How To Analyze An IPO

this year after a long wait. Of course, many of them are huge, and they're going public at a stage in life UH that is much later than many of the big tech companies that are currently public when they decided to go public or when they decided to do their I p O. So I want to talk more about the I p O market on today's episode, and

to discuss this I have with me Rhet Wallace. He is the founder and CEO of triton Ai, a company that analyzes I p O s for various proprietary measures, and we're going to talk about the evolution of the I p O market as well as how to analyze an IPO because theoretically there might be people out there looking at some of these that would like to have some perspective on how to think about the value and the investment appeal of these well known companies. So, Rhett,

thank you very much for joining us. Great to be here. Thank you. Let's start with that question about why these companies are so people say coming public much later in life. So company is like Amazon and Microsoft and Apple. They essentially became did their I p o s when they were fairly tiny startups, at least by today's standards. What's changed since then eighties to two thousand nineteen such that these big companies are already produced billionaires and people have

gone on to great fortunes ever before floating a sheriff stock. Sure, well, like most things, there are a couple of different narratives. By way of explanation, what you will hear from people in Silicon Valley is that founders don't like to take their companies public because being a public company CEO is kind of a pain in the neck. And so anybody who's abut to comply with the sarbians Oxley Act and other things that were imposed on publicly traded companies as

a protection against retail investors who buy their shares. You know, if you have access to capital in the private markets, it might be easier for you to stay private and not expose your numbers, expose yourself to liability, and so forth. So almost all of the reasons that you could think of why a company wouldn't go public are regulatory there. They stem from the changes in the regulations of the securities business. And there's a long, geeky narrative that we

get into about that. When companies like Amazon and Netscape and Yahoo went public on a couple of million dollars of sales, and you know, earlier generations of companies like Intel and so forth went public, you know, really as soon as they got to revenue. That's because capital formation happened in the public market. Let's actually, let's back up for a second. Tell me about your firm and why

this is an area that you pursued. What is it about I p O s that are interesting in general, and what is your background that caused you or that prompted you to go into analyzing them and providing the service of breaking them down. Sure, well, it's I p O s are a very good example of what came after the Great Depression when the government decided to reform the securities industry so that you didn't have a big speculative bubble anymore of the kind that created the stock

market crash. And so the innovation at that moment was that securities come with data stapling, the ten k's and the ten queues, the regular are recurring reporting and disclosure so investors would know what they are buying was the great innovation after and that prompted a situation where companies, if they wanted to trade stocks with each other or have people by their shares, they had to be public.

And so companies went public much earlier. If you you know again geekily read like the biography of Rockefeller, for example, before the crash, one of the reasons he was so successful in investing is that he had access to information that wasn't broadly available. That always helps, right, So information has always been a key component of being successful as

an investor. And so the origin story of our firm is that we saw what was happening that fewer and fewer companies were going public, and that meant that more and more of the interesting companies were private. And these companies operated outside of the information regime of the Securities

Acts of the United States. The other thing that we noticed is that all of the information architecture that was installed as the operating system of the securities trading institutions was developed in the nineteen thirties, So, like generally accepted accounting principles, some people will tell you it's like, you know, the perfect information that you could have about a company, but it never existed until like Moses did not come

down from the mountain with gap company categorization, this standard industrial classification system again like the nineteen thirties, and so these pieces of data architecture haven't iterated an advanced so we're still sort of stuck in the thirties with the

way companies are analyzed. So the origin story of our company was we were looking for ways to be smart about investing in companies that were generally private companies, and the architecture that people used to look at public companies wasn't particularly serviceable to that end, so we had to build a new one. So obviously, when a company files to go public, and it files, it's s one to the sec the company engauges in the practice of putting its numbers into a type of a structure that's similar

to other public companies are identical. It then has to correct. There's a template that everyone has to adhere to. But there's still the problem of investors haven't really gotten to know these companies, and even within generally accepted accounting principles, there's all kinds of idiosyncrasies and opinions and different approaches.

And companies that have been public for a while, people become familiar with aspects of their business model and they understand the moving parts, and that just doesn't exist yet, certainly at the time of the S one filing. So when you look at an S one filing, besides the obvious the balance sheet and the income statement and the cash flow statement, what else are you looking for when you start to break down what you know looking at

these companies from the perspective of an investor. So our point of view on companies is that a company is really just a receptacle for different product lines. So our trope example is that uber x and uber Eats live inside the same company, but they're totally different businesses, completely

different product lines. So as companies go public much later in their life, what it means is that the audit of the consolidated entity disguises all of the individual operations that are happening inside of a company that might have a bike sharing you know business, and a scooter sharing business and operates all over the world in different types of jurisdictions, and so the bigger it is, the harder it is to get your arms around it unless you

