The Pomp Podcast - #1276 Oliver Rust | Here Is Proof That Inflation Data Is Wrong...

Starting point is 00:00:00 What's up, everyone? This is Anthony Pompliano. Many of you know me as Pomp. You're listening to the Pomp Podcast, which is my effort to find the most interesting people in the world and sit with them for hours while I ask questions in an effort to learn. So it would mean the world to me if you would subscribe to the show on your favorite audio platform, watch episodes on YouTube, and tell your friends and family about the podcast. My goal is to help millions learn from the world's most interesting people. So let's get into today's episode. Oliver Rust is the head of product at Truflation. In this conversation, we talk about why CPI, the Bureau of Labor Statistics methodology for calculating inflation is incorrect or inaccurate. What exactly Truflation is doing

Starting point is 00:00:42 with a new data collection and methodology, how the Fed would respond if they had a different data set, why Truflation believes that inflation will be stickier than everyone else believes in 2024? How good data could lead to better decision making? And also, then we talk about the product, who's using it? How exactly are they doing it? And what is success look like for somebody like Truflation, who wants to build a much better inflation measurement? I really enjoyed this conversation with Oliver, and I think that you all will learn a ton from it. So I'm excited for you all to listen to my episode with Oliver Rust. Anthony Pompliano runs Pomp Investments. All views of him and the guests on his podcast are solely their opinions and do not reflect the opinions

Starting point is 00:01:22 of Pomp Investments. You should not treat any opinion expressed by Pomp or his guests as a specific inducement to make a particular investment or follow a particular strategy, but only as an expression of his personal opinion. This podcast is for informational purposes only. This episode is brought to you by Auradon. They're a brand new startup led by a number of Silicon Valley legends who just raised $81 million to build the future of internet infrastructure. You're probably wondering what that means, so let me explain. There are numerous new disruptive technologies that are being adopted simultaneously, from blockchain to artificial intelligence to zero-knowledge technologies. In order to ensure that these

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Starting point is 00:03:57 no one can steal your time. All right, guys, bang, bang. I've got Oliver here with me. I thought a great place to start is Truflation wants to build a better measurement of inflation. That is probably the the high level uh kind of mission but first we gotta talk about the old method uh it is pretty well understood across wall street across macro economy uh across market participants the inflation metric is the best we got cpi uh a lot of questions a lot of controversies a lot of debate how do you all think about what is good about cpi and and the data collection and methodology and then where are the areas where maybe they're lacking or could be improved yeah so first of first of all thanks for having me on um I let me go through the BLS uh which is the official Bureau

Starting point is 00:04:42 of Labor Statistics which is the government measurement tool of inflation um is measured by doing roughly I think it's 80 000 interviews on a monthly basis where they go and either do store checks to check prices or they have a survey that goes out but eventually they ask households what are the price points of these particular items and I think the great thing is it's been on for so long that it gives you a very nice longitudinal trend. The downside for that history of having all that time series analysis that you can do with that dataset is that, of course, that you're bound by the constraints of innovation of this type of a dataset. And so the way that Truflation started approaching it was, like, we've got to find a way how to

Starting point is 00:05:31 update and modernize this this capability um and of course if you think back to the bls when it first started it was pre-first world war it's more than 100 years old and if you think about it what's the real evolution that's been there not that dramatic and since then you know we've also you know not only had the consumer boom of the 70s and 80s we've had the whole internet bubble of online shopping, e-commerce, and all that's changed how to measure inflation as what it was done historically. And I think that has allowed us to modernize it in our own way, what we believe is the right way to go forward to measuring inflation as comprehensive as one possibly can. Now, let's talk about how you guys actually are doing it differently. There's like

Starting point is 00:06:18 data collection, and then there's the methodology or the calculation. Maybe start first with data collection. What are you using different data points? Or you have some other methodology? Do have just way more people going into the stores? How does it work? Yeah, we don't actually send people to the stores. We collect data from about 40 different data sources. And all those data sources aggregate up to about 18 million price points of goods and services on a daily, weekly, monthly basis. So we aggregate all that data set into 12 product categories ranging from things like food and beverages all the way through to housing, transportation recreation and culture education health and so forth and we measure each of those

