Episode Summary
Executive Summary: The episode announces a collaborative book project built from the hosts’ closing-question interviews with top investors, then focuses on Michael Mauboussin’s core ideas: base rates, expectations investing, the limits of valuation multiples, and the paradox of skill. The hosts connect these concepts to investing, financial planning, business decisions, and even modern shortcuts like LLMs, emphasizing humility, probabilistic thinking, and the need to earn the right to use heuristics.
Main Topics: Book project and public drafting process: The hosts explain they are turning recurring closing-question answers from ~200 investors into a book, using Substack drafts to gather feedback publicly and improve chapters iteratively. Base rates as a decision framework: Mauboussin’s base-rate approach is presented as a powerful, underused way to evaluate outcomes by comparing a situation to a relevant reference class rather than relying only on personal judgment. Expectations investing and scenario analysis: The discussion breaks down Mauboussin’s expectations investing into reverse-engineering price, assessing whether expectations are too high/low, and assigning probabilities across multiple scenarios. Multiples are not valuation: The hosts stress that valuation multiples are shortcuts, not valuation itself, and that investors should understand the economic assumptions embedded in each multiple before using it. The paradox of skill and the role of luck: Mauboussin’s paradox of skill is used to explain why improving absolute skill can increase the importance of luck when competitors are similarly skilled and tightly bunched. Applying the ideas to life, planning, and AI: The episode extends the investing lessons to business, financial planning, journaling, and LLMs, warning against unexamined shortcuts that reduce learning and distort judgment.
Key Arguments: Base rates should be the starting point for forecasting because they ground expectations in historical reference classes rather than intuition. Expectations investing flips the usual valuation process: start with the market price, infer embedded expectations, then test whether reality is likely to beat or miss them. Probabilistic scenario analysis is superior to single-point forecasts because markets and life unfold across multiple possible outcomes. Valuation multiples are useful communication tools, but only if the user understands the underlying cash-flow, growth, and return assumptions they imply. Growth alone does not create value; growth adds value only when returns on capital exceed the cost of capital. As skill rises across a field, relative differences shrink and luck matters more, making outcomes in investing and sports more random than people expect. Shortcuts like multiples or LLMs can be helpful, but they should supplement—not replace—deep understanding, or they may prevent learning. Keeping records of decisions and judgments is essential because people misremember what they believed when they acted.
Data Points: Number of investor responses collected: about 200 - The hosts say they have asked the closing question to roughly 200 guests and are turning the best answers into a book. Substack cadence: every week or two - They hope to post draft chapters on the Substack at a weekly or biweekly pace. Book timeline target: within the next year or so - The hosts say they hope to finish the book sometime over the next year or so. Base-rate forecast example: 10% with some standard deviation - Used humorously as the kind of probabilistic forecast base rates would justify. Major League Baseball batting benchmark: .400 batting average - Used in discussing the paradox of skill and why no one has hit above .400 since Ted Williams. Ted Williams reference year: 1941 - The year Ted Williams last hit over .400, illustrating shrinking variance in elite skill. Tenure of valuation research survey: 9 out of 10 - Mauboussin notes that most analyst reports rely predominantly on valuation multiples. A growth example: 50% earnings growth - Used to illustrate why base-rate history matters when evaluating whether extraordinary growth can persist. A low-multiple example: 7 times earnings - Used to show how investors often cite multiples without understanding what they mean economically. Illustrative high-multiple example: 30 times earnings - Used alongside other multiples to emphasize hidden assumptions behind shorthand valuation metrics.
Pivotal Quotes: "Multiples are not valuation. They are a shorthand for the valuation process." — Michael Mauboussin: Used to explain why investors must understand the economic assumptions behind valuation multiples. "The key is to try to be sort of agnostic. You just want to say what has to happen for today's stock price to make sense." — Michael Mauboussin: Step one of expectations investing: reverse-engineer expectations from price before forming a view. "The skill is not only high, but it's uniform." — Michael Mauboussin: Core idea in the paradox of skill discussion, explaining why luck matters more among highly skilled competitors.
Implications: Listeners are encouraged to replace intuition-heavy forecasting with base rates, probability, and explicit assumptions. The episode also warns that convenient shortcuts can hide risk, so durable investing and life decisions require humility, records, and reference-class thinking.
From the Episode
Chapter, which is based on Michael Mobison and his idea of base rates. We hope you enjoy it and will follow along with us on the sub stack as we write the book. I think that I would encourage people to learn about and apply base rates as they think about the world of investing. By the way, it's not just valuable for investing, but really business or your life, actually. The point I make over and over is that multiples are not valuation. Let me just stop there. Multiples are not valuation. They are a shorthand for the valuation process. And one should never confuse those two things. Expectations investing has three steps. The first step is to go backwards and say the only thing we know for sure in this whole equation is the price. So let's go back and reverse engineer using a discounted cash flow model, which is an appropriate way to think about economic, both theoretically and I think practically, think about what has to happen for this current stock price to make sense. Skill is not only high, but it's uniform, right? And you think about how many smart people go into this industry and how motivated they are and how hardworking they are and how thoughtful they are. It just defies logic that.
Having a conversation, casual conversation, we might, I would maybe drop multiples about a particular business, whatever. That's fine. But the key is that you understand the economic implications of the multiples that you're using. So you're saying, I think this should be a 15 times EBITDA or the 30 times earnings. So what do I have to believe for those multiples to make sense? And so, as you know, we spent a lot of time writing about, we wrote a piece called What Does a PE multiple mean? We wrote a piece called What does Ne V D EBITDA multiple mean, essentially creating a bridge between those multiples as people tend to use them. And the underlying economic assumptions that you need to make in order for those to justify those multiples, and just to be really explicit about those things. And as Wat the Motorin at New York University, sort of the dean of valuation, he's talked a lot about this. He's surveyed investor reports and he's found, or analyst reports, pardon me, and he's found that nine out of 10 rely predominantly on multiples. So, this is how people tend to talk to one another. So, again, as I tell my students at the end of our evaluation module, you have to sort of earn the rights to multiples. You can use them, but earn the right.
And I went to him and I said, you know, it's actually the opposite. You know, the way to think about it is the skill is not only high, but it's uniform, right? And you think about how many smart people go into this industry and how motivated they are and how hardworking they are and how thoughtful they are. It just defies logic that there's no skill. There's huge amounts of skill. It's just that's the problem, right? And that skill gets reflected in prices. And if prices to the degree to which they're largely efficient, then that means the random walk kind of thing comes into play. This one is the most mind-bending for me of all of them. So it's this idea. Is as the absolute level of skill rises, relative skill or becomes less important and luck becomes more important. So, you might be able to explain it better than me, but this is like it's something that takes some thinking to kind of wrap your arms around it. Yeah, I mean, it's the loser's game thing, right? Like, this goes back to Charlie Ellis and the losers' game in tennis, where he basically points out: if a pro is playing an amateur, the pro is going to smoke the amateur nine times out of ten, one times out of ten, or whatever the stats are. I'm throwing my own stats into his.
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Excess Returns is dedicated to making you a better long-term investor and making complex investing topics understandable. Join Jack Forehand, Justin Carbonneau and Matt Zeigler as they sit down with some of the most interesting names in finance to discuss topics like macroeconomics, value investing, factor investing, and more.