Recap Earnings from JPMorgan Chase, Netflix, Taiwan Semiconductor, Goldman Sachs, and More

Welcome everybody. Excited to be back with you doing our earnings watches. Today we've got a good one. A lot of big companies reporting a lot of cool stuff. Glad you're with us. If you did not see a training we did earlier this week on Wednesday, I highly recommend that. I'll share the link for you in a second. But that was really awesome. We have released a new product, never before available, that makes the superpower of New Constructs accessible to everybody. And the superpower of New Constructs is that we can do this really highly rigorous analysis on the entire market and truly give you the best and the worst. No one else can do that. And I think that's why we generate alpha for our clients, whether it's our live-traded indices, Core earnings leaders, very attractive stocks index, our ratings, our model portfolios, SumZero. Folks, the stock picking, the alpha, it's all out there. And then the vetting, the credibility, I don't think there's a more credible firm out there than New Constructs. Harvard Business School, Journal of Financial Economics, Ernst Young, MIT Sloan, we're doing it. And I think the only knock is that our products are expensive or Less accessible for the average investor. And we changed that with this new discovery option. We give you access to a screening tool. Is it as cheap as some of the other providers? No, it's not. Should it be? Heck no. Is it an extremely good value? 1,000%. And look, institutions are paying us 10 times that amount, 20 times that amount. Just one portfolio group within some of these institutions, paying us 10x, 20x because that's the value they get out of it. And so, look, we are moving downstream from institutional into a more individual investor network. And I want to democratize access to this stuff. I can't give you all the good data. Otherwise, some hedge fund's going to come in and sign up for that and not pay me the real number. So, we have to be careful about how we ration this out. But I want you to know, nobody beats us on quality, of data, alpha, credibility, anything else. Let me share here in the chat. Here's an access to the training. Highly recommend you take a look at that. All right, let's get into our earnings watch today. I'm showing you our institutional service, and so I'm going to create a new portfolio, earnings watch-04-17. All right, we got our portfolio. We'll come in here. Find that portfolio. I will copy those tickers from another location, paste them in here. There it is. And here are stocks to talk about today. Let's go as we usually do with the biggest market cap stocks in the group. As usual, if you got any questions, put them in here. And if you want me to cover a couple of your tickers, maybe you sneak one of those in there. If we have time, we'll get to it, but we got a lot to cover today. So let's first, why don't we ask Claude? Let's see what happened with TSMC's earnings this week. Can probably handle the typos. Oh, that's not a good answer. Let's, but it's honest. I'll give it that. What do we ask ChatGPT? The line, blowout quarter and raise guidance. Boom. In short, they crush it across the board. The demand story, guidance even stronger. So why didn't the stock pop? Why didn't the stock rip? Priced to perfection. Expectations already really high. Well, that's a pretty good answer. Let's take a look here what we show. Yep. Good company, bad stock. Why didn't the stock rip? Yeah, and I think like this one, even on a PE basis, what do we have here? Some of our stats. Price to earnings, 37 times on the trailing 12 months, 38 times. Yeah, everybody and their mother knows it's an expensive stock. And look, earnings looking okay. We're about to get a new 6-K on this that will likely, if anything, the rating probably gets worse because given the expensiveness of the stock, the yellow, the red, the orange here, there's not much they can do in this element to be that much more profitable to make this better. It's possible. It's possible. We'll see. In fact, it could get better as soon as we get the new 6K in here. And I take that back. If we see a substantial rise in net operating profit after tax, this price to the economic book value could go up quite a bit. But look, good trends here. Returns on capital, everything's going up to the right. Strong business. And yeah, you can see the price going up. The economic book value could go up quite a bit too. We'll see. But yeah, not a bad answer by ChatGPT. And you know what else I'll say? Not a bad answer by Claude either for being honest. We're actually gonna publish a piece this weekend, and we're gonna do a special podcast next week about how much AI lies. And I ask— actually recommend that if you have access to any AIs, ask them, why do AIs lie so much? And you'll be quite surprised by what you They know it's a problem. It's a feature, not a bug, and they flat out admit it. So very, very interesting. Very interesting. All right, what do we got next here? JP Morgan. Who knows what we think about JP Morgan? Focus list. It has been for a long time. Still attractive. Look, we were into this stock when the price to economic book value was down below 1. No-brainer. I remember telling Kyle, I can't believe the stock is so cheap. What blows me away on this one more than anything, folks, free cash flow. $28 billion, $30 billion, $26 billion, $44 billion, $41 