Cutting Through Tariff Twisted Q1 2025 Earnings - May 2025 Training

Thanks for everybody for joining us today. We are super excited to provide this training. What I think is a really important point in that the world has changed a lot in the last few weeks, and it's time to talk about what What this means for the investing landscape in particular, we're seeing an unprecedented level of misinformation and what we're calling tariff-twisted narratives and tariff-twisted earnings. We've never seen— I can't remember in my career, 25 years in the business, never seen companies say, hey, I got 2 sets of numbers, one with a recession, one without a recession, or just pull it all together. Because things look so unclear in the future. The most important thing is that what's unclear and what creates volatility for so many people creates opportunity for us and for you. We're going to show you how to profit from the most misleading earnings season since COVID even more. As usual, our disclosures and disclaimers. We are not advisors. We are not providing advice. We are providing information. You need to speak to somebody else about specific investment advice. All right, I want to hear from you all in the chat. What I need to see is your request for tickers, because if we have time at the end here, I'm going to be putting some tickers into the system and sharing this with you all. But I also want to know, is this your first time with us? Do we have any first-time participants? Because those are always special. I know we've got a lot of loyal loyal clients and fans, but I'd like to know if you're a first time with us. But for sure, get your tickers in if you want them to be selected at the end of the show. All right, so I want to start off by asking you all, is your investment portfolio ready for what's coming? Because right now we're witnessing the most chaotic earnings season I've seen since the COVID crisis. Wall Street slashed S&P 500 targets for 2025. And earnings estimates are tanking like we've never seen. The numbers are scary. All right, we've seen the targets from Wall Street go way, way down, and then with one headline, all of a sudden the targets go back up. There's a great slide showing the huge declines in the S&P 500 index year-end targets. You can see on the right side of this image here This is how people lowered— this is where people lowered all their targets for the S&P 500 compared to where they were at the end of the prior year. That was just a few weeks ago. And now yesterday and today, we're seeing headlines about how the bulls are back in town and Goldman has raised their targets back up, and so is Ed Yardeni. That's quite a flop in a short amount of time. In the meantime, the one thing isn't really a flop is that trade is definitely down. We've seen a significant decline in imports, down 64%, exports down 30%. We've seen a dampening. Now, how long this is going to last, how impactful it's going to be, we don't know for sure, but it's definitely been a downturn. We saw tariffs as high as 245%, and then in the space of one meeting, get knocked down by 100 percentage points. So things can change quickly. There's a lot of noise. You see a lot of narratives. You see a lot of buys and sells and holds. What's funny about all this is that Wall Street is flipping and flopping where our rating systems are going to give you something much more consistent. The market remains very unpredictable. Yeah, we've seen the tariffs have dropped and we're taking this 90 days thing really 90 days at a time. So I think one of the big things to keep in mind is that as much as everybody says, oh, everything's okay again, things are not all okay. Even for the Magnificent 7, right? Names like Nvidia and Apple, right? They're off. And then I made it back already. And if you're wondering how do you make money out of this mess, you're exactly where you need to be. Hello. For those of you who don't know me, I'm David Trainer. Welcome. For those of you who have been with us before and been with us for the first time, I'm the author of Modern Tools for Valuation. I've been doing this kind of work for 25 years. I was Wall Street early on before the tech bubble, during the tech bubble, after the tech bubble, ever since. And I've seen the tricks that Wall Street pulls, the companies pulls. And I decided way back then that I wanted to build something better. I wanted to have a firm that gives investors like you clear, honest answers because I saw, especially during the tech bubble, that's not what Wall Street does. And over the last 2 decades, I've developed AI-powered stock research that digs deeper, picks stocks better, and produces alpha that beats the market. Our alpha comes from proprietary data extracted from footnotes in every financial filing that matters, because that's where the real story lives. We get data that nobody else has, and the alpha and outperformance of our solutions for this market Speak for themselves. Proof is in performance, folks. You don't have to take our word for it. Our stock picking has beaten 16,000 buy-side professionals to claim the number 1 spot in multiple categories for 47 straight months according to SumZero. That is a buy-side only platform. Buy-side means professional investor. Sell-side, those are sort of the traditional Wall Street people. They're called sell-side because they're selling stock. They're in the business of selling. We'll talk more about that later, why that creates conflicts. The buy-side people, they're professional stock pickers. That's who we're beating. That's where we're ranked number 1 in industrials and at least one other category, again, for 47 straight months. Not to mention the fact that our work has also been vetted and validated by some of the most prestigious institutions in the world, such as the MIT Sloan School of Management. The Harvard Business School, Ernst Young, the Journal of Financial Economics. Even better, the performance of our actively traded indexes based on our research proves our value add for you. What am I talking about here? I'm talking about live traded indices created by Bloomberg. You can go look up on the internet. This one is the Very Attractive Stocks Index. It beat the S&P 500 by 9%. In the first quarter of 2025. It's