Owen Lamont on Bubble Fever, Index Gripers & Inefficient Markets | #552

Episode Summary

Executive Summary: Meb Faber and Owen Lamont explore whether U.S. stocks are entering bubble territory, arguing that valuations are elevated but classic bubble signals like heavy issuance and a flood of new investors are still incomplete. They also discuss retail gamification, short selling’s decline, Korea-like speculative behavior, AI’s genuine long-term promise, and why passive investing and free financial data remain important.

Main Topics: Are U.S. stocks in a bubble? (Priority: 5/5): Lamont says valuations are high and bubble beliefs are rising, but the absence of major issuance and IPO mania means the market is not yet fully in bubble territory. Four horsemen of bubbles (Priority: 5/5): The conversation centers on Lamont’s framework: valuation, beliefs, issuance, and retail participation. He sees the first two present, but not the latter two at extreme levels. Retail gamification and speculative behavior (Priority: 4/5): They discuss Robinhood, zero-day options, sports betting, crypto, and how modern gambling-like behavior may be shifting speculation from markets into other venues—or vice versa. Short selling and market efficiency (Priority: 5/5): Lamont argues short sellers are widely misunderstood, increasingly constrained, and essential for fraud detection and price discovery, with declining shorting reducing market efficiency. Korea, meme stocks, and distorted markets (Priority: 4/5): Korea is used as a template for what extreme retail speculation can look like, including theme stocks, banned short selling, and stock prices disconnected from fundamentals. AI, machine learning, and real economic change (Priority: 4/5): Unlike crypto or the metaverse, Lamont views AI as a major, durable economic transformation comparable to or bigger than the internet, and machine learning as essential for quants. Indexing, free data, and long-term investing (Priority: 3/5): Lamont defends broad passive investing, highlights the value of open data from scholars like Schiller, Fama, French, and Ritter, and notes that free resources help democratize rigorous investing.

Key Arguments: U.S. equity valuations are elevated, but valuation alone does not define a bubble; issuance and retail frenzy are also required. Bubble beliefs are increasing, as shown by long-running Yale survey data, but current levels are still below the most extreme historical peaks of 1999 and 2021. A lack of IPOs/SEOs suggests companies do not yet see prices as sufficiently inflated to justify issuing equity aggressively. Retail speculation has migrated into newer channels such as Robinhood, options, crypto, and sports betting, making the boundary between investing and gambling blurrier. Short sellers are often vilified, but they historically help expose fraud and keep markets efficient; restrictions on shorting make mispricing harder to correct. Korea demonstrates how retail-dominated, short-selling-restricted markets can develop recurring “theme stock” manias disconnected from cash flows. AI is a genuine technological shift, while machine learning is already a baseline tool for modern systematic investing. Broad market-cap-weighted indexing remains underused relative to active management, in Lamont’s view, and is often unfairly criticized by active managers. Open, high-quality data sources are crucial to finance research and investor education. Closed-end funds and meme-like vehicles can reach absurd premiums when shorting is difficult and investor enthusiasm is intense.

Data Points: U.S. stock market return since 2009: near a 10-bagger - Faber cites the extraordinary compounding of U.S. stocks over the past 15 years. Cropland lost to urbanization (1997-2022): approximately 4.8 acres per minute - Used in the farmland sponsor read to frame farmland as a scarce real asset. Yale survey overvaluation reading: about 43% average say market is overvalued - Lamont discusses the long-running Yale sentiment/confidence survey. Yale survey peak readings: 70% in April 2000 and June 2021 - Historical highs in perceived overvaluation from the Yale survey. Yale survey low reading: 18% in May 2009 - Depression-era level of pessimism after the financial crisis. Short borrowing cost example: 1% per day on a $100 stock - Lamont explains how short borrow fees can annualize above 100%. Extreme short borrowing cost: over 1,000% annualized - Lamont notes some stocks/ETFs can become extraordinarily expensive to short. Retail trading losses in Taiwan: around 1% of GDP - Lamont references research showing retail investors lose heavily in Taiwan. DXYZ closed-end fund premium: about 2,000% - Used as an example of extreme closed-end fund overvaluation. Parlay share of FanDuel bets: 70% - Lamont guesses and Faber confirms a very high percentage of bets are parlays. 2021 stock-market-related mania: huge wave of IPOs, especially SPACs - Lamont argues 2021 was a real bubble-like episode that deserves more academic attention. Chinese stock market weekly move: up 25% in a week - Faber mentions a recent dramatic move as a reason to watch China closely.

Pivotal Quotes: "My definition of a bubble is it's when everyone knows, or many people believe the market's too high, but they're buying anyway." — Owen Lamont: Lamont defines bubble behavior beyond valuation alone. "Short sellers are an endangered species in the United States and elsewhere." — Owen Lamont: He explains how higher costs and stigma are reducing market efficiency. "AI as a general economic, business, commercial application is going to be at least as important as the internet was." — Owen Lamont: Lamont distinguishes AI from speculative fads like crypto and the metaverse.

Implications: Investors should watch not just valuations but issuance, retail activity, and sentiment. The episode argues for broad indexing, skepticism toward gamified speculation, and caution that fewer short sellers may weaken price discovery.