Starting point is 00:07:00 indexes on a daily basis and i think that the the key fundamental difference for us has always been not only the volume of data that we're dealing with but i think most important more importantly is the frequency which allows for a much more analytical capability by having many more trend points along the way yes by having daily you get a lot more uh noise and variability but it gives you considerably greater trendability and forecastability applications rather than having one dot per month. Now, when you start looking at the calculation and methodology, if you're getting, let's say, more robust data, better data, you could still screw up the methodology. You could be just as wrong as anyone else or not. How do you think about the calculation

Starting point is 00:07:45 being maybe more accurate or more advanced? Yeah, I think the calculation is more comprehensive as a result of having the volume of data that we have, the robustness, as you mentioned. And I think that's for a number of reasons, is that we don't need to put in separate calculations in there for people downgrading or upgrading or new materials coming into clothing. Therefore, the price point changes. We don't need to reflect those. And some, the BLS and others, use things like the Fisher Index to look at cost of living adjustments you also have the passion index which looks at this down trading up trading and all these different types of of calculations are sitting on top of the index means that you're

Starting point is 00:08:29 adding in our view you're adding a a potential error on top of a data set on top of a calculation that's sitting on top of another calculation on top of another calculation but at the root cause of everything is this 80,000 sample interview that they do to collect price points of goods and services. And I think that's the fundamental thing is the volume of data allows us to remove these additional calculations that other organizations have because we're measuring not only prices, but we're also seeing volumetric data set coming in, which gives us this consumer understanding whether downgrade and upgrading without having to create an additional calculation for that now as we look at a better calculation with more robust data one of the

Starting point is 00:09:15 questions becomes would the federal reserve or other people in the economy actually make better decisions like if we had a different but better measurement how much would it change decision making what what are the things that would be different if this became the standard uh kind of measurement that everyone looked at yeah look i mean at the end of the day we're we're trying to Truflation is trying to measure inflation in the most comprehensive manner possible. Our goal is to achieve that. I think we're a long way off from there. There's a lot more that we can do, but I think given the volume of datasets that we're dealing with, the frequency of datasets that we've got, I think it does alternatively change market outlook. If we look where our predictability

Starting point is 00:10:01 as a result of our data has been of the bls for example where we try and match our data to the bls and predict what their numbers are you know we've got a really comprehensive uh you know forecasting capabilities you know we're on an average month where for the last a year and a half i think we've been doing this we've only got a variability of 0.14 percent right and that's better than where bloomberg is it's better than the average of 40 different economists that we track so you know that gives us better forecast ability i think that's one aspect of it um do we see our data being a replacement of the bls by organizations look that's up to each of our clients and organizations to predict i think what we we tend to position ourselves as an alternative

Starting point is 00:10:46 data set at least in the interim so that they can start using our data seeing the value of it and then in due course people might choose to replace the data sets altogether but i think in the initial term we see it very much as an alternative data set which gives you another triangulation of what the likely trends are in the marketplace talk to me about who are the types of people using this are these macro fund you know kind of uh hedge fund traders are these uh economists who's actually consuming the data and what are they doing with it yeah so you got uh it ranges quite quite broadly and uh much broader than we initially thought where we launched the capability um so at one end you got macro uh people that are very interested

Starting point is 00:11:28 in just looking at what our forecast is for the next three months six months what are some of the structural foundations that we're looking in within the inflationary numbers that could point to a different trend in the for in the long term um then you get the quant guys um who are looking at to adjust their their trading strategies and how they adjust uh their investment investment decisions and then you've got people who are producing even in the d5 world who are producing products uh off our data uh for you know real world assets for example uh people creating inflationary protected stable coins or flat coins you're getting people looking at trying to use our data to um you know tokenize oil data then put added inflationary protection oil data on top

