New Constructs' Live Podcast: Intelligent Capital Allocation - 13 Sept 2024

Investors who use expectation investing will have a fundamentally better way to evaluate all stocks, setting them on the path to success. That's a quote from the homepage of the Expectation Investing website. It was also in David's latest e-letter on the secret weapon to call the top in Nvidia, and we'll talk about that a little bit later. But Thought it was a great quote to point out and lead with today's podcast here.

Yeah, I mean, I look, I think in a world where everyone recognizes the market is getting expensive, liquidity appears to be, has peaked, you know, and I think a lot of really smart people I've known over the years have said, you know, look, valuation doesn't matter until it does. And, you know, we're getting to a place where valuation appears to be mattering and expectations investing is probably the best, if not the only real way to make sure you're not putting yourself at huge risk, or to at least know how much risk you're taking by being in some of these risky stocks, expensive stocks.

This is Intelligent Capital Allocation. I've got myself, Kyle Guska II, and CEO David Trainer. And it's the 13th of September, Friday the 13th. Start off with the disclosures and disclaimers, quick review. We are publishing research. We're not providing any advice. You can take a look at these at your own time. The agenda, got a lot going on. We will be talking about what was going on in the community. I'm talking about some of our recent research, some different headlines, stuff going on with new constructs. Upcoming podcasts, we got one each month. You see their dates, October 18th, November 15th, December 13th. You're registered already. I believe you're already registered for all of those. should get emails on them. Put out a ton of stuff, research since our last podcast, some long idea updates, danger zone updates. David's put out some different e-letters on different market topics. We finished up our macro trends and sector fundamentals research looking at, you know, core earnings, ROIC, free cash flow yield, and different metrics for the S&P 500 and then the NC2000, which is our all-cap index. Let's go super in-depth. We've got client versions and then some abridged versions that are available to the public. You can check those out. share slides with the replays, and all these links will be available to you guys. The most overstated earnings, most understated earnings, looking at, you know, basically who— whose earnings are too high, whose earnings are too low compared to what we're actually seeing with our core earnings numbers. Um, and then comparing S&P operating earnings to core earnings, a bunch of macro and S&P-level work there. Um, different updates beyond that, you know, but David put out a video on how to read our stock reports. We'll talk about that a little bit. Um, put out Most Productive, Most Dangerous, Exec Comp, Safest Dividend Yields and Dividend Growth Stocks. Model portfolios had multiple updates, um, all available to clients as well. Um, on the next, you know, interesting headlines, we've got some articles here we'll talk about as we move into the, um, presentation podcast here. And then stock picks. If you send us any stock requests, we'll probably have time to look at one of them at the end. We can take a look at it through our ratings. So put those into the chat. Or the Q&A. Um, we'll gather those and find a lucky winner at the end, or maybe popular demand. We'll see if there's any repeat requests. But on the special webinars front, we do have an upcoming training, uh, The Hidden Metric That Reveals Undervalued Stars in the Stock Market, and that'll be September 18th. So next week, we'll send out emails right now on that signup. So the registration links for people to use, we're excited about that one. So. Want to get as many people signed up for that as we can. Interesting headlines. This will be in the community as well as new constructs information as well. Talk about some things going on. First, got a model improvement. We updated the way we're treating interest and debt for home builders. You can see here that the main update, you know, we start treating capitalized interest as an operating expense instead of a non-operating, and then treat all debt as operating debt instead of financing debt. I think The overarching thesis or reason for this update is to, you know, better handle the debt and interest for homebuilders when they're using it to acquire land, which essentially then sell the product. So it's more of an operating expense rather than non-operating as it would be with financing. Let's see here.

