S11E8: Bob Sheehan, Founder & Chief Investment Officer at Lighthouse Macro

This is The Weekly Bullen Bear by Wealth Fest, a podcast for financial professionals. Each week Drew Dawkins and Tim Prady will have an in-depth conversation on what's happening in the markets. Alright everyone, welcome. It is Tuesday, February 24th, a day after the famous Citrini sell-off, which was all of a 1% sell-off that we've regained most of today, but it was certainly more violent underneath the hood. We are going to have a more thoughtful conversation, I think today. We're thrilled to have Bob Sheen, who is the founder of Lighthouse Macro on the podcast. Bob and I only met about a month ago. Bob wrote a piece on inflation, where he dissected the parts of the inflation data that are sticky and the parts of the inflation data that are more transitory and not informative. I just thought it was an awesome piece. I told him that and we've been communicating ever since. He's got a Lighthouse Macro, has a sub-stack that is really outstanding. As I've gotten to know Bob, he's got a different background than a lot of us and I'll let Bob tell you that because I do think that the way Bob comes out the market, the way he comes at his research and the way he has a process that he is iterating and developing and improving upon, I think it's how you're supposed to do this business and how you're supposed to think about trading and making money. So anyway, with that, Bob, thank you for joining us. Awesome. Thank you so much, Tim. I'm thrilled to be here. As Tim just said, I'm Bob Sheen. It's a little background on me. I started my career at Bank of America. I was on what I call a dual mandate portfolio management team, meaning on one side we were managing a large cap equity strategy. You're kind of a typical, long-only institutional buy side role. And then on the other side, we had institutional wealth and honey earth clients where we were doing the multi-asset portfolio management, bringing in kind of the macro side of things. And I began to tie those together and at the same time I was getting my CFA, my CMT at the same time, same track. And so I got there's all done within my first three years. And through that process, I really just downed digging into the data was fascinating to me. I had a nickname at Bank of America. It was Sheen 2000 because they thought I was a wizard in Excel, which was funny because I just think my boss didn't even know how to open Excel and made me look that much better. But that beginning really helped to kind of lay the framework for everything that would come after. One, just understanding that you want things to have substance, you want to foundation underneath them. And the best way that I know how to do that is through the data, the data that we can see and the data that is out there. So I ended up going over to the cell side for a bit. I was at a macro research firm. And then my next spot after that was I actually went to back to school for data science. I had gotten a scholarship to one of the new new wave schools. Let's call them that are focused just on kind of the computer science skill set. And I got a full ride to this data science school right actually down in Manhattan, down in Stahoe called Brain Station. And I thought, you know what, this is a great opportunity to kind of deepen my day skill set. I had been teaching myself Python kind of on and off for a couple of years. And I really just wanted to hone that craft a little better and really be able to use it in a way that was going to be meaningful towards the work. And it was an awesome experience. One, because it gave me the skills, it really did help me learn Python and how to kind of approach data. But the other thing was it wasn't a finance only course. So there were people from healthcare, people from education and understanding how all these various sectors and all these segments of the economy. They all have, they're generating their own data and all of them have, you know, pillars that they stand on and watching the final presentations and kind of learning more through that. It always solidified what I had already felt, but really brought home and brought all the gather for me that having a process that is based in something that is falsifiable is huge. One of my favorite phrases is strong hands, weekly help, meaning you want to have conviction in your idea, but you want to be able to change your mind when the data change is against you. I think one of the downfalls of a lot of people in this industry is Cuber's. I think being unwilling to change your view to change your mind is, it's deadly. It's very costly, it costs your job, it costs clients their money. And so actually, an anecdote to bring it all the way back to my first role. We had a stretch on the long only side for the equity strategy where three years in a row, we outformed the market by six to seven percent, but they were wildly different years. It was 17, 18 and 19. And if you remember, 17 was a rip-roaring year. It was up to 31 percent. The very next, and so we were up 37 percent. And you know, that's great. But when everything's when all boats are rising, you're like, okay, we hit one or two good calls. The next year, the SMP finished the year down and believe right around 4 percent. The week ended up up up to up to 1/2. And I remember that year is probably the year I learned the most about what really matters. It's protecting the capital, protecting the downside. Knowing one to get out, manage risk and knowing when to kind of play your edge. And that was really helpful for me just to kind of experience that and watch the older portfolio managers and see how calm they were. They didn't owe ever panic and they just thought it rationally. We had a technical, technical analysis sell discipline and it was rules based. So if it triggers, it hits no emotion, you're out. And that really stuck with me. And I've now applied kind of that same framework to every