beaten the S&P 500 by over 80% over the last 5 years. So if you're interested in the very attractive stocks, you're in the right place because the very attractive stocks as a group of stocks, just as a portfolio, perform extremely well. That speaks a lot, I think, towards about the quality of our rating system. The core earnings weighted S&P 500 index, that's another Special Index. This is one of my favorite because all this does is say, look, even if somebody else picks the stocks, we can still outperform because we'll weight your stocks, in this case, the S&P 500 stocks, according to core earnings as opposed to market cap or equal weight or whatever the traditional or whatever the way of weighting stocks used to be. So when you weight stocks based on core earnings as opposed to market cap, you beat the S&P 500. We beat the S&P 500 by 1%. In the first quarter of 2025. Again, that's the same stocks, just weighting them differently. And then if you look over the last 5 years as of April 30th— and by the way, all these 5-year charts are as of April 30th— the core earnings weighted index beat the S&P 500 by 33%. Impressive, right? Again, this is Bloomberg's index out there being live traded. Proof is in performance, folks. I don't know what else to say. Like, if these are live-traded indices, there's alpha in our core earnings data. These indices are managed by Bloomberg and they are not available for the public to purchase. However, they're all based on our research, which you can purchase. For example, our focus lists long and short outperform even better. From January 21st, 2021 through the first quarter of 2025, our focus list long model portfolios outperformed the S&P by 18%. The Focus List Stocks Short Model Portfolio has outperformed the S&P 500 by 45% from 2021 through 1Q 2025. I don't believe you're here by accident. I believe you're here because you sense something isn't right with the market and the stories you're being fed. And today I'm here to help you navigate the most challenging earnings season in memory and give you the answers needed to make money. You're here because you want a reliable edge that enables you to pick the right stocks at the right time. And I'm glad you joined me because today you're going to get what you're looking for. While others are panicking or buying like there's no tomorrow, you're going to walk away with a clear roadmap for navigating what might be the most deceptive earnings season we've seen in years. Here's our agenda today. Today, why today's market presents unique challenges due to tariff twisted results and narratives. How to find the best stocks to own now, number 2. And I'm going to explain also how our research is the best in the world, how we prove that. I think I proved a lot of it already, but I want you to understand that we're going to give you transparency and auditability and authenticity you don't get to see other places. That's what makes New Constructs special. That's what makes our community special. That's what makes their clients special. That's what makes the relationships our clients have with each other special, is that we all know that we're doing something that is for the right and based on real data, real analysis, real math, real logic. And that's all something I think that gives us comfort, a special comfort, a comfort that's hard to put a price on. I'm also going to share how to get our top 3 tariff-proof stocks no matter what happens in the trade wars. I think it's important that we don't just talk about problems. We give you solutions. And then lastly, at the end, bring us your tickers. I'm going to analyze 3 stocks based on popular demand. So let's talk about what's really happening. With tariffs dominating the headlines, injecting uncertainty into markets heading into Q1 earnings season, companies are doing something dangerous. They're telling Wall Street-friendly stories that sound good on quarterly calls but don't reflect economic reality. A real view of the underlying business reveals an entirely different picture. Think about the investors who trusted Silicon Valley Bank earnings— bank's earnings calls last year. They were saying everything was great right up until the moment it wasn't. Sound familiar? Wall Street does it all the time. Valiant, WorldCom, Enron— they're all going to play the charade for as long as they can. That's their job. That's what gets them paid. Consider the other countless investors who bought into WeWork's story before its spectacular implosion, right? What was Wall Street doing? They're trying to sell you that one for $47 billion, and they kept doing it until guess what? We blew it up. Wall Street's looking to sell you. That's why they call it the sell side. Even the market darlings are not immune from all this. It's not all about just WeWork and Valiance and Silicon Valley Bank, the Magnificent 7. Have fallen a long way from their recent highs. Huge declines. And although we've seen a bounce back, we still believe they are vastly overvalued. When you dig into the real financials of companies like Nvidia, Apple, Alphabet, and Meta, the gap between their stock valuations and current cash flows is staggering. Wall Street doesn't want you to see that gap. They prefer you don't have any idea how big it might be. Because you'd be terrified if you knew the whole truth. The best Wall Street can offer is a few years of flawed EPS estimates. Here's an example of some estimates we pulled off of a public source. And the 2025 and 2026 stuff is free. The other stuff wasn't free. And so we just put some approximations of what those numbers were. But this is what you get. And what I'm about to show you next are slides we've never shown anybody before. We just figured these out because we're just trying to like The best way to help you guys see, like, how crazy things are. So another way to put this, we give you what you deserve. We don't give you just some— create some terrible estimates. We give you what you deserve, the whole truth. Our models are able to show all the cash flows baked into stock prices, not just a few years of estimates. And when you do that, the gaps are staggering. Let me show you exactly what I mean. Here it is for Tesla. The cash flows required to justify its price