One other comment I'd make about that model improvement is you're not going to find this kind of research, I think, anywhere else. I mean, name another— tell me another research firm that said, hey, by the way, we've gone out and we've improved our our earnings model to deal with accounting idiosyncrasies or accounting changes. Name another firm, put it in the chat, put it in the Q&A. Name another firm that's doing that. We are constantly refining, improving, maximizing the effectiveness of our models. Those models already proven to be the best in the world by multiple independent third parties. And, you know, and yet we're still at it. I think anybody who's ever performed at a high level knows, like, you know, the only way you get there is by working really hard and you don't stay there if you don't work even harder. And that's what we do. And I think that that's just another thing that makes us very unique.

Next one, we've got a link we'll share in the chat here. David, looks like I'm not able to send to everyone, so I'm gonna send it to you and then you can hopefully share it with everyone. Okay. But a video David put together on how to read our stock reports, it goes in depth on all the details that are available to the reports that you can get at our pro and institutional level. the different adjustments, different sections of the report. That's a great walkthrough on, again, how to read those reports. We'll, we'll send that out. And again, this link will also be there.

Free research on Amazon too, right? I mean, it's, yeah, it's a, this is, this is what's, this is just helps people understand like the depth of the work. And, and it's a, it's like, it's in an 8 or 9 page, 10 page PDF and like you're getting in that one PDF, you're probably getting $25,000 worth of minimum of work on a company. I don't know, at least that's what it would take, you know, expert on Wall Street. Like, that's bam, you know, and that's one ticker. And we do that for 10,000 stocks, ETFs, and mutual funds every day.

Yeah, a lot of times when we're sharing some of this, it's dated and whatnot. This is a recent report, so definitely check that out if you're interested in Amazon, as David said there. Yeah, nope, I do not want to play that. Let me go to the next one. Share a little bit of tooting our own horn here. We were ranked again number 1 on SumZero for 40 straight months now. We're very proud of this. Um, you know, shows the power of our research, stock ratings, and then basically putting that into action on those long ideas and short ideas, danger zone picks. We've got a bunch of different categories here that we are very proud to rank over, you know, number 1 against 16,000+ buy-side individuals. And what leads to that, those stock ratings, is, you know, recently finished up 2Q24 filing season, went through 2,800 filings, just over that, had some record days in there, had, you know, 436 filings parsed on August 9th here. I believe that was recent record. And so we're, you know, updating the models every quarter, every day when we get new filings, with huge amount of value created for everyone that is using those ratings. And it is this, this work that drives all those ratings that can then create the number one ranking on stock picking and all that. So I want to point that out. And just again, we're very proud of the work we do, and we like to be able to share that with you guys. Next up, I think we're going to dive into some of the community topics, maybe some topics David's put together on, you know, secret weapon, calling the top in Nvidia, kind of highlight what's going on in the community and in the market. I don't know if, David, you want to start with the secret weapon post you did?

Yeah. Yeah.

Talk about that a little bit.

Yeah. This, this post was, if you don't mind pulling it up, Kyle, I'll let you keep driving here if that's okay.

Cool. Yeah, that works.