Starting point is 00:12:12 of that so all these variabilities of data sets that we actually partially knew but partially didn't sort of expect the volume of growth that to come on has been phenomenal so those are broadly aspecting uh all the various types of users in our data sets now one of the things that's interesting is if you spend all day trying to figure out how to build a great product that can collect data can calculate and use the methodology to have this alternative data set you eventually have to have a personal opinion in terms of what's going to happen with uh inflation right like you can't just throw the data along like i have no clue um and so one of the things thing that's interesting to me is I get, maybe it's daily or weekly email from you guys, and

Starting point is 00:12:50 it's different kind of thought processes of, hey, this is something to pay attention to. This is something we're seeing in the data. This is something that we think is going to happen. One of those emails recently talked about sticky inflation in 2024. That is somewhat against the narrative. There's many people who think the Fed is winning the fight and inflation is going to wave the white flag. It's over. The Fed's going to win and let's move on with our life. Are they wrong? Why do you guys think that inflation is going to continue to be sticky? Yeah, so we have we certainly believe inflation is going to be a lot more stickier than people expect. I think the short term outlook for the remaining part of this year coming into the Q1 next year, you know, we sort of see a bit of a rise again, the back in maybe December and January, in inflation numbers, not a massive jump where we are, but it's sort of an upward trajectory. And then I'll slowly come down again. I think there are, you know, I think there are three longer term terms should longer term outlooks that I think we need to understand before we can really deal with

Starting point is 00:13:52 inflation and those are the structural elements and one of them is you know the government's investing a lot of money to onshore capability look at the semiconductor elements investments the government's doing you're looking at the green energy investments the government doing all that is bringing capabilities back onshore and using fantastically using U.S labor and but that's all increase costs from where they are produced today right and so that cost structure is going to be passed on to the consumer at some point or or at some point that's one aspect of it the second aspect of it is this removal of the middle class right you look at the variability of the last 10 15 20 30 years the metal classes the middle class has been eroding and the bulk of that middle class

Starting point is 00:14:39 has actually been um been either well the pocket has been dropping down into a sort of a lower income base but there are individuals that are going up in the higher income and the higher income are just spending and that's fueling again more growth and more uh more spending power therefore more pricing power that's coming into the market i think the third thing why we think that inflation is going to be a lot more sticky is going to be less and less innovation in the marketplace because the cost of capital is high and that cost of capital then is then you know where you're going to get productivity gains how much is ai going to impact that if the capital injection money flowing into organizations is going to is going to benefit through there and

Starting point is 00:15:19 i think finally within that you know i i don't i don't believe i i'm not a i'm an avid promoter and believer of ai but i don't believe the impact of ai is going to be instantaneously and i think think that's going to be a much longer outlook, about three, maybe four years before corporations start to really see the long-term gains of productivity gains from AI. So I think those are some of the structural elements that need to be addressed. I think in the short term, where we feel that things are going to be a lot more stickier, I think it's going to be the service-based economies of service-based goods, sorry, service-based prices. With the unemployment market, you look at the jobless claims, most recently been holding relatively stable. The

Starting point is 00:15:59 The continued jobless claims have been rising up a bit the last couple of weeks. It's coming down again recently. I think you're holding, it'll be interesting what the unemployment number comes out with, but that's been relatively stable. It's softening a bit, but not too much. So, and wage inflations are still quite high. So, although it's coming down, it's still quite strong. So, I think that whole service bucket is going to be a key focus for the Fed to look into

Starting point is 00:16:23 to see what decision base they come out with. I think that on the flip side, you've also got the housing market, right? And housing is one of the biggest contributors to household income, household expenditure. And I think the housing market in the U.S. is restricted by significant supply, right? I think volumes, the sales of housing has dropped. That's clear. No one's disputing that. I think that's caused by the increased mortgage rates, the interest rates as a result of that.

