VALUE: After Hours (S06 E07): New Constructs’ David Trainer on Forensic Accounting Analysis, AI and ML

Johnny HopkinsPodcastsLeave a Comment

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

  • Discernment and Propaganda on Wall Street
  • Wall Street’s Love Affair with Roll-Ups: Profit or Pitfall?
  • Understanding the “Kitchen Sink” Effect: When Companies Underreport Cash Flow
  • Beyond the Rockets and Robots: Unveiling Potential Flaws in Tesla’s Accounting
  • Beyond Price Tags: Why Economic Book Value Matters for Investors
  • Economic vs. Accounting Earnings During Market Cycles
  • Investing Lessons From Return on Invested Calories, not Capital
  • Data Center REITs vs Cloud: Can They Survive the Tech Shift?
  • Sell-Side Analysts: Conflicted and Inexperienced
  • Extracting Data From Footnotes Using AI & ML
  • NYCB Stock Plunges: Hidden Loans Exposed
  • Banks: A Different Beast, But Still Businesses at Core
  • Muddy Waters Short Report on Fairfax Financial: A Closer Look
  • Germany’s Regulatory Failings: How the System Protects Wall Street

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:

Apple Podcasts Logo Apple Podcasts

Breaker Logo Breaker

PodBean Logo PodBean

Overcast Logo Overcast


Pocket Casts Logo Pocket Casts

RadioPublic Logo RadioPublic

Anchor Logo Anchor

Spotify Logo Spotify

Stitcher Logo Stitcher

Google Podcasts Logo Google Podcasts


Tobias: This meeting is being livestreamed. This is Value: After Hours. I’m Tobias Carlisle, joined, as always, by Jake Taylor. Our special guest today is David Trainer from New Constructs. How are you, David?

David: I’m great. How are you guys doing?

Jake: Well. Welcome back.

David: Thank you. It’s good to be back.

Tobias: So, we’re going to talk a little bit about machine learning, AI, forensic accounting analysis. Where should we start? Let’s start with, what is New Constructs?

David: New Constructs is a forensic accounting firm that leverages machine learning to drive a better, I think, AI for doing research. It came out of the idea that there’s so much propaganda. I saw it firsthand when I was at Credit Suisse during the tech bubble. So much propaganda when it comes to research coming out of Wall Street, coming out of CNBC, coming out of everywhere that I felt like someone needed to lean into producing something reliable and worthwhile.

I feel like in some ways, people believe that machine learning and AI is like a magic wand, you can just wave over the internet and get all you need out of it and trust it. I think we got to maybe take a step back and recognize what it takes to make good research to begin with and whether or not AI can do that.

Jake: So, what goes wrong there then?

David: Well, the real issue is the propaganda, the underlying source data. So, I think one of the first things for me that was an epiphany was being on Wall Street and realizing, “Oh, wait a second, all these research analysts that I’ve been working with all these years, they’re not all made the same. The ones that are cozy with the bankers, they maybe have a different agenda.” There was no way to misunderstand that when Frank Quattrone joined Credit Suisse and they got into the tech investment banking, because before he joined Credit Suisse, it really didn’t have a tech investment banking platform. Then when he joined, it was really, really clear. Like, there was just a different focus.

I think the first thing that’s important for most investors to realize is that you just can’t trust most research. If it’s coming from Wall Street, it’s conflicted. And it’s conflicted in a big way. The research analysts don’t make money for the firm. The bankers do. So, who do you think decides who gets hired and fired? By the way, I don’t know how to make that funny thumbs up thing stop. You guys see that?

Tobias: [laughs]

Jake: Yeah. You did this.

David: Anyone know how to turn that off? I’ve been trying to turn that off for, like a month.


Tobias: Just let it go. It looks like it’s emphasizing everything you say.

Jake: Yeah.

David: It’s great. I think it does all kinds of stuff. Anyway, yeah.

Jake: The machine overlords agreed with you. [laughs]

David: That’s right. This is what I get for talking bad about machine learning, watch this going to do another one. It’s going to do the hands. Look at that, boom.

Jake: Uh-oh.

David: Anyway.



Discernment and Propaganda on Wall Street

David: So, yeah, for me, I think when we struggle a lot so much right now in society in general, it’s like, are we discerning about what we pay attention to and don’t pay attention to or what we trust and what we don’t trust. We lack that in so many ways. I think we see that in politics, and we see that in Twitter and social media, in general, where people are getting so upset and worked up, and then are isolated or polar in the way they address issues. You’re either like hardcore right or hardcore left, there’s no in between, there’s no civil discourse around things because people are, I think, feel like just so polarized.

It’s because they’re not discerning enough about what they’re paying attention to. You have to realize that most of what dominates the newswires, the TV, the research, is people who can pay to be at the top of the list. And they can pay to be at the top of the list because they’re making a lot of money doing what they’re doing. They’re more about making that money than they are about informing you. They’re at the top of the list because they want you to do what makes them money. Wall Street is a great example.

I’ve been replaying a video, the quiver quantitative people put together for us on WeWork. We were the first to blow that up. But remember, all of the propaganda about this great new idea, community adjusted EBITDA, right?

Jake: [laughs]

David: What’s WeWork worth now? Almost zero. Even the SPAC that they use to sneak into the public markets is about to go to zero. All that propaganda, they tried to sell that to the market. $45 billion valuation. And now it’s a zero. Does Zoom give me an icon for that now? No, it doesn’t look like–

Tobias: Did you take a look at WeWork through New Constructs?

David: We did. We did. We were one of the first to raise a red flag. We wrote an article. It was featured in Forbes. It was called This is the most ridiculous IPO of 2019.

Tobias: There was a lot of competition.

David: There was. There really was, and that made some headlines. That headline got featured in a couple of documentaries. People have sent me some screen shares of that being featured.

Tobias: Do you– [crosstalk] Yeah.

Jake: Yeah. What was the accounting that was throwing up the red flags there?

David: Well, it was the community adjusted EBITDA and how–

Jake: [chuckles] How could we have known? [laughs]

David: Yeah. That doesn’t sound weird? It’s a great example, like, of Wall Street crafting a narrative to make you want to buy something that’s worthless. The other thing that was an issue is in the footnotes, there were a lot of related party transactions that made it particularly bad, because we had a lot– Like you said, Tobias, there was a lot of bad IPOs in that period. But the related party transactions and the conflicts of interest that were disclosed were pretty bad. Adam Neumann paying his family exorbitant fees to cater parties and things like that, and him himself being paid a whole bunch of money for the WeWork.

