The Holy Grail of Macro | Prometheus Macro’s Aahan Menon on Why Tariffs Won’t Cause A Recession And Why Buying Dips Only Works In An Expansion
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What moves markets? Is it the captivating stories we hear, or is it the cold, hard numbers? While both play a role in macro, it's often the data that leads the narratives and price action to give investors an edge. I'm thrilled to have Ahan Mennon of Prometheus Macro with us here today.

When it comes to rigorously analyzing the data, Ahan is the expert that I turn to first. He's truly one of the best macro quants out there, and he's going to share what his data-driven models mean for stocks, bonds, and the US economy. For a limited time only, Monetary Matters listeners can get a special discount to Prometheus Macro. You'll find the link in the description. Check it out. Let's get started. The ECB is ready to do whatever it takes to preserve the euro.

And believe me, it will be enough. Thank you. Just close the door. Extremely pleased to be joined today by Ahan Menon, founder of Prometheus Macro. Ahan is a quantitative macro strategist, analyst, and trader. His clients include some of the biggest and most sophisticated hedge funds in the world.

Ahan, it is great to see you. Welcome back to Monetary Matters. I think we spoke last in the middle of March. It's fair to say that since then, a lot has transpired. How have your views evolved and changed since then, particularly on the equity market? Let's begin there. Hey, Jack. Thanks for having me back on. Always great to be back on the show. I think it's actually been exactly two months on the dot since I was last here.

It's interesting, in markets it's kind of been like, it's been a few lifetimes, but in the economy not that much has happened. I think the last time I was on here, we were talking a lot about the prospects of tariffs and what they could mean for the economy. Our views were that tariffs would not be super impactful. Following that, we went into Liberation Day, which had very, very outsized impacts on equity markets.

After Liberation Day, we did see a slow de-escalation. And since then, equity markets have risen. When it comes to the economy, not that much changes in a two-month span. I think that what has really changed is the pricing in equities.

So last time we spoke, I think the main takeaway of what we were seeing from our systematic process is the idea that the expected returns on equities would be positive, but with a high amount of variance. I think that's roughly in line with what we've got over the last couple of months. But at the same time, when we're looking at it today, we're probably much more neutral than

on equities looking forward than we were the last time we spoke. So we still think the variance is going to be there. It's definitely not going to be like it was, but the outlook for equity prices is more sober than it was the last time we were on. Yeah, Anand, that's a great prediction. Two months ago in the middle of March, you said, I think expectations will be positive. The returns for the S&P for stocks will be positive, but with a lot of volatility. That's exactly what happened. We're 7% higher in the S&P, but with a lot of volatility. Volatility probably averaging, you know,

in the 30s. So definitely a good prediction so far. So why have you gotten less constructive on stocks as the market has surged and regained and surpassed its pre-liberation day highs? And also just walk us through your process as well, kind of bleed that in there. I think when it comes to equities today,

I think a major reason that we've gotten a little bit more conservative on equities relative to where we were is kind of the inverse of where we were at the last time we spoke, where basically equity markets have done so much so fast in terms of pricing away any prospective impact from tariffs or any prospective impact on growth in the future that now they're looking largely consistent with what they were more like around the start of the year. And I don't...

In no way am I a bear on equity markets right now or are the Prometheus systems pointing to really bearish outcomes. I think it's just the speed of the rally, both relative to the speed of the rally for stocks in terms of prices relative to themselves, in terms of prices relative to the economy, relative to other assets has just been so tremendous and so fast.

It's very hard to sustain this kind of move unless you had a dynamic where earnings were meaningfully mispriced to the upside or downside. So if we wanted a rally, we would need earnings to be mispriced to the downside. But we just don't have those types of conditions today. The way we're looking at things, we basically see earnings as roughly consistent with where the economy is at.

And so as a result, we just don't think there's that much room for us to keep going parabolic higher. I think a very simple and common sense way to think about this is the rally that we've seen from the lows

So the most consecutive days of positive performance that we've seen, I think, on history. And so I think just kind of being a little bit more sober and level-headed and kind of saying that, okay, we've probably exerted a lot of equity market momentum in the short term, and now is probably a time to take a rest. That's basically the view right now.

Two months ago, you basically said you didn't think tariffs would have a hugely meaningful impact on economic data. I think it's fair to say so far that view has been proven correctly. Even though we've had a moderation in tariff rates, we did have multiple weeks where tariffs on China were extremely high, and one week where rates on basically the entire world, on non-deficit countries, were extremely high.

Why is it the case that so far the economic data has not changed that much? And also, can you just walk us through in terms of growth, inflation, the labor market, as well as your outlook on all of those things? Or maybe I should say your model's outlook on all those things and how they're impacted by the data have evolved over the past two months. Because we've had an incredibly choppy ride in the equity market, but it sounds like you're saying in the...

in the actual economy, the data and the somewhat implied data by your readings has been much more muted. Talk to us about that. Maybe we can start with the tariffs. I don't think that we know for sure yet what the impact of tariffs are. So far, the equity market views have been good, but I don't know if we can definitely say the tariffs have had a very deleterious impact or good or bad impact on the economy right now. We just don't know that yet. But what...

I think was really useful is prior to Liberation Day, as we talked about on the last show, we basically ran a stress test to understand what would be the impact of tariffs if we just had an absolutely ridiculous outlier outcome where tariffs were raised by 10x.

Now, that was supposed to be just like a crazy person's, you know, situation, which is which was it was supposed to demonstrate that nothing can nothing bad can happen even if tariffs go up a lot. The really interesting part is that the announced tariffs on Liberation Day were basically in line with that super, super outlier event.

And so we definitely didn't expect that. It was just nice and sort of comforting to know that it was still within the range of plausible outcomes that we looked at, but it was not our expectation. But when we look at... So following Liberation Day, we basically said, okay, we've got this crazy outlier sort of tariff event. What is the prospective impact on the economy if they're applied as announced? Again, we didn't think that it was going to be

maintained at this rate. I don't think anybody thought that, oh yeah, they're actually going to go through with, you know, the average rate was about 22.5% tariffs across the board. I don't think anyone expected that they would actually go through with that. It was, I think the general consensus is that you would do have some art of the deal type stuff going on. And so what we did was we said, okay, let's see, even if they don't do any art of the deal stuff, what would happen to economic activity if we apply the tariffs as is?

And so there are three channels through which we perform those estimates. The first was the direct effect of tariffs on corporate profits. And so when you have a tariff, it's basically a tax that tax takes away from the after-tax profits of companies.

So we can estimate the direct dollar impact. That was the thing that we discussed last time. And that effect is actually minimal to non-existent. You know, trade balances and export activity relative to total activity are just not that big a part of the U.S. economy. And so just the dollar hit from redistributing from the private sector to the government sector isn't that big a deal.

The second impact is the impact on the trade balance. Now, this is harder to model with any amount of rigor, which is what we talked about last time, but we wanted to come up with some rough estimates. So what we basically said was, okay, the tariffs, they're a price shock, right? They're a price shock to the trade balance. And so we can estimate the sensitivity of output based on the change in prices.

