New Constructs' Friday Webinar: Intelligent Capital Allocation 9 June 2023

Thanks folks for joining us. We're so happy that you could be with us this Friday. Today we have a great group with us. Myself, Kyle Guskey, Jacob McDonough, Lee Manetta Kohler will be your hosts today and look forward to discussing a bunch of different topics. Before I get into the agenda, here are our disclaimers and disclosures. Our agenda today is, as usual, to make sure that we get to the topics that you want to talk about, and we are going to make sure that we hit the topics that were brought up on Society. Wanted to remind you to please use the Q&A feature. We want to get to your questions as you have them. Don't worry about holding your questions for a particular time. We'd rather take them right away. Out on Society, you can always get the replays and the slides, our disclaimers and disclosures, and our privacy. Policy, so please don't hesitate to look through those as needed. A ton of research came out this week, so if you go out to newconstructs.com and click on research, you will see that like last week when Kyle and the publishing team put out a ton of work on the S&P 500 trends, this week it's all NC 2000 macro trends. The list is all here with all of the links both to the research that's available to our current members and also the free versions, which are abridged versions of the more in-depth research that the members get. I did want to put all of the links here for those folks who are not current members so that you can be sure to check that out because it's great work. In addition to the NC 2000 Macro Trends, there is Sector and Industry Fundamentals report from the first quarter, as well as Most Overstated and Understated Street Earnings. I'm going to hand it over to Lee in just 1 minute to go through the interesting headlines. As you can see on the right-hand side, the rest of our agenda today— Jacob is with us to talk about the analyst training program, which is a bit of a behind-the-scenes look on our analyst team work, what sort of training do they have. Then Kyle is going to do a DCF of a firm which is in the news this week, which should be interesting. And then as usual, we'll get out to society and talk about the topics that you all brought up this week before rounding it out with stock picks. So with that, Lee, I would love to hand it over to you for interesting headlines.

Thanks, Tam. Up first is the Bloomberg New Constructs True Earnings Index. We let you know earlier that earlier this year, we formed a partnership with Bloomberg to create some new indices. The first one is this Bloomberg New Constructs True Earnings Index, and it is still on schedule to launch this month in June. What that means is that they'll be publishing the index itself, not yet any ETFs or funds based on that index, but we are on schedule and gearing up to produce an ETF using this index, and that will be available to invest sometime later this year. So we're very excited about it. It's based on our core earnings and earnings distortion data. Bloomberg did a bunch of backtest work with the data. We've got great alpha and we're excited about the performance of the fund. I know that I'm personally looking forward to putting some money into it. The next thing I wanted to talk about is the SEC crackdown on crypto exchanges. They brought civil cases against Binance and Coinbase this week and at the very end of last week. I think that the SEC has made it pretty clear that they think that crypto and the kinds of products that Binance and Coinbase are offering on their platforms are securities, and that that means that these platforms are operating as unregulated exchanges, so they are illegal. According to the SEC, Coinbase is down 86% since their IPO. The S&P 500's up 4% over that same time period. We've had Coinbase as a— we've had it as a zombie stock and as a danger zone pick. And on the— have we had it on the focus list short as well?

Uh, just I think danger zone and focus list. I'm not sure the zombie, because they've actually generated—

they've got a lot of gas.

Yeah.

Yeah, that's fair. But I don't, I think the news, it's also not coincidental that when we first put them in the danger zone at IPO, our analysis found that they'd have to be the largest exchange in the world, not the largest brokerage, not the largest platform. We compared them to other exchanges because that's exactly how they were operating and the money was coming in similar to an exchange. So it's not entirely unsurprising to see this happen. It further adds that regulatory risk to an already risky company. And even though it has performed, you know, down 86% since the IPO, it's still overvalued, which is why it's on our focus list short there.

Crypto was the hot topic in the recent past, and I think that the SEC has had this opinion for, for a while. It's a little disappointing that they've decided to keep quiet about it until the space blew up on its own. then the SEC comes in and says, see, we told you so, or our opinion is that these things are illegal exchanges and that they need to be regulated more closely. It's a little too late for that to be very effective.