Jake: Yeah, he bought buildings and then was leasing them back or something as part of that.

David: Yeah, it was all pretty ugly for a business that was highly unprofitable and then valued so richly. And the voting structure. That was the same with a lot of other IPOs. Voting structures were very anti-friendly to public investors. You’re basically going to give them all this money and have no voting power. It sounds like a great deal.

Tobias: It’s very common. Increasingly common these days. It seems like every company’s got the super voting shares.

David: Yes. So, it just gets to the point that as a great example of just how bad the propaganda can be, how far they’ll go to mislead people in order to get them to try to buy something that they want to sell. It doesn’t just happen with the WeWork. It happens all the time. That’s the majority of information people are getting, whether it’s about stocks or politics.


Sell-Side Analysts: Conflicted and Inexperienced

Tobias: What do you think about the sell side analysts? Obviously, they’re trying to get business for the bank, which is why they’re often more optimistic than they probably should be, but they also seem to be– I thought the whole point of the change that they made post Quattrone and all those other guys from that period was they had to be independent. That seems to have just slowly disappeared.

David: Yeah. No, I’m with you on that one, Tobias, because the global research settlement driven by Eliot Spitzer. Not such a famous name anymore.

Tobias: Infamous.

Jake: Yeah. Right.

David: That was the biggest settlement against Wall Street in the history of the world. It was $1.2 billion. I think that Wall Street probably made about that much money in a week during the tech [Tobias laughs] bubble. There’s been a lot of articles written about how small the fines are and how that effectively is. It’s an incentive to break the rules, because even if you do get caught, it’s going to be less than what you made.

But to your point, Tobias, on the analysts, that was the fine is that there was huge conflicts, and they were getting paid directly by the IPO. So, I don’t think they’re getting paid directly on the proceeds of the IPO, but they are, for sure, getting paid for the proceeds of the IPO, because that’s the only revenue anyway to the firm. So, I think the bonus can’t be tied to how well a particular IPO does.

Yeah. I think part of the way they do it too is that how many silverback analysts do you see out there? How many analysts from Wall Street aren’t young and vibrant personalities? They bring these folks in so young, pay them so much money. They don’t even understand what they’re doing half the time. I don’t think they really get that it’s a conflict, because it’s not like they’re advertising it at the firm. I know when I was at Credit Suisse, there were just a couple of older gentlemen that were analysts, but everyone else was really young. I think that’s increasingly the trend.

Jake: Intellectual cannon fodder.

David: Yeah. And honestly, I think they’re just throwing so much money at them, and they’ve never really understood how the industry works. They don’t get it right away.

Tobias: It’s like, Druckenmiller hiring those two young gunslingers at the top of the dot-com boom, because he knew he was too jaded, too cynical to do it himself and he needed some guys who’d never been blown up. Fearless.

David: Yeah.

Tobias: And then they blew him up.

David: Yeah.

Jake: [laughs] He knew it was going to happen.

Tobias: And he knew it.

Jake: And he couldn’t stop himself.


Tobias: Let me give a shoutout to the folks who are watching. Clearwater, Florida. First in the house. Kotor, Montenegro. Ocean City, New Jersey. Winter Park, Florida, What’s up? Valparaiso. London. Castleford. Hamburg. Tienen, Belgium. Highland Park, Illinois. Albuquerque. Brandon, Mississippi. Mendocino. What’s up? Vancouver. Old Ocean, Texas. Milton Keynes. Sacramento. Toronto. Highland Park. We got them all. Albuquerque. Nashville. Someone in Nashville.

David: Nashville? Nice.

Tobias: Clunjjville, Netherlands. Reykjavik. McMurdo Station, Antarctica. That’s a good one. Is that real? Santa Monica.

Jake: [laughs]

Tobias: Koh Samui. Good for you. Thailand.

Jake: Jeez.

Tobias: That’s a good spread. I don’t know why you’re dialing in here if you’re in Koi Samui. Maybe it’s nighttime. So, David, you guys take the financial statements, you pass them, you’re looking to reconstruct them, so they’re comparable on a like for like basis, and then you store that in a database that’s searchable. Is that New Constructs, similar to it?


Extracting Data From Footnotes Using AI & ML

David: Yeah. It’s like, you take all these filings and all this crazy amount of data, and you organize it in a way that helps you understand profits better than what’s given to you in the filing, because you can’t really trust that for a variety of reasons. It’s been a problem that’s been around since the beginning of the stock market. The big benefit today in context of today’s conversation is that by doing this reorganization of the data, we’ve got real training data to drive machine learning and AI, so that– There are a lot of filings we can parse 100% automatically.

And so, the process of pulling this data out– Let me take a step back, because the reason that the automation is important is because if you’re going to do this work manually, you’re going to read a 250-page annual report and pull out all the data, not just the income statement or the balance sheet of the cash flow statement, but everything in the footnotes. And that’s the majority of the filing. The financial statements are three or four pages. Footnotes, that’s the other 247 pages.

The nature of footnotes is that you never know if the footnote is going to be on page 201 or 184. You don’t know. You have to look at all of them. We have been painstakingly parsing out the data from these filings for 20 years, so that now we’ve done it enough times and organized the data in a way that we can drive our machine learning with a real intelligence around how to categorize and understand the data, because we’ve got hundreds of thousands of examples of how to do that.

That’s the big distinction I want us to come away with today for the audience in particular is that, no matter how fancy or powerful your AI or machine learning engine, if the fuel driving it isn’t super high-quality, then it’s a waste. It’s just like we’re hearing with ChatGPT producing reports based on inaccurate data and producing inaccurate results as a byproduct. If you don’t have the good information to drive the formula, the calculation from the original simple models to the most sophisticated models, the source data, the underlying driver of the data for the model is what matters most. And if that’s not right, then you can’t trust the output, no matter how big the engine.


NYCB Stock Plunges: Hidden Loans Exposed

Tobias: Did you see that New York–? I think it’s New York Community Bank, NYCB, that stubbed their toe pretty hard. I think they were down like 34% in a day, and then– It might be down 50% from the peak. Did you have a look at that? Do you know what I’m talking about? Do you know that filing that they came out and they had the two–? It had two loans in it that had done most of the damage. And to read those loans, it almost read like there was nothing wrong. I read them, and I couldn’t figure out what was– They’ve clearly very cleverly drafted to hide what’s actually happened. Do you know what I’m talking about?

