B (4:24)

Just to follow up on that, you're selling memory. Does that include Something like a Micron,

C (4:30)

Micron, Sandisk, Kynix, Samsung, the whole complex. There's only a few western digits. Seagate, They've been the best performing stocks for the last couple years in the market. Everyone knows they're short. So the bull case would be the numbers are way too low. I think they are and they have good men. 3 month view. I'd stay long but in a 12 month view I think we'll have a problem. And I think everybody thinks that. And so like timing when to get out before everyone else is always the challenge. We have a problem that eventually they're going to sell off. Like if you look, let's take Micron as one example and I don't have the numbers in front of me, but I think the consensus has them earning $45 a share next year. Well, let's say they're in 75 at peak. Let's just assume that, you know, what are you going to pay for peak numbers when you know they have super perishable inventory and their earnings will get crushed eventually. Maybe you got 50% upside, maybe you pay 9, 10 times 6, $700 stock. We're in low mid fours now, 70% upside. But you also have 70% downside. Like institutional investors don't want to take a two year position at something that has equal upside downside. I think they'd rather get a 3 to 1 ratio of up down or something like that. So I think as this thing rallies, you'll sell. Now what is Micron? What are these guys saying? They're saying, well, we've gotten smarter because we've lost money so many times in the past and then so many done things and blown up so many investors for 30 years. We're smarter now. We're only going to build capacity if our customers tell us that they'll pay for it. So once you announce that, imagine you're one of the customers, you're like, you know what, let's give them a little extra dough and have them build a little extra more. Because we know that eventually when they put that capacity in place, the price will get killed. So I think you're getting closer to that story than maybe the consensus view. That's my opinion.

B (6:08)

I haven't talked to anyone who's negative on memory or even semiconductors because everyone

C (6:15)

seems, everyone knows they're short. I'm talking about how the stocks are going to act. But how many people have you talked to who were number one high ranked semis analysts like 20 years ago, for several years in a Row, you're the only guy. Yeah, I mean, I think I know stuff, but I might not. And like you can have, you can be. Look, I could be wrong. Everything I'm saying could be wrong for sure. And I think the challenge is the momentum's good. The numbers are too low and everyone knows it. The question is, what do you pay for something that's so cyclical? Remember, if you build extra memory, the pricing gets killed. If you build other parts of semis, there's no pricing problem. Why? Let's say I build an extra $2 converter at Analog Devices. And that converter, there's 20 of them in a dump truck cockpit for Caterpillar. If I cut the pricing from $2 to $1.90, it does not stimulate any Caterpillar dump truck demand. So if I build too many, I stick them in a factory and I wait for Cat to call me and I sell them to them designed in, I'm fine. Zero pricing pressure on my excess inventory. If I build too much, if, if, if, if supply growth starts at all. Catching up to demand growth for, for memory price pricing gets annihilated. They sell stuff at negative gross margin, they hemorrhage cash. So right now, for a variety of reasons, everyone on planet earth knows they're super short. The question is how much more will you pay? And when I see price action like this week on Nvidia where they have blowout numbers and the stock doesn't go up, it doesn't make me feel awesome about knowing Micron's numbers are too low. So it's more about how the stock is going to act than the fundamentals.

B (7:48)

So my take on Nvidia as a follow up to this Nvidia almost, it has a habit of going down after crushing earnings. I think that's a fairly recurring pattern.

C (7:59)

Yeah. Last year or so. Yeah.

B (8:01)

Yeah. So my sense is long term the bulls are still bullish. And that volatility is just from Nvidia's habit. Almost. Am I thinking about it too nearsighted?