Yeah, I was wondering, I wanted to ask, do people disagree? Are reasonable people disagreeing and saying, oh, no, no, they're not securities. This is ridiculous what the SEC says?

I don't think so. I think that the only place where we're seeing Arguments that they're not securities are from the lawyers who are working for these companies who are trying to defend them from these cases.

Okay.

Perhaps crypto itself is not a security, but these platforms offer like far, far, far more than just the ability to buy and sell crypto.

I think a lot of analysis focuses on not the big ones, you know, Bitcoin, Ethereum, but some of the other smaller products that are available where, you know, you pool your money together and you get a yield based on that, which by definition meets a lot of the legal requirements of a security. A lot of what trades on Coinbase would be securities.

The SEC's also interested because it looks like Binance is moving around quite a bit of money. Because these things are not being regulated as exchanges or brokerages, they are able to do all kinds of things with customers' money that they wouldn't be able to do otherwise. Binance has been moving sometimes $1 billion a week through banks, including Silicon Valley Bank and others. Right. So I think they're interested in seeing where the cash is flowing to.

Always curious. That was a great comment. With no military to back crypto, I'm surprised it has value in the first place. Given time, maybe. Yeah.

You know, I think crypto was really built on hype and everyone was interested in it because it was going up and going up so quickly. I think that there's some, there is some very interesting technology underlying it, especially in the blockchain. And in some ways it's unfortunate that that's tied up so much in the crypto hype because I think that it makes it hard to use it in other ways.

Yeah.

It makes the good stuff hard to find.

Yeah, it's, it's too bad that this has turned into the killer app of blockchain. It would be interesting if there's a perhaps more socially fruitful one.

That's right. Yeah, no, we've, we've allocated a huge amount of capital as a society to crypto over the last 5 years that I'm pretty sure we could have used more effectively in other ways, higher return activities.

Fair.

That's fair.

That's what I've got on crypto.

Awesome. Well, then we will click over here to Jacob, I believe.

Yes, I want to talk about training. I'm Jacob McDonough. One of my tasks at New Constructs is to help train new analysts that join the company. I enjoy the training process because New Constructs training program is a big reason I joined the company in the first place. The company does a Excellent job, devotes a lot of time and resources to it. Classroom training is the first key piece to the training process. It takes about 2 weeks, and David Trainer devotes time out of his schedule to run the classroom training for those 2 weeks. So when your CEO is not just involved but taking time out of schedule to run a portion of the training, this shows the company's commitment to it. Analysts are given books to read beforehand, which might stretch 1,000 pages. Somewhere in that ballpark. Training covers topics ranging from culture to why markets exist, what our role our company plays in it.

Hey, Jacob. Yeah, this is Lee. We have a comment from one of our listeners that it's a little hard to hear you. I don't want anyone to miss out on this. Jacob does an awesome job running the training program. It's an absolutely critical part of what we do.

All right. How's that? Testing. Is this a little better to hear?

I think it is a little bit better. Yeah, thank you.

I'll try to speak a little louder as well. Our training, the classroom training portion of it, covers topics ranging all the way from culture, why markets exist, where new contracts fits in the markets, all the way to how do you calculate invested capital and NOPAT. So very wide-ranging. Next is systems training. This is the portion that I lead. We have experienced analysts working side by side with the new analyst to help get that person exposure to all the different types of companies we cover, as well as, as many different variations of disclosure that we can generate for the new analyst. Repetition is very helpful here, especially with an experienced analyst working side by side. But importantly, we have an internal website that is an excellent learning tool for employees. as it stores examples of disclosure, definitions, explanations on why we treat things certain ways, explanations on accounting treatment or accounting rule changes. Another interesting aspect is that we include software engineers in the early part of training. Communication between engineers and analysts is a key priority for our company. It's rare for companies to have expertise on both sides of that situation, both on the software engineering side as well as the deep finance knowledge. That's a key thing we focus on is making sure both sides of that equation can communicate with each other in a good way, but also know what each other are doing. So we include engineers in the early part of training.

