What are the hedge funds shorting?

Episode Summary

Executive Summary: The podcast episode discusses the current wobbly state of markets, focusing on the potential AI bubble. Hosts Pushkin and Katie Martin, along with guest Robin Wigglesworth (editor of FT Alphaville), examine hedge fund positioning, particularly short selling around AI-adjacent companies like Oracle and utilities. They emphasize that while hedge funds remain heavily invested in core AI stocks, they are beginning to map out short strategies for peripheral sectors, indicating early preparations for a potential correction. The conversation highlights the risks of excessive debt issuance for AI infrastructure and draws parallels to the dot-com era, where even a transformative technology led to significant losses.

Main Topics: Market Wobbliness and AI Bubble Concerns (Priority: 5/5): Markets are at high levels but feel fragile due to fears of an AI bubble. Discussions center on whether we are in a bubble and when it might burst. Hedge Fund Short Selling Strategies (Priority: 5/5): Hedge funds are cautiously shorting certain stocks, focusing on AI-adjacent companies rather than major players like Nvidia. Short interest in utilities has reached record highs. Mechanics of Short Selling (Priority: 3/5): Explanation of how short selling works, including borrowing shares and using options like puts. It highlights the risks, such as unlimited losses if the stock rises. AI-Driven Debt Issuance (Priority: 4/5): Technology companies have significantly increased debt issuance to fund AI data centers, with investment-grade tech debt up 80% this year and project finance deals rising tenfold to $125 billion. Comparison to Dot-Com Bubble (Priority: 4/5): Even if AI proves transformative, market excesses can lead to crashes, akin to the dot-com era where correct predictions still resulted in massive losses. Michael Burry and Short Selling Difficulties (Priority: 3/5): Michael Burry, famous for betting against housing in 2008, exemplifies how hard short selling is, having closed his hedge fund after unsuccessful short bets on Nvidia and Palantir.

Key Arguments: Markets feel fragile at current highs, with AI bubble fears dominating sentiment. Hedge funds are nibbling around the edges of AI (e.g., Oracle, utilities) rather than shorting core AI stocks like Nvidia. Short interest in US utilities is at a record high since 1995, driven by concerns over AI data center power demands. Record tech debt issuance for AI infrastructure could lead to overinvestment and future distress if AI demand fails to meet expectations. Even if AI is transformative, market mania can still cause severe corrections, as seen in the dot-com crash. Hedge funds, while individually smart, tend to move as a herd and are not reliable for timing market turns. Michael Burry's struggles highlight the difficulty of shorting rising markets, even for famous investors.

Data Points: Short interest in S&P 500: 2.4% of overall value - Current level is high relative to past five years and above the average since 1995. Increase in tech investment-grade debt issuance: 80% year-over-year - UBS note on the surge in debt from technology companies. AI data center project finance deals: $125 billion - Estimated tenfold increase this year. Record short interest in US utilities: Highest since 1995 - Driven by AI-related investments in power infrastructure. Bloom Energy valuation vs. earnings: $30 billion market cap vs. ~$100 million forecast profit - Highly shorted stock due to AI frenzy.

Pivotal Quotes: "The reality is that hedge funds, at least the smart ones, don't want to bet against a bubble whilst it's still inflating. You don't get run over. You wait until it actually is already collapsing and then you pounce on it, essentially." — Robin Wigglesworth: Explaining why hedge funds are not yet heavily shorting core AI stocks despite concerns. "Even if you believe that it is transformational, even if it does prove transformational, crisis can still be stupid. And people forget that dot-com, everything was right. Everything that people said in 1999 was completely right. But people still lost an ungodly amount of money in the years that came afterwards." — Pushkin: Highlighting that even transformative technologies can lead to market crashes. "There's a reason why we're financial journalists and not bazillionaires sitting on a Caribbean island by ourselves counting our massive stacks of money." — Robin Wigglesworth: Joking about the difficulty of predicting market crashes despite their skepticism.

Implications: Listeners should expect continued volatility in AI-related stocks, with potential corrections in peripheral sectors like utilities. The record debt issuance signals overinvestment risk, but timing remains uncertain. For investors, monitoring hedge fund short positions in AI-adjacent companies could provide early warning signs of a broader downturn.