DeepSeek crashes the AI Party: Story Break, Change or Shift?

    I am going to start this post with a confession that my knowledge of the architecture and mechanics of AI are pedestrian and that there will be things that I don't get right in this post. That said, DeepSeek's abrupt entry into the AI conversation has the potential to change the AI narrative, and as it does, it may also change the storylines for the many companies that have spent the last two years benefiting from the AI hype. I first posted about AI in the context of valuing Nvidia, in June 2023, when there was still uncertainty about whether AI had legs. A little over a year later, in September 2024, that question about AI seemed to have been answered in the affirmative, for most investors, and I posted again after Nvidia had a disappointing earnings report, arguing that it reflected a healthy scaling down of expectations. As talk of AI disrupting jobs and careers also picked up, I also posted a piece on the threat that AI poses for all of us, with its capacity to do our jobs, at low or no cost, and what I saw as the edges I could use to keep my bot at bay. For those of you who have been tracking the market, the AI segment in the market has held its own since September, but even before the last weekend, there were signs that investors were sobering up on not only how big the payoff to AI would be, but how long they would have to wait to get there. 

The AI story, before DeepSeek

    The AI story has been building for a while, reflecting the convergence of two forces in technology - more computing power, often in smaller and smaller packages, and the accumulation of data, on technology platforms and elsewhere. That said, the AI story broke out to the public on November 30, 2022, when OpenAI launched ChatGPT, and it made its presence felt in homes, schools and businesses almost instantaneously. It is that wide presence in our daily lives that laid the foundations for the AI story, where evangelists sold us on the notion that AI solutions would make our lives easier and take away the portions of our work that we found most burdensome, and that the businesses that provided these solutions would be worth trillions of dollars.

    As the number of potential applications of AI proliferated, thus increasing the market for AI products and services, another part of the story was also being put into play. AI was framed as being made possible by the marriage of incredibly powerful computers and deep troves of data, effectively setting the stage for the winners, losers, and wannabes in the story. The first set of companies were perceived as benefiting from building the AI architecture, with the advance spending on this architecture coming from the companies that hoped to be players in the AI product and service markets:

1. Computing Power: In the AI story that was told, the computers that were needed were so powerful that they needed customized chips, more powerful and compact than any made before, and one company (Nvidia), by virtue of its early start and superior chip design capabilities, stood well above the rest. Not only did Nvidia have an 80% market share of the AI chip market, as assessed in 2024, the lead and first-mover advantage that the company possessed would give it a dominant market share, in the much larger AI chip market of the future. Along the way, the the AI story picked up supercomputing companies, as passengers, again on the belief that Ai systems would find a use for them.
2. Power: In the AI story, the coupling of powerful computing and immense data happens in data centers that are power hogs, requiring immense amounts of energy to keep going. Not surprisingly, a whole host of power companies have stepped into the breach, with some increasing capacity entirely to service these data centers. Some of them were new entrants (like Constellation Energy), whereas others were more traditional power companies (Siemens Energy) who saw an opening for growth and profitability in the AI space. 
3. Data: A third beneficiary from the architecture part of the AI story were the cloud businesses, where the big data, collected for the AI systems would get stored. The big tech companies with cloud arms, particularly Microsoft (Azure) and Amazon (AWS) have benefited from that demand, as have other cloud businesses.

Since the companies involved in building the AI infrastructure are the ones that are most tangibly (and immediately) benefiting from the AI boom, they are also the companies that have seen the biggest boost in market cap, as the AI story heated up. In the graph, I have picked on a subset of high-profile companies that were part of the AI market euphoria and looked at the consequent increase in their market capitalizations:

Using the ChatGPT introduction on November 30, 2022, as the starting point for the AI buzz, in public consciousness and markets, the returns in 2023 and 2024 are a composite (albeit a rough) measure of the benefits that AI has generated for these companies. Note that the biggest percentage winner, at least in this group was Palantir, up 1285% in the last two years, but the biggest winner in absolute terms was Nvidia, which gained almost $ 3 trillion in value in 2023 and 2024.

    The investments in that AI architecture were being made, with the expectation that companies that invested in the architecture would be able to eventually profit from developing and selling AI products and services. Since the AI storyline required immense upfront investing in computing power and access to big data, the biggest investors in AI architecture were big tech companies, with Microsoft and Meta being the largest customers for Nvidia chips in 2024. In the table below, I look at the Mag Seven, not inclusive of Nvidia, and examine the returns that they have made in 2023 and 2024:

As you can see, the Mag Seven carried the market in the two years, each adding a trillion (or close, in the case of Tesla) dollars in value in the last two years, with some portion of that value attributable to the AI story. With requirements for large investment up front acting as entry barriers, the expectation was these big tech companies would eventually not only be able to develop AI products and services that their customers would want, but charge premium prices (and earn higher margins).

    In the picture below, I have tried to capture the essence of AI story, with the potential winners and losers at each stage:

There are parts to this story where there is much to be proved, especially on the AI product and service part, and while investors can be accused of becoming excessively exuberant about the story, it is a plausible one. In fact, my most recent (in September 2024) valuation of Nvidia bought into core elements of the story, though I still found it overvalued:

Nvidia valuation in September 2024 (Pre DeepSeek)

Note that the big AI story plays out in these inputs in multiple places:

1. AI chip market: My September 2024 estimate for the size of the AI chip market was $500 billion, which in turn was justifiable only because the AI product and service market was expected to huge ($3 trillion and beyond).
2. Nvidia market share: In my valuation, I assumed that Nvidia's lead in the AI chip business would give the company a head start, as the business grew, and to the extent that demand is sticky (i.e., once companies start build data centers with Nvidia chips, it would be difficult for them to switch to a competitor), Nvidia would maintain a dominant market share (60%) of the expanded AI chip market.
3. Nvidia margins: Nvidia has had immense pricing power, posting nosebleed-level gross and operating margins, while TSMC (its chip maker) has generated only a fraction of the benefits, and its biggest customers (the big tech companies) have been willing to pay premium prices to get a head start in building their AI architecture. Over time, I assumed that Nvidia would see its margins drop, but even with the drop, their target margin (60%) would resemble those of very successful, software companies, not chip making companies.

My concern in September 2024, and in fact for the bulk of the last two years, was not that I had doubts about the core AI story, but that investors were overpaying for the story. That is partly why, I have shed portions of my holdings in Nvidia, selling half my holdings in the summer of 2023 and another quarter in the summer of 2024.

The AI Story, after DeepSeek

    I teach valuation, and have done so for close to forty years. One reason I enjoy the class is that you are never quite done with a valuation, because life keeps throwing surprises at you. The first session of my undergraduate valuation class was last Wednesday (January 22), and during the course of the class, I talked about how a good valuation connects narrative to numbers, and followed up by noting that even the most well thought through narratives will change over time. I am not sure how much of that message got through to my studentls, but the message was delivered much more effectively by DeepSeek's entry into the AI story over the weekend, and the market shakeup that followed when markets opened on Monday (January 27).

A DeepSeek Primer

    The DeepSeek story is still being told, and there is much we do not know. For the moment, though, here is what we know. In 2010, Liang Wenfeng, a software engineer, founded DeepSeek as a hedge fund in China, with the intent of using artificial intelligence to make money. Unable to get traction in that endeavor, and facing government hostility on speculative trading, he pivoted in 2023 into AI, putting together a team to create a Chinese competitor to OpenAI. Since the intent was to come up with a product that could be sold at bargain prices, DeepSeek did what disruptors have always done, which is look for an alternate path to the same destination (providing AI products that work). Rather than invest in expensive infrastructure (supercomputers and data centers), DeepSeek used much cheaper, less powerful chips, and instead of using immense amounts of data, created an AI prototype that could work with less data, using rule-based logic to fill in the gap. While there has been chatter about DeepSeek for weeks, it became publicly accessible at the end of last week (ending January 24), and within hours, was drawing rave reviews from people well versed in tech, as it matched beat ChatGPT at many tasks, and even performed better on scientific and math queries. 

    There are parts of this story that are clearly for public consumption, more side stories than main story,, and it is best to get them out of the way, before looking at the DeepSeek effect.

