Chris Mayer — I Studied Every 100-Bagger Stock in History. Here's What I Found

0:01 The guest and the new book

• Tobias Carlisle and Jake Taylor host; Chris Mayer is "a portfolio manager, author of 100 Baggers, and author of a new book, The Investor's Odyssey." The new book is what he thought about after 100 Baggers — "a lot more thinking about long-term investing and what it's all about."

0:49 The woman on the plane — one decision, a lifetime of compounding

• Flying to the Berkshire meeting he sat next to a woman bumped from business class who turned out to be one of Berkshire's original investors: she "just invested with him and basically left the money there," became very wealthy, and now gives shares to her grandchildren.
• 1:37 "She basically made one decision, which is to buy this stock, and just left it alone. And she's got a track record that beats most every active manager anywhere on the planet." That started the question the book tries to answer: what actually is a good investor?

1:58 The Odyssey as the organizing metaphor — and what the sirens are

• He'd just read Daniel Mendelsohn's new translation of the Odyssey; the obstacles to holding a stock for decades are "reminiscent of Odysseus and his journey and all the temptations, all the travails."
• 2:27 The sirens are "anything that is calling us off the course of holding on to our investment" — chiefly the media: "every financial program or show or newsletter… always makes it seem that whatever's happening now is really important and you have to do something about it."

3:54 How to ignore them — a handful of key essentials, and the bad habits

• "There's no secret per se… a lot of it's common sensical." Focus on the business itself: "every business you can probably boil down to a handful of key essentials and just tracking those things. And as long as those things are within a reasonable range of performance that you expect, then you continue to hold on."
• 4:16 The habit to break is price-checking: doing it daily or several times a day "makes stocks seem a lot more volatile than they are," and "those little blinking green and red colors are kind of calls to action."
• 4:56 He used to read the Journal and the Financial Times every day; "now I don't do any of that… you can cut back on your media diet as well."

5:20 AI as a threat — case by case, and probably ubiquitous rather than differentiating

• Asked how to separate real threats from manageable ones when there's "no evidence in the results yet": "that's going to be something you have to evaluate case by case, business by business."
• 5:57 The analogy is the late '90s internet — "there will definitely be casualties… businesses that are just zeroed out," the way Amazon hollowed out brick-and-mortar retail.
• 6:27 But the base case is ubiquity, not advantage: "today nobody would claim they have a competitive advantage because they have a website… I imagine AI will be something like that. It'll be so ubiquitous that everybody will have it… but no one's going to be able to claim that we use AI and that's our competitive advantage."

7:09 ROIC is the northstar — and the Munger inversion runs alongside it

• "Return on invested capital is a good northstar. Companies that can reinvest or earn high returns on capital over a very long period of time tend to be good investments." The key question in any business he analyses is "ultimately what's return on capital and their ability to continue to do that for a very long period of time."
• 7:41 "You can also look at it sort of inverted like Munger would do. So what things do we know probably don't work out well?" — heavy competition, heavy leverage ("that could be a problem next time there's some sort of financial crisis"), unscrupulous insiders. "There's lots of things we can kind of knock out."

8:34 What hasn't changed — high returns on capital, plus the entrepreneur

• The core premise survives: "holding on to businesses that generate high returns on capital for a very long period of time… it's hard to get away from." The second half is "the quality of the people involved in the business."
• The illustration: New York Times and News Corp had "the same market cap at one point and then like 30 years later… the New York Times basically had the same market cap and News Corp was up 80x."
• 9:37 "Some of the biggest winners are companies you can readily put a name to. If I say Walmart, you know about Sam Walton's story. Say Apple, you know about Steve Jobs… Charles Schwab, you know about Charles Schwab."

10:24 What has changed — M&A revisionism and the Swedish serial acquirers

• "I have a much more favorable view of companies that grow by acquisition than I did back then." Two causes: reading — Deals from Hell "summarizes a lot of good research on M&A," and the conclusion "goes against the grain… it's no worse off than anything else that companies invest their money in" — and personal experience.
• 10:56 The experience is the "Swedish serial acquirers… companies like Lifco and Lagercrantz and Addtech… names I didn't hear about and knew nothing about when I wrote 100 Baggers," plus Constellation Software, which he "maybe was vaguely aware of, but otherwise didn't really know or appreciate."
• 12:20 Carlisle frames the old orthodoxy — short the acquirer, buy the seller — and the classic failure mode (Valeant): deals get "proportionately bigger… proportionately more expensive," heavy leverage, "they need probably a promotional CEO to work." Something changed in the last decade.