Jacob, we still— we're getting some more comments about people still being— having a hard time hearing you. I wanted to chime in though and say that one of the pieces of magic that allows New Constructs to do what we do and to use machine learning effectively is that we get analysts who are experts in what they do in building models, folks like Jacob who are experts at financial disclosure, and folks who are technically capable software developers who can help us build the kinds of machines that we need to build to build these models automatically and get them in the same room talking to each other, sitting around the same screen, solving problems together. And in order to have those conversations effectively, we have to be able to speak a common language. And that means teaching engineers, teaching software developers a little bit of finance and showing them what analysts are doing and try to explain to them why. And, and having the analyst side understand a little bit about how the technology works.

And that almost never happens inside software companies. That is the holy grail that so many software companies work towards that level of integration, but it almost never happens. It's incredibly difficult. You guys make it look easy, and no, it's not easy.

No, I've been to, you know, I think other larger companies have, have tried to solve the same kinds of problems that we're solving and have spent a lot of money on it. Financial analysts on Wall Street are generally not super enthusiastic about machines taking over some parts of what they do.

Sure.

I've seen technology teams with 30 and 40 people teamed up with, in some location that's not New York, teamed up with analysts in New York. And they're trying to automate even just simple parts of their processes. And the finance people are totally uncooperative. One group of people I talked to a few years ago hadn't spoken to their analyst contact in over 6 months. They had tried to reach out to ask for feedback. So people were building products with no real guidance around what it is that it needs to be able to do. We literally sit side by side around the same screen. It absolutely makes a difference.

Pair programming with, with an analyst is fantastic.

Yeah. Yeah. Not all day, every day, but during those critical moments where we need to get, we need to get people together to be able to talk. They need to be able to understand one another. There's not a lot of people out there that have both the technical skills and the finance knowledge to be able to do these things well. So our training program is really critically important for us to be able to talk to each other effectively. Jacob, you want to give that microphone a try again, see if we can hear you?

I don't think it's going to work this time. I, I'll test one more time. How's this sound?

Still, still pretty muddled.

All right, I'll let you lead the way. Sorry about that.

That's okay. Yeah. The last thing that we do is, is, is part of training is, you know, like Jacob said, we have a classroom training that's taught by David. I think it's amazing that we get his time to bring people up to speed about why the company exists and what we're trying to do broadly. That's critical to everyone being on mission together. Jacob does an awesome job teaching analysts what they need to know. We have an ongoing mentorship program for analysts as well. We team up new analysts with existing analysts so that they have someone that they can ask questions to who's an expert. There are all kinds of disclosure variations out there in the world, and analysts need to know how to model those effectively. There's really no substitute for practice on that kind of thing, and mentorship really helps when you're You know, build it. I always say building profitability models is a lot like shooting free throws in basketball. Someone can tell you how to do it and you can do it a couple of times, maybe you can get lucky or unlucky, but the only way to get good at it is to just do it a lot. And the reality is that companies are moving, changing the court all the time. So you gotta get good with understanding what those things look like. Finally, we've got that analyst reference library. It's an internal wiki that we use. To collect information about unusual disclosure. It's a critical part of the training program. Jacob uses it as a reference library. It's thousands of pages long, which maybe sounds big and unwieldy, but it's easily searchable. It's analysts' Bible for understanding how modeling works, why it works that way, and all the possible disclosure variations that we've seen, which are anything that's possible has happened. You know, we've got hundreds of thousands of filings that we've looked at and built models from. And so the reference library is a great way to understand what we've done in the past and why. We have a deep writing culture at New Constructs where we like to write down and document everything that we do. And the reference library is a critical part of that. That's what I've got to say about the training program. Sorry, Jacob's mic didn't work out great right there, but He does an amazing job of running a training program. All new analysts turn to Jacob for help. He turns them into experts in relatively short order, and they all love him for it.

Are there any questions, folks? Please don't hesitate to use that Q&A tool or the chat tool, whichever works best for you. And yes, thank you, Jacob. I know it's a metric ton of work that, that you guys get through in short order. It's an impressive, impressive Program. All right, shall we move along to Kyle?