1. Cost of development: The notion that DeepSeek was developed for just a few million dollars is fantasy, and while there may have been a portion of the development that cost little, the total was probably in the hundreds of millions of dollars and required a lot more resources (including perhaps even Nvidia chips) than the developers are letting on. No matter what the true cost of development is finally revealed to be, it will be a fraction of the money spent by the existing players in building their systems.
2. Performance tests: The tests of DeepSeek versus OpenAI (or Claude and Gemini) suggests that DeepSeek not only holds it own against the establishment, but even outperforms them on some tasks. That is impressive, but the leap that some are making to concede the entire AI product and service market to DeepSeek is unwarranted. There are clearly aspects of the AI products and service business, where the DeepSeek approach (of using less powerful computing and data) will be good enough, but there will be other aspects of the AI business, where the old paradigm of super computing power and vast data will still hold.
3. A Chinese company: The fact that DeepSeek was developed in China throws a political twist into the story that will undoubtedly play a role in how it develops, but the genie is out of the bottle, even if other governments try to stop its adoption. Adding to the noise is the decision by the company to make DeepSeek open-source, effectively allowing others to adapt and build their own versions.
4. Fair or foul: Finally, there has been some news on the legal front, where OpenAI has argued that DeepSeek unlawfully used data that was generated by OpenAI in building their offering, and while part of that lawsuit may just be showboating, it is possible that portions of the story are true and that legal consequences will follow.

While we can debate the what's and why's in this story, the market reaction this week to the story has been swift and decisive. I graph the performance of the five AI stocks highlighted in the earlier section, throwing in the Meta and Microsoft for good measure, on a daily basis in 2025.

As you can see in this chart, Nvidia Broadcom, Constellation and Vistra have had terrible weeks, losing more than 10% in the last week, but just for perspective, also note that Constellation and Vistra are still up strongly for the year. Meta and Microsoft were unaffected, and so was Palantir, Clearly, the DeepSeek story is playing out differently for different companies in the AI space, but its overall market impact has been substantial, and for the most part, negative.

    What is it that makes the DeepSeek story so compelling? First, is the technological aspect of coming up with a product, with far less in resources that the establishment, and I have nothing but admiration for the DeepSeek creators, but the part of the story that stands out is that the they chose not to go with the prevailing narrative (the one where Nvidia chips and huge data bases are a necessity) and instead asked the question of what the end products and services would look like, and whether there was an easier, quicker and cheaper way of getting there. In hindsight, there are probably others who are looking at DeepSeek and wondering why they did not choose the same path, and the answer is that it takes courage to go against the conventional wisdom, especially when, as AI did over the last two years, it sweeps everyone (from tech titans to individual investors) along with its force.

    The truth is that even if DeepSeek is stopped through legal or government action or fails to deliver on its promises, what its entry has done to the AI story cannot be undone, since it has broken the prevailing narrative. I would not be surprised if there are a dozen other start-ups, right now, using the DeepSeek playbook to come up with their own lower-cost competitors to prevailing players. Put simply, the AI story's weakest links have been exposed, and if this were the tale about the Emperor's new clothes, the AI emperor is, if not naked, is having a wardrobe malfunction, for all to see.

The Story Effect

    In this first week, as is to be expected, the response has been anything but reasoned. If you are a voracious reader of financial news (I am not), you have probably seen dozens of “thought pieces” from both technology and market experts claiming to foretell the future, and even among the few that I have read, the views range the spectrum on how DeepSeek changes the AI story. 

    In my writings on narrative and numbers, where I talk about how every valuation tells a story, I also talk about how stories are dynamic, with a story break representing radical change (where a great story can crash and burn or a small story can break out to become a big one), a story change can be a significant narrative alteration (where a story adds or loses a dimension with big value effects) or a story shift (where the core story remains unchanged, but the parameters can change). Using the pre-DeepSeek story as a starting point, you can classify the narratives on what is coming on the story break/story change/story shift continuum:

With all the caveats, including the fact that I am an AI novice, with a deeper understanding of potato chips than computer chips, and that it is early in the game, I am going to take a stand on where in this continuum I see the DeepSeek effect falling. I believe that DeepSeek does change the AI story, by creating two pathways to the AI product and service endgame. On one path that will lead to what I will term the “low intensity” AI market, it has opened the door to lower cost alternatives, in terms of investments in computing power and data, and competitors will flock in. That said, there will remain a segment of the AI market, where the old story will prevail, and the path of massive investments in computer chips and data centers leading to premium AI products and services will be the one that has to be taken.

    Note that the entry characteristics for the two paths will also determine the profitability and payoffs from their respective AI product and service markets (that will eventually exist). The “low entry cost” pathway is more likely to lead to commoditization, with lots of competitors and low pricing power, whereas the “high entry cost” path with its requirements for large upfront investment and access to data will create a more restrictive market, with higher priced and more profitable AI products and services. This story leaves me with a judgment call to make about the relative sizes of the markets for the two pathways. I am generalizing, but much of what consumers have seen so far as AI offerings fall into the low cost pathway and I would not be surprised, if that remains true for the most part. The DeepSeek entry has now made it more likely that you and I (as consumers) will see more AI products and services offered to us, at low cost or even for free. There is another segment of the AI products and services market, though, with businesses (or governments) as customers, where significant investments made and refinements will lead to AI products and services, with much higher price points. In this market, I would not be surprised to see networking benefits manifest, where the largest players acquire advantages, leading to winner-take-all markets. 

    In telling this story, I understand that not only am I going to be wrong, perhaps decisively, but also that it could unravel in record time. I make this leap, not out of arrogance or a misplaced desire to change how you think, but because I own a slice of Nvidia (one quarter of the holding that I had two years ago, but still large enough to make a difference in my portfolio), and I cannot value the company without an AI story in place. That said, the feedback loop remains open, and I will listen not only to alternate opinions but also follow real world developments, in the interests of telling a better story.

The Value Effect

    Now that my AI story is in the open, I will use it to revisit my valuation of Nvidia, and incorporate my new AI story in that valuation. Even without working through the numbers, it is very difficult to see a scenario where the entry of DeepSeek makes Nvidia a more valuable company, with the biggest change being in the expected size of the AI chip market:

	In September 2024 (pre DeepSeek)	In January 2025 (post DeepSeek)
AI chip market size in 2035	$500 billion	$300 billion
Nvidia's market share	60%	60%
Nvidia's operating margin	60%	60%
Nvidia's risk (cost of capital)	10.52% _> 8.49%	11.79% -> 8.50% (Higher riskfree rate + higher ERP)

With the changes made, and updating the financials to reflect an additional quarter of data,  you can see my Nvidia valuation in the picture below:

Nvidia valuation in January 2025 (Post DeepSeek)

There are two (unsurprising) results in this valuation. The value per share that I estimate for Nvidia dropped from $87 in September 2024 to $78 in January 2025, much of that change driven by the smaller AI chip market that comes out of the DeepSeek disruption (with the rest of the decline arising for higher riskfree rates and the equity risk premiums). The other is that the stock is overvalued, at its current price of $123 per share, even after the markdown this week. Since I found Nvidia overvalued in September 2024, when the big AI story was still in place, and Nvidia was trading at $109, $14 lower than todays price, estimating a lower value and comparing to a higher price makes it even more over valued..

    More generally, the value effect of the DeepSeek disruption will be disparate, more negative for some companies in the AI space than others, and perhaps even positive for a few and I have attempted to capture those effects in the picture below, comparing DeepSeek to a bomb, and looking at the damage zones from the blast:

In my view, the damage, in the near and long term, from DeepSeek will be to the businesses that have been the lead players in building the AI architecture. In addition to Nvidia (and its AI chip business), this includes the energy and gas businesses that have benefited from the tens of billions spent on building AI data centers. It is not that they will currently contracts, but that it is likely that you will see a slowing down of commitments to spend money on AI, as companies examine whether they need them. More companies are therefore likely to follow Apple's path of cautious entry than Meta and Microsoft's headfirst dive into the AI businesses. As for the businesses that are aiming for the AI products and services market, the effect will depend upon how much these products and services need data and computing power. If the proposed AI products and services are low-grade, i.e., they are more rule-based and mechanical and less dependent on incorporating intuition and human behavior, the effect of DeepSeek will be significant, with lower costs to entry and a commoditized marketplace, with lower margins and intense competition, If on the other hand, the AI products and services are high grade, i.e,, trying to imitate human decision making in the face of uncertainty, the effects of the DeepSeek entry are likely to be minimal and perhaps even non-existent. Thus, I would expect a business that is working on an AI product for financial accounting to find its business landscape changed more than Palantir, working on complex AI products for the defense department or commercial businesses. There is a grouping of companies, primarily big tech firms with large platforms, like Meta and Microsoft, where there may be buyer’s remorse about money already spent on AI (buying Nvidia chips and building data centers) but the DeepSea disruption may make it easier to develop low-cost, low-tech AI products and services that they can offer their platform users (either for free or at low costs) to keep them in their ecosystems.