Starting point is 00:16:49 I think there's also the fact the lack of movement of labor and talent across the country we've seen previously. And I think all this work from home and this new working environment is causing less movement of labor as well. And I think somewhere that lack of a supply and the lack of restriction of housing is going to keep those prices relatively strong in the short term. In the longer term, that will slowly start to come down and reverse the trends. But at least in the interim, we don't see a viewpoint of our opinion that that's going to come down in the near future. As we see AI continue to permeate throughout the society, economy, et cetera, how much of AI is just like a reinforcement of the deflationary effects? And that actually gives more runway to the Fed and others for loose monetary policy and kind of like, hey, our big worry should be deflation, not high inflation, because AI is going to be this dominant thing.

Starting point is 00:17:46 Yeah, I think, you know, look, I'm of the I mean, we use AI like crazy in our in our organization and we love it. right? But as I said, I think that the timing of when AI is really adopted at a mass scale that produces the productivity gains that everyone is expecting, I don't see that in the immediate horizon. I think it's much more in the longer term. And so therefore, the Fed is probably, in our view, probably looking at that more as a longer term outlook and coming back to that structural element changes that's coming on board. I think in the more shorter term, The Fed's going to be focused on things like core inflation. They're going to be focused on services, and they're going to be focused on gas prices.

Starting point is 00:18:27 If OPEC can proceed with their desires of Saudi Arabia and Russia looking to try to restrict OPEC production and what's going on in Israel versus Hamas and the war there, I think there is a lot of opportunity or a lot of concern for the Fed to maintain their interest rates at a higher level for longer because if oil prices go up, that affects so many product categories that we use on a daily basis, whether it's 50% of the oil prices at the pump, at the oil prices follow through right down to the pump, but then it affects all the whole raft of other product categories

Starting point is 00:19:08 and services, right? So I think it's the shorter-term outlook is where the Fed will be are concerned about for the next three to six months and their outlook horizon there, I think the services element is going to be a critical factor for them and see if that starts to soften. I think they'll start to see a bit of a maybe a loosening of their viewpoints of interest rates and maybe that start coming down a bit earlier than expected. I think the other thing to think in effect is the rate of increase of interest rates has been so fast and it's so rapid. The question now is also being how does the Fed cut its interest rate and

Starting point is 00:19:48 what volume does it cut its interest rate? Is it going to be significant chunks at a time or is it going to be gradual? I'm of the belief that it will be significant chunks rather than smaller 25% basis points drops. I think it's going to be more likely 75, 50, 75, if not even 100 basis point drops why do you think that what why do you think it's going to be so aggressive i i just think if you start looking at economic data and if you start looking at the level of which they've accelerated to and if there is a softening in the economic data sets that's coming through in q1 early late q1 um you know no one's expecting i mean the gdp forecast in quarter three was at 4.9 percent uh you know you like that it's obviously anomaly in the grand scheme

Starting point is 00:20:40 of things you're everyone's expecting the q4 number to come down again um but still it's still going to be it's going to be a strong number or at least the forecasts are and i think somewhere once the the number starts to soften a bit and if if the i know the prices of goods and services start to see some softening then i think they'll start to drop it and because of the level they're at, it's going to come down more dramatic than otherwise. And so that's why I think it's going to be much more of a dramatic chunks of decline rather than a gradual 25 basis drops at a time. Got it. Now, when we start to look at maybe other areas of the economy in terms of inflation, one of the things I always remind people is when prices go up, they don't come back down.

Starting point is 00:21:23 I don't see any of the restaurants cutting their prices back. I don't see a number of these things that all went up. How do you think about trying to incorporate that level? It's almost more like cost of living and the persistent rise of that over time, more so than it is just a true year over year inflation number. Yeah, if we go back, I mean, this is the thing that we've been reporting on for quite a while, true inflation, which is to say, if we went back to before the inflationary increases started occurring, so it's back down to 2020, for example, people have had 20% of their money has been eroded right and a very income groups it varies but more than 20 percent of your income has been eroded because of inflation and that number is not going to come down right

