New Constructs' Live Monthly Podcast - 15 Nov 2024

Welcome in everybody. David will be joining us in just a few minutes, but we'll kick it off right here at the top of the hour. It's our monthly podcast. I wanted to start with a quick quote that we'll expand on a bit in the podcast today, but AI is not magic. There's no such thing as magic, especially in the stock market. That was from our recent report, Beware of AI Fakes. David's e-letter sent out through email, and we also catch it on the website as well. But we'll get things moving. This is our monthly podcast. We're calling this one the Post-Election and Earnings Season Insights. Be with myself, Kyle Geske II, and like I said, David Trainer will join us here in just a moment. Um, welcome in. Start off with the disclosures and disclaimers. Um, you can read these at your own, but main thing to note is we are not advisors. We are publishers of research. We're not making any recommendations. So take that and read these as you will. Um, on the agenda today, we've got quite a bit in here. The podcast is once a month. We take topics from the community, take questions, talk about different research on the site. You can get the replays and slides from this podcast presentation in the community. I've got a link in here that we can also share. If you have not signed up for the community, you can go to newconstructs.com/society, or we can send out that link as well. The next podcast, like I said, these are monthly. The next one will be on December 13th. Had quite a bit of research since we last talked with you guys, at least on the podcast here. You may have been in some of our other trainings or webinars. But we've got some danger zone and long idea updates, some new danger zones as well. We've closed some positions, updated the model portfolios. David, like I mentioned, David put out his latest e-letter. That was e-letter 19, Beware of AI Fakes. David was at the Stansberry conference recently. He did another interview on how AI is not magic. That's where that topic came from. Got new info on the Bloomberg New Constructs indices that we'll talk about a little bit. We finished up our Sector and style ratings reports for 4Q24. So you can get the how to find and how to avoid the best and worst ETFs and mutual funds by sector, by style. Those reports go in detail, you know, 5 best and worst sector and style ETFs, mutual funds, and those are actually available on the website for free. So you can check those out. Updated our model portfolio performance through the 3rd quarter of 2024. And then like I said, we've got most attractive, most dangerous, a bunch of different model portfolio updates. Those get updated monthly. We'll email those out when they are available. And yeah, get the emails and then we can also access them through your portfolio when you log into the website. As for the topics we'll go into today, and we do have some special webinars and trainings coming up and just happened as well. We'll talk about 3Q24 filing season a little bit. Like I said, David's latest e-letter. And then some topics from the community and the market in general. The SMCI auditor news and some warnings behind that. The new constructs indices. We had a question on Honeywell we might get into via our rating system. We had some community member trade discussion we can look at briefly. And then I want to note to send us any other questions. We want to hear from you guys in the chat or the Q&A. And then at the end, we'll take stock requests. We'll, you know, Get them in the chat, in the Q&A. If there's any repeats, we'll do those first, you know, most requested, and then otherwise we'll just do some random picks. Those are only available for the live audience. They will not be in the replay as a special thank you for attending live on the presentation. And with that, we'll get into the special webinars. We do have an upcoming training this Monday, 11/18, called Decoding Q3 Earnings: Investor's Guide to Finding Tomorrow's Winners Today. Emails have gone out and will continue to go out through the weekend. So you can look for an email there to sign up. And then we just had our Let's Talk Long Ideas for pro and institutional members only. David goes in and does kind of deep dives on recent long ideas, questions from our pro members, questions about the market, you know, anything David's seeing. We recently did one of those on November 12th. We've got the replay posted in the pro-only, pro and higher section of the community. So if you are a pro or institutional member, that is available in the community. You can go check that out. There's also links to sign up for future ones, I believe, if we got them in the community. If not, we can get those sent out to you as well. Let me see here. We've got requests for a ticker here. So yeah, definitely get those in and we'll take those at the end. First topic here, interesting headlines and happenings. We wanted to talk about 3Q24 filing season. We've almost finished up. I think we're finishing up the big chunk of filings today. But so far since November or October 23rd, we have parsed 2,768 filings. We had some record days in there. We saw, you know, down here on Friday, November 8th, 465 filings came in for calendar 3Q24. And so that is mainly 10-Qs right now, some 10-Ks mixed in between. But we estimate that as being worth, you know, $2.5 million in value to pay someone to do that yourself. So we're very proud of the work to get all of this knocked out in, you know, what is this, a couple weeks here, and get all of those models updated with the latest quarterly data. It's a massive undertaking, you know, made possible through our roboanalyst and our team of analysts going through and validating all that data, making sure all the models are accurate and up to date. Hey, David, I see you jumped in there.