can see the detail. So that's that's really interesting points. So if a company is just in the business of making widgets, then you can have some sense of like, okay, widgets cost the company this much to build, and raw materials cost as much, and labor costs as muge, and you sell the widgets for this much, and then you look at the gap between costs and the sale and

you know something about the business. But with these big companies and with new businesses that people don't understand and sort of novel business models, simply so tracting costs from revenues, it just doesn't tell you that much about the company. The architecture of a digital company is just completely different than the architecture of a nineteen thirties railroad or metals

and mining company. One of the things that you know, for again, geeks that have spent a lot of time studying how gap works and have suffered through accounting class inventory accounting is one of the things that's like really painful and the fiefold life folk kind of stuff. How

do you track the inventory of Facebook? Well, so then that gets to the question, Okay, going back to the Uber example, Obviously it's still probably mostly a car sharing company, but in many different businesses, and they do also now have several different lines and in some places they have scooters. So how do you go about essentially trying to disassemble

the business from this consolidated these consolidated financial states. So when we started out, we were looking for ways to be smart about how to tell which dog walking app is going to be better than the other dog walking apps, for example, because you listen to the young entrepreneurs come and pitch you a company, and it always sounds good,

but you don't have a comparative base of data. And so the s I C code system was no use to us whatsoever in how to categorize companies into the bucket of dog walking apps and then figure out which one was going to be the best dog walking app. So we had to design an architecture that you could get the apples and apples in the same buckets and separate them from the oranges and the grab apples and

the tangerines and everything else. And so one of the things that was fairly funny about this is if you use a sort of you know, a top down E. S I. C. Level type categorization system, and you use a word like transportation, what we found is that companies like Uber bucketed into the same bucket as zip car, right. But you look at it and you're like, okay, well, Uber doesn't own any cars. Zip car owns thousands of cars that they have to park, maintain, fuel, paint, all

that sort of stuff. So it's like, okay, even though from a a sort of narrative perspective, these things look the same, they're really not the same. So our response to this was to flip everything upside down and to look at how the thing works in terms of what does the customer pay for and what does the customer

actually get. So in this example, if you're trying to go to Brooklyn from Manhattan, you could rent a car with zip car and drive it yourself, or you could have Uber drive you there, and it just turns out that the mechanics of the system that delivers a ride versus the access to a car are totally different things. So is there enough information straight from the s ones or I guess zip car has been public for a while right to actually perform that calculation, or do you

need to go elsewhere? Well, so what's great about it is usually you don't need the s one to know like how a zip car works, because zip car tells you everything about how it works on their website. So if you flip the thing upside down and look at it like a user, it's actually not very difficult to figure out how these mousetraps work. Now, one of the things we've talked about, because we've talked on air on TV before is sort of non financial statement characteristics of companies.

So people are interested in things like, you know, just the level of transparency period, structural things like voting control. What are the other things that you look at when you analyze a private company or assumed to be public company beyond just the numbers? Sure, well, one of the things about GAP is that GAP translates everything into dollars.

So like the numbers, you see on a GAP pan L are all dollar denominated, but most of the numbers that are the most interesting about companies aren't dollar denominated, like how many customers and how much do they pay? And how long do they stick around? And where do I get them from? And things just how many cars they might have an inventory, for example, right, And so

there's a big debate that you could read about. Matt Levin here is very articulate on the subject about non gap reporting, and some people get kind of religious about this and say that you shouldn't report things that aren't gap because then companies aren't comparable anymore. But the problem is that if you only have the P and L, like for example, if you were looking at the Snap I PO and you saw that Snap lost a billion dollars in the trailing year, you don't know very much

about Snap. But the intuition that people have about that company as well, I know my teenager can't put it down, But you don't have the statement about how many teenagers and how long they stick around. And what you definitely don't have is the statement of how many advertisers and how long they stick around, and how many salespeople it takes to go get those advertisers to pay you and

so forth. So to us. Again, the numbers that matter are the numbers that help you calculate the mechanics of how the masse trap works, and those things are often not disclosed in an US one at all, and you need other ways to go get them. What do you think you know? It's interesting you mentioned snap And maybe this is a slight tangent or maybe not, but it feels like there have been efforts with a lot of these Internet companies to essentially standardize some of these non

financial metrics. So m a use monthly average users is a popular way to compare them, but it feels like the companies are really pushing back against that or like to and they want to create their own bespoke ones and they say, no, no, no, you can't compare our m a US to facebooks or our d a used. Twitter recently announced that they were going to for the first time start revealing d a use daily average users.

