What We’re Reading (Week Ending 14 January 2024) - 14 Jan 2024
Reading helps us learn about the world and it is a really important aspect of investing. The late Charlie Munger even went so far as to say that “I don’t think you can get to be a really good investor over a broad range without doing a massive amount of reading.” We (the co-founders of Compounder Fund) read widely across a range of topics, including investing, business, technology, and the world in general. We want to regularly share the best articles we’ve come across recently. Here they are (for the week ending 14 January 2024):
1. The Impact of Shipping Disruptions in the Red Sea – Tracy Alloway, Joe Weisenthal, Mohsis Andam, and Craig Fuller
Joe (04:00):
There really is a lot to talk about, but why don’t we start off with the disruptions in the Red Sea. Why don’t you characterize, as you see it, the situation right now?
Craig (04:10):
So, I think there’s the short term anxiety that exists in terms of the safety of the crews, the dependability of the global supply chain. A lot of short-term concern, but I think the bigger story [that] is going to play out over the next couple of years is we’re now reaching a point in history where global trade and global shipping is no longer as dependable or as predictable as it has been really since the post Cold War period. Civilian ships are being fired upon. And this is an unusual development that we haven’t seen for really many decades…
…Tracy (04:46):
So walk us through the importance of the Red Sea route. What kind of ships are actually going up and down?…
…Craig (04:59):
There’s a lot of oil and gas, obviously being in the Middle East, it has a lot of exposure to oil and gas and the derivative products that come out of that portion of the world. But it’s also one of the major trade lanes for container flows. And so, think of what moves in container. It’s largely manufactured and consumer goods that are largely dependent upon containers. A lot of these products are coming from Asia, and particularly China into Europe, some products going to the United States East Coast. But the predominance of the products that move through the Suez in the container freight is largely related to products out of Asia, going to Europe for European consumption.
Tracy (05:36):
What other routes are available for that kind of trade?
Craig (05:40):
Well, you have to go around South Africa, and so you’re really adding thousands of miles of additional distance when you aren’t able to cut through the shortcut that is the Suez. I mean, [the] Suez Canal has cut out an enormous amount of distance that geographically the ships have historically had to go around with the Suez. It was able to sort of expedite trade flow from Asia, in particularly to Europe. We do benefit from it in North America, but a much smaller percent of the freight that we depend on in the United States is dependent upon the Suez.
Joe (06:16):
What is the historical role of the US Navy in securing or protecting some of these routes, and what are we seeing from US defense officials now at this acute moment?
Craig (06:29):
There’s a lot of conversation in geopolitical circles about whether the Navy’s role has changed or shifted or is no longer effective in the role that it was believed to be played for the last, really since World War II. So if you think about it, the United States has the largest navy in the world. It’s also a one of the only Blue Water navies that can go anywhere to defend any place on the planet. And that’s really the call to fame.
Joe (06:57):
Sorry, what does it mean “Blue Water?”
Craig (06:58):
It means that they can go into deep oceans…
…They can be anywhere. Basically, there’s no place on the planet that the Navy and the Marines can’t actually reach. And so, the whole purpose of that is to protect trade lanes. That is one of the primary calls of the US Navy is its role is to protect commerce and ensure global trade and really the world. And China has mostly benefited from that, [the] US Navy’s role of protecting sea from things like pirates and state sponsors that want to attack global trade.
And the question now is in a post-, we’re now in this sort of new generation of trade, what does it mean? There’s a lot more protectionism that happens with US policy. And really to be able to defend the role of the US Navy being able to protect all aspects of it with geopolitical tensions in East Asia means that we may not have the resources to actually protect all aspects of trade the way that we did at one point in time.
Joe (08:02):
Just real quickly, pirates and pirate attacks, and you mentioned them, they’re somewhat common. They’re in the news, but what’s different about this is that it’s missiles being fired. They’re not trying to steal the cargo. These are military attacks on private corporation.
Craig (08:23):
These are military techniques…
…Craig (08:26):
We’ve seen helicopters actually land on tops of ships and actually take cruise hostage by way of helicopter. It looks like a SWAT. You probably have seen the video floating around where it looks like a SWAT video. Where they’re flying in and they’re basically taking over a ship through use of a helicopter. We’re seeing situations where, as you mentioned, they’re using missile technology, military grade technologies, which is an unusual development. And then with the proliferation of drones, you now have a low cost way to actually avoid some of the defenses that are set up to protect these ships that they’re able to reach them without, without obstruction.
