VALUE: After Hours (S05 E13): Matthew Cochrane, History Of Insurance And Gambling, Value, And Recession

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In their latest episode of the VALUE: After Hours Podcast, Matthew Cochrane, Jake Taylor, and Tobias Carlisle discuss:

  • This Time Is Different And The Same
  • Buy 1% Of Your Competitor’s Disruptive Business
  • Can Amazon Be Beaten?
  • The Insurance Industry Was Started By Gamblers
  • Never-Sell Is Not A Religious Dogma
  • Berkshire Hathaway – Industry Leaders In Insurance
  • Will AI Disrupt The Insurance Industry?
  • Sears Should Have Bought Amazon Stock
  • ChatGPT Is Like A Freshman Book Report
  • Value Is Very Cheap
  • 10:3 Inversion Steepest Ever
  • It’s Hard To Trim Multi-Baggers

You can find out more about the VALUE: After Hours Podcast here – VALUE: After Hours Podcast. You can also listen to the podcast on your favorite podcast platforms here:

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Full Transcript

Tobias: Preparing to livestream. This is livestreamed. I’m legally obliged to tell you, Matt, that you are now live. This conversation is going out to one– [crosstalk]

Jake: Dozen people.

Tobias: To 12 people.


Matthew: [crosstalk] So, it’s all good. [laughs]

Tobias: I am Tobias Carlisle. I’m joined as always, by my cohost, Jake Taylor. This is Value: After Hours. We have a special guest, Matt Cochrane. How are you, Matt?

Matthew: I’m doing great. And for the record, thank you so much for having me on. It’s an honor. I’ve told you this before, but I watch you and Jake every week. When Bill was on, it’s one of my favorite podcasts. So, it’s an honor to be here, truly.

Tobias: It’s great to have you. I’m a big fan of your takes because you’re not so beholden to any particular style. You seem to be– [crosstalk]

Jake: Reasonable.

Tobias: You buy growth, you buy value, you buy whatever.

Matthew: [crosstalk] something that works.


Tobias: Yeah, me too.

Matthew: [crosstalk]

Tobias: Let me know if you ever find something like that. [laughs]

Matthew: [laughs] One day.

Tobias: Just before we get into the part where we just talk complete nonsense, tell us a little bit about 7Investing. Get a plug out right at the top of the show.

Matthew: Yeah, great. Thanks for that. Yeah, 7Investing, look, it’s basically a stock recommendation newsletter. We release seven recommendations each month. Obviously, a lot of those are repeats from previous months. Look, it’s definitely catered more to a growth investor, though I think there’s a wide range of picks and recommendations that we release. Each recommendation is accompanied by usually a 2,000- to 3,000-word research report. We do a video when we pitch our stock to our other advisors. There’s seven of us. The other advisors can ask questions and push back a little. That might be the most valuable part of the service, to be honest, just like where you get other takes and the questions about it. But yeah, that’s our service and we’ve been doing it– We started in March 2020. [crosstalk]

Tobias: Good timing. How are the returns since then? [laughs]

Matthew: Right.

Jake: Have you strategized yet what you’re going to do when someone comes out with 8Investing? That could be a problem.


Matthew: That’s crazy. Why would anyone do 8?


Tobias: How would you categorize the service? Is it more growth or is it a blend? How do you think about it?

Matthew: Yeah, look, Simon Erickson is the founder and leader of our pack. He lets us pick whatever we want. I would say though the overall bent is probably towards growth. But there’s income payers on there, dividend payers. There’s value stocks too. You get a wide range from all cross industries. Yeah, the overall bent, there’s probably a lot of tech and growth more than anything else.

Tobias: Any energy picks so far?

Matthew: Yeah, there have been a few energy picks. Some of those are more of the– [crosstalk]

Jake: Those are growth stocks now, Toby. Come on.

Tobias: That’s why– I’m getting there.

Matthew: Obviously, not as many. There’s even some new greener energy picks too in there and stuff like that. One of the things about our team, which I appreciate, we all have different takes on the world. So, you do get a wide range of investment philosophies that go across sectors, and industries, and companies within those industries. Sometimes, I might like a legacy company within an industry, and one of our other advisors likes more of a potential disruptive upstart. But you’ll get both takes, and you can hear us read our report, and battle it out, and just choose for yourself what you like.

It’s Hard To Trim Multi-Baggers

Tobias: If you were super wealthy– You’re already well established where you’ve got all of these positions in the portfolio. So, you’ve got like big chunks of legacy holdings. It just makes sense to have a little holding in every single little potential disrupting company that comes along. Would you have a little option size position in anything that pops its head up and might threaten an industry?

Matthew: Yeah, I think there’s probably some wisdom to that. The one thing we all have in common at 7Investing is we’re all buy and hold long-term investors and #neversell, right? That’s the team we’re on. We can talk about that, but we don’t have to. I think one thing about that is, I think it’s hard to be a long-term buy and hold investor with a really concentrated portfolio. I myself have 30 positions and some people on our team have more than that. Again, a wide range of portfolio strategies and things like that. I don’t think there’s one size fits all when it comes to that, but I think– I allow myself to hold anywhere from 30 to 40 positions at a time. I might start eliminating positions at that point, but that just helps me take chances on companies that I might not otherwise take on a disruptive upstart that I like.

Like Shopify. Even with Shopify, huge drawdown. I was fortunate enough to get in earlier on that and it’s still a multi-bagger for me at this point. I would have never had the guts though to buy it if I had a rule that set a position has to be like 5% or 10% or something like that. If I only had 5 to 10 positions in my portfolio, I would have never bought Shopify, but that’s what works best for me. [crosstalk]

Tobias: Did you trim it as it went up? Or you just let them ride?

Matthew: Yeah. I’m not perfect on this. I need to, I guess, make some rules for myself. So, I actually did trim Shopify, but there’s a lot of positions we could talk about that I didn’t trim and I’m really like, “Why didn’t I trim?” At the same time, yet, I can look back on it and be like, “Well, if I trimmed as the valuation went up–,” I would have never trimmed at the top. You know what I mean? I would have sold it well before I got to the top.