And so when we did those estimates, what we found is they actually modestly improved the trade balance, which is kind of consistent with the government's objectives. But now they don't, they're not a sign of, that's not a sign of economic health, right? Because gross trade volumes would decline in a manner that would be consistent with like the global financial crisis. But the net, because we actually have a larger, we have larger exports of services in the United States relative to imports,

the sensitivities are slightly different, which means that you would actually have your imports fall more than your exports would. And so that would kind of help the trade balance a little bit. It would actually help GDP. That candidly, we do a lot of quantitative work and it doesn't really hold quantitative standard, but it's a nice guidepost to just kind of think about it that. The last and most quantifiable effect of tariffs

are the confidence effects that come from what's happened, are the confidence effects on the economy. So when you have something like these massive changes in policy, they impact businesses' expectations, consumers' expectations, all of these types of things. And what that does is it basically dissuades businesses and consumers from making large investments or large purchases.

And so the most direct impact that we could model and estimate with a good amount of rigor is the effect that the pass-through of confidence has on the economy in the form of investment and durable goods consumption.

And so when we looked at that, we said that if tariffs were applied in the way that they were announced, it would basically turn into about a 1.5% drag on the economy in terms of real growth. And that would actually be consistent with the recessionary pressure. Now, the important thing is that you need two things for that to happen. You need the tariffs to, one, be applied as announced.

And two, you need a persistent decline in expectations as measured by things like what's happening in the equity market, things like what's happening in the credit market, what's happening to consumer surveys, business surveys. And what we've seen is that as tariffs, you know, will kind of walk back a little bit, a lot of those pressures have just reversed.

And you know, while tariffs, if they were, if the pressures were kept on and markets kept doing what they were doing and confidence got really bad, we could have had a recessionary circumstance. We basically had a lot of that just dissipate. And now this is all about expectations and what the future would likely hold, right? In terms of the actual hard data,

Nothing much really happened. We did have a significant amount of tariff front running. So we had the gold imports front running on the trade balance side. We had a lot of, a huge amount of motor vehicle demand. I'm sure everybody that's owned a vehicle or leases a vehicle has got a call from a motor vehicle sales rep trying to do some type of deal or whatnot before the tariffs are in place. So we've had a lot of pull forward of that demand.

And that has actually juiced a lot of economic numbers. So retail sales numbers, personal consumption numbers actually looked a lot better following the announcements of tariffs. But now we're probably going to give away some of those gains. And, you know, when you look at today's retail sales numbers, a little bit more sober, the picture is beginning to slow down a little bit.

But I think the big takeaway is that you've just had a very large change in expectations around the economy over the last couple of months, but not necessarily like the economy hasn't done that much in the last two months. The economy hasn't done so much in the last few months. Yeah. And I think that I will start off by saying

I was probably too bearish on the economy, the impacts of tariffs on the economy. A lot of economists who were bearish were probably too bearish on the impact of tariffs on the economy. You know, things are still to be seen. So your perspective about, hey, maybe things are not going to be that bad is very welcome on the show now. And it was definitely welcome two months ago. Number one, good call. With that being said, I'm just going to like,

pick your poker poker model a little bit because number one, you said that the impact of corporate profits will be minimal. As you know, it's companies, importers who pay the tariff costs. So how is it that it's going to be corporate profits is going to be minimal? Is it that they're just going to be able to raise prices by 100% of what they have to pay? Is it going to be that the company they're going to pass on those costs increases by demanding lower effective costs by the factories around the world?

And then also, how are you thinking if Walmart and Target are not a huge percentage of the S&P, it's all about the Magnificent Seven and service-based companies, but a lot of employment is at Walmart and Target in the country. So if Walmart and Target importers are really struggling,

that net net wouldn't impact the S&P's profits a huge amount. But if they have to lay off people, then spending across the country could decline sharply. Basically, we did a really, really simple model because we like we didn't want to deal with too many, you know, modeling nonlinearities. So what we said was really simple, right? Which was the idea that

If we have X amount of tariffs announced, so the number goes from whatever the current rate was, you know, 1%, it goes to 22%.

That 22% tariff directly comes out of the pockets of corporate profits. Now, what you do is you basically, how you model that is you go and you look at the customs and excise duties tax that the government receives, and you scale up that number commensurate with the announced tariff rate. So we did those calculations, and what we found is that basically the amount of

the amount of tariffs in dollar terms, even assuming these massive, massive numbers, just weren't enough to actually meaningfully dent. So like customs and excise duties taxes, I think are something like $80 billion. Okay, so you 10x that, like, you know, you get to $800 billion. But you're basically looking at

a few companies worth of profits. The main point was that on just a dollar impact basis,

you can't really like hurt profits just through the redistribution channel. Now that's a pretty simple and maybe arguably simplistic lens. But what we just wanted to quantify is, hey, like what is the thing that we know for sure? This is the baseline we start with. And so the baseline assumption is that, okay, like on a dollar impact basis, you can't take away that much from corporate profits. From there, you have to start accounting for more nonlinear effects, which is that, oh, my prices have risen a lot.

What are the adjustments I make? Do I pass it on to the consumer? Do I eat some of that cost? Those components of it are a lot harder to model, which is the analysis that we talked about when it came to the trade balance. So the way we model for that

is to basically assume that it's a price shock and that demand responds, demand and output, hand in hand, they respond to that price shock. And so what we have found over history, one, there's a very tenuous link between those things. So anybody that's certain about that

Take it with a bag full of salt. There's a very tenuous link. But even if we use the most optimistic pass-through numbers, which is basically that, okay, if tariffs move by 100%, then output has to fall by 100%. Even then, because of the way the trade balance is distributed, where we have a lot more services exports and we have a lot more goods imports,

you basically get to a point where it's actually a small plus for GDP. And we tried to do a bunch of sensitivities around that. Now, I think all of this is just to say that what we wanted to do is we wanted to understand the worst case outcomes. And the worst case outcomes for us are clearly not in the trade balance.

They're not in the immediate profit impact, but they're in what happens to consumer investment in terms of consumers buying automobiles, washing machines, air conditioners, and then businesses investing in property, plant, equipment, real estate, all of those types of things. And so that is a much more predictable channel and can be measured through a combination of financial conditions and surveys in a timely manner.

And when we looked at that, like what you would need is equity markets would have to stay really bad. Credit spreads would have to widen a lot and surveys would have to stay in the toilet. Right. And two thirds of those things basically reversed. And so a lot of the pressure that you had basically just started to started to pull back over the last two months. Yeah. I mean, I think that the profit impact alone is.

Could be right, could be wrong, but that's the thing that we know for sure. We know the dollar redistribution. Then from there, you start getting into a little bit more complicated, nuanced, and frankly, hard to model areas. And yeah, we think a lot of that basically just reversed.

Even though, as you indicated earlier, your model's position in the equity market is moderate. You're not short, but you're not extremely long in the model. You're not super optimistic. Your model's not super optimistic about stocks. Your model's economic outlook is somewhat benign relative to the somewhat unanimous recession calls of a month ago. And so just walk us through, for example, your impacts on growth and inflation and how

how your model gets that forecast? The baseline is basically that, you know, we think that currently growth is running on a year-over-year basis at about 1, 1.5%. A lot of that has trade numbers in it, which have all kinds of issues, which we've discussed on the previous show. And so growth numbers aren't great. If we look at only private, we look at private consumption and investment in the economy, we're basically running at about 2%-ish growth.