    When faced with a development that could change the way we live and work, it is natural, especially in the early phases, to give that development a catchy name, and use it as a rationale for investing large amounts (if you are a business) or pushing up what you would pay for the businesses in the space (if you are an investor). In my early piece on AI, I talked about four developments in my lifetime that I would classify as revolutionary – personal computers in the 1980s, the internet in the 1990s, the smartphone in the first decade of the twenty first century and social media in the last decade, and how each of these started as catchall buzzwords, before investors and businesses learned to discriminate. Cisco, AOL and Amazon were all born in the internet era, but they had very different business models, and as the internet matured, faced very different end games. I hope that the DeepSeek entry into the AI narrative, and its disparate effects on different businesses in this space, will lead us to be more focused in our AI conversations. Thus, rather than describe a company as an AI company or describe the AI market as “huge”, we should be more explicit about what part of the AI business a company fits into (architecture, software, data or products/services) and apply the same degree of discrimination when talking about AI markets. If you also buy into my reasoning, you may want to follow up by asking whether the AI offering is more likely to fall into the premium or commoditized grouping.

The Bottom Line

    My early entry into Nvidia and my holdings of many of the other Mag Seven stocks have allowed me to ride the AI boom, I have remained a skeptic about the product and service side of AI, for much of the last two years. I can attribute that wariness partly to my age, since I cannot think of a single AI offering that has been made to me in the last two years that I would pay a significant additional amount for. I see AI icons on almost everything that I use, from Zoom to Microsoft Word/Powerpoint/Excel to Apple mail. I must admit that they do neat things, including reword emails to not only clean up for mistakes but change the tone, but I can live without those neat add-ons. Since I work in valuation and corporate finance, not a day goes by without someone contacting me about a new AI product or service in the space. Having tried a few out, my response to many of these products and services is that, at least for me, they don’t do enough for me to bother. In many ways, DeepSeek confirms a long-standing suspicion on my part that most AI products and services that we will see, as consumers and even as businesses, fall into the “that’s cute” or “how neat” category, rather than into the “that would change my life”, If that is the case, it has also struck me as overkill to expend tens of billions of dollars building data centers to develop these products, akin to using a sledgehammer to tap a nail into the wall. Every major innovation of the last few decades, has had its reality check, and has emerged the stronger for it, and this may the first of many such reality checks for AI.

    I know that much of what I have said here goes against the "happy talk" narrative about AI, emanating from tech titans and business visionaries. I know that Reid Hoffman and Sam Altman believe that AI will be world-changing, in a good way, relieving us of the pain of tasks that are boring and time consuming, and even replacing flawed "human" decisions with be more reasoned AI decisions. They are smart men, but I have two reasons for being cautions. The first is that I have had exposure to smart people in almost every walk of life - smart academics, smart bankers, smart software engineers, smart venture capitalists and yes, even smart regulators - but most of them have had blind spots, perhaps because they hang out with people who think like them. The second, and this perhaps follows from the first, is that I am old enough to have heard this evangelist pitch for a revolutionary change before. In the 1980s, I remember being told that personal computers would eliminate the drudgery of working through ledger sheets with calculators and pencils, but as young financial analysts will tell you today, it has just created a fresh and  perhaps even more soul-sucking drudgery, where monstrously large spreadsheets govern their workdays. In the 1990s, the advocates for the internet painted a picture of the world where access to online information would make us all more informed and wiser, but in hindsight, all it has done is weaken our reasoning muscles (by letting us look up answers online) and made us misinformed. In this century, social media too was born on the promise that it would keep us connected with friends, even if they were thousands of miles away, and happier, because of those connections, but as my good friend, Jonathan Haidt, and others have chronicled, it has left many in its orbit more isolated and less happy than before. 

YouTube Video

Nvidia Valuations

1. Nvidia valuation in September 2024 (Pre DeepSeek)
2. Nvidia valuation in January 2025 (Post DeepSeek)

Tesla in November 2023 : Story twists and turns, with value consequences!

I was planning to start this post by telling you that Tesla was back in the news, but that would be misleading, since Tesla never leaves the news. Some of that attention comes from the company's products and innovations, but much of it comes from having Elon Musk as a CEO, a man who makes himself the center of every news cycle. That attention has worked in the company's favor over much of its lifetime, as it has gone from a start-up to one of the largest market cap companies in the world, disrupting multiple businesses in the process. At regular intervals, though, the company steps on its own story line, creating confusion and distractions, and during these periods, its stock price is quick to give up gains, and that has been the case for the last few weeks. As the price dropped below $200 today (October 30,2023), I decided that it was time for me to revisit and revalue the company, taking into account the news, financial and other, that has come out since my last valuation in January 2023, and to understand the dueling stories that are emerging about the company.

My Tesla History

    When I write and teach valuation, I describe it as a craft, and there are very few companies that I enjoy practicing that craft more than I do with Tesla. Along the way, I have been wrong often on the company, and if you are one of those who only reads valuations by people who get it right all the time, you should skip the rest of this post, because I will cheerfully admit that I will be wrong again, though I don't know in which direction. My first valuation of Tesla was in 2013, when it was a nascent automobile firm, selling less than 25,000 cars a year, and viewed by the rest of the automobile sector with a mix of disdain and curiosity. I valued it as a luxury automobile firm that would succeed in that mission, giving it Audi-level revenues in 2023 of about $65 billion, and operating margins of 12.50% that year (reflecting luxury auto margins). To deliver this growth, I did assume that Tesla would have to invest large amounts of capital in capacity, and that this would create a significant drag on value, resulting in a equity value of just under $10 billion.

    In subsequent valuations, I modified and adapted this story to reflect lessons that I learned about Tesla, along the way. First, I learned that the company was capable of generating growth much more efficiently, and more flexibly, than other auto companies, reducing the capital investment needed for growth. Second, I noticed that Tesla customers were almost fanatically attached to the company's products, and were willing to evangelize about it, yielding a brand loyalty that legacy auto companies could only dream about. Third, in a world where many companies are run by CEO who are, at best, operating automatons, and at worst, evidence of the Peter Principle at play, where incompetence rises to the top, Tesla had a CEO whose primary problem was too much vision, rather than too little. In valuation terms, that results in a company whose value shifts with narrative changes, creating not only wide swings in value, but vast divergences in opinion on value. In 2016, I looked at how Tesla's story would vary depending upon the narrative you had for the company and listed some of the possible choices in a picture:

I translated these stories into inputs on revenue growth, profit margins and reinvestment, to arrive at a template of values:

Note that is multiple stock splits ago, and the prices per share here are not comparable to the share price today, but the overall lessons contained in this table still apply. First, when you see significant disagreements about what Tesla is worth, those differences come from divergent stories, not disagreements about numbers. Second, every news story or financial disclosure about Tesla has to be used to evaluate how the company's narrative is changing, creating multiplier effects that create disproportionate value changes.

    Along the way, Tesla (or more precisely, Elon Musk) has made choices that could be, at best, described as puzzling, and, at worst, as perilous for the company's long term health, from borrowing money in 2017, when equity would have been a much better choice, to setting arbitrary targets on production (remember the 5000 cars a week for the company in 2018) and cash flows (positive cash flows in 2018) that pushed the company into a corner. If you add to that the self-inflicted wounds including Musk tweeting out that he had a deal to sell the company at $420 a share, funding secured, in 2018, it is not surprising that the stock has had periods of trauma. It was after one of these downturns in 2019, when the stock hit $180 (with a market cap of $32 billion), that I bought Tesla for the first time, albeit labeling it as my corporate teenager, an investment that would frustrate me because it would get in the way of its own potential. 

