Episode Summary
Executive Summary: Patrick O’Shaughnessy and Michael Mauboussin dissect active vs. passive investing, behavior gaps, public-listing decline, and how to build moats using base rates and shrinkage toward the mean. The episode argues that market structure, regulation, technology, and investor behavior have reshaped returns—and that analysts need both narrative and data to find edge.
Main Topics: Active vs. passive equilibrium (Priority: 5/5): Markets need enough inefficiency to justify active research, but too much competition compresses alpha and fees. Behavioral gap and dollar-weighted returns (Priority: 5/5): Investor timing errors can matter more than fee differences and transfer wealth to corporations. Decline in public listings (Priority: 5/5): Fewer U.S. public companies push value into private markets and reduce the public investor opportunity set. Base rates and forecasting (Priority: 5/5): Forecasts improve when inside views are tempered by outside-view base rates and regression to the mean. Defining and measuring moats (Priority: 5/5): Moats are sustained excess returns driven by industry structure, tradeoffs, and firm-specific advantage. Applying the frameworks to asset management (Priority: 4/5): The industry faces compression, but opportunities remain in alternatives, non-U.S. markets, and forced-flow situations.
Key Arguments: Alpha has fallen faster than fees, so active/passive is rebalancing toward lower costs. Behavior gaps can exceed fee savings; Didchev found 120 bps/year on average. Passive flows can raise valuations, increase correlations, and weaken liquidity provision. Public-company count is down despite GDP/population growth, shifting gains to private markets. Base rates matter because many growth and earnings forecasts regress hard to the mean. Moats depend on industry economics plus firm tradeoffs, not just branding or size.
Data Points: Behavioral gap: 120 basis points per annum - Didchev’s global study of dollar-weighted vs. time-weighted returns Average index fund fee: 20 basis points - Discussed as the 2015 average across index products Average active fund fee: 80 basis points - Discussed as the 2015 average across active products Fee differential: 60 basis points - Index vs. active average fee spread Amazon 2015 sales: $107 billion - Used to illustrate the inside/outside view base-rate forecast Amazon 2016 sales: $136 billion - Used to show the company was already ahead of a 15% growth path Amazon growth forecast: 15% through 2025 - Example of an analyst’s inside-view projection Historical sample: 313 companies - Companies with $100 billion of revenues since 1950 used in the base-rate analysis Observed base-rate result: exactly zero - Number of companies in the sample that grew 15% or more for 10 years U.S. listed companies vs. 1976: less than what it was in 1976 - Shows long-run decline in public-company count U.S. listed companies vs. 1996: down 50% - Peak-to-present decline in listed firms IPOs per year, 1976–2000: about 280 per annum - Historical average IPO cadence IPOs per year, since 2000: about 115 per annum - Reduced listing pace in the modern era U.S. public equity value creation: $110 billion - Facebook’s market value at IPO mentioned as value created before public investors could access it Amazon IPO market cap (2016 dollars): $625 million - Illustrates how early public investors captured a huge run-up Facebook IPO market cap: $110 billion - Illustrates late-stage private appreciation before listing Unicorn aggregate value: $500 or $600 billion - Approximate private-market value sitting outside public markets Private equity fees vs. returns: almost 40% of the pie - CalPERS example showing GP fee take relative to total returns Indexing liquidity support: $3 trillion less in active management - Estimated reduction in active-liquidity supply over the last decade Consumer staples ROIC shrinkage factor: 0.9 - Example of high persistence in returns on capital S&P 500 year-to-year correlation: zero correlation - Used to show annual market returns are mostly noise S&P 500 value mix: about two thirds steady state and one third future value creation - Historic decomposition of business value since 1961
Pivotal Quotes: "markets have to be efficiently inefficient" — Michael Mauboussin: Explaining why perfect efficiency is impossible and why some alpha must remain "You haven't accomplished anything until you're liquid." — Bill Gurley: Used to argue that private-market gains matter less without realizable liquidity "the gap between those expectations and that fundamental performance that's the key to making money" — Michael Mauboussin: Summarizing how investors can find edge through expectations analysis
Implications: The open question is where future edge will survive: investors should focus on expectations gaps, liquidity stress, and markets where forced flows or lower efficiency still create mispricings.
From the Transcript
And as a compensation for that cost, there should be a requisite benefit in the form of inefficient markets. So, Professor Lasse Peterson's got this phrase, which I love, called markets have to be efficiently inefficient. Enough inefficiency to get people to keep doing this, but not so efficient that there are a lot of money laying around. So, that model, Grossman Stiglitz, I thought, was always for me very motivating. So, now the question is: how much available excess return is there? So, how does one think about that? So, you mentioned a moment ago the model by Jonathan Burke and Richard Greene, and I think that's a really nice way. To approach that. So these guys said, you know, this is here's one of the ways to think about this. By the way, usually when we give data on mutual fund performance, we'll say X percent outperformed the market or the standard deviation of performed some number. But the challenge is every fund is the same. You know, whether you're 100 million, a billion, or 100 billion, you're like counted as one datum. And as we know, what we really need is to have it all asset weighted for the most part. So what these guys said was, here's a way to think about this: is to evaluate fund performance just as you would evaluate firm performance.
So, there's just fascinating market dynamics happening underneath all this. Why? How could this change? So, your friend Bill Gurley has a great quote I always love using, especially when talking about private markets, which is something like: you haven't accomplished anything until you're liquid, and for the obvious reason. And he's a big proponent of more companies going public. I think literally just yesterday, or maybe it was even this morning, Fred Wilson at Union Square Ventures wrote a piece about kind of an ode to going public and thinks that a lot more companies should go public. Because when you're public, it imposes transparency, accountability. It makes companies better. That if you're going to lose your biggest customer or have a management problem, it's very public. So it imposes sort of a discipline on companies, which is a good thing. So if there's these positives to being public, what are the negatives that are holding companies back? Why isn't Uber public, for example? Maybe not them in particular, but more generically. And is it something we can fix? Because it seems like we've got.
With your example on the Fang stocks. So, one of the key ideas always to go back to in investing is that you need to dwell fundamentally on the difference between expectations, what's priced in, and what's going to happen in terms of corporate performance. And it's really the gap between those expectations and that fundamental performance that's the key to making money. So, stock prices or any asset price reflects a set of expectations about future financial performance. So, step one is really to say what has to happen for this stock price to make sense. Step two is to say, based on your strategic and financial analysis, how is this company going to perform? And you're looking for mismatches. Those are your opportunities. So the base rate work obviously is going to be very helpful in guiding that thought process, as you point out. If expectations are very high, by the way, sometimes expectations are high and they're fully justified. Company actually does everything it hoped and delivers the results. Other times they're completely not justified. So that to me would be sort of the key idea there.
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