Yeah. Hey, sorry for being late, man. I was on a call with another firm. It was some potentially very good news for a big client section of the client base out there about more availability of our research. So yeah. Awesome.

Anyway, well, we can say we planned it like this because we're just finishing up the filing season recap here and we'll move into the latest e-letter that you wrote. Beware of AI fakes.

Are you guys able to see my— is my video on? Can you see me? I can see you and see the screen, but I can't really tell what else is going on here.

No, I can see you.

Oh, you can? All right, good.

Great.

Yeah, I'm going to then share my screen. Is that working? No?

Yeah, I can turn— oh, let's stop that. I can turn off the screen share and you can jump in. You know what?

I don't need to. I don't need to share my screen on this because it's It is what it is. Yeah. So let's talk about AI. I mean, look, Kyle, I mean, we've been talking about AI forever with our clients, and this is just a great interview and a great piece I put together to just kind of summarize what we've been discussing with, with folks and on in these meetings for, you know, several years. And that is that, look, most AI is fake. Like, it's smoke and mirrors. I mean, look what we've— look at the All the money and hoopla that went around ChatGPT, you don't hear anything about ChatGPT anymore except about how much it hallucinates. And people have, unfortunately, I think, really put the cart before the horse. And, and by that, I mean they're thinking that the technology is all that matters. As long as we got this AI, large language model, machine learning, whatever acronym you want to throw at it, as long as that's in place, Oh, well, then things are good. And that's just not true. It's not true at all. What matters more than the technology is the data. Just like any model since the beginning of time, when I remember starting in research, everyone was like, oh, model's only as good as the data points. Because I started my thing in modeling and financial modeling was about economic earnings and better metrics to analyze corporate profitability. And people pushback would always be, oh, you know, The model's only as good as data goes into it. And I'd always say, well, yeah, we focus on data back then. And today, it's about the data. Models are like engines. Data is the fuel. The model can't move forward without any data. You got to have some. But if you really want a sophisticated model, you need to have high-end fuel. If you really want a sophisticated technology like an AI to work, you know, you don't put regular unleaded in there. You know, you put jet fuel in there. And that's the only way it can work. I just wanna make sure people get that, right? AI is a, is, is a bunch of programming and, and manipulation of data in a new way. And if that data's not good, then the AI is not good. So it's as simple as that. Simple as that. And so if any AI out there isn't willing to let you see their data, Run away. If they don't let you audit their data, run away. If it's a black box, run away. People should be proud of their data. Pure and simple. If the data is good, then the AI should work. And I think when it comes to AI in general, AIs that'll be useful, it will not be the ChatGPT, the Gemini, the whatever AIs that we've heard about there in the popular press. Those AIs don't really work. Right? What percentage— somebody chime in here in the chat— what percentage of the internet do we think is reliable? And if it's only, you know, then, like, I mean, how do you base your models on something that's 50% reliable? Let's say— and here's the problem— let's say it's even 90%, which we know is way higher than what it is. The problem that even when it's 90% reliable, You don't know what 10% is wrong. So if you don't know what's wrong, you can't trust any of it. That's the problem with XBRL. It works most of the time, but the problem is when it doesn't work, you don't know unless you go in and check the filings yourself, which is how we do it. So this whole thing about like cleaning data and fixing up data and the data doesn't have to be exactly right, that is just wrong. That's the propaganda they want to serve you and teach you so that you buy what they're selling. And that just comes back to what makes us different. All of our data is 100% auditable. We have proof from some of the most prestigious institutions in the world that our data is superior and the best in the business. And there's that same, that same proof compares to the legacy datasets to show that it does not have it. Why? That's why you get novel alpha in our data. So, That's exactly what we're talking about.

And on that topic of, you know, how accurate is the internet, we could be entering a part where it's almost circular in that the AI is now populating on bad data, which then feeds it even more bad data. And so you've got that circular down spiral of, hey, things might not be more accurate as we go forward if we keep basing off of these, you know, AI generative AIs and everything on faulty data.