David: Yes. That’s what we’ve been battling. I’ve been doing this work for 25 years, and that was part of the reason I had such an epiphany when I was on Wall Street and putting together, “Hey, look at this tech team and what they’re talking about.” I’m looking at these filings and I’m seeing how the complexity is not just– It’s not just a lot of complexity. It’s changing every quarter. You’d think that the quarterly report for one company from one quarter to the next would be exactly the same. Why would the auditors want to introduce change, and why wouldn’t the annual report look just like the quarterly reports? They don’t. They change it all the time. You could look at IBM over its history. I know at one point they had an income statement with maybe 10 items on it, and probably now there’s 20. I don’t know.

And so, yeah, Tobias, the lawyers are constantly going through and trying to redraft these things in a way that can walk the line between disclosing what they need to disclose while not raising any red flags. Because we know with the bank you’re talking about, the issues have been there for months. It just now got surfaced. Same with true with Enron, right? It took Jim Chanos blowing them up on a call to ask questions and see things that had been around for a long time. It takes them sometimes a while to manifest it all in the financials, and then it takes a while for people to dig that.

Jake: Is anybody working on an AI that is actually on the offensive here, so you’re like, “How could we write the most– get our maximum obfuscation without tipping into illegal, and then selling that product to a corporation”?

David: They probably are.

Tobias: I think that’s what they sell.

Jake: Black hat. [laughs]

David: The audit and the legal firms are probably trying to figure out a way to automate it, but that is what they sell, I think, in general, for sure. It’s all about trying to maximize shareholder value, part of that is to obfuscate the things, bad things are going. Yeah.

Tobias: The New York Community Bank, when they had that filing of those two loans that they were writing down and it looked like the first loan was some– they’d taken a big hit from the first loan. The second loan looked like it was part of a category of loans that I think that they were saying that we’re going to have to take a haircut across the category, but we don’t have to do it just yet, so we’re not doing it just yet, was the way I read it. I don’t know if you guys seen those. Sorry, I didn’t bring along the slide that had, because it’s not a long disclosure. It’s only two paragraphs disclosing these two things. I just wondered how you deal with that if that was something that– Because they seem to be talking about other– [crosstalk] The second one as being part of a category.

Jake: Was it just an 8-K that they put out?

Tobias: I can’t remember exactly what I was looking. I think possibly.

Jake: Friday night dump?

Tobias: Yeah, I was just interested to know how everybody missed it because it was a big hit in one go.

David: Yeah. It must have been an 8-K, because we’re showing the last 10-Q was– Well, that was for September 30th. So, that probably came out before the end of the year.

Tobias: This would have been last week or the week before.

David: Yeah, it was a couple of weeks ago. And so, yeah, we have not yet got a new filing. The 10-K is supposed to come out in March. So, this was probably– They were probably forced to surface that news a little early because it was so important.

Tobias: But it certainly blew the stock price up. The market agreed.

David: Yeah. Look, there are probably going to be some more blow ups.

Tobias: Yeah. I have this theory that none of that office has been properly account. None of the haircuts that they’ve taken on the office has been properly accounted for yet and you’re going to see that through all the regional banks. But all the regional banks are– Everybody else knows that too. That’s why the regional banks are trading low where they are. But I’m just interested. I was just wondering, because the filing was benign. It was a cleverly drafted filing.

David: Yeah. We show that the free cash flow– It had a neutral rating in our system, and it has for a while– The free cash flow is terribly negative. The valuation looks cheap, of course. But yeah. The thing about the banks oftentimes is that you don’t get in the 10-Ks and the 10-Qs, the quarterly annual reports. They don’t give you visibility into the underlying loans-

Tobias: The loan portfolio.

David: Loan portfolio. Correct. You’ve got to look through some other filings if you can get it at all.

Tobias: It’s also the way they treat it though. They’re waiting for particularly– — it has to hit certain thresholds before they have to recognize it?

David: That’s right. Especially, if it’s held to maturity versus available for sale. Those kinds of rules mix it up as well. So, it’s somewhat of a complicated issue, because these are long–term loans. And at some point, commercial real estate will come back. So, to mark to market a at time when things are abysmal is a bit overreaction.

Tobias: Held to maturity allows you to do that. You don’t have to recognize it mark to market in the interim. It’s only if it’s held for sale that you have to recognize that.

David: That’s right. Exactly.

Tobias: Which is sort of– it’s sensible. It makes sense to me that you can do that. But unless it gets impaired, in which case you have to recognize it.

David: Correct.


Banks: A Different Beast, But Still Businesses at Core

Tobias: It just makes bank investing so hard. That’s why most people avoid banks.

David: Yeah. It’s a completely different set of financials to analyze. I remember back in my Credit Suisse days and I was doing this work on a bunch of different companies. When I first started doing this kind of economic earnings, as opposed to accounting earnings work, they said, you couldn’t do it for financials. And most of the databases from the legacy data providers, if you want to look at the S&P in any kind of financial metric, it’ll be X financials.

And the truth is, the economics of businesses are the same universally. At the end of the day, when you boil it down to the essence, which is, a certain level of cash flow generated from a certain amount of capital. That’s what any business does. Anything for profit. You got to hopefully generate, either you’re generating a profit or a loss based on some capital that people gave you in the business. Maybe you have no capital, but you get the point.

That’s what we’re trying to get at in New Constructs, always is, what’s the cash flow, what’s the capital to start for the business? Whether it’s a bank or a trucking company or restaurant, those concepts apply. It’s about really unwinding all the accounting jargon to get to those core concepts and footnotes to get to those core concepts with integrity, so that people have information they can rely upon.


Muddy Waters Short Report on Fairfax Financial: A Closer Look

Tobias: Did you see Muddy Waters short note on Fairfax?

David: We have an online community, and someone brought that one up last week. Oh, man, I didn’t look into that that much. But I do remember seeing someone mention something about that. What’s the trick there? [crosstalk] any idea?

Tobias: FFH.TO, I think is the one that I used to pull it up. I think might be traded on the pink sheets in the States.

Jake: Yeah, it’s FRHFH, I think.

David: Fairfax Financial Holdings?

Tobias: Jake’s probably over that a little bit better. Do you want to give a little background on that?

Jake: On the short report?

Tobias: Yeah, just on Fairfax in that short report.

