(This investment thesis also appears on the buy-side investment platform, SumZero.)
The choking uncertainty around U.S. economic policies caused me to abandon Meta Platforms, Inc. (META: $592.49/share) with all the grace of a dog caught ripping up the sofas. This uncertainty opened up a possibility that seemed inconceivable before: that Meta might be grievously harmed. That oft-quoted remark, oft misattributed to Vladimir Lenin, “There are decades where nothing happens; and there are weeks when decades happen”, came to mind. The recent announcement by U.S. Secretary of the Treasury, Scott Bessent, that the United States and China have agreed to swingeing albeit temporary cuts to existing tariffs, leaving them at the baseline rate of 10% for Chinese tariffs on US goods and 30% for US tariffs on Chinese goods -10% baseline plus the fentanyl-related tariffs-, has made U.S. markets and Meta specifically, more palatable. That announcement provides a safe entry point for the firm I believe is the most compelling investment proposition among U.S. large caps, a business I have long admired, and sometime held.
A History of Exceptional Growth and Profitability
It is easy to see why Meta generally trades at a premium to its economic book value. From 2011 to the last twelve months ended in the first quarter of this year, Meta compounded revenue by 31.43% a year, and compounded net operating profit after tax (NOPAT) by 33.69%. Meta’s exceptional performance has carried on even in the last five years when it has been one of the largest companies ever, with the company having a 5-year sales CAGR of 14.66% -Credit Suisse’s “The Base Rate Book” shows that just 3.3% of firms with a market cap of over $50 billion enjoyed a 5-year sales CAGR of more than 10-15% between 1950 and 2015- and a 5-year NOPAT CAGR of 10.2%. Meta’ return on invested capital (ROIC) has averaged 31.71% in that time, with current ROIC at 31.79%. In that long history, management has never failed to earn an economic profit. Exceptional growth and profitability are a byproduct of the business.
Baseline Tariffs are Acceptable
At former levels, tariffs on China were in effect so high that they act as a trade embargo, an act of decoupling. Temu and Shein, who are responsible for the majority of Meta’s Chinese ad revenue, have both already slashed their U.S. ad spending in response. Analysts at MoffettNathanson Research warned that tariffs on China would reduce Meta’s Chinese revenue by $7 billion, although I worried that not only could Meta lose all its Chinese revenue, which in 2024 was $18.35 billion, according to its annual report, but that tariffs would hurt businesses so much that Meta’s revenue would be affected by even greater amounts. At the same time, capex spending would become less efficient as inflation eroded the impact of that expenditure. Overall, I worried that the value of the business would fall in expected ways. Indeed, although markets responded euphorically to Meta’s first quarter results, that was largely because expectations had been so low that markets ignored the fact that advertising metrics deteriorated, while economic profits, by my estimate, fell from around $51.53 billion in 2024 to $45.06 billion in the LTM. Maintaining the old regime was clearly unsustainable. For now, those concerns have abated and growth and profitability should do better than where I imagined they were headed. At current levels, tariffs are an acceptable cost of business.
I do not believe that baseline tariffs will be removed. It has been my contention for some time that tariffs are here to stay, and that of all the nations in the world, tariffs on China will be the hardest to remove. In an earlier thesis, I explained that,
…regardless of one’s opinion on tariffs, the Trump Admin. has powerful motives for supporting them:
- The China Shock has gutted the manufacturing industries of countries across the world, such that, despite the broad wealth created, working class people have been left behind, stoking populist outrage. Such a system is unsustainable.
- In a military contest with China, the economic benefits of a global division of labour pale beside the risks of relying on a trade partner that builds the things that America will need to wage war.
- From the perspective of economic competition, the current division of labour is not static, and China can use it to achieve parity with the U.S. in those areas in which the U.S. is currently a world leader. BYD’s stunning success is an example of this.
…it really does not matter if one agrees with the administration’s motives, just that they are powerful enough that one should not expect tariffs to end completely. At a minimum, tariffs on China are likely to stay, even under a Democratic administration, all that is to be decided is the size of those tariffs. The Magnificent Seven, the most profitable businesses in human history, are a third of the S&P 500. Tariffs will erode their profitability and force investors to look elsewhere for investments, and that “elsewhere” will not benefit from the same premiums-to-value that the Magnificent Seven does, and that implies a downward revision in the price of the S&P 500.