Let's do it. Affirm was in the news this week with an announcement of an integrated or expanded integration with Amazon Checkout. You can start using some of the, I think, adaptive pay with Affirm. It's not the first time they've made headlines with Amazon. I think back in 2021, they announced that Affirm would be available on Amazon, and the stock saw similar bounce in price for like the week, kind of fades as we go on. And so we wanted to take a look at what the valuation implies and is that expanded integration with Amazon already baked in. And with Affirm being a danger zone pick and zombie stock, the answer is yes, the expanded integration with Amazon and much, much more is already baked into the stock price. So I'll take the screen here. And dive into the DCF of exactly how we quantify that and what it looks like. Let's just start here.

Kyle, maybe everybody already knows, but could you say a little bit, they are the ability to pay over time?

Yeah. So the, you know, big catchphrase a couple years ago, buy now, pay later. That was what got hot with the buy now, pay later installment loans. Some of them could be interest-free, some of them have interest, but the ability to split that payment into multiple Payments. If that doesn't sound unique, it's because it really isn't. There are plenty of companies that offer this. We've since seen Apple being one of the bigger ones integrate that within their own Apple Pay system. And that was one of our original points in the first danger zone we put in a firm, or we wrote on a firm back in October 2021, was that essentially this was a byproduct of the current market. People were chasing growth. The firm was exhibiting high revenue growth, growing losses on the bottom line. But in that quest for growth, money was being thrown at companies like this. But in the end, they are undifferentiated buy now, pay later installment loan business. And so that shows up in the ratings. We've got bottom quintile, negative 41% ROIC, valuations all look dark red, overall rating of unattractive. And so we can look at the DCF model and see what is baked into around a $19 stock price. I think before this Amazon announcement, it was in the $16 range. There's been a decent bump. We'll see how long that one lasts because the actual value of the company is much lower in even optimistic scenarios. So what I wanted to look at here, we've put together previous scenarios with Affirm because obviously they've been in the danger zone before. I used some of that and some of the industry growth rates on our forecast page and built out, you know, what do they have to do to justify the current price of that $19 a share? In the forecast page here, that is my optimistic scenario. In that scenario, we assume they can increase margins here to 8%. As a shortcut, I don't use any cash tax rates, so the pre-tax margin is the after-tax margin. Just makes it a little easier to run through these scenarios. So if we give them credit for 8% NOPAT margin, for reference, their current NOPAT margin is negative 78%. So that is miles away. But if we say 8%, and then they need to grow revenue by 33% compounded annually through 2030, we looked at the expected industry growth, that's around 26% through 2030. To justify the current price, Affirm has to— we can look at the DCF review. They have to go 8% margins, 33% revenue growth out through 2030, and that is just to justify the current stock price. So anything less than that means the stock is worth less. They have to do more than that to be worth more than the current stock price. And so you can see that in this scenario, we've got that revenue growth rate, 33%, got that NOPAT margin of 8%, and then the shareholder value of around $19 a share. Key point in this analysis, we're actually being super optimistic and we're not increasing invested capital. And so the ROIC of the company increases in this model or in this scenario from, what was it, -41%, I believe, to positive 37%. I think over the past few years, their invested capital has grown something around 46% compounded annually since 2019. For being super optimistic in this scenario. And you can see what they have to do to justify just the current stock price. $13 billion in revenue, over a billion in profits for a company that, like I said, has a negative 78% NOPAT margin right now. And it's only gotten worse since they've gone public a couple years ago. And so then the logical next question is, okay, well, what could it be worth? How bad could this get if they don't Grow by 33% a year and have 8% no-PEP margins. We did look at two other scenarios here, a similar neutral scenario with keep that 8% margin. I think it's actually double what Square, now called Block, has achieved in the past. 4% was the highest margin Square and Block has ever achieved. So it's double, make it 8% consensus revenue growth in years one and two, and then. market industry growth, 26% a year out through 2030. We looked at that neutral scenario and we see that it actually implies that the company would be worth just $10 a share today. And so that's 47%, 50% almost downside, even if they grow 26%, 8% margin. And we've got that $10 a share, which would imply, or which would require 23% compound annual revenue growth, ROIC up in the 20s, 20% here in this scenario. Still highly optimistic expectations based on a currently unprofitable and getting less profitable or greater losses business. I wanted to look at one more scenario. If we say 4% margin, which again was the highest that Block had ever achieved. And give them credit for consensus revenue growth, and we'll just push that revenue growth consensus from year 2 out through the rest of the scenarios. So if growth slows a little bit below average or the market projected, some competitors come in, Apple Pay comes in and takes a little bit of the growth out of the sales there. We can see what that looks like in our pessimistic but still optimistic if we actually look at the underlying growth scenario. And we find that in that third scenario there, Affirm would be worth right around $3 a share, 80-plus percent downside from current price. So when you see the headline Affirm is expanding with Amazon, you might think, oh, that's great news, this is a growing business, that'll help them out. But in reality, that is already priced in and then some, especially when there isn't really any Quantifiable numbers that they provided. It was they'll expand reach, they'll expand customer base, but there's no numbers they can point to that say exactly how much this will increase their business or grow their business. The headline here could get people to buy it when in reality this is a focusless short company for a reason. Even in a kind of optimistic scenario where our margins improve from 78 to 4, ROIC goes from negative 41 to 7%. You're looking at a stock that's worth 80+% less than it's trading at today.

