Stocks Most Likely to Miss and Beat Wall Street’s EPS Estimates - 2Q25

Welcome to our special edition training webinar for stocks most likely to beat and stocks most likely to miss. This is based on really cutting-edge research that we do on earnings that you can't get anyplace else. We have proprietary data that gives us proprietary insights that have been proven to generate idiosyncratic alpha in the stock market. And we are sharing it with you today based on our analysis of the entire S&P 500. And by the way, we do this work for all companies, but we're focusing on the S&P 500 because those are the big movers and shakers. That's where Wall Street analysts are supposed to be paying attention, and we are giving it to you today. So this special training is really one of my favorite topics. And something that I look forward to doing every quarter. I think it's a really cool product. I'm glad we're bringing it back. We're really excited about the interest and the demand we're seeing. And with that, let me just jump into this. Let's start. Let's get into the details. Let's get it going here. So as I said today, stocks most likely to miss and beat Wall Street's earnings estimate. This is screening based on our advanced AI agent for investing or the financial analyst. AI agent, whatever you want to call it, robo-analyst. We've been doing this kind of work for 20 years. We're ahead of the curve, to say the least. Disclosures and disclaimers. We are not investment advisors. We are here to provide information to help you make more informed decisions and not make decisions for you. I want to hear from you in the chat. It's great to see some people jumping in already. I love that. Always put questions in there. Those of you who've been to a few of these before, you know that we are Very open. I'm here to answer all your questions. We got nothing to hide. We want you to know how much work we do. Let us know what kind of investor you guys are. And then if we have time, put a stock in there and we'll run through the system as a special treat to show you guys how it works. So look, I think everybody's got to be surprised, interested, whatever you want to call it. Everything's at an all-time high— S&P, NASDAQ, Bitcoin. Everything's at all-time highs. Everyone's saying, hey, maybe you want to be a little more careful here. And I look, we're always advocates of being careful, of being diligent. Here's our agenda for the day. We're going to talk about why we created new constructs and how this benefits you. Then we're going to jump right in to how to find stocks most likely to miss. We'll give you a sample one of those. We're going to show you how to find stocks most likely to beat. We'll give you a sample one of those. You're getting a free sample stock on the beat side. And then as a free bonus, we're going to analyze the stock at the end. So background. Look, after years of— after many years on Wall Street, I saw the sausage was made. I saw really early on that the bankers can find a ratio or a number to make any deal look good. That's what they do on Wall Street. They're in the business of selling stock, not good research. The research departments don't make any real money. So I felt like Society needed something to give people the truth about profitability and valuation. And I knew it was a really hard thing to do because that data is buried in thousands of pages of filings. But we've done it. And we have proof in our stock picking, proof in the results, right? Look, at the end of the day, if you're going to do all this work, you're going to create an ontology for taking data from the source and putting it to its highest and best use. Well, the highest and best use for fundamental data is to predict future stock prices. Very few people in the history of the world have ever succeeded at that. It's very difficult to consistently beat the market. We're doing that. 49 straight months ranked as a number one stock picker across multiple categories on a buy-side-only platform. That buy-side-only means professional investors. These are not the sell-side Wall Street analysts. These are the buy-side folks. So, it's a real Real honor to be ranked that highly on SumZero. And if you're not familiar with that platform, you should check them out. We've also had multiple papers published by some of the most prestigious institutions in the world proving that our data is superior, proving that our analytics are superior, proving that our stock ratings are superior. Name another firm that you know has similar papers published and I'll give you a free Most Attractive Stocks report. Name one. But probably the best proof of all is in the actively traded indexes based on our research. Number 1, the Very Attractive Stocks Index outperformed in the first half of this year, beat the S&P 500. But over the last 5 years, it's beaten the S&P 500 by 77%. That's a great stock picking strategy. This is an index that just holds our very attractive rated stocks. How about the core earnings weighted S&P 500 index? This is just saying, hey, instead of the S&P 500 and being weighted based on market cap, we're going to weight those stocks based on core earnings power. That index also outperformed in the first half and has outperformed by 31% over the last 5 years. So if you think there's alpha in core earnings, I think you're right. And then the Core Earnings Leaders Index has outperformed actually the strongest in the first half of this year. It's beat the S&P by over 7%. This is an index that just focuses on the top 1,000 stocks and identifying out of those 1,000 the ones with the greatest core earnings power. And that's basically negative earnings distortion