Regime uncertainty persists: a comprehensive trade deal cannot be negotiated in 90 days -the fastest ever such deal was with Jordan, and the U.S. took four months to negotiate and the average is one and a half years-, but the U.K. deal framework suggests that the U.S. has shifted from attempting to strike comprehensive trade deals to pursuing small, focused deals that target specific industries. Even so, such deals are typically not conducted within 90 days, and Peter, Lord Mandelson’s framing of the U.K deal as a “platform for going further and opening up more trade opportunities”, not only points to such small, focused deals, but that regime uncertainty of some sort will persist for the next year or more as countries try and reshape the economic order in more favourable ways.
Meta Should Win its Case Against the FTC
The tariff announcement shifts the calculus in another way, placing the Federal Trade Commission’s (FTC) case against Meta at the head of Meta’s biggest risks. The case rests upon a flawed though pervasive theory of competition. In some ways, Meta’s defence of its actions is also flawed, and is responsible for the company’s lethargy in responding to the threat from ByteDnce’s TikTok. In the case summary, the FTC alleges that,
…the company is illegally maintaining its personal social networking monopoly through a years-long course of anticompetitive conduct. The complaint alleges that Facebook has engaged in a systematic strategy—including its 2012 acquisition of up-and-coming rival Instagram, its 2014 acquisition of the mobile messaging app WhatsApp, and the imposition of anti-competitive conditions on software developers—to eliminate threats to its monopoly.
Jennifer Newstead, the company’s Chief Legal Officer, has credibly argued that,
Meta has made Instagram and WhatsApp better, more reliable and more secure through billions of dollars and millions of hours of investment.
Moreover, she has said what is obvious to many, that Meta has just 30% of time spent in its properly defined market, in which it faces competition, not just from “Snapchat and an app called MeWe”, but also from TikTok and YouTube. In 2020, she called the case, “revisionist history”, writing that, having acceded to both acquisitions,
Now, many years later, with seemingly no regard for settled law or the consequences to innovation and investment, the agency is saying it got it wrong and wants a do-over. In addition to being revisionist history, this is simply not how the antitrust laws are supposed to work. No American antitrust enforcer has ever brought a case like this before, and for good reason. The FTC and states stood by for years while Facebook invested billions of dollars and millions of hours to make Instagram and WhatsApp into the apps that users enjoy today. And, notably, two FTC commissioners voted against the action that the FTC has taken today.
This is closer to reality, but does not fully comprehend the problem, because even Mark Zuckerberg has fallen into the same error. From his 2012 letter in advance of then-Facebook’s listing, he said,
Facebook was not originally created to be a company. It was built to accomplish a social mission — to make the world more open and connected.
This is both correct, and wrong. Meta is not, ultimately, a social media company, and framing it as such leads to the sorts of confusions that cloud the FTC’s case, because a social media company, or “personal social networking monopoly” to borrow the FTC’s nomenclature, cannot compete with a video-sharing service such as TikTok, unless they are in the same industry. TikTok is not a social media company, after all. The FTC’s deliberately narrow view of Meta creates this logical problem and compels a denialism about the extent of competition faced by Meta. Ben Thompson of Stratechery has tried to get round this by characterising Meta as evolving through “three eras”, with this being an era of competition. I think this is still off. The social media business is at once the core of Meta’s business and a deux ex machina to compete in the Attention Economy.