portion of my analysis from the price action all the way to the macro level as you'll see in my sub-stack and as we'll talk about today. Yeah, I think that's a great intro because look, nobody's going to disagree with you that hubris hasn't ruined more Wall Street careers than anything else, right? I mean, if it was just being really, really smart, there'd be a lot more, you know, billionaire traders out there, but nothing is more humbling than the markets. And I think that the way you talk about the term I think people use now is sort of a quantum mental, right? You've got your, the fundamental work that you do, you're a CFA, you understand how to analyze companies, you understand macro, but sometimes the market can stay, you know, what is it? The market can stay irrational longer than you can stay solvent and having that quant and CMT background and staying 100% loyal to it. The wrong thing to say is the market's wrong. I think that's absolutely. I mean, you've seen things like GameStop and all these things that you're seeing through eyes and you're like, that doesn't make sense. It's irrational. And it just reinforces to me every time those things happen. The markets can be irrational and you have to deal with that. It's not the market's job to deal with you. It's your job to deal with the market. So I always think rules help with that because we don't humans ourselves. We don't always make the best decisions in those kind of scenarios. You mentioned just talking about how a little fanfare there's been now that Bitcoin's hit like 62,000, you know, and that's one of those things that seems pretty wild. It does, it has gotten quieter. I've noticed there, you know, people got shaken out and I think that was the first time for a lot of them in that market specifically that they've really dealt with kind of a draw down that wasn't just a quick V. But at least in some time. And I think some of the younger people that are, you know, just coming out of college too, anecdotally, I know family friends who have done this, but like a lot of them are looking for jobs so they're playing the crypto. And, you know, that's a scary, scary way to try to, you know, make the next meal, especially when you don't have a process or anything behind it. So, yeah, I think what's, and we don't have to spend a lot of time on Bitcoin, but what has been so disappointing is that gold is acted so well, right? And as a flight to safety, as volatility has gone up, when we had the freak out in October, gold worked really well. Bitcoin didn't. And all of a sudden, you start to say, okay, do I just have a risk asset here? Do I not have something that is going to be a flight to safety? You know, you mentioned GameStop before of every portfolio manager I worked with at HpGallion had 28 p.m.s. The biggest invest p.m. was in my opinion, by far, again, Leon Schollove, who now runs a hedge fund called Mabel Lane. And Leon and I are not friends. I don't even particularly care for the guy, but he's the most talented p.m. I've ever met in my life. And he almost got taken out by GameStop. Now, like awesome p.m.s, he ended up coming back with Avengers and come, but it almost took him out. And it did take out Gabe Plocken, who, if you worked in an institutional sales desk, those guys at Melvin were considered the best consumer guys on the street. And he basically got liquidated. Yeah, I mean, that's what's crazy to me is you even coming into the industry. You hear all these stories. And like in college, if you don't know about long-term capital management, then you come out and you're like, these geniuses have they've done this. And your p.m.s are handing you books to read and stuff like that. And you're going through there. You're like, this is crazy. And there's one thing to read it. And kind of it's like, oh, that's insane. But then if you're in the industry long enough, you witness it where you're like, that's a smart person. I know that they know their stuff. And that's not a good year for them. So if anything for me, I think that reinforces it. The rules, putting barriers around yourself is the way to go in my opinion. Yeah, because I mean, your biases become inescapable. Look, when I came into the industry, everybody in 1995, everybody was really still scarred from the 70s and the 80s. All the old guys were right. And they were value guys. Everybody was a value guy. The way I learned business was literally a quantitative bottoms up value approach. Which if you really just followed that for the last 30 years, you really, really struggled. And then the other thing was the hedge fund managers that we all studied. And the Michael Steinhearts and the George Soros, those were guys who went out into big, huge, concentrated macro bets. And in both cases, it's almost an agronistic to what portfolio management looks like now. I just feel like guys like you, we had, I'm on men on the podcast. Like you mentioned how much respect you have for Jeff to graph. I think that the guys over at Hedge I do an incredible job. All the same idea of we're going to do really good fundamental work, but we are going to be super, super quiet, disciplined in managing and managing downside risk. And I think it's great about is you can put the risk parameters around any kind of long part of your book if you are a value guy, if you are a macro guy, if you are a growth guy, and you can still put parameters around kind of any of those and not have to change your core thesis in the way you approach the market. So it's definitely cool to see how other people are using it. And I mean, I'm always learning from other people. Some of the best guys I know are doing. And I think that's the way you should be. I think surrounding yourself or reading smart people is the way to go. And I'll be the first to admit it. I didn't make up any of this. I'm not the first person to do this, but I'm taking bits and pieces and coming up with my own version of it. And it's been good. Yep. All