The Market Correction “Cash-In” - April 2025 Training

Thanks everybody for joining us today. I'm excited to do 21st training in the last few years or so, and we have once again done some research in our system to identify what we believe to be some really unique and special picks, but most importantly Stocks that we feel like will survive no matter what happens in the current tariff environment. Let me share my screen and we will get going here. As usual, please let me know if you have any questions and if you want us to cover some stocks. You got any requests? Get them into the chat sooner rather than later. We will go by popular demand, but When there's a tie, tie goes to the person who puts their submission in first. So, great to be with you today. I'm going to jump right in here. Look, the market correction cash-in. What people don't realize is that when the stock market goes down or when it's as volatile as it has been in the last few weeks, that creates opportunity. That's an opportunity for people to go in and make hay while most folks are getting afraid and running away. And we have the best system in the world for doing that, which we're going to share today. How we have identified the 10 best unjustly beaten down stocks that you can get before earnings season. As usual, our typical disclosures and disclaimers. I am not an advisor. We do not give out advice. We provide information. We provide the best information in the world, the best fundamental information in the world, and I'll show you why that's the case. And as usual, I'm going to offer some freebies to people who can disprove that later on. We are not an investment advisor. Talk to somebody else about that. We provide information. Now, we also like to engage, so get your questions into the chat or the Q&A. Also, let us know what city you're from, and we'd like to know, are you more retail? Are you more quant? Are you a hedge fund? Are you an advisor? And if you want us to cover a specific stock, put it into the chat and we will get you on the list, and we will put that ticker in before the end of the presentation. So here's the agenda today. I'm going to talk about the current market opportunity, why that's a special time and an excellent time to make super smart investments. I'm going to talk about how the media and Wall Street manipulate their research and manipulate the messaging to trick you into buying the wrong stocks. And I'm going to show you how to access our cheapest and best stock picks for the first quarter of 2025, the best stocks that you can identify or find in this market right now. And then I'm going to give out 3 bonus— 3 bonuses here, 3 danger zone picks that may seem attractive or popular, but these are stocks you should avoid. So we're going to tell you what you need to focus on buying, and then we're going to show you what you want to run away from. And then at the very end, I'll take some requests for specific tickers that people ask us about. So let's get going here. It's ugly out there. It's been scary. Now, the last week or so, things have looked better, but there are some dark clouds on the horizon that it could get worse at any point in time. And I've done a couple webinars about the game plan for 2025. I'm not going to go into the whole game plan for 2025. This is going to be specific about stocks you can buy no matter what happens with tariffs. But the bottom line is that we're not through this and not anytime soon. Look, what we saw recently, one of the sharpest corrections in the the history of the stock market, this is not ending. We are at the beginning of what I believe a major shift in the economic landscape globally and domestically that's not going to go away. We are no longer, I think, in a risk-on environment where everything goes up, FOMO, MOMO, Roaring Kitty, whatever you want to call it, the go-go days. We'll look back on that and laugh at how silly it was. that people bought SPACs and NFTs and meme coins and meme stocks. What a joke that was. What a waste of capital that was. What a grift that was from regular everyday investors to Wall Street insiders. And I'm glad to say that I think those days are behind us. It's not as easy as it used to be just to go buy 7 great stocks that were popular. We're seeing a, a retake on all that. And look, part of the reason I believe that this is going to be more of a long-term situation than a short-term situation is that everywhere you look, consumer sentiment, economic activity, these things are going down. There's no doubt that there's a permanent hit that's happened from the tariffs just because of the paralysis it puts businesses in with respect to investment decisions and how they're going to grow and how they're going to invest in a world where they can't be sure what's going to happen. Consumer confidence, its lowest level in 12 years. I mean, that includes COVID, folks. That's a pretty serious comp. And then corporate insiders, the people that know the most, what are they doing? Selling at the fastest pace in at least the last 2 decades. Right? So, if that's not an indication that maybe the good old go-go days are behind us, I don't know what is. This is an awesome chart we put together here that really, that's a really strong— nobody knows better. Like, there have been tons of great studies. About who knows what's going to happen most about the stock market. Top of that list, the insiders, the corporate people running the company. They know what's going on. So with tariffs crushing the market this quarter and earnings season kicking off already, these next few weeks are especially critical. And in New Constructs, we've uncovered some very specific opportunities for today's market— 10 overlooked but highly valuable stocks. And those words are just— don't do service to what we're talking about. These are not just overlooked and highly valuable. These are some of the best stock picks in a system that has proven to outperform. We have an edge, and we salivate over markets like today's because we're seeing more opportunities than we used to see when everything else was going up. Volatility is a gift that creates more overvalued and undervalued stocks just by definition. You start pushing things around, stocks get too overvalued, they get too undervalued, The best investors make their hay in markets like this. While overpriced stocks are finally getting exposed, some high-quality companies, businesses with strong fundamentals, have not only been overlooked but also unfairly dragged down. They're currently trading at prices that don't make sense. And we believe it's only a matter of time