Yeah. Kyle, is there any sense that the Amazon business will be more profitable for them than their existing businesses? It doesn't seem that it's all that different. There's just potentially more volume.

It's, it can increase volume for sure. And we looked at it in the past when they first added, were added to the Amazon platform, you know, it can increase sales. But ultimately, this is a business where you're providing installment loans. It's all going to be about the rates you charge and the rates you can charge. And when you've got other companies out there competing, offering it for less of an interest rate on that payment, means less margin for the companies to take. And you end up with multiple companies that are unprofitable. That would require, you know, the only real way to offer this as a long-term product is probably similar to what Apple's doing, where it's a feature of a larger Apple Pay, where they're capturing much more than just the installment loan portion of it. So in this case, volume has actually been a problem for Affirm, because like I said, with the profitability of the company, we've seen NOPAT margins— Negative 15 was the best ever in 2020. And then we've seen negative 39, negative 61, and negative 78. But over that time, revenue has gone from $200+ million to over a billion, $1.5 billion. So as they've grown, they've gotten less profitable and this could be another similar situation.

Sure.

It's generally easy to grow revenue whenever you're destroying value while you do it. Customers are happy to take you up on those offers.

Yeah. I mean, if you can give me an option to split a big payment interest-free, you know, People are going to take it, but doesn't make it a good business or investment. So I think that's what we're seeing with Affirm.

Yikes.

We have any questions on Affirm right now, but we did have a question for Jacob and Lee about the analyst program and whether or not that might be something that we could turn into a training program for clients. And I know that Jacob has actually been kicking that idea around a little bit, so I wondered if you guys would like to comment. On that question.

Yeah, it's a great question and something we've absolutely talked about internally. I think our training program is a big strength of the company. We're, we're very good at it. We have— we once years ago had a customer come in and participate in the training program in person. It was a great experience. Jacob is working on putting together some courses in the Society maybe, and other places that would serve online courses like you can get through a place like Coursera with some of the parts of the training program. We haven't figured out exactly what that's going to look like yet, but we're talking about it and we're interested in it. Much of what we talk about is already in the education section on the website. We have huge amount of resources there for customers to look at. If you haven't spent time reading through those things, those are— were thoughtfully put together. Are clear and are very detailed. They were built from the training program as well. It's the very detailed part.

Yeah, it's the very detailed part that's hard.

Right?

Yes.

They're super clear, but wow, they're, they're detailed. That's right.

All right.

Please, guys, don't hesitate to ask questions as they occur to you. We're gonna go ahead and jump out to society next. I think we wanted to start with AI.