dwarf the EPS estimates. We put this into a chart, and this was created from one of the best, if not the best, discounted cash flow modeling system in the world. I've demonstrated this. If you're not part of our community, you can sign up for free. We've got all kinds of reverse DCF scenarios in there for folks to see. You can probably find a few for free on YouTube. What we do is we reverse engineer What the cash flows have to be to justify a stock price, and when you do that, you find that those cash flows are way more than the analyst estimates that are provided. This is a great picture of that. The blue section here. Well, these are the analyst estimates we got, and that was a paid service, right? Going out for for six years. That's what this is: the analyst estimates, the cumulative value of the analyst estimates. Okay, right? That's what analysts, that's what Wall Street's having you focus on. Well, to justify $276 a share, this is the cumulative present value of free cash flow. That's the real value they got to create. Wall Street doesn't talk about that because if you knew it, you'd run from this stock. Same is true with Amazon. The estimates only get you so far, but look what the actual stock price implies. Nvidia, another example, for $117 a share. The annual assessment's only going out to 2029. Why does Wall Street not do this work? Because if they did, they wouldn't have been able to convince themselves to try to take WeWork public. It would have been such a, such a joke, right? And so it's a whole lot easier to sell you stock if you don't realize how expensive what it is you're buying is. So I hope I made my point clear. EPS estimates are not nearly enough. To make informed investment decisions, and definitely not in this environment when they're changing every day or they're they're based on different potential future scenarios. Look, U.S. Economic Policy Uncertainty Index has hit an all-time high, and yeah, maybe it's come down a little bit here, but do we think it's going to go back to normal? U.S. inflation expectations are at their highest since 1981. And then the market rips on news that China is good with 30% tariffs. And I think that's part of the Trump strategy, you know, hey, I'm going to start out with 145%. So by the time I get down to 30, you'll be thanking me. Whereas if we started at 20 and tried to move at 30, never would have happened. Because it worked. But I think the takeaway for you all is that we're in the most confusing environment I've ever seen. Even the most sophisticated investors Can't make sense of conflicting headlines. The markets acts as if everything is great again, but we know number one: tariffs are here to stay. Big tariffs, 30%. President Trump's aggressive agenda is not done. I don't believe President Trump is going to go into his cave for the remainder of his term. He's going to keep kicking bees' nests. That's the nature of this guy. Do you remember? Did you watch Liberation Day? That was a show. Almost every interview with President Trump is a show. Super entertaining. He understands that attention is the most valuable commodity, and he will continue to get attention. And he's clearly not afraid to kick some seriously big bees' nests and send markets roiling. I believe extreme volatility is more feature than a bug in the Trump era. The Trump era. And not all stocks are treated equally. You can see here, Magnificent 7, they're still down compared to the S&P. The S&P is back to normal, maybe even up a little bit. The Mag 7, they're still down 3%, some down worse than others. So I think it's important to understand that just because we've seen a bit of a reprieve here after like, what was it, 6 weeks of hell, I don't think things are all back to normal. However, that's not what Wall Street's telling you. And a lot of other investors seem to be erring on the side of optimism. I'm seeing these headlines. Nvidia, the drama's over. Back to $150. Here we go. Let's get it back. That's probably written by somebody who bought Nvidia at $150. How about Boeing stock jumping as China opens? China's back open for business. That doesn't mean there's, you know, look, they're going to stake the— they're going to take the planes that they've already bought. Are they going to still buy more? I don't know. This is, I think, potentially overly optimistic. And if you're feeling uneasy about your portfolio in this environment, you should be, because the tools that most investors rely on simply aren't designed to cut through this level of noise and misdirection. The good news is there's a new technology that delivers the right stocks in today's market. It involves shifting focus from the narratives to verifiable financial data. Stop paying attention to the day-to-day noise. And let's get down to the real numbers. Real numbers that, in my opinion, are the way to protect your portfolio and find the right stocks while others are being misled. That's right. You know, you're going to build your analysis on sand. You're going to build your analysis on solid rock. The answer starts with fundamentals, real footnotes, not the surface-level metrics that everyone else uses. Look, there are all kinds of services out there that can give you data. Oh, it's all over the place. Just like there are all kinds of services out there that can give you food. Is it all good for you? No, it's not. A lot of people selling stuff that's bad for you. Remember the cigarette company saying that tobacco was okay? Right? Everyone says their data is good and okay. Is it? You don't know. I'm telling you it's not because I've done the work. And New Constructs, we developed a special technology, a cutting-edge AI that cuts through the noise systematically. Our AI ingests and analyzes every page of financial reports, 10-Ks and 10-Qs, especially footnotes and the MD&A. It's built for truth-finding, not narrative spinning. It exposes bad information legally hidden in companies' footnotes. Here's an example of how that would look inside our system. It's a great pull-down from one of our models. We call this our marked-up filing feature. And all of our models are backed by this. This is why some of the most sophisticated investors in the world, some of the most sophisticated people have written