C (8:15)

Look, Nvidia's whatever it is, 4.7 trillion mark cap company. I think it probably hard for it to act much different than the S and P going forward. Right. Meaning like can they grow their earnings 15, 20% a year for the next five years and can the multiple contract a little and then the stock doubles in five year view, maybe that might be the bull case. 15% of your five years on the stock, that would make it almost 10 trillion market cap. That's not impossible. But if that's the case, the market will probably be up close to that. Right. And so is it really going to outperform the market by a ton? I don't think so. I like to think about things, distribution of outcomes, you know, and I would assign the highest probability to it performs close to in line with the market. I mean The S&P 500 is what, 60, 65% in AI ETF at this point. So you think Nvidia is going to really act completely different from the entire market? I think that's going to be hard.

B (9:08)

We explain that. What do you mean it's a 60, 65%.

C (9:11)

I mean the biggest eight stocks, a great eight, are 37% of the market cap, 50, 55% beta adjusted. If you add in correlated industrials, power utilities, software, maybe even metals, maybe even. It's probably 2/3 that complex. So Nvidia is the biggest and most important company in the complex. So like are you. If you're saying you love the S&P 500 and you hate Nvidia, I don't know if that's super likely. So I think it's like a market perform in the true sense of the word almost, you know. Do you think for Nvidia in specific?

B (9:48)

Yeah, sure, sure.

C (9:50)

It'll grow faster than the market, but the multiple like you just saw pretty. It's been a year since the EV to sales has expanded, right? So it's going to be hard for the multiple to expand. Why? Semis get multiple expansion when their gross margins go up and the company's got peak gross margins. So you're going to pay a lower multiple two years from now that you know for Nvidia than you are today. That I think is a high probability bet.

A (10:14)

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B (10:56)

and not just guessing.

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B (11:21)

So something you've been doing with your team is you've broken the semiconductor sector, let's say, into nine different categories for a more granular categorization. I have a couple of them listed here. You got equipment and testing, manufacturing, packaging, connectivity and interconnect.

C (11:41)

Yeah.

B (11:42)

Analog interfaces.

C (11:43)

You did your homework here.

B (11:44)

I tried to, I tried to.

A (11:46)

I knew you.

B (11:46)

You've done your homework. You've got solar on there.

C (11:49)

Right.

B (11:50)

Can you walk us through this strategy as far as looking at it on a more granular level?

C (11:54)

Yeah, like we just try to do this all the time at Trivarit, which is. Look, everyone who covers semis would say there's four buckets, right? There's semicap equipment. So the guys that make the tools that, that you need to produce them, there's the memory complex, there's the industrial analog stuff, and then there's sort of the kind of processing unit group like that make. And so we thought maybe we can get a little more granular. So we took all the public companies we use, I think chatgpt for this and said, can you take all the language that we've taken out and cluster them into different buckets? And we got more granular. Nine, I think, nine baskets. Why did we do that? Because then we can track the forecasted earnings, the earnings revisions, the sales revisions, the valuation, the performance of those nine different clusters and see if eventually the market's going to start treating them differently or if the correlation returns change so I can build more of a balanced portfolio. The problem in semis historically was they were all very correlated. So you can. I can tell you this romantic story about how I want to buy mem, sell memory and buy analog, but they used to be highly correlated. So I want to see if any of these nine. But everyone knows memory and solar are different. I think people would say they're different. I think they all know industrial and analog stuff's different. But I wanted to kind of start tracking this a little bit more detail because I think semis have gotten such a big piece of the market that if you say you're negative on semis and software and you're a growth pm, well, what the heck do you want me to buy? I got to buy something. So I think more and more people are kind of figuring out, well, what part of semis makes more sense than the other. I just found out that you know, I'm not going to get multiple expansion for video. Maybe I trim a little, maybe I buy some Texas Instruments or maybe I buy some something in one of the other nine buckets. I think that was the thought process behind it. But we do that a lot because I feel like we do a lot of natural language processing the transcripts and try to cluster it. Example AI. Every company says they're doing AI benefit, you know, things that benefit them. So we kind of read in every word of every earnings called transcript related to AI, came up with a bunch of cost cutting categories and we could say, all right, does it make sense that they're doing back office automation? The company's saying they're doing it showing better margin trends, showing better revisions, outperforming as stocks. Like we try to kind of slice and dice it because every day for the biggest 3,000 US equities, we're downloading or computing tons of stuff. So I think you've got to get more granular. We do most of the work as you know, you know, quantitatively.

