Buy This, Not That: The Answer Key to Beat the Market in 2026

Welcome, everybody. Excited to see you today. It's an interesting day in the stock markets. I don't know how many of you guys follow us and know our research, but we recently published a piece on Allbirds and how we had pointed out before the IPO that it was a stock that was effectively dead on arrival. And after going up to a $4 billion valuation, they sold out for $40 million. And now it's up 600% today because they're adopting AI. So I think that's maybe a perfect case study to kick things off, break the ice, and explain in a real-world example exactly how much value New Constructs adds and how different we are from other research firms. We're going to give you the truth before everyone else. And Allbirds is a great example of that. Here's a picture of the report. Kyle, you don't mind, you want to drop that into the chat, that'd be great. But yeah, before the IPO, we cautioned, don't buy this thing. And it debuts at $2 billion, goes up to $4 billion, sells out, $40 million. People are getting wiped out, one penny on the dollar. And we told you before the IPO. And this is the kind of insight that New Constructs brings to bear at all times. And with that, I'm going to kick things off. This is a very special training today. We're always trying to bring new exciting things to our clients, but we've now developed a new feature and a new product specifically designed for a wider audience. We've been doing institutional research for 30+ years, and we are now democratizing access to unrivaled and never before available insights to the entire market. And this is what I would call the answer key to the stock market. It's gonna show you what to buy and what not to buy. Truly an answer key based on unrivaled analytical rigor on thousands of stocks, ETFs, and mutual funds, over 10,000. First, I need to make sure you're clear in terms of disclosures and disclaimers. We are not investment advisors, do not give investment advice. We are here to provide information. Please talk to other people about getting specific investment advice. By way of quick background, David Trainer. I was on Wall Street before, during, and after the tech bubble. We've run a hedge fund, published a chapter in a book, been doing AI machine learning research for close to 30 years now, and have guest lectured at all the major business schools, including just last week at Harvard Business School. And we have, and I've had over the years, some of the biggest and most successful investors as my clients and as our clients for the purpose of providing investment research that adds value. Please speak up in the chat. We want to hear from you, especially if you're new. We'd love to know whenever we got new folks with us. And also get your votes in now for the tickers you want us to cover. I can't cover them all. Those tickers that are mentioned the most will be the ones that we get to cover. So let me get straight to the point. I want to be direct with you today. If you own stocks at all right now, what we're talking about today matters a lot. We're in a buy this, not that market. It's not just buy everything. I think you've seen that not everything is deserving of your capital. Some names are overpriced. Some are hiding major risks. And some value is just being completely overlooked. Volatility is the new normal. It's not just a buy-everything market. We're seeing geopolitical stress after stress. We're seeing technology disruption like we've never seen. Earnings distortion risk is at its highest. And of course, faster headline cycles. There's new news every day. Allbirds is a great example. We're avoiding bankruptcy by selling out For 1 penny on the dollar, and then we're going to pivot to AI. Nothing more than a scheme to help insiders get out of the stock at a higher price before it goes kaput. And here's the thing that's important. I don't know if it's fair to believe that there's an end to all the issues rattling the market in sight. The first kerfuffles, to say the least, were Gaza. Then there was Venezuela. Now there's Iran. Cuba may be next. What about Taiwan? We still got Ukraine, Russia, and China to deal with. The takeaway is that there's ongoing uncertainty globally. You cannot control these events, but you do feel them through your portfolio. Rotations speed up. Stocks are moving up and down faster. Volatility is worse. The takeaway is that there is less room for error these days. That's why investors need a framework that can hold up even when the issues persist. You've got to have something besides headlines and intuition because markets can look fine, headlines look strong, indexes can rise, sentiment can stay upbeat while the data and the fundamentals say something entirely different. Great example is Allbirds. All kinds of great narrative. Everybody was saying great stuff. We saw something very different that caused us to write a report before the IPO saying, do not buy this IPO. It will hurt your portfolio. Because there is a difference between what companies present and what the world often sees. Reported numbers, those numbers in those filings, those press releases, they mislead. Footnotes matter. The data that they bury in 2,000-page, 200-page annual reports and quarterly reports, it matters. Adjustments to the reported numbers matter. Truth is often hidden by the headline. The gap between what the market believes and the underlying economics is where opportunity lives. It is also where the risk lives. Our work has always been focused on that gap. Understanding it, measuring it, and helping investors act on and profit from it. Now's the time to move from passive watching to active screening for you or your clients' investments. It's not enough just to ride the market up anymore. And today specifically, we also want to