In my framework for digital firms, I wrote that,
A consequence of taking a complexity approach to competition is that competition is seen as a multi-level process, in which firms compete and relate with other firms within an industry, who, given the tendency of wealth toward destruction, seek to survive over the long-run and grow in the short run. Within markets, firms maximise their profits and compete for market share by providing sustainable products and services. Competition between firms can also be described in Coasian language as competition between intra-firm and inter-firm organisation, between whether economic activities should be done within the firm, or by the market. Within firms, individuals, units and divisions compete and cooperate to maximise their individual payoffs. Nicolas Petit and Thibault Schrepel call these the macro, meso and micro levels of competition. Competition at the industry level forces changes within firms that result in a firm facing new competitors at the market level. Concretely, by way of example, each of Meta Platforms divisions compete and cooperate over resources, and at the market level, Meta enjoys a monopoly in social media networks, but faces fierce competition at the industry level, where it is part of the Attention Economy. …The emergence of TikTok at the industry level forced changes in Instagram, by way of Reels, which triggered an evolution from a chronological feed of content surfaced from one’s social network to algorithmically sorted content from the universe of all Instagram users.
Meta’s error in not quickly recognising TikTok as a threat, was because Meta itself fell into the error of seeing itself as a social media company and therefore not existing in the same competitive landscape as TikTok. TikTok, after all, was not built on social networks but on algorithmically surfaced content. Calling TikTok or indeed YouTube a social media company, is a stretch if the intuitive sense of the phrasing implies the necessary existence of social networks. What Meta is is a business in the Attention Economy, where, regardless of the deux ex machina that brought one there, the battle is fought for attention, i.e. time spent, and victory is measured in advertising dollars. Meta is not completely oblivious to this. In the first quarter earnings call this year, Susan Li, the CFO, said,
There are two primary factors that drive our revenue performance: our ability to deliver engaging experiences for our community, and our effectiveness at monetizing that engagement over time.
There’s that old saying, “Follow the money”, and in Meta’s case, that proves remarkably revealing in understanding what the business actually is, as opposed to how it is framed. Although Meta’s defence fails to fully reframe what the company is, the weakness of the FTC’s case is such that it is unlikely to succeed, because, ultimately, in order for a final judgment to hold that the company operates an illegal monopoly, it must ignore the competition the company faces.
There is also the rather mundane fact that the deals to acquire Instagram and Whatsapp were both vetted by the FTC and at the time, it was not clear that a monopoly existed or was being created and that it would become so profitable.
Meta is Well Placed to Profit from AI
In the first quarter earnings call this year, Mark Zuckerberg highlighted the importance of AI to Meta in terms of “improved advertising, more engaging experiences, business messaging, Meta AI, and AI devices”, pointing out that Meta does not need to succeed everywhere to enlarge its returns. The most important of these opportunities in terms of immediate investment results lies with advertising, with Zuckerberg explaining that,
Our goal is to make it so that any business can basically tell us what objective they’re trying to achieve — like selling something or getting a new customer — and how much they’re willing to pay for each result, and then we just do the rest. Businesses used to have to generate their own ad creative and define what audiences they wanted to reach. But AI has already made us better at targeting and finding the audiences that will be interested in their product than many businesses are themselves, and that keeps improving. And now AI is generating better creative options for many businesses as well. I think that this is really redefining what advertising is into an AI agent that delivers measurable business results at scale. And if we deliver on this vision, then over the coming years I think that the increased productivity from AI will make advertising a meaningfully larger share of global GDP than it is today.
In the post-App Tracking Transparency world, Meta’s success has been built on its ability to deploy machine learning tools to probabilistically target users. Without realising it, Apple’s ATT policy may have hurt Meta in the short-term, but, in the long-term, widened Meta’s proverbial moat, by denying social media networks such as Snap access to the data needed for deterministic ad targeting. Meta has the scale and infrastructure to make the best probabilistic targeting available. With generative AI, this competitive advantage becomes even stronger: Meta will be able to test an infinite number of ad ideas and verify the success of each ad, pushing that probabilistic process closer toward certainty. With the scale and infrastructure available to meta, the company will be able to take over the entire creative process for advertisers, with even greater success than it now has, which will attract more advertisers, raising prices and margins. Already, the AI recommendation model Meta is testing on Reels has led to a 5% increase in conversions and has been used by 30% of advertisers.
