The study of how humans make decisions is something that’s endlessly fascinating—especially as it relates to investing theory. This week, three investors —Elliot Turner, Philip Ordway, and John Mihaljevic—discuss this subject on their podcast,This Week in Intelligent Investing. They cover so many important elements of investing behavior: anchoring bias, overconfidence vs. humility, planning fallacies, the ostrich effect (i.e. sticking your head in the sand when you’re wrong), framing effects, and so on. I particularly liked Ordway’s comment that “everything is a probability-adjusted bet.”
“By far, for me, the three most important words in investing are, ‘I don’t know.’ If I take that attitude—that everything has a probability, I don’t often even know what that probability is… but that I’m trying to take what I know and disprove it. I’m looking for disconfirming evidence. I want people to disagree with me.”
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When price and value diverge, opportunity exists
A core challenge of outperformance in the market often comes down to approach to valuation—the better your framework, the better chance you have at succeeding long-term at identifying mis-priced securities. Okay, but how? (Well, that’s what makes this fun and challenging). Alfred Rappaport and Mike Mauboussin, authors of (the now-updated) Expectations Investing, offered a peek behind their own valuation framework—which they call an “expectations infrastructure” for valuing stocks—in this week’s Financial Times. It’s a good short read, but I like their strategy which “views the world probabilistically… and overcomes the shortcomings of traditional analysis that uses multiples.”
“Investors also like to compare the multiples of companies with those of peers when seeking the most promising investments. Indeed, psychological research shows that people are good at discerning relative attractiveness of stocks. The problem is that price may differ from value for all the stocks being compared. And while multiples save time, they also lack clarity because they conflate the key drivers of corporate value such as sales growth, profit margins and investment needs.”
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Is lab-grown meat our salvation—or an expensive distraction?
Over the last few years, I’ve seen the same narrative repeated over and over: meat is terrible for the environment, and lab-grown or synthetic meat is the long-term solution. The problem is that, while the first part of the statement is almost definitely true, the latter—that lab-grown meat is the answer—is not exactly proven. “Splashy headlines have long overshadowed inconvenient truths about biology and economics,” Joe Fassler wrote this week in a sprawling deep-dive on the lab-grown meat market. “Now, extensive new research suggests the industry may be on a billion-dollar crash course with reality.” It’s a long piece, but one of the better analyses I’ve come across on the “future of meat” topic.
“Who’s right? Is cultured meat our best hope to save the climate, a billion-dollar boondoggle, or something in between? Will it ever make sense to produce food the way we currently make our drugs? The stakes couldn’t be higher. In August, the United Nations released a nearly 4,000-page report amounting to what it called a ‘code red for humanity’: Unless the world’s nations make a vast, coordinated effort to stop burning fossil fuels and razing forests, we’ll find ourselves locked into an even more dire, unforgiving future than the one we’re facing now. At a time when bold environmental solutions are needed, we can only afford to direct public and private investment toward solutions that actually work. But without looking more closely at the fundamentals—something media has largely declined to do—we can’t know whether cultured meat is our salvation or an expensive distraction.”
“IBM was once — and still is, for people whose main sources of information about technology are television ads during sporting events — an American innovation icon, a company that literally created what we now think of as information technology. Its fortunes have risen and fallen with broader trends in computing, but around the time of that meeting in late 2013, its business and technology reputation began a steady decline that it has yet to avert.”
“Freud claimed that technology only solved problems that technology itself had created. The alienation and malaise caused by one modern invention was momentarily relieved by another, a process he compared to ‘the enjoyment obtained by putting a bare leg from under the bedclothes on a cold winter night and drawing it in again.’ Nobody seemed capable of articulating what problem these language models were designed to solve. There was some chatter about writing assistance, about therapy bots, about a future where you’d never have to write another email (‘Can A.I. bring back the three-martini lunch?’ asked Fortune), all of which seemed to skirt the technology’s most obvious use: replacing the underpaid and inefficient writers who supplied the content that fed the insatiable maw of the internet — people like me.”
“As ESG investing has been accelerating, the planet has experienced the warmest two decades on record, Antarctica has been melting, U.S. income inequality has been gapping, and species have been disappearing at rates unseen for millennia. And the Dow Jones Industrial Average is hitting new highs and asset managers are collecting attractive fees to oversee a popular new investment category. Here’s what’s wrong. Investors are finally taking ESG investment seriously. But as currently practiced, most ESG investing delivers little to no social or environmental impact.”
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Reflection doesn’t come naturally to me, but writing—especially for others—makes it non-negotiable. These aren’t just lessons. They’re pieces of a year that shaped me.