Yeah. This, this, this was like a, a big effort on, on our part to try and make the reverse DCF model more accessible, easier to use, right? Because so much of what we do— there's 2 reactions I usually get when I'm talking with clients, potential clients. The first is, oh, it's too good to be true. I can't believe this has been done. And that's really kind of gone away a lot over the years, but it still happens quite a bit, especially at the institutional level when people haven't heard from us. It helps a lot that we have this deal with Bloomberg. Yes, recordings will be available. Sorry, just going through a couple other questions here. And yeah, in terms of the PACER, I'm sorry to get off track here. The PACER ETF, Cal's just looking at questions here. Yeah, it's not real free cash flow. It's operating cash flow from operations. It's like, that's like, that's just a super easy, quick way. I hope someday we'll have a competing product based on a more, a much superior version of cash flow because ours is superior. And so That's, that's a backdrop. Like, we got superior data, and, and one of the things people, you know, they have a hard time believing in that. But then when we point out the fact that we've also got this superior valuation platform, right, we have all this great data historically, and we put it to even greater benefit by being able to roll it into a reverse discounted cash flow model, one of the most, if not the most sophisticated reverse DCF models in the world ever built. And look, discounted cash flow models are not easy to use. And so the big, one of the biggest and first things I ever did when I was planning new constructs was how do we scale this thing? And it's really not that hard when you break out of Excel because Excel is like all single individual users. And for that, you know, people are so used to Excel. I used to, you know, I'm a, I used to be an Excel guru. I think it's been a while. I'm still pretty good at Excel, but nowhere near the dudes that have been, you know, cranking on it. a lot more than I have in the recent past. But trust me, I love Excel, but it's got limitations. You can't scale your Excel models. You can't make updates across multiple models at the same time. You can't do all the things you need in order to run an enterprise system like what we have. So we created that. And that's a big part of what the roboanalyst does. And what it allows us to do is to do exactly what expectation says should be done at scale. And the most beautiful thing about doing this at scale, and probably the most important thing about doing it at scale, is that we have even better comparability around the feasibility of expectations baked into stock prices. We know where expectations are the absolute highest, most optimistic, most ridiculous, and the least, most pessimistic, most conservative. Because we're looking at thousands of companies, which gives us the ability to create these screens— most attractive stocks, most dangerous stocks— with an unprecedented, unrivaled level of precision and accuracy. Thus the great performance. Our focus list, thus the great performance. Some zero stock pick rankings, thus the great performance. Not only we're doing things with a, with a, an unrivaled level of analytical rigor, But we're doing it at an unprecedented level of scale. And that's a big, that's a big deal. And this reverse DCF model just kind of gets overlooked because, you know, we've got all these great ratings models, whatever, stock ratings, you know, tons of great stuff. But then, like, when you can go in and drive one of these, you know, I call it a weapon because no one else is doing this at scale or no one else, and very few people actually doing this with, you know, individual companies. But you can put in whatever scenario you want. I say loading the weapon. Let's put in multiple different kinds of scenarios for Nvidia. Let's put— let's forecast NOPAT margins and revenue growth at super high levels. What does that mean? How does that— what does that fall out? You know, then let's do something that's a little more conservative. And so when we do that, we can really take aim at like, what is the value of the stock we imply? And so, you know, in Figure 2, This was done after I called the top. So I called the top at 126, and at the beginning of this report, if you haven't seen it, you know, you can, you can hear the recording. I'm not making it up. I called the top August 26th, and I think the stock was trading at about 126. And we wrote this a little bit while later. I think this— I'm not sure where the stock is right now today, but I think it's come back some, but it went down some more since then. And so You know, what we do is in that middle column, in the blue and yellow squares there, we tell you exactly, like, to justify the price, it's got to grow at like 47% compounded annually for 8 years with a 513% return on capital versus cost of capital spread. And then on the left, you can compare that to what the company's done in the past. So the revenue growth is around— is aligned with what the company's done in the past over the last 5 years, not as much as the recent past. But 47% over any significant amount of time is pretty ridiculous, especially for a company this large. What's even more ridiculous is that 513% return on capital versus cost of capital spread. And by the way, that's the average over the 8 or 9 years, 8 years. And then in the yellow column, I say pessimistic, you know, you can call it whatever you want. And keep in mind, you can do an infinite number of these in our system. The point is just to provide some examples for folks, right? So don't quibble with me about like, oh, you should be at 48% or 52%. If you want to do that, put it in there. That's the beauty. Like, I love showing the portfolio managers we talk to, like, you know, oh, you want to try 75%? You want to try 200%? Go for it. Put it in. We'll see what happens. We can do this as many times as we want. So I'm just throwing some examples out there. And in the pessimistic scenario, I say, listen, why don't we knock growth down a little bit, 29%? Instead of 47%, and, and margins too. So what happens? Well, now it takes twice as long into the future to get a value in the DCF model that equals the current stock price. Makes sense. If I'm not growing as fast, I'm not as profitable, it's going to take more time for the business to grow its profits, to grow into its valuation, to grow the profits that are baked into the current stock price. And that growth appreciation period number that gives us for the, for the stock price at $117, 8 years and 16 years, that means that's the number of years the company's going to grow its profits. So after that 8 years, profits flatten out. After the 16 years, profits flatten out. There's no more profit growth. That's how you do this kind of work. That's what makes it a dynamic discounted cash flow model, because we're not out there trying to predict the future. We're going to look at multiple timeframes. And as you'll see in the next part here, we're looking at over 100 years. Right? So the idea is, is, is, is when you are, you know, you aim the weapon, you get the expectations, and firing the weapon is answering the question, do I agree with the expectations baked into the stock price? Do I think Mr. Market is about right? Or expectations too high? Expectations too low? And I think that's a much better position to be in than trying to be a fortune teller and predict the future. And so this Figure 3 comes straight from the decision page of our models, just like Figure 2 did. And you can see the implied values over a long period of time. And you can see that high growth in the, in the early years is, is, you know, jacking the prices up. Exactly right. And so the blue line, that's the optimistic scenario. That's the 8-year gap. The yellow line is a 16-year gap, and that's the pessimistic scenario. And then I think what's even more cool is, is on our— is on our decision page is this ability to look at historical revenue compared to future revenue and historical profits compared to past profits, or historical ROIC compared to future profits. And I do that in the video replay. I, I, I toggle through a bunch of those. But this is like— this, this is just a great way to put it into context. Like, you know, we know Nvidia is a big profitable company. One of the biggest and most profitable of all time. But look at just how ginormous the future revenues have to be compared to what the past has been.

