Q3 2025 Earnings Watch Party: Major Banks and Consumer Products

Welcome everybody. Let's get going with our first earnings watch for the 3rd quarter earnings of 2025. Before I jump in here with more details, I want to make sure everybody understands that we are not investment advisors. So none of this is to be taken as advice or investment advice. Please seek out your tax. Advisor or your professional, professional advisor for that. We are a research firm. We publish information, some of the best information in the world, but we are just an information provider. I apologize for looking a little beat up today. Jiu-jitsu class got a little bit rough, so I got a couple of marks to show from it. But don't worry, the other guy looks worse, I promise. Before we jump into some of these specific stocks, I want to talk a little bit about our earnings distortion scores. How many of you are familiar with our earnings distortion scores? Give me props in the chat or put your hand up there. I see one person raised their hand. That's great. So the earnings distortion score is one of the better and most direct ways to take advantage of the alpha in new constructs data. You guys know we're more long-term oriented. So we're not here to sort of try to pick stocks on short-term drivers like momentum, et cetera. We want to be there for the long term. We want to make sure we're making We're giving the kind of like analysis and ratings that you can rely on for long periods of time, not to be short and quick. But we know the market moves up and down pretty quickly, and we think that earnings quality is a big deal. So to take advantage of the core earnings, the alpha in core earnings, and by the way, if you ever want to see how much alpha is in our information, Check out the Bloomberg indices based on our data. We've got 3. One of them is called the Core Earnings Leaders Index. And you can see here, if you want to compare this to the S&P 500, you can see it's beating it today. Over 6 months, it's beating it. Year to date, it's beating it by like 10 percentage points almost. The last year, it's beating it by 7 percentage points. So anyway, you're right, there's alpha here. And when you're thinking about how to take advantage of our data, think about these earnings distortion scores, which predict whether or not the company is likely to beat or miss. Now, many of you also are aware— raise your hand if you're aware of the AI that we're building with Google Cloud. Who knows about that? Has anybody heard anything about that? We partnered with them recently to build an AI. And the reason they're working with us is because, look, we've got better data. We see that the data is good enough to drive outperformance in the market. I'd say that means it's really good. That's the best thing about the financial business or the investment research business and the stock picking business is that there's no ambiguity about who the winner is. Right? It's, it's even better than a boxing match, right? 2 men enter, 1 man leave. Well, sometimes there's controversy about who really should have won the match, but there is no controversy about whether or not you beat the market. Either you do or you don't. And when you do, there's something there. There's something there, there when it's over not just a short period of time, but a long period of time. Here you can see 5 years is the amount of time that we're able to outperform the S&P 500. You can see here, 5 years. And again, as I mentioned a second ago, 6 months, year to date, 1 year, 1 month, 1 day, right? Outperforming. And we've got 2 other indices with Bloomberg that also outperform. So this is what we're talking about. So when you're able to take advantage of our earnings distortion scores, and I'll drop this into the chat for you guys, you've got better data to deal with. You've got better data to deal with. And today, as we go through the stocks that we're going to talk about today, I'm going to be showing you our professional membership. So that's going to give you sort of the full-scale access to what's going on and what we do. And the last thing I want to make sure you're aware of is the reason that Google Cloud chose to work with New Constructs is all explained in this article. I'll put this into chat as well. This article explains why our data is better and why it can actually drive an AI that AI models are like every other model since I started programming in BASIC back in 5th grade. I learned very quickly there's no such thing as computer model language error. The models do exactly what you tell them to do. And I remember writing one of those first little programs, like the script and, you know, the go-to button. And, you know, I made a mistake, made a couple mistakes. I made the mistake, not the machine. Machines do exactly as they're told. And if you don't put good instructions into the machine, you're gonna get bad results. Period, paragraph, end of story. So large language models are, are trying to get people under the illusion, and all the people that use large language models under the illusion that, oh, you can just pour the internet in here and, and the model's gonna figure everything out. Great. Haha. Wait. Awesome. We don't have to do any work. The machine is just going to take over the world. Well, if that were the case, it would already have happened. Small language models are what you need to power AI agents. Kind of the same thing. It says, listen, let's be realistic. Let's break the world down into smaller pieces. Make sure the data is perfect so that the rules we build based on that data are 100% reliable. And that those rules can also feed an ontology. They can have meaning. We need something besides rules. It's like A plus B equals C. We know that, haha, whatever. That doesn't help me much. But rules that can predict stock prices, well, that's