The other day, Stratechery had a great interview with Craig Moffett of MoffettNathanson ($), where he briefly noodles on the category of "TMT," or Tech-Media-Telecom. In a later, non-paywalled piece, he looks at the commonalities across these spaces: they all have high fixed costs and very low marginal costs, and shrink at least one dimension of reality—distance matters less with instantaneous communication, time matters less when you can enjoy content recorded rather than live, and software lets you do virtually what would otherwise require physical effort.

These kinds of descriptions are broadly true, but get fuzzy around the edges. If it's about fixed versus marginal cost, then TMTRP (Tech-Media-Telecom-Real Estate-Pipelines) is just as plausible. And non-TMT businesses compress dimensions, too; the shipping industry has certainly made the distance between Shenzhen and your local Target much less relevant. But that critique, too, applies to just about any industry you could name: Costco and Dollar General are both retailers, but Costco's economics revolve around converting real estate into recurring subscription revenue through massive discounts on bulk purchases of a small number of items ($), while Dollar General is more about opportunistically snapping up a somewhat random assortment of cheap inventory and making its profits the old-fashioned way: by selling stuff at whatever markup it can get.¹

It does make sense to bucket the TMT companies together, it’s just not entirely because of their economic commonalities. It’s partly because they're close together in the supply chain: if you don't understand what cable companies are up to and how movie studios are thinking, it's hard to have a coherent opinion on the long-term economics of YouTube and Netflix. And you can think of social media and search as somewhat figurative reimplementations of the physical hardware or delivery networks that got TV shows, movies, and newspapers to their customers.

There’s also a bit of path dependence here: "TMT" as a category is partly a creation of market forces, specifically an initial surplus of analyst headcount, followed by a surplus of alpha. The basic story goes like this: in the 90s, there were enough telecom companies, enough independent media companies, and certainly enough dot-coms that it made economic sense for an analyst to specialize in just one of those spaces. If that analyst was either lucky or mercenary, and had the right timing, the best of those spaces was Internet.²

After a few years of what was no doubt a very fun party for most of the people involved, the hangover set in: almost all of the Internet stocks crashed, most switched from mid- or large-cap to small cap; telecom went through a wave of bankruptcies; and M&A shrank the number of companies across the board. In short, an Internet analyst circa 2002 or so did not have a very interesting job: there were a handful of reasonably big companies, but most of the sector had either disappeared or reached a size where full-time research coverage didn't make sense.

Which raised the question: if the tech, media, and telecom teams have each lost about two thirds of the tickers it makes economic sense for them to cover, why not combine them into one team (with a third the headcount) and have them look at everything? Usually, this kind of decision can lead to fights over territory.³ But when everyone's just glad to have a job, they end up being more cooperative, so analyst teams consolidated to form TMT.

After a few more years, the Internet IPOs started coming back, the dot-com survivors went through corporate drama (Yahoo, AOL) or just kept on growing, and soon enough, there were more than enough stocks for analysts to go all-in on Internet. But by that time, entire TMT analyst teams could point to an impressive track record; online advertising mostly sidestepped the Great Recession, SaaS held up fairly well, and, in the post-crisis period, people started noticing that these Internet companies could grow at a surprisingly healthy pace for a startling long time.

But instead of investors deciding to draw stricter lines around their sectors, the economy made those lines blurrier. The convenience of pattern-matching struck again: Peloton is technically an exercise equipment manufacturer, but it doesn't make sense for the same person to cover small-cap stocks like Nautilus and Escalade, and also to cover Peloton when Peloton accounts for 98% of the market capitalization of the space. A SaaS analyst starts with better intuitions for Peloton’s economics than an exercise equipment analyst does: there's a high fixed cost to acquire a customer (pay a salesperson, ship a bike) followed by a stream of high-margin recurring revenue.

Companies in the TMT sector have another commonality: they’re unusually data-rich! There are lots of useful channel checks to perform, plenty of ways to get data, and the businesses are sensitive to the details of unit economics, like retention. Plus, a fixed data budget for an analyst can be amortized over more companies and over many more exploitable changes in investor sentiment in TMT than in other sectors. So even though index fund companies tried to even out the size of different sectors, the TMT designation stuck around.⁴

It was a random contingency driven by cost and org chart concerns that the same analyst would have covered the DVD-by-mail company and the cruise lines/resorts/theatrical/cable sports business. But it turned out to make a lot of sense when both of them became bets on streaming. At this point, to the extent that there's a critique of "TMT" as a category, it's that it's too narrow, not too broad; many other businesses are trying to move to a subscription model, and just about every company wants to ingest and analyze as many bits of information as possible about the world. In a way, anyone who's been a TMT analyst since the beginning has had a phenomenal career as a market timer: they bought into an industry, and a narrative, when both were looking pretty dicey. If they've held, they got the ideal investor outcome: they kept making more money, and they kept sounding more right.

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Read More in The Diff

The Diff is not a purely TMT-focused publication, but does cover the space a disproportionate amount—in part for historical reasons (I worked in tech and then mostly on TMT teams in my financial career), and in part for some of the reasons outlined above, i.e. the durable growth trajectories and frequent changes in investor sentiment. Some examples:

• The Surprising Durability of Google’s Growth ($) is all about how Google, and other big tech companies, performed well for second-derivative reasons: they’re outliers in how little their growth slowed once they got truly huge. Over very long periods, if other metrics are roughly constant, a larger and larger share of a company’s stock performance can be explained purely by revenue growth.

• The Value of Time Rounds to Zero or Infinity compares different software and media companies’ implicit attitudes towards the value of customers’ and users’ time.

• One other place “tech” intersects with “media” and both collide with “telecom” is when changes in the media distribution model change the economics of content.

• Another way tech companies are connected: they’re often one another’s biggest customers, so changes in investor sentiment can actually drive fundamentals by changing how fast growth companies spend.

1. Any generalization about any industry will run into fun exceptions—annoyingly, many of these exceptions crash and burn, but a handful make incredible long-term returns since their differentiation makes them hard to copy.

2. The 90s Internet boom was very rewarding to analysts for many reasons: the stocks kept going up, and the connection between analyst compensation and investment banking fees was much tighter back then. But the companies were also interesting and newsworthy; the analyst covering Netscape probably spent more time on CNBC than the analyst covering, say, Newell or Nucor. But perhaps more importantly for analysts' impact and ability to advance their careers quickly, dot-coms generally had little revenue and negative profits, so the valuation was more of a function of stories. And the analyst's job is to tell those stories. If Henry Blodget had been covering banks or industrials rather than dot-coms, he wouldn't have been able to set a price target almost 70% higher than the price of the stock after it had already risen 860% that year, and then see it hit the target in a few weeks.

3. This happened elsewhere, too. If you were a retail analyst, wouldn't you have more fun covering the retailer that's also big in cloud computing, logistics, and streaming media?

4. It's hard to get clean data on how big TMT teams were relative to other teams at hedge funds, and the ratio of TMT-specific firms to generalists is also hard to track, but anecdotally, it seems that TMT was the largest category of discretionary stock-picking, though not a majority of the performance fee-earning assets under management.

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