Yeah. When you see the future, it makes the past look like nothing. Yeah.

It's like they've done nothing. You ain't seen nothing yet, right? And that's when we say price for perfection. That's what that means. And so, you know, these numbers here speak for itself. You know, you're looking at 1.3 of implied revenue at the end of the growth appreciation period. $3.7 trillion in implied revenue at the end of the pessimistic growth appreciation period. And the next thing is to like, you know, how does that compare? Like, I don't know what $1.3 trillion means. That's more than the 17th largest country in the world GDP, right? And keep in mind, you know, and the $3.7 is more than the number 5 world, number 5 largest country in the world GDP. I think that makes it pretty clear that those are some really, really big numbers. Now, part 3 here is like, okay, so maybe I believe in the revenue growth, but do I also believe in simultaneous improvement in return on invested capital? So we're seeing huge growth in revenue, huge market share gains, while also returns on capital going through the roof. Like, I don't think you can do both. Either or are extraordinary. Both Ridiculous. So you can see here the implied— the return on invested capital for Nvidia at the end of the growth appreciation period for the optimistic scenario would be 839%. It would be 975% in the pessimistic scenario. Both of those are extremely high. I went back and looked at the S&P over the last 5 years. The number of times a company has earned a return on invested capital over 700% for any one period in the last 5 years? Zero. It's only happened once, 600%, twice at 500%. And yet Nvidia is going to do better than all of those, you know, anything that's ever happened there, way better at 839% while also growing revenue. Seems ridiculous. Anyway, I'm, I'm, I'm gonna— we're gonna move on here, Kyle, because I think I've beaten this.

Yep.

You know, the idea is, is that there's— I don't think there's a snowball chance in hell that Nvidia can achieve the expectations baked into the stock price. And this is the kind of work that goes into every one of our ratings.

I think that last point you mentioned on the, you know, S&P, how many times it's happened, also points to the scale that you mentioned in the beginning. If you don't know the companies in the S&P 500 and don't have models on them, you can't compare what does 839% ROIC mean.

Such a great point.

Great. That number sounds cool, but what does that mean compared to everyone else? I think the chart here on Apple and Microsoft also speaks to that as well.

