The 100 Year Thinkers: Long-Term Compounding in a Short-Term World

Chris Davis and Robert Hagstrom explore the tension between holding great businesses and keeping a winning stock from becoming too much portfolio risk. Why do two investors who believe in letting winners compound also use 10% position limits?

On this episode of 100 Year Thinkers, Chris Davis of Davis Funds and Robert Hagstrom of EquityCompass join Matt Zeigler and Bogumil Baranowski to discuss position sizing, selling mistakes, index concentration and the cost of growth. From Chris Davis’s experience selling Costco to the debate over who will capture AI’s economic benefits, they examine what it takes to hold a business through uncertainty without ignoring risk. Stay for Matt and Bogumil’s closing discussion of the lessons for investors.

Topics covered:

• Why selling a genuinely great business can be an investor’s most expensive mistake
• How client behavior and fund constraints influence 10% position limits
• Chris Davis’s concerns about index concentration, momentum and future IPO incentives
• Robert Hagstrom on trimming positions as the margin of safety shrinks
• The bull-case pre-mortem: asking what could make selling today a mistake
• What Chris Davis missed about Costco’s growth and ability to adapt
• Why identical earnings growth can produce different shareholder returns
• Whether AI spending builds durable pricing power or delivers more value to users
• How customer trust and restraint on margins can strengthen competitive advantages
• Balance sheets, circular financing and the humility required to size a position

Chris Davis / Davis Funds

Robert Hagstrom / EquityCompass

Chapters:

00:00 Holding great businesses and the case for position limits
06:47 Robert Hagstrom on concentration and client risk
12:40 Index concentration, momentum and IPO incentives
19:03 Trimming winners, margin of safety and the Costco lesson
30:09 Valuation, return on capital and the cost of growth
36:01 Is AI’s capital spending cycle temporary?
40:10 AI pricing power: builders versus users
45:35 Competitive advantage, margins and customer trust
51:45 Balance sheets and circular AI financing
55:53 Evaluating the AI investment cycle
01:00:23 Matt and Bogumil’s takeaways: position sizing and AI
01:10:25 Being an AI user versus an AI investor

Learn more about the Excess Returns podcast network.

No information discussed in this podcast should be construed as investment advice. Securities discussed may be held by the hosts and guests, their firms or their clients.

Chris Mayer and Robert Hagstrom join Matt Zeigler on 100 Year Thinkers to explore how investors can identify great businesses, hold them through volatility, and let compounding work over decades.

Drawing on Mayer's book The Investor's Odyssey, they discuss Warren Buffett's investing philosophy, durable competitive advantages, investor psychology, and the portfolio management decisions that help long-term investors stay the course.

Buy the Investor's Odyssey
https://amzn.to/4gCVMMp

Chris Mayer on Twitter
https://x.com/chriswmayer

Robert Hagstrom on Twitter
https://x.com/RobertGHagstrom

Topics covered:

• The original Buffett partnership investor who held Berkshire Hathaway for decades

• Why individual investors can have an advantage over professional money managers

• The coffee can portfolio and resisting the pressure to trade

• How loss aversion and constant price updates undermine long-term investing

• High returns on capital, reinvestment, and the power of compounding

• Assessing whether competitive advantages can survive AI and new competitors

• Distinguishing temporary stock declines from deteriorating businesses

• Why great investment track records include periods of underperformance

• Invisible moats, employee incentives, and lessons from companies that survived 100 years

• Position sizing, letting winners run, and combining stock picking with index funds

Timestamps:

00:00 Chris Mayer's The Investor's Odyssey and the Berkshire buy-and-hold story
04:20 Why more investors don't hold great businesses for decades
09:44 Resisting financial media and the pressure to act
15:59 Loss aversion and protecting yourself from market noise
21:12 Compounding returns and how long a competitive advantage lasts
26:25 Separating AI disruption fears from business fundamentals
30:38 Why outperforming investors still lag the market frequently
36:45 Evaluating the business before the management team
41:26 Invisible moats in trucking and insurance brokerage
48:03 Building a business culture that outlasts its leaders
53:05 Position sizing and why stock picking is only half the job
58:06 Combining index funds with a patient stock portfolio

Learn more about the Excess Returns podcast network:
https://excessreturns.co

No information discussed in this podcast should be construed as investment advice. Securities discussed may be held by the hosts and guests, their firms or their clients.

Robert Hagstrom joins Matt Zeigler and Bogumil Baranowski to revisit the 25th anniversary edition of The Warren Buffett Portfolio and explain why volatility is not the same as investment risk.