divided by assets. It's the amount that the core earnings are higher than the reported earnings. So, reported earnings are understated, and you divide that by assets. That's how the Harvard Business School people do it. That's how Bloomberg does it. And guess what? It's outperforming, outperforming like crazy this year, and by 48% over the last 5 years. So, if you want proof that the ontology works, if you want proof that we're able to interpret, collect, and model fundamental data better than anyone else, This is it. Doesn't get any better than that. One thing you have to keep in mind is these indexes managed by Bloomberg, they're not available for the public to purchase. Sorry. But you can get this information from our research. And that's what we're here to provide. So now, why do you need better research? Well, let's start with the fact that 96% of stocks covered by Wall Street Are listed as a buy or hold. Here's the chart. Check it out. There's a link down here in the bottom. Let us know if you want to see that. You can go look this up on your own. 96%, my friends, buy or hold. What does that tell you that Wall Street cares about? Selling stock. They're not going to be able to sell the ones they don't tell you to buy, right? Their paychecks depend on you buying stocks. They don't make a profit from research. As I said before, you got to buy stocks. So their ratings, a little biased. Here's another study showing the number of stocks that get just a pure buy rating, 57%, over half, right? For us, it's much less, 13%. Guess how many stocks get our, our strong buy rating? 4%. We're selective. We're discerning. We do real work. We're honest. Let's face it, there's no way the market would be efficient at all if everything was a buy. This shows you the majority of the market is not undervalued, which just makes it an efficient market. Where the majority of the market is undervalued, that's inefficient. And I believe we work in a semi-efficient market, not utterly inefficient, which is what Wall Street effectively is trying to sell you on. Here's another thing. Earnings estimates are such a drop in the bucket of what explains the valuation of most stocks that it's not even funny. Wall Street doesn't want you to know that there's a big difference between their estimates and valuation. Wouldn't be any good, right? Because if you saw this difference, you'd be terrified. The best they're going to offer you is a few years of earnings estimates. Now, I'm going to tell you why these earnings estimates are flawed in a second here. But look, at least they're giving us something all the way up to 2030. Isn't that great? Well, what does it really take to justify the price of Tesla? What's the entire future cash flow required to justify the price of these stocks? I'm going to show you right now in a second, but I'm telling you before we even get to the slide, the gap between Wall Street's estimates and the cash flows required to justify the price— staggering. Here you go. Tesla. This is back when it was $276 a share. Now it's $300. These are the cash flows when you put them through a discounted cash flow model. This is what you have to put into the model here in red to justify the price. This is what you got to put in the model just for the price, all this. And for $300, it's probably like up here, and that takes 10 years out to 2034 or longer for going to $300. But this is what Wall Street gives us, this little bitty baby bit, a little bit of a baby bit. And they're going to have you obsess over a penny a share here or a penny a share there. Come on. It's ridiculous. We see the same thing with other stocks. Nvidia, similar story. Big difference between what Wall Street's telling you they got to do in terms of estimates per share and what the cash flows have to be to justify the price. Again, this is taken from a while ago. Nvidia is up to $130, $140. Even more expensive, even bigger disconnect. So I hope I made my point clear. Earnings estimates are not nearly enough to make informed investment decisions. Definitely not in this environment. How do we do it? What's our edge? You guys know, robo-analyst technology, also known as financial analyst agent or AI agent for investing. We've been building this technology for 20 years. We're way ahead, folks. Executives from Goldman Sachs, Morgan Stanley, Merrill, UBS, you name it. They've all used this system. And for you and for them, we're doing an enormous amount of work with tons of data to give you an answer, an answer about a stock, an ETF, or mutual fund as simple as green means good, red means bad. The indices from Bloomberg prove that this works. Here's some examples of what it looks like. All right. For Tesla, you type in a ticker, you get an answer, you get our rating here for Tesla, and you can see the earnings distortion score, strong miss. Now, earnings distortion scores and overall ratings are not always the same. Not always the same. In this situation, they're both bad for Tesla. But this is a shorter-term metric. Earnings distortion score, it's a shorter-term metric. It's just about how likely it is that company's going to miss or beat in the next earnings report. Here's an example of an earnings distortion score that's positive. It's a beat. You can see that. See, it's a neutral rating. So again, these 2 are not always the same thing. You get the idea though. This company's more likely to beat. Now, how much should you trust what we do? Where does it come from? Well, we have a patent. Name another research firm that has a patent. Another research firm that has papers from prestigious institutions published that proves our data is superior. Name it, drop it in the chat. Be