Yeah, it's, it's hard to really honestly quantify how valuable like the platform like this is when you can not only do this analysis but then have apples-to-apples comparisons across so many companies over, over time as well. Have we got any requests for tickers? There we go. Oh, there's some Q&A. There it is. My bad. I read an article that said Nvidia chips were available from resellers in China cheaper than retail here. Can anyone verify that? I've definitely heard of people who, who, who've built businesses and had to shut them down. A friend of a guy I just met recently owns a small manufacturing business and does specialized manufacturing and had to insource it all here in the United States because he tried doing it in China. And what, lo and behold, he found out at one point that China was knocking off his, his very specialized builds and selling them to His his same customers at 50% off. I mean, talk about biting the hand that feeds you. Question about companies in the new coverage queue. Yeah, I'm not surprised. I know we're working on some new companies. So Kent, thanks for asking. We're adding companies, and I know we're adding a bunch. I think there should be a few more coming out. I'm not sure if they're on your list or not. Yeah, Carl Mays, great question. Companies that have maintained a profoundly overvalued. Price based on sentiment, Wall Street narratives, etc. What's the longest? Yeah, I think I am saying Nvidia sort of 3 sigma territory. And that's part of why we wrote the Nvidia report when we did is because it's about liquidity. As long as the liquidity environment is strong, we're not going to see any pullbacks.

I don't think—

I just think it's going to keep going on because there's no risk. Right. And that's part of why my ears perked up when the yen carry trade started to unwind and you saw Nvidia get crushed. And I said, oh, This is one of the most leveraged names in the market. It's a lot of hot money going into this name. That's part of what's pushed it up so far, right? Clearly a crowded trade. Everybody knows it's a crowded trade. Wall Street, as I've written in some of my e-letters, they can afford to take the risk of being in overly, overly expensive, super risky, crowded trades because they see the order flow. They're going to know that stock's going down before it goes down. And that flash crash we had back in the beginning of August, Right? Institutions could trade, but could retail people trade? All the retail platforms were down, some longer than others. You know, that's just another way of like, you know, giving you a warning. You know, when the music stops, you could be in real trouble. So that's part of what we do. We're not here to say that— like, Carl, to your point, I can't tell you exactly when the music's going to stop. I can tell you, you know, how dangerous certain chairs are or how much How unlikely it is you're going to be able to get a seat in certain chairs when the music stops, you know. But I can't tell you exactly when, but I think it's about liquidity, and I think we're starting to see here that liquidity is coming down. Would it be interesting to hearing what you think about CERE as it was announced that Berkshire Hathaway is now their largest shareholder?

We'll do that.

We can do CERE at the end here. Let's see what else we got here. We got a deep dive on counts. SMCI, awesome post by Ryan Mitz. Man, you got to check that out. I mean, Ryan does some great work. I mean, you know, at some point we got to get Ryan on the team here because like his investigative reporting on what's going on to complement our work, unbelievable. And by the way, I want to make sure SMCI, we, you know, we waved the red flag on that a while ago. Anyone who knows our work, if you look that stock up, we had suspended the rating because there was a big red flag about a lack of internal controls. Raised by the auditor. That's a big deal. In addition to the super expensive, you know, you got to watch out. And then there's another post here that that that Garrett said. Is it because this Garrett talking about the poor disclosure?

Yeah.

I mean, dude.

Yeah. This was back in our the filing season 2023.

Yeah. In the community right there, we were out early on this. We've been really early. Sometimes we're too early. I get it. I get it. But you know what? When you look at our long side and you see the performance there, focusless long. And in a lot of our other model portfolios, the risk-reward pays off, my friends. We're staying out of the junk, crazy, risky names, and we're giving you people— giving people access to the, the better, you know, the cheaper, safer names. What's another— what else we got on our list, Kyle?

We've had some great posts from John here on a lot of stock trades and options trades going on.