So, I don’t know actually how to like– That’s something I struggle with myself, to be quite honest with you and to be quite frank. How do you trim when the valuation goes up and then how do you add back on as the valuation compresses? That’s something I need to work out better myself. [crosstalk]

Jake: If it makes you feel better– [crosstalk]

Matthew: I actually Shopify very well, but there’s a lot of positions, like we could talk about Block. I had that one really early, and I rode it all the way up, and I rode it all the way back down.

Tobias: [laughs] Round trip.

Matthew: Shopify is one I actually got right with that, but there’s a lot I didn’t.

Jake: If it makes you feel better, Munger is still figuring out his sell criteria at 99.

Matthew: There you go.

Jake: We’re all working on it.

Matthew: Right.

Tobias: Let me give a shoutout to all the people in the house. We’ve got Toronto. Brandon, Mississippi.

Jake: Let’s go, Brandon.

Tobias: Central standard time, what’s up? Santa Monica. Surrey, Canada. Bendigo, what’s up? Australia. Montreal, Atlanta. Sherwood, Oregon. Dover. Victoria, BC. Norberg, Sweden. Oh, no, that’s not a real one, is it?

Jake: Fairly newer.

Tobias: Wollamorarago. I’ve never heard of that. You must have made that up. Dubai. It’s in Australia, I should know it. Colin Armstrong has given us £50. Thanks very much.

Jake: Wow.

Tobias: Put that on the bar in Omaha.

Jake: Yeah.

Tobias: Sydney.

Sears Should Have Bought Amazon Stock

Jake: Interesting counterfactual history to imagine. What if Sears had taken three properties, let’s say, I don’t know, four properties, liquidated them and bought Amazon stock early and bought 1% of the company just as business interruption insurance. [crosstalk]

Tobias: That’s a process-type investment, isn’t it? It’s almost like– Yeah, imagine that.

Jake: Imagine that.

Matthew: What if they had sold those three or four stores and invested it in their own e-commerce, like operations and tried to copy Amazon strategy?

Jake: Many counterfactuals– [crosstalk]

Matthew: Yeah.

Tobias: Might have been torched in that.

Matthew: [crosstalk] had interesting hypothetical scenarios to go through.

Buy 1% Of Your Competitor’s Disruptive Business

Tobias: I don’t mind that. If you’re really well established in something and you see the competition come along, yeah. Like Blockbuster buying 1% of Netflix, and they almost got the whole thing, just put a little holding in knowing that if you’re completely wrong, there’s this 1% chance. 99% chance, you’re going to be okay. 1% chance, you’re not. So, you lay off your 1% risk by buying 1% of this thing, and then it goes really well and all of a sudden, you’re a passive investor. Don’t have to work anymore. It’s great. Let me know if you see any of those out there.

Jake: Yeah. Matt, if I remember correctly, your background is actually as a detective. Is that true?

Matthew: Yeah. Actually, I’m still currently a detective. Yeah. I’m actually doing what I think you used to do and work with two jobs and try to perform that juggling act. But yeah, I still got a few years till I can get a full pension. So, that’s the goal.

Jake: Investment research, can you draw some analogies to solving a case?

Matthew: Yeah, you probably can. A lot of detective work is just being thorough. It’s like very common-sense stuff like, “Hey, get the surveillance video–” There’s a crime at this building. “Hey, go get the surveillance video from the buildings around it. You might see the suspects coming or leaving,” or whatever. So, a lot of it’s really just being very thorough and following your common sense. Then the other half of it is probably just reading people. That’s probably harder to do as an investor, because it’s not like you get a chance to talk to many CEOs or things like that.

Tobias: They’re all sociopaths. They’re very good liars.

Matthew: Right. Yeah, I’m sure there are similarities there, for sure.

Tobias: There’s a good comment here. Yuheng Zhang, “That’s what Time Warner was thinking when they bought AOL.” Yeah, good point. I guess it doesn’t always work out. Maybe they sized it too big.

Jake: Might have overpaid a little bit.

Matthew: It worked out for AOL though.

10:3 Inversion Steepest Ever

Tobias: Yeah, that’s a very good point. Let me give everybody a little update on the– So, the 10:3 inversion, which– Cam Harvey’s result. So, two things I should say. One, Cam reached out. He didn’t like the way that I– He said I mischaracterized his view on the 2008 inversion. He said the inversion happened in 2007 and recession. He said that he believed that his metric had in fact predicted the oncoming recession, and the length and the timing of it. But he was wrong about the depth of the recession that came. He thought it’d be shallower. And as it turned out, it was quite a bad one.

So, he said his model did quite well on two out of three. He’s going to come on the show at some point. We’re just still trying to find a date. It’s likely end of April, early May. When he’s going to come on, we’re going to chat about it, which would be great. But the inversion, I checked yesterday after the close. It was 1.47 which is the widest it’s ever been in the data going back to 1980. There’s nothing to suggest that the steepness or the depth of that inversion is meaningful at all. I just keep on pointing it out, because I think it’s fascinating that every week it [crosstalk] out more.

Jake: But what if, Toby? What if? [laughs]

Tobias: If it is connected, then we’ve got a very deep recession coming, a depression coming, possibly. I don’t really know what the technical difference is between those two, but I think it’s interesting. I’m fascinated that inversion has such a good track record.

Jake: I think recession is when your brother-in-law loses his job and depression is when you lose your job.

Tobias: [laughs] That’s right. The record of this thing, given that there’s only a handful of instances where it’s happened, it’s like four before he published his work and then four after he published his work. There’s– [crosstalk]

Jake: Yeah. The lack of false starts is impressive.

Tobias: Yeah, no false positives and it’s called every single one that has happened. So, its track record is pristine. I just don’t think it can be dismissed at all. I think we have to treat it with some– I don’t think you can ignore the fact that we’ve had this inversion since October 25 last year. The record is very good. If you look in his paper, he says that the range tends to be seven months at the earliest, so that would be May 25 this year, to 15 months at the latest, which would be January 25 next year to a median of 12 months, which is October 25.

