In this issue:
- Is "Social" an Enduring Category or Just a Phase?—The big growth areas in social apps are mass media in the form of short video, and private communication through messaging and group chats. This is part of a broader pattern where purely social apps tend to get momentum and then slow down, as users specialize in either creating content or consuming it.
- The Carbon Discount Rate—Indonesia's increased nickel production has also led to higher coal consumption. Whether this is net good or bad from a climate perspective depends on what discount rate you put on emissions.
- Alternative Data—The single most important piece of alternative data for hedge funds remains what it's been for over a decade: anonymized data on spending patterns. The data itself has gotten more commoditized, but the analysis is still differentiated.
- Transitory Lessons—The current economic situation is a central banker's dream: steady growth, declining inflation, and plenty of room to cut rates if necessary. But that also means that whatever happens next gets blamed on their actions, not their reactions.
- App Economics—As it turns out, Reddit's API was, for many apps and their customers, completely worth it.
- Where Does the Basis Trade Come From?—An attention-grabbing trade as a template for financial specialization.
Today's issue of The Diff is brought to you by our sponsor, Percent, which offers investors access to private credit markets.
Is "Social" an Enduring Category or Just a Phase?
In 2011, Google tied every employee's bonus to their social efforts and started sticking "+1" buttons onto every other Google product. This effort ended ignominiously, with Google's core social product, Google+, limping along for a few years and then being shut down after Google discovered a security flaw that could expose user data. Google still has products that enable social interaction, like Gmail and whatever the current name of their current most-favored-chat-app is. And YouTube might support more parasocial relationships than any other platform. But the pure bet on "social" didn't work out.
Google, of course, has a reputation for launching splashy products and then quietly killing them (though they seem to have gotten better recently, aside from things like the death of cached pages). But they're not the only ones. Plenty of other companies have started with a peer-to-peer model and moved towards something that looks a lot more like a two-sided network:
- Lending Club's original idea was that some people would log in to get better-than-a-certificate-of-deposit returns on fairly short-term loans, while other users could consolidate debts or pay for a big one-time expense. But over time, more and more lending came from credit funds that specialized in crunching numbers on weird debt. Those funds could take some of the models they already used for consumer debt products like credit card ABS and repurpose it to underwrite individual loans at scale.
- Airbnb found that side-hustle part-time landlords were less scalable than full-time professionals. There's a wide range there, naturally, from people who downscaled their income and lifestyle by keeping their home in a nice city, buying a smaller and cheaper dwelling in a slightly less trendy location, and using the original home as a source of retirement income and a part-time job.
- The original eBay model was that people would clean out their attics and sell their appreciated collectibles to one another. This business still exists, but isn't as important as fixed-price sales from repeat sellers, i.e. small merchants.
And it's also striking to look at two of the biggest growth areas in social media right now. First, short-form video, and second, group chats. These are both on the social media continuum—there are long-tail creators in short video, and some group chats are large enough that they're closer to a miniature Twitter than a one-on-one chat. But they're both at far ends of the "social media" medium. A group chat is close to private communication, and a lot of their growth has come from that same privacy—part of the trouble with seamless shareability in social is that anything you say that only makes sense with context can still reach escape velocity and achieve a mass audience of maximally uncharitable people. And even though video creators tend to start out as independent creators working out of their bedrooms, more and more viewing comes from professionals who operate out of third-party studios or run their own.
This points to an interesting possibility: what if purely social products have a finite life? eBay could be the most illuminating example here: beanie babies, rare coins, no-longer-beloved heirlooms and the like provided the potential energy for a one-time creation of a powerful network. Some parts of the network were one-sided, with inveterate collectors disposing of some products in order to buy something else in the same category. But many more were naturally one-time users: liquidating some assets they didn't really want, or finally getting their hands on something they did.
But what eBay got from that orgy of beanie baby speculation and ruthless rare coin arbitrage was the beginning of a two-sided network: customers shifted to buying more fixed-price products, sellers moved in that direction as well, and now the company is a mature e-commerce platform, one that would be a lot bigger if it had embraced first-party business and logistics the way Amazon did, but still a viable business that generates billions in free cash flow each year.