They're no longer going to report monthly average users, but even their d A numbers, they're calling them m d a U s monetize herble daily average users to distinguish from users who they probably are gonna make any money from so their m d a us are going up anyway. The point is, what is your view on this. Do companies have an incentive to sort of try to break out of the standardized comparable numbers and come up with their own sort of vanity metrics that are always going

up into the right? Yeah? I think you know, the world doesn't divide on this, Like people don't like accountability, right, so if you don't have to be accountable to particular metrics, you'd rather not. One of the things that's interesting about what's happened in capital formation right now is that private company investors have access to all this information, all the real information, not the fake you know, monetize herbal daily

average users that you know. They can see all of that sort of stuff, and they have a real sense of how those mechanics work. Once you arrive in public company lands, many of those numbers are not disclosed anymore. So you find a situation where as capital is forming around these companies, the investors that put up the money have much better access to information, so more transparent situation, but an a liquid situation, and then you trade liquidity

for transparency in the sense that the look. Investors don't really get to learn any of the you know, the way that the mouse trap works, but at least they can sell the stock. And so that's the trade. As far as your question about the standardization, and sorry to go on so long, using like an ad supported companies metrics to analyze the subscription business is just not very helpful.

So like engagement metrics, for example, people ask us about our engagement metrics, which I always laugh because I think engagement is bad. We want our users to figure out the answer in as little time as possible because I'm not trying to serve. And add to that, right, so

each company is different. This is what we spent years doing is developing an architecture so that you can understand what kind of company you're looking at and look at the appropriate metrics to do So, going back to what you were saying about the trade between liquidity and transparency,

we had a recent episode a few months ago. We were talking to um a VC and he was arguing that one of the things that made this period in market unique is that whereas in the past, uh illiquidity was a penalty for a company and a private company had to offer a bigger premium to get um private capital because that was more locked in. These days, people are paying a premium for access, in his view, to

a liquid companies. Maybe they didn't want to have to mark their books day to day, or maybe there was some sort of prestige value of being in a lift or an uber that caused people to overpay. Do you see that that the sort of traditional discount that would have in the past come along with private equity stock has flipped. So I'm gonna give you two answers to that question. One, just to verify with data the claim

that people pay a premium. Over the last five years, the I p O s that we've looked at tend to trade up in the first half of the first year that they're public and then in general trade down again below the ip O price. Right, so public public market investors. And that's not just that that's over the US five years. So it's not just we're not just looking at effect and it's not just DOLLI Bober or whatever.

It's you know, a hundred and fifty odd transactions. And so what happens is as a capital markets matter, these things come out. They you know, the I p O prices, it begins to trade. You get the famous pop which some people love and some people hate, and in general, these things trade up for a while and then large amounts of shares are unlocked and people stop paying attention and they change the channel and they look at something else, and then they trade down. And so it's definitely true

that private market investors have paid a premium. Like the guys who bought the last round of those deals could end up underwater if they didn't sell, but they could sell, so it's unclear if they've been penalized for paying that premium because they had a moment where they probably could have made made a profit on the trade. But in general it's not a good trade for the broad base of shareholders. So that's out of number one. But item number two, why do people pay a premium for this?

And the answer we think is because if you want to invest in growth companies, you have to pay the price. And so if you are a long only manager who's managing a growth fund, who has a carve out that allows you to invest in Uber Lift, whatever, your ability to set prices very limited, but you want to participate in those deals, and as more and more capital has flowed into this place. What happens when there's more demanded supply,

prices go up. So it's kind of like it's a function of the fact that, even if we're just looking in public markets, we know that the growth factor has done extremely well in recent years, and that's just even more exacerbated in the ultra high growth private area. So that could explain at least part of this premium. Sure.

I mean, if you were a growth investor in you know, the ninety nineties, you would be investing in companies publicly that we're young, and you'd be buying you know, Amazon or you know Yahoo or the globe dot Com, right, you know, you buy the good and the bad. But you get to do all of that in the public market. Now, all of that capital formation and all of that value appreciation happens in the private market, and the guys with

large pools of capital want to participate in that. But what it's also done is created a situation where larger pools of capital, the vision funds for example, have formed

to participate in that trade. I'm glad you mentioned the I p o s prior to the bubble, because obviously everyone knows you'd be rich if you had bought into that Amazon i p O, but you would have lost all your money if you bought into the Globe dot Com i p O. People bemoan the decline of I p o s for precisely because they have memories of Amazon and Microsoft in their mind, and they say, well, the stock market used to be this avenue where people

could make a lot of money investing in these companies. Now that's closed off to anyone who doesn't have access, but of course there is. It does seem like there's a lot of hindsight bias because most of them, most companies are more like the Globe, right. Sure, well, Mary Meeker has a great statistic that was in her deck for a long time after the bust that two of the companies that went public during that moment in our

culture created more than the returns. So it's just so the vast majority of them were total flow totally adds. You know, well, if you were in the two that compensated for you know, the negative jacurb. Right, So it's the vast majority were a bust and more money was lost than made in aggregate. Right, So you had to be very very picky to not be one of the losers is the decline of the I p O a

bad thing. It's bens. I mean, if you were a retail investor and in hindsight you're totally convinced that you would have absolutely put your life savings into Uber if you'd been able to buy it, you know, five years ago, then it's a bad thing. But one of the reasons that the bar has been raised so much for companies to go public is to protect retail investors from themselves. Right, Retail investors fueled a lot of the bubble that happened.