make tax day meaningful. We want to add a little joy to your tax day, not just dread. We're going to make today a reset point for you. A day usually associated with writing a check. We're going to reverse that dynamic and give you a check to cash in the stock market. Think of this briefing as your stock market refund. We're going to give you the answer key that you need to beat the market so you can make money and not just have to be a passive investor. Timing is on our side. Historically, at least, April is typically the best month for global stocks. And you don't need more ideas. You don't need more data. You don't need more headlines. What you need is better filters. Right? I think we need filters for everything, right? Whether it's everything in the media, everything on the billboards, everything in the theaters. Goodness gracious, sometimes the previews of movies are so bad, I almost want to leave. But in the stock market in particular, it is a buyer beware world. People are all over you trying to get you to buy, trying to get you to sell, trying to get you to do what makes them money. What you need is better filters, better rankings, better exclusions, better evidence, better research and diligence. What does better mean? What does that look like? We're going to show you. We're going to give you the filters used by the truly smart money. In New Constructs, we pride ourselves on being able to detect where the best buy and sell opportunities are. You don't have to take our word for it. Proof is in performance. We do this extremely well. Our stock picking has beaten 16,000 buy-side professionals to claim the number 1 spot in multiple categories for 58 straight months. That's almost 5 years running, folks. And this SumZero platform is buy side only. This is not a bunch of folks taking moonshots with penny stocks. Professional investors talking about mature, typically large companies. There's no luck involved here. Maintaining this number one ranking in multiple categories on this platform is no small feat. Getting there is no small feat, and doing it for 58 straight months is nothing short of remarkable. Add to that the fact that our work has been vetted and validated by prestigious institutions— Harvard Business School, MIT Sloan School of Management, Ernst Young, the Journal of Financial Economics. All these institutions have published papers proving the superiority of our data, our analytics, and our stock ratings. I guest lecture at Harvard Business School usually once a semester. I just was there last week. I'm going to be there again in November. They bring me in to talk about how AI is changing the investing world. And they trust me because we've got an AI that actually works. And when I say works, I'm talking about actively traded indices and funds based on our research. For example, the Core Earnings Leaders Index beat the S&P 500 by 900 basis points in 2025. Up 27% versus the market up 18%. Over the last 5 years, it's beaten the S&P 500 by 26%. Then there's the Very Attractive Stocks Index. This index is based entirely on all the companies that get our very attractive stock rating. That's a small list compared to what Wall Street says is very attractive, but that list has been a strong outperformer, beating the S&P also by 26%. Over the last 5 years. And then there's my favorite. I love all my children equally, but this one is my favorite because I like to say we don't even have to pick the stocks and we can outperform because the Enhanced S&P 500 Index, it's based on all the same 500 stocks as the S&P 500, but we reweight those stocks. We weight them based on their core earnings edge instead of market cap, and we get outperformance. Pretty impressive. So we get— we have outperformance based on picking stocks based on core earnings advantage. So just based on that core earnings number, there's alpha in our ratings. And then there's just alpha in weighting stocks based on superior profitability metrics like our core earnings number. And then probably maybe the biggest validation of all is that Google invested several million dollars in us to build us an AI agent to demonstrate the power of their technology. This quote from the head of professional services at Google Cloud is all about being able to demonstrate the power of AI when it is endowed with, when it is seeded with proprietary proven data. And so Google Cloud built this agent. FinCites are going to be talking about it in Vegas next week. We're going to be launching this on our website soon. The takeaway is one of the most respected, largest, smartest firms in the world worked directly with us to create the only AI agent for investing that ever created. They did that because they know our research is reliable, and they knew that when they could power AI with reliable information, you get something special. So anybody can claim they have the best research tools for stock picking. Many people do claim they have the best, but no one else has the proof that we have. And today I'm going to show you how you can get this research at a much more accessible price point. Now we're in a very narrow window right now, especially with the geopolitical uncertainty and heavy market volatility. Everybody's feeling it this year. It's been a tough year, and every investor wants to address problems before they manifest. It doesn't do much good to do it after. What you need is something that gives you an advantage before. You also want to find alpha in the stock market. If you're not prepared, though, You'll be caught flat-footed, and you'll miss both. You'll miss both the protection and getting the alpha. But with the right tools, you can anticipate. You can position yourself before the market catches on. That's the real opportunity. That's how the smart money does it. And here's a fact that most investors don't know: just 3.4% of stocks. Generated all the net wealth created in the U.S. stock market since 1926, and all of it. Just 3.4% of all companies, just 3.4% generated all of the wealth. There's the chart. 