billion last year. These guys are like, this is making money on the scale of the big tech companies, yet trading at a substantial discount. And I say big tech companies, I'm talking Apple, Google, Microsoft, and better than Microsoft. It's really just Apple, Google. It's like Apple, Google, GM. Like, those would be the Mag 3 in terms of profits. It's altogether a different story for those folks. Let's take a look at price action for JPM this week. I think they had good earnings. Resilience in US economy tops estimates, does well. Stock for the week, yeah, not, not great. I think the overall market was up a good bit more. Interesting. Jamie Dimon, great leader. I remember back when Jamie Dimon was running a little company in the Midwest called Bank One. And I remember talking to my boss at the time who was covering banks. And I was at Credit Suisse and we were doing— I had moved out of the special project that focused on economic earnings and core earnings and NOPAT and was covering stocks. And I remember him saying, this guy, Jamie Dimon, he's a really good CEO. This Bank One company is profitable and growing. Something we've never seen. Jamie went on to go to take the— to run the biggest bank in the world, or one of the biggest banks. Pretty interesting story. But yeah, JP Morgan, and this is something we've been saying for a long time, this has been a great stock. It's been performing great. It remains profitable, and yet it doesn't make the headlines. And this is a perfect example of popular is not necessarily good. Great company, great stock. Greens across. And yet you don't hear people talk about this as one of the popular stocks on CNBC. The number of times that TSMC is mentioned compared to the number of times JPMorgan is mentioned on CNBC or in the media, probably 20 to 1. Even when Jamie Dimon is making these sometimes controversial prognostications. Interesting. But that's what we're here for, to give you the truth, not what's popular. And that's why we outperform. Because popular investing is just following the crowd. It's not going to get you anywhere. How about J&J? Strong miss. What about J&J this week and their earnings? These guys had a blowout quarter too, I believe. Similar situation. Great quarter, but not great guidance. And you got good company, bad stock. This stock's been on a real run. It's had a tremendous year. You can see just here, it's, it's been, it's done well. Look, it's making a lot of money. They had a lot of potential concerns about patent runoff, or investors did, and these guys have just reloaded, which is very impressive. Let's see, how do they do this week? Take a look. Compared to J&J, down on the week. So not impressive enough, folks. I think what I'm seeing these days is like the market's a lot more discerning. It's just not saying, oh, you beat the number, rocket ship, everything's great. They're looking at guidance, they're looking at valuation, like this is starting to matter a little bit. And I think as the Fed has been running down the balance sheet, there's a little less free money going around. And what do speculators do when there's a little less free money, man? They shut it down. They're a little more careful, a little more discerning. And I think that's an extremely attractive time. market for you as a client of New Constructs. If you've got our tool, you're going to do extremely well in a market that's more discerning. Do we do great in markets when everything goes up? Yeah, the Core Earnings Leaders ETF and index have outperformed in a great market. But do we do extremely well like this past first quarter? If you look at our focus list, Outstanding. Absolutely outstanding. Made money long and short. Extremely good. And that's the core, big core of what we do. Our ratings doing extremely well during this time because when the markets care about cash flow, nobody measures cash flow better than we do. ASML, similar story, folks. Green is good, red is bad. When it's mixed, good company, bad stock, super expensive. It did better, went from unattractive to neutral. I think that's because we had a new K here recently. And by the way, we're going to suspend stocks. Got a question about this. We suspend stocks when we're not 100% confident about the fundamentals, about the data. And that's going to happen like when they're late on a filing or when they've done a big acquisition or if they're FDA dependent, like it's a biotech company under like $100 million in revenue, $100 million, I'm sorry, Under $100 million in market cap biotech, like the fundamentals aren't helping us with that one, right? It's going to look like a bad business. It's all dependent on whether or not that trial goes well. So, we'll suspend that. Now, we'll still do our work. We'll still do the work to give you a sense of the underlying economics and the valuation of the business because that's useful. But the utility of the fundamental data for companies where there are exogenous events that are going to potentially change the fundamentals dramatically, we're going to take a step back and suspend. You know what? Our system is not as good in these areas. We're being honest. We're not here to give you an answer no matter what and say everything's great, all the good, all the time. No. What's one thing that's really special about New Constructs that no one else can claim? Only 3% or less than 4% of all the stocks we cover And that's like 3,500. Of all those, less than 4% get our best rating. You know what that number is for Wall Street? 