papers and published these papers proving that our data is superior because it can be audited right back to the source. This is a picture of an SEC filing. Here you can see on page 113, they're recording sublease income in their operating earnings and their net income. They're counting Properties that they're leasing, and this is a firm; they're not in the business of leasing property, but they're counting it. It's not part of their operations. We pull it out to give you the real numbers. Now let me share three other key ways our clients leverage our AI to pick the right stocks. First, we've already updated over 2,000 financial models post Q1's earnings data. These model updates drove around 800 ratings changes. It's about what we see every quarter based on the new filings. And ratings changes can identify winners and losers every day we get new filings. For example, Motorcar Parts of America was upgraded from neutral to attractive on February 11th after we parsed this 10-K. Over the next month, the stock increased 60%. Dell Technologies upgraded from neutral to very attractive on April 4th after we parsed this 10-K. Over the next month, the stock increased 32%. Remember, very attractive stocks as a portfolio outperform. When you get upgraded, that's an extra special layer of outperformance. While the rest of the world is quibbling over EPS pennies, our clients are positioned to make big money with the stocks we identified with the most under- and overstated earnings. Second, our clients enjoy the most rigorous financial analysis in the world on US stocks. Here's how it looks inside our membership. You type in a bunch of tickers, you get answers. Green is good, red is bad. Each company model that we build on all 3,000+ companies we cover, each model in our, in our PDF reports Represents, I believe, $50,000 of time and forensic accounting expertise to get to the truth and correct numbers. If you were to hire an expert on Wall Street to build you like a really good model, I think it's gonna cost you $50,000. That's how much work goes into doing this. How do I know? It's what I've done. It's what I built my life doing. Right? And that's why I built the technology to scale it because I know no one can afford $50,000. Per report or per company. This consistency in our analysis, this robust analysis means that you're getting results you can trust across thousands of stocks. That's another reason I built technology, because when I had a team of people doing this back in my pre-tech bubble days, not everybody does things the same way. Machines, same way every time. Trustworthy, reliable, consistent. And to give you some context of how our proprietary research scales, I'd like to bring up Warren Buffett. Experts estimate that Warren Buffett read more than 100,000 financial statements in his 70-plus-year career. This was from the Wall Street Journal. Buffett has read— conservatively, I believe Buffett read more than 100,000 financial statements in his more than 7-decade career. We've spent 20 years optimizing our AI for financial statements analysis. And we've analyzed over 500,000 filings and counting every day. And that does not include the number of filings that the AI uses for testing. This includes only those that have been perfectly marked up and analyzed and reviewed by experts. Now, the AI does most of the work, but an expert has gone through and made sure it's all perfect. So we have 500,000 perfectly marked up filings. That's what our AI is based on. There's hundreds of thousands and even more filings that the AI has tested itself on, right? Because we can say, hey, AI, go parse this filing for Apple in 1998. And we don't tell the AI that we actually had an analyst already do it. We know all the answers. We're gonna see how well you do. And, and so AI goes and parses it, and then we grade it based on what the expert does. And we say, AI, oh, you missed this, missed that, missed this, this, this, and that. And the AI goes back and tries to fix it. And we do that over and over. This $500K doesn't even count those. At New Constructs, we've analyzed 5 times as many financial statements as Mr. Buffett and counting. We are the AI version of Mr. Buffett. Third, we maintain true independence. We have no investment banking conflicts, and it shows up in our ratings. Less than 4% of all the stocks we cover get our very attractive rating. Less than 13% get an attractive rating or better. Sad truth, 96% of stocks covered by Wall Street are listed as buy or hold. 96%. Why? Because they're selling stock. How many stocks do you think they can sell that have a sell rating? Right? They're not selling stock for companies that get sell ratings. They're not doing any investment banking business if they got a sell rating on the stock, most likely. Right, because their paychecks depend on you buying stocks. They make no profit from research. The research doesn't actually make many money. Research analysts don't make money for the firm. You know who makes money for the firm? You guys have been with me before. You know the answer to this question. The investment bankers make the money for the firm. According to more recent data, 50% of Wall Street ratings for stocks are listed as buy. 57%. compared to our 13%. You don't think there's some bias there? Come on. How about some specific examples recently where Wall Street rated stocks as buy and our system disagreed? How about Shake Shack? It's been rated a buy or hold almost all this year. We've called it unattractive or very unattractive. You can see here, this is what our ratings were during this time, rating system. Guess what? Stock is down 12% year to date through just yesterday. How about for Peloton? It's been a buy or hold this year. We called it unattractive. It's down 21% year to date. How about Warby Parker? Also buy or hold by the majority of Wall Street analysts. We had it unattractive all year. It's down 23%. The value of our AI solution is proven by our performance. What better way, folks? I mean, papers from Harvard Business School, Ernst Young, the Journal of Financial Economics— those are great. But performance? Can't argue with that. The Very Attractive Rated Stocks Index beats the S&P 500 by 9% in the first quarter of 2025, 80% over the last 