And we think that there's probably some scope for us to get to 2.3% over the next 12 months right now, which is roughly where we were at the last time we spoke as well. The way we get to those numbers is basically what we do is we look at business cycle indicators to understand what is likely to transpire in the economy from a business cycle perspective.

And so when we look across those business cycle indicators, those are things like fixed investment, business fixed investment, corporate profits, all of those types of indicators. And when we look across those types of areas of the economy, we basically see an environment where investment in the economy has actually been starting to tick up very modestly. Now, part of that is perhaps overstated because of the tariff front running, right? So we're

We don't know that for sure, but we're a data-driven process. So what we're looking at today is a situation where we've seen industrial equipment investment rise. We've seen motor vehicle investment rise. We've seen construction get a little bit better. Construction has been kind of meh over the last six months and kind of stays there. But broadly speaking, we're basically, and then intellectual property investment has just been tremendously strong, remains tremendously strong. And so when we're looking at these drivers of the business cycle, we basically see an environment where, oh yeah, things are pretty good.

Are we going to go to 3%, 4% GDP growth? Absolutely not. Can we stay here if nothing really meaningfully changes on the tariff front and on the policy front? Yeah, we could totally stay here. So that's basically the outlook and what's driving that outlook there. On the inflation side, we're roughly running at, I believe, headline CPI is about 1% or 2.1%-ish, something like that. We see some softening, but a lot of that is just technical effects. So

Shelter has been softening. It's probably going to continue to soften. A lot of that has to do with the way shelter is computed. We do, you know, we've also seen a little bit of like mixed readings in the commodity sector. So we basically see, you know, an environment where we can basically stay around where we're at. So the economy to us is,

through the lens of all these kind of systematic processes, basically looks like a kind of steady state, not too exciting, you know, not a boom, not a recession, just where we're at kind of situation.

I generally believe in, I think it was Neil Duddy who said on the show, the data is the data. In other words, you know, if someone forecasts a recession and then the data comes out and it's clearly not a recession, you can't just say, oh, well, here's five asterisks why I'm actually right and why the data is wrong. I generally believe that. And I know you do too.

However, I would say with GDP and particularly front running, there can be some distortions. Like, for example, Brad Setzer, who I've interviewed, a trade balance payments expert, he said just the amount of imports of

pharmaceuticals from around the world into the United States to front-run tariffs is just simply enormous. The same as you indicated with gold, the same with motor vehicles. And so that is going to come in as a negative for GDP because as you know, GDP is net exports, so imports is a minus. So the more the imports to front-run tariffs, the lower the GDP. So the negative reading we had in GDP for the first quarter isn't necessarily

necessarily as bad as it looks. So I actually happen to agree with the economists in the Trump administration. You say that it's not as bad as it looks. And likewise, if we get a boom in apparent GDP for the reasons that you indicated, that imports are going to go way, way down and exports are going to go down by less. So net exports are going to go up and that will be indicated with good reading for GDP. I would probably disagree with those Trump economists are going to say that it's great. And I'm actually probably would disagree and say,

That is, you know, in the same way that bad reading is artificially bad. This reading, you know, a good reading can be artificially good. Yeah, I think that's that's totally right. And, you know, it's I think it's really important today to recognize that the U.S. is not a trade dependent country, like in the sense that a lot of activity of the

the majority of all activity in the United States is domestically oriented in terms of consumption. And a lot of clarity can be gained just by like not worrying about the trade. I'm not saying don't look at the trade, don't, you know, but I think that if you're looking for clarity, a lot of times you can get a read on what's happening just by looking at what's happening to businesses and domestically. And so when you look at that picture today, yeah, investment conditions are fine. Consumption is fine. The government is still spending money. And so I think that

Yeah, the trade usually is important at one of two times. Either you have a trade war, right? Like that's when trade's important. Or, you know, you're at a point where you're in a recession. And so trade actually...

actually is a counter-cyclical indicator. So often the times where trade contributes the most is when you're in a recession. And when trade contributes the least, you're actually in a really, really strong expansion. So I think that looking at the net trade balance is probably not the best idea generally. If you look at gross trade flows, right? So like how much imports are happening, how much exports are happening, that can be very informative depending on what you're trying to do.

Yeah, like I would agree with that. And I think that the easy way to kind of sort through a lot of noise perhaps is to focus on domestic conditions.

And just the observation that, as people could tell you're a data guy, the observation that the US economy is much less dependent on trade than a lot of other countries. I mean, I think Hong Kong is over 100% of the economy is in trade. That's a very valuable insight that would have done me well over the past two months. And I think that

tell us a little bit about your other data, your systematic process that other ways it can help investors. As I will have said in the beginning, you are an affiliate partner of Monetary Matters. Today, people who are interested in your process and will get into your process will have access to a discounted version of your process. So people will be able to click the link in the description. But I'll

But just tell us what is the problem that you are trying to solve and get into the process. And I guess we'll start with a question that is kind of the Holy Grail of investing that everyone wants to do is how do you think about beating the stock market over a full investment cycle? At the end of the day, this is basically like the value that we provide, right? Like we've spent a good amount of time talking about kind of like the macro views and all of that, but where...

What we bring to the table is basically taking all this kind of stuff, systematizing it and turning it into portfolios that both retail and institutions can use. Right. And I think, you know, I started Prometheus three years ago. And one of the things that I repeatedly got, you know, particularly in this particular three year stretch was always how do your strategies compare to the S&P 500? Right.

And at every point in time, you have to answer this question as a quantitative investor with a bunch of caveats and really, really complicated answers that is not intuitively satisfying to most people. And I think after a while, what we basically said was we want to meet investors where they're at. We want to basically create something that is consistent with what most investors are trying to do, which is just outperform the stock market over the long term, which we call a full investment cycle.

And so what we did was we basically said, can we take our various alpha signals and combine them in a way in which we create a process where investors can dynamically adjust their exposures to the S&P 500 in order to create a return stream that is reasonable,

isn't super high risk and avoids very, very large drawdowns while maintaining upside participation to the S&P 500. And so we spent a lot of time and put a lot of effort and research time into creating the strategy. And we came out with the strategy earlier this year. The official launch was about a month ago. We started delivering insights from the strategy at the start of the year. And that strategy has

been really, really helpful in kind of navigating all of this turmoil. So I think, you know, in some senses, the best value that I can potentially provide in this conversation is like how we thought through the environment so far and how we're thinking about the environment going forward through those lenses. But basically, this is what we're trying to achieve. We're trying to say,

Can we beat the equity market over a really long period of time using quantitative measures? Now, we think that there are four big ways to do that. We think that you need to have an element of sector selection. You have to have an element of market timing. You then have to also introduce a small amount, not a very large amount, of diversification.