They discuss concentrated portfolios, active share, business valuation, behavioral finance, complex adaptive systems, and Warren Buffett's warning that the market's casino can overwhelm its cathedral.

The Warren Buffett Portfolio - 25th Anniversary Edition
https://amzn.to/3TVXoru

Robert Hagstrom on X
https://x.com/RobertGHagstrom

Equity Compass
https://www.equitycompass.com/

Topics covered

• Why Markowitz's definition of risk as variance shaped modern portfolio theory

• Why Buffett views permanent capital loss, not volatility, as the real investing risk

• What Hagstrom's study of 3,000 portfolios revealed about concentration and market outperformance

• The difference between know-something investors and investors better served by indexing

• How benchmark awareness creates closet indexers and weakens active management

• What loss aversion and prospect theory explain about investor behavior

• Why Darwin, William James, and complex adaptive systems offer better models for markets

• Buffett's cathedral and casino metaphor for business ownership versus speculation

• The El Farol problem, Jim Simons, and why successful market models stop working

• Why options trading, leveraged ETFs, and record single-stock dispersion may be strengthening the casino

• How to evaluate portfolios using cash flow, return on invested capital, and look-through earnings

• Why permanent capital and System 2 thinking are essential for focused investing

Timestamps

00:00 Intro
04:00 Why Markowitz defined risk as variance
11:47 What 3,000 portfolios revealed about concentration
17:17 Know-something versus know-nothing investors
22:23 Kahneman, loss aversion, and modern portfolio theory
26:58 Darwin, pragmatism, and adaptive markets
32:28 Buffett's cathedral and casino metaphor
37:37 The El Farol problem and why markets resist prediction
42:08 Why investors crave market forecasts
46:16 Why investing is most intelligent when businesslike
51:38 Record stock dispersion, options, and leveraged ETFs
56:00 Measuring portfolio progress through business economics
01:00:43 Why permanent capital enables focused investing
01:04:43 How markets survive widespread investor mistakes

Learn more about the Excess Returns podcast network:
https://excessreturns.co

No information discussed in this podcast should be construed as investment advice. Securities discussed may be held by the hosts and guests, their firms, or their clients.

On this episode of the 100 Year Thinkers, Chris Mayer and Matt Zeigler discuss long-term investing, 100-baggers, AI stocks, SpaceX valuation, founder-led companies, and why the best investments often come with brutal drawdowns. We also cover his new book The Investor's Odyssey, the danger of letting labels like AI do too much work, how to think about TAM and capital allocation, and why patience may be the biggest edge for investors trying to own great businesses for decades.

The Investor's Odyssey: Resisting the Sirens and Playing the Long Game
https://amzn.to/44BMXeJMain topics covered

• Why SpaceX, AI and trillion-dollar IPOs are testing investor discipline

• How Chris Mayer thinks about valuation after watching Google become a huge winner

• Why great businesses can still be terrible investments at the wrong price

• The danger of letting labels like AI, quality and TAM replace real analysis

• Why many AI features may not create real customer value

• What the dot-com bubble can teach investors about AI adoption and shakeouts

• Why investors do not need to be early if a company is truly exceptional

• How to separate AI anecdotes from real financial impact

• Why capital allocation and return on invested capital matter more as companies scale

• How to evaluate founder control, governance, incentives and trust

• Why the best long-term stocks can still fall 50 percent or more along the way

• What rational exuberance might look like for long-term investors

Timestamps

00:00 Intro: Chris Mayer on AI, SpaceX and long-term investing
04:00 SpaceX valuation vs Google and the risk of paying too much
08:01 Why labels like AI and quality can do too much work
12:05 The AI pause, the dot-com analogy and where real value may emerge
16:06 Why investors do not need to be early when a business is real
21:00 Becoming a great company versus already being mature
25:10 Thinking about TAM, market share and realistic growth expectations
29:43 Corporate governance, free float and shareholder rights
34:27 How to judge founder trust, incentives and compensation
38:57 Employee ownership, culture and building enduring companies
43:02 Investor frustration in a lopsided AI-driven market
47:02 Why even a perfect stock picker would face brutal drawdowns
52:17 The rise of trillion-dollar IPOs and the question of rational exuberance
56:29 The Investor's Odyssey and playing the long game

In this episode of The 100-Year Thinkers, Robert Hagstrom explains why modern portfolio theory pulled investors away from business analysis and toward portfolio math. In this episode, Hagstrom, Matt Zeigler and Bogumil Baranowski discuss Markowitz, beta, efficient markets, Warren Buffett, Charlie Munger, business-driven investing, owner earnings, benchmarks, and why thinking like a business owner changes how investors understand risk.