5 years. Core earnings weighted S&P 500. That's the core earnings enhanced version of the S&P 500. Beat it by 1% in the first quarter, 20— and 33% over the last 5 years. The core earnings leaders, the winners, the best core earnings companies beat the S&P 500 by 5% in the first quarter of 2025 and 43% over the last 5 years. The focus list long stocks beat the S&P 500 by 18%. The focus list short stocks Beat it by 45%. Our AI data-driven system allows clients to cut through the trade-twisted narratives and identify stocks where the fundamentals are strong regardless of the noise. And per one of the comments in the chat just now, we're also really good at identifying overvalued companies where the narrative overstates the financial reality. You got to have both. Right? As Ben Hogan said, it's not— your golf score is not always so much about how well you hit the good shots. It's really how badly you hit the poor shots. All right? And it aligns with more Buffett's philosophy. You can't predict what stocks will do in the short term, but you can predict what businesses will do. We're not trying to be predictors. We're just trying to identify where the fundamentals are good and the valuations are also cheap. We let Mr. Market predict the future. We just try to understand risk-reward, just as Mr. Buffett said. So how do we do all this? What's our secret edge to outperform even in the most chaotic markets? Well, if you've been part of our community for a while, you know what our edge is by now. It's our robo-analyst technology. How do we do it? We use the first and best and only AI for investing. Here's what it looks like. Look, we make it simple, right? You know, I just had a meeting earlier today and they were talking about how You know, we were talking about a lot of really complex stuff with some sophisticated hedge fund and institutional investors. They're like, David, we like how you make it simple. I said, yes, if we make it complex, then we're just doing what Wall Street does, making it seem hard when it doesn't need to seem hard. We've done so much work. We boil it down to a very simple overall risk-reward rating. Risk-reward. We can measure that. 5 key metrics that drive these ratings. You've got economic versus reported earnings. The economic earnings are the full picture, the full profitability picture of a company. Return on invested capital, Buffett's favorite metric, my favorite metric. We do this better than anyone in the world. It focuses on how much cash flow does a business generate relative to how much capital has gone into it over its life. Most important metric there is. I just, you know, what do you care about if you're an investor? How well are they doing with my capital? Right? How much cash flow does the business generate relative to how much capital's gone into it over its life? Valuation. 2-year average free cash flow yield. Super smart metric. Looks at a 2-year average free cash flow excluding cash divided by enterprise value. Great metric. Price-to-economic book value. One of my favorites, as you all know, because I love understanding how much the stock price differs from the no-growth value of the business. I think that's always very interesting. And then, of course, the market implied growth appreciation period. That is probably the strongest individual metric of the 5, and we have done special offers and trainings just on this metric. It is based on our reverse discounted cash flow models, the best in the world, the only ones that have been developed at scale. This AI has the ability to comb through thousands of government filings with precision. analyzing every line and footnote. So what we make simple for you is based on a ton of work. That's why executives from some of the top firms in the world have all used this system. And again, the beauty of it is that we boil it all down to something very simple. Green means good, red means bad. All 5 metrics play a critical role in the rating that— and but it all boils down to green means good and red means bad. We're the only stock rating system that I know of that has an official US patent behind it. If you know of another one, please put it in the chat. If you know another firm that has the performance that we have as a research firm, please put it in the chat. If you know another firm that has papers published to prove the superiority of the data, please put it into the chat. And if you haven't seen this interview that I did, it's the Stansberry Research Conference, which is an excellent conference, by the way. On why AI is not magic, I highly recommend it because I explain exactly why our AI is real. And there's a few key takeaways from this, from this interview. Number one, AI is not magic. Data matters more than technology, right? I don't care how great the technology is. You know, just like with a car, it doesn't matter how the, how, how great the engine is. If you put bad fuel in it, you're gonna get bad performance. If you don't have good data, performance isn't going to be great. Now, to that point, for you to trust in AI, you need to be able to audit the data. That's why all of our work is auditable. We want you to, we want you to like see, oh my gosh, New Constructs, they want you to, they want us to audit everything. They, they're going to show us it all because I want you to challenge any of our competitors and any other research firm to do the same thing for you. All these FinBots and, and FinChats or whatever, you can't audit any of that work. They don't want you to see what goes into it. They don't want you to know how the sausage is made, because guess what? They're not proud of it, or they don't have it. So they don't even know. ChatGPT is a great example. Why is it not reliable? We can't audit the entire internet, right? It's based on the entire internet. That's what a lot of all these big new large language models and chatbots— I mean, they are based on the internet. How much of the internet can we trust? And to that point, Reliable AI has to be focused on a body of data and knowledge that is small enough that you can audit the whole thing and get it right. Now, eventually, we're going to be able to put a lot of those little pieces together into a larger AI. But in the beginning, it's going to be