And then you have to finally always end with very, very strict and consistent risk management. We think that combining those levels allows you to basically deal with the age old question of how do you beat the stock market over the long term? I'll pause there and we can pull on whatever thread you want to get into. So those are the four pillars. But in some or all of those pillars are values.

many different things that a lot of people can offer alpha, but a lot of people focus on and perhaps over index on. So for example, people talk about liquidity conditions, people talk about predicting changes in growth and inflation. And I feel like we've become friends over the years and I've brought those up to you. You say, oh yeah, I do that. But if I just did that,

you know, that has a Sharpe ratio of 0.5. This has a Sharpe ratio of 0.3. That's not good enough. You've got to layer all of those on top of them, stack them up together, and then use those basically diversified bets in order to generate superior risk adjusted returns. And that's what your models do. And that's what, you know, I mean, your clients, your institutions, some of the biggest, best hedge funds in the world who I know are your clients, like they wouldn't be your clients if you'd

you didn't do a good job at that. And so I think that that is a little bit of a challenge as we sit here today of like, how do you describe your process? Because your process involves so many different signals, so many different things. But I guess let's start with beta timing. I mean, that is something that everyone wants to know. How do you predict what's going to happen in the stock market? Like I

I, as an amateur, have tried to do that. It's tough. People watching this, they know it's tough. Often the market moves exactly against your intuitions and your thoughts. So tell us what's your quantitative process for kind of predicting where the stock market is going to go, what you call beta timing. Beta timing is always super interesting and it's like the sexiest part of the business, right? And I think beta timing, what is beta timing? It's basically you're saying that, okay, I have a view on an asset.

a beta, so the S&P 500 is the most common beta that people use. Can I move around my exposure to create something that is uncorrelated to the underlying beta? So can I just basically and simple, can I time the market well? So how do you think about timing the market? There are basically three things that determine what the future returns on an asset are going to be, right? And this is definitionally true.

The first is the amount of carry the asset generates. The second is the amount of momentum there is in the asset. And the third is the amount of mean diversion. To perhaps make it even more clear, you basically can get compensated for owning an asset either because it has a positive carry or because the price changes.

Now, when you're trying to do beta timing, what you're trying to do is you're trying to predict which one of these things is going to be the driver of asset prices tomorrow. And so what we try to do at Prometheus is we try to have a dynamic but balanced exposure to all of these factors, all three of those factors. Now, I think both of these things that I'm describing are really important. So why balanced? Because

Everyone knows somebody that happens to get lucky, start their business or whatever, doing one particular style of investing. So, you know, if you just happen to be at the right place at the right time and you were a trend follower, you may be a tremendously successful investor. Alternatively, you may have just said that I'm a value stock picker, which is often a

synonymous with carry, then you may have been tremendously successful. But the flip side to that is also the fact that if you are betting only on one thing, like you just silo yourself and say, hey, I'm a value investor. Like I like carry. Or hey, I'm a mean reversion, short-term mean reversion guy. I like that. You basically run the risk of

prospectively decades of underperformance. So what we want to do is we want to have a balanced exposure. We want to be able to bet on all three things. We want to be able to bet on the carry of an asset. We want to be able to bet on it trending upwards. We want to be able to bet on it mean-rewarding.

Now, along with having that balance, what we want to do is we want to have a dynamic exposure to those things. Because like I was describing, sometimes it just makes sense to go long momentum and own momentum for a long time. And so what we want to do is we want to be able to say which one of these things is offering us the best returns, right? And tilt our strategies to those types of factors,

over time. Now, I know all of this has sounded pretty quantitative or whatnot, but I think that this will square the circle nicely. The way we try to think about tilting between carry, mean reversion, and trend is to use macro factors to understand which one of these things are going to work. I think last time we spoke, it was a really good example where markets had begun to really, really break down, right? Like we had, you know,

I think the last time we talked, we had a short-term momentum reading, which we shared with you guys, which was maximally negative. And what we came on the show and talked about was the idea that momentum is a good bet, but only if you're in a recession. If you're not in a recession, the best trades to have on are mean reversion style trades.

Alternatively, if we're in an environment like today where we don't think that earnings are meaningfully mispriced in any direction, up or down, which means that price wall is probably going to be pretty muted. You don't want to bet on mean reversion or trends because you're just not going to have catalysts to generate that. So what do we do in that environment? We look for carry.

And so what we're trying to do with our process is basically have dynamic but balanced exposure over time to all of these things that are

predictive of future returns. And the way we do that is by saying, which macro relationships allow us to get a little bit of edge in understanding which one of these strategies is going to do really well? Does that make sense? I hope that wasn't too like, quantity. Yeah. So trend is basically, if the stocks go up on Monday, they're more likely to go up on Tuesday. Meaner version is the opposite. If stocks go up on Monday, they're less likely to go up on Tuesday, and in fact, could go down on

on Tuesday. That's such an important point, Ahan, that you brought up in our previous interview, that in an expansion,

when the equity momentum is negative, i.e. stocks are going down Monday, Tuesday, Wednesday, in an expansion, you actually want to bet that on Thursday, they will go up. It's only in a recession when a negative trend, Monday, Tuesday, Wednesday, down in stocks, is going to have a Thursday going down. So is that insight on, and we can flash on screen a beautiful chart that you've made for clients showing that it's really instructive.

Was that on display over the course of April where, I mean, maybe you would say that we're still in an expansion. I mean, you tell me. But if we were in an expansion that the fact that stocks crashed on Thursday, April 3rd, Friday, April 4th, you know, surprise, surprise. We have a Wednesday, April 8th or something where stocks went up 10%. And then, you know, so far now, I guess.

I assume equity momentum is very positive because Monday, Tuesday, Wednesday, stocks are just going up and up and up as we record in the middle towards the latter half of May. Yeah. Was that insight that you shared with us in March, was that on display over the past month?

Yeah, that has been the defining characteristic of this rally from our perspective. So what we saw, and it's not always something that's easy to do. We have these systems, we have the models, and we trust them. But you can imagine we had our conversation, and following our conversation, equity markets did pretty well, which was consistent with our expectations. And then we had Liberation Day, and equity markets overnight meltdown.

And our signals at those times began to trigger because nothing had changed with the economy, right? And even if we were going into a recession, the recession wasn't going to start next week.

And the amount of negativity that was brought forward so quickly allowed us to actually say that, hey, like this actually looks like a situation where you could easily bet on mean reversion, right? Maybe not easily, but you could bet on mean reversion with a high amount of signal and you could expect positive outcomes. And so that is definitely something that's happened. But now, right, those same signals basically tell you the exact opposite thing, right? Which is the economy is still where it's at.

But prices relative to themselves, right? So like if I look at the history of prices and then I look at them relative to other assets or relative to global assets or relative to cash, equity markets have just been on a rocket ship back in this recovery. And so what those same signals are telling you is that, hey, like we've done a lot of improvement.

But at the same time, you probably need to calm down a little bit because the economy isn't doing that well. We haven't got the most explosive gains that you can have in the equity market on the upside is when earnings expectations are in the tank or have fallen a lot, but the economy is actually recovering.

And so we are not at that type of time. So the ideal time to ride a trend is when earnings expectations are down, but the economy has begun to recover. We're not in that type of environment. So again, much like the last time we spoke, I'd be much more inclined to bet on mean reversion at this particular junction than I would be to try to ride the trend even higher at all-time highs.

So, mean reversion means that if stocks have been going up so much, you're not going to bet against stocks, but be underway stocks because of that. Yeah. Yep. That makes sense. And then tell us about carry. I think of an example of if the overnight borrowing rate for risk-free is 4.3% and the 10-year is 4.5% of the 10-year treasury, you get a 20 basis points of carry by borrowing money to be long of the 10-year. Mm-hmm.