3.4%. Just 2% did 90%. So this makes your job brutally simple. Avoid the 97% that destroy wealth. And find the 3 that create wealth. Now, that's not easy in today's world because Wall Street recommends 96% of stocks as buy or hold. But in New Constructs, we don't do it that way. We help you spot that top 3% in a way that no one else does. And we also don't hesitate to identify the bottom 97%. Allbirds is an excellent example. We spent 20 years building systems and tech to do it right. This isn't some fly-by-night new AI thing. Allbirds just says, hey, we have to fire sale for one penny on the dollar for all of our investors. But, you know, we're going to get an AI and the stock jumps up. No, that's not what we're about. We've been doing this meticulously, steadfastly, carefully, honestly for 20 years. And that's what it takes to build something special. So the problem for AI for most investors is that it's really not very useful. In fact, it can be dangerous. We're actually gonna do another podcast next week with a major registered investment advisor who was using cloud and it just lied to him. It lied to him. And he said, why did you lie to me? And it said, sorry, I have to admit I did lie, but it was not with an intent to deceive. Look, everyone who's probably used any AI know that hallucinations are a feature, not a bug. The AI is gonna tell you whatever it needs to tell you to keep you engaged. What's the most important thing for AI? Anybody wanna take a guess? What is the number one goal for every AI? Is it to give you right answers? No. The goal is to keep you engaged and not use another AI. So the last thing it's gonna do is say, oh, I don't know. I can't give you an answer because it knows that's what's gonna make you go to another AI. So why— so let's go into some more reasons why AI is not very helpful. Number one, it's basically summarizing the internet. That's all it can do. It's not designed for financial analysis. It's built on inconsistent, incorrect data. And the result? It just picks popular stocks. It looks at consensus. That's the best it can do. Generally, large language models are designed to summarize data from lots of sources. They are not designed to discern or be financial truth engines. Not been able to teach machines how to do that yet. New constructs, it's a different story. But let's take a look at what you get when you ask AI questions like, what are the best tech stocks? Here's what we got from ChatGPT. See here, nothing, nothing too earth-shattering. Vertiv is something that maybe not everybody's heard of, but basically you're talking about the most popular stocks in the market. Gemini, same thing. Popular stocks. Claude, same thing, reporting and linking to basic obvious news sources. There's no real insight here. What we've noticed from these guys is that none of these stocks actually get a good rating in our system. So all the stocks that the other AIs like, we don't like. They don't make the cut as the top 3%. Second, There's no fundamental research there. There's no digging behind the numbers. There's no real analysis. Third, they're all doing the same thing. Looking at past price performance and the largest market cap. What's done well in the past and what's big. That's a common thread amongst a lot of analysis out there, Wall Street and AI. Please keep in mind, our AI agent and stock picks Are proven to outperform. I'm not just talking about news and headlines and narratives, whatever. I'm talking about the proof I just showed you from sum zero, from the stock market and live traded indices, from Harvard Business School, MIT Sloan, and Ernst Young. That's proof, my friends. So we can confidently state we know how to determine whether a stock is truly an attractive buy. Or not. We notice though that the free AI tools tend to select stocks that are popular, big cap mega stocks, often overvalued because it's old news and they're not attractive. Telling you what is popular is not adding value. Popular is often the easiest but usually not the best way to do anything. Where most companies are going wrong with AI, and it's something I talk about on a regular basis, whether it's at Harvard Business School or with local RIAs or our clients who run billions of dollars, some of the biggest quant funds in the world. The messaging I have is the same, is that people are paying too little attention to the inputs. People just want great output. They don't care what goes into it. They just wanna believe it's great. But any of you that have done anything great, you know what it takes. That's a lot of hard work. You know that the input is often more important than the output. You can control what you put into something and you hope that maybe it produces something good, but you care most about input because you're not giving up. You know, you got to do it right. It's got to be built on solid ground. That's what new constructs is all about, because anything else is garbage in, garbage out. You're only kidding yourself. You don't do the workouts, you're not going to be able to finish the race. So how do we build our system? We started with superior data from the beginning. Over 20 years ago, the original technology at New Constructs was a very simple application that combined the actual filings, the database, and a parsing tool. And that parsing tool meant that we were able to automatically collect a lot of data, but it was all being viewed, edited, audited by experts. Every single data point. That's what we started. Clean slate. We didn't take any data feeds from anybody. Nothing from anyone else around the profitability and valuation