One of the questions people designing social products have to ask is: how do relationships scale? It's obvious that people can sustain meaningful relationships with close friends, family members, a spouse, etc. But there are clearly limits; someone with thousands of friends usually doesn't have many, or any, close ones. Broadcast as a general concept has existed for a long time (it's arguably not just pre-printing press but pre-literacy, given that some older texts—the Bible, Bhagavad Gita, Odyssey, etc. were oral traditions before being written down, and seem to have had some level of mass distribution without needing to be a mass-produced text. So we've long had distinct categories for flesh-and-blood individuals we interact with regularly, and for quasi-mythic people—the Emperor, the President, Taylor Swift—for whom the relationship is real to us but meaningless to them. Those relationships are closer to media consumption than to personal conversation. They're also much, much more scalable than conversation. It's a necessary consequence of days being 24 hours for everyone that the people with the most interesting lives are the people with the least free time to document them, so the median piece of social media content is, through selection effects alone, pretty boring.
Social media companies have built apps that absorb a billion-plus hours of attention each day because they can highlight the small set of updates that are interesting to people. But there's a whole industry devoted to creating content that's interesting to a large audience: the media business, minus the social. And that is increasingly what social media looks like: some content sponsored by big companies, some content sponsored by smaller ones (who often monetize through bigger ones), and, just to keep things interesting, some life updates from people you know.
This is not just content, though; it's training data. The place where peer-to-peer systems really shine, whether it's early eBay, forum culture, or modern, Twitter, is connecting people to niche interests they didn't realize anyone else would ever share. But over time, the requirement that some other human being share your exact interest gets weaker and weaker, because every interest can be described as some sort of latent space, i.e. a cluster of existing content or statistically-equivalent hypothetical content that satisfies someone's interests. This isn't social, since there isn't an author on the other side of the screen. It's not mass-media, though, because nobody's experiencing the same media. Instead, it's an exit from social.
Social as a model works when people have about as much to offer as they want to receive along a given axis. But no trait is distributed uniformly; there are are outliers in the nice-to-look-at, nice-to-listen-to, nice-to-read, nice-to-get-stock-tips from axes, there's a population that can offer a respectable performance with these traits, and there's a substantial majority with below-mean performance. So, over time, most platforms end up with a more consolidated list of suppliers and a dispersed set of consumers. The shift in progress is that the platform itself is positioned to be a content supplier, too; AI really shines with never-before-seen search queries. And when that happens, the temporary oversupply of some content category that kickstarts social sites won't exist any more, and social will be a strictly inferior model to generative AI. There will still be room for messaging, and for community-based apps and chats, but the communities will be largely preexisting, rather than accreting within a larger platform. There was a time when connecting people online produced value automatically, both socially and for shareholders, but that time was due to particular circumstances that couldn't have held true forever.
Disclosure: Long META
For a long time, the meme was that Google only awarded promotions to people who shipped a new product, but that these promotions often involved the sponsor abandoning the project; whoever else ended up running it wouldn't expect a promotion without launching something. So their incentive is to kill it as fast as possible. Somehow, beanbag chairs and fancy food notwithstanding, its corporate politics were red in tooth and claw. Anecdotally, Google has moved away from this approach over time, but they still have the persistent question of whether a given person's effort is better spent launching something totally new or adding another basis point to search revenue. Ironically, as with tech as a whole in certain market cycles, a part of Google that isn't producing material revenue is safer than one that is, because it can't be directly compared to an existing business. Given the choice, a 100x price/sales ratio is harder to justify than a price/sales ratio of #DIV/0! ↩︎
For sarcastic tweets, a good measure of virality is: has someone who actually agrees with the point you're making furiously corrected you, and possibly threatened to kill you, because they missed the joke? That's viral! ↩︎
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The Carbon Discount Rate
Indonesia's industrial policy around increasing nickel production to contribute to green energy has led to an increase in coal consumption, too ($, WSJ). This story partly highlights the importance of coming up with a rigorous climate discount rate. There are some activities that produce net emissions in the short run but reduce them long-term, and others with the opposite setup, but in either case knowing which one matters means knowing what the tradeoff is between present and future emissions. As things stand today, we don't even know what the term structure looks like. For example, planting a tree today extracts carbon as the tree grows, sequesters it when the tree is mature, and then releases it again when the tree dies. Is the impact of that release bad enough to offset the impact of reducing emissions now? The answer is probably yes: if you have to do emissions some time, doing them in a richer future with a lower cost of carbon capture is probably better. But we won't have a good sense of what those future variables look like without more sophisticated pricing today. The alternative model is to just insist that coal consumption monotonically decrease while renewables increase (or total power consumption goes down). But that's like managing a company with a mandate that they need to be free cash flow positive every day, or every hour—the nature of investments in general is that they're worth making when the cost of the current outlay is exceeded by the benefit of future profits, so knowing when that happens is valuable for an investment theme that has so much money aimed at it.
