A fundamental part of the capital asset pricing model is the idea that, if you don't have an edge in selecting individual investments, diversification is an economic free lunch: your average return stays the same whether you put all your money into one stock or into a portfolio of a thousand, but your volatility is lower. And that benefit accrues even more when you diversify across asset classes, or across strategies.

But there's more to life than money. There is, for example, time, including the time you spend earning money in order to spend it enjoyably. Which raises the question: can we apply the same logic of diversification to time? This is really asking two questions: first, is diversification across different activities the same kind of "free lunch" as diversification of money across investments? And second, if that's theoretically true, is there a practical way to implement it?

The practical question is the easiest to address, because back in the day, when transaction costs were higher, diversification in the stock market was not a practical thing to do. This paper estimates that individual investors who used standard mutual funds before the introduction of index funds were outperformed by the market by around 1.4% annually. That’s because while an investor in the mid-60s could try indexing themselves, the commissions on small orders were nearly 3%, before other transaction costs. Someone buying $10,000 worth of each stock they bought would only pay commissions of around 0.5%, but that still implies investing $300k just to replicate the Dow (43x the average annual family income at the time).

But one thing that sets finance apart, and makes it such a good source for mental models that can apply elsewhere, is that today transaction costs are low. For example, the cost of dumping all of your shares of a consumer Internet company and putting the money into Nvidia is trivial, but it would take years to pivot from being a frontend developer to being a hardware designer.

It's also easier to be cross-disciplinary when you’re investing money instead of time. Every company has a balance sheet, income statement, and cash flow statement. And even if these work differently for, say, an insurance company compared to a movie studio, the basic goal of maximizing risk-adjusted returns on capital over time is consistent. In fact, the relative similarity of financial statements across different industries is a fruitful way to make productive analogies: foot traffic for a physical store is analogous to good SEO for an online retailer, for example; a valuable building that's held on the balance sheet at cost is similar to network effects, company culture, and other valuable intangibles.

But in fields where success has metrics besides money, it's much harder to standardize inputs and make relevant cross-comparisons. Brain surgeons and movie directors both have to work hard and study their craft, and it's possible to fail at either of them, but measuring success accurately is harder.¹

But there are some limited kinds of career/time diversification that can pay off. These include:

• Pairing a narrow, domain-specific skill with one that has broader applications—where, depending on the domain, broad skills could include sales, writing, programming, or accounting. The goal here is to optimize for situations where someone wants the best Y conditional on being very good at X—a 90th percentile geologist who can make an effective presentation, a 90th percentile data scientist who can summarize results in a succinct memo, a 90th percentile hardware designer who can understand whether a given design can actually be cost-effective at scale, etc. This has the nice trait that it increases the payoff from success in a chosen career while mitigating the worst-case scenario (by leaving room for a pivot).²

• If you can't do this in your career, you can do it in your hobbies. A decent barbell approach here is to optimize for immediate money 9-5 and optimize for surprise and learning on nights and weekends.

• Deliberately under-consume real estate: real estate prices are still a rough proxy for local labor markets (even in cases where people move somewhere for the natural surroundings or urban amenities, high enough housing prices can set an economic minimum wage well above what it otherwise would be). If you buy real estate, you're betting that the local labor market will remain strong. Even if you rent, you're constraining your options.

• Marry your complement. In practice, this is hard to implement. How do you encounter someone who's your polar opposite in the first place? What do you talk about on dates? But in practice, what it tends to mean is marrying a complement within a narrow range; there are many happy couples where one of them is extremely introverted and the other is on the friendly end of introversion, or where both of them are high-agency but in different domains.

Fundamentally, there are limits to diversification, and they're driven by uncertainty and transaction costs. In asset allocation, you have a wide range of products that are in some sense comparable—a corporate bond is just a treasury plus some risk; most of the news that's good for one oil company will be good for another (and probably bad news for an airline or basic chemical producer). But in real life, the theoretical argument for diversification is just as sound—the practical task is much harder. So we can take comfort in another aspect of the argument for diversification: it has steeply diminishing marginal returns, and you get most of the total available benefit from just doing a bit of it.

Of course, you do face a cost. Skim the Forbes 400 and you'll find plenty of people who made their fortunes in a diversified way, whether it's assembling a conglomerate, running a multi-manager hedge fund, or making index funds more accessible. But you'll find far more people who made all of their money from one asset; usually a company they started and ran. But even in those cases, you'll still find evidence for diversification: Bill Gates could have devoted less time to negotiation and strategy in order to spend more time learning about low-level assembly language tricks, but he got better marginal returns elsewhere. And Sam Walton didn't spend all of his time thinking about how to run his existing stores; he also had hobbies, like flying (to scout out locations for new stores). Even if you're going to be obsessively focused on one thing, that "one thing" will probably turn out to be the intersection of a complicated venn diagram. So even if you're relentlessly focused, diversification pays off.

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Read More in The Diff

The Diff often talks about the power of diversification, and the tradeoffs involved. Sometimes this is explicit, but it’s often the subtext of pieces about specific tricky decisions or categories of challenging scenarios. For example:

• In Just One Thing or Every Single Thing? we look at two related phenomena, that of companies’ side projects and distractions that turn into parts of the core business, and that of CEOs doing individual contributor-style work (writing code, handling customer service issues) well past the point where it makes direct economic sense.

• The Startling Convexity of Expertise is a model of learning in fields where there are power-law rewards, meaning that an obsessive commitment to maximum knowledge pays off.

• Correlations go to One, in Good Ways and Bad: crashes are a case where diversification pays off less than it should, because many trades go bad at once. It’s not the only instance of this.

• Growth, Diversification, and Shaky Foundations ($) considers the payoff for diversification within a single company, with Atlassian as a case study.

• And closing things out, Heuristic/Model Synthesis ($) asks whether or not professional investors can apply some of the challenging but hard-to-argue-with theoretical results.

1. In movies, it's often the case that the most skilled personnel get access to the best opportunities, but in medicine a good specialist is someone who gets the hardest cases; it's at least theoretically possible that if medical talent is allocated perfectly and everyone tries their best, the most effective specialist is also the one who loses the most patients.

2. This kind of approach to skill development is sometimes described as "spiky," by sources ranging from science fiction author Bruce Schenier to Enron ex-CEO Jeff Skilling.

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