13:38 Bolt-ons vs splashy deals — size and leverage are the red flags

• Why the perception is wrong: "the large deals get all the attention, so we know the big deals and their spectacular failures… nobody writes about the little humdrum acquisitions that happen behind the scenes."
• The two research-supported red flags are leverage and size: "when they're really big and they use leverage, odds are against you."
• 13:57 The counter-examples are programmatic: "lots of companies have been able to grow sustainably with good returns doing more programmatic smaller acquisitions… Watsco and Roper of the world, and HEICO, however, 100 plus acquisitions in this time. Those companies have been enormously successful. But they're out of the limelight."

14:21 The era-defining acquisition — and where this cycle's might be hiding

• Host riff: every era has its emblematic deal — RJR Nabisco in the '80s LBO boom, AOL/Time Warner at the dot-com top. "What's the big emblematic acquisition this time around?" Mayer: "maybe we haven't had it yet."
• 15:25 Two candidate explanations for the gap. First, IPO maturity: "companies… IPOs are much more mature now and bigger than they were." Second, the deal template is "a big incumbent who is desperate to change the narrative and feels like they're left behind and they need to grab on to something that looks like the life raft to the future" — so this cycle's version would be "somebody buying some AI related thing or chip maker right at the top."
• 16:17 Or it may already have happened privately: the top-tick deal may be "still sitting on a private equity balance sheet today" — "there's not like the stock price a year later to show how much it blew up in your face yet."

17:15 The four-legged stool — where he will and won't compromise

• People: no compromise. "I'm certainly not willing to compromise on the character of the people… bad capital allocators or… any question of their integrity, or taking advantage of minority shareholders. So steer clear of that." Most of his analytical time goes on competition (how the moat is defended) and incentives.
• 17:47 Returns on capital: look-through allowed. "It doesn't necessarily have to be something that's earning high returns right now — could be decent returns now and then there's some underlying scale or some other parts of the business that are going to improve over time that are pretty reliable."
• 18:15 Balance sheet: near-absolute. "I'm always scared of dealing with high leverage balance sheets because I've been burned by that in the past… I just prefer to sleep well at night… when things get crazy, then I know my companies will be fine and maybe have the ability to take advantage and do something during those distress periods."
• 18:51 Valuation: an IRR that makes sense. "I run through some sort of analysis where I'm looking at what kind of IRR I expect, and that's got to make sense as well. So all four of those things are a pretty good little stool." 19:15 Horizon: "five to 10… five is not that long, but it's long enough" — and beware what you can make a 10-year model say: "whatever you want to say, you get to say."

19:39 Culture — the markers you can actually observe from outside

• "That's huge for me… For a long-term investor, I think that's really important. If you're holding a stock for a year or two or three, who cares?" Asked whether culture is the single uniting trait beyond ROIC: "For me, I think it would be."
• 20:19 The observable markers: employee tenure; employee ownership ("do they have some culture of ownership there"); supplier longevity — "there's good studies that show that long-lasting companies also have long-lasting relationships with their suppliers… it's kind of like an ecosystem"; and 20:57 promote-from-within — "a team that promotes from within, has a lot of executives that have been around, worked their way up the business."
• 21:52 The caveats on the two obvious shortcuts: expert networks ("those people don't work there anymore and sometimes there's a reason" — if the culture rejected them, that's an inverse signal) and Glassdoor ("could just be disgruntled employees, very small sample size").
• 22:42 The benchmark: Buffett on Berkshire's culture — "don't lose money for the firm. Don't lose a shred of reputation. Deal with people fairly" — "you probably won't find anything as clear as that, but anybody else who's talking in those terms I thought would be doing a pretty good job." 23:52 Carlisle's banking version: collateral doesn't save you from a man you don't trust — "there's always a way."

25:23 Dilution — the stand-still arithmetic, and flat share counts

• Share-based comp matters, and matters more the longer you hold: "If you're just going to own a stock for a year, what do you care if there's one or two percent dilution? If you're going to own something for 10 years, 1% dilution adds up quite a bit. 2% dilution is very significant." Carlisle notes 15% dilution is "common" in some names.
• 25:40 "Think about how much more you have to grow just to stay in place. There's a table in the book I have about that… even at 2%, how much more growth does it require over say five years just to stay even? And there's some surprising numbers there."
• 26:06 "That's why I love and admire these companies that have share counts that are unchanged over a long period of time. Constellation Software is an obvious one, but Lifco has the same number of shares as when it went public… and then perhaps even better, the companies that slowly shrink it over time opportunistically. Those are pretty special."

