crash.
• US vs. China AI Strategy: US focus on controlling technology choke points versus China's strategy of commoditizing AI and making it open-source and low-cost.
• Geopolitical Competition: The intense technology race between the US and China, with potential beneficiaries like India.
• Monetization of AI: The challenge for the tech industry in generating revenue from AI investments.
• Data Blackout: The impact of government shutdowns on the availability and interpretation of economic data.

US Technology Strategy and Geopolitical Competition

The discussion begins with the assertion that the US strategy is to control every choke point of technology. The aim is to ensure that other countries must rent technology from American companies and pay them significant fees, thereby keeping advanced technology out of the hands of rivals like China. This strategy is presented as a means to maintain American technological dominance.

This leads into a broader discussion about the US-China technology race, framed as a decisive factor in determining the outcome of the race for economic hegemony. The US approach involves controlling chip design, large language models (LLMs), and hyperscalers, with a desire to also control chip manufacturing (e.g., reviving Intel). The goal is to create a scenario where the rest of the world is dependent on US technology providers.

In contrast, China's strategy is centered on turning AI into a zero-price commodity. This is evidenced by their open-source LLMs, with three of the six best LLMs being Chinese and open-source. Furthermore, at least 20 Chinese chip companies are developing AI chips at a fraction of the cost of Nvidia's. China's philosophical stance is that AI should be accessible to everyone, and they aim to make it as cheap as possible to counter the US "stranglehold" and potentially "bankrupt the US" through this strategy.

The market, by pricing high valuations on NASDAQ, is currently pricing in a US victory. However, the speaker emphasizes that China is rapidly closing the gap. Recent announcements from Chinese companies like BU releasing AI inference chips next year, and the development of their own etching, printing, and lithographic machines, highlight their progress. The US "entity list" strategy, designed to give the US a 2-3 year lead, is now estimated to provide only a 6-month advantage. This rapid catch-up by China is identified as a major risk to the US AI bubble and potentially detrimental to the US dollar, stock market, and economy.

US Political Landscape and Economic Policy

The conversation shifts to the US political landscape, specifically President Trump's actions leading up to the midterm elections. It is argued that Trump has an overwhelming incentive to help his party retain congressional majorities because losing control of the House or Senate would transform him from a "powerful" president to a "lame duck" and expose him to significant legal challenges, including impeachment proceedings related to his alleged crypto dealings.

Trump's current actions, such as readying tariff cuts and new trade deals with countries like Argentina, Guatemala, and El Salvador, are seen as politically motivated. The speaker posits that Trump is likely to reverse some tariffs and focus on driving down gasoline prices to combat inflation, which is his weakest approval area (35%). This is to moderate inflation before the midterm elections, as historical data shows that presidents' parties typically lose seats in the midterms, and Trump's approval rating (42%) is significantly lower than that of presidents Clinton and G.W. Bush during their successful midterms.

The speaker anticipates further fiscal stimulus, specifically mentioning a potential $2,000 tariff rebate to be rolled out through a reconciliation bill, possibly in the first quarter of the next year. This is seen as a politically advantageous move, as it would be a tangible benefit directly received by citizens.

Consumer Sentiment and Economic Concerns

A significant portion of the discussion focuses on the deterioration of consumer sentiment, which has dropped to a multi-year low, a decline comparable to the start of a recession. This is attributed primarily to the impact of tariffs. While inflation data (CPI at 3%) hasn't fully reflected the tariff impact, it's argued that companies lack pricing power due to weak consumer sentiment. This has led to pressure on operating margins, forcing companies to cut costs and lay off workers.

The speaker notes that companies are using AI as an excuse to lay off workers, with layoffs year-to-date approaching one million, the highest since the dot-com era. This job insecurity, coupled with rising prices, contributes to consumer wariness. The AI bubble is also mentioned as a source of concern for many Americans.

The impact of tariffs on manufacturing is highlighted, with sectors like automotive and furniture shedding workers despite the intention of tariffs to boost domestic production. General Motors' operating margin drop from 7.2% to 2.2% is cited as an example of the negative impact on profitability, leading to layoffs. Analysis from the Center for American Progress indicates a loss of 12,000 manufacturing jobs in August alone, with 10,000 in the auto and furniture industries.

The AI Bubble and Market Dynamics

The conversation delves into the AI bubble, with the speaker expressing a bearish outlook and having personally shorted NASDAQ. The trigger for this decision was the announcement of OpenAI's partnership with Oracle, leading to a significant surge in Oracle's stock. The speaker believes that Sam Altman's strategy of announcing partnerships and promising future spending to justify a high IPO valuation for OpenAI, despite current losses, is unsustainable. The rally in NASDAQ over the past two months is attributed to OpenAI's pursuit of becoming a hyperscaler, even a competitor to its partner Microsoft, which is seen as a bearish indicator for the AI sector.

The speaker questions the monetization of AI, citing an MIT report indicating that only 5% of US companies have put AI into production, with the remaining 95% finding the technology not ready for prime time. The slow pace of AI development (e.g., the 3-year gap between GPT-4 and GPT-5.0) and the rapid depreciation of AI chips (3-year lifespan) are presented as significant challenges to the AI revenue story.

The Federal Reserve's stance on interest rates is also discussed in relation to the AI bubble. The speaker believes the Fed is concerned about the AI valuation and does not want to become an "accomplice" to the bubble. This is why Jerome Powell pushed back on expectations of a December rate cut. The correlation between the stock market and rates is noted: if the stock market rises, the Fed is less likely to cut rates, and rates will go up. The Fed's potential concern about repeating past mistakes, like not stopping the dot-com or housing bubbles, is implied.

The immense investment needed for the AI revolution is highlighted, with Morgan Stanley estimating a $1.5 trillion financing gap for global data center capital expenditures through 2028. While mainstream bond markets are a source of funding, the speaker is less concerned about the funding itself, believing the bubble will crash before reaching that point. The core issue is the inability of the tech industry to monetize AI.

Investment Strategy and Future Outlook

Regarding investment strategy, the speaker is short NASDAQ due to concerns about the AI bubble. For those looking to be long, the speaker favors India. India is seen as the biggest beneficiary of the intensifying US-China technology race. The fact that the iPhone 17 is being manufactured in India, outside of China, is presented as evidence of India's capability to produce at high quality. With a significant Indian diaspora in Silicon Valley, India is well-positioned to leverage AI and benefit from geopolitical shifts.

The speaker also touches upon the data blackout due to the government shutdown, noting that while it has ended, the ability to interpret economic data is still delayed. The job data is considered key, but the lack of October data means that November data, when released in December, will be difficult to interpret without context.

Personal Journey of David Woo

David Woo shares his personal journey, explaining his decision to leave Wall Street to start his own business. After leading a highly successful macro strategy team that won numerous awards, he felt he had achieved all he could on Wall Street. He then "retired" and moved to Israel with his wife. He now runs his own advisory business, is a professor in Israel, and enjoys his current lifestyle.