singular datasets, singular niches within society. That's what we've done for investing. So specifically, our, our robo analyst leverages AI get the data that the market is missing and do the diligence that no one else does. To win in this world, you got to be willing to do things other people won't do. New Constructs is that for you. Our roboanalyst analyzes footnotes where companies hide critical information. This is the data that no one else has. There's alpha in the footnotes. We've seen it in the Bloomberg indices. And there's alpha across hundreds of thousands of filings, just like needles in millions of pages of haystacks. That's what our AI pulls out for you to benefit. Think about it like this. Who has time to read 200+ page 10-Ks and 10-Qs and do proper diligence every quarter? They don't do it. They stopped doing it during the tech bubble. This process cost— would cost them millions of dollars per quarter. They wanted to do it right. That's why nobody— that's why no one, no one else does it. The comprehensive nature of our research entails countless pages of data and documentation, including information from balance sheets, income statements, cash flow statements, footnotes, and dozens of other disclosures. Here's a sneak peek of how it looks inside our membership. This is an institutional view where you can see The actual footnotes that we're pulling out. A couple of great examples. Both these are from Meta, which we— this— we put this together for a presentation we did for Bloomberg recently. They wanted some examples and we just pulled them out in just a couple seconds. And Meta was one of the big stocks, big outperformers in the Core Earnings Leaders Index over the last year. Now, by understanding the true profitability and identifying the hidden risks, we can build a superior financial model To find the best stocks. That's how we do it, folks. We're not just like winging it here. We're not making something up. We are systematically building a better system to understand the truth and make better investments. Our stock ratings are grounded in the verifiable numbers from the filings, not speculative narratives or potentially biased analyst targets. This gives you a much more accurate picture of the company's sustainable profits. and helps us discover stocks such as Mind Technology, upgraded from neutral to attractive on April 9th, up 32% in the next month. Alibaba Group upgraded from neutral to very attractive on April 8th, and it was up 24% in one month. We also help you avoid stocks such as Caesarstone. It was downgraded from neutral to unattractive on March 6th of this year. Since then, down 24%. Voyager Therapeutics downgraded from neutral to very unattractive on March 12th. Over the next month, down 22%. Those are some pretty impressive stats, folks. Do you think you want to know what's going on with the ratings? Remember, producing and maintaining this level of detailed research would set you back millions of dollars of each quarter. I wouldn't just say detailed research. How about successful? How about effective research? And does it surprise you? Of course it's hard work to do something like that. But our membership is going to give you access to a depth of financial research that's considered a gold mine to financial advisors and hedge fund managers around the world. This super high-level research consists of superior unbiased ratings on 10,000+ stocks, ETFs, and mutual funds. You can see you get all the data behind the ratings and each criteria. You can benchmark that against The major, the relevant indices, large cap and small cap. Portfolio tracking. You got a portfolio, throw it in here, whether it's stocks, ETFs, or mutual funds. We'll give it a rating. We'll let you know what it looks like, and we will alert you when it changes. Anytime a rating changes, you get an alert. Anytime an analyst note comes out, you get an alert, and we explain what those analyst notes are for our professional members. It also gives you stock screening with precision. More quickly, when you are a professional member, we will explain what that note is. So you'll understand if it was an acquisition or if it was a warning from the auditor about internal controls. These notes are extremely important and difficult and value-added, and those come across as part of the professional membership. You also get stock screening. And let me just say, like, our stock screening, it's unbelievable. Traditional stock screening was a way for people to do less work. And by that, I mean, and I know, because when I was on Wall Street, they would screen through, use these rough screens. The data was never very good. Data still isn't very good because you guys are using the same data that Wall Street uses. Not good. The idea was just to try to get down to a group of stocks that you could trust were close enough, and then you would do the real work. And so you maybe winnow it down to like half a dozen stocks, and you're hoping to find maybe one good stock in that. But you would do the real work. And by real work, this is pre-tech bubble, go through all the filings, $50,000 per company work on those 6 companies. That's what people get paid $500,000 a year to do on Wall Street. Right? And so, but with our, our stock screening system, we've done all that work on 3,000 companies. So when you're screening, you're getting incredible picks. That's why, that's why our performance is so good. When you look at all the other competitors out there, Whether it's Holt or EVA Dimensions, FactSet, SIFRA, like they don't do what we do, folks. They don't go the extra mile. They don't go that critical extra mile into the footnotes to get the alpha. That's why we're the ones that are ranked number 1 for 47 straight months. So to summarize, with our professional membership, you can invest your money with confidence, knowing that you have access to the most accurate research and ratings available. Maximize your profits by making informed decisions based on proven data. Leverage a new AI for investing that empowers you to thrive in any market conditions. Enjoy real due diligence, peace of mind from knowing you have the complete financial picture when making financial decisions for your clients. Our clients consider us an