What does carry mean in the stock market where you have the US market with the earnings yield of 2% or 3%, you tell me, and earnings yields around the world are higher because they are cheaper markets. So does carry really ultimately mean valuation? And if so, how does that jive with the old saying that you can't trade valuation, which is probably true in individual stocks? You can't be saying, oh,

Palantir is expensive and this random material stock is cheap. Therefore, I'm going to go long the material stock and short Palantir. Like that has not been a good trade over the past year or two years. But is it the case in macro assets, stocks, bonds, commodities, that carry and valuation is actually a trading tool? Carry is a catch-all term, right? It's a concept. The concept is basically, what do I get paid if nothing happens, right? If the price doesn't change at all, what do I get paid over the long term for owning this asset?

And so in bonds, like you said, the shape of the yield curve, which is the difference between your tenure and your overnight rate,

That is very informative of the amount of carry that you're going to own on the bond. That's how most professionals are evaluating whether they want to own bond exposure or not. In equity markets, there is less consensus on what exactly the definition of carry is. There are many different ways to kind of quantify that. But I think a really nice metric and simple metric is to use something similar, which allows for cross comparison across markets, which is a close cousin of valuation, which is the earnings yield.

And so you can look at the nominal earnings yield on an equity, any equity market, and basically say, what is that earnings yield relative to cash or relative to other equity markets or relative to other assets, right? And those measures are generally pretty informative of forward returns. Now, are they informative about tomorrow's returns? No, they're not. Are they next week's? No. But over reasonable horizons, you can basically say that

carry or earnings yields or however you want to define them are generally informative of the kind of returns that you want. Now, when you look at that today in a U.S. context, that carry is basically indicative of zero expected returns over any reasonable horizon.

Now, that is relative to cash rates. That is relative to bonds. That is relative to global assets. And in fact, U.S. equities on that basis are one of the most expensive assets in the world. Now, what that does is it basically creates an opportunity for investors, though, which is that you can get better expected returns in other countries and create a diversified portfolio, right?

which allows you to improve both the amount of portfolio risk you have and the amount of expected returns that you have. And I think that that is something that's super underappreciated today because people don't realize that, I think there's a general conception of you should, you know, what I'm saying describes the fact that U.S. equities are highly valued, like the P.E. ratio is very high.

But that is not the same thing as an earnings yield. An earnings yield is not, I think a PE ratio is a poorly constructed estimate of mean reversion. Whereas earnings yields

are estimates of carry you get for owning the asset. And when we look at the carry that's available on equities today relative to global assets, the divergences are just massive. You know, you can own something like a 5% premium owning a mix of global assets relative to equities

just by tilting your portfolio away to global assets rather than equities. And so I think that that's a pretty big source of expected returns for investors generally. And the advantage of doing that is also the fact that you can probably get a lot of diversification benefit. And so your risk comes down, your expected returns rise, you

It's one of the very few cases where you can sort of have your cake and eat it too. Price to earnings ratio, PE ratio is price over earnings. You're talking about the earnings yield, which is basically earnings over price, which is, so you divide one by the price to earnings ratio to get where you're talking about. And it is a valuation metric. Let's now look at your positioning

So you've got two basically different things of position. You've got one which you compare just to the S&P and then one which you compare, I guess it's what's it called? Absolute returns. One is your different constituents are the S&P and then four sectors of the S&P, industrials, energy, tech, and home building, and then bonds, long-term bonds, short-term bonds, and then cash. And

And so the latter one is just stocks, bonds, commodities. So it's pure macro. That's the total return one. Tell us about your positioning right now. We could share it on screen for people only listening. Like in that S&P thing, you're actually short stocks, 17%. You're in industrial 7% long, 4% long in technology, 18% in both short and midterm bonds, and then 69%

in cash. So I guess you have explained a few reasons why about that. But do you view that as being neutral on stocks? Because even though you're only 11% long industrials and tech, respectively, you're 17% short the S&P. But

but is it a beta? Does the tech and the XLI have a higher beta? And then also, how can you hope to beat the S&P? I know on your back test, it has definitely, particularly in volatility-adjusted terms. If some of the time you're short the S&P, are you trying to beat the S&P by

avoiding the drawdowns and capturing most of the upside because like generally, you know, being underweight stocks generally doesn't work. So you have to, you have your bait, your timing tool has to be pretty precise, right?

So maybe we can start with the, with regards to the differences in positions, they also have like literally a few days apart in rebalance times. So the absolute return portfolio rebalanced on Friday. So it managed to catch Monday's gains and then the S&P 500 program rebalanced on Monday, which means...

It reduced position. But, you know, we'll have a rebalance for our ETF portfolio literally tomorrow, the day after we record this. And likely those positions are going to come down. So a lot of the divergences there are actually just about rebalancing times. There were really, really juicy gains, as you know, on Monday. And so that was definitely a sign for us to take some off the table. But that being said, I think the major thing when it comes to the net position and equities is that the way we've structured it is

We want our sector exposures to always be long exposures, right? For a variety of reasons, because people are replicating these in various different formats, right? Like it's hard to get short sector exposures. I mean, and it's expensive for the average investor. There are a proliferation of ways now where you can get short S&P 500 exposures. Lots more people have access to futures now than they ever did. You also have lots of levered short ETFs which have nice liquidity exposures.

So what we wanted to do is we wanted to basically say that, hey, our sector exposures are always long. Now, I would say that we have about negative 4%.

notional exposure to the S&P, like to equity beta right now. And so I think, you know, I wouldn't read too much into the fact that we're short, you know, the S&P and we're long the industrials. I think the major thing is that our S&P 500 component is primarily a timing tool. And so what we're trying to do is we're trying to catch inflections up, inflections down. We're trying to catch breakouts. We're trying to catch trends.

all of those types of things. And so today, the way the portfolio is mechanically constructed is that we're saying that, okay, you should have exposure to the S&P 500, but the price gains are probably a little bit too much. So what you end up doing is reducing your net exposure a little bit. That's that. But when it comes to thinking about beating the S&P 500 over long periods of time, basically the

The way to think about it, like you talked about a little bit earlier, is that you have to have multiple layers that do slightly different things, which add up to create a portfolio that has inherent diversification characteristics. And so our S&P 500 program, right, the thing which you're noting, which is short, the S&P 500, over time has a 0% correlation to the S&P. The trades that we do in that program have no correlation to the S&P.

And why is that? It's because it's continuously evaluating whether earnings are rich, earnings are poor, whether prices are up, whether prices are rich, prices are poor, going long and short, near constantly. On the other hand, our sector exposures are basically looking at the cross-section of sectors to say which sectors offer us the best risk-adjusted returns. And then we're scaling those sector exposures by their carry rate.

to give us a consistent long exposure. What that does is it basically creates two parts of the portfolio where you basically have one part which is meant to be a pure alpha sleeve, which trades up and down constantly. And the other part basically gives you a dynamic exposure to S&P 500 beta based on the amount of carry and expected return, but tries to pick the correct assets to be in. I feel like that got a little bit

quantitative, like a little too quantitative there, but does that answer the question? So your model is quite risk off right now. And I should say what I described, it's just for the S&P portfolio. And that is as of May 15th. So next week, if people listen to this and later in May, it could totally change. And people want that they have to be a subscriber, which is we have an affiliate program where people can get discounted access. So

Just walk us through again why your model is risk off because equities are going up and you don't want to be long momentum. Equities are expensive. But is that it? Because there are a lot of times, right, when equities are expensive and it's a good time to be long. Your equities were expensive a year ago and it has been a good time to be long. You could say equities were somewhat expensive even two years ago and it was a very good time to be long. So it's not just about carry, right? Tell us more about the stuff. And I know there is some stuff in your model that is expensive.