right. So what I want to do is get into, and by the way, someday value is coming back. I'm going to live long enough and be in this business for long enough. I can go full circle and be a value guy and a successful value guy again. It's easier than changing my mind and becoming a momentum guy. But anyway, you wrote a piece on on on labor. And you said something to me the other day, which I say every time non-farm payrolls come out. We always write a little blurb on non-farm payrolls because even though, as you said to me, it's like the worst piece of data, everybody freaks out. Like CNBC's got a countdown clock. So what choice do you have but to pay attention to non-farm payrolls? So tell us a little bit about how you look at data and data quality and what that means in terms of your outlook for labor. And I know you've got some slides that you can share. For those who are listening to this, we will walk through what the charts are telling us. So, or let me know if that is working all right, but the slides? Yeah, so the way I approach data and the way I believe is it flows over stocks. So it's going to be kind of the movement, the velocity of what's going on in the meat-the-labor market that matters a lot more than the level. So when I mean flows over stocks, I'll break that down a little bit more. So the stocks is the unemployment rate. It's how many people are out there working. It's just the level of people and it's a lagging indicator. It's pretty well documented through economic research. Various publications have all come up with their own ways to look at it and pretty much every way you slice it, it lags the economy. But what doesn't lag is the flows. It's the movement of people between jobs when you see things like less people quitting or when you see things like people are job switching a lot. That's usually when something is turning and when something is happening. When you see those metrics moving in a meaningful way, that's when it's time to perk up. And that's one of the funny things about the media is you would never know that because on the front of the journal or when you open up Bloomberg, it's the one number, unemployment rate. And a lot of even policy gets based on that. When in reality, that's too late, that's after the fact. And so I've always believed that the best way to look at data is the opposite of the one number. You want to know what feeds into that number because averages can average out and look okay, but there could be some crazy stuff going on underneath. You have one thing shooting up while something else is is tanking and you could still get at the same average if everything was acting even keel. And so I've always felt that the best way to really get a holistic view on things is one to go wide and to go deep. It takes longer. It takes longer. It's a more in depth process, but I find it's worth it. And I find it gives you insights that not everybody's going to catch. And also it just gives yourself a little more confidence in the data you're seeing. When you can put up multiple metrics, there is. And I feel that you know that this is backed up by reality because there's multiple different data points rather than when you try to put one data point on reality, it kind of hurts things. So, yeah, I mean, I've right at at any given point, Bob, you know that you can turn on CMBC and find somebody who wants to make a really bearish call on labor, right? And he could pick five series, you know, NFIB, you know, employment intentions or the household survey for a one month. So it or you could do the opposite. There's so much data out there. So I think somebody like you who's looking at it and saying, no, this is what we're going to dismiss. This is noise and here is where there is real signal. Here's that where there is quality data in it. And maybe there's two pieces or preferably three pieces of quality data. And now all of a sudden you have something that probably may not show up in the household series from which the unemployment rate is derived in really a erratic series. Yeah, absolutely. And there is in this world where generating so much data and there's you've got to try to cut through it somewhere. And I was data science, excuse me, that skill set to do that mathematically. And it makes things so much clearer for you when you know, like I don't really have to pay attention to that number. Obviously, you have to know it just to speak to it. But that's not the one that I'm going to look at in my end analysis. You know, I want to just dig a little deeper on some of the ones that I do look at. Quit's rate. This is really a signal worker confidence, right? But if people are not quitting, there's a reason for that. It's because they can see what's happening, whether it's inside their company or in the broader economy. And they're voting with their feet. They're not going to mark out the door right now because they don't see better prospects. Or they know that things might not be so so rosy on the other side. But when the opposite is happening, when you're seeing lots of people switch jobs, when you're seeing the premium for job hopping higher than the premium for job staying, which is the reverse right now. That's when things are really good for the worker. That's when labor is kind of in charge. But as of right now, it's the opposite where we're seeing jobs staying is actually earning more than job hopping. You know, job hopping has really been hot, especially, I would say, since COVID, but hotens for a decade. And, you know, shorter, there's been shorter stays by workers kind of throughout the past four decades. It's a little bit shorter, but it's really, really got short around COVID. And so work from home thing leads into that. But when you see that number really separate, when you see the premium for going to a new job, excuse me, be significantly higher. That is when, you know, things are really about to boom. That's when you got that run up after