entire equity research department. department at their disposal. They tell me that like every year when it comes time to discuss renewals. David, we're very happy to pay you a couple hundred thousand dollars because it would cost us millions to replicate this. Let's go into some case studies here or some testimonials. This is a wealthy client, several million dollars. He put it with a big trust company, one of these big blue blood firms. He let the big boys manage it, and I'm going to take some time off after a 45-year career. Mistake. Incompetence can be wrapped in a very pretty package, as he put it. He took over the account, and since that time, and with our research, he made his money back with a reduced risk. He sold off the bad stuff and kept the good stuff. The stocks he sold off had a 5% return, and the stocks he kept had an 18% return. These are my purchases based on your tools and my additional research. I think this tells the story about your research. I was skeptical. But the results have given me confidence. How about some testimonials, some notes from clients? Simply and instantly, you can see how your stocks or funds are rated. And I highly endorse the New Constructs system as a— as one must-have tool in any stock or fund selection system. I sincerely appreciate all the work that has gone into creating New Constructs in the database, going from marked-up footnotes and filings to reliable, easy-to-understand indicators. Is a huge undertaking. I find New Constructs to be reliable, relevant, and trustworthy. Thank you, Chris. Thanks to you and your team for all you do, but mostly for your integrity. Thank you, Nancy. I look for value in my selections, and I found your analysis superior. As a business owner, I know how financials can be manipulated. Your research digs that out. I use other metrics, but I rarely buy something that does not have solid ratings from New Constructs. Thank you, Kurt. New Constructs leverages my expertise in areas where I don't have enough people to break down all the balance sheet stuff, footnote stuff, and standardize it and do it every quarter. It amplifies your capabilities. Thank you, David. It provides me with concise insights into investment opportunities derived from meaningful metrics that I couldn't duplicate on my own. Thank you, David. Look, in a world where trust is in a downfall. Trust in most U.S. institutions has withered. It's Congress, big business, newspapers. Who knows? The stock market. How about political affairs, right? Media. Can't trust it. We give our clients in this kind of world, we give you a port in the storm. We give you a place you can trust information. Because at New Constructs, we believe in trust and transparency. We only recommend stocks we believe are truly valuable. We don't have some other hidden agenda. We're here to help because that's what we believe in. That's what my mission is, to improve the integrity of the capital markets. We're not talking about stocks that we are compensated to promote or rate as attractive for, for a paycheck. That happens more than you think. Now, free live demonstration time. Let's take 3 Tickers, stocks that you guys want to take a look at. What do we got here, Kyle, as requests? The first one we had was for UHC, which I think might be the ticker UNH, UnitedHealthcare. Okay, type in a ticker, get an answer. Yeah, we've seen a lot of this in the headlines recently, a lot going on here. This stock rating downgrade, we just got a new 10-Q. On May 8th. And so yeah, you know, this is a neutral rating, folks. Valuation, you know, I always like to see a price-to-economic book value that implies a permanent profit decline, but they've already come out and said that their cost is going to be a lot higher. So we, we know profits are likely headed in the wrong direction. We're seeing the economic versus reported earnings is a false positive. So what that means, accounting earnings going up A lot more than economic earnings. So yeah, this would be one that I think it'd be tough to make a straight-faced argument that you'd want to be in this. And yes, the CEO did quit recently. Other things you get from from the professional membership: remember that report I mentioned? Click here and you get a PDF that will show up in just a matter of seconds, and that had that's an entire model. As we mentioned before, you can see you. Here's the rating. Here's all the charts, backup details on what all the income statement adjustments are, what the biggest adjustment is. You also can see— can break down the ratings according to each one of the elements. So you can see economic earnings versus— I'm sorry, accounting earnings is in red and economic earnings is in blue. See the trends in return on invested capital and the cost of capital. You can break that down further into the DuPont model. So you got NOPAT margin, versus invested capital returns, the free cash flow yield over time, and details— like, we provide details behind all the charts. So you want to know what the free cash flow has been for UnitedHealth? It's been kind of up and down. Really good in the trailing 12 months, not so good in 2024. I think 2025, considering their forecast, might not be so good either. You got a free cash flow margin, the price-to-economic book value. You can see the stock price come way down. So is the economic book value, though. Economic book value started dropping a while ago. So you get all this backed-up data. We got a little testimonial here in the chat. It says, thank you, David, the person who suggested— requested UHC. Thank you. I owned it a while ago and got out on reason— on reasons consistent with your research. Glad to hear that. Thank you, Gerard, for that comment. Here's a summary of the reverse DCF model there at the end. You also get This GAAP reconciliation. So here's where we show you the reported net income. Here's where you show— we show you the net operating profit after tax. All the adjustments we're making, we'll show you where we get them. All the balance sheet adjustments, we show you where we get them. All the valuation adjustments, we show you where they come from, right? Because we, we do the work. We're proud to show. And if you've done the work, wouldn't you be proud to show too? So I