happy to give you a free Most Attractive Stocks report if that's true. The comprehensive nature of what we do— the work you got to do to be this good is huge. It's part of why we've been technology-driven from the beginning. I knew that I could never replicate the work I did on Wall Street by hand at scale, so technology's always been a big part of it. And my favorite thing about technology Favorite thing is that when you teach a machine to do something, it does it exactly the way you say every single time. That means if you tell it to do the wrong thing, you're in trouble. Part of the reason why people love us and why our AI is so special is that our rules get it right every time. We've been built for a machine from the beginning, so our data is As close to perfect as can get. That's why we outperform the market. It works across all stocks. It's not like 97%, 98%, and you never know what of the data you get is going to be that 2% that's wrong. That's a disaster. It's a disaster. The data's got to be right. And you got to go through a lot of data, which is what makes what we do so special. We've gone through hundreds of thousands of balance sheets, income statements, cash flow statements, And footnotes, dozens of other disclosures, hundreds of thousands human experts going through those. Now, the number of repetitions we've had on those where we've trained people on them, where we've tested people on them, where we've tested the machine, we said, hey machine, go see how well you can parse this footnote and we're going to give it a grade. And that machines have done that. You know, we add that in, we've been through millions of Here's a sneak peek of how things look. If you're an institutional client and you have access to our marked-up filings, you actually see exactly where we're finding the data. Here it is. We got a special interface here that lets you drop down and take a look at any filing. We got filings back to 1998. We'll come right down here and say, hey, here's earnings distortion from hidden items. Hidden items are items you cannot find on the income statement. Okay. And we detail them all right here. Boom, there it is, 4611. There's the number, right? If you click on these other items, it's going to take you to another spot in the filing. So really powerful, powerful transparency. Why are we transparent? Because we can be. Name another firm in the world that can match that, match that transparency. Here's another item we found. This is in the 2023 10-K. So a little bit different, different filing, but same idea. We're finding data in filings, in footnotes that matters, and we're bringing it to bear to build a superior ontology and a superior dataset, superior research platform. So let's get down to it. Most likely to miss second quarter earnings. Start with the fact that nobody believes GAAP earnings are a good measure of value anyway. So that's why they create their non-GAAP numbers. Oh, wait a second. Non-GAAP numbers are even worse than the regular GAAP? Why am I surprised? Wall Street's in the business of selling you stock. They're going to make up a number needed to get you to do the deal. That's how they do it. So we have found that the failings of the Street research are quite significant, material, and frequent. In fact, we found that 184 companies of the out of the S&P 500, over 30%, close to 35-40%, are overstated by 7%. They overstate earnings on average by 7%. Not a lot necessarily. 64 companies are more than 10%, right? Some of these companies are probably 30-40-50%. The key is being able to screen through all of them and know. And by the way, you don't know that 30% or 40% is even a big number necessarily until you've looked at the whole marketplace. That's why our research at scale is so important. These companies are special not just because we did the work and found this information on them, but because relative to all the other stocks out there, they're even more overstated than anyone else. That's what it takes to get An earnings distortion miss score. You got to be worse than everyone else. And the only way to know if you're worse than everyone else is to do the work on everyone else. And only New Constructs has done that. See, remember what I told you? More than 40%. Some of these companies overstated by 113%, overstated by almost 100%. These are big numbers, folks. That's why this report is so valuable. The company I want to talk to you about today as an example is a likely to miss, Caesars Entertainment. Let's take a look. Here it is, miss. You can see here that this is not just a miss stock in terms of earnings beat, it is also unattractive. Double whammy. This is why we're raising the red flag here. And for these other 5, you know, the earnings miss is going to be potentially worse because the earnings distortion score is probably worse because they were overstated by a larger percentage. But you can see the data here. Very, very bad stock situation. Most likely to miss and a very expensive valuation. You can see this valuation whenever you see red up here in the upper right-hand corners. This is a big-time red flag. Tune into another training around our professional membership, which is what I'm showing you here, and I'll show you exactly, you know, what goes into each one of these elements of the rating. See, look, accounting earnings way up. Earnings distortion. You can see accounting earnings went above core earnings, come back some. But they got more to come back. Way overvalued, come back, probably going to keep coming back here in the near future if you follow this trend. But you get the idea. Enormous amounts of data available here. Takeaway, Caesars Entertainment earnings distortion score miss, unattractive rating. Next, let's move into most likely to beat. Rather than rely on flawed GAAP or Street earnings, Let's use our AI agent to get the real numbers. Now, surprise, more companies in the S&P 500 have earnings understated than overstated. 