Jake: October. It’s all connecting. [laughs]

Tobias: I just think it’s kind of interesting. I’m a big fan of simple statistical models as superior to the best experts, particularly even when the experts have access to the simple statistical models. I just think it’s a simple statistical model that’s giving a very clear signal and we should be paying attention to it, but I don’t know what the future holds like anybody else. What do you guys think? You persuaded it all in this thing?

This Time Is Different And The Same

Tobias: How do you feel about the economy, absent this little metric? Do you have a view?

Matthew: Well, I won’t be surprised at all if we go into recession. There’s a lot of factors at play. We still have a persistent high inflation that I wish was lower. The Fed raised rates really fast. We just had some bank failures, fail from that stress. At the same time, I just wonder, and again, I’m not going to be surprised if we go into a recession. But Toby, we talked about this last week. COVID just made everything so funky, for lack of a better term. I feel like it just mucked up the picture so much. We had interest rates go to zero and now they rose the fastest they have I think ever. We had supply chains just you almost turn a switch off and now they’re being turned back on. You just had so much stuff going on. You had a whole bunch of stimulus go to the economy from the governments, and now you have tightening.

I just wonder if, say, at least maybe the steepness of the curve– I know you said that’s not really an indicator of the recession coming, but it does make me wonder though, with just so much mucked up, if this– Again, I’m not going to be surprised if we go into recession. In fact, if you made me guess, I would say I think we are, but COVID just really mucked up the picture, right?

Tobias: Yeah. It muddies the inputs, it muddies the data as much as anything else.

Matthew: Yeah, as much as a lot of muddiness there. So, I just wonder about all this.

Jake: Yeah, I think my counter to that, I agree, but it would be, like there’s always something weird, it seems like, going on that you make it– You always say like, “Well, it’s different this time, because there’s a housing boom in 2006, or there’s a tech boom in 1998, or rates were too low for too long, or rates moved up too fast.” There’s always shit going on.

Matthew: This time is different.

Tobias: This time is different. It’s never clear looking forward. At no point in my career has it ever been like, “Oh, this is obviously smooth sailing from here.” So, I don’t know. I bet if we read journal entries of ourselves at this point, we would say like, “God, it seems so uncertain.” And we’d been saying the same thing 3 years ago, 5 years ago, 10 years ago, 15 years ago. [chuckles] That’s just the nature of– [crosstalk]

Tobias: I distinctly remember how scary– The fourth quarter of 2008 and the first quarter of 2009, how scary those two were, just because the volatility was huge, the market was moving around so much. It was like March 2020 for those folks who haven’t been around for that long. [crosstalk]

Jake: But for months, not just for like a weekend.

Tobias: Yeah. It was a little bit like this. It had dragged on. We were down a lot. It had been for more than a year.

Jake: That’d [crosstalk] summer of 2007?

Tobias: June 2007 I think was the top. And then [crosstalk] whatever it was, September, October 2008, like a year and a quarter later, and then the fireworks started and it was two quarters back-to-back of massive dips and drawdowns in volatility. Funnily enough, through that period, I was buying net-nets because I thought if the market goes to zero, the net-nets at least have liquidation.

Jake: Liquidate.

Tobias: Might have been a little bit caught up in the moment. But I thought yeah, when they liquidate– I think that was a good place to be, because they don’t come around very often. But I still think even though the picture is muddied, if anything that suggests to me that there’s reasons to be cautious rather than reasons to dismiss those things, but I do take your point. I think it’s a fair one that the data is not very good across just every sector. You can’t have oil going negative.

Jake: What’s normal? How do you normalize anything?

Matthew: Yeah, it’s a great point. Everybody feels like they live in unprecedented times. That’s a great point. It’s a great point.

Value Is Very Cheap

Tobias: By the same token, I think value is very cheap.


Tobias: I did find myself in this odd position where I think the index is– [crosstalk]

Jake: Yeah. Hell’s coming, but I’m in pretty good shape. [laughs]

Tobias: Yeah, which the thing is everybody feels that way.

Jake: I know. Everyone feels that way.

Tobias: So, I feel like dismissing it, but the spread is very wide for my favorite metric for that EBIT/EV. It continues to be wider than 2000, wider than 2009 at the bottom. It’s so wide that not much has to happen for it. Fair enough. It’s filled up with energy, but energy could work. Anything could work from here.

Jake: Yeah, it could. Everyone’s portfolio is like their politicians where, “Oh, all these other guys suck, but my guy’s okay.” [laughs]

Tobias: Also, lawyers. Everybody feels that way about lawyers. All lawyers suck except for my guy, like having a junkyard dog.

Never-Sell Is Not A Religious Dogma

Matthew: There is a point– I’m not going to be surprised if we go into recession. It could be really bad. I really don’t know. I shouldn’t even be talking about it, because that’s how much I don’t know. But even with those thoughts in my head, it doesn’t change my investment process. As a long-term investor, I know there will be downturns in the economy at some point in my investment journey. And the plan is to be able to, for lack of a better term, stay in the game.

One great advantage of being an individual investor, I don’t have to answer to investors. That’s what mostly our newsletter is for. We’re individual investors. So, you don’t have to answer to anyone. As long as you understand, I think, why you’re in the companies you’re in and that they can survive economic downturns, that’s the way the world works. There’s always going to be downturns, there’s always going to be booms and busts. I don’t know when there will be, but I expect that there will be many along the way.

As long as I understand why I’m in the companies I’m in, can they survive in downturn? They might get beaten up a little bit, but can they come out the other side? A lot of times I believe they’ll come out the other side stronger. Even that stock price doesn’t reflect it at that time. Like, can they take market share in a downturn, because they’re a stronger company than others in their industry? It’s great to talk about, but it doesn’t change anything, I guess, in the way I approach investing.

Tobias: Billy’s in the comments section. Sorry, Jake. Keep going.