Completely true.

100%. I'm gonna throw in the chat for everyone here. David said we've been talking about this for a while. We got an ebook actually back from 2018 talking about machine learning and AI for smarter investing. So if anyone wants to check that out, I'm gonna share that with everyone.

Yeah, and the slides which will be available in the replay will have a link to the Stansberry conference video, which is great. I was really happy to have, uh, an opportunity to articulate this, uh, in, in a modern way. But that— because that ebook is old, man. We OGs on like data quality and AI, man. Seriously, we, we wrote, we wrote about that a long time ago, and it's— that's the real deal. It's good.

I think we'll move to the next one. Topic here been in the news: SMCI auditor resigning. Which leads to, as David mentioned, AI issues with that and, you know, fake accounting in AI. It's a topic that not often does the auditor, I think, resign in public, kind of state, you know, hey, we're leaving and making, you know, a news release out of it. But it was something that we warned about in the community actually back in August of 2023, well before a lot of the SMCI was making headlines. There was some Poor disclosures, items they were leaving out that Garrett found in the filing that kind of led us to, you know, suspend the rating and note that, hey, there's issues here with the internal controls and some of the accounting going on.

Yeah, man, this is, this is like stellar work by Garrett O'Grady. I've forgotten about this, Kyle. This August 2023?

Yeah.

Yeah, I mean, unbelievable. And then again in August of 2024, Garrett suspended SMCI because of lack of internal or questions about internal controls based on some research he did. So, I mean, we really, and thanks to Garrett, crushed it on warning on SMCI. And so, yeah, the joke here, that's that I made Kyle put that in there, like fake accounting and AI. You know, we're talking about fake data, you know, and AI driven by that. Well, some of the AI firms maybe are faking their accounting as well. Look, there's so much hype here. I think everyone's trying to chase these crazy returns and stock performances that you, you just got to be careful. I mean, the, the, the, the, the— what the riches are so tantalizing to these folks that they'll do anything. I've seen it happen on Wall Street selling deals. They would do anything to make that kind of money, including sell stock in companies that had No business model, like a joke.

I've heard—

you've probably heard that story 100 times. That's what Wall Street does. That's how they make their money. And, and if you don't know many people on Wall Street, you know, the reason they get away with that is because they only have to be there for a couple years. You're making $30, $40 million, $100 million a year, you know, you got to do that for a couple years, you retire, you never look back. You don't have to be accountable for what you sold folks. So yeah, Kyle, that's, that's amazing work by, by Garrett to Pulled this out. Wow, it's almost to the year. So it was I think it was August 24th when we saw the if you look at the rating on SMCI, it's got that suspended warning around internal controls on August 24th, 28th, 28th, even closer. So like literally 365 days later, he nails it again. That's amazing. That's freaking amazing. And then, yeah, the auditor resigning. You never see that. You never— I mean, that's like, I don't remember that's happened. Maybe Valeant, which we also warned about. And then Enron and WorldCom were before New Constructs, so we didn't get a chance to warn about those. Yeah. Awesome work there. Awesome work. And look, we're really proud that we do this kind of— provide this kind of service to our clients. It's amazing. On top of the great data we're parsing all the time, these kinds of warnings. You know, you just can't put a price on how valuable that would be, how much we could have saved folks. We did save folks who paid attention.

I think great segue there with the value of data. Next slide here is talking about the Bloomberg New Constructs indices. We've got a new section on our site that details all of these with links out. I don't know if we want to go and take a look at those pages or—