308 companies are understated, have understated earnings. 153 understated by more than 10%. And the understatement is higher than the overstatement, 10%. Right? So what do you want to know? Which stocks have the most understated? Which are most likely to miss based on the data and this deep diligence that is possible only with cutting-edge technology shows us? Well, here we go. Street estimate understated by 33, 23, 23, 15. Big numbers. Big numbers. Who we're going to reveal for you today as an example? Halliburton. Let's take a look at this one. We go type in a ticker, get an answer. What do you like about Haliburn? Okay, nice. I'm getting an earnings distortion score beat. I'm getting an attractive rating. Bonus looks good. I'll take it. I'll take it. That's why it makes the list. Now if we want to go a little bit further, earnings distortion. What's this look like? I got core earnings above my accounting earnings. I like this trend. It's accelerating core earnings even more above reported accounting earnings. That's attractive. That's extra attractive. And again, cheap stock as well. Price to economic book value of 0.6%. That's a good number. Stock's undervalued by 40% here according to price to economic book value. We'll take it. All right. So, so far, I think we've shared a lot of value in our very short time together. That's the way we do it at New Constructs. We do a ton of work so that you, in a matter of seconds and on a silver platter, can get incredible insights. We covered the bias of Wall Street and their ratings, especially during earnings season. We revealed the gap between certain stock valuations and cash flows. We've shown why you can't trust Wall Street stock ratings. We've shown how our proprietary robo-analyst uncovers earnings distortions for thousands of companies. And now I have a question for you. Would you like to have access to the current stocks that are most likely to miss or beat? We put together a special report normally only available to our professional members called Stocks Most Likely to Surprise in 2Q25 Earnings. And our AI agent for investing has already found the truth. It dissects the accounting tricks and reads the footnotes buried deep in quarterly filings. It calculated the true profitability of every company in the S&P 500 using our proven superior core earnings model. And what our agent found for 2Q25 earnings season is striking. Hundreds of companies with overstated earnings, hundreds of companies with understated earnings. But just 5 that are most likely to miss. 5 with an earnings distortion score of miss or strong miss and a stock rating of unattractive or very unattractive. And then 5 stocks where estimates are too low. You'll also receive a full professional-grade stock report on each company detailing the specific accounting distortions that give you this analytical edge. And due to the nature of the depth and proven superiority of our research, considering that our institutional members have to pay $4,000 a month to access these same stock picks, to do the same kind of screen to figure out how to find these stock picks— institutional members, they're $4,000 a month. That's what it takes to access the same kind of data or to do that kind of screen. 2 trainings. So total, if you purchase all this stuff separately $5,000. What are we charging? $399. How much are you saving? $4,600. Incredible deal, to say the least. Here's what the order form looks like. If you only want the stocks to miss, you can get that for $99. If you want stocks to beat, that's an extra $300 for $399. So you either have stocks likely to miss or you buy both. You can't buy them separately. Kyle, if you would drop that link into the chat. We'll now start taking some questions. Folks have them. In the meantime, I'm going to go through some testimonials from some of our customers. How about Nancy? Your commitment to maintaining high standards and your courage for saying so makes you one of my— the top of my list of respected companies. I like it when clients say that stuff about us. It's true. We're doing work. We're going to ends and to efforts that no one else can match. That's why we outperform. The only way you beat the market is if you do things that no one else can do. Simply and instantly, you see how your stocks and funds are rated. Joe says, I highly endorse the new Construct system. as one must-have tool in any stock or fund selection system. Thank you, Joe. That's great. I sincerely appreciate all the work that has gone into creating New Constructs in the database. Going from marked-up footnotes and filings to reliable, easy-to-understand indicators of a company's performance is a huge undertaking. You deserve my utmost respect. I find New Constructs information to be reliable, relevant, and trustworthy. Thank you. I expect to continue using New Constructs throughout my life to avoid ever running out of money. I mean, we've got some awesome, awesome testimonials. I have found your analysis superior. I know how financials can be manipulated. Your research digs that out. I rarely buy something that does not have solid ratings from New Constructs. Awesome. They give me work I can't duplicate on my own. Guess what? No one can duplicate what we do at scale. No one has. That's why we outperform the market. So any questions there, get them into the chat here as we're wrapping up. Uh, I'll go through a couple common questions