The Warren Buffett Portfolio, 25th Anniversary Editionhttps://amzn.to/4uz8sZ3

Topics covered:

• Why Hagstrom thinks modern portfolio theory changed investing’s objective

• The difference between volatility, variance and real investment risk

• How Benjamin Graham and John Burr Williams framed risk around intrinsic value

• Why beta became the dominant shorthand for risk

• How the 1973-74 bear market helped institutionalize modern portfolio theory

• Why Berkshire preserved the business owner’s lens

• The “cathedral and casino” distinction between owning businesses and trading stocks

• Owner earnings, return on invested capital and cost of capital

• Why business owners often make better long-term equity investors

• Look-through earnings and building a “mini Berkshire”

• The difference between making money and beating a benchmark

• How benchmarks can distort investor behavior

• Why knowing yourself and your clients matters in portfolio construction

Timestamps:

00:00 Robert Hagstrom on why risk is not volatility

00:40 Business-driven investing vs portfolio math

02:42 How modern portfolio theory defined risk as variance

06:38 Graham’s margin of safety vs Markowitz’s definition of risk

09:44 Sharpe, beta and simplifying portfolio risk

12:51 Why the 1973-74 bear market helped MPT take over

16:20 Why MPT became institutionalized without proving it could beat the market

18:53 Buffett, Keynes and concentrated investors violating MPT

22:53 Stocks as businesses and Buffett’s cathedral vs casino

30:01 Business analysis, owner earnings and return above cost of capital

36:41 Look-through earnings and running a mini Berkshire

41:34 Making money vs outperforming a benchmark

47:30 Why Berkshire’s public and private businesses shaped Buffett

50:05 How investors can start applying the Buffett way
54:05 Bogumil on how investing theory becomes accepted truth
58:09 Why direct ownership creates responsibility and conviction
01:00:15 Investor know thyself and the limits of outsourcing caring
01:03:35 Finding the right clients for a business-owner investing approach

This episode of 100 Year Thinkers brings together Chris Mayer and Ian Cassel for a deep discussion on long-term stock picking, microcap investing, business quality, AI disruption, management teams, and the behavioral skills that separate great investors from great analysts.

They explore why the edge in investing may increasingly come from judgment, presence, relationships, patience, and the ability to hold the right businesses through uncertainty.

Resources Discussed

The Last Moat
https://microcapclub.com/the-last-moat/

Stock Picker by Ian Cassel
https://microcapclub.com/stock-picker/

The Investor’s Odyssey by Chris Mayer
https://www.amazon.com/Investors-Odyssey-Resisting-Sirens-Playing/dp/B0GJ3G6F2S

Follow Chris Mayer on Twitter
https://x.com/chriswmayer

Follow Ian Cassel on Twitter
https://x.com/iancassel

Topics Covered

• Why being present with management teams may still be an investor edge in the age of AI

• How microcap investing differs from small-cap, mid-cap and large-cap investing

• Why talking to management can build conviction but also create bias

• How Chris Mayer thinks about vertical market software, mission-critical systems and AI disruption

• Why AI may become table stakes rather than a durable competitive advantage

• How small companies can use AI to improve workflows, sales, inventory and productivity

• Why many microcaps have short shelf lives and rarely become true long-term compounders

• The role of intelligent fanatics, owner-operators and repeat winners in great investments

• Why management transitions can create powerful microcap opportunities

• The difference between being a great analyst and being a great investor

• Why execution, position sizing, selling losers and holding winners matter more than hit rate

• How Matt and Bogumil apply the lessons to AI, business quality and the limits of small business scalability

Timestamps

00:49 Introducing Chris Mayer, Ian Cassel and 100 Year Thinkers
04:59 Ian Cassel’s first management meeting and XM Satellite Radio
09:00 Why management meetings deepen understanding but can also mislead
14:32 Chris Mayer on the real edge in long-term investing
18:40 Mission-critical software, systems of record and AI disruption
22:45 How microcap companies are using AI in real businesses
27:02 AI as table stakes and when disruption creates opportunity
31:29 Why most microcaps have short shelf lives
35:51 Finding Tom Brady before the market knows he is Tom Brady
40:53 Why owner-operators and intelligent fanatics matter
45:03 Second-in-command leaders, repeat winners and chips on shoulders
49:27 Analyst vs investor and the missing skills of stock picking
54:00 Using data to identify investor strengths, weaknesses and decision errors
58:14 Position sizing and letting small positions earn the right to grow
01:03:00 Peter Lynch, stocks as businesses and learning to think like an owner
01:07:00 AI, human judgment and the limits of automation
01:11:00 Why not every small business can become the next Facebook
01:15:00 Where to follow Bogumil and the 100 Year Thinkers series