before their price catches up to their valuation. I think the market's getting more efficient. Not less efficient. We've needed a reset on a lot of things, especially the stock market, for a long time. I mean, for all the complaining, what's the market down like, 8% this year? What does that put us at, like November of last year? So the churning we're seeing is mostly beneath the surface. The overall stock market hasn't really been— it's not down that much anymore net, but a lot of stocks are down a ton, and some great stocks aren't down at all. The key point here is that it's time to get smart about what stocks you pick. You can't just play games. And that, my friend, is where the opportunity lies. Think about it. Fear often drives prices down irrationally. Good companies with solid fundamentals get caught up in the downdraft. Happens all the time. That's where we come in. We know what's— what the real value, the real profitability of businesses are. Then picking the stocks kind of gets easy. Our goal today is to help you identify the broken stocks, not broken businesses. Again, difference between price and value, the truth about profitability and what Wall Street wants you to know. At New Constructs, we've built our reputation on digging deeper, on using superior data straight from the SEC filings, including those footnotes that most people ignore. Footnotes is where a lot of great data goes to hide. See, while Wall Street's panicking or trying to get you to panic, we're leaning into superior research. Not only is it great right now for us at New Constructs because we can identify the best stocks, but we've already been in them. We've known going in. I'm going to show you some slides in just a second about how well our stock picking strategies are outperforming this year. Blow your socks off. But the point here is it's not just about finding the best stocks now. We've already— we've been in a lot of this stuff. We can prove the performances there because we've been, we've been saying to buy for a while. So while we're running the numbers, filtering out the noise, and identifying the stocks that are unjustly beaten down, that's what we're doing while Wall Street panics. These stocks are trading at a discount, not because they're bad businesses, but because the market is mispricing them. That's what today's session is all about. We're going shopping for bargains, stocks that get our very attractive rating and are poised for major upside. Plus, we'll also reveal 3 danger zone stocks you should avoid, the ones that look good but are actually fundamentally flawed. By the way, looks are deceiving. Wall Street's great at painting great pictures about, about stocks all the time. Remember, remember WeWork? Oh, they made— they painted a beautiful picture for that. How about Beyond Meat? How about Groupon? How about Robinhood? How about Peloton? Oh, those are going to be amazing companies. Yeah, whatever. You can't believe everything you see on CNBC or what you hear from Wall Street. You can believe us. If you want to invest like a true professional and stop falling for Wall Street's hype, then stick with me, because by the end of the session, you'll know exactly how to find the best opportunities right now in this volatile market before their price catches up to their true value. Before. So let's get to it. I'm David Trainer. Nice to meet you. Founder of New Constructs. I've been doing this kind of forensic accounting research for over 25 years. I'm the author of Modern Tools for Valuation and The Valuation Handbook. And I've also been studying machine learning and AI for the last 20 years. Our work, our new constructs technology, and our research has been studied and vetted by prestigious institutions: MIT Sloan School of Business, Harvard Business School, Ernst Young. Articles have even been published proving our research is superior in the Journal of Financial Economics. It's one of the top 3 peer-reviewed journals In the world. These institutions don't get convinced by accident. We are a discovery for them. We've helped the careers of some of these folks that have written these papers because they've been able to go to their peers and say, look, I found something you never knew about. We've discovered a new, better dataset for picking stocks. We've also been amongst the first to recommend many of today's most valuable stocks. So this is not just an academic exercise. This is proven in real-world stock picking. Such as Microsoft at $42 a share, Apple at $195 a share, Eli Lilly at $36 a share, even Nvidia at $0.57 a share. We— $0.57 a share, sorry. This is not an ivory tower service. This is a real-world stock picking service that's better than anything that's out there. And we've also been able to recommend many lesser-known hidden gem winners. Such as Williams-Sonoma up nearly 500%, Jabil up over 266%, Sprouts Farmers Market 428%. And today I'm going to show you how to get the latest very attractive stocks in today's market whose returns could rival the performance of any of our previous recommendations or even better. This recommendation is based on a combination of 4 key factors. Number 1, unjustly beaten-down stocks, things that are down more than 10% year to date. They have to get a highly rare, very attractive rating. So very few of our stocks get a very attractive rating. They have to be recently upgraded. We've also found in our backtest that when stocks get upgraded in our system, they tend to outperform. And it's got to have a minimum 1% dividend yield, which we threw on there to add extra safety. This combination of characteristics on stocks is unbelievable. Let me explain why. Our track record on one element of this, of this 4 combination of 4 items is super strong. Number 1, stock picking generally overall, we've been number 1 for a long, long time on SumZero, 46 straight months now, I believe it is. And again, SumZero is professional investors, not retail folks. These are people that pick stocks for a living. That's who we're beating out to earn the number 1 stock pick, number 1 spot for picking stocks for multiple categories. But what I want to emphasize the most here is that when you want to look at how good the very attractive stocks do as a group, I got proof. So Bloomberg created an index. Bloomberg came to me a couple of years ago and said, look, we want to grow our equity ETF business because we do really well in bonds. Everybody knows that Bloomberg is really big on the fixed income and bonds world. But they came to me and said, hey, we want to work with new constructs to create a bunch of new stock indexes and ETFs. But we