COVID, when we got the money back and spending, not only were workers kind of being able to jump around freely and kind of pick up that momentum, but they also were flush with the cash. And that's when you get that kind of overheating. And those metrics, these flow metrics really were early on that. And they've been early consistently. This is what I found as I went back through the data. They've consistently led before we had these big movements, whether it was to the upside or they've all led on the downside, recessionary, like quits great, for example, 2%. We're actually right at that level right now. That is kind of the threshold. If we see it meaningfully dip below that, that's when I get really worried. That's when historically things have not been great for the labor market moving forward in the broader economy. And so watching these, the flow really helps to kind of bring some clarity. And when you think about the fact that the economy can't go without labor, as much as the AI doomer should have us believe at the opposite is true. Right now, there is no economy without the people who build and the people who produce and are the ones showing up at those jobs. And so we workers ourselves, we might not even realize it at times, have kind of the best sense. It goes up in the data and it really helps to clarify things when the headlines are only saying it's something else. All right, so right now you've got quits, super-tepid. So everybody has talked about it. You've got a stagnant labor market, right? Firings are low, but hirings are super low. Job openings have fallen below the number of people looking for jobs. So when you look at the trends, when you look at all the data, are you still seeing the labor market that is more likely to weaken from here? Or do you expect some firming from here? I would say not weakened, but kind of stay stagnant for the time being. I think I wouldn't be surprised if we kind of get a little jostling around at the area we're at, but I don't see kind of the makings of a prolonged expansion yet. We really haven't washed out kind of the negatives that we need to, and we have long-term unemployed is one of the metrics that also feeds into a lot of the indicators I'm looking at. Those are people who have been out for six plus months, and this is where I do get a little bit worried that something could deteriorate further is when they stay out longer and then it becomes harder for them to come back into the workforce and then they lose out on the skills and it becomes kind of this vicious cycle. We talked about that a little bit, the AI kind of backing up that as well. That is the one part of the market where I do worry it could see at this floor level that we're at, kind of this low level, and maybe push it a little bit further down, but I don't see necessarily deteriorating to a point where the actual unemployment rate jumps up to 8, 9, 10, something crazy. It's a wild labor market. You said it before, there's the old expression, averages yield, average analysis, and especially in the labor market where you have some industries that are just really, really labor constrained, right? Cannot find people. Aftermarket construction, engineering, a lot of those kind of jobs. Whereas if you're a white collar, if you're a kid coming out of college, you're looking for jobs, it is going to be and continue to be a tough labor market. I think on the AI side, is AI causing that or is it managers who have invested in AI and have to show, love made these investments? I can't go out and be increasing headcount with revenue flat. I think that is one of those things, which is we just, there's a psychological aspect to it, and I don't know that we can differentiate the signal from the noise on that side of the hiring weakness. I totally agree with that. More on my point about the AI was that there is the actual AI and the productivity gains or it's the what we saw yesterday in the markets and the boogie man of the AI, the thought and there's so much investment that's being put in. There is, you hear anecdotes of managers who put stuff in and it just isn't working and it's been months and months and months of this. There's a psychological aspect for short, but I am trying to find it in the data. It hasn't really shown up yet. It's early kind of innings. I still believe so it'll be interesting to follow that and see was there a meaningful shift. I think there's, I have to believe, I hope this is true, that there has to be a human aspect to the labor force. There has to be a guidance. There's still AI models that mess up all the time and I don't think we're ready to step back in that regard. I guess one of the major concerns would be that if you're not hiring post-crabbs, then how are you in a white collar industry developing a pipeline for middle-management? What does 10 years from now look like? Sure. That's kind of feeds into the long-term unemployed where if you are out of the workforce for a while, there are some who are creating themselves. They're doing the start-up there using Maltbot and Cloud Code and all this stuff to build things. There are others who aren't going to get their requisite skills because they've been out for a long time and that does have issues further down the line. As they mature into the workforce, does that leave it get for a decade or so where there's just people who don't have the skills that are required to do their role? We're not there yet but that is one area where longer-term I do get a little bit scared. The longer this goes, the worse it gets. Yeah. We'll leave it there on labor and I think we're in the same place. It is a very, very hard call. I feel the same way about the housing market as they do about labor. It just feels like it is going to go sideways here, soft-ish without inflecting stronger and without, and it's obviously unprecedented from the standpoint that we have no workforce growth. You have a situation where you've had cyclical