In this episode of the 100 Year Thinkers, Robert Hagstrom and Chris Mayer explore how investors should think about base rates, extreme outcomes, and the realities of long-term wealth creation in markets. Applying the work of Michael Mauboussin, the conversation challenges conventional ideas like mean reversion and highlights why a small number of companies drive most stock market returns—and what that means for portfolio construction.tives distort investing decisions

Topics covered
• Why markets are driven by extreme outcomes and power laws, not averages
• The Best & Bessembinder research showing a handful of stocks create most wealth
• Base rates vs outliers and when to trust historical probabilities
• Why the 100 bagger framework focuses on studying winners, not predicting them
• Portfolio construction as a way to capture asymmetric upside
• Buffett’s approach to consistency, durability, and long-term operating history
• Inside view vs outside view and how narratives distort investing decisions
• Why AI may be breaking traditional base rate assumptions in software and tech
• The limits of mean reversion and why it can lead investors astray
• Return on invested capital and how competition erodes excess returns over time
• Identifying durable moats and why most advantages eventually get attacked
• Winner-take-all dynamics and how they shape long-term investing outcomes
• The twin engines of returns: earnings growth and multiple expansion
• Return on incremental capital as a key driver of long-term compounding
• Intangible assets and why accounting understates true business value
• Amazon as a case study in misunderstood profitability and reinvestment
• AI CapEx cycle and why current spending may not be sustainable long term
• Why great businesses matter more than great management in long-term investing

Timestamps
00:00 Why extreme outcomes drive stock market returns
01:00 Base rates vs studying 100 baggers
03:00 Power laws and why markets are a game of outliers
05:00 Just 46 companies created half of all market wealth
07:00 Buffett on consistency and long-term operating history
10:00 How to think about base rates in AI, energy, and macro cycles
12:00 Does AI invalidate historical base rates?
15:00 Inside view vs outside view in investment decision making
19:00 Buffett’s “certainty at a discount” framework
23:00 How often investors should evaluate businesses vs prices
29:00 Mean reversion myths and where it breaks down
33:00 Return on invested capital and competitive pressure
36:00 Moats, winner-take-all markets, and long-term dominance
41:00 Twin engines of compounding: growth plus multiple expansion
43:00 Return on incremental capital and forecasting future returns
47:00 Intangibles and why accounting distorts real business value
50:00 Amazon, CapEx cycles, and hidden profitability
53:00 AI infrastructure buildout and the future of returns

In this episode of the 100 Year Thinkers, Matt Zeigler and Bogumil Baranowski continue their conversation with Robert Hagstrom and Chris Mayer, diving deeper into general semantics and what it means for investors navigating AI enthusiasm, market volatility, benchmark obsession, and the gamification of markets. From Warren Buffett’s cathedral versus casino metaphor to the risks hiding in so-called “safe” consumer staples stocks, this discussion explores how language, expectations, and mistaken certainty shape investment decisions. If you want to think more clearly about markets, technology, valuation, and your own reactions as an investor, this episode offers a powerful mental framework.

Topics Covered

• What general semantics is and how language influences how investors think

• IFD disease idealism frustration demoralization and how unrealistic expectations impact markets

• AI hype, capital spending, and the prisoner’s dilemma facing major tech companies

• Warren Buffett’s cathedral versus casino metaphor and what it means for investors today

• Why beating the S and P 500 may not be the right benchmark for success

• The gamification of markets, retail trading growth, and the shift from long-term investing to speculation

• Terminal value risk in software stocks amid AI disruption

• Why low volatility “warm fuzzy” stocks like consumer staples may be more dangerous than they appear

• Expectations investing, confidence versus overconfidence, and avoiding mistaken certainty

• The map is not the territory and how to avoid confusing models with reality

• Everything is connected to everything else markets as biological systems rather than mechanical systems

• Delayed gratification, compounding, and why wealth is built later in the investment journey

Timestamps

00:00 Cathedral versus casino capitalism and the market metaphor
02:00 What is general semantics and why it matters for investors
03:00 IFD disease unrealistic expectations and AI hype
06:40 Outperformance, Bill Miller, and unrealistic return expectations
09:00 Are market benchmarks the right way to measure success
12:00 What if stock market indexes did not exist
14:00 Public versus private markets and myopic loss aversion
18:40 Compounding, volatility, and delayed gratification
21:00 AI valuations, strategic capital spending, and economic returns
24:20 The AI adoption cycle frustration and demoralization
30:40 The man in overalls story and delaying reactions
33:30 Warren Buffett cathedral versus casino metaphor revisited
35:00 Gamification of markets passive flows and species shift in investing
39:00 When to sit still versus when to act in volatile markets
43:00 Mistaken certainty and the biggest risks in today’s market
45:00 The hidden risk in consumer staples and low volatility stocks
47:20 Expectations investing confidence versus overconfidence
49:40 Everything is connected markets as living systems
53:00 What success really means beyond beating an index
56:20 The map is not the territory final lessons for investors