And I think that has changed the game. And look, we can argue whether these are truly state sponsored or not, but at the end of the day they have access to military grade technology and they are using this to attack civilian vessels. And their goal is to disrupt global trade.
Tracy (09:23):
This was going to be my next question, which is, even if the Navy said, yes, absolutely, we’re going to go in, we’re going to protect all the ships. How much can they actually do in the face of that kind of threat, which has new technology that they’re clearly using, but is also very, very flexible in terms of what it can do?
Craig (09:45):
I think the question is at what cost? Because, I think the US has the capabilities to largely defend every ship or the ships that we have decided to defend. But at what cost? I mean, you’re looking at a missile, anti-missile technologies, a million dollars. We’re firing these defense missiles off at a million dollars apiece, and you’re fighting a drone that cost a couple thousand dollars. I mean, at some point there is a massive tax on US consumers and the US economy for us to do this. And the question is what is our appetite to continue to fund this type of defense technology when the United States is not the primary beneficiary of that type of trade.
Tracy (10:25):
And on a similar note, I’m always curious about the decision-making process to not go through a certain route. So, Maersk said it wasn’t going to go through the Red Sea anymore after the missile was fired. What are the factors that go into making that type of decision? And then if the Navy were to say tomorrow that “We’re going to escort all of these ships”, would that completely address their concerns? Would they [say], “Okay, yes, we’re going to resume this route”?
Craig (10:52):
It’s a great question because, I don’t know that the US with all of our other geopolitical commitments, particularly around China and what’s happening around Taiwan. I mean, the Chinese want our Navies in the Middle East. That’s where they want them because [that] enables them to have an enormous amount of power over East Asia. They want us moving our assets and being distracted in the Middle East. So they actually win geopolitically in terms of their power over their region by moving, forcing us to be distracted in the Middle East. But I don’t know that we have all the resources to defend every single ship from these attacks. And ultimately, what the container lines have to really think about is what’s the cost of a ship? You’re talking hundreds of millions of dollars. What’s the cost of a cargo, again, measured in probably billions of dollars when we a look at a 20,000 TEU (Twenty-foot equivalent unit) ship. And then you have the insurance companies which are saying, “Hey, we’re not going to insure these ships that go through these channels.” And that means that ultimately Maersk and others have to look at alternative routes. They will obviously protect their crews. The crews do understand that, the nature of their jobs is on occasion they put themselves in harm’s way. And we’ve seen that with the movie with Tom Hanks plays as the Captain…
…Joe (28:26):
Well, I’m glad you mentioned the freight tech companies because that’s where I was going to go next. So we already said, we already know it was bad for a lot of companies in 2023. But, going back to 2021, 2022, we got interested in freight, obviously on the Odd Lots podcast, that was also a big year for tech and tech investing.
A lot of VCs suddenly probably woke up to this idea, this world we’re like ‘Oh, the freight industry looks like a mess. I’m sure if we just apply our software magic, we can solve all of these problems.’ We saw some really huge fundraising, but then also in 2023, we saw the reversal of it. So we saw the freight brokerage, Convoy, just basically completely go out of business. I think we saw a pretty big downturn at Flexport. We’ve had their CEO Ryan Peterson on the show a couple of times.
What happened with freight tech? What were the theses maybe of the investors who were going in, they’re [thinking] ‘Oh we can solve this.’ And what reality did they run into that maybe it’s a bit harder to solve some of these problems then they may have assumed?
Craig (29:31):
You know, they were playing the Uber, Lyft, even Airbnb playbooks, which is, ‘Hey, I have this capacity and I can go out and create a digital app. If I could disrupt the taxi industry the way Uber did. Then I could also disrupt the trucking industry.”…
…Craig (29:47):
Here’s the problem, is that the investors that really drove the high valuations didn’t understand freight. They didn’t understand the boom and bust cycle. Convoy arguably had the best roster. Like, it had a dream team of investors. I mean, you had Bill Gates, Jeff Bezos, you had Reid Hoffman, you had the who’s who of sort of Silicon Valley and legacy tech that were investors. I mean, it was the best lineup of investors of probably any company in supply chain you could possibly have. And yet that did not help them survive.
And the reason is that really the investors and the management team, when it first raised money and got into this business, did not understand how cyclical this industry is and how fungible the capacity is. So if I want to disrupt the taxi industry, the reason that that works is I have all of these consumers sitting at home with their cars that are idle 90% of the time. That can create incremental capacity in and out of a market. So as the market surges, you can have, and Uber has piloted this with their search pricing, they will send out messages to their drivers and say, ‘Hey, there’ a football game in town, or there’s a big event in town, please come out and get three to four or five X your normal rate.’ And they’ve created this sort of surge flexible capacity model that works really well in a business like Uber and personal transportation.