Yeah, I wanted to talk about this one a little bit. I thought it was a great article that Robbie found. And we had some, some excellent comments from some of our users. I think Roger Green in particular pointed out that we should be, you know, understand where Marc Andreessen's coming from and make sure that we understand that he probably invested billions into this. He made huge amounts of money on, in the crypto world. and wants to, intends to make, and probably will make tons of money in AI. But I wanted to talk a little bit about AI will save the world and a little bit about the fear of AI that's going on as well. You know, we've worked with machine learning and AI here at New Constructs for a number of years, and I have 2 broad thoughts about it. One is that it's extremely powerful and it is amazing What it, what it can do. We have, even with pre-AI machine learning things, achieved things that if you had shown them to me fully developed as a new— whenever I started out in a career in finance, you know, about 20 years ago, I, it would've absolutely blown my mind. I was spending so much time reading through 10-Ks and 10-Qs. And what is possible now is, is absolutely Fantastic and powerful. But on the other hand, what machine learning and AI are good at is taking training data that you've given them and producing, generally speaking, believable generalizations about that data. What that means is it can take a large number of income statements and balance sheets and notes about operating leases and employee stock options and pensions generally. And if we do the same sorts of things, it can help us collect that with that data. It can help us collect that data and model it accurately. Super simple example, if there's revenue at the top of an income statement and it's called revenue, we can— machine learning and AI can put that in the right place pretty much every time. You probably don't need machine learning or AI to do that. But what it, what it is really good at is picking out specific paragraphs in the notes that are probably of interest. That's what our analysts spend their time doing. But what we've— but what we have found though is that For financial statement analysis, that disclosure is always changing. Companies are aware of the kinds of things that people are looking at, and they're aware of the kinds of things that other companies are doing. So they're constantly changing their practices to take advantage of what's possible and what other companies are capable of doing. And that means things are always shifting and people are always trying out new things. And AI and machine learning in our experience so far is only, only partially helpful in that kind of experience. AI as a tool, you still need analyst experts to understand what's happening in disclosure. And whenever you're working with data in finance, you're often looking for outliers and unusual situations. We've got a sort of a bell curve, right? Like this. When you're an investor, you're interested in these things out here. The highly overvalued or highly undervalued companies. Those are the best investment opportunities. And then you're also interested in models that are outlier models, unusual things that are happening. And those are the things that the AI is worst at. We're not yet close to a place where AI is going to be able to solve those problems. So I think what AI will allow us to do is take all of the more mundane work off of analysts' plates, at least in the space of finance. This is probably true in other areas as well, but we're still going to need people to provide clear and accurate training data. And the kind of training data that we need is always changing. AI will almost certainly get better at helping us get those new situations correct as well. But as a generalizing tool, it's still not going to be great at new, radical new scenarios.

Not yet.

Not yet.

Maybe not this lifetime. The robot uprising is probably not quite here yet.

That's right. I think that Mark Andreessen's right. It's a tool. We can use it in a variety of ways. And for finance, the one I know most deeply about, I think there's still a huge amount of ground that we need to cover. We often say here internally, when you think you're 90% of the way done, you're halfway there. And I think my experience with AI is that we're not even at 90% yet. I don't even think we're at 90% yet. So I don't, I don't even know that we're halfway there. I think we've got, we got a lot of ground to cover still, and it will be hard.

It just gets harder the further you get along down the problem. It doesn't get easier. It gets seemingly harder and harder. Yeah, exactly. I don't know if it's quite exponentially harder, but it's harder.

Yeah. And I think that it's going to be, I think I see a comment there from, from Kyle that AI is useful in biotech and genome technologies. I think that's absolutely right. It's used, it's very useful in finance too. Like I said at the beginning, you had showed me what AI can do today, 20 years ago, whenever I started out doing this, you would have immediately blown my mind. It can take 80% of the work off of the plate of an analyst and allow them to focus on the 20% that's actually the most interesting. That stuff is amazing. It's, you know, I've got to watch it slowly develop, so I didn't get that big reveal.

I know we just have 5 minutes left. Any other comments on AI, guys, before we move on to our last few comments from society today? Don't hesitate to ask questions as usual. If things come up afterwards, just go ahead and head out to society and ask questions there as well. Kyle, I think there were a few topics that you wanted to hit. Charles Schwab.