Jake: You know my reading of it was that– To me, it seemed like they were really just mostly complaining about account–

Tobias: IFRS

Jake: Yeah, IFRS accounting standards and how things are marked. In all of these things where you don’t have a liquid market for it, there’s a lot of judgment that can go into how do you determine what you carry something on the balance sheet for. So, I don’t know. It seemed like a lot of much ado about nothing to me personally, but there’s probably other more things that more substantial to complain about than the accounting.

Tobias: I thought it was a funny target, because it’s one that’s well known by value guys. Value guys like Fairfax. Value guys read financial statements often.

Jake: It’s had a good run.

Tobias: Good value—[crosstalk] Yeah.

Jake: It’s had a good run. And if you were more of a casual holder, and Muddy Waters comes along and drops something that might scare you out of it, then they can cash in a little bit on that. Maybe that might work for them as a strategy. But on any longer-term basis, I didn’t really think it was much of anything.


Tobias: Who got Valeant? Who got Valeant right on the short side? Because it caught a lot of value guys long. And there were some big names in Valeant long. Ackman was long.

David: We were early on Valeant too. I remember having debates with people on Seeking Alpha, and maybe sum zero about Valeant. I was making the point that their adjusted EBITDA was not a reliable number. I said, “You can’t pay bills with basically fake EBITDA.” You can’t pay the bills with that adjusted EBITDA because there’s no cash. And I remember people like saying–

Jake: You Just don’t get it, man.

David: Yeah, “You don’t get it, man. You don’t know how to do the math.” I’m like, “Bro, I’m doing the math.”

Tobias: That’s the problem. That’s the problem.

David: Yes, it is a problem and I’m really doing the math. Yeah, Valeant, that was a really pretty obvious one, especially with the disincentive with just all stock-based compensation.


Wall Street’s Love Affair with Roll-Ups: Profit or Pitfall?

Tobias: Canadian roll up. Levered roll up.

David: Right. Yeah, the roll up stuff has always been– That’s an old time Wall Street trick.

Tobias: It makes it hard, because you got to deal with new financial statements every single time. With a big acquisition, every single time, so there’s no continuity.

David: Yes. They tend to be very well supported by Wall Street, because Wall Street is making a bunch of money [crosstalk] earnings.

Tobias: I don’t like the money. Yeah.

David: Right?

Tobias: Yeah.

David: All the way along, and they love selling that. And as long as the acquiring company has a higher PE and they’re buying lower PE companies, it’s earnings accretive, regardless of the economics.

Jake: Yeah, top line can look really good.

David: Yeah. One of my good buddies, I was at Credit Suisse with, who went over to Goldman Sachs, I remember he called me maybe 5 years or 10 years ago and said, “David, man, I just realized these roll up things are just a scam.”


David: I’ve done enough of them now to realize, once you’re done and you got no more to roll up, you end up with a business that’s got all these acquisitions. Most of the acquisitions were overpaid, and so they’ve got all this– just a junk pile of stuff that’s not really been fit together, but all the way Wall Street is making a ton of money. The acquiring executives are making tons of money. Their comps just going up because they’re a bigger and bigger company, they get bigger peers to judge comp against. Yeah, it’s a great money-making scheme for those that are in the know, but the investors, at the end of the day, usually get left holding the bag.

Jake: Well, David, there’s synergies at the end of the rainbow that are going to make it all work.

David: Yeah, that’s great point. The synergies are [chuckles] rolling there. That’s right.

Tobias: In the 1980’s, that sort of roll up was very popular. They called them entrepreneurs. They had their own index, the entrepreneurs index, and you’ll never guess how it finished.

Jake: In Australia, right? This is–

Tobias: Yeah, this was in Australia, which is why I’m skeptical. I’m always skeptical of anything. That’s a roll up type thing, which is why I probably missed Credit Suisse, not Credit Suisse, Constellation for a little while. Just looks like a roll up. But probably smarter than your average roll up. Berkshire’s a roll up, right? Smarter than your average roll up.

David: Yeah.

Jake: I don’t know if I would classify that. That’s a serial acquirer. But roll up to me tends to be in the same industry.

Tobias: Industry specific. Yeah.

David: It’s a consolidation theme, where there’s the synergies in a highly fragmented industry, we’re going to bring these companies together and see all these synergies. Fairfax is mostly rebounded from the Muddy Waters report. It’s surprising, because I thought the Muddy Waters guys did good work. But if they’re just leveraging their reputation to try to make quick buck on a short, that’s not a good look.


Tobias: They got that one wrong, I think. I couldn’t even find it on the site. When I went to the site, it wasn’t even up. I could only find the preceding one.

David: Really? So, Muddy Waters already took it down.

Tobias: I don’t know. I just couldn’t find it. I didn’t look very long. I just wanted to see what the meat was and see what they were actually saying, but couldn’t dig it up.

David: Yeah. When I did a Google search on Fairfax, the Muddy Waters thing is not in the top on the first page. It doesn’t have any mention of it. To think it, it’s really strange.

Tobias: You should be skeptical. It’s good to read this short report. Good to have a look.

David: Yes. Skepticism is good.

Tobias: People probably needed a little bit more skepticism with Valeant. Yeah, I thought it was a little bit, yeah, all smoke, no fire.

David: Interesting. Yeah, I think that’s just another example, guys of like, just the propaganda machine, the misinformation. It’s a problem. It’s a real problem, I think that– I’d look at it not necessarily as something that means spells the end of mankind. I just think it’s part of a process. I think if you were to believe that there were other intelligent species and other planets that probably far advanced than ours or whatever, they all probably went through the information age, and they would all tell you that the beginning of the information age is the misinformation age.

Tobias: [laughs]

David: There’s a deluge of data, information, whatever. And in the beginning, we don’t have the equipment, the sophistication, the ability to discern between good signal and bad signal.

Jake: So, David, if you ask a hypothetical there, then let’s say ChatGPTs, all these LLMs are trained on “the internet.” What percentage of the internet would you call fact versus propaganda?

David: That’s a big question, Jake.

Jake: [laughs] I try to only ask the big questions.

David: I don’t know. 50/50, is it that good? I feel like bad information is a lot easier to create than good information.


Jake: That’s true.

Tobias: It’s easier. You don’t have to go and look at facts.

Jake: It’s a real time saver to just– [laughs]

Tobias: All right. “Fairfax is up on the website. It’s been up there for five days.” Thanks, BrownMarubozu for checking that out.