know if we're going to be successful in that space, we got to do something different. And I know new constructs, we've got different stuff, so we want to work with you. So they created 3 indices. One of them is already an ETF, and so we're not really allowed to talk about that one yet because we're not a financial advisor, not a registered investment advisor. But I'm going to talk to you about 2 of those 3 indices. One of them is the Very Attractive Rated Stocks Index. This just holds the very attractive rated stocks. That's all it does. You want proof how good the very attractive stocks are? They were up 4.5%, over 4.5% in the first quarter while the S&P was down over 4.5%. Outperformed by 9% in one quarter. Now, these— this index was just launched recently, just a few months ago, a little bit before the end of the year. So in the first full quarter of performance, already beating the S&P by 9% in one quarter. So if you're talking about a pond of stocks to be fishing in. Very attractive stocks is an extremely good spot to start. That index, by the way, it's not available to the public. The only way you can get access to the very attractive stocks is through us. We have another index in the market. This one's actually my favorite because I like to say, look, we can outperform even if someone else picks the stocks. So in this case, the S&P 500, it picks the stocks. And all we say is that, well, instead of weighting them based on market cap, let's weight the stocks based on core earnings. So this is like a core earnings weighted S&P 500. It's outperforming by over about 1% in just the first quarter. So all we're doing different is saying, hey, instead of weighting based on market cap, weight based on core earnings. And doesn't it make sense? Don't you want to Wouldn't you want to overweight the companies that have higher earnings quality and higher earnings power? Makes sense that they would outperform. And by the way, you look at 5-year studies with the same data, just as powerful. We outperform significantly in the short term and the long term. So, you know, if you want to come to a place that knows how to pick stocks, I think this proves it. There's nothing better than live-traded indices by Bloomberg. Our ETF is on the New York Stock Exchange. You can look that up too. But these 2 indices are live traded on Bloomberg. You can look it up on their website. You can see I took this picture from a website. Stuff works, folks. Our stuff works. As much as I'd like to give myself credit for all this stuff though, it's number one ranking to the stock picking. It's really based on the proprietary RoboAnalyst technology And our stock rating system. I don't do all this work on my own. I'm not out there, like, studying all night reading filings. No, we created technology to do this because technology is how you scale. And, and, and if I have a methodology on how I want to do stuff, and I know I can't do it all myself or train people to do it, I'm going to get a machine to do it. My favorite thing about working with machines is that they do exactly what you say every single time. Now, that's the hard part. Because if you don't tell them how to do it exactly right, they're going to do it totally wrong. But we've spent a lot of time in new constructs, 20 years, to make sure that we have fed our machines only the most exactly right instructions. That's why you see we get the results that we get. And in this training, not only will I test some tickers against our rating system, some of your picks, I'll be showing you how to grab my number one very attractive and cheap recommendation today are enhanced, very attractive stocks is what I like to call them. Now, before I reveal the stock pick, I want to give you some background on our stock rating system. In the late 1990s, I started on Wall Street at Credit Suisse First Boston. I was hired to build a new, better earnings model to better understand a company's profitability. So I started doing this work again over 25 years ago, building these kinds of models, did all the stuff by hand. Within a few years, every major analyst at Credit Suisse was using my models. And in creating these models and working with analysts around the world, I learned that the majority of financial reports are inaccurate or misleading. I was an auditor before that. I was an executive compensation consultant before that. And so I've been doing this work for a long time. I know how the sausage is made, and it's really unfortunate how much misinformation is out there. And that's exactly how we enable you to beat the market and your peers. You get to have insights that the rest of the market don't know because they don't understand how misleading the existing data is. We find the data that gives investors an edge so they can make more money. That's what this is all about. We're not here just to sell you the same old slop that everyone else has. We have an edge proven with real stock market performance. This opportunity starts with companies reporting earnings based on generally accepted accounting principles, or GAAP accounting rules. If you've ever seen any of our research, we're constantly comparing our numbers to the GAAP numbers. Unfortunately, GAAP falls short when dealing with the complex nature of many companies. I know, I used to work for the firm that makes all the rules, FASB, and I've been studying accounting for More, more, more time than I care to admit. The problem with GAAP rules is that they're filled with inconsistencies and neglect entire parts of companies' operations. The income statement in particular, it's just one piece of the pie. You know that analogy about the 7 wise men touching the elephant in different places? Well, the income statement is just like having one hand on the elephant. You're not going to see the full picture. That also means they could be manipulated a lot, which is what Wall Street loves to do. But as a result of what GAAP misses, the rules end up distorting earnings by the millions, obscuring the truth about companies on the good side and the bad side. It's not just me saying this. There's hundreds of papers out there that have said it. I'm just the only one that's provided a solution. Solution to the problem, which is that you can't trust GAAP numbers not to buy and not to sell. Can't trust them on either side. To uncover a company's actual earnings, you have to study the footnotes. And that's where our AI-driven technology gets its edge. It meticulously scans thousands of filings and footnotes to uncover earnings distortions. Here's an example of a picture from our system. And by the