firing. You have manufacturing and construction employment really shrinking but you don't actually have any excess labor because we have exported so much of the labor that we had. But let's go to inflation and this is where we met. This is the piece that you wrote that I really was blown away by and I reached out to you and said so. Why don't you throw that slide up and talk about how you dissect inflation and again signal from noise? Yeah. So, it's least when you look at it, you have to break it down into kind of, it's moving parts. Again, you're going to hear there's a lot from me to kind of throughout this call. You can't look at one number. You never just want to look at one metric and call that. That may be what the headlines say, maybe what the narrative is, but the reality is most likely different and pretty immediately so at times. So what you see is that certain things are leading indicators and then they move fast and they move kind of rapidly and wildly up and down in inflation and those are your things like your energy, your food products, the things that are a little bit more demand-driven and kind of struck the old and have opened around where you're getting people need food, people need it and are the various trade routes all affected. So you're getting kind of a shorter term bias in the movement and kind of in the corrections. Then you have things like shelter, your rent inflation, your homes inflation and that lags pretty significantly. It's by 12 to 18 months. So that's a year and a half, a year and a half. And we saw kind of post-COVID, this inflation dynamic where everything was transitory, but a lot of the eyeballs were focused on kind of the fast moving parts and so when things were going one way, it was a panic in one direction and then when things turned back the other way, it was too slow to correct. And I think what people often don't look at is the thing that's lagging behind, but that is often the area that's going to have the lasting effect that's going to maybe change the next cycle and shelter is really that because it is one third of CPI, it lags even rents themselves. Rents are much faster because people are moving obviously between apartments a little bit more often and there's different rules, laws and different cities and things are kind of constantly changing on the rental market, but shelter like long-term shelter homes, that's an investment for family and for the backbone kind of of where people are going to live, they're domiciles and so it takes longer for the prices to change and then you have it taking longer and it's a bigger portion of the pie. So when your analysis is focused too much on the front end of that kind of spectrum of the inflation dynamic, you're missing a big portion that's going to kind of bring everything in like a wave that is really what's going to settle the field at the end of it. So with that, because everybody who's focused and your right inflation is one CPI is at 2.4 PC is at 3, it probably depends on your political party which one you want to embrace is the right number, but that shelter component which is you said is somewhere between 30 and 40% of CPI and lags, do you agree with kind of the consensus opinion that looks CPI is not going to get away from us here over at least the next three, four months because even if rencer stabilizing in the south and in kind of the southeast and in California, it's going to take a while for that inflation to catch up. And then the other question is let's say that's the case, does the market look through that? In other words, you get a 2, 4 CPI print, but some of those, some other parts of CPI really started picking up used car prices, commodity prices, consumables. And therefore, you know, the market really starts to get worried about inflation even though you're still at a 2, 4, 2, 5 seemingly benign absolute number. Yeah, so I actually wrote a piece back in October, which is called the last mile of disinflation. And it was kind of all about this dynamic. The move from 3% to 2% is going to be more painful or have more going on than the move from the highs of inflation down to 3% were. So this is where kind of all that stickiness that we were talking about, these longer term prices, this is where they can either make or break the inflation call. And you are focusing on the short end, you want to know what car prices are doing, what commodity prices are doing, and you obviously have to pay attention to that. And that does, it's a portion of the component. But I think the lagging component, I still believe, has kind of the upper hand, so to speak. Yes, it's higher. But also it's the one that is going to kind of wag the tail of the whole beast. And the one thing I will say is we are seeing some stuff coming in from Zillow that it is coming down, but it's been drastically sticky. It's staying up there a lot longer than I think people thought it would. And I still believe we are going to be kind of puzzling around kind of in the upper twos, between 2 and 3 range, but really not settle down at that old 2% level that is the psychological level everybody is kind of targeting. I think that is probably a ways away still. And when you see things kind of come under cooling. And so I think we might have something where this is a whole new dynamic even longer term, where you're never going to kind of see that 2% statistical norm that we had for so long. Or at least not for a decade. We won't have really been at that normal level that had historically been the inflation spot that everybody targeted, but the Fed themselves targeted. So yeah, I kind of mean the camp that it does, those could still kind of hover and we don't see a full a patient of it. But it's fun to watch. It's interesting to see kind of in real time what's moving and then what ends up mattering kind of over the long term as I look back just from a personal level when I'm like, oh, I remember egg prices were huge. And now you don't hear