David: Yeah.


Understanding the “Kitchen Sink” Effect: When Companies Underreport Cash Flow

Tobias: I got a good question for you here, David. You ever seen any companies trying to underreport their true cash flows?

David: Yeah, that happens quite a bit, especially during bad economic times. We call it the kitchen sink effect.

Tobias: Oh, yeah.

David: The idea is when, look, the market is bad, you might as well just tank your earnings, because if you beat in a market with negative sentiment, you’re not going to get any credit for it, and the market is just beating everything down. So, you understate your earnings and cash flows for as long as you can, and then when the market sentiment turns, you take all the cookies you put in the cookie jar and you throw them on the pile when the market sentiment is positive, and you get a multiplier effect on positive sentiment, on earnings, beats on top of the fact that your comps have been reduced as well. So, you beat the numbers down, and then you can come back higher, faster and you get better comps. And so, it’s part of the way they play the game.

Tobias: That’s smart.

Jake: And you want to time your option pool for that big bath quarter?

David: Great point. Yeah, we should– Can we grant a few more options here during this bad time?

Jake: We need to retain all of our management. We don’t want people to leave.

David: Yeah. Especially when things are looking bad, bonuses are going to be lower, maybe we need to increase our equity comp. Yeah, so it does happen. It does happen. I’m not here to say that every single company is intentionally manipulating their earnings. That’s part of the challenge. It’s not always intentional for all of them. But for some, it’s a big deal. For some, it’s a big deal to the negative, it’s a big deal to the positive. For some, it’s accidental. For some, they don’t really realize, because you don’t really want a management team that pays that much attention to accounting stuff. You want them to focus on the business. That was a huge red flag for Enron. Two-thirds of the organization was employed in the accounting division. And all they did was try to figure out ways to manipulate accounting. They called it the risk management division.

Tobias: It’s a good name.

Jake: The accounting was the product at the end of the day.

David: That’s the best way to put it, Jake. It was the product. Two-thirds of the organization worked there, and that’s what they, exactly, it was the product. [laughs]


Beyond the Rockets and Robots: Unveiling Potential Flaws in Tesla’s Accounting

Jake: David, any thoughts on–? I heard David Einhorn interviewed recently, and he says that there’s a lot of red flags with Tesla’s accounting. What does New Constructs see on that front?

David: Yeah, it’s been there for a while. We’ve pointed out so many flaws in Tesla for, like, I don’t know, how many years, and people just don’t want to hear it. So, we’ve stopped pounding that drum despite the fact that, you know, it feels like every other week, I’m like, “Oh, the walls are closing in on this one, finally.”


Jake: And then it’s up another 50%.

David: Yeah. “Oh, guess what? Hey, we’re going to send a rocket to Mars.” [Tobias laughs] “Hey, pay attention to that. Don’t look over here. We’re going to Mars.”

Tobias: We’ve got a robot.

David: Yeah, “I got a robot. It can dance.” “Oh, wait, that’s somebody in leotards.” “Oh, okay, wait a second,” or spandex. Gosh, the gullibility, it feels like is just people want to believe what they want to believe. And that’s another thing. It’s like, not even that people aren’t discerning. They totally fall in the confirmation trap, and they will only focus on things that will confirm what they already believe. Because, by the way, that’s easier too. Speaking of what’s hard or easier, producing good information or bad information. It’s a whole lot easier just to say, “Oh, you know what? I believe in Elon Musk, and I’m going to focus on all the things that make me want to continue to believe and not look at anything that doesn’t confirm my existing beliefs.”

Tobias: Well, you just assume you’re missing something that everybody else has figured out, and you don’t want to say anything because you don’t want to be the guy pointing out the emperor has no clothes if in fact there are fully dressed.

Jake: Oh, really? I think it’s the other way around, where you get to feel smarter than everybody else. Like, you figured out something that no one else understands.

Tobias: But isn’t that why you wouldn’t want to stand outside? Like, you don’t want to stand apart?

Jake: I think that’s why it’s such a battleground stock. I think you have both sides that feel very religious about it.

Tobias: I will say this. I was short the stock at some point, and I’m highly skeptical of the accounting. I think that it’s worth a lot less than everybody thinks it’s worth. But it was in trouble before it raised a whole lot of capital through that 2020, 2021 period and that’s probably donut has been taken off the table. But driving the car– So, I recently got one of the cars.

Jake: [laughs]

Tobias: The cars are beautiful. It’s very thoughtfully laid out. It actually makes me angry at the other car companies when I drive it, because I just think, there’s nothing in here is genius. It’s just thoughtful, and anybody could do this. And they’re not. Like, what are they doing? Makes no sense.

David: I think it drives a lot of the sentiment. I think that’s a lot of the reason you got the Tesla fanboys, because they’re like, “This is so much better.

Tobias: It’s good product.

David: These other guys, the Indians, they can’t do it.” I think that that was true for a while, but they’re catching up. I think that these other cars, at least in terms of market share and sales are, for sure, catching up and even eclipsing Tesla,

Jake: it might be BYD is the actual–

Tobias: You see BYDs in the States?

Jake: No, not yet. They’re not in the US yet.

David: Are the trucks in the US? Because I thought I read that they had some trucks that were–

Jake: Maybe. I don’t know.

David: They’re coming. I think it was part of the deal. By the way, in terms of accounting with Tesla, absolutely, the biggest and most important one I think is the regulatory credits, considered normal recurring profit. I don’t believe that they are. They’re going to go away because they’re just not going to be able to enjoy those forever. You should not consider that as part of the operating margin of the business. It won’t survive.

The time they’re raising capital in the US markets and they got the capital from China when they needed it. I believe that BYD has done as well as it has, probably in no small part to robbing some technology from Tesla.


Investing Lessons From Return on Invested Calories, not Capital

Tobias: Jake, do you want to do your veggies?

Jake: Absolutely. I think this is kind of a fun one. I’m actually a little excited about this, more than normal. All right. So, life is essentially a game of turning energy into kids. And every trait is tuned by natural selection to maximize that evolutionary return on each calorie spent. So, I thought it’d be fun to look at different strategies in nature and their ROICs. And in this case, it’s return on invested calories, not capital.

David: Nice.

Jake: So, we’ll start with what I think is the most impressive one, and this is whales eating krill. Blue whales are the largest animals on earth. They weigh on average 200,000 to 300,000 pounds, which is 136,000 kilograms for our non-US or non-imperial. And krill are these little tiny floating sea creatures that are in the same class of animals as crabs and lobsters, crayfish, shrimp. They make up the vast majority of the blue whale’s diet.