B (14:14)

So let's say in these nine semiconductor categories, which ones are you finding that let's say look the best right now and which ones are lagging?

C (14:24)

I mean my premise is that if I have a sense that the probability of multiple contraction is greater than expansion, it makes me a little bit less optimistic on the group. So in a 12 month view, and that's kind of how I try to think about stuff, you may have listeners who don't care and they have a three week or a two month view and the answer would be different. In a one month view I'd probably stay long all the memory stuff. In a 12 month view I think we have a chance for a really big correction. So it's timing it. But I think you want to be more negative on memory, more negative on semi caps and a 12 month view. I think you're more market weight the processors, Nvidia, Broadcom, et cetera. And I think you're more optimistic on the Aditex and microchip kind of more broad based industrial stuff because semis work when gross margins go up and when you have really high inventory and it starts coming down, investors anticipate margins going up. And I think the industrial stuff's got a better chance of that than the memory stuff. So it's not about current trends, it's about what you think the market's going to anticipate a little bit. And semis trade on changes to gross margins versus expectations six months from now. That's what they trade on.

B (15:36)

Do you think it's, let's say, a worse bet than to buy something like The VanEck Semi ETF, SMH, something like that, rather than trying to go into one of the nine categories?

C (15:51)

So it really depends. You know, our core business, Trivarit, we just sell content to institutional investors who are buying individual securities. We have a business, I think, you know, called Trivecta Research where we sell to advisors, individuals, advice, and most of them buy ETFs. And I think an ETF for someone who doesn't have the bandwidth and time to study any individual names is a really sensible thing to do. Obviously, I know I'm benevent personally. Thank you. His products and his business are great. So no issue with. I think it's a very reasonable way to do it. I'm not as big of a fan of the levered ETFs. I know a lot of retail investors want to buy like triple long Nvidia or triple long, that stuff. But I don't think that's really giving you what you think because it rebalances every day. So I think the estimate is completely reasonable. Way to play semi exposure.

B (16:38)

Okay. You bring up some of the risks to semiconductors, but I'm also thinking about the fears around AI right now.

C (16:47)

Right.

B (16:48)

Is there a way to, let's say, gain exposure to semis? But maybe this is the granular part, get exposure while hedging yourself against some of the broader AI risk?

C (16:59)

Totally. And I think there's a few ways to do it. One is say you take an AI semiconductor basket. We have our own custom on a trivarit, but you could take the SMH and we look at the correlation of every stock in the market to that basket and say, okay, what's not in technology that's very correlated? Maybe it's electrification, industrials like Eaton or even Cat is trading. Like, maybe it's some of the financials, maybe it's Power G for Nova, Vistra, Constellations, eeg. And so you have to say to yourself, okay, well if I own some semiconductors here and I also own Eaton and G Vernova and Constellation, I really have a much bigger bet. So one is being mindful of what you own that's not in semiconductors, that is correlated. And I think the second is finding things that have a low correlation to AI semis but are up. I can find stuff that has Low correlation, that's down. Those are called bad stocks, right. So you got to make sure they're up. So when you look at the list of low correlation and up, you get a lot of defense, healthcare, select, things like Philip Morris, et cetera. And so I like that group a lot because when and if we get more or increasing concern about getting close to the data center overbuild, I'm going to be diversified as opposed to being in the names that are. Texas Hedge they call it where they really the same thing. So you've seen flash of this. If you go back to early January 25th when you had that deep seek thing, the initial deep sea thing, you know, and Constellation and Eaton and Nvidia were all down 9% in one day. So it's. If you're a sector based guy and you're like, oh, I own some industrials and utilities and semis, that didn't help you at all. So I think you've got to look for diversified sources of what the market's telling you. If you look at the market recently in the microstructure, is that anything that has a lot of value in the terminal value people don't want to pay for. They want stuff that's a hard asset or real asset. That's why Cat's chart looks like it does. That's why metals act well when there's uncertainty, you're supposed to pay a lower multiple for things that a lot of the values in the future. So I think that's probably a reasonable setup.