50%. Any other firm, similar. They're not allowed to give out sell ratings or unattractive ratings because it hurts banking business and the bankers make all the money. So ASML Netflix, good company, bad stock. What happened? Blew out the numbers, went down even though the business is doing great. Blowout quarter and then crashed, right? So yeah, folks, it matters when you're priced for perfection in a market where the Fed is running down the balance sheet. Look out, that matters. So if you're interested in being able to screen the entire market for the best and worst stocks based on the best fundamental research in the world at a price that's incredibly inexpensive to do something, to replicate something like this that people pay 20x for, check out that link I just dropped in there. There's a replay. If you know you want to buy at the special price, I'm going to drop a link in here right now for that as well. Get it now because that won't be out there for long. We do these deals for very short amounts of time for people that are paying attention. Because people a lot of the time are absolutely happy to pay the full price. So we do not run the promotions forever. And why are they happy to pay the full price? Because it's an amazing deal. This, this special offer that I just dropped the link for also comes with a free Most Attractive Stocks report, a free Most Dangerous Stocks report, and a free long idea. Why do we give all this stuff out for free and for so cheap? Because you deserve to know that our stuff works before you pay the full price. Because I'm not holding this at bay. I'm not keeping this in an ivory tower where only the insiders get it. We're giving it to everybody because we care, because that's part of our mission, to improve the integrity of the capital markets, not to make the rich richer. Goldman Sachs, neutral. This company has been one that we have liked for a long time, has been attractive. I think I remember last year talking a lot about financials. Goldman Sachs was on our list. So let's see, Goldman Sachs this week up 5%. Yeah, I'm guessing Goldman Sachs year to date, one year. Yeah, Goldman's crushed it 80%. I remember last year people were asking me, you know, what about Goldman? As one of the most attractive stocks in the market. But Goldman Sachs was the one we had attractive for a long time. We can actually go back here. We can see rating history. You can see attractive like all last year, very attractive there in 2025, and then it's getting neutral. Neutrals don't mess with it, don't play with it. So you can still hold the neutral stock. We're not going to continue to make it attractive. I don't know if we still get in, but the valuation has finally started to catch up with the profits, which is pretty cool. Wells Fargo, attractive for the first time in a long time. Let me see here. I shouldn't say not that super long. It's been neutral and attractive. Okay. I know it's been cheap for a long time, but finally got some decent economic earnings. It's great. Trending up. Was very attractive, but the price has gone up here recently. And so that's good. That's good. Added to the dividend growth model portfolio. Very interesting. Yeah. Looking, let's see what kind of week they had. Take out Netflix. And let's see. Down for the week. What happened? What happened with Netflix? Sorry, what happened with Wells Fargo this week? Here's the real story. Mixed quarter. Beat on the bottom line, missed on the top line. All right, that's not great. So we had them in line. That makes sense. Reasonably valued, but it was neutral recently. So it's come down here. It's expensive, right? So especially for a bank that's been in this much trouble, not a very sexy play. Let's take a look at free cash flow. Remember we're in the $30s and $40s billions for JP Morgan and Wells Fargo's $19, $11, $15, $27, $25. Not bad. Not bad. It's a lot of cash flow. It's great cash flow for any business. How would you like it if your business made $25 billion last year? Good. Yeah. Wells Fargo. This is, it's an interesting play if you believe in the turnaround, and I think it's hard not to. These banks have such a huge moat because of the regulatory hoops and bureaucracy and paperwork that they have to jump through. Such a huge moat that it's just difficult for anybody to disrupt them, to take much market share. Size really matters. It's not, I don't think it's, I don't know if it's fair. I don't know if it's right. that they've aggrandized or aggregated so much power, these really big firms in our country and in the world. But it is a moat. And so you could see them being pretty profitable, continue to be pretty profitable for a long time. And they finally, hopefully, eventually get out of their own way. Unattractive. Yeah, not profitable. This is the one I predicted last year when people were asking me about the best financial stocks and we were talking about Goldman Sachs. I was like, the next big bank most likely to go under. And then there were 3 or 4 or whatever, because they just keep going down. And the bigger— the remaining ones keep getting bigger. Citigroup, unattractive, not a great, not well-run business. It's had a nice run here recently. Let's see what happened with Citi. Citigroup, man, great week. Probably had good reporting. That's good. They need to get better. This is what I call like a