How Leverage Turned An AI Boom Into A Crash

SUMMARY

Scott Galloway and Ed Elson analyze the dramatic impact of single-stock leveraged ETFs on the South Korean stock market, highlighting the dangers of excessive leverage for retail investors. They also review recent earnings from Microsoft, Amazon, Meta, and Apple, exploring how the AI boom is complicating valuations and investor sentiment in Big Tech.

MAIN POINTS

• Discussion shifts from cultural trends to the recent extreme volatility in the South Korean stock market, driven by leveraged ETFs tied to major chipmakers. [5:00]
• The hosts detail the human and financial toll of the crash, noting that 3.4% of South Korea's adult population received margin calls and the government responded with debt counseling hotlines. [11:01]
• Retail investors in South Korea have lost $39 billion, with 70% of investors in key chip stocks now in the red, prompting public protests and regulatory intervention. [18:00]
• Regulators in South Korea halt new listings of single-stock leveraged ETFs, acknowledging the products' dangers and the need for greater investor protection. [21:01]
• The conversation explores the link between South Korea's loneliness crisis, declining marriage and fertility rates, and the surge in risky financial behavior among young people. [28:02]
• The hosts warn that the rise of leveraged ETFs in the U.S. mirrors South Korea's trajectory, with assets under management jumping 70% in a few months. [32:03]
• Attention turns to Big Tech earnings, with Microsoft and Amazon rewarded by investors for strong AI-driven results, while Meta and Apple face declines. [39:00]
• Apple's supply chain challenges and record iPhone sales are discussed, along with the massive capital expenditures by Alphabet, Amazon, Meta, and Apple. [43:01]
• The hosts highlight how private investments in AI companies like Anthropic and OpenAI are distorting Big Tech's earnings and valuation metrics. [47:02]
• Microsoft's advantage in enterprise AI adoption is examined, emphasizing the importance of mass adoption over having the best model. [52:01]
• Concerns are raised about Big Tech's aggressive capital spending on AI, with questions about the sustainability and return on these investments. [56:02]
• The discussion analyzes how Big Tech valuations have shifted since the AI boom, with Apple trading at a significant premium for staying out of the AI race. [1:05:02]
• Apple's enduring strength is attributed to its dominance among affluent consumers and the aspirational value of the iPhone, despite questions about future growth. [1:10:01]
• Predictions are made about upcoming forced sales due to leverage in AI stocks and the likelihood of further volatility in the markets. [1:19:02]
• The episode concludes with personal investment reflections and a prediction that Meta's stock has likely bottomed after recent declines. [1:20:01]

DETAILED ANALYSIS

The episode opens with a vivid account of the fallout from South Korea's stock market crash, where retail investors have suffered staggering losses—$39 billion to date—largely due to the proliferation of single-stock leveraged ETFs. These financial products, which allow investors to amplify gains and losses by borrowing to increase exposure to individual stocks, became wildly popular during the AI-driven rally in South Korean chipmakers SK Hynix and Samsung. When sentiment around AI shifted and SK Hynix reported disappointing earnings, the resulting selloff was catastrophic.

Samsung fell 32%, SK Hynix 40%, and the broader KOSPI index entered a bear market, marking the worst downturn since the 2008 financial crisis.

The hosts emphasize that the devastation was concentrated among retail investors, who make up 92% of participants in these leveraged ETFs. With two brokerage accounts for every citizen and 3.4% of the adult population receiving margin calls, the crisis became a national emergency. The psychological and social impact is underscored by the imagery of funeral wreaths placed outside the National Assembly in Seoul, accompanied by calls to abolish leveraged ETFs.

Regulators responded by halting new listings of these products and publicly acknowledging the regulatory failures that allowed such risky instruments to proliferate.

The conversation situates the South Korean experience within a broader pattern of financial manias fueled by leverage. The hosts draw parallels to U.S. examples, such as Michael Saylor's leveraged Bitcoin bets, Cathie Wood's aggressive positions in Tesla, Bill Hwang's collapse, and the infamous downfall of Long-Term Capital Management. They argue that leverage is often mistaken for intelligence during bull markets, but it exposes investors to catastrophic losses when markets turn.