The problem in trucking is there is none of that excess capacity sitting against the fence that can flex in and out of a market. And so what ultimately happened is that they were able to apply some digitization to the dispatch process and to the driver management process. But that was incremental. And one would argue, and Brad Jacobs has argued that the incumbents were doing the same thing, is that effectively all of these companies were spending billions of dollars to build technology that everyone else was also building. And not just existing companies like XPO and CH Robinson, but you also had all these tech vendors, companies that provide software that were also building technology that they could sell to hundreds of companies.
All this was happening at the same time. And effectively what Convoy did not understand early on, which I think they certainly understood at the late part of the cycle, a late part of their business is that freight is commodity, it’s highly fungible. The capacity is highly fungible. And no matter how much money I spend acquiring the capacity, there is nothing to keep that capacity from going to the next highest bidder. And because of that, all of the money that they wasted in acquisition costs to acquire capacity was effectively meaningless at the end of the day because that capacity could be found elsewhere….
…Craig (37:35):
So it’s interesting because Brad talked about the fact that when he got in this industry 10 years ago it was largely humans and then over time it had digitized. And I think the statement was he had 97% of its freight was electronic. That very well may be the case for his business. Think of XPO’s role in the business. It’s a big really predominantly, in its focus on LTL, which means it has very large enterprise shippers, big commitments. It’s able to digitize a lot of the transactions. And most of the bigger trucking companies are digital. Like if you go look at Knight-Swift’s operation, okay, look at Schneider’s operation, go look at Old Dominion.
Joe (38:13):
And so that is like placing an order on a thing and it automatically…
Craig (38:15):
That’s right. Okay. And that’s what the big companies want to do. Okay. Is they actually want to eliminate human contact as much as possible. Yeah. Because that’s how they’re able to optimize the, the model. They use technology to do electronic transactions and that is, that probably represents 20% of the business. It’s the cream of the crop business. It’s the business that every company wants because it’s the high volume shippers, dependable volume and…
Joe (38:41):
Standardized lanes, standardized shippers, standardized carriers. Over and over.
Craig (38:45):
Exactly. Highly predictable. Yeah. Highly consistent business. And if you’re building a network, then that’s what you want. Because I can depend on it day in, day out. That’s what the larger companies focus on. I see. And if, if you ask the CEO of Knight-Swift, you would probably get a similar answer about how much of its freight is electronically tendered. CH Robinson the largest freight broker in the country publishes that 78% of its freight doesn’t have a human touch. But the reality is, Joe, is that the hundreds of thousands of freight broker people that are out there making up, at least, the numbers are as high as registered freight brokers in the 60 to 80,000 numbers. We track and think there’s about 5,000 high scale freight brokers that do more than about $10 million in revenue a year. They’re still predominantly human-based and what they’re dealing with are the exceptions…
…Craig (39:39):
So what happens is, a large volume shipper takes 95% of its freight and sends it over to the XPOs and the CH Robinsons and the Knight-Swifts. And so they get all of the electronic stuff dispatched. What’s left over is the really hard to manage. It’s either a lane that nobody wants, it’s somebody who literally chop shops price on every single load. It’s a commodity that nobody wants. And you’ll see in the meme, if you go on Twitter or on X, you see all the memes and freight making fun of the kinds of freight that nobody wants. This is the type of freight that’s left over.
Joe (40:13):
What’s an example of a type of freight that no one wants to deal with?
Craig (40:16):
Grocery. Driver unload…
…Craig (40:21):
Well, it’s typically going to a grocery store. It takes a long time to unload it. They’re miserable because they’re in a cold trailer, in a refrigerated trailer, they have to use something called a Lumper. A Lumper is, I pay somebody at the dock to unload me, or the driver has to unload themselves. They can take eight to 10 hours to load at a farm. They go into a farm facility or distribution center because they’re all hand loaded. Think of like a crate of tomatoes or oranges or something. A lot of it’s loaded not on pallets, but actually sort of flow loaded. So this is undesirable freight for a lot of these guys. It has really tight transit times. So that’s a type of undesirable freight.