You're somewhat of a black box, but just do your best just to describe it. So I think the difference between, let's say, last year and what you have today is basically just a situation of like, how are the earnings going to get a lot better? Right. And for us to have a really, really strong rally and continue a really strong trend, you basically have to have a situation where the earnings get a lot better from here.

And so intuitively, it's pretty straightforward. The idea is that when we look across measures of the business cycle, they're good, getting maybe a little bit better, right? And then when we look across measures of financial conditions, they're also good, but there's a limit on how much further they can tighten, right? Like we can't, you know, credit spreads can't go a lot lower than they have been in recent past. And when you add up that picture, you basically have an environment where, yeah, like equities are probably better

okay, right, as a medium term asset to own. But locally, they're just a little bit rich relative to other assets and fundamentals. So I think the main thing is like if you want to own equities here, you're really looking at a situation where you need some sort of catalyst in the form of economic data, macro data or whatnot to

to basically justify your exposure. And when we look across the macro data, we haven't seen any acceleration. The last time I was on with you, we had a 2.5-ish percent GDP forecast. We're at 2.3. Now, like, there's no...

material information in the shift from 2.5 to 2.3. There's no material information on that. We basically just think that the economy is at the same place and equity markets have brought forward so much expected return. It just makes sense to take some bets off the table, reevaluate, take some time. And maybe if the economic data, all the macro data really accelerates over the next three months and nobody cares about any tariffs and does CEO confidence go to the moon and we have a new credit cycle,

then we probably get more bullish. But at this point in time, it just doesn't seem like there's a lot of fuel for a further rally. And how many pieces of data go into your model? I assume it's hundreds. Is it thousands? And also, how do you weight? Like, oh, the price of copper, maybe the copper to gold ratio, CEO confidence, various soft data that's negative and people make a huge stink about, but actually maybe the soft data doesn't matter at all because it's no correlation to the actual data. How do you do this sort of weighting? Yeah.

Yeah. So across our programs, we use close to a thousand inputs and, you know, it, the way you weight it is depending on like what you're trying to predict. Right. And so if you're trying to predict, if you're trying to predict S&P 500 prices, you have to

This might be a little complex, but the way you have to weight it is based on the nature of the return stream that you're trying to predict. So if you're trying to predict S&P 500 prices, what you have to recognize is most of the variance doesn't actually come from carry. It actually comes from the mean reversion and the trend factors. But if you are talking about, say, a bond,

almost 50% of the variation over time comes from just carry factors. So like if I can, you know, a lot of times you don't even need to forecast carry. We do some amount of work with forecasting carry because there's some adjustments that you can make. But

Well, it varies by what you're trying to forecast. So like if I'm trying to forecast GDP data, I wouldn't use a copper to gold ratio ever, right? Because there's no way that the copper to gold ratio actually fits into the GDP forecast. But what I would do is I would say, okay, like what's the most timely indication I can get of GDP? Maybe a really good predictor is initial claims, okay? Like how much

how much of the initial claims actually goes into total jobs data, how much of the total jobs data do I think impacts GDP growth. And so it's a case by case weighting. I would never just

I think that just taking an average across a bunch of things is easy, but it's not going to yield the best results. So how we weight things is always going to be conditional upon two things, like the effect it has on the target variable that we're trying to forecast, and then how much signal a particular thing is generating. So for example, today carries a non-signal. It's a non-signal. It's not telling you to be short US assets at large.

It's not telling you to be long assets at large. It's just telling you that, hey, like there used to be a very nice kind of headwind for owning, sorry, a very nice tailwind for owning U.S. assets. But today that is non-existent. So what would be my weighting on that? Almost nothing.

And so what are the things that make much more sense? It's the business cycle indicators that tell you whether trend, domain, revolution, and things like that are going to work well. And Ahan, another step in your process is the treasury overlay. Talk to us about that. What are the various signals there, as well as what's your current view on bonds now with the cash rate at 4.3%, the 10-year at 10.5%, which...

or I would have thought the 10-year would have been lower, i.e. bond prices higher given the amount of uncertainty. And also, if tariffs are not going to be inflationary, but disinflationary perhaps in slow growth, I mean, even you think it'll slow growth just way less than a lot of mainstream economists think, then yeah, I would have thought the bond yield would be a bit lower, but it's at 4.5%. How are you thinking about bonds?

So bonds are definitely an integral part of like portfolio construction, right? And the way we think about bonds like in this particular context is you have to think about it as a residual after you determine how much conviction you have in your equities, right? That's the specifics of this type of program. So what we do is we basically come up with, what do we think about equities? Do we want to own a lot? Do we not want to own a lot? And then we go to bonds. And then we say, okay, like are bonds attractive to own right now or not?

I think the big difference between what we do and what a lot of people do is they just say, hey, whatever cash I have left over, maybe I can own a little bit more in bonds. We don't think that that's the optimal approach. We think that you do own excess returns over cash for owning bonds. But what is really attractive in bonds is basically to try to say, when are bonds going to be most attractive? And so when are bonds most attractive? Bonds are basically...

assets that benefit from really, really weak growth conditions, which result in cutting cycles. Those are the best outcomes for bonds. And so what you really want to do with bonds is you want to be there when a cutting cycle starts and the cutting cycle is more than what's priced in. And that's a really, really integral part of the process and any process in general. When we're looking at that kind of today,

you already have a bunch of cuts priced in. So we have about four interest rate cuts priced in over the next 18 months or so, I think. And

That is pretty inconsistent with what we're telling you in terms of our expectations for growth and inflation. So without any very, very material change in economic activity, like maybe if our original tariff estimates where they actually did the liberation day tariff levels actually came to fruition, then okay, then we would be much more in line with, okay, there need to be eight interest rate cuts priced into the forward curve. But today we don't have any of those conditions.

And so without a very, very material kind of weakening of the economy, it doesn't really make sense to just own the bonds by itself. Another reason why you just can't own the bonds by themselves is because the level of carry that you have is just not

enough or adequate compensation for the amount of risk because you could very well have a situation where economic activity is a little bit harder. And so as a result, you would fade all of the cuts that are priced into bond markets today. And that would basically be a really, really bad outcome. So when we look at bonds, what we want to do is we basically right now, bonds for us have become like

What I've been saying often is that bonds are for trading, they're not for investing. And so whenever we think that bond markets have gone too far in either direction, where they've priced in too many cuts or they've priced in almost no cuts, those are times where bonds are a little bit attractive. So you can imagine a situation where we go from pricing four to eight cuts. We would be probably more likely to short bonds in those types of environments.

If in the environment that we actually went to zero cuts, or maybe we went to a few hikes, we would be more likely to say that, oh, you know, it's more likely that we have some cuts priced. So I think that basically what it comes down to with bonds is that they have a lot of structural challenges in this kind of macro backdrop. A lot of that has to do with the fact that there has been just tremendous amounts of bond supply over time. And that bond supply is

has basically created a richening of bonds over maybe the last few years, which has basically created an environment where you continually have these pricing of discount of policy rate card expectations. And bonds, I think, if we have a growth downturn, which we don't think we have right now, they will be really, really attractive. But unless we have that kind of outcome, you basically want to be trading around your bond positions a lot, not holding them indefinitely. Stig Brodersen

And bonds would have to have a much higher carry in order for you to be bullish on them. You've got this great chart of, I think it was in the month of April, showing what happened to yields. And actually, I mean, you could just see the steepening on that chart that the 10-year yield is now much higher relative to the 2-year or the cash rate than it was at the beginning. So carry is starting to emerge, but it's not close enough for you to get viewing them as investing instruments rather than trading instruments.