The story of Leopold Aschenbrenner, a hedge fund manager who achieved viral fame and extraordinary returns by leveraging into AI stocks before being forced to liquidate, serves as a cautionary tale. His entire portfolio, including stakes in SK Hynix and shorts like Adobe, was sold off to Citadel's Ken Griffin, illustrating how sophisticated buyers can profit from the distress of forced sellers.

The hosts advocate for a more nuanced understanding of leverage, likening it to prescription drugs: beneficial in moderation but potentially ruinous in excess. They call for greater financial education, suggesting that concepts like leverage, margin, and forced selling should be taught in high school and college. The South Korean episode is presented as a warning for the U.S., where assets under management in leveraged ETFs have surged from $120 billion to over $200 billion in a matter of months, and more than half of these are single-stock products.

Regulatory responses are debated, with the hosts weighing the balance between protecting retail investors and avoiding paternalism. They note that financial innovation often outpaces regulation, with new products like perpetual futures and DeFi yield farming offering even higher leverage and risk. The marketing of these instruments often blurs the line between investing and gambling, and the lack of clear disclosure or education leaves many retail participants vulnerable to losses they do not fully understand.

A sociological dimension is introduced as the discussion explores the links between South Korea's demographic challenges—declining marriage and fertility rates, and a pervasive loneliness crisis—and the rise of speculative financial behavior. The argument is made that financial nihilism among young people, who see little hope of achieving traditional milestones like homeownership or stable relationships through conventional means, drives them to seek outsized returns through risky bets. This phenomenon, the hosts suggest, is beginning to take hold in the U.S. as well.

Attention then shifts to Big Tech earnings, where Microsoft and Amazon are lauded for delivering strong results tied to AI initiatives. Microsoft's revenue rose 18% and net income 31%, with cloud revenue up 43% and over 30 million paid seats for Copilot. Amazon's AWS division also posted impressive growth.

In contrast, Meta and Apple saw their shares fall after earnings. Meta's free cash flow plunged 91%, and the lack of a clear monetization path for its AI investments led to investor skepticism. Apple's record iPhone sales were offset by supply chain issues and rising memory costs, highlighting new vulnerabilities for a company long celebrated for its operational excellence.

A critical issue identified is the distortion of earnings and valuation metrics by Big Tech's private investments in AI companies like Anthropic and OpenAI. For Amazon and Alphabet, the majority of net income in recent quarters has come not from core operations but from mark-to-market gains on these stakes. This inflates price-to-earnings (PE) ratios and can mislead investors about the true profitability of these firms.

Adjusted for these gains, Amazon's PE multiple jumps from 19 to 30, and Google's from 19 to 31, revealing that these stocks are not as cheap as headline numbers suggest.

The hosts argue that traditional valuation metrics are becoming less reliable as the AI boom introduces new forms of financial engineering and uncertainty. They call for analysts to develop 'venture-adjusted' earnings metrics that strip out the effects of private investment gains. The sustainability of current capital expenditures is questioned, especially as free cash flow turns negative for Amazon and Google, and Meta faces skepticism over its massive AI infrastructure spending.

The risk is that these investments may not yield the expected returns, but the companies' dominant market positions and cash-generating capabilities provide a cushion against failure.

Microsoft's success in enterprise AI is attributed not to having the best model, but to its ability to drive mass adoption through its existing relationships and integration with enterprise workflows. The hosts note that the installed base and trust in Microsoft give it a significant advantage, even if its AI offerings are not technically superior. Meanwhile, Apple is praised for its discipline in staying out of the AI spending race, with the iPhone remaining the most profitable and aspirational hardware product globally.

The company's growth prospects are debated, with one host arguing that Apple's premium positioning and dominance among affluent consumers will continue to drive revenue as more people enter the global middle class, while the other questions whether this is sufficient to justify its elevated valuation.

The episode concludes with predictions about further forced sales and volatility in AI-related stocks due to excessive leverage, and reflections on personal investment decisions. The hosts agree that leverage is not a strategy but a source of risk, and that the lessons of South Korea's crisis and the current dynamics in Big Tech should serve as a warning for investors and regulators alike.

LINKS

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