How much of your portfolio does a good investment idea deserve? Kris Abdelmessih of Moontower joins Matt Zeigler to explain why having an edge is only part of the decision: position size can determine whether favorable odds translate into long-term growth or damaging losses.

Through a coin-flipping experiment and everyday examples, Kris makes the Kelly Criterion accessible without a complicated derivation. The conversation explores the difference between expected returns and compounded wealth, why growth-maximizing bets can still be uncomfortable, and how uncertain probabilities make a case for betting less. From portfolio decisions to insurance and extended warranties, the goal is to build better intuition about how much risk to take.

Topics covered:

• How a favorable coin-flipping game exposed costly mistakes in bet sizing
• Why maximizing the expected payoff of one bet differs from maximizing long-term compounded growth
• How oversized bets can undermine an otherwise profitable opportunity
• The Kelly Criterion's three inputs: probability of winning, probability of losing, and payoff
• Why a constant percentage of your bankroll means changing the dollar amount after wins and losses
• How different payoffs change the appropriate size of a bet
• Applying the framework to hypothetical self-insurance and extended-warranty decisions
• Why full Kelly can involve substantial drawdowns, and the tradeoffs of fractional Kelly
• Working backward from a position size to the odds needed to justify it
• Allowing for uncertainty in your estimates and preserving capital for future opportunities

The essay behind this conversation:
After this post you will be sizing bets in your head
https://www.panoptica.com/after-this-post-you-will-be-sizing-bets-in-your-head/

Research discussed:
Rational Decision-Making Under Uncertainty: Observed Betting Patterns on a Biased Coin
https://arxiv.org/abs/1701.01427

Kris Abdelmessih's Moontower newsletter:
https://moontower.substack.com/

Moontower:
https://moontower.ai/

Kris Abdelmessih on X:
https://x.com/KrisAbdelmessih

Chapters:
00:00 Position sizing and the favorable coin-flip experiment
04:45 Why a good bet can produce bad outcomes
13:49 The Kelly Criterion formula explained
18:10 Adjusting your bankroll and accounting for the payoff
23:03 Applying Kelly to a self-insurance decision
30:25 Full Kelly, drawdowns, and reasons to bet less
34:59 Working backward from bet size and evaluating warranties
41:09 Volatility drag, uncertain odds, and the experiment's results
46:09 How much capital does your edge deserve?

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.

How do you learn from Warren Buffett without simply copying him? Gary Mishuris, managing partner and CIO of Silver Ring Value Partners, joins Matt Zeigler to explain why building your own investing process matters more than memorizing great investors' quotes, and how he uses AI to strengthen that process without outsourcing judgment.

Drawing on his experience investing and teaching, Gary Mishuris explores the lessons of Benjamin Graham and Philip Fisher, the balance between conviction and flexibility, and his own mistake of putting too much weight on valuation. He also shares practical examples of using AI to screen companies, challenge investment theses, and revisit existing holdings while keeping the final decisions in human hands.

Free online Value Investing Seminar signup
https://mailchi.mp/silverringvaluepartners/vis

Company Overview Deck Skill
https://behavioralvalueinvestor.lemonsqueezy.com/checkout/buy/22dc0ac3-5bae-4dec-a2e4-95b03ace4c6c
Gary's published code for 100% off the skill: YZMDK4NQ

Gary Mishuris' AI toolkit and workflow guides
https://newsletter.behavioralvalueinvestor.com/p/the-toolkit

Topics covered:

• Gary Mishuris' framework for learning from great investors: understand, apply, and customize.
• Why copying Warren Buffett's language or holdings is different from developing his depth of understanding.
• Combining the analytical rigor of Benjamin Graham with Philip Fisher's focus on business quality.
• What poker psychology reveals about investing under pressure, and why paper portfolios cannot replicate the emotional stakes.
• Finding an investing style that fits your temperament while balancing conviction with a willingness to change your mind.
• Gary Mishuris' biggest mistake: focusing too much on cheapness and too little on how businesses were changing.
• Where AI can amplify an existing investing edge, and why a polished report is not the same as a capable analyst.
• Using Company Overview Decks to decide which ideas deserve deeper research, including companies in Japan.
• Using AI as a devil's advocate to test assumptions, surface risks, and reassess long-held positions.
• Focusing on the research process and decisions you can control as markets and technology evolve.