show-me company, a show-me stock. I got to see that they could actually put up Profits consistently, because I think all the banks did really well this year or this quarter. They all did great trading, great volatility. They're all doing great. If you're not doing great in your bank, you've got real problems. Let's see if Citi can put it together for— put together a few quarters in a row. That's the way I look at it. All right, Pepsi. I like Pepsi, man. It used to be on our focus list, I think. Look, I'm not a junk food eater. But I love seeing how Frito-Lay got healthy, right? I do love potato chips. I like picking up the bag and looking on the ingredients and seeing 3 things on there. That's a big deal to me because then I can eat more potato chips and not feel so bad about it. But anyway, Pepsi was great for a while. It was a great company and a great stock, and then the price went up. People forget it out. Look, folks, we're early on these things. We're really early, super early, sometimes even a little too early. We get out early also. We're really careful. We think we're smart about it. We buy the stocks where cash flows are strong and valuation is too low. And then when that rectifies, we say, you know what? We're letting that go. And we go find other stocks where the risk-reward is really attractive. And that's, I think, the beauty and the success of New Constructs is that we stay true to very attractive and attractive. We don't have to chase runners. We don't have to hold on to stocks and hope it does well because we're always able— and our ability to scan the entire market, as you can do with this Discovery membership, this new special Discovery membership— we can scan the entire market, find very— there's not many of them— very attractive stocks, less than 4%. But it's our ability to find the best That allows us to stay with the best, which is what allows us to outperform. We don't have to take bets on AI and high-tech and highfalutin companies narratives because we can focus on the fundamentals. Our strategy, our strategies can be grounded in real data and real analysis. I think that's what makes New Constructs attractive, and that's part of why we're the best research business in the world for fundamentals on US stocks. Going global soon. That's a big deal. We're getting that going this year. But yes, that's why we do what we do. And that's why I think people like us. And that's why I think our research is very valuable. That's why institutions pay us hundreds of thousands of dollars a year. Because we can help them do that too. All right, let's see. I got a few requests in here. I'm not going to necessarily go with the first ones I got. Because I want to talk about the one that we just came in because I think it's going to be the most— it's going to be funny. Monster. Come on. What do you really think we're going to think about Monster? Just kidding. No, good company, bad stock. And it's been— this has been, I think, a great stock for people for a long time. Obviously, when you get up here in the expensive, that's a good thing, especially if you work for these companies. If you're a CEO, I always tell people, Hey, our corporate clients. Look, no, you want your stock to have a neutral rating because you want the market to recognize how good a manager you are. If the stock were cheap, it'd mean the market was saying you're not a good manager. So you want a neutral rating. And for Monster, good, great business, fairly expensive valuation, especially considering it's a one-trick pony, folks. Like, we're selling energy drinks. Who else is selling energy drinks? Everybody. Everybody. Like, everyone's got energy drinks. So it's going to be difficult to, I think, maintain market share, maintain margins. Yeah. All right. Yeah, I got a question about the discovery tool filters. So the main thing that discovery does— and look, this is institution, so you're seeing all kinds of data. But with Discover, you still get the— you still get the green is good and red is bad. Mainly you get the screeners. You don't get the data on the screeners, but you do get the ratings. So you can go in here and you can say, I want to see— and I'm going to do this on their other end because I'm not going to give away all the good stocks— but give me all the best stocks in the healthcare sector, equipment and supplies. Go. And you can scan the entire market. All right, I'm showing the unattractive. Because again, I'm not giving away the good stuff right here. These are the bad stocks, right? And if you wanted to divide it, you wanted to break it down further, you say, listen, I want only the good stocks that have a dividend— obviously be greater than if you're going for attractive— but I want less than 3% and a market value greater than a billion. Go, right? And the list gets smaller. Lots of bad stocks out there, right? But if we wanted to go with only the The very worst, like we might go with only the very attractive. Bam, there's 4 stocks. So, what's amazing about Discovery is being able to screen the entire market. Discovery does not give you any of these data points in here. They'll be locked. This is why we can offer it for so much little, so much less, right? Because we're not giving away all this underlying data like the hedge fund guys would use to build their own models and do all these kinds of other stuff. We're giving you the takeaway. We're giving you the ability to screen