way, every one of our footnotes can be audited back to the source. I'm not here to pretend I got a black box. I want you to see how much work we do. I'm proud of it. I love this click-through feature. It's one of my favorite things. I show it in every demo. But the point is, there's no substitute to getting to the truth. There's no shortcut except to go through and read all these really complex disclosures. And once our system finds these distortions, well, then we can correct them. You can't fix what you don't know about. That's what you got to— that's why you got to do this work. And once you correct it, well, then you can identify stock picks before the rest of the market catches on. Again, this has been proven in multiple papers, not just by Harvard Business School, but quant firms that have studied our data and written papers show that there's at least 2 weeks before the rest of the market catches on to any of our Footnotes insights. These insights are how we were able to find hidden gem stocks like Siga Technologies. When it was upgraded from unattractive to very attractive, it went up over 37% in the next month. Now remember, one of those key criteria to these special stock picks. Not only is it, is it a very attractive rating, but it's been upgraded recently. So, and we've noticed upgrading independently as a trend itself is very impactful. Cytosciences upgraded from unattractive to very attractive, up 32% in the next month. So over the last 25 years, I've found more than 30 different loopholes in generally accepted accounting principles that can distort a company's earnings. I've even published white papers on every single one of them. Why? Because I want you to know how much work we do. Go ahead, take a look at all this. It's no secret. I want you to see what it's like, right? And then, you know what, go read a filing and build a model and make an adjustment. Do that for just one of these. And you'll realize why no one else on Wall Street does it. It's way too much work. You'll realize why the technology that can do something like this is so incredibly valuable. Because it is super difficult, even for the most highly educated CFA, CPA, whatever you want to call it, to do this work for just one company, for just one adjustment. Takes hours and hours and hours for one period. So if you're doing it for like over 10 years, that's 40 filings. Takes hours and hours and hours. Now, sometimes these distortions occur by chance, but more often than not, they are deliberate. The flexibility in GAAP rules creates loopholes that companies can exploit to manipulate their reported earnings. In other words, the numbers can be manipulated to make earnings profitability appear more impressive than they truly are. You think they ever do that? And that's the tough truth about today's stock market. You cannot trust GAAP earnings or any earnings from companies or Wall Street. They mess with the numbers. There's so many papers and articles written about that over the years as well. Thankfully though, over the past 20 years, we've trained our system to identify and close the loopholes and uncover the true distortions among companies at scale. It helps warn investors about bad stocks in the market, such as Beyond Meat reported. This is, this is an example. Beyond Meat, you can see when it's all expensive up here on the left. Well, that was when accounting earnings were most overstating economic earnings. Groupon, you can see accounting earnings most overstating economic earnings. That's when the stock went down the most. Allbirds, same thing, counting earnings, overstating economic earnings, not a good thing. And I got some questions here recently about, okay, so can we screen for all these kinds of things in our system? Absolutely. Where do you think I got this research? Right now, a lot of these features available only to institutional clients. Some of these are only really available in our, in our database, but that's what makes us so valuable. Is that we have this incredible database where we can screen for things like recently upgraded stocks. We can screen for things like stocks that are recently upgraded and are down 10% and also have a dividend. It's the beauty of our system. So the system helps us spot the good ones, the bad ones, and the good ones, and, and allows us to quickly reveal those to our clients. And here's a good example. of a stock that got upgraded from neutral to very attractive over the next month, up 32%. LifeVantage upgraded from neutral to attractive, up 20% in the next month. These very attractive stock picks closely align with Warren Buffett's philosophy, where he, where he highlights the difference between a good company and a good investment. We love this quote. Investors making purchases in an overheated market, which is what we've seen for most of the last several years, need to recognize that it may often take an extended period for the value of even an outstanding company to catch up with the price they paid. We see this in spades. How many of you all have seen any, any of my special webinars on our reverse DCF model? Anyone see the NVIDIA one? Raise a hand in here. Or the one on IonQ, or the one on Amazon, where we did a reverse DCF to show people exactly how far ahead the price had gotten of the underlying— over the underlying fundamentals of the stock. Thanks for everybody for raising their hands. That's awesome. You guys saw those webinars. We'll keep doing those. Those are super fun. We call them reverse DCF case studies, and it's just math. It's just math. And what Warren Buffett is talking about here is just math. When the price gets ahead of the fundamentals, that's math, and that's not a good thing. So it's an investor superpower to find companies earnings earning significantly more than what the market perceives. And it's an investor superpower. If you can go in and find the flip opposite of what Warren Buffett is talking about, one where price is behind the fundamentals, that's an awesome thing to be able to do. And if you could do that in a way where you're looking at earnings that are higher than what the market thinks. It's a pretty amazing capability. We call it an investor superpower. That's how you get an edge like the greats. But you can only do that if you have the right research. Wall Street's numbers are based on faulty data and will not give you a good read on what's really happening. But we can. The key is getting your money in ahead of the crowd. It's important. Telling you what's already good that everybody knows about doesn't help. That's why it's sort of frustrating to see this Mag 7 thing. All