a real ontology. That's what we have in New Constructs. We have a perfect dataset, as close to perfect as we can get. And don't take my word for that. Harvard Business School wrote a paper. They did, I think, 300 or 350 individual case studies. I know we cover 10 times more than that in companies. Well, 20 times more than that, but we were 350 out of 350 on the data and it was perfect. And the rules built on that are therefore reliable, and the ontology is good enough that it drives outperformance in the stock market, as you can see here, beating the S&P handily over pretty much any timeframe you want to choose. So with that, let's just jump in here. Let's see. Also, don't hesitate to ask questions. I'm here to help. Anyway, big bank earnings. Woo-hoo, man, it was a good week for big bank earnings. Let's, let's look at headlines for JP Morgan. Big beat, all kinds of good stuff around JP Morgan with their earnings and their announcements. Not much, you know, not a big surprise in the stock market. What did our model say about JP Morgan? We expected earnings about in line, which is about what the stock market did. No major changes to guidance, and that's kind of oftentimes what matters most. You know, look, JP Morgan is one of our focus list stocks. We love it. So you're getting a lot of value today. You're getting to see some of the top picks. It's been a great performer. We still like it. You're seeing a lot of green here. This is why we like it. The JP Morgan, a winner on a lot of levels. Let's take a look at Wells Fargo. Okay, this baby's doing great. So Wells Fargo is also dramatically benefiting from the fact that there's going to be looser liquidity. We've known that for a while. But these guys are coming out of the doghouse, the regulator doghouse, which is basically hamstrung their business for the last, I don't know, 5, 10 years. They've been really being watched closely because they basically did a lot of bad things. They deserved to be put in the doghouse. And as they're coming out of that, I think you're seeing some, some value realized. Let's take a look here. Wells Fargo. Yeah, neutral rating. So a lot of that good news has been priced in. I bet before we— before this pop, it was probably a good bit, you know, maybe had a better rating, up 8%. Either way, we don't like it as much as JP Morgan. Not as profitable, lower return on invested capital, and it's more expensive. So, you know, whatever comes out of these guys for earnings, I'm not too surprised. They topped it. They're all topping it. You know, I've got less and less credence for these beats because even the banks look around, they're like, let's see, you know, Tesla, they beat all the time. How do they do that? Hmm, let's go look at how earnings estimates change during the quarter. Oh wow, right after the call, they start out up here. After an earnings call, they started up here, and then by the time we get to the next earnings announcement, oh, they're way down here. Oh, and then they beat. Wow! What? Ah, okay. Yeah, they beat a really low number. So let me tell you a story about the time back in the time when I was early on Wall Street. It's a long time ago. I had a lot more hair, and I was meeting with the co-heads of research for the technology group, which was the number one technology investment banking group and research group in. the world. And I remember there's a couple of guys, I won't mention their names, but one was named Dr. Quatt because he was so cool. He didn't even go by his real name. And I'm talking to him about using my model and the model that I built for Credit Suisse, which is a very similar model than what we use at New Constructs. Same idea, same thesis. Let's get to the economic earnings. Let's take into account footnotes. Let's do the work that we need to do to understand the profitability of the business. And then let's use a reverse discounted cash flow model to understand how those profits have to change. Pure and simple. And so, those guys were the only analysts in the firm at that time that were really resisting. And I pressed them. I said, guys, what's up? Like, this is a better model. They're like, David, don't you understand how the business works? I mean, what do you mean? He goes, well, we can't use your model. And I said, well, all right, explain to me why. He says, well, because if we put our published estimates in your model, the stock's going to look expensive because You know, as you know, our published estimates are low for the stocks we like. But it's like, wait a second, what do you mean? He goes, you know how the game works, David. For the stocks you like, you need them to beat earnings so they go up so your recommendation looks right. So for the stocks we like, we have an extra low number. That's fine. But then how do you justify the valuation if that's— if your number's so low? Oh, there's another number that we use when we talk to our institutional clients. So we got the one number that we publish out there to the public. That's really low, so it's easy for the company to beat. And then we got the number we give institutions, which might even be higher than how much they beat, because that's what they believe to be the long-term profitability of the business. So that's how the game works. And a big part of our earnings distortion scores is to flush that out, give you an understanding of what the real profitability is before overstated earnings come crashing down or Understated earnings rise up. All right, that's Wells Fargo. How about Goldman Sachs? So this is a stock that we've liked a lot for a while, but it's gotten expensive. This is one we've talked about. I know on CBC when asked about financial stocks, you know, JP Morgan is one we always talk about. Goldman Sachs is up there too. Keeps getting expensive, folks. What's not expensive these days? Very