Flatbed, which is hauled to project sites. You’re not going to a warehouse, but you’re going to a construction site that has to be manually unloaded. It can take sometimes hours or longer where the truck’s got to sit. And so there’s a lot of freight that’s just undesired. And that’s where a lot of the freight brokers, the humans still take and manage a lot of these sort of long tail transactions. That isn’t the world that an XPO plays in. That is the world that the predominance of your freight brokerage…
…Joe (48:18):
One last quick question. I’m going to pivot. Founder and CEO of FreightWaves. We always talk to you about freight. You also have this whole other business and aviation media and other aviation assets. I want to do like an hour with you at some point. Talk about that. But just real quickly, is it really true that there’s more airports than McDonald’s in United States?
Craig (48:36):
This is an insane stat that no one, I think everyone finds it hard to believe. So if you take the total amount of private, this includes private airports and public airports. So most people think of airports, I’m thinking of like JFK and LaGuardia and Newark. The predominance, the vast majority of airports in the United States are actually privately owned airports or community owned airports. Places that have very small runways of a thousand to 2000, 3000 feet can’t accommodate even a jet. They’re accommodating small aircraft. Yeah. There’s 19,000 of those. And I think the number on McDonald’s is like 16,000…
…Craig (49:26):
People think that private airports is all about jets. And they always think it’s like really rich people. But the predominance of the folks that use these small airports are farmers and their agriculture. And our entire [agriculture] ecosystem is dependent upon airplanes and bees, but airplanes to do things. And so a lot of the airports are used in places out in the heartland for farming. They’re also used for things like mining extraction and stuff. And so the vast majority of those airports are very small airports that most people will never see, will never notice unless they get in a small airplane.
2. My Parents’ Dementia Felt Like the End of Joy. Then Came the Robots – Kat McGowan
WHEN MY MOM was finally, officially diagnosed with dementia in 2020, her geriatric psychiatrist told me that there was no effective treatment. The best thing to do was to keep her physically, intellectually, and socially engaged every day for the rest of her life. Oh, OK. No biggie. The doc was telling me that medicine was done with us. My mother’s fate was now in our hands…
…Beyond physical comfort, my goal as their caregiver was to help them to feel like themselves, even as that self evolved. I vowed to help them live their remaining years with joy and meaning. That’s not so much a matter of medicine as it is a concern of the heart and spirit. I couldn’t figure this part out on my own, and everyone I talked to thought it was a weird thing to worry about.
Until I found the robot-makers.
I’m not talking about the people building machines to help someone put on their pants. Or electronic Karens that monitor an old person’s behavior then “correct” for mistakes, like a bossy Alexa: “Good afternoon! You haven’t taken your medicine yet.” Or gadgets with touchscreens that can be hard for old people to use…
… Instead, the roboticists I learned about are trained in anthropology, psychology, design, and other human-centric fields. They partner with people with dementia, who do not want robots to solve the alleged problem of being old. They want technology for joy and for flourishing, even as they near the end of life. Among the people I met were Indiana University Bloomington roboticist Selma Šabanović, who is developing a robot to bring more meaning into life, while in the Netherlands, Eindhoven University of Technology’s Rens Brankaert is creating warm technology to enhance human connection. These technologists in turn introduced me to grassroots dementia activists who are shaking off the doom loops of despair…
…The robot-makers are a shaft of light at the bottom of the well. The gizmos they’re working on may be far in the future, but these scientists and engineers are already inventing something more important: a new attitude about dementia. They look head-on at this human experience and see creative opportunities, new ways to connect, new ways to have fun. And, of course, they have cool robots. Lots and lots of robots. With those machines, they’re trying to answer the question I’m obsessed with: What could a good life with dementia look like?
THE ROBOT’S TORSO and limbs are chubby and white. It seems to be naked except for blue briefs below its pot belly, although it does not have nipples. It is only 2 feet tall. Its face, a rectangular screen, blinks on. Two black ovals and a manga smile appear.
“Hello! I am QT, your robot friend,” it says. It says this to everyone, because that’s its job. QT raises both arms in a touchdown gesture. The motors whir. They sound expensive.