it is was people just crowding into one particular trade, and that became its own self-fulfilling phenomenon because everyone was crowding into it. It was inevitable that it would blow up. It had to blow up. That's why I called the top for Nvidia at $120 or $127 or $130. It's come way back. Went past it, but it came back. Why? Because no one can avoid the law of gravity. The law of gravity is also relevant to the fundamentals of the business. You can't be so super overpriced forever. That's what our proven stock rating system is designed to do, help you identify disconnects between price and value. And we boil this all down into a rating system. Our ratings are powered by our roboanalyst AI, and it's a 5-point system. In order to get a very attractive rating, you see over here on the far left, you have to have good quality of earnings and good valuation. By valuation, I mean low expectations. So risk, you know, in a world where you can't predict the future, the best thing you can do is think about risk-reward. You want to position yourself to have the best risk-reward in all things. Don't take unnecessary risk when it's not going to be compensated with a commensurate or more amount of reward. So how do you do that when it comes to fundamentals? Well, you find businesses that are really profitable. But whose stock prices are behind the profits, underestimating the profits and not reflecting the profits. That's what's— that's how you get a very attractive rating. And our AI has the ability to comb through thousands of government filings with precision and analyze every line and every footnote so that you can get to the truth. Not surprisingly, executives from some of the top firms in the world Have been using our system for a long time. Our, our superpower is, is really not just being able to take the data out of filings. That's, that's easy to do, but it's understanding what the data means so that we can really hone in on the earnings distortions, but do so across thousands of publicly traded companies. Doing it across thousands is what allows us to know that what we have is the best. If we're only looking like at 50 companies, well, then we don't have a lot of companies to choose from. Those 50 could be the worst 50 in the whole, in the whole market. But if we're only looking at 50, we gotta find the best. You know what I'm saying? When we're looking at the entire market like we are, 3,300 stocks, that's really, that's doing something. So our rating system has got 5 key metrics I wanna go over real fast. You've got economic earnings versus reported earnings. What is economic earnings? That's the true comprehensive earnings of a business, also known as EBA. Or economic value added or residual income. If you read all like the really fancy textbooks on finance and Warren Buffett, they talk about this stuff all the time. I've implemented it for you. I've implemented it. I'm taking it off the bookshelf and putting it on Main Street. So, we're looking at how economic earnings reconcile with accounting earnings because, look, if they're the same, then what's the point? And what our rating system does is identify where they're different so that you can find companies with understated profits or misleadingly overstated profits. Then we look at return on invested capital, probably the best ratio in the world. One ratio, you look at one number for companies. I want to know how much cash flow that company is generating relative to how much capital has gone into it over its life. Same way you measure your money manager. If your money manager made you $1,000 last year, that could be good. It could be bad. If he made $1,000 on $1,000 of capital, that's great. If he made $1,000 on $100 million of capital, not so good. The numerator and the denominator matter. Guess what you never hear Wall Street talk about? The denominator. So we've got proof that our numerator is superior. That's core earnings, net operating profit after tax, core earnings, very similar numbers. Both of them take into account the unusual gains and losses that distort earnings. But then we've got all this work on the balance sheet. That's part of our rating system. And then the next 3 here are valuation metrics where we look at 2-year average free cash flow yield. We have the best measure of free cash flow. We look at a 2-year average because free cash flow can be very noisy. And we exclude cash from the equation because companies can mess with cash and that can affect free cash flow. And cash balances really ultimately have no impact on the underlying economics of the business on a, on a periodic basis. The price-to-economic book value, my favorite valuation metric, because it so simply captures what— how much of the stock price is based on future profits, or how much the stock price might be predicting a permanent decline in profits. And then the market implied growth appreciation period, the strongest metric of all 5 of these. It's based on our reverse discounted cash flow modeling system where we do all the reverse DCF studies that you guys raised your hands about. You guys have seen that at work. It's a super powerful tool. Super powerful. The most sophisticated valuation tool in the world. And we have it on over 3,000 stocks. Super powerful. No one else has that. Super great metric. And we're really, we're really proud to have that as part of our overall rating system. And then the best thing about all this is we take all the sophistication, all this data, all this modeling. And we make it simple. We're not here to blow you away with complexity. I don't believe in that. I don't think that's doing right by investors because that's just an attempt to disempower you, to make you more dependent on me, to just trust me that I'm going to give you all the right tools and all that. That's what the financial advisory industry has mostly been about. Don't get me wrong, most advisors are good people, but a lot of them are looking to just make you feel disempowered, overwhelmed by it all. So you just trust them. Don't ask too many questions. I'm going to give you unparalleled transparency, and I'll let you get down as deep as you want. I'll show every metric. I'll show every definition, but I will make it simple for you at the end of the day. Green means good. Red means bad. Green is very attractive and attractive. Bad is unattractive and very unattractive, or red. All 5 metrics are important to giving you a good picture of the business. the best picture of a business. But again, it's boiled down simply. Green means good. Red means bad. Our rating system is so good that Harvard Business School