Yeah, exactly. Like if you're getting a few basis points of carry, you know, you are much better off. The way to think about it is like I could own, you know, a three month bill and with no volatility, or I could own a 10 or 30 year asset with, you know, some, you know, close to 10, 15, 20% volatility. What is the incremental return I get for that volatility? Five basis points or 10 basis points, you know?

It only starts to become attractive once you have a much steeper yield curve. And those steepening, so I think something that, you know, a lot of people don't always recognize is that the steepening of the yield curve is almost entirely driven by whether

the Fed cuts policy rates or not. So the yield curve is its steepest when the Fed is actually cutting policy rates. And so you get the double whammy. You basically get policy rates coming down and your carry is super attractive. And so as a result, you basically, those are the best times that you actually want to be invested in bonds. And when we look at bonds today, it's just, that's not the set of conditions that you have.

So for subscribers to your non-institutional product with people can get discounted access to, it's three things, right? It's the S&P model. It's the total return model, which stocks, bonds, commodities. We'll talk about commodities in a second. And then it's the think piece that comes out roughly once a week. So for example, one of the think pieces was on tariffs and it's

It's discretionary to you with what you share with your non-industrial clients, but it's one a week. And it's funny, one of the few discretionary things about you is that. So is it three pieces a week? Do I have that right? Is that what people would be signing up for? Yeah, about three pieces a week. And we also offer a really like a slow asset allocation program, which allocates between stocks and stocks, bonds and commodities once a month. You know, we know that a lot of people can't trade every week.

And we just wanted to have something simple, durable for them to be able to manage. So we have an asset allocation piece that comes out once a month. And talk about who your type of clients are. Obviously, your model focuses on beating the S&P, hopefully in an absolute way, but also in a risk-adjusted return way.

And your back test is quite impressive. And in a risk-adjusted way, if you don't beat the S&P, but you beat it in a risk-adjusted way, that basically means that you could have used that strategy to lever up and just keep on levering it up until you beat the S&P. So it's quite obvious to me, Ahan, how your institutional clients who are

Hodge shops, for example, they take that and they put the signals in and they make all of these uncorrelated bets, hopefully uncorrelated bets, and put that there. But in terms of a non-institutional client, how can people use this? Is it purely for people who are looking to minimize their volatility?

Or are there potentially other people who could be interested in this? Yeah, so that's definitely a part of what we do. So the baseline we want to start with is we want to start with something that a relatively conservative investor, and everyone has the definition of what conservative is, but our programs have basically a 15% maximum drawdown baked into all of them. We have

We have quantitative ways of basically figuring out what our expected drawdown is, and we just never let that drawdown exceed 15%. Now, the nice feature about something like that is that if you are just like, 15% means nothing to me. I'm happy to take a 45% drawdown, and I want to maximize my gross return.

Our portfolios are perfectly scalable in that way. Like if you're interested in a 15% return, or sorry, a 30% drawdown, you can just scale up our portfolios 2x. And so what we always have-

Yeah, we have, you know, very, very clear risk measures that we send to everyone, you know, along with kind of the, these are the positions we tell you, this is the expected volatility, this is our expected drawdown. And you can tailor that to your circumstance. You know, we have some people that are retirees, they want to take 5% drawdowns, you know. And so we try to keep it so that the program is scalable to whoever wants to use it. There is no

invest this is the way to do investing it's all about you if you're you know 27 you should be able to take a lot more risk than if you're 77 and but maybe if you're 77 you're like charlie munger you're like oh i i only own costco and berkshire hathaway and that's that's you i mean i'm definitely someone who in my own personal investing you know everything is informed by macro macro but i really focus a lot on the micro and i'm just thinking okay i really like this one stock and i i

I'm quite confident in it. And if it goes down, I'll just buy more. Because I'm in that favor. So I'm playing difficult in the market. Obviously, some of your clients who are managing tens of billions of dollars, they can't expect inflows all the time. And sometimes they have to prepare about outflows. For example, Harvard, if they own some private equity, they may have to go into the bond market to borrow money so that they don't have to sell their position. So everyone's different. But I think, yeah, it's not...

The conservative investor who wants to minimize the drought on it is an obvious fit. And I'll say like a lot of products try and do this. And I do think that, you know, you are the best that I've encountered and in terms of quantitative macro. And, you know, there's two levels of being, you know, of kind of what I respect of, you know, there's,

I have to have, I think you're good enough to like be on the show, but then I think there's have to be good enough to do an affiliate deal where I'm, you know, basically bringing a deal to, to my audience and, and talking about the diversities of the product. And, you know, I, people can rest assured that I have a high standard for it. You may disagree, but just, just know that I, you know, I,

I'm not going to do these things with people who I don't think are good or even who I don't think are very good. So it's an obvious fit for those conservative people. But even if you're much less conservative, just multiply by 1.5 or multiply by two. Or if you're someone who likes to invest in individual stocks, I think it's still super relevant. I'm saying, oh, I'm feeling like I'm just going to buy a ton of this stock that I really, really like. Whoa, I just got Ahan's research note. Oh, he's feeling a little cautious. Oh,

Oh, that's a little interesting. And even if I don't even use your signal, your signal is going to point me in a direction that is going to help you find useful. So I think that there's a wide array of people who your product is useful to. I know most of your clients are institutional. And this is kind of, I guess, an early foray into bringing it to a non-institutional

institutional audience. I think a lot of people listening may find this interesting. Click the link in the description to learn more and you do get a discount for both an annual as well as a monthly. And if you buy an annual subscription, it's

It's a 25% discount relative to the cost of the monthly. Did I miss anything, Ahan? I appreciate you saying all that, Jack. I mean, you know, I've loved watching the growth of your various shows and, you know, it's been really great to kind of see you grow your own business over here. And like, I'm really happy to be on. So I...

I appreciate it. Just know the respect is definitely mutual. I will say with regards to conservative versus non-conservative, I think the only standard there is for all investors is everyone has, you're totally right, there is no right way to invest. But I think the only thing that we can say for certain is that the right thing to do is not to maximize absolute returns. It's to maximize your risk-adjusted return

And then scale the risk however you think is appropriate. So what we want to do, our job is to bring you the risk-adjusted return that we think is appropriate and put it in a package that we think the most number of people can use it. With regards to other people that don't, we work with institutions, like you say, really, really big hedge funds,

And there is no hedge fund that we work with that I have ever tried to pitch or would ever even consider pitching to that just use our process. We think that if you're an active investor doing this, that, and whatnot,

we can offer a diversified kind of return stream, which is pretty different from what other people are doing. That's what hedge funds use us for. If you're just a solo investor kind of doing this by yourself, you can definitely fall back on using JustUs, right? That's definitely an option.