First one, we've gotten this question a lot with the TD Ameritrade-Charles Schwab merger transition finally taking place about whether our research is on Charles Schwab. Right now it is not. It is only on the TD Ameritrade platform. So if you've been transitioned over to Charles Schwab, you wouldn't be able to access that. Unfortunately, at this point, our best option for you is to reach out to Charles Schwab, tell them you would love to have new constructs. They're gonna listen to their clients much more than they would listen to an outside company. So if you reach out to them, whether you have a specific contact or their general contact us page on their website, reach out and tell them you'd love to have new constructs on Charles Schwab, just like it was on TD Ameritrade.

We would love to be there. And I think there was one other. What was it? Earnings distortion.

Yeah, this is on the earnings distortion score. Just wanted to bring this one up. Jerry puts a nice explanation on it in a different, less technical way. I love this one.

I love this explanation because it's very visceral.

Yeah.

And so, you know, we think of earnings distortion, you know, the likelihood that the company will beat or miss. the next quarter. And with the thought being, you know, unusual items can't persist forever. So if you have a lot of unusual items in one quarter, they disappear the next quarter. If those expectations were built on those unusual items, you're going to either beat or miss whichever way it was. And so that earnings distortion score is a way to look at how, how much unusual items were there and whether that could lead to a beat or miss moving forward. And you can get earnings distortion scores for All the companies have under coverage, that's right atop the ratings table if you're looking at tickers. And so you can find that on our website, use it as a short-term rating, not the long-term stock rating.

Thank you, Kyle. There's another question about the TD Ameritrade Schwab thing. So if you still have your TDA account, how do you get to new constructs from your TDA account?

It would be on the individual stock, ETF, or mutual fund pages. There's a column on the right side, unless they've updated the user interface since I've last seen it, a column that has analyst reports. And we can actually send— we've got a link on our page that has a screenshot of what it looks like, so we can send that out over Society as well.

Okay, that sounds awesome. And before we head over to Stock Picks, one more question, Kyle, for you or Lee on the ETF that's coming out. The question is, is if a stock qualifies as a good investment, but the technical analysis shows it's continuing to fall, will the ETF invest in it?

Sure. The True Earnings Index is based on our core earnings and earnings distortion data, and it's specifically looking for stocks that have the least earnings distortion. So we're closest to zero on earnings distortion. There's some additional overlays to make sure that the stocks that meet that criteria aren't bad investment opportunities for a variety of reasons. But the technical analysis is not a meaningful part of what is happening in the index.

Well, Kyle, as usual, you've got—

Its performance is great though, by the way. The ETF.

Thank you, Lee. Sorry to interrupt you there.

No, I wanted to throw that in.

Okay, good, good.

Kyle, you get 1 minute as usual. I'm so— I'm sorry.

Yeah, not a problem. These are— we can make these quick. I always want to highlight 2 big movers in the past week or so. Blue Apron, zombie stock, danger zone, down 18% in the past 5 days. They announced a, I guess, 1 to 12 stock split to get them back above that dollar to remain listed and trading. Down 91% since our original report. Wanted to feature that as a big mover on the danger zone side. And then the next one on the long side being Ford, up 12% over the past 7 days. Versus the S&P up 2%, 16% year to date versus the S&P up 12%. And then I think as a general note on some of these stock picking success, check out the post on our site about the SumZero rankings. It's a group of, I think, 16,000 analysts and buy-side group that all post their ideas. The June rankings have come out and we've got a lot of number ones there. And so we're proud of that. It's been over 2 years now that we've been ranked at least number 1 in 1 category, and oftentimes in multiple. So it's great to see that our stock picks, those are the long idea and shorts danger zone picks, are having the success and kind of recognition on the SubZero platform.

Number 1 out of 16,000 isn't so bad, Kyle.

Yeah, I'll take it.

Well, thanks folks for joining us on this Friday. I hope you have an excellent weekend and we will see you out on Society and next week, hopefully. Take care, everybody. Bye-bye.