The Bubble Most Will Get Wrong | Aswath Damodaran on How He Is Investing in a World of AI

Video Description

In this episode of Excess Returns, Professor Aswath Damodaran joins Matt Zeigler and Kai Wu for a wide-ranging conversation on valuation, portfolio construction, and how investors should think about risk, discipline, and opportunity in a market shaped by AI, market concentration, and rising uncertainty. Damodaran walks through how he builds and manages his own portfolio, why price matters more than story or quality, and how AI-driven capital spending could reshape margins and returns across the economy. The discussion blends practical investing frameworks with big-picture market insights, offering a clear look at how a valuation-driven investor navigates today’s environment. Main topics covered • How Aswath Damodaran builds a stock portfolio, including diversification, position sizing, and turnover • Why investing is about buying at the right price, not buying great companies • Using valuation frameworks to invest in young, unprofitable, and fast-growing companies • How stories and narratives fit into valuation without replacing financial discipline • Watchlists, patience, and waiting for price rather than chasing popular stocks • Sell discipline, overvaluation triggers, and avoiding emotional attachment to winners • Using probability distributions and simulations instead of single-point estimates • How company lifecycles affect growth, margins, and capital allocation decisions • Why many companies struggle as they age and how management quality shows up late in the lifecycle • AI as a capital cycle and why massive AI investment may lower margins overall • Why AI is likely to create a bubble, even if it delivers long-term economic value • Winners and losers in the AI value chain, from infrastructure to applications • Risks from AI infrastructure spending, debt, and cross-ownership structures • Why private markets may not deliver better outcomes for individual investors • How Damodaran thinks about cash, diversification, and assets uncorrelated with equities • Reentering markets after selling and avoiding the trap of staying in cash too long • Time horizon, legacy investing, and managing wealth across generations More Videos About Long-Term Compounding and Finding Great Stocks https://www.youtube.com/playlist?list=PLOPDD0ChIJDjbUOxtjHodSXCu7iq4ViqI Timestamps 00:00 Investing is about price, valuation, and early thoughts on AI and market risk 01:54 Personal investing philosophy and why portfolios must be investor-specific 03:00 Diversification, number of holdings, and managing downside risk 05:00 Valuation frameworks and buying companies at the right price 06:00 Stories versus numbers and avoiding the circle of competence trap 08:20 Political risk and why some sectors are hard to value 08:47 Watchlists, patience, and waiting for price to meet value 11:43 When and why to sell stocks as a value investor 12:00 Using probability distributions and simulations in valuation 15:48 Sell discipline, fund flows, and separating skill from luck 18:00 Company lifecycles, aging businesses, and management discipline 23:18 Apple, Meta, and contrasting approaches to AI investment 24:08 AI bubbles, winner-take-all dynamics, and capital cycles 27:48 Infrastructure investing, debt risk, and societal spillovers 32:20 Cross-ownership risks and AI ecosystem fragility 35:00 AI’s impact on profit margins and competition 39:41 Where AI value may accrue over time 44:38 AI tools, valuation bots, and the rise of investment scams 49:17 Private markets, alternatives, and cost structures 53:05 Cash, collectibles, and diversification beyond equities 56:33 Reentering markets after selling and avoiding market timing traps 58:35 Time horizon, legacy investing, and generational wealth