so much about egg prices. There's kind of a flavor to sure of what inflation, what's hurting is it as a pump prices, is it this, is it housing prices, but really it's the aggregate, but you have to kind of separate those things along the way. Yeah. Tim writes a lot about secular drivers inflation among those is kind of declobalization. China's no longer disinflationary impulse. And you think with broad sectoral change like this, the Fed might articulate a different mandate at some point, right? That's 2% might seem pretty stale. That's, I've thought that kind of for some time, when I was writing that piece, I thought, you know, there's going to be a time where they kind of have to come out and be a little more explicit that they are, that 2% is dead. You've had some kind of hints at it, but I don't think they'll go up to 3% necessarily, but I do think that paradigm is a little bit shifted and the world doesn't really have that deflationary pressure that had been there as you pointed out. So I think the paradigm has shifted and I think a higher level should be expected from both, you know, as a consumer and then as an analyst kind of approaching the markets. That's the way I've been viewing it and until kind of something proves me otherwise. That's how I'll continue to frame it. Yeah. You know, I think what gets lost in it and this is more of a sociological observation and an economic one is that, you know, look, when you let inflation run at 3 or 3 and a half percent year after year after year, unfortunately it does create real societal bifurcation, right? If, you know, your truck is a big part of your expenses and getting it fixed and putting gas in it, well, gas has been the exception, but all every other cost around owning a truck is going up, right? You know, if you make a million bucks a year, the cost of your cars and your consumption is really somewhat secondary and you're making money because you own assets. So my only, that's my big thing about why the Fed should respect the importance of the 2% mandate, but at the same time, how hard that is politically. I firmly believe it would be beneficial to get that 2% mandate. It's just the lack of communication around it, the fact that they can't kind of get there right now. It's tough because it is very political at the moment and it's hard for them to communicate kind of where they're really ballparking it because as we'll touch on pawn and consumer and as you just hit on what's really crazy is not only is inflation affecting kind of the economy as a whole, but it affects those who are the lower class, the ones who are already struggling because they are a bigger portion of their pie goes to the ones that I was talking about, those bigger pieces, your shelter. You know, when you don't have as much money, it's a bigger percentage. You got to find a place to live and you got to find things to eat. And so when you're getting higher inflation for longer, it chips away, chips away, chips away, especially when the rest of the cohort is investing at a rate that's higher than inflation. So their pie is going bigger, bigger, bigger, bigger, and we've really seen that to a dramatic degree. And it's not looking better right now. It's been getting worse ever since, you know, I think that's pretty well known that right now that they could decay economy, but I'm not sure right now how we fix it. Yeah. Well, one way we will get to 2% inflation is of growth really stalls. And again, back to your data science and your CFA and looking at, nobody can really agree. I mean, you have really smart guys out there who will argue that GDP data is way off and that real growth in this economy is somewhere between zero and 1%. And that it is not really, and all of the AI spend is not really durable at CAPEX. It is not the same as Ford and GM building plants as me and you buying dishwashers and new houses and cars that this is much more of an ephemeral spending that isn't really going to dorelbly push the economy. So kind of where do you come out on growth and how do you think we really are growing? And again, the quality of the data, when you start, when you start every quarter, it feels like with the Atlanta Fed coming out and saying, we're going to have 7% GDP growth. It's like, come on guys, come on. And I know it's a now cast. It's not a forecast, but still it just people's getting trying to get their hands around GDP. I felt like it's never been so difficult. No, it is pretty funny because not only do you get the now cast that comes out usually pretty high and lofty and let's call it optimistic. When you get the revisions on the back end and it's like you go almost months at a time before you get the real number and it's like do we have to go through all the all the all the the happen about what what it really was and we should standardize something and really look at things holistically. And yeah, this one for me is is simple. You know, GDP doesn't really tap her what we want to know. It's like you're driving a car, GDP is the speed and the second derivative is what you want to know, whether you can be going faster or slower, whether you're speeding up, slowing down. GDP is kind of just here what you are maintaining at the time and it has the revisions. It has kind of the now cast are an attempt to kind of attack of this problem, but so far they haven't really gotten to the point where they can be trusted, especially with the revisions that we've seen, especially to your point kind of the durability of some of the growth that we've seen. I think that's really been apparent kind of the last let's call it your 18 months. But so like if you look at Q4 GDP, you had it at like 2.3%, which looks fine, but then net exports and invitaries, they're doing a lot of the work, right? You know, we we have certain parts of it that are doing most of the kind of the legwork. And you strip those out and it's softer. And so you if you over index to one thing that aren't necessarily