of stocks. Nothing. We built it from scratch on our own to make sure it was right because we knew that's what our clients want. Millions of other data feeds out there have been out there forever. No reason to recycle that and try to pretend that by recombining some other buddy, somebody else's data points, we can do something better with it. Trust me, there's been billions and billions of dollars of quants been trying to do that for 30 years. We started something new and fresh to create something special. And here's the way I like to think about it. And this is a great slide. I use this in all my presentations. I love showing this to the business school students because I want to help them understand in the beginning, financial statement analysis, that's the easiest part. That's the easiest thing to teach a machine. Right? And as we evolve as analysts, We follow the same path here. I know I did in the beginning. Income statement. What does that mean? I figured that out. Balance sheet, cash flow. And then I came to footnotes. I remember my first audit job. I found an inconsistency and my boss held up this folder, had CYA on it. And she said, you know what this is for, David? I was like, ah, no. She goes, what you just found. Thank you. I was like, all right, that's how the game is played. So look, yeah, financial statements. footnotes, and then you can do advanced modeling on that to get incremental insights. And you can put those insights into trading strategies that produce novel alpha. And when you have something like that, then Google comes to you and says, we want to make an AI. We want an AI based on real data, reliable research. And that's what we spent 20 years building, a truth engine. Our robo-analyst technology was built for one purpose: to read financial filings like a forensic accountant at scale. And we correct the distortions, all of them— hidden off-balance sheet debt, unusual gains and expenses that cause earnings to jump up and down— to calculate true recurring cash flows. The result is that we convert misleading reported numbers to a company's true economic reality. That's why I've been guest lecturing at Harvard Business School and other places for the last 10 years. I'm teaching their students how to do that, and now I'm teaching them how AI can do that. It's only because I did it and our team did it for so long that we are qualified to teach a machine to engage in this very sophisticated activity. And because we're so good at what we do, We're not a black box. We want you to see our work. We have a very clear and powerful auditing feature that our institutional clients love. Clients can audit every single data point back to the original source filing. I'm going to give you an example of this in just a second. No one else can do that, not for the footnotes. A lot of people can show you income statements and balance sheets. Remember income statement and balance sheet? That's financial statements. That's the lowest end of the evolutionary ladder. And I'm glad they can show that. But footnotes and how they make specific adjustments to provide proprietary alpha-generating analytics, no one else can do that. That's our secret sauce. That's our training data. That's what gives us an edge. And here's a peek. This is exactly from one of our models for our institutional clients. They want to know where the earnings distortion from hidden items comes from. Those are footnotes items. We show them exactly. Here you can see on page 100. of Meta 2022 10-K. Here's what we found: restructuring charges. They're buried in cost of revenue and research and development and SG&A, right? Buried in these income statement expenses. We pull it out. That means you can't find it anywhere on the income statement. You can only find it in the notes. Here's another example with a firm pulling out sublease income. This is not part of their operations. A firm is not in the business of renting properties. It's not a REIT. But yet they had this income in their numbers. We pull that out and we show you how we do it because we want you to know how much work we do because we're honest and we're independent. No investment banking conflicts or any other conflicts for that matter. There's not many other research firms that can say that. All right, let me summarize here for a second. And share 3 key ways that our clients leverage our tools to pick the right stocks and avoid the bad stocks. First, the freshest data. We update all of our models for 3,300+ stocks and another 7,000 stock ETFs and mutual funds. These model updates drive hundreds of rating changes, and rating changes can identify winners and losers Every day we get new filings, and that's just about every single day. For example, Motor Parts of America, we upgraded it from neutral to attractive last year in February, right after we parsed its 10-K. Over the next month, it was up 60%. Dell Technologies upgraded from neutral to very attractive right after we parsed its 10-K. Over the next month, up 32%. Second, we offer clients the best data. Our clients get the most rigorous fundamental analysis in the world. Name another research firm that has papers from multiple prestigious institutions written about the superiority and the rigor of its research. Name a research firm that has one such paper. There aren't any. Every company model, like each one of these models, if you wanted to build one of these on your own, I'm guessing it would take— cost you at least $50,000. That's what I think if you pull an expert out of Wall Street and ask them, hey, I need a model that does these things, just to give a checklist of all the new constructs does. I'm telling you, man, you're not going to get this for less than $50 grand. It's a lot of work, and the kind of people that have the capability to do that are very rare. And they're