B (19:12)

Okay. When you look at the, you know, the recent market action, it's been so negative. Really the. It's been a market that's so jittery. I feel like it's looking for reasons to sell. Is there anything that, let's say you're watching that you think, okay, this is something that's really bullish, but somehow no one's picking up on yet. Why is the market not reacting to this yet?

C (19:36)

I mean it's funny, it would almost be like the opposite of the Nvidia print. Like meaning if I got a company that missed and the stock didn't go down, I always think that's a nice all clear signal. We track really carefully anyone who misses on earnings, misses on revenue, misses on margins, subsequent price action. Same thing on beating right now, the way I would phrase what you said, I agree with how you set it up, but I would say the penalty for missing has been a lot harsher than the reward for beating. If you saw that skew change some I think that'd be more bullish. I think part of it is because relative to history, things are a little more uncertain now. And the source of uncertainty is really from two main areas. One is trying to figure out what businesses are impregnable to AI, benefit from AI on revenue or costs or are disrupted by AI. It sounds lazy, but the best way to think to figure that out is just look at what's happened. Stocks that are going down have a higher probability of being disrupted and stocks are going up have a higher probability of benefiting. So if you try to use mean reverting valuation, all you can do is buy companies that have a higher probability of losing and sell them. That's why valuation hasn't worked to pick stocks. I think the second source of volatility has come from the administration where in an attempt to, you know, make the midterms less severe in their switch and make the economy look good, you do stuff like hey, caps on credit cards or hey, the GSEs are going to buy MBS or hey, there's antitrust issues and home builders or whatever comes out. That stuff has been harder to position for proactively. So my sense is it's not stupid to like stocks at higher prices than you used to not like them at, because stocks that just got more expensive actually have a higher probability of beating estimates and the conditional probability they beat a second time given they beat the first time is higher than the unconditional probability. So it actually makes sense to buy companies that are up and that was not maybe the case in the past.

B (21:39)

Is it fair to say that old valuation models are sort of moot in this market?

C (21:45)

You mean stuff like Cape and Schiller and those kind of things? Yeah, those things work on a ten year view, but not like in a three year view. So I don't. All you're saying if you're a caper Shiller PE guy is that you think margins are going to get killed and so if you're right that margins get killed, then the valuation for the market will come in. But I feel like that's a demonstrable way to destroy wealth in a time frame less than three years or something like that.

B (22:17)

Yeah, that's fair. Okay, if I had to force you to make the bear case on semiconductors, where would you start?

C (22:25)

Well, it's going to be a data center overbuild, right? For sure. And the question is, how do you time that? I mean, it's a cyclical industry and as you know, there's been some circular lending what causes a top in every, in every cycle there's two components that are always in place. Always. One is debt and two is arrogance like hubris, you know. So if you are kind of, if hubris and debt were a stock they're up. I mean just watch Sam Altman do an interview. Google did a hundred year bond. Whenever you see the words 100 year bond you should kind of sink into what the heck that is or you know so there's some stuff squishiness that's happening that's made things a little bit trickier. I do think that you need goldilocks on hyperscaler catbacks right. So if it doesn't come up a little bit people will say well wait a minute like I thought this is like so awesome. We need more. So you need hyperscale capex to come up but if it goes up too much and we've seen flashes of that with some of the capex from hybrid scalers last quarter then people say the porge is too hot. Right. Because it'll bring forward your suspicion about what the overbuilt happens. So I think for the time being we track that, that data center overbuild a lot cost of inference a lot. We track anything on the financial conditions side because you know financial conditions tightening always causes a risk off trade. So there's things to monitor and I actually came into this year with a more cautious view than the previous three years which was I think the probability the S&P 500 multiple contracts is probably greater than it expands. So it's if earnings grow 10 and the multiple chops are on this could be a flat to up 5 or 10 year for the market and not double digit. That was perceived as wildly bullish. Wildly bearish. Sorry earlier in the year but maybe it's. I mean sentiment is always two week price momentum. Right. So if the market goes down the last two weeks and magically everyone's bearish. But I did a dinner last night with a bunch of CIOs cross asset big bigwigs and you know we talked about almost nothing that we talked about three, six months ago. Six months ago it was dollars weakening. We love bitcoin. Last night we didn't talk about currency or bitcoin so I think it's always sentiments fueled by the last two weeks price action.