wrote— there's been a couple of Harvard Business School papers on New Constructs, but one of them is specifically just on our stock ratings. Guess what? The paper proves that our ratings outperform those on Wall Street. This is all the way across the spectrum. Very unattractive, attractive, neutral, attractive, and very attractive. So this paper was out before the Bloomberg index came out. And it said all these ratings are better. Not surprising. I mean, Wall Street, to be honest, is kind of a low bar for picking stocks in terms of ratings, but it's great for it to be systematically proven in a paper published by one of the most prestigious institutions in the world and will soon be in a peer-reviewed journal, The Accounting Review, if it isn't already. We're also the only stock rating system with an official US patent behind us. If you know of another firm that has that in there, has a patent, a research firm, let me know. Put it in the chat. I'd like to know because as far as I know, we're the only research firm that has a patent and the only research firm that has multiple papers by prestigious institutions published that prove the superiority of our data, our analytics, and our ratings. Let me know if you got another one. As far as I know, we're the only one. And a lot of this is all about AI, folks. I don't like to talk about the AI so much because I feel like it's kind of a dirty word because everybody's kind of bragging about how they— our AI is not sexy, by the way. Our AI is built on a lot of blood, sweat, and tears going through filings. If you paid attention to AI at all over the last month, few months, or years, It's all over the news. But if you pay attention, like, the really smart folks that, like, will go into the details, and it's hard to follow because it's really complex. But if you, if you listen to any of those podcasts or interviews, what you're gonna find, then we're gonna— they say every time is that they're running out of training data. And they're not running out of data per se, because the internet's like infinite. They're running out of training data. What does that, what does that mean? It means high-quality data. Because if you're gonna build a machine based on a particular set of data, and I told you my favorite thing about machines, they do exactly what you say. So if the data that you put into them is not exactly right, what's gonna happen? The machine's gonna make mistakes. That's why all this AI stuff based on the internet is not working because it's based on the internet. What percentage of the internet is reliable? Maybe 50%. I don't know. Our AI is based on a perfectly manicured, curated, and developed data set. From the beginning, the most important thing was not how many companies we covered, not how many line items we collected, but how correct it was. Our system is based on that. Years and years of culture based on perfectly curated and organized data. That's what it takes to get firms like Ernst Young and Harvard Business School to want to write a paper about you. It's what it takes to get firms like Bloomberg to want to create index based on your data and your ratings. So a couple warnings about AI just in general, my friends, coming from somebody who I would say I'm an expert in AI because our AI is proven to work. Number one, AI is not magic. You're not— there's no experts out there like writing some formula. Go figure all this stuff out, machine. Go. Poof. And the machine goes, figures it out. No, machines aren't that smart yet. They need the human to do it first. That's what it's— that's why it's called training data. The humans put together the training data, which is exact, exact instructions on how to do things. And then the machine can learn from that. Number 2, I've said this 100 times, bad inputs equals bad outputs. The machines are only as good as the data that fuels them. To trust an AI, you need to be able to audit the data. If you can't audit it, they're not willing to show it to you, then don't trust them. They're faking it. They should be proud of their data. ChatGPT, all these other popular stuff, all these popular big AI things out there, they're not reliable because there's no way to audit the entire internet. And they know that. That's why they got hallucinations. Reliable AI has to be based on a focused dataset. And I say focused, small enough that someone can go in and make sure that it's been properly curated for a machine to use it. By properly curated, I mean no errors. No, any error is going to cause a bad signal. So I can— I think you can say the quality of our signals are really strong. So what does this really mean for you at the end of the day in terms of a technology? It allows you to do research that most people don't do or can't do. It also allows you to do the proper diligence, right? So for all of you advisors out there, You want to do right by your clients. New Constructs helps you do that in a new, better way. And another thing is keeping— keep in mind, look, as Tom Brady says, if you want to win in this world, you have to be willing to do things other people will not. The footnotes research from our AI, nobody else is doing that. It's proven. You want an advantage, do things other people will not do. And our robo-analyst technology delivers alpha from these footnotes. And that's a big part of what the Harvard and MIT paper goes to great pains to prove, is that the market is missing footnotes. They don't have the time or interest. A lot of them don't believe fundamentals matter. That's part of why we're crushing it in this market, because all those folks that were like, oh, fundamentals don't matter, I don't know what you're talking about, I'm just going to go FOMO, MOMO, Mag 7, NFT, SPACs, whatever. It's too easy. Don't make me do work. Well, guess what? Those easy days are over. The other part of the problem here is that it's really hard work to get to the footnotes. They're buried in filings that are 200+ pages long. Some of them are 2,000 pages. When I started, a lot of the filings I read were like 10, 15 pages. This is in the mid-'90s. And, you know, and they're like, the long ones were 40 pages. And you immediately get skeptical because guess what? Like, an income statement takes 1 page, balance sheet takes 1 page, cash flow statement takes 1 page, statement of shareholders' equity, 1 page. Just 4 pages for the financial statements. And so if there's 200 pages for footnotes, footnotes in the management discussion and analysis, hey, why do you need that much space? It just makes it a lot harder to find the needles if the haystack is bigger. That's why we