the long term drivers of growth, you get yourself believing that you're having growth at this clip year and a year out that really aren't and kind of starts to wear away. So I lean definitely on the side of I think historically we've been a little bit high in the estimates and kind of in the forward thinking on that because when you kind of dig into it underneath, it isn't as rosy. And especially kind of to your point, I do agree with kind of that broader thinking that there is two there's different growths. There's the sustainable true power forward kind of growth. And then there's the one that's more femoral to your point. So within within the GDP data, what do you concentrate on? What do you like to look at? Do you look at kind of final demand or what are some of the other growth numbers that you think give you a better sense of as you say the absolute is secondary. It's all about the ready change. Yeah. So I look at orders and the orders within the ISM that's kind of managers putting their money where their mouth is better is a good way to put it. It's them, you know, forecasting the future themselves, seeing what they're what they're inclined for seeing, seeing what they're seeing internally. And so when you're seeing new orders and there's it's also like bathanatically it's the fastest kind of indicator even within the ISM index, which is already a leading indicator. Orders leads that. So I find it to be one of the one of the best ones to follow. One of the best ones to stay on top of it's a little bit noisy. You have to kind of take that into play. Usually the faster moving series are, but it does kind of give you a better picture of what is actually happening at the kind of the company level at the industry level. And I find that helps me to kind of then ground the rest of the analysis is starting up front and seeing kind of where the forward view is from from the workers themselves and not necessarily from those looking down from the policy seats. And then another one would be like, GDI and GDP separating those two. So when GDI lags, it's usually because GDP is overstating growth. I'm sorry, just to interrupt it. Gross domestic income versus gross domestic product. GDI tends to have lower revisions, but it gets printed after GDP gets printed. So nobody tends to pay attention to GDI because you've already gotten the GDP, but just to clarify that. Yes, yeah, good call. It is, it's the little brother almost so speed. It gets no attention. That he's a better player and nobody was better. Yes, exactly. And we've all seen it and Jack used one. He was dynamic. He said, I, I, I, a couple of brothers that I played with popping from my head and it's very funnier. It is true. Nobody kind of pays attention to GDI and I'm like, that is the one, like if you do it in the modeling, that's the one that kind of is going to be the longer term view of what's growth and truly sustained and where it's really headed, especially, especially given the revisions. And as you just pointed out, GDP gets revised a lot. The FDI, not nearly as much. And so it's a lot more kind of stabilizing. So I find looking at the fast indicators, the ISN new orders, kind of the buildings, inventory to sales ratio is another one that I really like to look at. You know, our inventory is getting overheated. Our managers a little bit too excited. Or is it, you know, is it turning? Is it a good, good kind of excitement? And you have to, you have to ballpark it relative to kind of history, but to itself as well and understand where, when you look at all these, it's human behavior underneath it. So it kind of helps you to understand, you know, who are really the first movers of the economy? Well, it's the people doing the ordering. It's the managers who decided they need more stock, more inventory. And then if sales don't pull through, that's when you start to see the corrections. So, so tracking these relative to each other really helps to kind of frame it for the analysis. And then mathematically, within the models that I run, it works better that way. Just being able to kind of pair two things together because nothing is in standalone in our economy in the world today. So always kind of matching things up that go together and make sense, really helps to anchor and give you some, some areas to look for. Kind of, hey, this, this is historically where it is an issue. And then this is where things usually actually turn around. It's usually when people are scared at the bottom. That's when things turn. And so when you start to notice a pattern of that over time, it becomes a lot easier to see through kind of the day-to-day noise and the flashy ones on the headlines. Yeah. That GDP, GDI discussion is interesting one, too. Most people wouldn't agree. But just from the standpoint that one of the reasons why consumer demand, and this is our transition to talking about consumer demand, is that, look, this has been, as Bob Elliott has talked about, this expansion since 2022, kind of an income-driven expansion. Well, real incomes are declining, you know, rate of change. And yet GDP stays high. And is that because of the disavowing that is happening? And that maybe is getting reflected when you see GDI. And if you, and that might be a signal that maybe consumer spending could be running at a gas a little bit, which never seems to be the truth, but let's have the conversation. So I have my first and foremost thought on kind of this spending-driven economy that we've had is, I think people need to first of all understand the magnitude of what we had in the COVID era. The move that we had in the COVID era, the extra money that we had in our pocket, our disposable income per person, was five times higher than it was back in the Great Depression when they broke out the new deal. And that had historically been, you know, a massive influx of capital. So what we had in COVID was, post-COVID was an anomaly like we couldn't frame. In any way, but