B (24:49)

What did you guys talk about?

C (24:51)

Software and semis. So I think you're hitting on the right topics. I think there's also a bit more, maybe anytime in the last 10 years more interested in non US equities than US equities. Just thinking that there'll be some things that have to benefit from spend people like European defense, it's kind of money, good Rheinmetall, that kind of stuff. Maybe if we're right about the hard asset versus soft asset thing that tends to benefit some of the EM stock markets a little bit more that have more metals and that kind of stuff. So I would say sentiment is a little bit more non US over US equities than normal and in the past.

A (25:36)

Real quick, we'll get right back to the interview. Just wanted to pop in and say if you like this content, I write a newsletter every single morning called Opening Bell Daily. I cover macro, the stock market, asset prices, why things are going up, why they're going down. And if you want to get that for free, you can sign up at the link in the description.

B (25:54)

Let's get back to the interview. More and more in the last few months, people on this show even have brought up Korea as one of the biggest winners of the current trends and the current momentum in AI. The etf EYW has done extremely ewy I think the Korea ETF and that has sk, Hynix and Samsung in it. Is that something you're keeping tabs on or are you mostly focused on let's say us?

C (26:26)

I mean our core business, we focus on US Equities. But look, the Korean equity market is I don't have the numbers in front of me, but I would guess it's 40% Hynix and Samsung. So all anyone is saying they like Korea is like why just by Micron it's the Same Thing or SanDisk, it's the same thing. So I don't, you know, again, like I think you know my view at this point. Like yeah sure, you know a lot of people that own those things would just say well when it's down 30% it's all profits. I'll just lose. I'll lose what's up. But if you walked in today and say should I buy like the Cosby or whatever, it's like you're just saying should I buy Micron? I mean you're saying it's the exact trade. Samsung's cheaper than Micron, it has other businesses besides memory, but it has, it doesn't trade any differently trades on memory pricing. So like I don't know if you're sitting in the US and you're a retail investor or financial advisor watching this saying should I buy the Korean equity market? Well of course not. Of course Not, I mean, just buy. If you, if that's your trade and you want to get prey on the memory pricing and that it keeps lasting and it's not all on the price, then just buy Sanders or Micron. Why would you mess around with that? I mean, that's just giving you my opinion. I mean, sure, okay, it's just a memory trade.

B (27:33)

What are you most bullish on right now

C (27:38)

relative to the s and P500? We really like the healthcare sector and I think the whole point of all of this stuff is that people live longer and they're more productive while they're alive. If I look at the inefficiencies in a lot of healthcare businesses, I think there's just a lot of potential to predict employee and customer behavior and drive out costs. And you know, S and P is, I don't have the numbers in front of me. It'd be 8, 9% healthcare. So we're recommending 14, 15% weight. You know, be pretty overweight, that group. Obviously there's so much more tech in the S and P that you can be market weight tech and overweight health care and own twice as much tech as health care. So people have to take it, you know, in the context of an S and P, you know, waiting. But I like health care a lot. I think there's a ton of low margin businesses. I think demand will be steady. We got a lot of old people who need drugs, need services, need managed care, need tools, need diagnostics, etc.

B (28:41)

So it's a demographic play.