More than a decade ago, sophisticated hedge funds were looking for alpha by licensing anonymized spending data and then using it to predict companies' revenue trends. This is still a big business, and still a source of differentiated ideas, even though credit card spending data has been widely available for a long time. Sometimes, strategies will go through a cycle where the initial version is data-constrained, but periodically offers the opportunity to make a quick 10% return, and later on the situation evolves into 50x the opportunities to make a 1% return, i.e. still better, but with worse trade-level performance.
But another perspective on data is that it actually increases the potential rewards from an analyst's work, by increasing the number of conclusions someone can meaningfully derive. The same credit card data, sliced by two different people, could tell one person that the company in question is growing faster than expected and could tell another that their low level of repeat customers indicates that their growth must come from some kind of heavy marketing campaign that also isn't landing with its audience. A fundamental uncertainty about how the business is doing gets replaced with a more abstract uncertainty about whether or not the people running the business know what they're doing.
This scales more broadly than finance. Increasing data availability, and better tools to analyze it, means that the low-hanging fruit gets picked faster. But it also means that broad theories that explain a little bit about many different domains are more easily accessible, and that meta bets about how someone might optimize for an easily-tracked metric at the expense of a more meaningful but slower-to-update one are more valuable.
Central banks have been deliberately vague about the path of rates recently, in part because they don't want to make any unforced errors ($, FT). If you'd asked a central banker five years ago about their dream economy, they'd probably describe early 2024: robust growth, decelerating inflation, low unemployment, and interest rates high enough that there's plenty of room for monetary policy to have an impact. (The central bankers of 2019 would be quite surprised at how we got to this point.) Paradoxically, a goldilocks economy is an awkward position for a central banker: when all trends are pointing in the right direction, any policy change they make gets seen as directly responsible for future inflation spikes (if they ease too fast) or a recession (if they keep rates too high). And, given enough time, at least one of those two outcomes is inevitable. Dealing with a crisis may be harder day-to-day, with many more unpleasant surprises and last-minute ruined weekends. But at least it's also a problem where the general direction the bank needs to head in is obvious.
Seven months after Reddit increased its API fees for third-party apps, a few have shut down, and the remainder have adapted, either by charging for their services or by limiting usage. Some of these apps were addicted to fantasy economics and had built their entire business model on getting Reddit's content for free, but for the rest, it turns out that the app did something users valued, that they were willing to pay for, and that the amount they were willing to pay both defrayed Reddit's hosting costs and left some room for margin. Most companies won't have a similar ecosystem, where the same content can be worth paying for in several different ways through multiple interfaces, but at least in Reddit's case, the economics shook out fie. It will be interesting to see Reddit's financials when their IPO launches in March. It's possible that they've set prices in a way that lets them be agnostic about whether users are monetized by ads through a first-party experience or monetized by charging app developers for the third-party one instead.
Where Does the Basis Trade Come From?
There was a flurry of news coverage of the treasury basis trade last year, including in The Diff ($). The big question was whether there is some kind of systemic risk from lots of hedge funds continuously making massive bets on the spread between treasury bonds and treasury futures. But one question that doesn't come up as often is why the trade exists in the first place. Futures and underlying products get arbitraged all the time, even in the physical commodities world where that arbitrage actually involves making sure physical oil is somewhere in the vicinity of Cushing, Oklahoma. There is a reason ($, FT): futures are much more convenient to trade, and offer built-in leverage; active fixed-income managers who take credit risk are shortening the duration (if you switch from a 10-year bond paying 5% to a 10-year bond paying 8%, you're probably buying something with a higher default probability—but becaues more of your returns come earlier, you're taking lower rates risk, and if you're tracking a benchmark that includes credit and rates risk, you need to add to your rates exposure to match it). So what the trade really illustrates is that different investors specialize in different sides of the balance sheet: if one investor is going to spend their time thinking about assets, they need to pay someone to think about the liability side.
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