little. JPMorgan is surprisingly not very expensive. I know on a price-to-accounting-book basis it's expensive, but on a cash flow basis, it gets an attractive rating. So I'll take that all day long. I think the Goldman— how did the Goldman numbers come out? Those guys crushed it too. They all had great, great earnings on dealmaking, investment banking, right? They pushed out a bunch of IPOs here in the last few months. Very profitable. Good for the bottom line. Why are the stocks not reacting more? Because everybody knew it. Right. Everybody knew it was like time to cash in on IPOs. There was no new news here. No new news here. And they got a beat. But that was, you know, earnings were not expected to be really anything special up or down. I think that's why even despite a beat, you see the stock actually down. Nothing, nothing there. There. That's why we've got an in-line rating for earnings distortion score. All right, let's round out the financials. BlackRock, another expensive stock. These guys beat too. Top and bottom line, you know what? Great business. I mean, you think so. I mean, they're not very profitable. See what's going on here with a false positive. Yeah, accounting earnings are doing a lot better than economic earnings. You see both are positive, but accounting earnings looking at looking like they're going up and economic earnings going down. You know, I mean, look, the asset management business, especially if you've got all those passive indexes that are doing great and you're the one that's winning. I mean, basically that's just that's what BlackRock is. They've got the indices. They get the majority of the assets. And that's, that's how you win. Winner take all in that kind of situation. They're doing really, really well. They've talked about using some AI in their model portfolios or some of their ETFs, and it doesn't work. Theirs doesn't work. Ours does. What's the difference? Better data. All right, let's, let's go one more financial here. Did we do Citigroup? We didn't do Citigroup. Yeah. Citigroup. This is what a lot of like my friends on the, in the, on the street will say. Citi is kind of like the worst of all, the weakest of all the banks. And they kind of have a reaction like, like Wells Fargo. I think people may be more surprised that even these guys did well. But this is, you know, look, I see the investment banks kind of, they're slowly dwindling in number because the business is is really not— doesn't really necessarily add a lot of value. And you've had so many people rush into it. They're all trying to get their piece. And I mean by that employees, people who are looking to make themselves money, not really their clients or the markets. It's become basically, you know, a way for financial pirates to steal from unsuspecting investors. And so I don't know, I feel like we're going to continue to slowly see the big investment banks implode. One by one until there are very few left. And then, and then there will be— you won't need an investment bank. You'll have— you don't need them as an intermediary. You'll have sources like our AI agent with Google Cloud that will give you answers on stocks, all stocks that are reliable and trustworthy. And so you can skip the middlemen and just go straight to the good stuff. One other financial company I want to add. They just reported in line. What happened in their report? It's a beat. Estimates will loosen credit as consumers remain resilient. Charge-off data, higher profit and revenue. So it's a beat, but the market doesn't care. Market doesn't seem to care. Why? Well, because it's probably a fake beat. Decentralized finance beats the middleman too. Agreed with that. But at the end of the day, you can do all the finance you want. You don't have good information about what to invest in. That's what matters, folks. That's really what matters. I wrote a piece on this a long time ago around our DIY ETF. And really the idea here is that, look, why DIY ETF? Why? Why build your own? Why not? As long as you have got good information. Now, for sure, we've seen some major innovations in the trading business and investing business by virtue of the fact that, right, well, you don't have to pay transaction costs. You can invest in small lots or fractional shares. So typically, so you can put whatever kind of money you want to put to work. At whatever level, and I think that's great. I think the real thing is like that's going to make a difference long term. And here's my view of the investing business, right? Like, I mean, it's 103 trillion. This was these these slides were from like a year ago, but 103 trillion and a huge numbers in revenue and profit. And what's protecting the Citadel here, right? It's the ability to trade before long ago. You had to call up your broker. They traded for you. Costs of trading were prohibitive. High-quality research, couldn't get it. Distribution is just me. I don't have any economies of scale. The ability to own lots of stocks, super difficult because I had to buy everything in 100-lot shares. So fractional shares, free trading, online trading gets rid of all these walls. Really, except for high-quality research. That's the only thing that we're missing to put individual investors on the same footing with all these insiders and completely disintermediate them. That's decentralizing. That's disintermediating, Sam. So I'm with you. But I think a big part of the disintermediation, decentralization of finance is in high quality of research. And that's what New Constructs does. We have broken down that barrier and we're making available to everybody this incredible analysis that we do. So good that it drives alpha. That's how good it is. That's the best way for me to talk about how good our research is. Drives alpha. Name me another research firm that drives that much alpha. And name