Jake: I was just going to say something that I think about when it comes to that though is that, you hear a lot of own quality into a downturn for all of those reasons. The business is just going to get stronger, they’re going to take market share, they’re anti-fragile. Fair enough. That could definitely be true. But if everyone has that mentality, we run into this Keynesian beauty contest, where maybe it’s fully baked into the price today that buying quality to handle a recession. Everyone’s doing it. Guess what? Maybe they’re throwing away all the other stuff that’s too leveraged, too economically sensitive, too scary to own knowing that a recession is coming and therefore, it’s mispriced.

At the end of the day, these are all para-mutual bets that we’re making. We’re looking for mispriced bets. Not necessarily easy, sure fire winner bets. So, I don’t know. Sometimes, I think there’s a little second-order thinking that’s required to play this game.

Matthew: I would say there’s more than one way to skin a cat, I think. I definitely would never ever say my way is the only way to make money in the market. I think there’s a magical simplicity to telling retail investors, individuals like me, “Hey, buy Alphabet, buy Microsoft, buy Texas Instruments and don’t sell them.” Especially for people where investing isn’t their whole life. They work a 9 to 5, they coach a little league for their kids, they’re off living their lives. That’s me. There’s simplicity to that.

I think a simple investing strategy that can be practiced is better than a complex trading strategy that’s not feasible for most people to do. It doesn’t have to be like binary either. I would never tell anyone like, “Hey, you either index or you pick stocks.” I think that’s crazy. Like, “Hey, put 80% in index. If you’re really into this, and you think this is interesting, and you think you might have an advantage in understanding the industry you work in, because of a hobby you have, you understand like, this company is taking off just as a consumer–”

I love Peter Lynch, and he was like the champion of the retail investor and he said, “Everybody has an advantage somewhere if you look for it.” His example was always like, “Wife or daughter’s at the mall, what shops are popular at the mall?” Now, it might be like, “What app is it your kids are on?” or something like that. But I bet in an industry you have or the region you live in, like there’s a new restaurant that’s out and maybe it’s public and it’s growing really fast, and everybody loves it. I think there’s a simplicity to that that I think most people, including myself, can practice. I think the market just seems like–

I guess I would counter– I don’t disagree with what you said, but I would also just say I think there’s like– Just lost my train of thought, but I think something that people can follow and that’s not like, “Hey, I always have to sell at the top and I always have to buy back at the bottom and do a lot of that.” You bring in taxes into the work, you bring in many more decisions in the work, and you just take your emotions out of it and you say, “Hey, I have this long-term thesis,” and I want to make sure that’s still intact. Never sell is not a religious dogma. It’s definitely more aspirational.

Jake: Yeah.

Jake: [chuckles] Sometimes, people get mad. They’re like, “You sold that stock and you’re–” It’s not like I’m going to my church and–

Jake: You’re kicked out of the church for–

Matthew: Right.

Jake: Excommunicated for some–

Can Amazon Be Beaten?

Tobias: Let me ask you a question, because you said before we got on, we were talking about, you read something bearish and it makes you feel bearish. You read something bullish and it makes you feel bullish. I think if there’s a criticism of JT and I, is we’re always a little bit bearish. This is not necessarily your prediction of what’s going to happen. This is just I’m explicitly asking you, what are the bullish arguments for the market?

Matthew: That’s a really good question. I think my nature, my tendency is to be bearish anyway. My wife would say I’m a pessimist.

Jake: Welcome.

Matthew: Just waiting for my sports team, and they go down by a touchdown early in the game, like- [crosstalk]

Tobias: You knew it.

Jake: They’re never coming back. It’s over.

Matthew: -“Oh, they’re done. They’re playing horrible,” whatever. My wife will yell at me for being a pessimist and things like that. So, I think my tendency is to naturally be maybe a little pessimistic. All right, but that being said, I don’t know if I can do it for the whole economy, but I think there’s a lot of names– [crosstalk]

Tobias: For the market.

Matthew: A lot of companies, maybe big companies that dominate some of the indices, they’re going through a spell where they’re underearning. Let’s just take Amazon for an example. One of the big parts of the index for an individual company. AWS is earning less. AWS is taking– supposed to growth is slowing down there, at least for the next few quarters. I expect that. As an Amazon investor, I think that’s very much expected. I would be shocked actually if that didn’t happen. However, I think part of never sell is you look at things and say, “Is this a short-term problem or a really long-term thesis breaker?” And so, I think with Amazon, you go, “I don’t think the cloud is going away.” They have admitted like, “We overbuilt our logistics and delivery fulfillment centers. We overbuilt during COVID because e-commerce just spiked so much and we thought that was a permanent spike.” Then, it came back to the long-term growth line that e-commerce is on after that spike. It’s come back down to the long-term growth trendline. They said, “Hey, we overbuilt.”

I think there’s so many companies, when I said COVID just muddied the pictures, you see almost company after company just messed up during COVID, either giving projections, guidance that didn’t turn out to be accurate, or overbuilding because they expected this e-commerce demand to stay. A lot of companies just messed up. They had the inventory wrong. Target ordered TVs. The TV sales spiked through the roof at the beginning of COVID So, Target ordered a lot more TVs and electronics. By that time, people were trying to buy clothes, because they’re going out again and things like that. Everybody had bought a TV. You bought a TV last year, I don’t think you buy a TV this year.

That being said, I just think a lot of people messed up during COVID or a lot of companies. But you look at Amazon, they overbuilt their fulfillment centers. Okay, they built too many– I live down in South Florida. So, they built too many in the Miami area. Well, I think they’re going to grow into them. It’s not like those go to waste. It wasn’t the most efficient use of capital at the time, but I think their lead in e-commerce is just substantial. When you look at the square footage Amazon has dedicated to e-commerce and fulfillment and logistics and delivery, it just dwarfs anybody. There’s a caveat to that because somebody like Walmart or Target, you could say, the back of their stores could be– that’s not counted. There’s a little bit of a caveat. But it’s still dwarfs exponentially higher than anyone else. The back of the Walmart stores and Target stores, they’re not built for e-commerce. They’re built for buying in store.