So, you have these huge whales, and they’re eating up to four tons of krill every day, which is like 3,600 kilograms or 8,000 pounds. And the whales, how they do this is they work together to execute something called a bubble netting, and they dive below a school of krill, and they release bubbles strategically to herd and confuse the krill into these piles of krill, basically, and then they come through and basically gulp them all up and then strain the water out and then eat the krill.

And so, you might be wondering, like I was, how much krill can a whale eat in a single bite? And if a big whale attacks a particularly dense swarm, it can swallow up to 500 kilograms, which is 1,100 pounds of krill in one go, that equates to eating 457,000 calories in a single giant mouthful.

Tobias: [crosstalk]

Jake: Yeah, talk about binge eating. And yeah, I do have to assume this is a relatively keto diet.


Jake: So, the whales get back almost 200 times the amount of calories burned in this attempt, which a 200x return seems like quite the ROIC to me. But how does it stack up to other strategies in nature?

So, let’s next look at something that’s quite a bit different, which are cheetahs. Cheetahs spend about three hours per day walking around, which uses up about 40% of their energy budget. They chase prey less than two times per day. And it’s about 38 seconds spent per sprint to try to chase prey. The rest of the time, they just lay around napping like house cats, basically. And so, they either catch dinner or they give up rather quickly. And they’re successful about half the time when they are chasing. So, a cheetah can eat up to 14 kilograms, 31 pounds, at one sitting, which is similar to Toby at Thanksgiving.

Tobias: [laughs]

Jake: A group of four cheetahs can finish an impala, which weighs between 90 pounds and 150 pounds in about 15 minutes. So, talk about really being able to pound it down there.

So, now, let’s transition to humans. Like, how do we do this? How well do we fare? Looking at first at hunting and gathering, the Hadza tribe, which is one of the most studied tribes because they’re the most hunter-gatherer of today’s day and age. They live in Tanzania, and they’re near the Serengeti. But they live in tribes of, call it, 20 to 40 people. And Hadza men will burn 2500 calories per day while hunting. It’s mostly just walking around. They’ll shoot these poisoned arrows at giraffes, for instance, and then spend the next few days tracking the animal as it slowly dies.

And in case you were wondering, there are about 1.3 million calories in a giraffe. And so, for reference, the number of calories in a cow is about 430,000. So, they’re considerably more calories in a giraffe, so next time you’re ordering off the menu. But that entire cow is still way less than the single giant mouthful of krill that the whale eats, which is rather remarkable.

So, anyway, if we assume that the typical three-day hunt of 20 Hadza men burning 2,500 calories per day, we get a total investment of about 150,000 calories, and you’re getting 1.3 million calories then if you do catch the giraffe. So, that’s a 9x return on calories. Nine bagger, pretty good, but that’s still an order of magnitude below the blue whales 200x.

And by the way, the Hadza men land a big game like a giraffe only about once a month. So, they would starve if the Hadza women weren’t out there executing an equally sophisticated and complementary strategy, which is using their knowledge of local plant life to bring home reliable food every day. It’s mostly like digging up tubers with sticks. So, the men get to feel like heroes, but the women are probably the ones actually doing the real work.

So, then let’s transition. About 10,000 years ago, we humans landed on a different strategy than hunting-gathering called farming. And today, that’s about 42% of our daily energy supply that comes from cereal crops like rice, wheat and maize. And on a per acre basis, rice produces 14 million calories per acre per year. That means that an acre produces enough to rice to feed 15 people for a year at 2,000 calories per day. And that’s like bagging 10 giraffes per year roughly, but we should probably ignore the quality of calories between grains and meat. I don’t want to weight into that online [laughs] battle.

But for reference, corn produces a similar 14 million calories per acre to rice. Almonds, pistachios, walnuts, tomatoes, wheat, barley, carrots, hay, those all produce about 5 million calories per acre. So, it’s about one-third. And then spinach and broccoli come in at under 1 million calories per acre which– So, so much for veggies segments. It turns out that there’s actually probably no real reason for us to be growing those things other than for people-


Jake: -to feel healthy. So, Toby, just to bring this back to the business world, if you had to guess like what ROIC strategy above, encapsulated by either whales or cheetah or humans, would you say most closely matches your own investment process?

Tobias: Oh, that’s a good question. There’s a good comment here from Tyler Pharris. He says, “Blue whales would trade at 20 times sales.” [Jake laughs] That’s the appropriate multiple to put on that strategy.

Jake: That’s a great comment [crosstalk] think about it.

Tobias: I’m a farmer.

Jake: Okay. How so?

Tobias: Lots of small bets rebalanced regularly. Just not relying on a single big hit. Just trying to get little wins all the time.

Jake: Okay. That’s good. Obviously, farming has allowed us to increase the carrying capacity of the globe for humans in a pretty dramatic way. In general, I think we should probably be thinking about how many calories we’re spending chasing around our investment ideas, and what are the returns on those calories spent. I’ve heard Wes Gray call it before like, “Return on brain damage.” I think that’s probably pretty closely related to this. But David, what do you think about how you do things and what that means for the amount of calories that you have to spend compared to the nutrition that you get back?

David: Yeah. I think the nutritional value of investment information is what we’ve been talking about all day today. It’s the raw material, the source data. I think that’s what it’s all about, because if you think you’re eating giraffe meat and you’re really just eating grass, you’re not going to have the results, no matter what however people package it. I think that’s what Wall Street is good at doing is making you think they’ve got selling a bucket of krill, and its maybe just sand. You need better ways to discern between what Wall Street’s selling and what a lot of other sites, these big, big retail sites. There’s a lot of misinformation.

So, at New Constructs, we’re just trying to– Basically, we’re farmers too. We’re farming the footnotes to really produce a more reliable signal for understanding profitability and valuation. And it’s a day by day, it’s a grind. It’s not sexy. I think it’s a very different strategy than the big game hunting, for sure. That’s more speculating to me.

Tobias: David, got a good question here from Tyler Pharris, who’s our producer


David: Nice.

Tobias: Unofficially.

Jake: Yeah.


Data Center REITs vs Cloud: Can They Survive the Tech Shift?

Tobias: “Does David have any opinion on the Chanos thesis of shorting the data center REITs (such as Digital Realty Trust and DigitalBridge) because their accounting (D&A mostly) is shoddy?”