    I profited mightily on that investment, but I sold too soon, when Tesla's market capitalization hit $150 billion, and just before COVID put the company on a new price orbit. In fact, I revisited the company's value in November 2021, when its market capitalization hit a trillion, marveling at its rise, but also noting that it was priced to deliver such wondrous results ($600-$800 billion in revenues, with 20%+ margins) that I was uncomfortable going along:

In 2022, the stock came back to earth with a vengeance, losing more than 65% of its equity value, leaving the stock (on a post-split basis) trading at close to $100 a share at the end of the year. Three weeks later, i.e., at the start of 2023, I revalued the stock, allowing for uncertainties in my estimate of revenues and margins to deliver a median value per share of $153, with significant variation in potential outcomes:

I was about a week late on my valuation, since the stock price had already broken through this value by the time I finished it, leaving my portfolio Tesla-free, in 2023.

Tesla Update

    My last Tesla valuation is less than ten months old, and while that is not long in calendar time, with Tesla, it feels like an eternity, with this stock. As a lead in to updating the company’s valuation, it makes sense to start with the stock price, the market’s barometer for the company's health. The stock, which  started the year in a swoon, recovered quickly in the first half of the year, peaking around mid-year at close to $300 a share. 

The last four months have tested the stock, and it has given back a significant portion of its gains this year, with the stock dropping below $200 on October 30, 2023. Since earnings reports are often viewed as the catalysts for momentum shifts, I have highlighted the four earnings reports during the course of 2023, with a comparison of earnings per share reported, relative to expectations. The first earnings report, in January 2023, has been the only one where the company beat expectations, and it matched expectations in the April report, and fallen behind in the July and October reports. 

    The earnings per share focus misses much of Tesla’s story, and it is instructive to dig deeper into the income statement and examine how the company has performed on broader operating metrics:

In the twelve months, ending September 2023, Tesla reported operating income of $10.7 billion on revenues of $95.9 billion; that puts their revenues well ahead of my 2013 projection of $65 billion, albeit with an operating margin of 11.18%, lagging my estimate of 12.5%.  That makes Tesla the eleventh largest automobile company in the world, in revenue terms, and the seventh most profitable on the list, making it more and more difficult for naysayers to argue that it is a fad that will pass. Breaking down the news in the financials by business grouping, here is what the reports reveal:

• Auto business: Tesla's auto business saw revenue growth slow down from the torrid pace that it posted between 2020 and 2022, with third quarter year-on-year revenue growth dropping to single digits, but given the flat sales in the auto sector and a sluggish electric car market, it remains a stand-out. The more disappointing number, at least for those who were expecting pathways to software-company like margins for the company, was the decline in profit margins on automobiles from 2022 levels, though  the 17.42% gross margin in the third quarter, while disappointing for Tesla, would have been cause for celebration at almost any of its competitors.
• Energy business: Tesla's energy business, which was grounded by its acquisition of Solar City in 2016, has had a strong year, rising from 4.8% of the company's revenues in 2022 to 6.2% in the twelve months ending September 2023. In conjunction, the profitability of the business also surged in the last twelve months, and while some of this increase will average out, some of it can be attributed to a shift in emphasis to storage solutions (battery packs and other) from energy generation.

In short, Tesla's financial reports, are an illustration of how much expectations can play a role in how markets react to the news in them. The post-COVID surge in Tesla's revenues and profitability led to unrealistically high expectations of what the company can do in this decade, and the numbers, especially in the last two quarters, have acted as a reality check.

    As a story stock, Tesla is affected as much by news stories about the company and its CEO, as it is by financials, and there are three big story lines about the company that bear on its value today:

1. Price Cuts: During the course of 2023, Tesla has repeatedly cut prices on its offerings, with the most recent ones coming earlier this month, The $1,250 reduction in the Model 3 should see its price drop to about $39,000, making it competitive, even on a purely price basis, in the mass auto market in the United States. Some of this price cutting is tactical and in response to competition, current or forecast, but some of it may reflect a shift in the company's business model.
2. Full Self Driving (FSD): Tesla, as a company, has pushed its work on full self driving to the forefront of its story, though there remains a divide in how far ahead Tesla is of its competition, and the long term prospects for automated driving. Its novelty and news value has made it a central theme of debate, with Tesla fans and critics using its successes and failures as grist for their social media postings. While an autopilot feature is packaged as a standard feature with Teslas,  it offers  FSD software, which is still in beta version, offers an enhanced autopilot model, albeit at a price of $12,000. The FSD news stories have also reignited talk of a robotaxi business for Tesla, with leaks from the company of a $25,000 vehicle specifically aimed at that business.
3. Cybertruck: After years of waiting, the Tesla Cybertruck is here, and it too has garnered outsized attention, partly because of its unique design and partly because it is Tesla's entree into a market, where traditional auto companies still dominate. While there is still debate about whether this product will be a niche offering or one that changes the trucking market, it has undoubtedly drawn attention to the company. In fact, the company's reservation tracker records more than two millions reservations (with deposits), though if history is a guide, the actual sales will fall well short of these numbers.

This being Tesla, there are dozens of other stories about the company, but that is par for the course. We will focus on these three stories because they have the potential to upend or alter the Tesla narrative, and by extension, its value.

Story and Valuation: Revisit and Revaluation

    In my Tesla valuations through the start of 2023, I have valued Tesla as an automobile company, with the other businesses captured in top line numbers, rather than broken out individually. That does not mean that they are adding significantly to value, but that the value addition is buried in an input to value, rather than estimated standing alone. In my early 2023 valuation, I estimated an operating margin of 16% for Tesla, well above auto industry averages, because I believed that software and or the robotaxi businesses, in addition to delivering additional revenues, would augment operating margins, since they are high-margin businesses.     

    The news stories about Tesla this year have made me reassess that point of view, since they feed into the narrative that Tesla not only believes that the software and robotaxi businesses have significant value potential as stand-alone businesses, but it is acting accordingly. To see why, let me take each of the three news story lines and work them into my Tesla narrative:

1. Cybertrucks: The easiest news items to weave into the Tesla narrative is the Cybertruck effect. If the advance orders are an indication of pent-up demand and the Cybertruck represents an extension into a hitherto untapped market, it does increase Tesla's revenue growth potential. There are two potential negatives to consider, and Musk referenced them during the course of the most recent earnings call. The first is that, even with clever design choices, at their rumored pricing, the margins on these trucks will be lower than on higher-end offerings. The other is that the Cybertruck may very well require dedicated production facilities,  pushing up reinvestment needs. If Cybertruck sales are brisk, and the demand is strong, the positives will outweigh the negatives, but if the buzz fades, and it becomes a niche product, it may very well prove a distraction that reduces value. The value added by Cybertrucks will also depend, in part, on who buys them, with Tesla gaining more if the sales comes from truck buyers, coming from other companies, than it will if the sales comes from Tesla car buyers, which will cannibalize their own sales.
2. FSD: As I look at the competing arguments about Tesla's FSD research, it seems clear to me that both sides have a point. On the plus side, Tesla is clearly further along this road than any other company, not only from a technological standpoint, but also from business model and marketing standpoints. While I do not believe that charging $12,000 for FSD as an add-on will create a big market, lowering that price will open the door not only to software sales to Tesla drivers, but perhaps even to other carmakers. In addition, it seems clear to me that the Tesla robotaxi business has now moved from possible to plausible on my scale, and thus merits being taken seriously. On the minus side, I do agree that the world is not quite ready for driverless cars, on scale, and that rushing the product to market can be catastrophic. 
3. Price cuts: The Tesla price cuts have led to a divide among Tesla bulls, with some pointing to it as the reason for Tesla's recent pricing travails and others viewing it as a masterstroke advancing it on its mission of global domination. To decide which side has the more realistic perspective, I decided to take a look at how price cuts play out in value for a generic company. The first order effect of a price cut is negative, since lowering prices will lower margins and profits, and it is easy to compute. It is the second order effects that are tricky, and I list the possibilities in the figure below, with value consequences:
   
   
   In short, price cuts can, and often will, change the number of units sold, perhaps offsetting some of the downside to price cut (tactical), make it more difficult for competitors to keep up or enter your business (strategic) and expand the potential for side or supplemental businesses to thrive (synergistic). This figure explains the divide on the Tesla price cuts, with the pessimists arguing that electric car demand is too inelastic for volume increases that will compensate for the lower margins, and the optimists arguing that the value losses from lower margins will be more than offset by a long-term increase in Tesla's market share, and increase the value from their software and robotaxi businesses.