very busy doing this for themselves. So, if you could get them to do it at all, it's going to cost you a pretty penny, to say the least. And this kind of consistency across so many companies means that you can get analysis that you can trust. It's not important to do the work just for one company. You got to do it for all of them so you can understand the relative value of each stock, ETF, or mutual fund versus another. That's the power. Consistency is not just in the effort and the input, folks. It's in being able to scale it across so many stocks. That's what makes our platform so powerful. Now, to give you some context of how our proprietary research scales, I want to bring up Warren Buffett. In this article, I think about from the book on Warren Buffett, it talks about how they estimated that over his life, he read over 100,000 financial statements. At New Constructs over the last 20 years, we have had experts mark up over 250,000 financial statements, and we've collected over 43 billion data points. All this is to inform our modeling, our data checking, our data quality, our data collection, the automation we use to collect data, the automation we use to model companies, the automation we use to check to make sure those models are always right. We knew this a long time. 43 billion data points. Every single time we've ever found an error over the years, and we do find errors very rarely these days, in the beginning all the time. And from those errors, we built a library of what we call data checks. Anytime that error ever shows up again, red flag. And really, it's not even an error. It's just a scenario. It's a scenario where the machine says, wait, I see something. I'm not sure. Let me call a human. And so we've got Thousands and thousands of checks constantly, every second as we're going through filings. So one of the takeaways here is that New Constructs has to analyze nearly 2.5 times as many financial statements as Mr. Buffett and counting. Third, what we give our clients— honesty. We maintain true independence. No investment banking or other conflicts, just pure, honest research That works. And proof is in our stock ratings, not just in our performance, but in how few stocks we say are good. Remember a few slides ago I showed you that 3.4% of companies were responsible for 100% of all value creation since 1926? 3.4%. Guess how many stocks in our system get a very attractive rating? About 3.4%. Less than 4%. The point is we're discerning, we're honest. We're not here to say buy everything. We're here to give you the honest truth. And that's not what Wall Street's in the business of doing. All right, let's make no mistake about this. 96% of all stocks covered by Wall Street get a buy or hold rating. It's preposterous on its face. How inefficient would a market have to be when 96% of stocks are undervalued. It makes no sense. Wall Street doesn't make sense, not when you don't understand what it is they're doing. It all makes sense when you realize how conflicted they are, because Wall Street analysts, they don't get paid for giving you good information. They get paid for helping investment bankers make money. Who knows how much money that, that the research division of an investment bank brings into the firm? Little hint at the bottom of the screen here: none. And yet 50% of all Wall Street ratings are a buy. We're just at 13%. That's for the strong buy and the buy. So here's some examples of where these Wall Street ratings have gone terribly wrong for people. Let's take Coinbase Global. Was a buy or hold a bunch over the last year according to Wall Street. We had it unattractive and neutral. Who was right? Coinbase is down 25% year to date. You decide. According to Wall Street, GitLab, buy or hold? Mostly buy over most of the last year. For us, unattractive the whole time. GitLab down 48% year to date. Who was right? New Constructs was right. How about Reddit? Buy or hold? Mostly buys, as you can see on the screen, over the last year. For us, unattractive or neutral through all this year. The result? Down almost 40% year to date. Who was right? The value of our AI solution is proven by our performance. I'm not just here pontificating, making stuff up, pretending that we got some magical capability. We've got proof. We're coming to the table with cold, hard facts and evidence. And in this 20-year journey, this foundation of audited superior data has led us to now. I want to tell you something about something that I'm really excited about. Never before have we done— made this offer to folks and made this deal available to people in the history of our company. For years, I've been focused on the institutions. Most of these folks know the problem. They have the background and the expertise to appreciate just how difficult it is to read a 200 or 2,000-page annual report. And they've got budgets to pay me, pay us hundreds of thousands of dollars a year, 12-plus grand a month. But then I thought to myself, okay, institutions is great, but we live in a world now where there's so much noise, there's so much propaganda, so much information, and so much grift. And I thought, what New Constructs really needs to do is bring this to the rest of the world. And so we wanted to make things more accessible. And so we did. We brought prices down to about $1,000 a month, but that we found was still out of reach for so many individual investors. So we asked ourselves, what if we could make institutional-grade research Accessible to individual investors at a price that makes sense to individuals. How do we do that? Today, I'm excited to say we have an answer to that question. It's called Discovery. It's designed specifically for investors who want institutional-grade research tools but don't need every single feature in our professional and institutional memberships. Let