Go ahead. Yeah, listen, you know, Don't take my word for it is my favorite line in marketing because, you know, I came from Wall Street and those guys are not afraid to say whatever they need to say to get your business. And, and they've, you know, I mean, I've heard lines like, if you ain't lying, you ain't trying. A friend of mine who's one of the top Wall Street sales guys, that's like his, that's like his, his thing. We've had a lot of experience with these vendors. And so I think it speaks volumes when third parties write papers or invest tremendous amounts of resources to create indices based on our data. All right. It's not— this is— this takes— it took months and months and months for these guys to get this stuff set up. And they've created 3 of them and we're probably going to create a whole bunch more. But we've got the New Constructs Core Earnings Leaders Index. There was a press release about this one. The Core Earnings Leaders Index because it's been licensed to an ETF. But the Core Earnings Leaders Index just basically takes advantage of the alpha in our core earnings data, very similar to what the Harvard Business School and MIT Sloan paper said they should do. And then probably my favorite one after core earnings is the New Constructs 500 Index. This is one of my favorites because I've been talking about this, Kyle, for like 25— even at Credit Suisse. I, we had the idea that, look, instead of, instead of weighting the stock, excuse me, weighting the stocks in the S&P 500 based on market cap, why don't you tilt towards earnings capture or basically core earnings power? Like, isn't that a better way to put together an index? And not just the S&P. Why don't we do it for the NASDAQ? Why don't we do it for the Russell 2000, 3000, 1000? The S&P 1000, the S&P 1500? How about every sector fund out there? Why don't we weight stocks that are representing any given market or sector? Why don't we weight them based on their core earnings power? Why not? Right? Like, it's just a better way to do things. So, I think that this, what I call smart indexing or enhanced index, I believe that's going to take over the market. Like, how do you make a straight-faced argument? Everybody in the chat, like, can you— is there an argument against weighting based on core earnings as opposed to market cap or equal weight? Is there any good reason not to go with core earnings considering it's proven superior measure of profitability? It's got idiosyncratic alpha. Let me know because I can't think of one. And then the last one, hey, if you had any question about how good our ratings are before, Harvard wrote a paper, Harvard Business School wrote a paper based on talking about how our ratings outperform Wall Street ratings, right? Well, guess what? Bloomberg has created an index based on our very attractive stocks. And that's done really well too. Click on one of those tickers. Click on the Total Return Index, please. So on the comparison tab in the middle of the page on the right, you type in S&P and it'll pull up the S&P 500. Should give you— yeah, there you go. And then look at the last year.

Oh, that's not the right one.

Is it going pretty slow?

Yeah, it's— screen share is eating up computer.

Question about the core earnings. No, the core— it weights based on core earnings. So, oh, but they're cap-weighted choices for inclusion. There's some truth there. Yeah, it's, it's only includes stocks in the Bloomberg 1000, and then there are weights on, on how, how, uh, big a percentage each holding can be. That's answering Stephen's question in the Q&A. So yeah, and by the way, on all those pages You got the year-to-date. Go to one year. I'm not seeing. I can't see actually.

Chart chart's not loading. I don't know, but we've got the performance up the top here. There's the one year.

We're dominating.

Twenty-two to nineteen.

Yep. And then five year. It's even better.

Yep.

Yeah, it does really well. You could do the same thing with the B. You go B core T. If you look at the five-year, add that instead of no, no, no, no, no. Put it in there.

Oh, into the yep.

Yeah, that way we can look at all three at the same time.

Yeah.

There are not ETFs for the other indices. There's only an ETF for the Core Earnings Leaders Index.

Yeah, you can see that one does even better than the very attractive.

Yeah, it's it's pretty awesome.

One twenty one there.

And then I think B500 is—

that might be why Bloomberg wants me to log in.

Oh, do you have access to, to the login? If you don't, I do.

Nope, I don't have it right now.

Okay, maybe that's why we were— yeah, why— maybe it was also why it was slow. Let me share my screen, see if that works. See here, indices. And click on one of these tickers. Yeah. Is that all visible? Yeah.

Now we see it.

It's looking— it's coming up way faster on my screen than it was on yours. I don't know if that's S&P. There we go. And we can do 1 year crushing it. And then let's see, what's the ticker? B500 NCT. That's already in there. We go Bcore.

Bcore.

Is that the right ticker?

That was the Bcore T, right?

You got to see Bcore T. Yeah, yeah, I'm sorry. That's the funny thing about— there it is. And then let's get ticker for the Bloomberg 500. That's what B500NCT.

I think you've already got that one. I think the one we're looking for is BNCVA1T.

Thank you, Kyle. So many tickers, a little time. All right, there we go. Yeah, it's— I mean, that one really does— that's— I'm impressed, like, because they're very attractive stocks, you know. Hey, look, don't fix it if it ain't broke, folks. We got a great rating system. But you can see all 3 doing way better than the S&P 500. 1-year, 5-year, really impressive.

