The Next Michael Burry (EP. 480)

Episode Summary

Executive Summary: The episode is a wide-ranging market discussion centered on whether the AI investment boom is a bubble or a durable growth engine. The hosts argue that the outcome may be messy and non-binary, with AI potentially boosting productivity, margins, and bonds even if some excesses unwind. They also cover Fed policy, software-stock volatility, asset-management M&A, consumer resilience, housing, youth sports, and entertainment recommendations.

Main Topics: AI capex boom and bubble debate (Priority: 5/5): The hosts dissect Barron’s/New York Times coverage of AI-related debt and capital spending, arguing the story is likely to remain central for years and may not end in a simple crash-or-bust outcome. Fed and macro uncertainty (Priority: 4/5): They react to Kevin Warsh’s Jackson Hole remarks, focusing on the Fed’s uncertainty about forecasting and how AI may affect productivity and policy. Market rotation and software-stock volatility (Priority: 4/5): They discuss the sharp drawdown and rebound in software stocks, using it as evidence that disruption can create violent but ultimately uncertain market paths. Bonds, yields, and macro normalization (Priority: 4/5): They argue higher bond yields may be rational given growth, deficits, and nominal spending, and that rising yields are not necessarily a crisis signal. Consumer, housing, and generational trends (Priority: 3/5): They cover consumer resilience, buy-now-pay-later delinquency data, housing affordability, and Gen Z homeownership trends, suggesting some fears may be overstated. Bull-market behavior in wealth/asset management (Priority: 3/5): They note a wave of acquisitions across custodians and asset managers as a sign of late-cycle confidence and scale-seeking behavior. Pop culture and personal life tangents (Priority: 2/5): They close with TV/movie recommendations, sports parenting, and humorous personal anecdotes that provide levity and audience connection.

Key Arguments: AI could be a multi-year, non-linear force that reshapes markets without producing an immediate collapse. The market is too eager to force AI into a binary outcome: either a historic productivity boom or the biggest crash ever. If AI succeeds, it may be deflationary and bond-positive; if it fails, growth slows and bonds may still rally. Software stocks show that even severe disruption can produce round-trips and violent rebounds rather than clean trends. Higher bond yields may reflect healthy nominal growth and confidence that the “lost decades” are over. The U.S. economy remains resilient despite housing weakness, mixed sentiment data, and worries about consumer strain. AI’s real employment impact still appears modest in the near term, so many dramatic claims may be premature. Asset-management M&A and rising margins in the S&P 493 suggest that a broad market beyond the Mag 7 is participating in earnings growth. Young people’s homeownership rates may look low now, but historical life-cycle patterns suggest improvement is likely later. Negative survey results and fear-based headlines often reflect biased framing more than objective deterioration.

Data Points: AI company debt raised in 2024: $217 billion - Reported in the discussion of Barron’s and NYT coverage of the AI capex/debt boom. AI company debt by mid-August: Nearly $450 billion - Cited as the pace of AI-related borrowing accelerating in the current year. Projected AI company debt in 2026: About $600 billion - Used to illustrate the scale of future financing needs for AI infrastructure. Projected future AI capex share of GDP: Roughly 3% of GDP from 2027 to 2029 - Mentioned as an unprecedented level of planned investment. Projected annual AI capex: Almost $1 trillion per year - Back-of-the-envelope estimate from the hosts based on future spending plans. Software ETF drawdown: Almost 40% off highs - Used to show the severity of software-stock volatility before recovery. IGV recovery from lows: About 40% off the lows and within 7% of highs - Shows the sharp rebound in software stocks after the selloff. S&P 500 dividend yield: 98 basis points - Described as a record-low or near-record-low dividend yield due to tech dominance. Korea single-stock leveraged ETF turnover: Nearly $50 billion at peak, then basically zero - Illustrates how quickly retail mania can collapse under regulatory tightening. Guaranteed real return scenario: 7% annual real return - Used in a thought experiment about whether investors would accept market-like returns if guaranteed. Gen Z homeownership rate: Less than 30% - Cited in a Redfin chart comparing generations’ homeownership rates. Millennial homeownership rate: 55% - Used to compare generational progress in housing ownership. Gen X homeownership rate: 73% - Part of the generational homeownership comparison. Baby boomer homeownership rate: Around 80% - Used as the highest ownership cohort in the generational chart. Housing mortgage rate: 6.8% on the 30-year fixed - Mentioned as mortgage rates approached 7% again. AI employment impact in census survey: 2.3% increased employment, 2% decreased, 96% no change - A census-based survey of firms suggesting AI’s near-term labor impact remains limited. SP 500 493 net margin: 13.6% - Chart showing margin expansion for the non-Mag 7 constituents. SP 500 493 net margin in 2024: Less than 12% - Baseline for the margin expansion discussion. Projected SP 500 493 net margin by Q4 2027: Almost 15% - Used to argue that broader market earnings may be improving.

Pivotal Quotes: "This will be bigger than anybody thinks for longer than anybody thinks." — Ben Reitz: Quoted from Barron’s discussion of the AI capex/debt cycle. "If AI succeeds, rates will be lower. If AI fails, rates will be lower." — Torsten Slok: Referenced as a bond-bullish framing of both AI success and failure scenarios. "We’re team middle. We’re team gray." — Michael and Ben: Their shared stance that AI likely won’t end in either extreme euphoria or collapse.

Implications: Listeners should expect AI, rates, and market rotation to remain dominant themes. The episode argues for humility: outcomes may be messy, slower-moving, and less binary than headlines suggest.