do the proper diligence. And by the way, this process would cost you millions to do this on your own. That's— this is, this is all again why no, almost nobody does it. It's too expensive. It's so much easier just to blast out buy, buy, buy, sell, sell, sell. Make it a game. Make it entertainment. People are paying a lot of attention to this entertainment. It's a very successful business. CNBC does great. Roaring Kitty does great. Reddit does great. They're preying on you because a lot of times people want to be entertained more than they want to be informed. Unfortunately, that can work in the short term. Doesn't work so well in the long term. Another sad truth: 96% of stocks covered by Wall Street are all listed as a buy or hold. This comes directly from this report from 2000 in December 2000 last year, and that 96 rose at the end of the year. By the way, interesting that it would rise, right? To lagging indicator too. You know another funny report I saw from some very smart people. They publish a daily newsletter. Guess where they said the place, the best place to find Wall Street's best recommendations? The best time to buy stocks is when Wall Street rates it a sell. So, if you want to use Wall Street ratings, use the opposite of what they say, if anything. The reason for that is because their paychecks depend on you buying stocks. That's how they make their money. Wall Street people make money selling stock. They need you to buy. So when they've capitulated to the point when they're marketing a sell, they got no chance of banking business, no chance. It's already probably already gone down. They're not going to upset anybody. That's when it's probably going to bounce back because they wait till it's too late because it's only after they've exhausted all attempts to probably prop it up or to get banking business from the From the company. But keep in mind, Wall Street is in major conflict with you. Now, Wall Street wants you to, to buy or hold 96% of stocks. Less than 13% of our stocks have an attractive rating or better, and only about 4%, less than 4%, are listed as very attractive. We're the opposite. Surprise, surprise. Good stocks are hard to find. If it was that easy, everybody would outperform. But of course, that's impossible. Now, we've already mentioned that Wall Street wants you to either buy or hold over 96% of their stock recommendations. But according to recent data, 57% of Wall Street ratings for stocks are listed as buy compared to our 13%. Here's another study. Buy is over, over half. Over half. We're just at 13%. And it's not just the big Wall Street firms. It's the firms that also claim to be somewhat independent. And I say somewhat independent because firms like Morningstar, you know where they make a lot of their money? From fund companies who pay to license the Morningstar rating. By the way, New Constructs does ETF and mutual fund ratings. I don't talk about that all the time. We do those too. They're based on the ratings of the underlying stocks that the fund holds. Sounds like a good way to do things anyway. We're a lot different from Morningstar. Here's a report I found from them. You can see that all these Morningstar top ratings—that's five stars for Morningstar—a one, whereas we give it a four. That's unattractive. You can see a difference in the majority of ratings. We're the same sometimes. Every now and then we're the same as Wall Street, but not very often. Not a lot of overlap when only four percent of your stocks get very attractive. And probably only 4% of their stocks get sell. So not a lot of overlap. Here's some more examples of misleading Wall Street buy ratings and how they compare to our honest ratings. Sunrun, according to Wall Street, was a buy or a hold most of this year. New Constructs is attractive or very unattractive. This is a chart directly from our professional subscription site where you can see The rating, you can see red is very unattractive and unattractive. Orange just shows what the rating was over this time period. Well, guess what? Guess what? Sunrun is now down 35% year to date. Wall Street said buy, we said sell. According to Wall Street, Affirm, it's a buy rating. It was a buy or hold most of this year. New constructs, it's been unattractive the whole time. Who's right? I don't know. Firm down 24% year to date. How about for Warby Parker? Buy or hold so far this year? We've said it's unattractive. What's the result? Down 23%. I said this before and I'll continue to say it: trusting Wall Street research is like trusting tobacco companies saying cigarettes are not harmful, addictive. They will lie to your face, and they have for years. I was on Wall Street, so I know what I'm—I know I'm talking about. I'm speaking from direct experience. They got a big, huge penalty from from Elliot's the the the the attorney general back in the turn of the century for how much lying they did. They still do it, and they are allowed to do it as long as they disclose it in their reports. And if you read the disclosures in any Wall Street report, you'll see. By the way, we could have positions opposite of what the rating on this report says. It's there. So why is our research different? Well, number one, we don't lie. But the main difference, all that aside, is that we've done the diligence. We've done the work. I told you about all those big filings that we've gone through, that, that how long these filings are. We analyze hundreds and hundreds of millions of pages of SEC filings. And in that process, we uncover data that is often legally buried in the footnotes. You also may be wondering, sure, your stock ratings and new constructs are different from Wall Street, but how do we know they are better? Well, how about the fact that we've been, been ranked number 1 by SumZero every month for 46 straight months in at least one category? Again, that's versus buy-side professionals or people that invest for a living. We've gotten top-tier institutionals— institutions proving the superior superiority of our ratings at every level. The data is better, the analytics are better, the ratings are better. Makes sense. Better ingredients, better ratings. Look, based on our current data, less than 4% of stocks get the very attractive rating. And then of these stocks, even less are recently beaten down, even less are recently upgraded, even less have a dividend of more than 1%. It's important to know these picks go above and beyond the typical rating system. They are considered outliers even amongst the very attractive rated stocks. They're not in any kind of model portfolio yet. Kind of too few stocks we could