think it's safe to assume other firms that don't show you the work because they're not proud of it, or they haven't done any. They don't have adjustments, right? And, and, and look, you know, for institutional clients, they can actually go even further and dig straight in and see where the big adjustments come from. I think you saw on that adjustments page there's a big income statement adjustment. $3.3 billion right here on the cash flow statement that you didn't see. You can't find it on the income statement. A gain on the sale of strategic— gain on dispositions and other strategic transactions. That's where we got that, right? So full transparency into everything that we're doing. All right. Do we have any other, any other tickers to talk about? Yep. Next one up is AMD. AMD. Popular. Doesn't look like a very good stock here. Unattractive. The economics of it look pretty bad, and the valuation looks very expensive, folks. I would avoid. 9.4 price-to-economic book value and more than 100 years of profit growth. That's what this means. The market implied growth appreciation period is the number of years that the market price implies the company will earn an ROIC greater than WACC on new investments. So this means the company's got to grow profits for more than 100 years. That's expensive. If we were to do one of those charts like we did in the, the presentation where we covered this chart here, right, if we were looking at a similar chart for AMD, it would look like this, right? You've got earnings estimates, you know, can account for about this much, whereas the stock price is accounting for this much. Right? A big disconnect. That's what these— that's what— when you see red here, that's a big way of— a good way of thinking about what that means. We also got a credit rating. So the credit rating on this business is better than the equity rating, which is interesting, right? That's part of our professional subscription is you get a stock rating and a credit rating. And all the credit ratings are going to also show you exactly how the traditional data compares to the adjusted data. And that's where we go in and say, okay, if you just take the unscrubbed data from the income statement and balance sheet, this is what free cash flow looks like. If you adjust it as we do, this is what free cash flow looks like. So very different numbers, very different numbers. And we're, again, we're showing it. We want you to know the difference because that's what you should be going after. That's how you get an edge. The difference in the data is where you get an edge. If you don't have a difference in data, you don't have a difference in results. And that's why we're always trying to show you exactly how much value we add by showing you exactly the difference in the data all the time. We also have sector research, right? You want to know what sector we like most? This has changed a lot and it's going to continue to change. We get new filings. Yeah, I mean, utilities has been upgraded. They used to be the worst-ranked sector. Financials at one point was the best. Right now it's consumer non-cyclicals. Makes sense in a tariff-driven environment. You want stuff that isn't cyclical. It's going to move through cycles. That's a good thing. Cyclicals has dropped way down, middle of the pack. But you can see great sector research here as well. And if you wanted to break it down further, you want to know more about, okay, well, which ones, which parts of non-cyclicals do I like the most? Well, we can break it down to beverages, food and drug, not as good, food and tobacco. Not quite as good as beverages. Personal household and services. So the best subsector is beverages, but we got some that aren't so good, like food and drug retail. Kind of makes sense. Retail is going to get hit double-sided, right? There may be a little bit of recession because of people like not spending as much and, and import and, you know, and tariffs and stuff like that. And then prices are going to go up because of tariffs. So they're going to get squeezed on both sides. So that's an example of our sector research here. And we also will show you within each one of these sector groups, our, you know, our best industry, our best stocks, our worst stocks, best ETFs, worst ETFs, best mutual funds, worst mutual funds, and some overall stats on the sector as well. So great high-level detail there for you as well. All right, Kyle, we got time for one more stock. What's it going to be? Yep. The next one that came in was ZS. ZS, Zscaler. So suspended rating because we had to update our required cash assumption, but it doesn't look good. Poor quality of earnings, expensive valuation, 181 price-to-economic book value. Whoa. That means this chart, like you might not even see the blue if you, if you did that. 181. Price, economic book value, and obviously more than 100 years of profit growth required to justify that stock price. Pretty incredible. All right, next what we're going to cover quickly is stock screener new constructs, right? So this is all stocks. I can come in here and I can sort based on return on invested capital. I can sort based on the risk-reward rating, good or bad. For across all stocks. But more specifically, let's say I want to go and say I want all the very attractive and attractive stocks in that consumer non-cyclical sector. I also want return on invested capital to be greater than 10%, and I want a dividend more than 3%. Go. Bam. There it is, right? Really impressive. Really impressive. I want to do the same thing for a subsector. Bam. There it is. Right? Let's say we want to go for the entire basic materials sector. There it is. Very, very impressive. Very impressive. I don't want to give away too many great picks because this filter is incredibly strong, but you get the idea. You get the idea, right? You can come through and you can screen entire sectors or the entire market based on these key criteria. Institutional clients can download tons of data and sort through it all. Yeah, that's a whole nother level. Right? But as a professional member, you can come in and see, find all the good stocks and the worst stocks in every sector and industry in the entire market in seconds based on super precise models and information.