John is awesome. And, and, and for those of you that are pro and institutional, Definitely check out John's posts on, on options and a lot of trading strategies. He's doing a lot of really cool stuff here. Yeah, I think a lot of our Prosperity Pub new, new clients and, and members would love John's work. He's doing some super cool stuff with the options. You know, people ask us about options all the time. Look, we don't really do any— we don't do any option research, but we do provide best-in-world, I believe, analysis on the underlying. So, you know, when your option strategy is bullish, we can help you be smarter about which stocks it's good to be bullish on with an option strategy, or for the option strategies bearish, we can help you with that too, and all the combination of that. So it's just a better fundamental foundation for an option strategy because you got a lot of, you know, you got a lot of choices about where you want to make your play, and there's just better fundamental risk-reward to make an option play or run an option strategy on stocks where fundamentals are better, or stocks where fundamentals are worse, depending on whether or not you're bullish or bearish.

I'm gonna go up at the top here. I think it was actually in the questions, something hopefully some community members will chime in. I saw a post on, is now the time for consumer discretionary stocks? Now there's a lot in the system that have good ratings, you know, could be value traps. I think that's one of the topics people are looking at. So I'm hoping we get some more action and commentary on this one. It's definitely an interesting topic. And our consumer discretionary in our macro research profits are looking good. They've been growing actually quarter over quarter, year over year for quite a bit now. But it's a situation of, is it getting, you know, too hot or is it, you know, coming to the end of its time on the stock prices as, you know, we look at interest rates coming down or, you know, consumer spending, where's that going to go? So I think if we can get some commentary here, that would be great from the community members. I know you guys are definitely interested in this stuff.

Yeah, let's talk, you know, and Ray, new member, welcome to Ray. Shout out to Ray. Made some great posts questioning about fixed income. You know, I don't, you know, I'm not, I'm not a political expert, and this is a cop-out, Ray. I just, you know, and I think one of the things you'll— that I'm proud of at New Constructs is that we sort of know our limitations. We don't try to, to sort of, I don't know, wade into discussions where we don't really feel like we have an advantage or insight. So, you know, one of the things I think the takeaways that I've been reading is that the policies between Kamala and Trump are really not that different when it comes to taxes and, and most of these things. I think really maybe foreign policy is mostly where they're different. But for the market, in terms of the market, the Democratic versus Republican policies are not that different. And we're going to probably see a split Congress. So nobody really expects much to get done. So sort of the difference between the 2 candidates maybe doesn't matter that much. That's what I'm reading. I try to keep what I'm reading very middle of the road. I abhor the extremes and will refuse to spend any time there. Don't watch any of the TV or any of that stuff. I just don't, I don't play with that. I try to follow some people who are willing to do some of that and subject themselves to that kind of punishment and come out with intelligent Responses on the back end. I'm grateful to those folks, and but yeah, so yeah, it's tough, Ray. I'm really tough. We're not we're not great. You know, we're not fixed income focused. We do have credit ratings, and we can provide credit ratings at the macro as well as the micro level. And a lot of that you get, you know, in the equity ratings too. If you just look at the quality of earnings, so sorry, it's hard for to hard for me to say which fixed fixed income sectors instruments are likely to perform more favorably depending on whether the election goes Democrat or Republican. I I think the I think my main takeaway is that it doesn't make that much of a difference. We're not going to see really anything pay off that well. You know, I think there's some slight differences in the energy policies, but I don't see them as that different myself. So not a lot to say there. Yeah, Kyle, go ahead and hit the, the macro stuff because we just published a new batch of macro research and the macro research is some of the best stuff we do by far.