Yeah.

Can we put this on the website every month? Probably not going to like do that, but I do, we do, we might be able to throw a picture on here. That's not a bad idea, Kyle. We, we do have a, where do we put the, the, the blog posts for the S&P 500, for the, for the indices, Kyle? Do you remember where those are?

Not off the top of my head.

Let's see. Core earnings. There we go. October 29th. You can see I did put some performance in here. This was back at the end of October. So it's not a bad idea. Not a bad idea. Yeah. Yeah. Great question. So from Fazal, Nvidia is in the Bloomberg New Constructs 500 index. Correct. But the rating is coming up bad. This isn't just about the ratings, right? So, and if you guys have been watching any of our recent trainings, you know, we are moving beyond our ratings. Look, ratings work great, but that's not the only thing we can do well. I mean, we've got a lot of great data, and it was important to me early on with New Constructs to, to find at least one way to manifest the superiority of our data. Well, now we have a new way— core earnings. The core earnings strategies are all about core earnings, and And how core earnings are better or different than the accounting earnings, or how core earnings are moving versus accounting earnings. So that's a strong enough signal in and of itself and on its own to drive investment decisions. So yes, the core earnings index will— core earnings leaders index will often have stocks that may not get a good rating because, you know, our rating system isn't perfect. It's not perfect. And there are stocks oftentimes that get bad ratings that do extremely well. If our rating system were perfect, friends, we'd be doing this meeting on my jet or my yacht because I need more. I don't know if I could fit everybody in a private jet. On our yacht, which would be the size of a cruise ship. By the way, Kyle loves cruise ships. Kyle's the cruise ship king. There's tons of cool cruises. Anyway, you get my point. Like, Yeah, there's better— there's other great ways to take advantage of the data. So it doesn't always have to work that way. But great question. What stock universe to choose from? The B500. So yeah, all these guys choose from the Bloomberg New Constructs 500. Let me go in here. Let's go back to these pages. What you can also find on these pages is a ton of detail. So like the index methodology will give you all the details about How this ETF is create— sorry, this index is created and everything that goes into all the security selection, all of that. Like, you want— here's the formula. It's earnings capture equals this, right? Index weighting. Look at these fancy formulas, right? No securities weight shall exceed 4.5%. All right, so, you know, all the details, they're there for you. So there it is. All right, Kyle. You want to take back over? You got some more, some more slides we want to go through here?

Yeah, we've got just a few. Let's see.

If you don't, I want to jump in and answer some of these questions about Tesla because people say—

I mean, the only other question the slide was going to have is we had a question about Honeywell. Maybe we can look at that on the ratings. And then just wanted to let everyone know that the replays and slides will be on Community. Again, you can check those out if you have not signed up.

Yeah, community, guys.

Link right now.