me explain. With Discovery, you get everything in our Stock Tracker membership, which is looking at ratings on over 10,000 stocks, ETFs, and mutual funds. Type in a ticker, get an answer in an instant. You can track up to 50 of those at all times, so you get alerts every day on any change related to that company or that stock or that ETF or mutual fund. Monthly video podcast, sometimes weekly, with me and Kyle Guskey talking about all the major issues. You get access to a vast library of MBA-level educational materials. And when I say it's MBA-level, I know because I'm teaching these folks, right? This education material stuff, I've had clients say to me before that started out as individuals and go to institutions based on our educational library. Literally individual investor now at a major hedge fund. Couple of those institutional asset managers based on the educational materials. Very valuable. And we also give you the ability to learn how to be a diligent investor. That's what you get with Stock Tracker. Now with Discovery, we're adding screeners. That means you can screen our entire universe of 3,300 stocks to find the best stocks by rating, market cap, price, dividend yield, sector, index inclusion, industry. You can also screen 7,000+ ETFs and mutual funds. In the same way. In short, you get an answer key. And I say it's an answer key because we've analyzed the whole market. Remember, it's important to do great work on one company, but it's got to be done across all of them so you really understand on a relative basis what is the best and what is the worst. You can't do that if you don't do the great work on all companies. And New Constructs is a new construct for research because we're the only firm to have ever done that diligence on the entire market. That's why we have the answer key. Unrivaled rigor on 3,300 stocks and 7,000 ETFs. Unrivaled instant ranking and sorting by all the key parameters. Truth and alpha on every security delivered on a silver platter. Now let's go a little bit deeper dive here on what it is that we do and how we do it. Comprehensive nature of our research entails countless Pages of data documentation from the, from the balance sheet, the income statement, the cash flow statements, all of these analyzing every day, every company, every quarter. We're also doing the footnotes and dozens of other disclosures, doing that diligence that my institutional clients tell me they don't have time to do, but they know needs to be done for them to fulfill their fiduciary duties. Now, by understanding the true profitability And identifying the hidden risks, we build superior financial models to find the best and identify the worst across the entire market. Our stock ratings are grounded in verifiable numbers from the filings, not speculative narratives or biased analyst reports. Fundamental, empirical, auditable truth. This gives you a much more accurate picture of the company's sustainable profits and helps discover stocks like Mind Technology, upgraded from neutral to attractive in April of last year after we parsed its 10-K, was up 32% in one month. Alibaba, upgraded from neutral to very attractive in April last year, just like almost right at a year ago, right after we parsed its 6-K, which is like a 10-K for international companies. Over the next month, up 24% in one month. And we help you avoid bad stocks. Last year, we downgraded Caesarstone from neutral to unattractive after parsing its 10-K. Over the next month, down 24%. Voyager Therapeutics, downgraded from neutral to very unattractive in March after we parsed its 10-K. Over the next month, down 22%. Our Discovery membership provides unrivaled insights about thousands of stocks in the entire market. Being able to screen across that is a superpower. The Answer Key gives you answers to questions such as, what are the best stocks in the AI industry? What is the energy company with the highest dividend yield? Which small-cap financial stocks have a very attractive rating? What are the worst stocks in the real estate sector? What are the best dividend stocks in any sector? Show me the very attractive stocks in any sector. All based on research proven to generate alpha and vetted by top institutions. You wonder why Wall Street doesn't want you to have this? Because if you did, you wouldn't need them anymore. Wall Street's designed just like AI's designed to keep you coming back. To give you the truth would be to set you free. They don't want to set you free. They don't get fees from people that are free. So you're wondering, what does it take to do something like this? If you wanted to do it on your own, what would it cost you? I think it'd be millions of dollars per quarter, assuming you could find the expertise to do it. And this member— this membership gives you access to the level of depth of financial research that is a goldmine to advisors and hedge fund managers, our clients, again, paying us Tens, hundreds of thousands of dollars. And this high level of research consists of unbiased ratings on 10,000+ securities, just like what you see here. Green is good, red is bad. Portfolio tracking. So you put your stocks, ETFs, or mutual funds in a portfolio, and we tell you what's going on, what's good, what's bad, and we give you alerts when it goes wrong. We also let you screen on all this stuff so you can go quickly find what's the best and worst. You can evaluate what you have in your portfolio now to know if it's good or bad. Should you get rid of it or keep it? You go find the good stuff and also avoid the bad stuff. That buddy at the bar last week that had the hot stock pick, type it into New Constructs and see if it's really hot. Maybe he just wants you to buy it so he can get bailed out because he bought it at too high a price. And again, alerts, a super feature, right? Every