26:53 Cannibals and capital allocation — AutoZone, and Buffett's five-year rule

• Carlisle's framing: "there's a lot of return to be had from buying a good company and then letting the company take out half of your other co-owners… and just concentrating your share of it."
• Mayer's example: "it was AutoZone… even though the business didn't really grow that much over that period of time, the stock was phenomenal because they were just gobbling up so many shares year after year after year." A low valuation, sustained, is a gift to a buyback machine.
• 27:47 Why capital allocation dominates: a management team earning 15% on equity will, over the next five years, "invest the same amount of capital as the business has to that point in its history — which is remarkable, but mathematically true."

28:30 Selling is the hardest thing — and the scratch-the-itch sleeve

• "I always say selling is like the hardest thing in investing. I don't know anybody who's really good at it." The triggers he does act on: "thesis is way off from where I started or something dramatic has happened."
• The structural argument for inertia: "if you're buying good businesses generally, then what you're selling is eventually going to be worth more at some point. It's just a matter of what you do with the capital instead."
• 29:18 The practical fix for the urge to act: split the money. "Take some portion of your money and do this where you're going to leave it alone, be long-term… And then you have that itch you have to scratch. You have some other smaller portion of your money that you allow yourself to trade more."

31:04 Jake Taylor's veggies — the case for coarse tuning

• Host segment (Taylor, not Mayer). Nature looks badly optimized on purpose: the great tit could feed 18 chicks in a good year and lays about nine; desert seeds stay dormant after the best rains in a decade; songbirds migrate on day length, not weather; the cockroach runs from a harmless puff of air.
• 33:03 The source: Rick Bookstaber and Joseph Langsam, On the Optimality of Coarse Behavior Rules (Journal of Theoretical Biology, 1985). Fine-tuned rules are optimal only "inside the world that that animal can perceive"; the gap Bookstaber calls extended uncertainty is events that "cannot even be delineated, much less assigned probabilities" — so "the fine-tuned animal isn't just wrong. It's wrong in proportion to how well tuned they are to the old world."
• 34:43 "18 eggs is the arithmetic hero and nine is the geometric survivor" — give up average to cut variance and the smaller clutch compounds further across enough winters. Animals moved to an unfamiliar lab get coarser on their own: unfamiliarity is the signal to stop fine-tuning.
• 36:13 Bookstaber ran risk at Salomon through LTCM. His crystal-ball thought experiment ends with: simplify the models, flatten the hierarchy, shorten the reports, don't over-optimize — "less of a laser focus on risk and more like 360 degree coarse radar coverage."

37:53 Five ways to coarse tune (Taylor)

• 1. Coarse measurement. Graham: the margin of safety exists "to render unnecessary an accurate estimate of the future." Taylor leaves "out all decimal places in my note-taking and analysis. I don't want my brain to get subtle clues that there's more precision… than really exists." Carlisle's EV/EBIT is offered as the same idea in a multiple — 37:03 it captures debt, minorities and off-balance-sheet liabilities, is "hard to game if you're doing those calculations yourself," and is "imperfect… but I like it as a rough cut."
• 38:39 2. Coarse sizing. In 2009 three finance professors tested 14 portfolio optimizers against simple equal weighting; "out of sample, not one of these fancy algos beat the equal weighting consistently." For 25 stocks the optimizer needed ~3,000 months — about 250 years — of data to justify its precision.
• 39:24 3. The migrating-bird rule. "Rebalance maybe on the calendar, not on some ever-changing macro signals. Review your rules once a year, not after every loss," so you don't overfit to the last war.
• 39:56 4. Coarse monitoring. Every blowup — Barings, Long-Term Capital, Archegos — "can be explained in one sentence and usually it's leverage and hubris." So run a one-sentence premortem: "if you can't say how a position dies in one simple sentence, the thing that actually is going to get you is probably still lurking off the page."
• 40:23 5. Coarse prompts. Two years ago precise AI prompts won ("think step by step" moved one model's math score from 20% to 80%); now OpenAI's own guidance says keep it simple and stop saying it. "A precise prompt is a bet that today's model will hold" — what survives every generation is the brief you'd give a new analyst: "what do you want, why do you want it, and what does a good answer look like." 41:27 The cost is real: coarse tuning underperforms every year the world holds — the fine-tuner "collects that premium every year until the year the picture isn't complete and then… hands it all back at once."

