Excess Returns Podcast
Episode: The Bubble Most Will Get Wrong | Aswath Damodaran on How He is Managing His Own Money in a World of AI
Date: January 16, 2026
Guests: Jack Forehand, Justin Carbonneau, Matt Zeigler (Hosts), Aswath Damodaran (Guest)
Co-Host: Kai Wu

Episode Overview

In this episode, the hosts of Excess Returns sit down with renowned valuation expert Professor Aswath Damodaran for a candid, wide-ranging discussion about how he is personally managing his investments amid the AI boom, potential market bubbles, the realities of diversification, company life cycles, and the evolving risks of cross-ownership in tech. Damodaran shares his highly personal, story-driven investment approach, how he evaluates when to buy and sell, why he’s wary about current market pricing, and his nuanced views on private markets, collectibles, and asset correlation in today’s environment.

Key Discussion Points & Insights

Damodaran’s Investment Philosophy & Portfolio Construction

• Person-Specific Investing (01:54)
  Damodaran stresses that investing is deeply personal and what works for one person may not suit another:

  “[I]nvesting is very person specific. What works for me will not work for you. So ... rather than trying to replicate what I do, you got to look inward and say what makes me comfortable, what is right for me.”
  (A, 01:54)

• Diversification & Conviction (03:00)
  He prefers broad diversification (30–45 stocks), especially since he includes young, potentially riskier companies:

  “I don't have enough confidence, no matter how much work I put into an investment, to put my money in five stocks or four stocks because I think too much rides on it. So I spread my bets to ... about 30 to 40 stocks.”
  (A, 03:37)

• Valuation and Story Over Product Knowledge (06:16)
  Damodaran focuses on stories and undervaluation, not deep product understanding:

  “I don't have to completely understand a product, but I have to understand the business. ... I bought Nvidia in 2018. If you make this about ‘I need to know what a product is’, you're going to end up in the Buffet trap.”
  (A, 06:34)

• Avoiding Politically-Driven Businesses (07:23)
  He avoids companies where value is driven more by politics than business fundamentals, such as those in heavily subsidized sectors or dependent on government connections.

  "There's a subset of companies I avoid. That subset includes companies where I have to forecast who will win the next election to decide whether to buy a stock. And I don't want to be in that space."
  (A, 07:55)

Managing Watchlists & Opportunity Selection

• The Role of “Watchlists” (08:21)
  Damodaran maintains an active watchlist of companies with great stories he admires, tracking them until market prices become attractive. Examples include Mercado Libre and Palantir.

  “If you find a company that you find fascinating, ... even if it's overpriced today, don't just let it go, keep it ... on your radar, track it, follow it.”
  (A, 09:36)

• Tesla Case Study (11:43)

  “With Tesla ... I like the company, I like the product, I like the way it's approaching the market, but I don't like the price. Then in 2019 ... the stock price collapsed, it got to a point where ... it's at the right price.”
  (A, 11:43)

Sell Discipline & Behavioral Traps

• Why Sell Discipline Matters (12:46)
  Damodaran critiques “buy and forget” investing and discusses using Monte Carlo simulations to determine both buy and sell points based on value distributions:

  “If you buy when something is undervalued, the flip side ... is you [should sell] if it's overvalued. ... I run [Monte Carlo] simulations. The advantage ... is I have a distribution of value ... gives me a margin of safety on both sides.”
  (A, 12:46, 13:24)

• Emotional Difficulties in Selling (15:00)

  “The stocks that you fall in love with ... it's really, really, really difficult, even when they get overvalued, to let them go.”
  (A, 15:11)

• Automating Re-entry Decisions (57:17)
  On avoiding the trap of never reinvesting after successfully timing a market top:

  “Put it on autopilot. ... Pre-commit ... to take a quarter of this money and invest every six months for the next two years ... you got to get that money working for you again because you can't leave it in cash.”
  (A, 57:48)

The Company Lifecycle Framework

• Staging the Corporate Lifecycle (19:08)
  Damodaran uses financial metrics to gauge where a company is in its lifecycle—growth, maturity, aging—and looks for management teams that “act their age”:

  “If you're a middle-aged company that ... keeps trying to squeeze yourself into tight jeans ... you're going to take my money and try to be young again. ... I want to invest in companies that act their age.”
  (A, 22:48)

• Acquisitions as a Red Flag (19:50)

  “One of my signals ... to take a closer look at a growth company is when they start to do a lot of acquisitions.”
  (A, 19:50)

• Apple vs. Meta AI Strategy (24:02)
  Praises Tim Cook’s discipline at Apple for not chasing growth via large AI investments, in contrast to Meta’s aggressive CapEx.

  “You can be a great company and not be a growth company going out after new business and throwing tens of billions. That's a sign of recognizing your age and acting your age.”
  (A, 22:11)

AI, Bubbles, and the Coming Capital Cycle

• Is AI Creating a Bubble? (24:52)
  Damodaran argues that any major technological change inevitably creates bubbles:

  “Any major change in the way we live and work is going to create a bubble. ... I would expect AI to create a bubble because it is changing the way we live and work.”
  (A, 24:52)

• Winner-Take-All and Net Present Value (25:50)

  “There will be one or two players who make those investments. ... but collectively ... the collective investment is going to have a negative net present value. ... That's the nature of bubbles, we overreach.”
  (A, 25:50)

• What Drives Returns in Tech Bubbles (26:57)

  “It’s difficult to predict who the big winner from a bubble is going to be early on. ... If you can do it, you’re going to make a huge amount of money. ... But I think it's too early to anoint Nvidia and Microsoft and Meta as the winners, as some people are.”
  (A, 27:20)