Starting point is 00:22:05 it's it's the rate of increase will slow down that is clear um but we're not expecting i mean one or two categories will expect we'll expect real deflation but again it's real deflation versus last year or versus a year ago it's not real deflation back to you know three two three years ago, we've had this massive surge of 20%, 25% increases of erosion of people's income and therefore purchasing power. And I think that's the real fundamental thing. And I don't see us going back down to those levels in any manner, shape or form. Now, when we see the consumer, obviously they feel inflation. They complain about things being expensive. But I think if you walk down the street, most people couldn't tell you what the inflation number is itself. How do you

Starting point is 00:22:52 see their behaviors actually changing in terms of these high inflation environments? And is there some sort of psychological scarring that occurs where the high inflation that we experienced over the last couple of years will change behavior that even when inflation gets back under control, these people will continue to kind of act the same way as if inflation was still closer to 10%? Yeah, that's actually an interesting question for us, because we've been actually doing some, we're starting to do some quite deep analysis into that right now. We're trying to understand what are the trigger points of when we'll start to see a real change? One of the factors we're looking at, of course, is consumer expenditure, consumer purchasing power,

Starting point is 00:23:31 consumer spending levels. If you look at all those variables that are out there for a form of metric of consumer spending, they haven't really slowed down. There's post-COVID we saw huge government stimulus packages coming in to bulk up people's expenditure patterns. They spent more. The savings rate went up. They couldn't go out. Then they had revenge spending and that all came back. And now where people are came out this summer, a huge retail sales. Yes, it's markedly come down a bit this month, but a huge, significant retail sales in September. And I think somewhere, you know, the question for us is to say is how are people funding that the expenditure happens? And we're seeing saving rates being eroded. We're seeing debt levels increasing, whether it's household debt from a mortgage perspective, whether it's credit card debt, you got all these other debt factors that people are dealing with, whether it's auto loans, whether it's student loans and so forth.

Starting point is 00:24:34 And they've only been increasing at a household level. And so you're starting to see, OK, well, savings is eroding and household debt levels increasing. I've got higher interest rates to refinance that debt. So, you know, that's the sort of correlation that we've been looking into. And one of the things that we're looking into now is that saying, well, if you look at an average, if there's lack of mobility and people are not moving around the country, not buying new homes because of the higher interest rates and the owner occupancy rates are very high in the US. Therefore, people are most likely not going to be switching out from their 30-year fixed mortgages to get anything else. Their purchasing power is still relatively strong, unlike if you look at other markets like in Europe, where the variability of that mortgage rate changes every five years. You don't have a 10 to 30-year fixed in other markets. Very few

Starting point is 00:25:29 markets have that and so that gives it the us that takes a bit of a longer longer time for that impact of an erosion of consumer expenditure to change behavior and we see that most likely to come in probably sometime in the end of q1 q2 next year if things hold as they as we expect them to hold but we'll get more up to date to that once we start finishing our modeling talk to me about the product itself in terms of um how do people interface with you all how much of this is api versus more like dashboard type stuff? What are you seeing from actual customer usage? Yeah, so we got three. Trueflation's got three basic platforms. You either go on the dashboard, you look at the website, and you can access all the data that's there. You can see that.

Starting point is 00:26:13 You can also go there and consume as a retail investor. You can go and purchase the data, or you can get the access data through an API with the forecast ability with matching into into uh into the BLS data sets if people want that we have our our economist teams or analyst teams coming together with clients one-on-one to to debrief the outlook of the future why it's happening uh what our forecasts are what our three months rolling forecasts are and so forth so those are generally three platforms you either go to Enterprise solution at one end or you got the dashboard access on the website on the other end now what are some of the challenges that you guys facing right now from a pure product standpoint? So not data collection, not kind of the methodology,

Starting point is 00:26:56 but what are some of the things you're thinking about with user experience or how you'd be able to actually make this much more kind of prevalent across Wall Street and elsewhere? Yeah, I think for us is one, I think, first of all, the exposure of our data set, I think it's fairly well known. Of course, there's more work for us to be doing to accelerate exposure. But I think the other factor for us is how do we drive more defined usability of the data right you know especially now in a world where we believe inflation is going to be hanging around a lot more a lot longer than than the market is expecting um but how do we translate that into additional models forecasting and we start doing now casting with every new data injection that we