David: Yeah. We agree with Chanos. In fact, he’d reached out to me one point and suggested take a look. Back when we were doing our zombie stocks, he’s like, “Hey, take a look at these guys.” We did a deep dive, and we came away with a similar conclusion and also feel like from a strategic competitive position that they’re maybe in a bad spot, because so much of the demand for the data centers is moving to the cloud. And then the big users of it, traditionally your Facebook’s and Amazon’s and Microsoft’s even–

Tobias: They’re doing it internally?

David: Yeah, they’re using their own cloud or they’re going to buy their own. They don’t want to go through a third-party for security reasons. And so, it’s hard to see how those businesses are really going to grow. They’re valued very expensively, and the cash flows do not look good. So, yeah, we wrote a couple of reports a while ago.

Jake: What was the accounting issue then? Are they under booking depreciation and amortization to make themselves look more profitable? Like, the assets aren’t as long lived as they’re saying? I’m trying to imagine how you could goose it.

David: I’m trying to remember exactly what it was about too, and I’d have to go back to look at it, for sure. But just as an example, in terms of quality of earnings, we’re showing for digital realty trust, economic earnings over the trailing 12 months are negative $8.18 cents and the accounting earnings are showing $5.98 cents.

Jake: But you make it up in volume.

David: I guess. There’s been a pretty strong disconnect for quite a long time. What we’ve seen in the last couple of years, it’s getting worse. The reported earnings are staying flat and the economic earnings are getting worse. I think a lot of times, when it comes to REITs, what people miss is just the size of the balance sheet. And so, when you go back to that old ratio of how much cash flow you’re generating relative to how much capital is going in, people tend not to look at balance sheets very often. When the balance sheet takes it to–

When you get a ton of ton capital required, this is a bad return on calorie. You are taking in a lot of calories, you’re not getting a lot of energy. Taking a lot of capital, you’re not getting a lot of profit or no profit for that matter. And that’s what happens a lot with the REITs. And then add on top of these REITs focus on data centers, and you got to question whether or not the data center business really even makes that much sense.

Tobias: The old bull case for the data centers used to be, it’s high return real estate. Once you get someone in there in a rack or if they’ve got their equipment in there, then it’s just a pain to move all of your services. So, they’re pretty sticky once they go in. But it’s real estate, it’s air conditioned and has lots of power and a few other-

Jake: You can’t put it anywhere. Yeah.

Tobias: [crosstalk] floorboards and– It’s pretty good real estate.

David: It’s specialized.

Tobias: Yeah, it’s very specialized. But that’s a real problem if all of the big guys are building clouds and going internal, it’s just like you’re not going to need your own power station anymore, you’re just going to get power from the grid.

David: Right. It’s so much easier. We’ve been through that. As a company ourselves, we had stuff at a data center. “Look at me, you want to go make a change, you got to make an appointment two weeks in advance and go through all the security and go in and lock the thing and do all this stuff.” It’s like, “Oh.” Or, you can just click send it to the cloud, it’s like, “I don’t know.”

The budget that Amazon has to spend on security, how does a data center business manage that? Because Amazon, it’s so centralized. Data centers, you need to have in different locations to serve different people. You can’t really just bring it all into one.

Tobias: And it’s just Amazon employees going in there. You don’t have to deal with a million employees from different places.

David: That too, which makes the security more challenging. So, yeah, good question. Yeah. And too bad. I think losing Jim Chanos from the market for investing is a telltale sign, man, of just how nutty things are. This guy’s one of the OG, short selling, kind of contrarian, skeptical investors out there. We don’t need to be running those guys out of business. They’re healthy for the market.

Tobias: It’s not just he’s made too much money. He’s too old. He’s doesn’t want to do it anymore. It’s more related to not even the environment, the regulatory environment, or the reception.

David: Like, everything he said, I just thought it was sad. I do know I follow him and see what he talks about and enjoy what he says. I share his perspective on a lot of things. It is frustrating to be right about the numbers for a long time. And stocks just go up.


Germany’s Regulatory Failings: How the System Protects Wall Street

Tobias: You got to be pretty Zen as a short sword I think just to be– Just read that Einhorn fooling all the people some of the time or whatever it’s called. Like, what a saga. He was upset with the accounting of a business development company, which is, they’re already a little bit of a funky thing. That took him years.

David: Right. And he was grilled by the SEC for like– He was the bad guy. The system is definitely geared toward helping Wall Street. Wall Street makes a lot of money. They pay a lot of taxes. They got a lot of money to put with lobbyists. I know I’ve been down that road too. I’ve been to DC, and I’ve suggested to the SEC and to the Senate Banking Committee for that matter. Look, we have technology that can do a lot of these things that we spend a lot of time doing manually and don’t do very well.

Jake: And how was your IRS audit after you went to all that trouble?


David: Fortunately, I make so little that I just can’t even make the radar, so it doesn’t matter. But yeah. No, great question. That’s been weaponized in a lot of ways too that’s part of. Anyway, it’s a tough market to sell the truth when you can make so much money selling misinformation.

Tobias: You remember that Wirecard, that German fraud, where the guys–? It was the journalists. I think the FT journalists and the short seller got visited at least by the German authorities. I think somebody scarier than that too.

David: Yeah, that’s my favorite joke to say to my kids is, whenever we see something that’s tough, like, “Oh, you think you got it bad, right?” And you think about the United States, where we at least have some independence between different regulatory associations. I think in Germany, it’s all just one, and they all get nominated by the investment banks. So, there’s– [crosstalk]

Jake: Like, the wolf hot watching the hen house, huh?

David: Yeah. I’m like, “Wow. Okay, that’s tough. That’s really tough.” That’s a really upside down regulatory environment. Ours isn’t great, but that one’s way worse. [laughs]

Tobias: Bill of rights is helpful in the States, I think. Stops some of the really bad things from happening.

David: True.


Economic vs. Accounting Earnings During Market Cycles

Tobias: Another good one from Tyler. “Does David see a bigger difference between “economic earnings” and “accounting earnings” during bull markets or bear markets? Could the gap between the two numbers be a useful tool to figure out where we are in the cycle?”

David: We do that research. Once a quarter, we publish the economic versus accounting earnings for the S&P, all its sectors. We do the same thing for free cash flow. We even break it down to return on invested capital, WACC, NOPAT margins and capital turns.

