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
In this episode of Excess Returns, Matt Zeigler sits down with Kris Abdelmessih and Matt Cashman to break down one of the most important — and often misunderstood — concepts in options: gamma. They explore what gamma really is, how it interacts with delta and theta, why gamma scalping (a.k.a. delta hedging) matters, and what both individual traders and professionals need to know about it. If you’ve ever wondered how options traders actually make money from volatility, this is your guide.
Topics Covered
Why understanding gamma is critical to options trading
The relationship between gamma, delta, and theta
Using physics and middle school math to explain gamma’s role
How gamma P&L works and why it creates curvature in returns
Where gamma “lives” (at-the-money vs. in/out of the money, short vs. long dated)
The mechanics of gamma scalping and delta hedging
Why option trading is really volatility trading
The practical applications for retail traders and professionals
Common misconceptions about “income from options”
Timestamps
00:00 – Why gamma matters in options trading
02:22 – Defining gamma and its sensitivity to price moves
05:04 – Practical explanation: delta vs. gamma
09:00 – Physics/acceleration analogy for gamma P&L
18:00 – Mapping acceleration math to options gamma
23:30 – Where gamma lives: at-the-money and near-expiry options
29:00 – Introduction to gamma scalping (delta hedging)
36:00 – When gamma trading works best (volatility path dependence)
41:00 – Real-world applications for individuals and professionals
47:14 – Why selling options isn’t “guaranteed income”
What can bar bets, coin flips, and the length of your subway commute teach us about options pricing? In this episode of Excess Returns, Matt Ziegler is joined once again by Kris Abdelmessih to break down complex options theory into intuitive, real-world analogies. From prediction markets to probability distributions, Kris helps us understand how the options market reveals what the stock market often hides—how investors are pricing not just if something happens, but how much it matters when it does. This is options math with a twist, taught like you’re five, but ready for Wall Street.
📈 Whether you're an investor trying to size a high-risk, high-reward position, or simply curious about how the market “thinks” about uncertainty, this episode is full of mental models you’ll want to revisit.
📌 Topics Covered:
Coin flips vs. futures: the two dominant styles of betting
Over/under bets and what they teach us about prediction markets
Why odds ≠ probabilities—and how to convert between them
The difference between probability and magnitude in financial outcomes
Bar bets and beer-drinking contests on Wall Street (!?)
Using call spreads to isolate probabilities, not potential profits
A visual breakdown of skewed vs. symmetric return distributions
Why two stocks can have the same price but completely different implications
How the options market understood the dot-com bust better than most investors
Why thinking in bets makes you a better investor and allocator
⏱️ Timestamps:
00:00 – The stock market vs. the options market
01:42 – Over/under bets and their connection to options
05:59 – Understanding prediction markets and odds
10:00 – Future-style bets: Magnitude vs. probability
14:35 – The subway commute example and tail risk
19:00 – Why volatility and skew matter in pricing
20:38 – Stock A vs. Stock B: Same price, different outcomes
24:00 – Visualizing probability distributions
28:00 – How call values reflect both vol and probability
32:00 – Truncating the tail: turning options into “bar bets”
35:00 – Using call spreads to extract implied probabilities
37:00 – What investors can learn from this framework
39:00 – Options markets during the dot-com bubble
40:45 – Where to follow Kris online
🎙️ Guest: Kris Abdelmessih
🧠 Follow Kris’s work: https://moontower.substack.com
What if the biggest market moves aren't driven by fundamentals—but by flows you can't see?
In this episode, Brent Kochuba of SpotGamma joins us to explain the hidden mechanics of the options market that are quietly reshaping stock prices. We explore how dealer hedging, gamma squeezes, and volatility dynamics like Vanna and Charm are influencing everything from individual stocks to the S&P 500. Whether you're an active trader or a long-term investor, understanding these forces is crucial to interpreting today’s markets.
We discuss:
Why dealer flows are moving billions in stocks each day
What Gamma, Vanna, and Charm really mean—and why they matter
How implied volatility creates powerful reflexive market moves
Why options expiration dates often mark key turning points
What long-term investors should know about short-term flows
Real-world examples: GameStop, Tesla, Nvidia, COVID, and more
Even if you never trade an option, this conversation will change how you think about market behavior.
In this episode of Teach Me Like I'm 5, options expert Kris Abdelmessih breaks down one of the most foundational—and misunderstood—concepts in options trading: put-call parity. Using Lego analogies, homemade spreadsheets, and Fast & Furious references, Kris shows how options are like building blocks you can combine to create any payoff you want—including replicating a stock itself.
Whether you're a beginner trying to understand options basics or a seasoned investor looking for deeper insights into synthetic positions and implied interest rates, this episode is packed with practical lessons presented in the most approachable way possible.
What We Cover:
Why calls and puts are “the same” through the lens of put-call parity
How to visualize and replicate stock payoffs using only options
The concept of synthetic positions: synthetic stock, calls, and puts
How put-call parity collapses complex strategies into basic building blocks
The real mechanics behind covered calls—and what they really are
How professional traders use options pricing to infer interest rates and stock borrowing conditions
A deep dive into "box spreads" and how they replicate zero-coupon bonds
In this episode of our new show Teach Me Like I'm 5, we’re joined by Mat Cashman, Principal of Investor Education at the OCC, to break down a powerful yet often overlooked concept in options trading: the Rule of 16. Whether you're new to volatility or a market veteran, this conversation takes you from the sandbox to the risk desk, explaining how this simple rule transforms annualized volatility into daily insight—and how professionals use it to assess market surprises, portfolio risk, and trading decisions.
What We Cover:
What the Rule of 16 is and why it mattersTranslating annualized volatility into daily expectations
Why understanding standard deviation helps traders interpret large price moves
How experienced traders use the Rule of 16 to adjust to fast-changing volatility
Real-world examples including recent five-standard-deviation events
The psychological and behavioral impact of “surprising” moves on market participantsHow to build a daily baseline for expected price movement
Using the Rule of 16 to contextualize options positions and risk management