So, Amazon just has that advantage. In some ways, I think you could say, they even increase their long-term advantage even while overspending and spending all that money on Capex. For a bullish case for Amazon, I think they actually increased their long-term advantage with e-commerce, even though they spent all that money on Capex, making their cash flow look like crap for a good solid year or two.

Tobias: Let me ask you a question that– I don’t know if this is answerable question or not, but I’m interested to know. How does Amazon get beaten? Because I think that every other example– Buffett famously talked about department stores being very good businesses for a period of time, but various things have happened. They needed to be situated near where public transport got off in 40s. And then later, it became less relevant because most people drove, and then you needed a big floor space because people wanted to shop in bulk. Hasn’t Amazon got to that point where the convenience is it’s right on your computer, so that’s taken away the need to travel. And then, they’ve got all of the space, which is going to be hard to compete with, just hard to build anything like it. So, is Amazon now insurmountable?

Matthew: It’s one of my two largest positions. So, obviously, I’m very bullish on Amazon. But if you told me to write a bear case, I would say Shopify, I think, is positioned interestingly and they can partner with the Googles of the world, like with Google Shop. Google’s been spending a lot of money and bolstering up their Shop tab at the top of their search if they can bolster up their logistics. I think Shopify would say– because Shopify wants to get the two-day delivery everywhere in the US, and they say, “That’s going to be good enough for most people.” If that’s right, I think Shopify is positioned pretty interestingly. I don’t know if it is.

I think with most things I buy now– If you told me it’s here in two days, I’m not going to freak out, that’s fine. But what’s interesting is, my 16-year-old son ordered something the other day. We ordered it after he was home from school. He’s like, “Dad, will you order this on Amazon? I’ll give you the money.” We ordered it. He comes home the next day. He gets home from school and he goes, “Where is it? How come it’s not here yet?”

Tobias: [laughs]

Matthew: I’m like, “It’s not coming here till tomorrow,” or whatever. He’s like, “What?” I just wonder if two days really is this magic number where people are going to be happy with it or that’s just consumer expectations and where they were for so long. I don’t know the answer to that question. But the government could come in and break up, say, “Amazon, you’re too big and we’re separating AWS from e-commerce.”

Capital allocation is still a thing in Amazon. They spent a lot of money. I was just saying like, “Okay, I don’t think a lot of it goes to waste, but man, they have these projects.” They spent how much on Alexa? They spent how much on this satellite internet thing? Why are they spending that money? As a shareholder, I wish they would cut that back. I think the Jeff Bezos Day One mantra, it might be hurting them more now than it helps them, because sometimes, Jeff Bezos would say–

I think Jeff Bezos was the greatest businessman, entrepreneur of our time. You could categorize me as a Jeff Bezos fanboy. But I do wonder, if that Day One mantra there and them spending so much on these bets, and he would use to say, “Well, the bigger we get, the bigger bets we have to make, because that’s the only thing that’s going to move the needle.” And that is right but when you see how much they spend, I would just say they’re wasting it. They’re not a perfect company by any means, but I do think their long-term advantage in e-commerce is, I don’t see how people catch them. That’s almost insurmountable.

ChatGPT Is Like A Freshman Book Report

Tobias: Bill says, “We have to ask you about ChatGPT and Google.”

Matthew: Well, I think Bill probably has the best way to say it. As an Alphabet shareholder, I wish it wasn’t there. I think that’s something to consider. What we were talking about, having a 1% position in disruptive threats, and how I’ve done this is position my portfolio, I own Microsoft and Alphabet. Now, there’s a scenario where they just outspend each other and the consumer wins and both companies lose.

But that being said, I think Alphabet’s advantage is still there. I think they have this tremendous distribution strategy advantage. They own Android. So, they’re already on whatever that is, 70% of the world’s phones. They have a long-standing distribution deal with iPhone that I don’t think Apple would be too eager to go to Microsoft. Maybe, that’s a potential weakness.

Plus, it’s just habitual. We’re habitually going to Google. I think a lot of the stuff you’re going to see on ChatGPT– I think AI is going to surprise us all in the next 5 to 10 years in what it disrupts. And so, I’m definitely not the futurist who best understands implications of AI. But I think a lot of it is not monetizable as easily as a lot of–

Mexican restaurants near me, when I Google search that, that’s monetizable. I’m in a hotel, and I want to eat, I want to go get tacos and margaritas or something, and I go “Mexican restaurants near me,” and it comes up with three options that are within a mile of me or whatever. That’s obviously a very monetizable search. ChatGPT and talking about philosophy or trying to get it to answer some kind of questions or trying to get it to write a book report for me because I’m a high school student or something like that, the monetization model isn’t as clear to me.

Jake: You mean, like you’re writing a poem about Ben Bernanke or something? Is that the way-

Matthew: Right.

Jake: -to pay for that?

Matthew: Right.

Tobias: I pay for it, because I’m interested in learning how to use it. I think it’s potentially very powerful. I follow a whole lot of Instagram channels where people purport to– They call themselves prompt engineers now. Can you get the prompt to deliver a good answer that you like? Even going deeper down the rabbit hole and spending a lot more time in there, you don’t really miss any of the prompts that come through that yield kind of interesting answers. As far as I can see, nobody’s really figured out how to use it well. Nobody’s getting excellent answers out of it. When I use it, I always think that the answers are very– it’s a little bit like getting somebody to write a book report for you who doesn’t really understand the subject matter. The book report is– [crosstalk]

Jake: Freshman book report?

Tobias: Yeah, that’s how I would categorize it. It’s pretty well researched, except it’s full of obvious errors that I know the first time I look at it. It’s not that well written that I wouldn’t cut and paste something that it said and say, “Hey, this is something that I write.” I’d be embarrassed to do that.