It might look and sound sort of familiar if you know anything about humanoid social robots—contraptions built to respond to us in ways we recognize. You may also remember their long history of market failures. RIP Kuri, Cozmo, Asimo, Jibo, Pepper, and the rest of their expensive, overpromising metal kin. QT is not like them. It is not a consumer product; it’s a research device equipped with microphones, a 3D camera, face recognition, and data recording capabilities, built by a Luxembourgian company for scientists like Šabanović to deploy in studies. She’s using QT to explore ikigai, a Japanese word that roughly translates to a reason for living or sense of meaning in life, but also includes a feeling of social purpose and everyday joy. Doing a favor for a neighbor can create ikigai, as can a hard week’s work. Even reflecting on life achievements can bring it on. Her team, funded by Toyota Research Institute, is tinkering with QT to see what kind of robot socializing—reminiscing, maybe, or planning activities, or perhaps just a certain line of conversation—might give someone a burst of that good feeling…
…One challenge is that dementia is never the same for any two people. There are different varieties, such as Alzheimer’s, frontotemporal dementia, and Lewy body disease, and they are dynamic, changing with time. Some people have no problem with memory but struggle with words; others make strange decisions. Many say their perception of time changes, or their senses become more acute. Some people are angrier, some calmer, and others lose all filters and say whatever they think…
… Today, Hsu will demo a storytelling game between person and machine. Eventually QT will retain enough information to make the game personalized for each participant. For now, the point is to test QT’s evolving conversational skills to see what behaviors and responses people will accept from a robot and which come across as confusing or rude. I’m excited to see how this plays out. I’m expecting spicy reactions. People with dementia can be a tough audience, with little tolerance for encounters that are annoying or hard to understand…
…Soon, Maryellen, an energetic woman in a red IU ball cap, walks in and takes a seat across from the robot. Maryellen has enjoyed talking to QT in the past, but she’s having an off day. She’s nervous. “I’m in early Alzheimer’s, so sometimes I get things wrong,” she apologizes.
The robot asks her to select an image from a tablet and make up a story. Maryellen gamely plays along, spinning a tale: A woman, maybe a student, walks alone in the autumn woods.
“Interesting,” says QT. “Have you experienced something like this before?”
“I have,” Maryellen says. “We have beautiful trees around Bloomington.” The robot stays silent, a smile plastered across its screen. QT has terrible timing, pausing too long when it should speak, interrupting when it should listen. We all share an apologetic laugh over the machine’s bad manners. Maryellen is patient, speaking to QT as if it were a dim-witted child. She understands that the robot is not trying to be a jerk.
Today’s robot-human chat is objectively dull, but it also feels like a breath of fresh air. Everyone in this room takes Maryellen seriously. Instead of dismissing her pauses and uncertainty as symptoms, the scientists pay careful attention to what she says and does.
Next enters Phil, a man with a tidy brush mustache, neatly dressed in chinos and a short-sleeve button-down printed with vintage cars. After taking a seat across from the robot, he chimes in with QT to sing “Take Me Out to the Ball Game.” He faces the machine, but he’s playing to us, mugging and rolling his eyes. Song over, he first teases Hsu, then another resident, then pretty much every woman in the room. In other circumstances he’d be patronized or “diverted”—someone would attempt to distract him. Instead, we join him in being silly, joking about the situation and the robot.
QT pipes up with another round of awkward conversation (“I love the song. Do you?”), and Phil replies with a combination of graciousness and sass (“You sing very well. Did you have that recorded, maaaybe?”). Hsu asks Phil how he felt talking to the machine. “Like I’m a fool talking to nothing,” he says sharply. “I know it’s not a real person.” Theatrically, he turns to the robot. “You’re not real … are you?” He winks, and laughs uproariously.
He likes the robot? He doesn’t? It’ll be the team’s job to figure out these enigmatic yet relatable reactions. The three of us plus robot pack up and head back to Šabanović’s R-House Lab at the university. In the big conference room there, her team will converge, students of informatics, data science, computer vision, and psychology. They’ll pick apart Maryellen’s kindness and hesitation and Phil’s glee and annoyance, looking for their next task, the next skill QT needs to learn…
…In 2005 she spent time with the pioneering roboticist Takanori Shibata at Japan’s National Institute of Advanced Industrial Science and Technology and his robot seal pup Paro. Handcrafted, the little critter responded to speech and touch by bleating—it was programmed with actual seal pup cries—closing its eyes, and flipping its tail and flippers. It was one of very few robots at the time that could be used outside the lab without expert assistance.
Even at this early stage, elderly people were the target audience. The researchers took the machine to care homes, and Šabanović was startled to see the effect. “People would suddenly light up, start talking to it, tell you stories about their life,” she says. Shibata’s studies, then and later, showed that the cuddly seal improved quality of life; it got people to interact more, reduced stress, and eased depression.
So Šabanović joined the emerging field of human-robot interaction. Her experiments since have explored how we project our “techno-scientific imaginaries”—our cultural baggage, fears, and fantasies—onto these hunks of metal and plastic. Sort of like if Isaac Asimov became an experimental psychologist.