To bring these stories into play, I break Tesla down into four businesses - the auto business, the energy business, the software business and the robotaxi business. I do know that there will be Tesla optimists who will argue that there are other businesses that Tesla can enter, including insurance and robots, but for the moment, I think that the company has its hands full. I look out the landscape for these businesses in the picture below, looking at the potential size and profitability of the market for each of these businesses, as well as Tesla's standing in each.

Note that the auto business is, by far, the largest in terms of revenue potential, but it lags the other business in profitability, especially the software and robotaxi businesses, where unit economics are favorable and margins much higher. Note also that estimates for the future in the robotaxi and auto software businesses are squishy, insofar as they are till nascent, and there is much that we do not know.My Tesla story for each of these businesses is below, with revenue and profitability assumption, broken down  by business:

With these stories in place, I estimate revenues, earnings and cash flows for the businesses, and in sum, for the company, and use these cash flows to estimate a value per share for the company:

Download spreadsheet

In sum, the value per share that I get with Tesla's businesses broken down and allowing for divergent growth and profitability across businesses, is about $180 a share. That is higher than my estimate at the start of the year, with part of that increase coming from the higher profit potential in the side businesses, and expectations of a much larger end game in each one. 

    Given that this value comes from four businesses, you can break down the value into each of those businesses, and I do so below:

Just as a note of caution, these businesses are all linked together, since the battery technology that drives the auto and energy businesses are shared, and FSD software sales will be tied to car sales. Consequently, you would not be able to spin off or sell these businesses, at least as these estimated values, but it does provide a sense of investors should watch for in this company. Thus, with a chunk of value tied to FSD, from software and robotaxis, any signs of progress (failure) on the FSD front will have consequences for value.

An Action Plan

    As you review my story and numbers, you will undoubtedly have very different views about Tesla going forward, and rather than tell me that you disagree with my views, which serves neither of us, please download the spreadsheet and make your own projections, by business. So, if you believe that I am massively underestimating the size of the robotaxi business, please do make your own judgment on how big it can get, with the caveat that making that business bigger will make your auto and software businesses smaller. After all, if everyone is taking robotaxis, the number of cars sold should drop off and existing car owners may be less likely to pay extra for a FSD package. 

    At $197 a share, Tesla remains over valued, at least based on my story, but a stock that has dropped $54 in price in the last few weeks could very well drop another $20 in the next few. To capture that possibility, I have a limit buy at my estimated value of $180, with the acceptance that it may never hit that price in this iteration. For those of you who wonder why I don't have a margin of safety (MOS), I have argued that the MOS is a blunt instrument that is most useful when you are valuing mature companies where you face a luxury of riches (lots of under valued companies). Furthermore, as my January 2023 simulation of Tesla value reveals, this is a company with more upside than downside, and that make a fair-value investment one that I can live with.  Put simply, the possibility of other businesses  that Tesla can enter into adds optionality that I have not incorporated into my value, and that acts as icing on the cake.

    Obviously, and this will sound like the postscript from an email that you get from your investment banking friends, I am not offering this as investment advice. Unlike those investment banking email postscripts, I mean that from the heart and am not required by either regulators or lawyer to say it. I believe that investors have to take ownership of their investment decisions, and I would suggest that the only way for you to make your own judgment on Tesla is to frame your story, and value it based on that story. Of course, you are welcome to use, adapt or just ignore my spreadsheet in that process.

YouTube Video

Data and Spreadsheets

1. Tesla 10Q  (third quarter of 2023)
2. My Tesla Valuation (October 30, 2023)

META Lesson 3: Tell me a story!

In my first two posts on Facebook, I noted that its most recent earnings report, and the market reaction to it, offers an opportunity for us to talk about bigger issues. I started by examining corporate governance, or its absence, and argued that some of the frustration that investors in Facebook feel about their views being ignored can be traced to a choice that they made early to give up the power to change management, by acquiescing to dual class shares. Facebook, I argued, is a corporate autocracy, with Mark Zuckerberg at its helm. In the second post, I pointed to inconsistencies in how accountants classify operating, capital and financing expenses, and the consequences for reported accounting numbers. Some of the bad news in Facebook's earnings report, especially relating to lower profitability, reflected accounting mis-categorization of R&D and expenses at Reality Labs (Facebook's Metaverse entree) as operating, rather than capital expenses. In fact, I concluded the post by arguing that investors in Facebook were pricing in their belief that the billions of dollars the company had invested in the Metaverse would be wasted, and argued that Facebook faced some of the blame, for not telling a compelling story to back the investment. In this post, I want to focus on that point, starting with a discussion of why stories matter to investors and traders and the story that propelled the company to a trillion-dollar market capitalization not that long ago. I will close with a  look at why business stories can break, change and shift, focusing in particular on the forces pushing Facebook to expand or perhaps even change its story, and whether the odds favor them in that endeavor.

Narrative and Value

As someone who has spent the last four decades talking, teaching and doing valuation that we have lost our way in valuation. Even as data has become more accessible and our tools have become more powerful, it is my belief that the quality of valuations has degraded over time. One reason is that valuation, at least as practiced, has become financial modeling, where Excel ninjas pull numbers from financial statements, put them into spreadsheets and extrapolate based upon past trends. Along the way, we have lost a key component of valuation, which is that every valuation tells a business story, and understanding what the story is and its weakest links is key to good valuation,

The Connection

In the first session of my valuation class, I pose a  question, "What comes more naturally to you, telling a story or working with numbers?", and I very quickly add that there is no right answer that I am looking for. That is because the answer will vary across people, with some exhibiting a more natural tendency towards story-telling and others towards working with numbers. In my valuation classes, the selection bias that leads people to come back to business school, and then to pick the valuation class as an elective, also results in the majority picking the "numbers" side, though I am glad to say that I have enough history majors and literature buffs to create a sizable "story" contingent. In the immediate aftermath, I then put forth what I believe is one of the biggest hidden secrets in valuation, which is that a good valuation is not just numbers on a spreadsheet, which is the number-crunching vision, or a big business story, which is the story-tellers' variant,  but a bridge between stories and numbers:

To explain what I mean by "a bridge", in a good valuation, every number you have in your valuation, from growth to margins to risk measures, should be backed up by a story about that number, and every story you tell about a company, including its great management, brand name or technological edge, has be reflected in a number in your valuation. If making this connection comes naturally to you, you are lucky and definitely the exception, because it is hard work for the rest of us. As someone who is more  naturally drawn to numbers, I came to the recognition of the need for stories late to the game, and I had not only to teach myself how to tell stories but also create a process where I stayed disciplined about incorporating them into valuations. In case you are interested, I did write a book on the process that I use to convert stories to numbers, but if you are budget-constrained, many of the ideas in the book are captured in posts that I have done over time on valuation.

Stories + Numbers: The Symbiosis

    The challenge in valuation, and it has only become worse in time, is that the divide between story tellers and number crunchers has only become wider over time, and has reached a point where each side not only does not understand the other, but also views it with contempt. Venture capitalist, raised on a  diet of big stories and total addressable markets has little in common with bankers, trained to think in terms of EV to EBITDA multiples and accounting ROIC, and when put in a room together, it should come as no surprise that they find each other's language indecipherable. At the risk of being shunned by both groups, I will argue int his section that each side will benefit, from learning to understand and use the tools of the other side.