C (28:43)

I mean, healthcare revenue per share has grown every year, 25 years in a row for the S&P 500, independent of financial crisis, Covid, whatever. So you have steady demand. And the biggest criticism is that the government's the biggest customer and could get more efficient. But you know, we've tried that. I think the RFK discount kind of peaked last summer. And you know, look, I, I'm, I run a business and I have, I know who has pricing power over me and who doesn't. And UnitedHealth has pricing power over me. Okay? They just do. It's a cyclical business. So yeah, I want to buy Elevance, Centene, Cigna, United Health. I think they're all way higher in a couple years. I like McKesson, Cardinal Syncora there. McKesson is the company that like nobody's ever heard of that has the most revenue of any company they'd ever heard of because it's a distributor. So. So I think they do around 360 billion in revenue. 3, 6, 0 billion in revenue. It's like a billion a day. They have 1% net because they're pass through. So could they get better predicting employee customer behavior and have 1 1/2% net? Probably. That's called 50% earnings growth. They'll trade at 30 times earnings in a minute. Right. So there's stocks like that. Syncora, McKesson, Cardinal, LabCorp blew up down seven or eight the other day. That's one of the few stocks that's down that I would buy because the world anytime you're young and good looking so you probably don't go to the doctor too much but when you get older you go and then they make you do stuff and what they make you do goes to the Lab. There's only two choices, Quest and LabCorp. They are going to get more efficient. They're going to grow above nominal GDP and they will probably have the same number or less employees five years from now. They have them today. Like I just think health care is about margin expansion potential. I also think that it's got low correlation to the AI trade. So I like it from the diversification standpoint it's a top M and A sector and then you can get really bullish down the road about things like computational chemistry and more efficient diagnostics and all that kind of stuff. So I think we're a few years away from do you have a wearable? Do you do one of those?

B (30:47)

I wear a garment.

C (30:48)

Garment. Okay. So let's get crazy and say like all new homes built in five years are going to have a wearable multiplied by a thousand next to your bed and it's going to know everything about you and it's going to say, you know, I made an appointment to get this checked out. Like it's going to be all much more efficient. So I'm like wildly bullish on that. But I guess I'd shut. I'll summarize, I'm talking too long by saying the market's telling me there's a 0% chance healthcare is the best performing sector in the market over the next five years. And I think it's 30 or 40%. And so I'm interested in that difference in my judgment and what the market's telling me.

B (31:23)

I love it. Yeah. You're not the only person who sat in that chair who's pitched healthcare as their favorite thing for this year. Interesting. Even long term.

C (31:33)

Yeah. I think when I took the top down consensus strategist views and put them in Gemini and chat GPT at the beginning of the year, it was not a very popular sector, which made me feel slightly better about it. I think the most crowded sector it was probably financials, actually.

B (31:52)

Yeah.

C (31:53)

Which is interesting.

B (31:54)

A lot of people think stablecoins, crypto, AI, that's all a boon for the financial sector.

C (32:01)

Yeah. I would say I'm a little bit more worried about financials being the AI beneficiary than I used to be. I think any one of us who's worked at a big company would say there's some inefficiencies that could be improved. And so it should be a primary AI benefit beneficiary sector if they predict their employee behavior or customer behavior. But when you look back and we published something a couple weeks ago, bank efficiency ratios really haven't improved in 25 years. Why? Well, they mostly just compete on pricing and then pay their employees more when time is times are good, so it doesn't always accrue to the shareholder. So I'm more optimistic Healthcare will benefit than banks actually from AI.

B (32:38)

Wow.

C (32:38)

Also, I think you have more upfront expenses to run things in parallel because you can't afford to have breaches, you can't afford to make mistakes. So it may take longer. The market has been in a everything's innocent until proven guilty about AI benefits. And I would suspect they'll get more impatient with the banks than they will with other sectors at some point.

B (33:02)

I think that's a fair take.

C (33:04)

I'm worried about it.

B (33:06)

You're throwing me off by being a semiconductors guy, but then you're pitching healthcare.