Starting point is 00:27:39 get you know how do we leverage that into um models and and quant aspects for for end users right and that creates for us um you know a bit more of a stickier relationship and a bit more of a deeper understanding with the community of what they're asking for versus what we can deliver so it's more trying to go deeper into the data set more trying to find deeper and supporting the analysis and applications that our end users are using the data for um and and i think that combination is where our focus is right now what's been the most surprising thing to you in terms of doing this has it been the receptivity maybe the resistance from people maybe something with the product what's really been surprising um yeah i mean i look we we i think we were very fortunate

Starting point is 00:28:27 around the timing of our launch let's be clear about that we launched uh nearly two years ago and the timing was spot on. I think that blew up the receptivity of it. The amount of monthly users we're getting on the site is incredible. The fact that there are Bloomberg chat groups about Truthflation data I think is amazing. I think the receptivity blew us quite considerably. I think that on the flip side, where we've been desperately trying to keep up with the to high demand is about how do we provide the data in the most usable format to be able for consumers to digest the data as much as they possibly can. And so it's keeping up with the usability of it.

Starting point is 00:29:19 It's keeping up with the volume of data. Can we find other data sets? Can we find things that explain the movements of inflation? So what's the housing supply? What's building material costs, for example? All these types of aspects is where we've been focused on, and that's been the flip side of it, is getting the demand to drive that as much as we possibly can with the resources that we've got.

Starting point is 00:29:41 Now, what does success look like in terms of 20 years from now, Truflation is quote-unquote successful? Does it replace BLS? Is it just the best alternative resource? Is there a bunch of financial products that are built off of this? How do you think about success for the product itself? Yes, I think, look, there are multiple prongs for success for us. One is how do we get more into products, especially in the DeFi world, but also in the traditional

Starting point is 00:30:09 finance world? How do we get our data ingrained in products and developments that's happening around? That's one aspect of it. I think the tokenization ability certainly plays very nicely into our dataset. I think the second aspect of it, yes, is that the data becomes in due course, not overnight, but I think in due course becomes the gold standard for inflation. That is our aim. That's what we've always been designed to do.

Starting point is 00:30:38 And we certainly hope the market will follow us on a journey to achieve that over a period of time. We're going to need more credibility, we have to get people to become more familiar with the data and so forth. But yes, that's very much the longer-term application. I think that the third thing for us is then also not only trying to get a gold standard and also becoming more ingrained in products, but I think also is driving the applications, the analytics of the data.

Starting point is 00:31:06 How do we customize this a lot more? How do we become more bespoke and apply all the data requirements that everyone wants to do? And that's going to require not only getting the analytical and using AI a lot more than what we already are using them today, but more also data sets. What other data sets can we build into this that's far reaching and then become potentially a marketplace where people buy and trade and create custom indexes off our data sets by combining, I don't know, oil commodities with inflation data or wheat production with temperature and rain data in Arkansas. Arkansas versus the price of carbs in grocery retailing, for example. So the applications, that's sort of where we're looking at where that future becomes success looks like from a three-pronged approach. Makes complete sense to me.

Starting point is 00:32:00 Where can we send people to find you on the internet or find out more about Truflation? Yeah, you can go to truflation.com. You'll find the websites there. Contact us is on there if you need anything from us. you can go to our telegram account or you can go to our twitter account both at trufflation or you can go to our linkedin account um but yeah any questions we're welcome any ideas suggestions love to hear from everybody awesome well i appreciate very much oliver it's been fantastic i always learn something we talk and i think people will learn from this conversation as well

Starting point is 00:32:30 so we'll definitely do it again in the future thanks a lot for having me anthony been great conversation Thank you for watching.

The Pomp Podcast - #1276 Oliver Rust | Here Is Proof That Inflation Data Is Wrong...

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