The Capital Intensity Shift in Tech & Infrastructure Risk

• From Asset-Light to Capital-Intensive (29:12)
  Modern tech companies investing in AI infrastructure are moving closer to utility-like, capital-intensive models:

  “With AI, you’re putting this on steroids. You’re building infrastructure into what’s definitely not going to be a monopoly.”
  (A, 29:27)

• Borrowing for AI Infrastructure is a Red Flag (32:38)

  “Those AI infrastructure companies that are borrowing money, I think are making a bad choice ... You don't borrow money to build infrastructure into a risky business.”
  (A, 32:47)

• Cross-Ownership Risk (33:39)
  New cross-ownership structures in US tech create entanglement risk:

  “You're creating this circle of companies all connected to each other and one of them makes a big enough mistake ... you can make a big enough mistake as a single entity to start dragging other players into the game.”
  (A, 34:09)

AI’s Economic Impact – Profit Margins, Value Chains, and Winners

• AI’s Impact on Margins (36:01)
  Damodaran’s contrarian prediction:

  “Overall, I think AI is going to lower profit margins collectively across companies. ... If everybody's spending on it, they're all getting the same crap.”
  (A, 36:02; 37:02)

• Who Benefits in the Value Chain? (40:25)

  “In the first phase, the architecture builders benefit ... But there will be a point where you're going to see product and service companies which deliver value. ... They're going to be more likely to be B2B companies rather than B2C.”
  (A, 40:25; 41:36)

• Historical Infrastructure Parallels (38:06 & 40:25)
  Notes that infrastructure builders (railroads, fiber, telecoms) rarely make the most money in the end:

  “The folks... actually building the future ... were the ones who made no money. ... Most of the railroads went bust. Many telcos did too. ... It was the Netflix and Metas of the world that came out later to enjoy the subsidized bandwidth...”
  (C, 38:06)

Private Markets, Correlation, and Asset Allocation

• Skepticism on Private Equity and VC (50:38)
  Damodaran is dubious about the private market’s supposed diversification benefits and return promises:

  “The only reason [VC returns] don't look close to one [with public markets] is because of ... lagged effect … I don't think anything good can come from individual investors being invited into private equity and the VC space.”
  (A, 50:51)

• Changing Nature of IPOs (52:22)
  Late-stage IPOs are much larger but often financially less mature than in the past:

  “Companies are less formed as businesses when they go public, which is strange because you think they're bigger companies.”
  (A, 53:09)

• Asset Correlation and Collectibles (54:02)
  He’s increasingly wary about finding non-equity-correlated assets, noting that even real estate and global equities now act like stocks. He includes gold and collectibles as possible diversifiers:

  “We've created asset classes that used to be separate asset classes that are now starting to behave like equities. ... But I think that this might be a time where if you cash out on a stock, some of that money should find its way into things that are. And that remains one of the few spaces which is relatively uncorrelated with equities.”
  (A, 55:15)

• Caution on Market Timing (56:41, 57:17)
  He doesn't advocate for selling out large portions of one’s portfolio—too hard to reenter successfully:

  “Even if you're right about the correction ... The problem you're going to face is you're now sitting on a mountain load ... of all cash. ... You can't leave it in cash because it'll stay in cash for much longer.”
  (A, 57:18)

Intergenerational Wealth & Time Horizons

• Shifting Time Horizons (59:18)

  “As you get to a certain age, you're not investing for yourself, you're investing for the next generation. ... your time horizon is not your life, it's what your investment is designed to do.”
  (A, 59:36)

Notable Quotes & Memorable Moments

• On “The Only Investing Rule”

  “Investing is about buying something at the right price. It's not about buying great companies, it's not about buying superior management. It's about buying at the right price.”
  (A, 00:00; 04:25)

• On the Nature of Tech Bubbles

  “Do you want to live in a world run by actuaries? We'd still be in caves … There's very little risk that's really worth taking.”
  (A, 24:56)

• On AI’s True Impact

  “If everybody's getting it, nobody's getting it. ... By spending this much, we will essentially weaponize the process where you have to spend to keep up with everybody else.”
  (A, 36:01)

• Data Abundance vs. Better Outcomes

  “We have more resources as investors than ever before in history ... But collectively, as investors, we're doing worse than we used to. ... we're being drowned by disinformation as much as information.”
  (A, 49:20)

Timestamps of Key Segments

• 01:54 – Damodaran’s personalized approach to portfolio construction
• 03:37 – Why he chooses broad diversification
• 06:34 – Valuation via “stories” and why product expertise isn’t required
• 07:55 – Avoiding politically-driven businesses
• 09:36 – The value of active watchlists
• 11:43 – Tesla and the importance of price anchoring to value
• 12:46 – Sell discipline and Monte Carlo simulation in valuation
• 19:08 – Company life cycle and “acting your age”
• 24:52 – Why every disruptive technology creates a bubble
• 27:20 – Picking the winners in a bubble
• 29:27 – AI as an infrastructure play and parallels to telecom/utilities
• 36:02 – The net impact of AI on profit margins
• 40:25 – Where value may accrue in the AI chain (architecture to services)
• 50:51 – Why Damodaran is skeptical about private market diversification
• 54:02 – Thinking about uncorrelated assets and collectibles
• 57:48 – How to automate market reentry after taking profits
• 59:36 – How wealth/time horizons shift across generations

Language & Tone

Damodaran’s tone is approachable, candid, and pragmatic, blending humor ("the Buffet trap," "middle aged companies in tight jeans") with practical advice. He frequently urges self-reflection and humility, dismisses fads, and resists overconfidence—grounding theoretical finance concepts in real-world, personal application.

This summary captures the episode's key ideas, discussion points, actionable insights, and the memorable language of Professor Damodaran, allowing a reader to benefit from his expertise and perspective without listening in full.