Matthew: Sure. Yeah. I think that’s it, actually, Jake. I agree with everything you said, but you see where it’s going too, I think. I think it’ll get there. I think it gets there within five years, maybe a lot sooner than that. I don’t know. But the more people use it, the more they can keep tweaking it. That’s why Google Search’s advantage was so big in search. More people used it than any other search engine, so they could just keep tweaking their model to best fit what users are looking for. I think you’re going to start seeing that with Bard AI and ChatGPT.

The Insurance Industry Was Started By Gamblers

Tobias: JT, you want to hit us with your vegetables?

Jake: Yes, sir. So, this week we’re going to talk about the early history of the insurance industry and actually how gambling sowed a lot of the seeds of the insurance industry. Some of this material is from Peter Bernstein’s book, Against the Gods, which is one of the all-time classics. It’s a great read, if you haven’t checked it out yet.

Tobias: There you go. It was on my book shelf too.

Jake: Right on cue.

Tobias: To hand. Yeah.

Jake: Well played, sir. So, we’ll start out with emperor Claudius, a Roman ruler around the time of Jesus Christ. He was eager to boost the corn trade within Rome. He made himself basically a one-man premium-free insurance company by taking responsibility for storm losses that are incurred by Roman merchants. So, he’s effectively insuring these Roman merchants. Actually, not that dissimilar to how the US government insures Bill’s house in Florida for us all without taking premiums. I’m just teasing, Bill.

So, let’s fast forward a few generations later. There’s this Roman jurist named– I think it’s Ulpian. I’m not exactly sure how it’s pronounced, but he created these tables that were life expectancies. These were actually the last word, basically, in actuarial tables for like 1,400 years. We made no progress. Not much happened.

And so, let’s fast forward now to the late 1600s. This guy named Blaise Pascal, he was a Frenchman and who unfortunately only lived 39 years before he passed away. He was always in really poor health, but he was a child prodigy in both math and science. As a teenager, he actually pioneered this mechanical calculator that worked– One of the first ones ever. He wrote several important papers on the scientific method. He invented the hydraulic press, and he also figured out how to use mercury to measure air pressure and actually had someone take it up into a higher elevation and he could measure the elevation. But he was also a philosopher. And of course, you might be familiar with Pascal’s wager, which might be his most longstanding thing.

Well, what you might not know about Pascal, at the time was approached by this rich, curious gambler named Chevalier de Méré, I believe. He was trying to figure out, how do you divide up a gambling game that’s called points, where one of the players has a slight lead–Let’s say you were going to stop the game and then figure out, how would we chop the pot, basically, and knowing that they’re coming at it from different scores. Pascal then reached out to Pierre de Fermat to consult on this problem–

A little background on Fermat. Along with Descartes, he was basically one of the leading mathematicians of the 17th century. Essentially, he created the modern theory of numbers, invented analytical geometry, contributed to early calculus. Newton actually gave him credit for it. And then, he worked also on light reflection and optics. So, another polymath. If you recall, we did an episode on the show, I don’t know, a year and a half ago or so, about this fiendishly difficult math proof that was called Fermat’s Last Theorem, that finally in 1994, this math guy named Andrew Wiles had solved it, but it had taken hundreds of years for people to try to figure it out.

Tobias: There’s a great book about it. Fermat’s Last Theorem is the name of the book.

Jake: That’s right.

Tobias: Fermat just gives this throwaway line where he says– [crosstalk]

Jake: It’s in the margin of something he’s writing. Yeah.

Tobias: Then, we’ve solved it using incredibly complex theories to get there.

Jake: Insane. Yeah. So, there’s this correspondence between Pascal and Fermat in 1654, and that became the foundation of probability theory. They were really the first to provide the mathematical proof behind what today we would call expected value calculations. So, basically, probability times risk, which is now the modern cornerstone of insurance and risk management. It seems obvious to us now, but before that, people had basically attributed the future to just fate. Whatever happened, no one could know. It was all up to the Gods. These guys finally brought some math enough through the enlightenment to make progress on this.

So, how could you insure against anything if you were just betting against the Gods, especially for the right price? In 1690, there’s a scientist and astronomer named Edmund Halley. He studied the data of births and deaths in this little town called Breslau. It’s now a city in Poland. The town fathers of this city had kept really meticulous records of annual births and deaths going back for centuries. And so, you had this really rich dataset. And Halley, his name might sound familiar because he pieced together that there was a series of comets, they were actually one comet that was appearing 1531, 1607, 1682. He predicted that the comet would reappear in 1758. It electrified the world at that time when it arrived right on schedule when he said it would. Unfortunately, he had died in 1742. So, that glory was entirely posthumous, but– [crosstalk]

Tobias: Did he use an inversion to predict the arrival of that comet? Did he look at the 10:3 inversion?

Jake: Yeah, it was a 10:3 inversion.

Matthew: [laughs]

Jake: So, now we know that as Halley’s comet, and it appears every 76 years. Last time was in 1986, and the next time will be 2061. So, hopefully, we’re all there to see Halley’s comet. Put that on your wish list.

Tobias: I saw it when I was a kid. I was four. I went and looked at the sky. It is a little white skid mark in the sky. I’ll never forget that.

Jake: Yeah.

Matthew: I was a little older than Toby, but I remember it being a thing where people go out and look. I don’t know if I actually saw it or not.

Tobias: Mom got me up at before the crack of dawn to look at this thing, pointed it out.

Jake: Yeah, it’s great.

Tobias: Sorry, dude.

Jake: Surprised you could see it from the bottom of the world.

Tobias: [laughs] I guess you are right. Turned in the right direction at the time.

Jake: Halley wasn’t just a stargazer. He used math to develop the first actuarial tables that were based on that Breslau data. This was in 1693. What it really allowed, the pricing of life insurance and annuities to be calculated. This math was actually very long overdue. If you remember, I was saying, it was back in AD 225, when Ulpian had made these tables in Rome, and now we have a replacement for it so much later.

But also, around that time, the English government had started taking and selling– They were taking a fiscal policy of selling annuities. What was crazy was that they ignored age completely and they were just like, it was the same price for everybody. This policy actually continued until 1789. So, literally almost a hundred years after Halley had already figured out the actuarial table, did the English government finally bake that into how they did this. And so, it’s good to know that governments have always been on the cutting edge throughout history.