C (33:12)

Well, I'm so old, I dropped coverage of semis in January of 2007. So it's been 19 years since I covered semi. So I've been doing strategy and quant research for most of my, you know, last 20 years. Yeah.

B (33:25)

Wow. All right.

C (33:27)

Just old man.

B (33:28)

No, no, no, it doesn't show at all.

C (33:30)

Yes, it does.

B (33:31)

So, Adam, can you talk a bit about what you're doing with trivariate and maybe what differentiates your team from, let's say, other research shops?

C (33:40)

Sure. So the reason the firm's called trivariate is it's supposed to be three variables, you know, so univariate one, bivariate two, trivarit three. So it's supposed to be macro quant and fundamentals applied to U.S. equities. So, you know, I was a number one ranked analyst covering semis and I worked at a bottom up stock picking hedge fund called Eminence Capital for a while. I have a PhD in statistics. So we did quant for a while and then I was the US Equity stressor Morgan Stanley, which is a pretty macro. So I just tried to say, okay, I've had these three kind of experiences and all of them were focused on US equities but from a different angle. So that's kind of our selling point. You know, it turns out when you work at a big firm, research is a loss leader. You get research for free. So when we started Trivarit we're like, we better do things that aren't what you get for free. Right. So we focus a lot on risk and risk management. We have many clients that send us their portfolios to do custom risk work. We do a lot of what we call available alpha, meaning where can I actually be a fundamental analyst and add value? Right. So you know, if I worked at a big firm and I had a bunch of alpha generating widgets like you working for me, where would I put you to separate from the index and where What's a risk issue? We do a lot of tech strategy, we do a lot of management decision making. We have a lot of clients that are boards and management teams, law firms, and they care about analysis that shows if they're good stewards of capital. So buybacks versus accelerate share purchases, dividends, Spincos, M and A, that kind of stuff. I'm going on the board of a public European company this year and I just think a lot more about the value that management can have over a medium to long term on a company. So we focus a lot in those areas. Of course we do some content on margins and multiples and earnings and sectors and the grade eight and that kind of stuff. But a lot of it's more consultative. Consultative, yeah. Then we also do a lot of events and the bespoke work too.

B (35:34)

Yeah, I will say I've read a bunch of your team's notes. They're excellent. There's a lot of trade ideas in them. So I think it's. No, you guys are doing really good work and where can people find this work?

C (35:47)

And yeah, so for individuals and advisors or people care just our business that they should be interested in is called Trivector Research. T R I V E C T O R Trivaritor Institutional Business. So if somebody listening wants to pay six figures for our content, that'd be great. But it's usually unusual for some guy walking down the street to be an institution like that. But more individuals. What we offer at Trivecta Research is we do monthly zooms where people can ask me Questions. We do a lot of ETF analysis. A lot of ETFs don't give you the exposures they say they do or they're wrought with some things. So a lot of times it'll say, all right, you want, you want metals exposure? Here's the three biggest ETFs, here's the one we think is the best one. And we kind of grade them almost like Dave Portnoy's pizza reviews. We give like a little bit of a. A letter grade for. Are they giving you what they say? We do a lot of, you know, kind of advice, insight about, you know, how do you stay, why you should stay fully invested, or how do you dollar cost average new business, or what's the right way to think about leverage, or, you know, why is gold looking correlated to semis or like, just kind of help people understand and give them insight. So we publish two or three things a week that are kind of quick reads for people, and then we do weekly video on kind of sentiment and stuff. So it's a $100 a month product that a lot of people buy. And then if, if they mention that they saw me on the Phil Rosen show, we'll give them a month free. So can you just put that in there? Pretty good deal so they can check it out? Yeah, so try Vector Research dot com.

B (37:16)

Yeah, that's fantastic, Adam. I really appreciate you taking the time and we'll have to do it again soon.

C (37:22)

Yeah, great. Thanks for having me. Pleasure to spend time with you.