actually put into a model portfolio, to be honest. We need more than that, I think. But it's also because it's a fresh recent discovery. There's special stock picks that could get a new type of rating. It's like enhanced very attractive rating, because not only are they rated very attractive, they have a new set of criteria which are unjustly beaten down Very attractive rating, recently upgraded, and a minimum 1% dividend yield. Therefore, these stocks would be considered an enhanced version of our very attractive stock picks not found in any of our current model portfolios. Look, we've been building and refining our data for over 2 decades, and it gets updated daily with new stock prices and any new filings from the SEC. Every day we update our models on over 3,400 stocks with the latest stock price and financial data. That means there are always new ideas coming out of our research. However, we still get very few stocks with these criteria in place, these special 4 criteria. And when we do find these special stocks, we pay extra close attention because most of the time these stocks will have us shouting, it's time to back up the truck. Now we're going to do a free Demonstration here on three danger zone picks: MDB, ICE, and EXC, and show you why they are dangerous with our proven superior research. So let's go to the site here. MDB first. MDB. So this is a $158 billion sorry $12.8 billion company. Stock suspended, suspended rating because the required cash is a little bit funny. But look, it's a very unattractive rating. I mean, a 90.9 price to economic book value is crazy. Credit rating also neutral, not good. Highly recommend you avoid this stock. Next on the list, ICE, International Intercontinental Exchange. Stock rating, very unattractive. 3.2 price to economic book value. Reasonable valuation. You know, the MDB number is absolutely crazy overpriced, expensive. This one is very overvalued, but it's also, you know, it's not a technology company, so it's probably not going to ever be crazy overvalued. But yeah, this business is looking so good. You got negative economic earnings with highly positive accounting earnings. It's a big difference, folks. You go down here, look at this, where professional members get to see this kind of detail. Look at the, look at the growing difference between economic earnings and accounting earnings. Not a good, not a good thing. Return on invested capital headed down. Margins dropping. Free cash flow good in the past year, mostly bad overall. Very negative free cash flow. Bad stock. Let's go. EXC, Exxon Corp. Very unattractive earnings distortion score. Miss. Bad economics, bad valuation. You want to avoid these stocks, folks. These are things to avoid. New Constructs helps you with both best stocks to find in the market, stocks you want to avoid. That's part of the purpose of New Constructs, the best and the best. So any other questions about this enhanced, very attractive stocks bundle, please let me know. And if you haven't already, sign up now before the window closes. It will not be open for long. All right, Kyle, I think we're ready to take some requests. Let's do 3 more stocks for folks, uh, the most popular stocks. For the first ticker, we've got ticker APP. Is this AppLovin, or did we cover this? Are we sure? Here we go. Yeah, AppLovin. Yeah, this has been a very popular stock lately. People ask me about it all the time. I'd say avoid this like the plague. Look, it's got good economics. Green is like good company, bad stock. And I've been saying good company, bad stock, I feel like for 7 or 8 months when I've been doing a lot of these webinars for other companies and, and for CNBC or whatever it is. And these are the companies that are getting crushed right now in the current market because everybody was piling in, popular stock. But this valuation, more than 100 years of profit growth baked into the current stock price. An 8.4 price-to-economic book value ratio. This means 760% of the, of, of, of the stock price is based on future earnings. So yeah, not good. Not good at all. Not good. Very expensive. Very dangerous. What's our next one, Kyle? Ticker COF, Capital One. Yeah, I know these guys. This is one of the first companies I covered on Wall Street. loved the business. They were really into— they were doing CRM before CRM was its own thing. And their ability in the early days to be better targeted analytics for giving people debt, super successful. So here we go. We got like mediocre company, cheap stock. That's a tough one. I think they're still digesting the Discover acquisition. So we really won't know how the quality of earnings look. But based on the price, it's probably not going to be good for quality of earnings. But the stock's pretty cheap. So if you think that they can, they can fold this acquisition in and, and, and get back to their higher return on capital ways, then this could be a good business. This could be a great stock. Let's see, economic earnings, you know, were as high as $5 a share before dropping negative. Return on invested capital was way higher before dropping negative. So there's potential for these guys to turn stuff around. If you think the return on capital is going to go back up to 10%, Then this could be a great buy. Could be a great buy. Depends on what you believe about what's going to happen here, but it's not guaranteed. All righty, Kyle, we got one more. Yeah, last one. CIX. CIX. Hmm. New one. Smaller cap guy. Attractive. Decent business. Decent valuation. I don't know much about what these guys do, but yeah, that gets an attractive rating. Economic earnings and accounting earnings moving kind of the same. Return on capital coming down but still pretty high. No PAT margin dropped here recently. Free cash flow— that's the other thing that I talk about in my game plan for 2025. Those future earnings numbers out there, nobody knows. They're more likely to be going down than up. So buying stocks that look expensive in this market Recipe for disaster, in my opinion. Recipe for disaster. The PE on the S&P is still really high. Still really high. I think there's room for multiple compression for the S&P, but the E in the PE ratio likely going down. So I think it's hard to argue that the E will not go down given how many, how businesses have been paralyzed by all the tariff talk. And then here's the stock price versus economic book value. You can see economic book value coming down quite a bit here. Not a great sign, but still pretty cheap. Okay, that's 3 stock picks. 3 stock picks for today. Thank you guys for being with us. This has been a great training.