Yeah, there’s definitely, for sure, you can see the spreads widen and narrow during different times. It’s not always a great leading indicator. I feel like the last few bull markets have just been kind of– So, I think the biggest indicators there is the liquidity being pumped in. You can almost see the market go up and down based on how much liquidity is being released, at least over the last year. I felt like there’s been a lot of people who pointed out like, “Oh, by the way, balance sheet getting bigger, and that’s what explains the rally.” That’s as big a driver as anything.

I think the macro trends are tough to read. We look at them a lot. And what’s way more fun is looking at the individual industry trends and how different they are. Because when you get to the S&P, it gets kind of vanilla-ized or normalized.

Tobias: Too aggregated?

David: I think so. I welcome people to come and take a look at the research and see if they can find more out of it, because we don’t– Honestly, we put the data together and we move on to the next thing, we don’t get as much time to look at our own data as we’d like always.

But at the industry level and at the individual company level, that’s where I think you see the bigger clues, because you can say, “Oh, look, this industry. It’s returns on capital is doing great, or economic earnings are great, better than accounting earnings.” And another one, it’s the opposite. And that’s where you want to go in and dig deeper for, both long ideas or danger zone or short ideas, where you’re seeing the disconnects at a micro level.


Jake: How the Mag 7 look right now in kind of quality, since they’re so dominant in market cap and the news?

David: We were just having a conversation about the Mag 7 or maybe large cap, in general.

Jake: Yeah.

David: I said, listen, especially with the Walmart run up recently– Walmart was a focus list stock for us a while ago. We took it off the list not too long ago, because it just got expensive. And we’re like, “You know, we think there’s better places on the margin to put capital. It’s gotten rich” Here, it is making a run. I think the takeaway from our meeting this morning was, look, the Bored Apes reserve the right to get smarter. They don’t just have to pile into meme stocks. [Tobias laughs] Maybe they want to pile into Walmart, right? I think I’d rather them pile into Walmart or Nvidia than to GameStop or AMC. I think they get that too. And so, yes, Jake, the Mag 7 are looking really expensive. Some, less than others.

Jake: I’m wondering if the Citadel, Blue Whale already ate all the Bored Ape krill. [laughs]

David: I think that that’s happening, for sure. I don’t know. Some of the meme stocks, they’re still around. But yeah, you’re right. A lot of them are down 70%, 80%, 90%. That’s probably put a lot of folks out of business. And the ones that are sticking around are the ones more likely to reallocate to something that’s probably going to last a little longer. So, I think that that’s going to be another phenomenon. I think as long as there’s just this excess liquidity just continues to flow, it’s going to go chase risk assets, because that feels like the easiest way to make money, and being discerning discernment is going to continue to play a subsidiary role, because it doesn’t help you to be discerning if you’re missing out on profits. And that’s why I think people think.


Beyond Price Tags: Why Economic Book Value Matters for Investors

Tobias: David, you track economic book value against– which is, your estimate of what the earning power of the company is normalized against other kind of opportunities. So, if you have an aggregated economic book value, can you compare that to the prices that people are paying, so you get an idea for the multiple that the market’s putting on, or the premium for economic book value over? Or, sorry for market prices over economic book value? Do you track that over time?

David: Yes, we do that at the macro level too. And you’re right. It is one of my favorite metrics. Economic book values, we call it the no growth value. So, we look at the perpetuity value of the existing cash flows. And the multiple on that, the price gives you a sense of how much growth is baked into the stock.

Jake: So, you’re trying to turn it into a bond, and then what is then implied based on if you treated that as a bond?

David: Yes. That’s a great way to look at it. It’s a net of all liabilities too. So, you take it to the bond, then you add whatever other claims might be senior to an investor claim. So, that would be deferred taxes, and deferred compensation, and option liabilities, and pensions and debt, in general. And that often really knocks the economic book value down pretty low and you’ll see some big multiples. That’s just another way of measuring risk.

If profits are here today, the stock price implies they’re going to be here, that’s more risk than profits are here today and the stock price actually implies profits are going to be a little bit lower. The stocks that make our long idealist tend to be stocks that imply permanent price decline. That’s just low risk. One of the regional banks we like is Zion Bank. It doesn’t have a lot of commercial real estate exposure, but it’s trading as if its profits will permanently decline by 60%.

We were long Nvidia years ago when its price to economic book value was 0.4, and its stock price was implying its profits going to also fall by 60%. We’re like, “Oh, that’s cheap. It’s a really profitable business. This looks like really good risk reward.” Now, unfortunately, we closed a position long before it went parabolic, but we were right on the front end, it just got kind of expensive.

Tobias: The value investors lament.

David: That’s right. Exactly.

Tobias: [crosstalk], it got the fair value and then it had its run.

David: That’s right. But it’s a good way to look at things, Tobias. I agree.


Tobias: We’re coming up on the full time. David, if folks want to follow along with what you’re doing or get in contact with you, what’s the best way to do that?

David: or @newconstructs on Twitter. But definitely, yeah, best way to keep in touch with us or follow us is just check out the website. We’ve got a lot of really low-priced products that we’ve added recently where we’re selling off individual company reports, model portfolio access, and model portfolios for stocks and funds. So, we do ETFs and mutual funds. Model portfolios, some of those are as cheap as 9 bucks or 10 bucks a month. And then for institutional clients, if you want access to the data and the models and things like that, you’re looking at 1,000 bucks a month or 4,000 bucks a month on average. One seat at 4,000 bucks a month is worth probably maybe 25 analysts or more.

Tobias: Yeah, I use it. That’s how I use it too. It’s better than having analyst. It’s analyst who doesn’t make any mistakes.

David: Yeah. And you’re covering a lot more companies.

Tobias: Yeah.

David: You get ETFs and mutual funds, and you get macro research and individual company research. Yeah. No, I think it’s easily worth– 25 is probably a pretty steep understatement, honestly. It’s probably worth a team of 100 analysts. And that doesn’t even count the technology you got to build to harness all the work that those analysts would do. But yeah, we’re not making the same mistakes as humans. That’s part of the reason why we got machines to do the work. Machines are very obedient.

Jake: [laughs] And they don’t have healthcare costs that keep rising.

David: Yes. They don’t complain.

Tobias: David Trainer–

For all the latest news and podcasts, join our free newsletter here.

FREE Stock Screener

Don’t forget to check out our FREE Large Cap 1000 – Stock Screener, here at The Acquirer’s Multiple:


Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.