In one early study, she brought Paro into a nursing home to study how the device turned wallflowers into butterflies. Most residents would ignore the seal pup until other people showed up—then it would become an icebreaker or a social lure. They’d gather to touch it. They’d comment on its sounds and movements, laughing. The robot, she saw, seemed to open a door to other people…
…A PAIR OF round, white blobs sit side by side, each the size and shape of a pumpkin. Every 10 minutes or so, the orbs croak like frogs, or chirp like crickets, and sparkle with light. They want your attention. Pick one up, and depending on whether you stroke it, tap it, or shake it, it will respond with noise and light. If the orbs are set to “spring” mode, and you stroke one, it will sing like a bird and blush from white to pink. If you ignore the second blob, it will act jealous, flushing red. If your friend then picks up orb number two, they will mimic each other’s light and sound, encouraging you to play together.
The blobs are called Sam, and together they form a social robot boiled down to its essence: an invitation to connect. Sam is one of the otherworldly creations emerging from the Dementia and Technology Expertise Centre at the Eindhoven University of Technology in the Netherlands. Rens Brankaert and his colleagues don’t call this—or the other things they make—a robot. They call it warm technology. “We want to contribute to the warmth between people,” he says. And to create gadgets that a wider range of people would enjoy using…
…One of the warmest technologies from the Eindhoven group and their collaborators is Vita, a patchwork pillow with vinyl panels. Pass your hand over a patch and a sensor detects your presence, playing a personalized, familiar soundscape: a stroll down a cobblestoned street in the rain, maybe, or the clatter of coffee cups and servers and spoons at a café. Family members and caregivers select the sounds they think will resonate with the user. Over years of testing, the pillow has been fine-tuned, and Brankaert is currently talking to a partner to produce it and bring it to market.
In one demonstration, a white-haired woman sits quietly, looking dreamy, or very possibly sleepy. “Good morning,” says her daughter, but the woman does not respond. The daughter places the pillow on her mother’s lap and guides her mother’s hand over a large yellow patch. The chorus of the World War II chestnut “We’ll Meet Again” emerges. The older woman’s eyes brighten, and a smile of recognition creeps over her face. She begins to sing.
What is this pillow gadget for? It doesn’t restore her speech or fix her memory or replace anything she no longer can do. It helps the two of them find each other again across the dim and confusing terrain of dementia…
…You learn a lot about people by hanging out with robots. QT made it plain to me how much human interaction depends on tiny movements and subtle changes in timing. Even when armed with the latest artificial intelligence language models, QT can’t play the social game. Its face expresses emotion, it understands words and spits out sentences, and it “volleys,” following up your answer with another question. Still, I give it a D+…
…It’s four days before Christmas, and QT is visiting Jill’s House again, decked out in a Santa hat and a forest-green pinny for this visit. With the help of ChatGPT, QT is now more fun to talk to. A few dozen residents, family members, and staff are here, plus much of Šabanović’s team. Šabanović’s 3-year-old daughter, Nora, is nestled on her lap, carrying on the family legacy. She stares shyly at the robot.
This is a holiday party rather than a formal experiment. The session soon devolves into friendly chaos, everyone talking over one another and laughing. We all chime in to sing “Here Comes Santa Claus,” the robot flapping its arms. Phil plays peek-aboo with Nora. It really does feel like a glimpse of the future—the people with dementia as just regular people, and the machine among the humans as just another guest.
3. A Framework For Spotting Value Traps – Dan Shuart
As for value traps, I like to think of them as somewhat of the anti-compounders. They display the opposite of the characteristics described above. Specifically, they demonstrate some combination of;
- A need to retain a significant amount of the profits they generate just to maintain existing levels of profitability. In other words, they tread water or slowly drown.
- They have very poor incremental, or even negative, returns on incremental invested capital. This results in the business retaining profits and standing still or shrinking.
- They return too much capital to shareholders and do not reinvest in the business to an adequate degree or take on excessive leverage to fund unsustainable capital return programs…
…Here is how we look for value traps and a few real world stock examples.
Cash-in, Cash-out Framework
An initial test/filter Matt and I use to spot a potential value trap, or identify a potentially good business, is what we call the cash-in, cash-out framework. It’s simple yet very powerful.
We are trying to answer a simple two-part question: how much cash does the business reinvest and what are the returns on the reinvested cash? We prefer to work from cash flow statements, as normally cash doesn’t lie and it is much more difficult to manipulate than GAAP earnings or balance sheet figures. Just don’t forget to consider stock compensation, which is a very real expense.
I like to look at ten year increments and add up how much cash came into a business from all sources – operating cash flow, debt issuance, and share issuance – versus how much cash left the business via debt repayments, share repurchases, and dividends. Add the two together and you get the dollar amount of cash retained (from all sources) over that time period.