Yeah, real quick, pull one of these up. I'm looking for the core earnings showing kind of what we're looking at on the— how the earnings look compared to GAAP earnings on these reports. And then here is actually the consumer cyclicals item. You know, consumer cyclicals has been core earnings way up, GAAP earnings actually down in the most recent quarter. And so this is kind of the, the analysis we've got on all the sectors in those reports and much more. We've got some details on the actual underlying drivers of each of the metrics. But I think the chart here, you're looking at earnings looking very strong core earnings-wise, you know, the dip in COVID, and since then it's had a super strong rebound. And so we've got, I think it's one of the few sectors that actually grew core earnings quarter over quarter in the most recent period.

And I just want to take a quick second, Kyle, to talk about like this data goes back at the sector level to December 2004, 20 years. And this, we have this for every single sector. And in the main report here, you'll see that we have a breakdown for every single sector. So overall S&P 500, every single sector. And one of the things we see every time we do this research is that sector by sector performance varies widely. So if you go back up to number figure number 2, Kyle, on the, or number, go to number 1. No, wait, wait. Where's the overall S&P? Oh, we don't have the S&P 500 in this. Oh no.

Yeah, I pulled up the public version. Just so we can— this one's available for everyone to see.

Yeah, the, the— whatever we see, oftentimes I like to think about— go, you can go back down to the, the figure 3. You know, as the S&P 500 is sort of like the ocean, and everything kind of looks calm and flat compared to the, to the sectors and, and underneath, like they're going like some are up, some are down. It's like wildly different, which is always fascinating. But there's a lot of normalization when you aggregate it all up to the S&P 500. And I think the other thing to point out is that we do this for return on invested capital, for free cash flow, for NOPAT margins and capital turns. So you have a really, really, really amazing macro kind of work here across all sectors and all the major indices. Like, here's return on capital versus cost of capital.

Yeah.

Oh, there you go. And then you can see we also break out the capital turns and margins. So you can see capital efficiency headed down. Right, which is you know part of why the tech companies look so great. But you know what have we seen here in this AI race? Well, it's going to be a big capital spending. So returns on capital profitability is going down on the margin. I think technology's kind of you know sucked as much as they can out of the workforce and consumers. We've seen unprecedented margins for a long, long time. It's only fair to assume that those things have maxed, and and now they got to go back into a spending phase. To do something new that's going to create value. And I think that means on the margin, you know, cash flows, returns on capital aren't going to be as good for a little while. Another quick question on the, the big picture environment, you know, from Ray. Yeah, maybe liquidity is more important than policy. Yeah. Yeah. And to the extent policy affects liquidity, yeah. Because it's, you know, as long as like you're still giving out money, people are going to still keep spending it, you know, because that's what happens. You give people money, they just go spend it. And the more you give them, the more indiscriminately they spend it, which is what creates inflation, which creates capital misallocation and creates meme stocks, right? A meme stock is like a direct correlation to too much liquidity. People are going and playing meme stocks. We've got too much money in the market. When stocks trade at valuations like what we got with Nvidia, we have too much money in the market and capital's getting wasted. You know, and, and it's part of why we do what we do at New Constructs is because we want to give people the information they need to allocate capital more intelligently. Because that's better for society. We don't need to make the people in the Mag 7 and Wall Street any richer. They're plenty rich. Last I checked, Zuckerberg, plenty rich. Elon Musk, plenty rich. Let's put this money into companies that are growing and creating real value. We don't need to enrich these other folks anymore. They're doing great. There's a crowded stage. Let's find places to put this money where it's going to make a, a better impact on society and do it to people that deserve it more. And that's, that's a big part of what we do. And, and, and that accrues ultimately to the individual investors as well. That's the purpose of the capital markets, the way this thing works. And, and I think we're really proud. I was going to say, I think Wall Street's not in that, in the business of that. And we are really proud to provide folks an alternative. And we're proud that what we do ultimately makes the world a better place.

Yeah, that'll do it. We'll get the replay up. We'll post that in the community, the video. We'll also share the slides in there as well. And we will see you out on Community in the meantime, and then again here next month. So hope you guys have a great weekend, and until next time.

Thank you.