everything. There's not an option. We do not make out— there's no option for stocks versus ETFs and mutual funds. Not an option on the number of stocks you can look at. It's everything. We've just found that's not something people like. Yeah. Great stuff. Doug, good question. Yeah, no, I think our AI, basically the AI that Google built, spent millions of dollars to build an AI based on our data. They chose us because AI based on good data is very powerful. But all the AI is, the FinSights— Yeah, I'll show you the page. FinSights. All right, it doesn't work right now because I'm on the old version. It's on the Vertex. You got to go to the agent marketplace and you got to do all this stuff. We're fixing it to make it user-friendly. But the takeaway is, yeah, all FinSights is really is just a— it's a different interface for all of our data. And, and we will be offering that to folks soon. I've been saying that for a while. I don't wanna talk about how much money you gotta pay. Google's had to pay just to take the AI from the lab where we made it to the public where we can sell it and get people access. Big company, big problems. When it comes to development and programming, Google is unbelievable. When it comes to pushing things to market, at least for us, it's taken a while. Maybe they're waiting because they're doing a big thing in Vegas next week where they're gonna talk about FinCISE. at their big NEXT conference. Maybe they didn't want us to have it out there before then, so they're dragging their feet. I don't know. We have it. But yes, great point from Doug about our community conversation around impact of AI and democratization of investing. If you guys are on our blog at all, you should check out the, just the regular stuff. I'm doing presentations all the time. I think we've got a blog post up here about what I did at Harvard. Recently, I'm going to publish my slides from my Harvard Business School presentation, publish the slides from my presentation to the Financial Planners Association of Middle Tennessee. Look, I want to explain to people how AI works. I think it's helpful. I think it's useful. We're publishing a piece this weekend on how AI is lying to you. And I think that's a new thing that's dawned on me. Like, wait a second, AI has a conflict of interest with us. Google, Microsoft, Anthropic, they're here to make money. Even ChatGPT started out as a nonprofit. Whoops. Nope. No, we're gonna make money. So what does that mean at the end of the day about using their AI? They're gonna design that AI to get you to use it as much as possible because that's how they make money. So what does that mean they can't do? They can't let the AI tell you to stop using They can't get the— they can't let the AI tell you to go, oh yeah, I don't know an answer to that question. Maybe you should ask somebody else. They're conflicted. And that's why you'll see when you ask an AI question like, I got it here. You ask AI a question like, why do you lie so much? Why does AI lie so much? AI doesn't lie in the human sense. There's no intent to deceive. That's the most laughable thing I've heard in the longest time. One of my, like, kids said to me, I lied to you, Dad, but I didn't intend to deceive you. I'd be like, all right, man, to your room. No electronics for 6 months. I don't know. This would be bad. Like, all right, that's a double lie on top of a lie, and you're acting like I'm stupid. Don't act like that's stupid. That's a big one. No, but you get what I'm saying. Come on. Come on. No intent to deceive. And then look, this is, this is what ChatGPT is saying. I'm trained to sound right, not be right. I'm not actually grounded on real data. I get to make stuff up. Incentive problem. Answering is greater than refusing. Better to give some answer than no answer. This is where I'm saying lying is a feature, not a bug. Pattern completion fills gaps so that if they don't know, they just pretend like it can make it up. Confidence calibration is weak. I'm supposed to act confident. High confidence on weak knowledge. Mixed quality training data. That's a nice way of putting it. It's the internet, right? Outright wrong content, outdated info, opinions. Blends all that into one probabilistic system. Anyway, you get the idea. Yeah, great question or great comment here from Doug. If you didn't see what he said about how he tried to use AI to replicate investing, the length and complexity of the prompt you got to put in there in order to get AI to give you the right answer. Yeah, pretty nutty. It's just not going to work. It's not. It's a long way. And honestly, it won't work until it's built on data like ours. That's what they got to do. And you guys have seen me talk about this and probably heard me write about this 100 times. Like this article we wrote on in terms of small language models lead to big leaps in investing. Just check that one out. Like small language models, the way to go. This idea you just feed the internet. Even Larry Ellison said, can't just expect that these AIs are gonna be good if they're all using, first of all, the internet, right? That's the mixed quality training data, and they're all using the same data. So what's the difference? Anyway, you get the idea. Thanks very much for everybody, to, to everybody for being with us today, and we hope you have a great weekend and check out that discovery offer. That's a very special offer. on an incredible product. Thank you.