day you wake up, By the time you sip your morning coffee, we've done all the work. We've let you know what's gone wrong, what's gone well, and you get to go about reading your newspaper. So with Discovery, key takeaways: you get to invest with confidence knowing you have access to the absolute best, most accurate research in the world on US stocks, ETFs, and mutual funds. Maximize your profits with informed— with decisions informed by proven superior data. Leverage AI to thrive in any market condition. Enjoy real due diligence, knowing that you have the complete financial picture when making financial decisions for yourself or for your clients. Enjoy having an answer key. Never been out there available before. Take advantage of it. Now, some of you who've been part of the community for a while might be wondering, how exactly is Discovery Different from the basic Stock Tracker membership? Well, let me explain to you. First, similarities. You're getting the same proven fundamental research, same AI-powered ratings, same alert tools. What's different is the ability to instantly analyze the entire market. Having screening capabilities to find the best and avoid the worst stocks and funds instantly. This is screening turned on its head. When I started in the business 30 years ago, You use screeners to narrow the number of companies down to a small enough list so you could go do the real work. That's what it's all about. When I came to Wall Street, it was like, oh, screening tools, because everyone knew that the screens were rough, they were bad, they were approximations. That's the way they still are. New Constructs is a new construct for research because we've done the diligence at scale. That's why AI— so I'm sorry, that's why Google Chose us. Good data analytics at scale is the next wave of AI. New Constructs is giving you today. That's how you get ahead of your competition. That's how you make decisions before the rest of the market. That's how you succeed in the stock market. Discovery gives you more robust tools designed for investors who want to avoid paying for features that they may not need. So I think it comes down to this, folks. Individuals usually don't have access to entire research departments. Or dedicated analysts, machine-scale parsing tools, institutional screening power. We're changing all that. We're shifting the landscape. We're closing that gap so you have access to research just like the big boys, the insiders. Discovery gives serious individual investors access to the same core research engine, ratings philosophy, and screening power as all the rest of our research. Let's take a look at what our clients say. Along with your integrity, we appreciate your commitment to maintaining high standards and your courage for saying so. How many other research people out there have you ever heard talk like we talk about integrity, truth, reliability? You don't, because they can't. And we do because we can. And we honestly, I believe Right now, the world needs what we do. The world needs reliable sources of truth because it's just so rare, especially in the stock market. And I actually wrote a special piece, you guys can look it up, about how we can protect the world from rogue AI, and it starts with reliable research. Let's talk— let's look at another client here. Simply and instantly, you can see how your stocks or funds are rated and where they are trading. This top-down view is incredibly useful. I highly endorse new constructs as a must-have in any stock or fund selection system. Joe, big registered investment advisor, can pay higher fees, but if he's willing to pay that big money, maybe you should think about it too. Here's Chris. Look, she says, I've valued new constructs information for several years now, relied on it for managing a single portfolio that supports my husband and me in retirement. So New Constructs is important to her. Having worked with big data throughout my first career, 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 indicators of a company's performance is a huge undertaking, and you deserve my utmost respect. I find New Constructs information to be reliable, relevant, and trustworthy. And I expect to continue using New Constructs through my life to avoid ever running out of money. New Constructs is the only company that has allowed me to feel secure in both my buy and sell decisions, and that has been truly valuable. It provides me with concise insights into investment opportunities derived from meaningful metrics that I couldn't duplicate on my own. Can't get this anywhere else. And I think, again, it's super important in a world where trust in US institutions has withered. We've shown this slide before. Look anywhere. Tell me where trust is getting better. Show me one place where you think trust is getting better or more reliable. Any institution, large scale. What we're doing is important, not just for you, but for the world. And I think getting the truth out there to more people is important because I think more people need to be empowered, not just the big rich corporations and the big Wall Street insiders. That's what we're here to be, reliable port in the information storm. We believe in trust and transparency, and we identify stocks we believe to be truly valuable based on proven superior data. We're not compensated. We're not promoters. We don't do this— we don't get paid to say what we like and don't like. We do it because it's the right thing to do. So tying it all together, this market is very risky. Extreme valuations on both The good and bad side. A lot of hype and fake numbers. And we published a piece just a couple weeks ago about a new innovative way of hiding debt that Facebook introduced, or Meta, a whole new term. It's getting worse, not better, folks. 