Yeah, community here, replay slides all here for trainings, for everything. I mean, get on it, right? Like, that's just a great, great resource. And by the way, we've got some like all-time amazing people making comments and thoughts in here. I mean, Ryan Mitts, check out the deep dive he's doing on SMCI and warnings he's got about NVIDIA. NVIDIA's round robin. Financing. John Hollinsby, you know, on these stocks and his option strategy stuff, unbelievable. I mean, we should be— we should— John might need to be on the payroll here pretty soon. I mean, we did a long Ideas Only, a private session with John and a bunch of other professional investors. That was unbelievable. I mean, I mean, John's a very modest, great guy. I wanted him to take over the meeting. Like, John, you can talk about this better than I can because I'm not really an options guy, so really impressive work by John. Really impressive. Yeah, and also, yeah, you're welcome on all these indices, everybody, every single page, fact sheet methodology, fact sheet methodology, all there as per the normal. New Contrast is extremely transparent and all that. Price to core earnings might be more helpful. Yes, kind of. Yeah, that's another ratio. We could do that one. That might be— who knows, Don? That could be, uh, or Gerard. That could be another way to get alpha from our data. But we're finding new ways all the time. In fact, we've done some— those of you who have not been at some recent trainings, we've had some special offer deals where we've got some stock pick bundles based on some really cool stuff we found in our data. They were like, oh, it's like a super rating, because when a good rating's in place and this new special criteria is in place Kaboom. And then there's another bundle that really just focuses on 2 criteria and the rating doesn't matter. So look, we've got a treasure trove of data here and we're really just scratching the surface. So the rating is not the end-all be-all. It does pretty darn well, as you can see here. Look at the purple beating everything over the 1-year, but not over the 5-year. 5-year, the B core and the B500 But you get the idea. All right, so let's talk about Tesla. How expensive is Tesla? So I ran in an optimistic scenario here that looks at a huge improvement in revenue and margins over the next 11 years. So what's really cool about this, this new, this new feature we have in our system is it shows, it'll show us the implied revenue, right, specifically for Tesla in the forecast horizon. So in order to justify the stock price at $350 a share, here's what the company's got to do. It's got to grow revenues at 30% compounded annually for over a decade and improve its return on capital versus cost of capital average to 163.6%. That means return on capital is going to be much higher, but the average over that time frame. So margins have got to like— but what we can do is say, okay, well, what does that mean? What does 30% compounded annual revenue growth mean for 11 years? $1.7 trillion. I think that would put Tesla in the top 10 in global GDP, right? So, and I think, Kyle, maybe you could look up like the last time we looked at the global And, uh, electric vehicle market by 2025, I guess, or sorry, '35, 11 years from now. What, you know, the global EV market is probably supposed to be, I don't know, probably around this big. So that's, that's a big number for Tesla. So then let's take a look at what this means for return on invested capital. It's been around, you know, mostly zero. And here recently it's gone up a little bit. Now it's come back down because I think everybody knows their margins are coming down. By the way, if you don't know that, you should know that. The last earnings report was— had a lot of fake numbers in there. Not good. Cutting back on R&D, capitalizing expenses, which is what WorldCom did, which is what Valeant did. So, but still margins are coming down. Returns on capital coming down, I should say, here, right? So you're 10.6% in the TTM, and the market believes it's going to go to 475%. You know how many times in the last 5 years there's been a company in the S&P 500 that's even had a 500% return on capital? I think it's maybe 3 or 4 times. You know how many times it's been maintained for more than a year or 2 years?

None.

But they're gonna maintain it, you know, into perpetuity, effectively what this means. And, and they're gonna just keep rising. And by the way, that's a car company. I think we can all agree by now Tesla's not an AI company. AI doesn't work. That thing in Austin a few months ago, that turned out to be kind of a joke. The robots were fake. They were controlled by humans. The, the cars, the machines, they drove down a Hollywood studio driveway. They didn't navigate anything, and Waymo is way ahead. So yeah, I don't know. I don't know what else to say except I'm happy to keep popping the bubble here.

Yeah, it looks like I'm trying to find a dollar value. I see some reports, you know, $1.6 trillion by 2035 for the EV market.

Okay, so the EV market's going to be $1.6 trillion and Tesla is going to be $1.7. That's to justify the price. So folks, this is, this is an institutional tool, as you can see, which is why it's so important. And if you wanted to actually see the actual numbers being crunched, here's the optimistic scenario. And you can see here, so here are the implied prices, right? You look at the cash flow over time, we're running it out, and 11 years out is when we get to— well, you get to $309. Now the lookup function on the, on the decision page there looks for the price that's closest to but still less than. Looks like really you're looking at 12 years. That's 365 because 350 falls in between. Implied revenue in 12 years is $2.2 trillion. So anyway, this is what goes into new constructs ratings, right? So when you're talking about ratings in particular, You know, the rating that reflects this reverse DCF analysis we just talked to you about is this market implied gap rating, and it's greater than 50 years because for Tesla, I don't put a— you know, our systems don't put in optimistic scenarios. Our system puts a default scenario in. That default scenario is, is going to be based on consensus. So guys, you can see the 30% numbers I put in here for optimistic. Right, are way, way above consensus, right? And we're actually probably being generous because consensus doesn't even go out this far. And then our margins are, are also pretty high, assuming they, they get back to some of the highest they've ever been, higher than what they've been before. That's in the default scenario, folks. When you put that default scenario in there, that's the blue line. You know, it's hard to justify more than $28 a share. That's one thing that Gordon Johnson and I have in common. We've been saying the stock's worth about $25 for a long time. And I think that's probably— that could be rich because a 10.9% pretax margin, an after-tax margin of 10% is way, way high for a car company. It's double, I think, any other car company, including Toyota. Like, maybe why don't we look that up real fast? Where, where's my rating? What's the ticker for Toyota?