here. As a first-time user, how can I confidently navigate and make the most of the reports and stock picks? These will get delivered to you on a silver platter via an email. Just click a link and download them all. But we got tons of trainings. We got another training next Friday. We've got a support desk. You can email them 24 hours a day. They won't email you back 24 hours a day, but they'll get back to you within 24 hours for sure. Usually much faster than that. But we have a free live training next Friday, a live webinar. Ask questions of that anytime. We're doing these webinars and trainings all the time. I take questions. We all take questions. We're very proud of what we do. We want questions. They're typically just an opportunity to go even deeper into how our research is better. There are tons of tutorials and video trainings on the site as well. All these reports that are going to be delivered to you will be delivered with a tutorial. The email will actually have a section in it with the links to all the reports that takes you to a tutorial that explains how to get the most out of the report. Question number 2, how to find the best stocks in a particular industry? That's using our stocks, our stock screener. All right, we've got a simple version of that for professional clients and a much more detailed version of that, which is what Kyle and the team used to identify these stocks most likely to beat and miss. He used our dynamic data screener for that. That's a really sophisticated screening tool that goes through tons and tons of data that allows you to do some really super specific and sophisticated screens. Question number 3, are the attractive and very attractive stocks in the membership guaranteed to have a double or triple gain? Did you gain in the next year? No. Nothing is guaranteed, my friends. I don't have a crystal ball. If I did, we'd be doing this meeting on my yacht. We do not promise any kind of specific return. I think the best thing you can do is risk reward. Like risk reward. I mean, that's my thing. Like, I believe that in a world where you cannot predict the future, the best thing you can do is position yourself to have the best risk reward. That's what we do here. No guarantees. Number 4, can I buy both stocks most likely to miss and to beat? Yes, that's exactly what we're offering here today, delivered to you on a silver platter based on our machines and people going through hundreds and hundreds of thousands of filings to get to the truth. It's the first time ever. The version, the one real true version of the truth. All right. Any other questions? Okay, let's take a request. Let's see here in the chat, Q&A. Let me check everything that's going through here. Take me a minute to read all these. I think the first one that came in is OMF, OneMain Holdings. Very attractive rated stock. Also in our dividend model growth. Dividend growth model portfolio, seven percent dividend, very attractive rating. Hmm, that's looking pretty juicy to me, my friends. That's looking pretty juicy to me. That's a great looking stock. I would love to do some more work on this and and make sure that there's nothing shady going on. We haven't flagged anything. You know, speaking of which, I do want to quickly show you there's a new feature in our screens that allows us to identify. Flags. So for example, if you wanted to come in and see how many stocks have a weak internal control and an attractive or very unattractive rating, bam. I can't— I got to brag about this one. They're all suspended because they got weak internal controls. But this is super cool new feature that we have in here. But back to the rating here. This looks like a good stock, doesn't have any of these flags and looks cheap. So 14% return on capital. If we go into the breakdown here, you can see economic earnings trending had been down but bouncing back here, which looks good. Number of shares outstanding going down. That's always a great bullish sign. Return on capital been pretty steady. Pretty steady. Still up there. It's been 19, 20, down to 14. That's impressive. Margins look just like capital. Capital turns going up. Most people probably aren't paying attention to this. This is why returns on capital have been, have been better than margins, right? Probably too many people in the market looking at margins when capital turns are up. So this business is better than people think. I like it. All right. We got a question here. One last question because we're over time. If you must make a trade-off as an investor between the new constructs metrics, which one to rate higher or lower? Which ones could be compromised or rated lower? All right. I don't understand the question that well, but let me first say nothing at New Constructs is sort of to be ignored. All of our stuff is true. But I think if what you're saying, should I focus more on earnings distortion score or the overall rating? I would say overall rating. Matters most. Earnings distortion score, it's a shorter-term thing. Part of the problem with earnings distortion is that it can stay, it can stay messed up for a while. You're not guaranteed. You can see these are close, but you're not always guaranteed that the earnings distortion is going to reconcile. So yeah, overall ratings matter most. For sure. That's what matters. That's the biggest. But the earnings distortion score, when paired with the overall rating, makes it even better. So that's the benefit here. That's the key benefit. All right. Thanks very much for being with me. We appreciate all the questions, all the interactivity, the, the ticker requests, and we hope that you enjoy this excellent product. Have a great weekend.