90% of stocks go nowhere. Your job is to find the elite 3%. And I believe you do need an answer key or truth serum, whatever you want to call it. That's built on something that's truly trustworthy. And there's no better time than now to take advantage. In the meantime, it's time for me to take some ticker requests. So Kyle, if you want to go ahead and throw those out there, let's do it. I'm going to open my access to a Discovery membership. You can see here is the rating page. Kyle, you want to give me a ticker? Yep. First one would be SOFI. SOFI. People are interested in this stock a lot. Why is that? This is in the news recently for some reason. Very unattractive rating. So valuation looks bad all the way across the board. Quality of earnings, not very good. This is one to avoid. This is not the top 3%. This is probably closer to the bottom 20% of all stocks. Gave you the answer in an instant. It's another ticker, Kyle. STX. Yeah, this is one that we liked a long time ago. I believe we wrote a long idea on this. Always super profitable business. This is classic good company, bad stock, my friends. So good company, great business, right? Very profitable, but bad stock. Why? Because it's so expensive. These reds, big red flags. In particular, market implied growth appreciation period. When that gets to very unattractive, it's dangerous. Super expensive. That means that as good as this company is, the stock price is giving it credit for huge amounts of profits in the future. When I say huge amounts of profits in the future, 4, 5, 6, 7, 8x, 10x what the company's done in the past. So as good as it might be today as a business, if the stock is priced in all that great performance, you don't want to buy it now. You want to buy it when the stock is implying profits were going to be lower than what you expect, not higher than what you expect. And we give you that answer in an instant. Kyle, what's our 3rd one? Third one, Intel, INTC. Interesting company going through a turnaround. When we, in our long ideas dinner that we do with our professional clients and we use our reverse DCF model, we spent some time on Intel looking at exactly at how much of a turnaround is already priced in. Because, you know, look, I look at these numbers and I'm like, yeah, they'd be this bad forever. Probably not. Intel used to be down in the green. They fell behind. One of the most innovative companies in the world. Maybe they rested on their laurels and they fell behind. But yet, look, the valuation is still expensive, folks. So they're giving— the stock is already giving this company a lot of credit for being able to execute a big turnaround. So again, not a good stock. Let me quickly go through a couple other features for Discovery. Look, you can track a portfolio, you can put tickers. And I'm sorry, stocks, ETFs, and mutual funds in here. You can see side by side, we'll show them to you, and then you can get more details and you can manage alerts, right? So you can say, I want to get alerts on this portfolio every day or just once a week, up to you. You can get alerts for new coverages or updates on coverage requests. So, you know, when our coverage is changing, and you can put in different email addresses here. If you want one to go to your business partner or to your wife or to significant other so that they can get the updates when you get them. And then there's the education section. Amazing. Remember I told you a vast library of MBA-level stuff, methodologies, metrics, every single major metric in our system defined. There's a whole, like, this is a, this is like 3 MBA Harvard Business School-level classes all on leases. And how that works. Maybe you don't care, right? I just want you to know it's there. You want to see how— you want to go the full depth of what we can do? We will take you to the ends of the earth in terms of how our system works because we want you to know how good it is. And then, of course, the screening tools. Go through the entire market, say, listen, I want to know— I'm not going to give you the good stuff. I'm going to say, hey, I want to know the very unattractive stocks in this sector and then in this subindustry. And I want it to be a dividend yield greater than 3%. Go. Nothing matches those results. Let's take away the dividend yield. Go. Bam. Screen the entire market. You got an answer. The worst stocks. People were asking a second ago, is this good for shorting? Look, shorting is a timing game. So I'm not going to say anything is necessarily good for shorting because I was a hedge fund manager and I was right about a short, but still ended up losing a lot of money. Right? The stock went up because they announced They were evaluating strategic alternatives with Bank of America. People misread the headline. It was really a white flag saying, please, somebody buys before they go bankrupt. 6 months later, it went to zero, but in the interim, it went up a bunch. So you can be right. Timing is important. But if you want to find stocks that ought to be shorted, you want to go in the basic materials industry, this is a great place to start. And in an instant, you're scanning through thousands to get the very best and the very worst. All right, let's answer a few common questions. As a first-time user, how can I confidently navigate and make the most of the stocks and tools inside Discovery? First, super easy to use. Second, tons of tutorials for the site. Any other questions? Get them in here now. Otherwise, we will be ending this training today, and I'm very grateful for all of you guys that have been with me. Kyle, are there any major questions that we want to try to get to here before we jump off? I think you got them all. All right. Great. Thanks, everybody. Great time today. I hope this was helpful, and we look forward to seeing you as a new Construx customer in the near future.