1. Why stories matter in a numbers world

    If you are a numbers valuation, you start with some advantages. Not only will you find financial statements easier to disentangle, but you will also be able to develop a framework for converting these numbers to forecasts fairly easily. In other words, you will have no trouble creating something that looks like a legitimate valuation, with numbers details and an end value, even if that value is nonsensical. With a just-the-numbers valuation, there are four dangers that you face:

• Play with numbers: When a valuation is all about the numbers, it is easy to start playing with the numbers, unconstrained by any business sense, and change the value. It is not uncommon to see analysts, when they estimate a value that they think is "too low", to increase the revenue growth rate for a company, holding all else constant, and increase the value to what they would "like it to be".
• False precision: Number crunchers love precision, and the pathways they adopt to get to more precise valuations are often counter-productive, in terms of delivering more accurate valuations. From estimating the cost of capital to the fourth decimal point to forecasting all three accounting statements (income statements, balance sheet and statement of cashflows), in excruciating detail, for the next 20 years, analysts lose the forest for the trees, and produce valuations that look precise, but are not even close to being estimates of true value.
• Drown in data: If the complaint that analysts in the 1970s and even the 1980s might have had is that there was not enough data, the complaint today, when they value companies, is that there is too much data. That data is not only quantitative, with company disclosures running to hundreds of pages and databases that cover thousands of companies, but also qualitative, as you can access every news story about a company over its history, and in real time. Without guard rails, it is easy to see why this data overload can overwhelm investors and analysts, and lead them, ironically, to ignore most of it.
• Denial of biases: It is almost impossible to value a business without bias, with some bias coming from what you know about the business and some coming from whether you are getting paid to do the valuation, and how much. In a valuation driven entirely with numbers, analysts can fool themselves into believing that since they work with numbers, they cannot be biased, when, in fact, bias permeates every step in the process, implicitly or explicitly. Put simply, there are very facts in valuation and lots of estimates, and if you are making those estimates, you are bringing your biases 

If you are a number-cruncher, at heart, and have run into these or other problems when valuing companies, bringing numbers into your valuation can not just alleviate these problems, but also help you in convincing not just other people, but yourself, about your valuation.

• Stories are memorable, numbers less so: Even the most-skilled number cruncher, aided and abetted with charts and diagrams, will have a difficult time creating a valuation that is even close to being as good a compelling business story, in hooking investors and being memorable. I believe that long after my students have forgotten what growth rates and margins I assumed in the valuation of Amazon that I showed them in 2012, they will remember my characterization of Amazon as my "field of dreams company", built on the premise that if they build it (revenues), they (profits) will come. 
• Stories allow for consistency-tests: When your valuation numbers come from a story, it becomes almost impossible to change one input to your valuation without thinking through how that change affects your story. An increase in revenue growth, in a company in a niche market with high margins, may require a recalibration of the story to make it a more mass-market story, albeit with lower margins. 
• Stories allow you to screen and manage data: Having a valuation story that binds your numbers together and yields a value also allows you a framework for separating the data that matters (information) from the data that does not (distractions), and for organizing that data. 
• Stories lead to business follow-through: If you are a business-owner, valuing your own business, understanding the story that you are telling in that valuation is extraordinarily useful in how you run the business. Thus, if you want to follow Amazon's path to the Field of Dreams, your business strategy should be built around expanding your market and increasing revenues, while also mapping out a pathway to eventually monetizing those markets and gaining access to enough capital to be able to do so.

If you are a number cruncher like me, you will find that adding a story to your valuation will only augment your number skills and improve your valuations.

2. Why numbers matter in a story world

    I am not a story-telling natural, but I have tried to look at valuation, through the eyes of story tellers, over the last few years. Again, you start with some advantages, as a skilled story teller, especially if you also have the added benefit of charisma. You can use your story telling skills to draw investors, employees and the rest of the world into your story, and if you frame it well, you may very well be able to evade the type of scrutiny that comes with numbers. There are dangers, though, including the following:

• Fairy tales: Without the constraint of business first principles or explicit numbers about key inputs, you can tell stories of unstoppable growth and incredible profits for your company that are alluring, but impossible. If you are a con man, that is your end game, but even if you are not a con man, it is easy to start believing your own tall stories about businesses. As you watch the unraveling of FTX, you have to wonder whether Sam Bankman-Fried (SBF) set out to create a crypto-based Ponzi scheme, or whether this is the end result of a business story that was unchecked by any of the big name investors who participated into its growth.
• Anecdotal evidence: Story tellers tend to gravitate towards anecdotal data that supports their valuation stories. Rather than drown in the data overflow world we live in, story tellers pick and choose the data that best fits their stories, and use them to good effect, often fooling themselves about viability and profitability along the way.
• Unconstrained biases: If number crunchers are in denial about their biases, story tellers often revel in their biases, presenting them as evidence of the conviction that they have in their stories. Using the FTX example again, SBF was open about his belief that the future belonged to crypto, and that his entire business was built on that belief, and to his audience, composed of other true crypto-believers, this was a plus, not a minus.

In every market boom, you see the rise of story tellers, and while many crash and burn like SBF, as reality bites, there are a few that succeed, building some of our greatest business successes. One reason is that they find a way to bring numbers into their stories, with the following benefits:

• Numbers give credibility to stories: As we noted in the last section, stories are hooks that draw others to a business idea, but it may not be enough to get them to invest their money in it. For that to happen, you may have to use numbers to augment and back up your business story to give it credibility and create enough confidence that you have the business sense to make it succeed. 
• Numbers allow for plausibility checks: If you are on the other side of a valuation pitch, especially one built almost entirely around a story, the absence of numbers can make it difficult to take the story through the 3P test, where you evaluate whether it is possible, plausible and probable. It is your obligation as an investor to push for specificity, often in terms of the market that the business is targeting and the market share and profitability numbers that will determine its profitability. Again, business owners and analysts who can respond to this demand for specifics and numbers are more likely to get the capital that they seek. 
• Number create accountability: For business owners and managers, the use of numbers allows for accountability, where your actual numbers on total market size, market share and profitability can be compared to your forecasts. While that lead to uncomfortable findings, i.e., that you delivered below your expectations, it is an integral part of building a successful business over time, since what you learn from the feedback can allow you to alter, modify and sometimes replace business models that are not working well.

Just as great number crunchers can benefit from bring stories into their valuations, great story tellers will benefit by bringing in numbers to add discipline to their story telling.

The Facebook Narrative

    In the last few months, as Facebook has collapsed, investors seem to have forgotten about its astonishing climb in the decade prior, with market capitalization increasing from $100 billion at its IPO in 2012 to its trillion-dollar capitalization in July 2021. In my view, a key factor behind the stratospheric rise was the valuation story told by and about the company, and the story's appeal to investors.

The Facebook Story

    The core of the Facebook story is its mammoth user base, especially if you include Instagram and WhatsApp as part of the Facebook ecosystem, but if that is all you focused on, you would be missing large parts of its appeal. In fact, the Facebook story has the following constituent parts:

1. Billions of intense users: If there is one lesson that we should have learned from our experiences with user-based and subscriber-based companies over the last decade, it is that not all users or subscribers are created equal. With Facebook, it is not just the roughly three billion people who are in its ecosystem that should draw your attention, but the amount of time they spend in it. Until TikTok recently supplanted it at the top, Facebook had the most intense user base of any social media platform, with users staying on the platform roughly an hour a day in 2019.
2. Sharing personal data in their postings: As a platform that encourages users to share everything with their "friends", it is undeniable that Facebook has accumulated immense amounts of data about its users. If  you are a privacy purist, and you find this unconscionable, it is worth noting that these users were not dragged on to a platform and forced to share their deeply personal thoughts and feelings, against their wishes. 
3. Which could be utilized to focus advertising at them: In 2018, at the peak of the Cambridge Analytica scandals, when people were piling on Facebook for its invasion of privacy, I noted invading user privacy, albeit with their tacit approval, lies at the core of Facebook's success in online advertising. In short, Facebook uses what it has learnt about the people inhabiting its platform to focus advertising to them.
4. In a world where online ads were consuming the advertising business: Facebook also benefited from a macro shift in the advertising business, where advertisers were shifting from traditional advertising modes (newspapers, television, billboards etc.) to online advertising;  online advertising increased from less than 10% of total advertising in 2005 to close to 60% of total adverting in 2020.

