It's not 1929, but it might be - Andrew Ross Sorkin | TCAF 224

Key Concepts

• Historical market comparisons (1929, 1999) are imperfect but offer valuable lessons regarding leverage, policy, and speculative bubbles.
• Current market valuations, particularly in private markets (AI startups), raise concerns about potential corrections, though a systemic crisis is not necessarily anticipated.
• A healthy bull market often corrects itself by “taking out the trash” – allowing weaker investments to decline without triggering a broad market crash.
• Investor sentiment appears muted despite the current bull run, suggesting a lack of widespread exuberance.
• The importance of thorough research, pattern recognition, and attentive listening in financial journalism and analysis.

Historical Context & Market Parallels

The conversation extensively draws parallels between current market conditions and historical events, specifically the crashes of 1929 and 1999. While acknowledging the allure of pattern recognition – humans have an evolutionary advantage in identifying patterns – the speaker cautions against simplistic comparisons. 1929 is deemed a less direct analogue than 1999 due to the existence of modern safeguards like the SEC, FDIC insurance, and capital requirements. However, 1929 wasn’t solely a market event, but the initial trigger for a series of cascading failures, exacerbated by poor policy choices. A key difference highlighted is the significantly higher leverage in 1929 (10:1 margin calls) compared to today. The 1999 tech bubble, with its pre-revenue companies, is considered a more relevant comparison, though even that isn’t perfect, as current AI companies do generate revenue. A 99% decline in the NASDAQ today would be comparable to the 1929 crash, given the current size of leading companies.

Current Market Valuations & Private Market Risks

A central concern revolves around valuations, particularly in the private market. OpenAI’s $500 billion valuation is questioned, with the potential for a significant drawdown if it were publicly traded, potentially exceeding Oracle’s recent 45% decline. The risks within the private market ecosystem are emphasized, citing examples like LM Marina, an AI evaluation startup valued at $1.7 billion, and the collective risk posed by numerous similar companies. The anticipation of tokenizing private equity and venture capital is discussed, predicting a 20-30% “haircut” upon price discovery, which is viewed as a healthy market correction. A recent example of valuation correction was a private equity firm’s merger with a public entity, resulting in a 70-cent-on-the-dollar valuation plummet.

Bull Market Dynamics & Investor Sentiment

The speaker posits that a healthy bull market doesn’t necessarily require a broad market selloff, but rather “takes out its own trash” – allowing weaker companies to experience drawdowns without dragging down the entire market. Coreweave’s 50% decline and the volatile trajectory of Circle’s IPO are cited as examples. The market is believed to have already undergone a correction in 2022, with Nvidia (down 35%) and Meta (down 70%) experiencing substantial declines. Anecdotal evidence suggests a lack of widespread retail investor enthusiasm despite the bull market, with a scarcity of stock inquiries, contrasting with the fervor surrounding Nvidia in 2021.

SPACs & Historical Lessons

The evolution of Special Purpose Acquisition Companies (SPACs) is examined. Initially offering a $10 downside guarantee, the celebrity-driven SPAC boom proved unsustainable. The speaker recounts advising clients in the mid-2000s that many SPACs would fail, but the $10 downside provided a buffer. The irony lies in the SPAC itself being the best part of the investment, with risk materializing after the conversion to an operating company.

The Art of Interviewing & Research

The conversation shifts to the interviewer’s approach, emphasizing the importance of curiosity, neutral questioning, and attentive listening. The speaker highlights the value of observing the interviewee’s physical reactions as often more revealing than repeated questioning. Interview preparation is described as planning a flight path with potential diversions, acknowledging the unpredictable nature of conversation. The speaker credits David Stern with teaching the importance of listening early in their career.

Technical Considerations & Data Points

Several technical terms were discussed, including drawdown, Cape Ratio, leverage, margin calls, tokenization, multiple contraction, and capex cycles. Specific data points included the NASDAQ’s 85% decline from 1999-2000, OpenAI’s $500 billion valuation, LM Marina’s $1.7 billion valuation, Nvidia’s 35% decline in 2022, Meta’s 70% decline in 2022, Coreweave’s 50% decline, and the approximately 1,000 IPOs on the NASDAQ and NYSE in 2020-2021.

Conclusion:

The discussion paints a nuanced picture of the current market, acknowledging the enthusiasm surrounding AI while simultaneously highlighting potential risks, particularly in private valuations. The emphasis on historical parallels, combined with a pragmatic assessment of current conditions, suggests a cautious optimism. The speaker’s perspective emphasizes that while excesses exist, a systemic crisis isn’t necessarily imminent, and a healthy bull market often self-corrects through the decline of weaker investments. Ultimately, the conversation underscores the importance of diligent research, critical thinking, and a healthy skepticism when navigating the complexities of the financial landscape.