prior to this, and it was pretty much broad base, right? There wasn't only you get some, only you are getting kind of a check and you're not. Everybody got the check and that means everybody kind of was flush at the same time. But the reality is not everybody had the same spending background, not everybody had the same savings that they could fall back upon. Not everybody had the same starting point. And so those who already kind of were doing okay, they kept doing well and even improved. We saw that the spending kind of stayed high, stayed high. And then if you look at the other end, it fell off where the other 80% was actually fully depleted by 2024. The Atlanta Fed came out and officially declared 2024. But if you even look at just some of the earlier cohort, it was early 2023 for the bottom 50%. So we've had multiple years now where a huge portion of the economy just has not been able to spend to the degree that the upper 20% have been able to. And you're seeing it now in the actual industries and kind of the divergence of what has performed well from a stock perspective. But we've got a slide where we show the dollar stores versus the cruise lines. And I think over the last few years, it tells the story very, very well in one slide. >> Yeah, I have a similar one that is, it's luxury brands. It's like your jewelry brands and all those kind of it, I made a basket. But it's the same exact story where, I mean, eventually your consumers are going to feed into your bottom line and it's going to pay for your stock. And this is where I struggle from the standpoint of improving the overall economy. I think you obviously want to bring back those groups so that they're not going like this anymore. They're coming back together. But it's hard to be bearish on stocks when the people who are buying stocks are spending still. And when they are, they're piece of the pie is growing more. And I think that's where some people kind of get it wrong and maybe aren't being objective about the data. And this is where even I sometimes would be like, but there's a huge portion that's not spending. But then if you think about who's really owning the stocks, there's a lot of metrics out there about that. And the spending is driving the same people who are kind of doing the spending or also the same people who have their money into securities. And so it's just a double edge sort that kind of keeps going around and the consumer right now, I think, is one of the most fascinating parts of the market because it's frustrating to see this divergence. And there's a lot of different things. We've even touched upon a couple today. There's inflation differences between the highest and the lowest. There is income gains have been worse off. The higher people who are already getting paid higher are now getting paid more because they're getting raises at a higher rate and at a greater distance, a greater increase. Whereas the people who are struggling as it was are not getting raises or are actually staying flat and there are losing raises on a real basis compared to inflation. So every kind of segment of the economy, you're seeing it within housing. You're actually seeing lower income housing is getting harder for them and hiring, hiring come homes. They're not selling. They're holding onto their houses. And so you're seeing this gap within who has the real estate, who has the assets and it's kind of making this spending gap even worse. And so there's kind of multiple levers that have to kind of be aligned again to get this to come back together. And so that's why consumer I always think is fast. It's 68% of GDP. It is kind of the last domino to go because of where we started this conversation that aggregate discussion, right? So everybody's saying, well, spending is great. That's true. If you look at one number, it is not true once you dig into it. And as we just touched upon, you're you've really break it down by cohort. And that's where I think again, I keep coming back to this. The headline level usually is lying in some capacity to you. And it's always very important in my process to dig down below it and really see, you know, the various segments and consumer probably as much as any of the others and is showing that right now. Why do you need to kind of look lower? Yeah. It is fascinating. You don't have the wealth effect, right, for the bottom half of the economy because you don't own stocks and you don't own your house. And if you own a house, it may be in an area where it hasn't had the same kind of appreciation as you've had in New York area, New England and all that. Why don't we leave it at that because we're bumping up against an hour. But this has been an awesome conversation. We were going to get into trade and tariffs. We'll have to do that the next time we have a conversation. And just again, Bob Sheen, Lighthouse macro, really, really thoughtful educational pieces on understanding data because I mean, I could not agree more that we live in a time where and look, I don't think it's malfeasance, but the economy is always changing and it's hard for the BLS and these other entities to make changes. They don't make them quickly. And to have a resource like Bob who can help you understand how to filter through that data. So I really couldn't recommend his sub stack more. That's right, yeah. Well, thank you so much to him. I really appreciate it. I was just going to say on that last point, I'm in the middle of a series right now where I'm going specifically through kind of each of these and how I measure it and what things I look at. If you're out there and you are curious, we touched upon some today, but it goes a little bit more in depth and I'm always available as well. I love being able to kind of explain this to people and bring this kind of in depth analysis to everybody. So thank you so much to him. This was awesome. The time. Very good. All right. Thanks, everyone. That'll do it. Thanks. Thank you. Thank you.