I cannot conclude this section without mentioning DeepSeek: although investors reacted negatively to it, as a kind of external shock, it is actually favourable, at least to Meta. Meta does not need the Llama family of open-weight models to be the world’s best generative AI tool, what it needs is for the cost of generative AI to sharply decline as models improve, and for content to become even more commoditised. In a 2024 interview with Dwarkesh Patel, Zuckerberg noted that,
there’s multiple ways where open source could be helpful for us. One is if people figure out how to run the models more cheaply. We’re going to be spending tens, or a hundred billion dollars or more over time on all this stuff. So if we can do that 10% more efficiently, we’re saving billions or tens of billions of dollars. That’s probably worth a lot by itself. Especially if there are other competitive models out there, it’s not like our thing is giving away some kind of crazy advantage.
…
Here’s one analogy on this. One thing that I think generally sucks about the mobile ecosystem is that you have these two gatekeeper companies, Apple and Google, that can tell you what you’re allowed to build. There’s the economic version of that which is like when we build something and they just take a bunch of your money. But then there’s the qualitative version, which is actually what upsets me more. There’s a bunch of times when we’ve launched or wanted to launch features and Apple’s just like “nope, you’re not launching that.” That sucks, right? So the question is, are we set up for a world like that with AI? You’re going to get a handful of companies that run these closed models that are going to be in control of the APIs and therefore able to tell you what you can build?
For us I can say it is worth it to go build a model ourselves to make sure that we’re not in that position. I don’t want any of those other companies telling us what we can build. From an open source perspective, I think a lot of developers don’t want those companies telling them what they can build either. So the question is, what is the ecosystem that gets built out around that? What are interesting new things? How much does that improve our products? I think there are lots of cases where if this ends up being like our databases or caching systems or architecture, we’ll get valuable contributions from the community that will make our stuff better. Our app specific work that we do will then still be so differentiated that it won’t really matter. We’ll be able to do what we do. We’ll benefit and all the systems, ours and the communities’, will be better because it’s open source.
In the wake of DeepSeek’s launch, Zuckerberg said he believed that not only could Meta incorporate some of the novel things DeepSeek did, which, presumably, would mean that spending would become more efficient, but also that,
There’s going to be an open-source standard globally, and I think that for our own national advantage it’s important that it’s an American standard. The recent news has only strengthened our conviction that this is the right thing to be focused on.
In effect, this would free Meta from the kinds of dependencies it had on Apple, while making more developers dependent on Meta.
Meta Is Attractively Valued
At the current price, Meta is not cheap, but rates attractively valued according to my stock rating methodology. It has a price-to-economic book value (PEBV) of 2.1, which implies that the market expects its net operating profit after tax (NOPAT) to grow by 110% from current levels. Using my reverse discounted cash flow ‘DCF) model, one can uncover the expectations implied by the current stock price.
If, in the first scenario,
- revenue grows by an average of 9.31% a year, in line with consensus estimates, before rising to 15% a year, as a function of its AI investments.
- and Meta maintains its current NOPAT margin of 36.97%, then,
the shareholder value equals its current stock price in 2045, with a market-implied competitive advantage period (MICAP) of 20 years.
If, on the other hand,
- revenue grows by 14.66% a year, its 5-year sales CAGR
- and NOPAT margin rises to 41.02%, its 2024 peak, then
Meta is worth $990.15 per share, an upside of 67.17% from the current price.
If, however,
- revenue grows by 13.47% a year, its 3-year sales CAGR
- and NOPAT margin rises to 41.02%, then,
Meta is worth $652.16, a 10% upside to the current price.
Impact of Footnotes Adjustments and Forensic Accounting
Here below are details of accounting adjustments made to Meta’s’ LTM periodic reports:
Income Statement: I made $6.63 billion in adjustments to calculate NOPAT, with the net effect of deducting $3.65 billion in non-operating income. The adjustments are equal to 9.95% of Meta’s GAAP net income.
Balance Sheet: I made $138.36 billion in adjustments to calculate invested capital with a net decrease of $83.54 billion. One of the largest of these adjustments was $72.99 billion in excess cash, an adjustment worth 26% of reported assets.
Valuation: I made $136.79 billion in adjustments with a net effect of increasing shareholder value by $9.19 billion. The largest of these adjustments was $63.8 billion in adjusted total debt, representing 4.28% of Meta’s market cap.