Next, we look at the cumulative profits over the same time period to get an idea what the reinvestment rate is as a percentage of total operating profits. Finally, by looking at the change in operating profits (often this requires some normalization) over the time period and dividing by total retained profits we can assess incremental returns on retained capital (incremental ROIC or I-ROIC). If profits grew by $1B and it took $5B of retained capital to generate that extra $1B, I-ROIC is 20% ($1B/$5B). Reinvestment rate and I-ROIC, in conjunction with shareholder yield, tell me roughly how the business has compounded in value on a per share basis…
…Verizon is puzzling to me as I would expect it to be a better business given it operates in a lightly regulated oligopoly with hard to replicate assets. Alas. The company soaked up 90% of earnings over the last ten years and barely grew for a measly 1% compounding rate. A generous debt-fueled dividend payout took business returns to an underwhelming 6%. While the yield seems attractive, a high dividend payout cannot go on forever if it’s driven by increasing levels of debt.
Macy’s has been a disaster. Left behind by better positioned specialty retailers and ecommerce businesses, Macy’s reinvested a third of profits at highly negative rates and has become far less valuable over the past decade, as you can see…
…To be clear, these stocks are cherry picked and meant to illustrate a point. I’m sure you can find a plethora of stocks that had cheap starting valuations, poor returns on capital, and still re-rated to a higher stock price for some reason over a ten year period. While those stocks undoubtedly exist, and probably in great quantity, I seriously doubt most people’s ability to reliably predict those situations for any extended period of time. I certainly couldn’t do it, it would be akin to throwing darts.
The point I’m making is, by assessing the economic fundamentals of a business whose stock may look cheap, you can implement guard rails as to whether or not you may be looking at a value trap. I’m skeptical of any stock that looks cheap but has flunked the cash-in, cash-out test over a many-year period. This filter at least gives us some hope of not fooling ourselves when we are enamored only by a cheap purchase price. Cheap businesses can be fine investments, but cheap and good businesses can be spectacular, and more importantly, limit your downside. To us, it’s also a far more replicable process, and a lot easier to stick with over the long run.
There are a few more critical other points to this discussion, as what I’ve described above is the easy part of the analysis (anyone can plug numbers into a spreadsheet).
- The historical numbers are the result of what happened over the past ten years, and what matters is what happens over the next ten years.
- Understanding what happened is easy, understanding why it happened and, more importantly, if it will continue to happen is where superior qualitative judgement and experience are required…
…Finally, using this I-ROIC framework will cause you to miss opportunities when businesses are at key inflection points and the future looks dramatically rosier than the past. That’s fine with us, because I think it causes us to “miss” more losers by keeping us out of trouble. It also means we will almost surely not find the next Amazon, but that’s not the game we are trying, or equipped, to play.
4. A beginner’s guide to accounting fraud (and how to get away with it) – Leo Perry
But now that I’ve worked out how to read accounts, and find it quite easy to spot signs of fraud, I also have some ideas for how we could run a good one of our own. And I’m not so sure there won’t be a lot more money in that line of business, if you can call it that.
The mechanics of making up sales are pretty simple. If we’re running a business and want to boost our top line, all we have to do is phone a friend. A good friend to be sure, who doesn’t ask questions. It’ll only take them a few hours to do the paperwork for setting up a shell company and then we have our customer, one we can invoice whatever we want. We have our fake sales (and I’m pretty sure our mate has done nothing wrong, in the eyes of the law).
You might think that sounds too easy, that someone would spot the problem and the con would quickly fall apart.
Well back in 2014 I explained what I thought looked like the most obvious fraud to an FT journalist. One of the things that caught my eye about Wirecard was the accounts of a company it bought in Singapore. Tucked away in the notes were references to specific customers — like Ashazi Services. [1] This was a Bahrain entity with no apparent operating business. A dormant shell that had never filed financials. Even the product Wirecard said it was licensing to it, the Elastic Platform, seemed to be a fiction (at least I never found any other mention of it by the company):…
…Dan McCrum, the FT journalist I met with, went to visit what there was of Ashazi as a part of a long-running series of Alphaville posts on Wirecard. And the whole scam did come crashing down . . . a mere six years later…
…Even if some over-eager analyst does turn up at our sham customer, we can always move the goalposts. A few years ago I asked a Chinese-speaking colleague to visit some companies on the mainland. These were businesses that were reported to have signed purchase agreements with a western mining startup, which I was short. This startup had announced a deal to sell product a few years earlier. Then the contract was suddenly cancelled and simultaneously replaced with a similar agreement, but with a different Chinese entity — which we’ll call Tulip Industries. The deal equated to an outlay of approximately $150mn a year by the customer.