When Robert Hagstrom and Chris Mayer sit down together, the conversation goes far beyond stock picking. Join them, along with Matt Zeigler and Bogumil Baranowski to explore how investors think, how language shapes decision making, and why many of the debates dominating today’s markets miss the deeper pointDrawing on ideas from general semantics, mental models, and long-term capital compounding, the discussion reframes market concentration, AI, valuation, and risk through a more durable lens built for long-horizon investors.

Topics covered in this episode

• Why high valuation multiples are not automatically a sign of overvaluation

• What return on invested capital really tells you about long-term compounding

• The difference between describing a business and understanding the business itself

• Market concentration, index construction, and why benchmarks can mislead investors

• The idea of time binding and what investors can learn from history without overfitting it

• Map versus territory and how financial statements can obscure underlying business reality

• AI investing, capital allocation, and separating durable businesses from speculative narratives

• Why many valuation debates are really disagreements about time horizon

• How language, labels, and mental shortcuts create overconfidence in investing

• What it takes for a company to compound capital over decades, not years

Timestamps
00:00 Introduction and why valuation multiples alone are misleading
02:30 Time binding and how accumulated knowledge shapes investing
04:45 Market concentration and what history can and cannot tell us
06:30 Index construction, market cap weighting, and benchmark distortions
09:55 Map versus territory and the limits of financial statements
12:30 History, narratives, and how descriptions shape beliefs
17:00 AI narratives, capital spending, and separating signal from noise
20:40 Technology cycles, bubbles, and what past revolutions can teach investors
24:20 Why language matters in investing and the danger of saying something is
29:50 Dating and indexing companies to avoid static thinking
34:00 Global markets, changing data sets, and why comparisons break down
38:30 Returns on capital, scale, and why today’s winners dominate indexes
42:00 The pace of change in technology and market structure
47:40 True, false, and indeterminate answers in valuation debates
52:00 Capital allocation, balance sheet risk, and surviving volatility
56:30 What really matters in 100x investments
58:30 Final thoughts and recommended reading

In this episode, Robert Hagstrom , Chris Mayer , Bogumil Baranowski and Matt Zeigler return for a wide-ranging conversation on how great investors really think. Rather than focusing on formulas, factor labels, or short-term market predictions, the discussion explores investing as a discipline grounded in philosophy, language, psychology, and long-term business fundamentals. Drawing on ideas from Warren Buffett, Charlie Munger, Bill Miller, and thinkers from outside finance, this conversation challenges many of Wall Street’s most common assumptions and offers a deeper framework for making better long-term investment decisions.

Topics covered in this episode

• Why value investing has nothing to do with price to earnings or price to book ratios

• The false divide between value and growth investing and why growth is a component of value

• How abstractions and labels distort decision making in markets

• General semantics and how language shapes investing mistakes

• Charlie Munger’s concept of worldly wisdom and the latticework of mental models

• Why reversion to the mean is a flawed way to think about markets

• The stock market as a complex adaptive system rather than a predictable machine

• Why most market forecasts fail and why people still believe them

• Myopic loss aversion and how frequent evaluation destroys long-term returns

• The importance of time horizon, patience, and long-term compounding

• How great investors think about conviction, uncertainty, and being wrong

• When to hold through difficulty versus when to exit an investment

• Lessons from Buffett, Munger, and Bill Miller on thinking independently

Timestamps
00:00 Value investing beyond ratios and labels
01:00 Introducing Robert Hagstrom and Chris Mayer
02:30 Investing as a subdivision of worldly wisdom
04:10 Abstractions, language, and Wall Street thinking
07:30 General semantics and investing mistakes
09:00 Latticework of mental models and interdisciplinary thinking
12:30 Buffett’s rejection of Wall Street jargon
18:55 Value versus growth and why the labels fail
23:40 Language, meaning, and investment errors
27:00 Time horizon, myopic loss aversion, and frequent evaluation
31:00 Sideways markets and where returns really come from
36:50 Complex adaptive systems and why prediction fails
40:00 Spurious correlations and false cause and effect
45:00 Forecasting, randomness, and the illusion of certainty
48:00 Conviction, expectations, and uncertainty in investing
50:00 When to sell and the cost of being wrong
54:30 Building an interdisciplinary investing framework