Toyota's TM. I think 7% was once the, like, highest sustainable.

Um, that's right, if I'm remembering correctly. Toyota, 9.7%. Okay, that's the best margin, you know. And guess what? Guess what Toyota's making the heck out of now? Hybrid. Hybrid's been taking market share from EVs for a while because it's way better for the environment and every way— cheaper, more efficient, all that. Okay, I think we are done. How do the best investors use the ratings in portfolio management as it regards timing of purchase and sales? For example, subject stock drops from attractive to neutral. Worse, do they sell immediately or put in to sell group at next stop? Same question for upgrades— immediate or next? Peter, great question. So we're not a market timing tool, and a lot of times the attractive rating is a great place to start doing research. An attractive rating is a great place to raise red flags. You know, the ratings themselves do really, really well. We've got a lot of model portfolios that are based on are based on our ratings and have a lot more kind of entry and exit idea. Like, we tell you to buy equal weight what's in the most attractive stocks. You know, most dangerous stocks would be a short equal weight, is the way that performance is measured. Same with safest dividend yields, dividend growth stocks. And so the answer, should you buy and sell immediately when ratings change, is I don't think so. You know, even with some of our our focus list stocks. We have kept them in the model portfolio even when ratings have moved to neutral, sometimes unattractive. Sometimes there are bigger factors at play. There are some short-term fundamental changes that, you know, will, will, will throw some noise into numbers. So again, the rating system isn't perfect. It's probably the best rating system out there, and we've seen the performance, but I would not say it should dictate what you trade. Should not dictate what you trade. It should dictate your research. If the rating changes, it's time to pull back the COVID take a closer look, and make sure you think your thesis is still good, especially if the rating changes because things get nutty out here, right? So like when you look at a stock like Apple, which I think we called it like $19.50 or something super low a long time ago, I can't remember, you know, great company, no longer a good stock. So when I think the ratings change because it's gotten expensive, That's for sure a place where I think it's time to start thinking about reducing exposure because you've had a good run. Now, in these days' environment, like, a good run might just mean it keeps going. You know, I mean, we look at some of the super nutty stocks, you know, as of late. One of the things we revisited in the danger zone lately is like Peloton. You know, what's it done? Just gone. It's nuts. This makes no sense. So do you see, you know, where, when do you short? I can't usually tell you when. And again, we're not in the business of giving out specific recommendations or trading advice, but it's information to help inform people who are professional investors. Timing is not really our thing, Peter, to your question, to be, to be candid. We're not really that good at timing. It's not something we focus on. We're really focused on giving you the truth about fundamentals. And we're really kind of old school like Warren Buffett. Like, we're not trying to be market timers. We're trying to allocate capital as intelligently as we can. and, and trusting that, you know, market psychology will do this, but market intelligence will help you do this. I hope that's a good question. On the energy companies, we like a lot of energy companies. It's hard to say. I'd have to go into detail on looking those up. But I, I think that energy, you know, if we look at our sector ratings, you know, energy is still number one, you know, looks great. So there's a lot of, a lot of good-looking stocks in that sector. that we think present a lot of opportunity. You can see here, like, the number of stocks, you know, 12 get a very attractive rating. That's the best, I think, in the industry, 18% of the sector. So there's a lot of mark— a lot of good-sized market cap stocks getting cheap, good ratings. So, all righty. Thanks for the, uh, advice on RA Channel, Vetify, and Bloomberg ETF IQ. I'm hoping, given our relationship with Bloomberg, we're going to be getting on Bloomberg ETF IQ Soon. But be sure, everybody, take a look at those pages if you want more information. Get the word out there about these indices. I mean, it's more proof that what New Constructs does. And as always, we thank you for your being with us today. Kyle, if I don't— you don't have anything else? I don't have anything else. We're good to go.

Nope. Just thanks for attending, and we'll get the replay up on the community once it's available.

Awesome. Thank you. See you.