Matthew: [laughs]

Jake: All right. So, last little piece of this is in 1687, there’s this guy named Edward Lloyd. He opened a coffee shop near the Thames. It was a favorite hangout of men from the ships who had come in that were moored at the London docks nearby. And so, 1696, he published this thing called Lloyd’s List regularly. It was filled with info about arrivals and departures of ships, intelligence of the conditions abroad and at sea. It was this continually rolling almanac about ocean-related things, maritime related.

News also came in from all over the world into this little coffee shop to help him create it. People are just coming and going. Ship auctions started taking place regularly in the corner. And then naturally, of course, gambling on what ships were going to return or not started to happen in another corner. As you’d expect, human nature being what it is. We like to gamble on things. By the way, talk about early network effects. You just have people showing up to the same place, they’re bringing information all over the place, you have auctions going, you have information, you have gambling. It was like a super app at the time.

So, of course, the individual risk takers would gather in this one corner, and they would look at deals to personally insure. And so, they would confirm their agreement to cover the losses if something went wrong and they figure out how much to get paid as a premium. It started from gambling and then evolved into– They would then write their name on the piece of paper under the terms of the contract. That’s where the term “underwriter” came from, is just literally writing your name under the words in a contract.

And so, this core group of underwriters then banded together, and they committed all their worldly possessions and all of their financial capital to secure their promises that they were making to make good on any losses that happened that they had insured. They had actually real skin in the game, which is interesting to think about when we’re talking about some bankers today that don’t seem to have as much skin in the game. But this syndicate of these original guys then were the early roots of what became Lloyds of London. It’s like this giant insurance syndicate now.

In multiple places, we have Fermat and Pascal trying to figure out this gambling like, “How do we chop the pot,” and that then led to the math of expected value. Then, we have people gambling on ships and whether they’re going to return or not that then eventually evolved into basically maritime insurance, and the rest of the insurance industry has sprung from there, basically. So, gambling leading to how insurance works.

Tobias: Similar thought process, probabilistic. Makes sense.

Jake: Probabilistic? That’s right. Risks, trying to take smart risk.

Tobias: I want to give a shoutout to a gentleman by the name of Trent Hayden. He’s gone through all of our podcasts on YouTube, and he’s put up where Jake’s veggie segment starts. So, if you go to any of our old podcasts and you want to zoom in on Jake’s veggies, find Trent Hayden’s comment [On The YouTube Video] and he’ll tell you. He’s given a little summary of what it’s about. So, for example, from our Bloomstran interview, he says, “Jake Taylor’s veggie segment begins at 22:04. Bamboo blooms, human catastrophe.” God’s work.

Jake: What?

Tobias: Yeah.

Matthew: [laughs]

Tobias: He’s done it across all of them. So, thanks very much for that, Trent.

Matthew: I always enjoy the veggies segment.

Jake: Beers are on us whenever we– [crosstalk]

Tobias: That’s right.

Will AI Disrupt The Insurance Industry?

Matthew: So, do you think insurance is an industry that can be disrupted by AI or machine learning or more computer power, or is this something that’s just the math is what it is and it can’t be disrupted?

Jake: I think that people have always looked for a data advantage when it comes to insurance. Geico’s entire raison d’etre was that they understood something about that class of driver that other insurance companies didn’t understand. Snapshot, for instance, telematics, that’s trying to get data coming in that others might not have. So, it’s always been a game about trying to understand the risk that you’re taking based on outside data. And it’s always been the law of large numbers at play. The more data we can capture about a population and the more sampling that we can do of a population, the more likely we are to understand the expected outcome of an individual ball being pulled out of that urn. So, I don’t think the game changes, really. I think AI helps with data gathering. It probably helps with the regressions that you would need to run to figure it out. But at the end of the day, I think it’s still sort of the same game.

Tobias: Yeah, I think so too. I think it’s a little bit like investing that if you can find a little edge, then you can make some money for a period of time, but I do think they all get arbitraged away overtime.

Jake: The other part not to be missed is that there’s a behavioral component to underwriting insurance as well, where people want to get a bonus for writing a certain volume and they write dangerous insurance when they do that. There’s a discipline required to get the right price for the risk that you’re taking. And that gets relaxed a lot at different points in the capital cycle. You saw a bunch of guys get into reinsurance at different points in time, because it looked like free money to them to go and invest it. Too much capital goes in, there’s not enough premiums to justify the risk that they’re taking, they get absolutely clobbered, they leave the industry. Prices then get really hard, and everyone can– and now the insurance companies that knew what they were doing start making good money again. This thing is very similar to the investment cycle.

Tobias: Very like investing.

Jake: It’s exactly like the investment cycle.

Matthew: Yeah, I guess if an insurance company wants to come in and just grow a lot, it’s real easy to write those policies. You could look good. You could look great for a few years before– [crosstalk]

Jake: Buffett makes the joke that if you could be alone in a rowboat in the Atlantic and just whisper the wrong price [Tobias laughs] for an insurance that you’re willing to offer, the sharks will be [Tobias laughs] crowding into your boat to take you up on it.

Matthew: [chuckles]

Tobias: Yeah, that seems right. I wonder if AI will ever get to the point that it can figure out that behavioral component, but then what will happen is the humans will override the AI.

Jake: Yeah.

Tobias: It’ll be saying, “Pull out,” and the humans will say, “No, this looks like a great opportunity. We should be in this.”

Jake: “Everyone else is doing it. We got to do it.”

Tobias: Do you know Lemonade well enough? Does anybody know Lemonade?

Matthew: Vaguely.

Jake: Only enough to be derisive. So, I better not say anything.

Tobias: Yeah. That’s what I meant too.

Jake: [laughs] We don’t criticize by name, Toby.