In sum, the story that took Facebook to the heights that it reached in July 2021 was that of an online advertising juggernaut, whose success came from using the data that it had acquired on the billions of users who spent a chunk of their days on on its platform, to deliver focused advertising. 

And its appeal

    Every business, especially in its youth, markets itself with a story and it is worth asking why investors took to Facebook's story so quickly and attached so much value to it.

1. Simple and easy to understand: In telling business stories, I argue that it pays to keep the story simple and to give it focus, i.e., lay out the pathways that the story will lead the company to make money. Facebook clearly followed this practice, with a story that was simple and easy for in investors to understand and to price in. Just to provide a contrast, consider how much more difficult it is for Palantir or Snowflake to tell a business story that investors can grasp, let alone value.
2. Personal experiences with business: Adding to the first point, investors feel more comfortable valuing businesses, where they have sampled the products or services offered by these businesses  and understand what sets them apart (or does not) from the competition. I would wager that almost every investor, professional or retail, who invested in Facebook has a Facebook page, and even if they do not post much on the page, have seen ads directed specifically at them on that page.
3. Backed up by data: In the last decade, we have seen other companies with simple stories that we have personal connections to, like Uber, Airbnb and Twitter, go public, but none of them received the rapturous response that Facebook did, at least until July 2021. The reason is simple. Unlike those companies, Facebook, from day one as a public company, has been able to back its story up with numbers, both in terms of revenues and profitability, as can be seen in the graph below, where I look at its revenues and operating profits from 2012 to 2021:
   
   
   

With revenues growing from less than $4 billion in 2011 to $118 billion in 2021, and operating margins of more than 40%,through almost the entire period, it is easy to see why both value and growth investors gravitated to this stock.

With value consequences

    I have valued Facebook many times over the last decade, and have bought and sold based upon my valuations. For those of you who have been following these valuations, I am sure that you are well aware that my most recent valuation of Facebook, at the end of February 2022, was $346 per share, well above the stock price then of $220/share:

Having bought shares in the company at $133/share after the Cambridge Analytica scandal in 2018, I stayed invested in the company. Obviously, at today's price of just over $100/share, it should be time for regrets, but I have none. There are clearly aspects of my valuation, where I overreached, including revenue growth of 8% a year that I would reset to a lower number, with the recognition that online advertising is seeing growth level off, faster than I thought it would, and is more cyclical than I assumed it would be. As for profitability, my estimated target operating margin of 40% looks hopelessly optimistic, given that the operating margins in the last twelve months is closer to 20%, but as I noted in my last post, that drop is less a reflection of a collapse in the online advertising business model and more the result of Facebook's big bet of Metaverse, and the expenses emanating from that bet.

Narrative Changes and Resets

    The value of a business is, in large part, driven by your story for the business, but that story will change over time, as the business, the market it is in and the macro environment change. In some cases, the story can get bigger, leading to higher value, and in some, it can get smaller, and we will begin by looking at why business stories change, and classify those changes, before looking at the Facebook story.

Narrative Breaks, Changes and Shifts

   If business stores change over time, what form will that change take? To answer the question, I broke down business story changes into three groups, with the proviso that there are some business changes that fall into more than one group:

1. Story breaks: The most consequential value change comes from a story break, where a key component of a business story breaks, sometimes due to external factors and sometimes due to miscalculations and missteps on the part of the management of the company.  In the former group, we would include acts of God (terrorism, a hurricane or COVID) and regulatory or legal events (failure to get regulatory approval for a drug, for a pharmaceutical company) that put an end to a business model. In the latter, we would count companies where management pushed the limits of the law to breaking point and beyond, damaging its reputation to the point that it cannot continue in business. 
2. Story shifts: At the other end of the spectrum are story shifts, where the core business model remains intact, but its contours (in terms of growth, profitability and risk) change, as the result of market changes (market growth surges, slows or stalls), competitive dynamics (a competitor introduces a new product or withdraws an existing one) or technology (working in favor of the story or against it). Note the resulting changes in value can be substantial, and in either direction, depending on how and how much the valuation inputs change as a result of the story shift. 
3. Story changes: Finally, there are story changes, where a company augments an existing business story by investing in or acquiring a new business, shrinks its existing business by withdrawing or divesting an existing business or product or attempts a story reset or rebirth, by replacing an existing business story with a new one.

I summarize these possible story alterations in the picture below:

As you can see from the types of changes that can occur, some business story changes are triggered by external forces, and can be traced to changes in macroeconomic conditions, country risk or regulatory/legal structures, some business story changes are the result of management actions, at the company or at its competitors and some business story changes are the consequence of a company scaling up and/or aging. It is worth noting that disruption, at its core, creates changes to a sector or industry that can break some status-quo businesses, while creating new ones with significant value.

Facebook: A Narrative Reset?

    In the last section, we looked at the incredible success that Facebook had between 2012 and 2021 with its user-driven, online advertising business model, both in terms of market capitalization (rising from $100 billion to $ 1 trillion) and in terms of operating results. You may wonder why a company that has had this much success with its story would need to change, but the last year and a half is an indication of how quickly business conditions can change.

Forces driving a reset

    Facebook's original business story was built on two premises, with the first being the use of data that it obtained on its customers to deliver more focused advertisements and the second being the rapid growth in the online advertising business, largely at the expense of traditional advertising. Both premises are being challenged by developments on the ground, and as they weaken, so is the pull of the Facebook story.

• On the privacy front, the Cambridge Analytica episode, though small in its direct impact, cast light on an unpleasant truth about the Facebook business model, where the invasion of user privacy is a feature of its business story, not a bug. Put differently, if Facebook decides not to use the information that you provide it, in the course of your postings, in its business model, a large portion of its allure to advertisers disappears. 
• The halcyon days of growth in the online advertising market are behind us, as it acquires a dominant share of overall advertising, and starts growing at rates that reflect growth in total advertising. As one of the two biggest players in the market, with Google being the other one, Facebook does not have much room on the upside for growth.

While many investors were shocked by the stagnant revenues that Facebook reported in its most earnings report, and some have attributed that to a slowing economy, the truth is that the pressures on Facebook's business story have been building for a while, and it is only the speed with which the story has unraveled that is shocking. 

Choices for the company

    Faced with slower revenue growth and concerned about the effect that privacy regulations in the EU and the US will alter its business model, Facebook has been struggling with a way forward. As I see it, there were three choices that Facebook could have made (though we know, in hindsight, which one they picked):

1. Acceptance: Accept the reality that they are now a mature player in a slow-growth business (online advertising), albeit one in which they are immensely profitable, and scale back growth plans and spending. While this may strike some as giving up, it does provide a pathway for Facebook to become a cash cow, investing just enough in R&D to keep its existing business going for the foreseeable future, while returning huge amounts of cash to its investors each year (as dividends or buybacks). 
2. Denial: View the slowdown in growth in the online adverting market as temporary, and stay with its existing business model, built around aggressively seeking to gain market share from both traditional players in the advertising market and smaller online competitors. With this path, the company may be able to post higher revenue growth than if it follows the acceptance path, but perhaps with lower operating margins and more spending on R&D, if market growth is leveling off.
3. Rebirth: The choice with the most upside as well as the greatest downside is for Facebook to try to reinvent itself in a new business. That may require substantial reinvestment to enter the business, and hopefully draw on Facebook’s biggest strength, i.e., its intense and mammoth user base. 

Facebook did pick the third path, and it made the choice well before the revenue slowdown in the most recent year, perhaps as early as 2014, with its acquisition of Oculus for $2 billion. In the last three years, the push into the Metaverse has intensified, with billions invested in Reality Labs and a name change for the company. 

Facebook has also telegraphed its commitment to be a leading player in this space, planning to invest close to $100 billion, over the next decade. The big question, as I noted in my last post, that hangs over the company is whether this investment can create enough in additional earnings and cash flows to cover these huge upfront costs.

What's the story?

    Facebook’s plans to invest tens of billions in the Metaverse makes it an expensive venture, by any standards, and there are some who suggest that it is unprecedented, especially in technology, which many view as a capital-light business. That perception, though, collides with reality, especially when you look at how much big tech companies have been willing to invest to enter new businesses, albeit with mixed results. 