another research firm that's got papers from Harvard Business School, Ernst Young, MIT Sloan School of Management published about the superiority of their data and ratings and models. The rest of my case. Let's talk about Albertsons. Let's talk about Albertsons. All right, we got a brand new Q coming out here any minute. They're also suing Kroger about the merger collapsing, but we like this stock. It's pretty, you know, it's good business, cheap. I think it's— I wonder how it's done this year. I know it was super defensive early on. They beat expectations on digital and pharmacy gains. So yeah, good jump, good beat. This was a beat that mattered. We predicted a beat that resulted in like 9, 10% movement in the stock. Not bad. Not bad. Gains in low margin businesses. So digital, getting more digital and pharmacy gains. You know, that's, that's, can I say, if you'd had our earnings distortion score for this, for this company before the earnings, you would've, you would've been able to do well. Decent company, cheap stock. Something to take a, take a close look at. Credit rating, not as strong, but these are highly leveraged businesses, so I wouldn't be too worried. This is again a relative score. They've got enough cash to cover the debt, so, or decent amount of the debt interest coverage is decent. So, but these have always been sort of low margin scale businesses, and Albertsons right up there with the best of the best. All right, let's talk about Johnson Johnson. Now these guys I think had a great quarter, so I think we missed on this one. Raises sales guidance, good results on earnings, so I guess beats Q3 earnings and resumes. So they, so they beat and raise guidance and stock is flat. So whatever the beat was, don't trust it. They're selling off the orthopedics business. I think they got some good stuff in the pipeline. Look, these pharmaceutical companies are great. I mean, you know, it's great business, great business with the scale they have. You can see it's been bid up. It's pretty expensive. So I think this is one of those, you know, all the good stuff is priced in. Avoid it, avoid it. Or, you know, look, if this is the best you can do is get a neutral-rated stock in your portfolio, I would take it. If you don't have access to attractive stocks, then you should maybe go for Domino's Pizza, poster child for one of the original super stocks. What is a super stock? Super stock is making more money than people realize. And if you don't know what that is, you should definitely sign up for our next training on super stocks or watch one of our prior trainings on super stocks. But these are companies whose profitability is way better than what, what the rest of the world understands, and we go into that in detail. And Domino's Pizza has been a pretty amazing performer when it was first recognized as being a super stock, or when the super stock conditions were first in place many years ago. I think it was like around here. Well, you can see the stock's done really, really, really well since then. Now, and it had an attractive rating back then too, right? So now, yeah, not so good. It's gotten expensive. You know, and I've talked to some good friends in the business about Domino's Pizza on this front because, well, we liked it a long time ago, but it got expensive. And, you know, I got a good friend in the business, didn't want to let it go. Didn't want to let it go. And I'm like, man, it's expensive, dude. I mean, we just can't. We run the reverse DCF model on this and it's just expensive. We're getting a new 10-K any day now. So we'll see how this changes. But look, really high return on invested capital. Got no problem with that. Got no problem with that whatsoever. But let's see what they say. Rise on earnings, they beat. Everybody's beating these days. Everybody beats, right? Because they keep the bar low. But you know, the last 5 days, nothing really going on. Nothing really going on. Up a bit and then down. So pretty much flat. Yeah, because yeah, you know, it's an expensive stock already. If you are interested and you want more access like this, we are actually doing a training next week on how to get the earnings playbook, the AI-driven research earnings playbook, and get earnings distortion scores for the companies that we believe are most likely to beat and miss this season for the entire S&P 500. We're running a special and we're going to be giving those stocks away. away and a special package that will give people access to those. I will see if I can't put it— give you a link to that. Here's the link to register for the training and promotion based on getting access to the companies most likely to miss and to beat and all of the research that goes into that, how we do it, how we create the list, who's on the list, why it gives you an advantage. And then, and then for the rest of this year, We're going to give you access to model portfolios that help you, help you find the best and the worst in the market. We scan the entire market to create the most attractive stocks model portfolio and the most dangerous stocks model portfolio. So you know where you need to stay away and where you ought to be. All right. Any other, any, any more questions before we sign off today? Okay. Thanks for being with me. And we will, we'll probably be doing a couple more of these over the next few weeks, but if you really want to get access To the information that gives you the real scoop on who's going to beat and miss, you need to sign up for the service or come to our training next week and get, get the top 5 and the top 5 likely to miss, top 5 likely to beat. But if you really want to know what's going on every single day, you need a professional membership. You owe it to yourself and your clients to do the diligence required to not get fooled by Wall Street. Thank you. Have a good day.