What we found at Tulip Industries was little more than a startup itself, with only a few field trials in progress. Even its most ambitious presentation forecasts involved a fraction of the product it had apparently agreed to buy. And its CEO was very clear that the deal wasn’t a firm commitment, only a loose framework. In fact he said he’d never spoken to the company that I was short, the deal was agreed through a friend in Hong Kong whose nephew worked for the miner. (He was much more committed to explaining to my colleague why China needed to invade Japan.)…
…If we don’t want to rely on a third party there’s also the DIY approach, using an entity that we control. A related party.
One of the first sets of financial statements I really struggled to reconcile with the story company management was telling was for Cupid, a UK-listed operator of dating apps and websites. I don’t know how many of its shareholders bothered to try out the sites it ran, even briefly, but I would guess not many. For anyone who did it seemed like they were too good to be true. Wherever you signed in from in the world, dozens of very keen and very attractive women would quickly get in touch. And they all happened to live nearby.
The Kyiv Post looked into how the company might be managing this back in 2013. Australian short seller John Hempton at Bronte Capital even took the trouble to log in from the most remote island in the UK (not in person, he used a virtual private network) and still found no shortage of admirers in the local area — even though the population there was small enough to all know each other. The fact that his profile stated he had syphilis apparently wasn’t a problem either.
Cupid commissioned KPMG to investigate; its report found there was “no evidence of a company-organised practice” of staff using fake profiles to encourage subscriptions.
Cupid’s accounts were not as straightforward as its business model, and shareholders seemed to have even less time for them than they did for its services.
The annual report for 2011 had a chunky £2mn receivable from a company called Amorix, which was controlled by Cupid’s founders. Cupid said Amorix owed it this money because it had been collecting customer subscriptions on its behalf. But Amorix’s own accounts showed it only had about £80,000 in the bank, and no other assets to speak of. There was no trace of the money Cupid said was being collected for it…
…The magic thing about fake sales is they are 100 per cent margin. All profit. You don’t need to go to the trouble of actually producing whatever it is you are pretending to sell, do you? So £100 in sales is £100 of profit. Hold that thought for a minute.
Now let’s think about what kind of business we want to start with to run our little fraud out of. Not a profitable one obviously. That would cost us good money to get control of in the first place, and we want nothing to lose. What we need is a business that has a lot of turnover but makes no money, but isn’t burning cash either. Something like a very low margin distribution business…
…So let’s say we go into the fruit wholesale business. We buy boxes of bananas and sell them on at cost. Why? Well, while we’re only washing our face, if we turn over £100mn in bananas who’s going to notice when we add £1mn that’s lemons? That’s still less than 1 per cent of our sales after all. But if the £1mn is fake then it’s all profit. And as we make no money shipping bananas, the fake lemons are all of our profit.
The reported value in our business now all comes from made up sales to a fictitious customer; a customer set up by a mate that no one outside our office is ever going to know about. No one can pay them a visit if they don’t know its name. And they won’t, because at that size we wouldn’t even have to mention it exists. From the outside there’s just no way to spot anything wrong in our revenue numbers.
5. Why Wasn’t there a Recession? – Michael Batnick
So, how did everyone get 2023 so wrong? Michael Cembalest hit on this in his 2024 outlook.
Monetary policy is tighter but below the level of real rates that led to prior recessions; corporate cash flow is still in good shape, unlike the cash flow deficits which preceded prior recessions; and the corporate sector termed out debt maturities before the rise in rates, partially immunizing itself from the interest spike that preceded prior recessions. Private sector credit creation was similar to prior cycles, but debt servicing risks are lower for companies and households that termed out maturities.
Even though the Fed aggressively raised rates, monetary policy wasn’t as restrictive as it was in the lead-up to prior recessions (not including 2020). That’s not to minimize their efforts of cooling inflation, only putting in perspective that historically, they just weren’t that tight.
And even if they raised rates to 6% or higher, it’s hard to say for sure that we would have had a recession. Almost 90% of S&P 500 debt is long-term fixed, which is why net interest costs didn’t go up with interest rates. Paradoxically, thanks to all the cash on the balance sheets actually earning something, net interest costs went down!
Disclaimer: None of the information or analysis presented is intended to form the basis for any offer or recommendation. We currently have a vested interest in Amazon. Holdings are subject to change at any time.