• Microsoft invested $15 billion for its entry in 2015 into Azure, its cloud business, and it has invested tens of billions in data centers since, expanding its reach. That investment has paid off both quickly and lucratively, and has played a role in Microsoft's rise in market capitalization.
• Google, renamed itself Alphabet in 2015, in a well-publicized effort to rebrand itself as more than just a search engine, and has invested tens of billions of dollars in its other businesses since, but with a payoff primarily in its cloud business, which generated $19.2 billion in revenues in 2021. Just to provide a measure of how its other bets are still lagging, Google generated only $753 million in revenues from its other businesses in 2021, almost unchanged from its revenues in 2019 and 2020.
• Amazon has also invested tens of billions in its other businesses, with its biggest payoff coming in the cloud business (notice a pattern here). It has much less to show for its investments in Alexa and entertainment, and it is estimated to have lost $5 billion on its Alexa division in 2021 and spent $13 billion on new content for Amazon video.

Facebook, Microsoft and Google have all used the cash flows from their core businesses (Online advertising for Facebook and Google, Windows and Office for Microsoft) to fund their entry into new businesses, but at Amazon, it is the AWS (its cloud business) that has provided the profits and cash flows to cover its growth plans in other businesses.

   Facebook's investment plans for the Metaverse represent a big bet, but it is not an unprecedented one, which raises the question of why investors have been less willing to cut it slack than they have for its large tech competitors. One reason is timing, since markets are much more receptive to big growth investments, when times are good, as they were for much of the last decade, than in bad times, as much of 2022 has been. The other is the story line that backs the investment. Fairly or otherwise, the big cloud investments that Microsoft, Google and Amazon made came with story lines of growth and profitability that investors bought into, and for the most part, the results have justified that view. The more opaque investments, including Google's bets and Amazon's Alexa and prime video spending have been viewed more skeptically. The problem that most investors have with Facebook's Metaverse investment is that it is not just that the payoff is uncertain, but it is unclear what business the payoff will come from. After all, the Metaverse is a space (virtual), not a business, and to make money in that space, you need a business model, which Facebook has not provided much guidance on. In fact, the most detailed document that I was able to find anything on Facebook's Metaverse plans were from 2015, where Zuckerberg described his vision for the business, and from 2018, in a 50-page presentation that Facebook, where the company talks about revenues coming from advertising and hardware, but only in very general terms. It is true that Facebook has laid out its Connect 2021 vision online, but the document is heavy on hype and technology, and light on business details.

    As I see it, the combination of market conditions and opacity about business plans is creating the worst of all combinations for Facebook, in financial markets. The market has clarity about how much Facebook plans to spend on the Metaverse and is not just skeptical, but extremely confused, about how exactly Facebook will make money in the Metaverse. To give you a sense of how negative investors are about Facebook's future prospects, I created the most conservative estimate of value, which I call my Doomsday valuation, for the company based upon the following assumptions:

1. I used the company's actual operating income from its online advertising business from the last twelve months, weighed down as they are from a slowing economy and a stronger economy, and assumed no growth and a remaining life of 20 years for the business, with a zero liquidation value at the end of year 20.
2. I assumed that the company will continue to spend R&D at the same scorching rate that it set in the last twelve months, where it spent just over $32 billion on R&D, for the next 20 years.
3. I also assumed that not only will Facebook to lose $10 billion a year on the Metaverse, but also that this will continue for the next decade and beyond, with no payoff in terms of increased revenues or earnings from this spending.
4. I assume that Facebook is a risky company, falling at the 75th percentile of all US companies in terms of risk, and give it a cost of capital of 9%.

The table below shows the value that I estimate with this combination of assumptions, and compares it to the value that I would obtain, if I removed the Metaverse numbers from the valuation:

Download spreadsheet

Note that in Doomsday scenario, where Facebook continues to spend money on R&D and invest heavily in the Metaverse, with no payoff in higher growth or longer business life from those investments, the value of equity that I obtain is $258.6 billion. Doing the valuation with the Metaverse revenues and expenses removed from the mix yields $330 billion, suggesting that treating the entire Metaverse investment as wasted expenditure reduces Facebook's value by approximately $71 billion.  

The market capitalization of Facebook on October 29, 2022 was $247 billion, below the Doomsday scenario value,  indicating that investors were, in fact, treating the $100 billion to be invested in the Metaverse as a wasted expense, a remarkably cynical and pessimistic take on a  company that has had a history of delivering profits. The market capitalization has risen to $311 billion as of November 15, 2022, and while that suggests a more positive perspective, that value still reflects a presumption that the Metaverse investment will destroy about $18.9 billion of Facebook's value. In truth, using a more realistic growth rate (rather than zero) or lowering the cost of capital (from 9% to 8%, the median cost of capital for a US company) or extending the life of the company (from 20 years to a longer period) can only add value to Facebook, and you can experiment with these inputs in the attached spreadsheet.

Turning the Trust Corner

    It is undeniable that Facebook has lost the trust of investors, and that it is being priced on assumptions that reflect that mistrust. In my experience, trying to jawbone investors to trust you does not work, but there is a plan of action that Facebook can follow, that will start the process of rebuilding trust :

1. Tell with a business story for the Metaverse: Investors do not have a clear sense of what the Metaverse is, and more importantly, the business opportunities that exist in that space. Facebook needs to fill in that gap with a business story for its investments, laying out what is sees as a pathway to making money in that virtual world, as well as the strengths it will bring to delivering value on this path. I am sure that Facebook is much more qualified than I am to frame this story, but just in case they could use some guidance, here are a few possible Metaverse business models:
   
   
   Of these choices, advertising clearly is the most logical extension of their existing business, but it also offers the least upside, since the company is already a dominant player in the online ad business. The acquisition of Oculus and the VR headsets that Facebook sells give it a foothold in the hardware business, but hardware is a business with lower margins and limited market size. The most lucrative story, in my view, is a ecosystem story, where Facebook gains a dominant share of the virtual world, and takes a slice of any business (transactions, gaming, subscriptions) done in that world, mirroring what Apple has done in its iPhone ecosystem. It is worth remembering that the audience that you are trying to sell this business story to is not the audience that you will be seeking out in the Metaverse, which would imply that your story should be less about technology and more about business. (I may be old and cranky. I have zero interest in the virtual world, but as a Facebook investor, I would be interested to learn its business model for this world.) 
2. Build in specifics into your investment story: Facebook has been clear about its plans to invest billions in its new businesses, but rather than just emphasizing the total amount that it plans to make, it would be better served connecting its investment plans with the business story being told. If nothing else, it would be useful to know how much of the $12 billion spent in Reality Labs was spent on people, on technology, on software and in making better VR glasses and why all of this spending is bringing the company closer to a money-making business model.
3. With markers on operating payoffs: I know that there are huge uncertainties overhanging these investments, but it would still make sense to give rough estimates of how Facebook expects revenues and operating margins to evolve on its Metaverse investment, over time. That will give investors and managers targets to track, as the company delivers results, and use the results (positive or negative) to make changes in the way future investments are made.
4. And escape hatches, if things don't work out: While many companies refuse to talk about what their plans are, if a business does not pan out, viewing it as a sign of weakness or lack of conviction, I believe that Facebook will be best served if they are open about what can go wrong with their Metaverse bet, and not only about what they are doing to protect themselves, if it happens, but also exit plans, if they decide to walk away. After all, if the market is already assuming the worst, as it was just a couple of weeks ago, how can any scenario you present, no matter how negative, worsen your market standing?

As I mentioned in my first post on Facebook a couple of weeks ago, I made an exception to my rule of not doubling down and doubled my holding of Facebook on November 4, 2022, because its valuation looks compelling. I did so with the acceptance that I will have little influence over the management of the company, in general, and Mark Zuckerberg, in particular, and it is entirely possible that I will come to regret it. If I do so, I am sure that many of you will remind me, and I okay with that as well!

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Spreadsheet 

1. Metaverse Value Effect

Facebook 2022 Earnings Report Posts

1. Facebook (Meta) Lesson 1: Corporate Governance
2. Facebook (Meta) Lesson 2: Accounting inconsistencies and consequences
3. Facebook (Meta) Lesson 3: Tell me a story!