42:45 General semantics — Korzybski, date subscripts, and the map

• Mayer's other book, Dear Fellow Time-Binders, is an introduction to general semantics — Alfred Korzybski, "a Polish engineer type who came up with this idea in the 1930s and wrote a big fat 800-page book about it," gear around "how we use language and how that influences how we think."
• 43:52 Taylor's no-decimals habit is "very Korzybskian… we do have this false precision when we say something has a P/E of 25.2… we'd probably be better off if we didn't know the number exactly. We just do a range."
• 44:29 The date subscript, the tool he "uses all the time": write "Berkshire Hathaway₂₀₂₅" to denote that your conclusion is from last year. "It prevents you from getting attached to your ideas… Using a date makes you recognize that things change and then you need to look at it again."
• 45:27 The map is not the territory — Korzybski's line, and "another good way to sum up general semantics." The toolbox is for parsing descriptions: "what's really being described, what those descriptions hide, what they maybe say about the person giving the description." 46:42 The payoff is "a greater dose of humility about your own ideas… being more open to being proven wrong."

47:55 Don't get attached to labels — "what is Tesla?"

• The practical implementation of general semantics: "you don't get too attached to labels. What other people say things are" — "compounder," "value stock."
• The worked example: "what is Tesla? Is it an auto manufacturer or is it a battery company or is it what? …how you frame it, how you describe it really greatly influences how you price it and how you think about it in your mind." He pointedly declines to answer his own question: "I just pose the questions. I don't answer them."

48:43 Position sizing — start small, 7–8% full, let winners get unruly

• "I like to kind of start things small and get to know the business." Ownership changes attention: "when you actually own something, you're just much more in tune… I feel like you know more about it when you've owned something for a year."
• 49:28 Why small first: "that stretch of time there is probably where you'll make a mistake, is probably early… It'll be easier to get out of if it's a smaller position." Starting big raises the stress level and makes exit harder.
• 50:10 And there's no rush: "if it's a really good business that you can own for 10 years, you could probably buy at the 52 week high this year, next year, the year after, and still do very, very well."
• 50:58 The ladder: full position "somewhere around 7, 8%… and then after that I will just kind of let it ride. I like to just sort of let the portfolio get unruly." A winner compounding into "12, 13% of the portfolio — that's good, that's great, earned. I don't feel like I have to trim it." 51:50 The hard stop is legal: "from my fund doc, it's legal at 25%. I definitely have to cut it at that point" — though "it might be a little before that."

52:13 Trimming the giant — Bessembinder, and T. Rowe Price's Walmart

• Carlisle raises Bessembinder's 4% study against the urge to cut a huge winner: "imagine it's 1972 and you have Berkshire… it's the lady who you sat next to on the airplane, and if she had been trimming that whole time, she probably cut her result by huge orders of magnitude."
• 52:35 Mayer's example: T. Rowe Price's small-cap fund bought Walmart early and "were constantly cutting it back… if they had left that, it was worth more than the whole AUM of the fund today. Obviously those are huge huge mistakes."
• 52:59 But he refuses to make it a rule: "I love Bessembinder's studies… But that's the cost of investing. For most individuals, if they had to keep chopping back… they're still going to do very, very well," and occasionally the giant "turned out to be Polaroid and went to zero." "Owning stuff for a long time doesn't mean you just ignore it completely."

53:33 Carlisle's never-sell backtest — error minimization, not stock picking

• Host research: take the cheapest free-cash-flow names each year from 1999–2000 through ~2010, hold, "never rebalance those portfolios." At the end "your portfolio becomes dominated by the big good things" — the names everyone now agrees are the best stocks to hold — "but at the beginning of the period of time would have been very difficult to predict."
• 55:10 The rationale: "there's an error rate in your buying, there's an error rate in your selling" — the S&P 500's committee "famously underperforms" a rule that just owns the largest 500. "I just think it's an error minimization. I don't do it, but I think it's an interesting idea that the never sell would be very very hard to do."
• 56:19 The honest caveat: these are bad businesses bought on price alone — "they're cheap because they're not doing very well… there's no selectivity in buying them," so it's "playing a statistical game that at least some of them in there are going to work out."

57:34 The coffee can — Shannon, Kirby, and where the return actually comes from

• "The winners really make a huge difference… they can be the difference between beating the market or not. It's that one giant that takes over."
• Claude Shannon's VC portfolio "ended up with Motorola and a few of these other absolute monsters. But he just didn't ever sell a share. And that was the secret."
• 58:11 Robert Kirby's original coffee-can story — the client's husband had been piggybacking every recommendation and never sold any, and one position was "worth more than all the money he was managing for the wife." Mayer: "a whole bunch went to zero, but the winners more than made up for it."
• 58:50 Wrap: The Investor's Odyssey is out now; Carlisle buys Dear Fellow Time-Binders live on air — "it's rare where you get kind of new big ideas these days."