There are other structural reasons why the Internet bubble happened, but there was a huge amount of demands in the same way that people now spect laid in cryptocurrencies and other things like that. Because it was perceived to be an easy buck, people are always gonna look for actions.

Let's uh talk about Okay, So as of this moment, when we're recording and we don't know any day now, we could get s one filings from some of these companies that we mentioned, so Uber and Lived and Slack and a bunch of others that we could get for the first time public data on these companies. So when these come out. What are going to be the first things that you look at and what should people listening

at home what should they start to look at specifically? Um, well, us first, our our system is just to take it apart and do the sort of fifteen point inspection on these things. So does the math makes sense? Like does this company make money? Is one of the things that we've talked about, you know, on TV before. There are times where will put companies numbers into our model machine and we'll look at it and see like, jeez, there's

no setting of the model that produces a profit ever. Right, So that's a really low low score as far as the earnings power of the company. But we also look at the management team. We look at the founder. When you say look at the management team, were okay? Uh paused there for a second. So how do you score in theory a manage the quality of a management team. They're the things that you think that you would think to do if you wrote out a rigorous system, like

have they done it before? How long have they worked together? Have they worked in places that you've heard of before? Were they successful there? Did they go to schools that you've heard of before? Right? Do they have advanced degrees, you know. And then when you toggle to the founder aspect of the management team, sometimes you see total control of the founders, which tends to be great because they're

highly invested and have a lot of skin in the game. Sometimes, you know, like for example a Twitter, you see like the company is totally post founder, and that means that the management team has economics that are heavily weighted towards the upside, but doesn't have a lot of pain associated with the Dow Todd So founder power is very important. The quality of the board, the quality investors is interesting. How famous is it? Like faym and buzz is one

of the things that we score. Companies that nobody has ever heard of, you know, do do less well than companies that are well known. Okay, so you have all these factors fifteen different We have fifteen different scores that will roll up into the summary score. Fifteen different scores, and so in your experience the aggregate, higher scoring companies do better than the lower one way better. Otherwise you

wouldn't have a business or totally right. But shockingly, because there are times where we get the score because you know, we see it when it comes out of the machine. We look at it and we're like, man, that can't be right. So it's always interesting to us, like maybe this will be the one that we we you know, have to rebuild the whole system one. I think here's sort of my final question, or the key question I have is do the do high scores say you should

invest in this company? Or is it if you invested in every company with high scores and shorted or avoided all the companies and low scores, would that be a superior strategy? You know? Do you see what I'm Do you see? Like? Yeah, so the aggregate trade is always better unless you are so good that you can sniper shot the singular winner. But that's incredibly hard to do.

But the premise of the scoring system is essentially that on aggregate you'll strip out a lot of noise and be much more likely to have a winning portfolio of I p O s with the higher scoring companies. Not only that, so that's certainly true if you're an institutional investorent. Most of our customers are institutions that buy at the I p O price, and so the returns are you know, three times better if you buy the high scores than

the low scores. But if you buy the first trade, if you're a retail investor buying high scores versus low scores, this is the difference between making money and losing money. Got it. Well, it should be a very interesting year for I p o s as mentioned, and looking forward to seeing over the coming years how your scores do. I think we have a week or two before it comes and then well I'm on vacation next week. It's

a good time for it. Hopefully, I'm really hoping I don't miss all these, but then I'll be back in hopefully. I think you're good six weeks. All right? Great Rott Wallace of Tried and Ai, thank you very much for coming out Odd Lot. Thanks for having me here. Well, normally I would do a little outro with Tracy here and we would talk about what a great conversation that was.

But I actually think that was a great conversation and I love this topic and I'm looking forward to all the I p o s this year and seeing how they do. So this has been another episode of the Odd Lots podcast. I'm Joe Wisenthal. You can follow me on Twitter at the Stalwart, and you should follow our co host on Twitter even though she wasn't here, Tracy Alloway at Tracy Alloway and you should follow our producer

on Twitter tow for four Heads. He's at four Heads t as well as the Bloomberg head of podcast, Francesco Levy at Francesca Today. Thanks for listening.