Timestamps:
00:00 Gary Mishuris and the Value Investing Seminar
05:28 Learning from Warren Buffett without copying him
12:59 The curriculum: analysis, business quality, and psychology
19:07 Why the investing masters' historical context matters
25:50 Balancing conviction and flexibility
30:42 Gary Mishuris on his biggest investing mistake
35:29 Moving from AI chatbots to an investing workflow
42:24 Company Overview Decks and screening investment ideas
49:06 Building a devil's advocate into the research process
59:58 Adapting your process and controlling what you can

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.

In this episode of Teach Me Like I'm Five, Matt Zeigler sits down with Matt Reustle of Business Breakdowns to unpack how great businesses actually work, why pattern recognition matters more than stock picking, and what investors can learn from studying the economics, value chains, and management decisions behind the world’s most durable companies. This conversation breaks down how to analyze a company from first principles, what separates good businesses from great ones, and the recurring traits shared by long-term compounders. If you want to improve your investment process, understand business models, or learn how elite analysts think, this episode delivers a masterclass in fundamental analysis and business pattern recognition.

Topics covered:
• How to start analyzing any business from scratch
• Understanding revenue models, value chains, and industry economics
• The difference between transactional and recurring revenue
• Why aftermarket services can be more profitable than product sales
• How cash flows through an industry and who captures the value
• Examples of hidden compounders in everyday industries
• What business breakdowns reveal about macro environments
• How investors should think about secular tailwinds vs GDP-level growth
• The three traits shared by exceptional companies
• The critical role of management teams and financial hygiene
• Capital allocation lessons from top operators
• Why durable tech growth is so hard to evaluate
• How intangibles shape competitive advantage
• What Amazon, Robinhood, and other companies teach about evolution
• The hidden business value inside SpaceX and Starlink
• Whether overall business quality has structurally improved
• Why pattern recognition is more valuable than gut instinct
• The single most important question to answer when analyzing a company

Timestamps:
00:00 Understanding what drives repeat sales
00:09 How businesses really make money
01:09 Opening and guest intro
02:00 How to begin researching a complex company
04:49 Using investor presentations and sleuthing for insights
05:12 Non-obvious revenue drivers in major industries
06:20 What to look for in early discovery
07:00 Mapping value chains and cash flow dynamics
08:46 Who captures value in industries like oil and gas
10:20 What 150+ business breakdowns reveal
10:48 Surprising hidden compounders
12:28 Lessons about industry cycles and secular growth
14:52 How to think about next steps after understanding a business
17:34 Pattern recognition in investing
18:00 How much work it really takes to understand a company
19:00 What rigorous analysis teaches you
20:44 Traits that separate great companies
21:24 Self-reinforcing sales models
23:00 Financial hygiene and cash economics
25:15 Adaptability as a core business superpower
25:44 How these insights evolved over time
27:31 Evaluating management teams
29:42 Capital allocation as a defining skill
32:02 How tech companies evolve and compete
34:15 What makes durable tech growth difficult to judge
36:11 Understanding intangibles and company DNA
38:16 The difference between real and exaggerated narratives
41:04 How companies like Amazon repeatedly reinvent segments
42:14 Why some companies survive major failures
44:24 Breaking down Apollo’s complex business
47:00 Lessons from Home Depot
52:00 What GE teaches about cycles and capital allocation
55:27 How to understand SpaceX as a real business
58:28 Has overall business quality structurally improved?
01:02:00 Why pattern recognition matters more than stock picking
01:04:33 Missteps and lessons
01:06:00 The single most important metric to identify
01:07:00 Where to find Matt Reustle online