Tobias: [laughs]

Matthew: They do claim to have an AI advantage and better, slicker mobile user interfaces. They do write a lot of their liabilities off to reinsurance. So, they’re not maybe as exposed to the downside as you might think. I don’t know that’s clever or not. I’m agnostic on Lemonade. I don’t have a position. I don’t short, but I’m not particularly bearish on it. I just don’t know enough. I want to say 75% of their liabilities, they sell to reinsurance. Now, that obviously gives them less float, which a couple of years ago, when interest rates were super low, that didn’t matter as much and now it probably matters a lot more. So, like I said, I haven’t made up my mind if that’s clever or not. But yeah, I know–

They bought a SPAC. I think it was Root or Mile– I forget what it was called. Metromile, I think, that was like a SPAC for pennies on the dollar just to expand into certain states and stuff like that, because that company was failing. I think it was Metromile. That’s really all I know. It’s pretty surface level. That’s why I asked the question though to Jake, if you think it can be disrupted. It’s an interesting thing to noodle over. I don’t know if it’s the next best thing ever or if it’s a total just sizzle and lights in magic show.

Berkshire Hathaway – Industry Leaders In Insurance

Jake: Something not to be missed either in the insurance industry is that the trust is actually a huge component. You’re taking counterparty risk when you buy insurance from someone. If they go bust and when the shit hits the fan, correlations go to one. And there’s a lot of risk that aggregates that people didn’t have on their radar. When that happens and you actually need to get paid on that insurance, that’s where the trust factor comes in. And so, a company like Berkshire, it stands head and shoulders above everyone else in their ability to pay no matter what else happens in the world. They’ve run so conservatively on how much they can actually underwrite relative to their capital base that there’s no question at all that the check is going to clear.

If you treat these other insurances more as a commodity where, “Oh, I’m just laying it off,” well, who’s reinsuring it and are they trustworthy? Rightfully so, there is regulation in insurance and banking, because anytime that you can just basically take money today and then give a promise for something tomorrow is a delicate situation and you don’t want shucksters to get into that type of scenario, that’s where even the best regulations don’t ferret out all of the baloney. And so, you’re going to have issues in those type of businesses where you can basically take cash today and give a piece of paper.

Tobias: Looking at the data will be the same as AI looking at the back test data investment. So many humans going through that data for so long has meant that there’s really nothing in that data that we haven’t figured out. AI is just running humans through it over and over and over again until they can find something. I don’t think they’re going to dig up anything there.

Having said that, making a really slick front end, that’s really easy to use, that might generate a lot of insurance [unintelligible [00:56:01], if it’s easy to use. I know every time I go and buy various parts of insurance that I have to buy for the business, they’re so hard to use. If someone solves that problem, they can have all my business.

Matthew: Again, I’m not an expert on Lemonade, but I know they started with renters’ insurance, because that was the very low end of the market. It was the classic– They wanted to put the other companies, the big insurance giants in an innovator dilemma kind of area. Are they really going to compete hard for this very low end of the market with renters’ insurance? Which are more often than not younger people, where if you promise, “Hey, we’ll pay you the next day. You have a claim and we’ll pay you within 24 hours and we’ll cover your $1,000 furniture in your first apartment after college,” or something.

Jake: Yeah. [laughs] All my CDs.

Matthew: Right. Yeah, exactly. If you’re going after that kind of market, I don’t know if– Trust in any financial institution I think is the most important thing. There’s nothing more important for a bank or for an insurance company. I think you have to have trust and confidence. [crosstalk]

Jake: Now you tell us, Matt.


Matthew: But I wonder if you’re a young consumer and you’re getting off in your career and you want a cheap renter’s insurance policy or whatever, I don’t know if they’re looking at– They see the slick interface, that matters to them at that moment. And then they [crosstalk] sell different policies to those people.

Jake: You just highlighted the moral hazard that is FDIC insurance and other forms of that where you don’t do any research to see, is this a reputable company or bank? You turn your brain off to all of that stuff and you just stick it in there and you assume that it’s all good, right?

Matthew: Yeah, you’re covered. You’re fine.

Jake: Sure.

Matthew: Right.

Tobias: On the counterparty risk, I thought it was interesting. I think it’s in one of Buffett’s letters or it might be– I’m pretty sure it’s in one of his letters where he says some gentleman came and looked at Berkshire, the company, and Berkshire’s insurance policies. And he said, “Your insurance policies are too expensive. So, I’ve gone and got insurance from someone else. But I think Berkshire itself is rock solid. So, I’ve bought a whole lot of Berkshire stock for myself.” Buffett holds it up as, “This is the decision that this man made.” But I always thought that’s funny. If you’re worried about the financial position of these other ones, shouldn’t you be also buying your insurance from the same place? I don’t know.

Jake: Well, you could almost guarantee that guy is– Whatever that he was buying that insurance from, did he have a fiduciary obligation to that? Let’s say, you’re the CEO and you don’t own any stock of the company and you have to buy insurance for something, business interruption, or whatever, who cares? Take the lowest bid, counterparty risk. That’s going to be the next guy’s problem, most likely, right? So, let’s keep our margins fatter, let me get paid more. I don’t need to do any worry about– Of course, it’s going to be more expensive, because they’re actually going to deliver.

Tobias: I wonder, things like car insurance where you’re legally obliged to buy it, so you’re always just going to go and try and buy the cheapest one you possibly can. Otherwise, most people probably don’t go and buy car insurance, even though as a society, we might want them to. At that kind of level, they’re not considering the counterparty risk. But clearly, if you’re selling on the insurance, what’s that reinsuring then? Yeah, that’s the most important time to be thinking about it.

Jake: Mm-hmm.

Tobias: Fellas, we’ve made it. Matt, thanks so much. Where can folks get in contact with you if they want to do that?

Matthew: Yeah, I’m always on Twitter. I’m on Twitter way too much. It’s @Matt_Cochrane7 with the number 7 or Check out our service. Thanks, guys, so much for having me. It was great.

Tobias: Pleasure.

Jake: Good see you again, Matt.

Matthew: Yeah, you too, Jake.

Tobias: Thanks, folks. We’ll be back next week.

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