I would just say that, you know, you have to understand that you are not going to, there is no version of the world where you don't run 25 strategies and you can expect to generate, you know, hedge fund like returns. What we're trying to do is we're trying to bring you something that's responsible, reasonable, and, you know,

results in probably like the higher upper quartiles of active investor performance. You know, you can think of a shop ratio between 0.7 and 1. That's what we're trying to bring investors. If that's something that's attractive to you, this is, you know, if that entire package of things is something that's attractive to you, then the product kind of makes sense. Otherwise, there are lots of other people that are seeking, you know, very different objectives that are probably better off, that better suit it.

So you said seeking a Sharpe ratio of 0.7 to 1. I believe that's higher than the long-term Sharpe ratio of the S&P, which is risk-adjusted returns. However, there can be months or even years where the Sharpe ratio of the S&P is very high. I think the Sharpe ratio of the S&P over the past few years has been upper twos or even threes. You're not promising manna from heaven or elixir. You're trying to beat the market in a risk-adjusted way over a long-term time horizon. And

You know, I mean, if the stock market is crushing it by definition, by doing risk management, that's going to underperform in an absolute way, even if you outperform in a risk adjusted way. But I guess you just have to lever that, right?

Yeah. And it just depends with what you can sleep at night with. So I think, you know, I don't, I don't usually, you know, like talking about backtests because, you know, we have to put a heavy discount on backtests and whatnot, but I think it's just informative. The way we've structured our programs, like I've described, we always want to have a maximum 15% drawdown. We don't want to do more than a 15% drawdown because what we found, like whether it's institutions, talking to RIAs, we're talking to individuals, the second you hit like this 15% drawdown, like, you know, things start to get a little bit shaky with your ability to stick with a strategy.

And we constructed our strategy is not to have more than a 15% drawdown. So what that means is basically you need to constantly account for the risk that, hey, like markets can crash pretty badly. Now, over the last decade, you've basically had something that's relatively unique relative to the rest of history where markets have crashed, right? So we've had about three 20% corrections over the last decade.

All of them have been resolved in less than six months, right? Or within six months. And so that type of crash is pretty anomalous. And, you know, equity markets have had a volatility close to 20% over the last decade, but they've also managed to recover really quickly. So anyone that, you know, I think this has been the ire of most professional investors, which is that, oh man, like I deliver a good shop ratio, but, you know, the equity market just continues to power ahead.

What we say to people that are really worried about something like that is two things. We can generate returns that are consistent with the long-term expected return of equities with a max 15% drawdown. If you are super, super concerned about just matching the S&P over time, our systems on average have a greater than 25% allocation of cash. If we just drop our risk controls, which basically means we're fully invested all the time,

Over every...

time horizon that we've tested our strategies, our strategies actually outperformed the S&P 500. That's not a promise to do that in the future. It's just to basically recognize that the reason that you may have lagged the S&P over the last decade is probably for being responsible, not for any other reason. And if you are the type of investor that doesn't care about having a prospective 40% drawdown, then it's just easy to reduce your cash,

And potentially even lever up strategies and get those results still. Yes. And I feel highly confident that most serious investors will find value in this product. I think there's some people who listen to macro podcasts who they may think they're looking for alpha or value, but they really want a guy who's writing a newsletter about how gold is going to go to $10,000 or $100,000 because of the Fed's balance sheet or something. And

there's not as much alpha, maybe there's negative alpha in those types of products. And that's not what you do. You're the apotheosis, the exact opposite of that. I feel confident saying that you can bring quantitative macro alpha. So if that is what people are interested in, they should check the link in the description. Aha, now let's get on to some serious business. How are you thinking about commodities? I know your model is overweight commodities. Why

Why at this very volatile, uncertain time would you be overweight commodities? So for a little while, we didn't have much exposure to commodities. But I think one of the things that we talked about is that within the investment complex, so in gross domestic investment, you've actually had an upturn in industrial activity.

And so commodities are basically just a function of what is happening with industrial activity over time. Those two things are very industrial activity and more broadly goods demand in the economy. And so those two things are very, very tightly related over time. And so what we're seeing in the economy today, part of it is a little bit of tariff front running. But also what we've seen is that

Manufacturers, who are the primary demand source of commodities, have begun to experience slightly better profit conditions than they have in recent past. Part of that has to do with the onset of a modest onset of a cutting cycle. Part of that has to do with the fact that they actually laid off quite a bit of employees without creating a really, really big calamitous event in the economy.

And so manufacturers today have a little bit more of a positive profit dynamic, which is actually allowing them to invest a little bit more, which is allowing them to produce a little bit more output. And we see that as basically a situation where commodities, which have begun to kind of ride upwards in terms of their trends a little bit, are actually well supported by economic dynamics. Now, the thing is, like I said at the top, we don't know how much of that

is just attributable to tariff front running versus organic growth. It's very, very hard to discern that. But what we're seeing from the data is a pretty broad-based improvement from a negative condition in the goods economy. And so that improvement in negative condition in the goods economy basically makes us a little bit more positive commodities. And so...

Do we think that position is something that we're going to hold for a very long period of time? I honestly am not very sure. I think that if we continue to have the kind of investment trends that we're seeing in the industrial complex today, then yeah, we probably do expect commodities to do a little bit better relative to other asset classes. But again, there's a lot of noise and data today, so we'll have to see. But that's overall kind of the commodity view.

Overall, over the past few months, you're saying that the industrial data has actually been quite positive. Tell us about that, because I know there was at least a few weeks where the Federal Reserve surveys, Empire, the Philly, whatever, were exceptionally negative in at least some manufacturing indices. But maybe those were, I don't know if this is not the overall index, to be honest, I don't remember, or just demand, but it was looking quite negative on at least some data points.

But then also you can speak to the macro fact that there's always going to be, of the 10,000 pieces of data, there's always going to be data that looks remarkably good. And there's always going to be data that looks remarkably bad. Like I remember reading a book, like during the Great Depression, Herbert Hoover was like cherry picking data that was good. And in the Great Depression, like that existed. And even in a strong economy, there is bad data that recessionistas who just always will see a recession can cherry pick.

So just speak to that. But in particular, there was some quite negative factor data, right? And then what was the odds of industrial data that you're putting greater weight on? So I think the readings that have been pretty negative are basically...

Survey-based data, right? And survey-based data has a very, very tight relationship with what's happening in the market. So things like ISM, things like the various regional surveys and reasonable PMIs are generally correlated over long periods, so like a year or something like that. If the equity market is up, you can bet that regional surveys, PMIs are all up.

Now, what we look at is what we try to do to gauge what's happening with manufacturing is we look across manufacturing sales for various industries, and then we estimate their cost, both in terms of their employment and then in terms of their interest burden, to basically come at a very rough estimate of what the principal component of profits is, basically. And when we looked at that, what we basically have started to see is

So we've started to see a little bit of improvement in industrial equipment sales, and we've also begun to see a good amount of motor vehicle sales kind of passing through from manufacturers. At the same time, as I described earlier, what we've had is a situation where the durable goods manufacturing economy was suffering for quite a while, for almost a year.

And what we've begun to see is that the layoffs that that industry had engaged in have allowed them to basically perform adequate cost cutting to basically bring their profit levels back to basically neutral growth.

And, you know, is the manufacturing economy booming and, you know, really, really surging? No. But what it does look a lot like is it looks like a situation where manufacturing conditions are basically back at neutral. And that could be the start of, you know, a very good environment. It could be just something where we stay basically flat. But what we see is basically an improvement from a contraction, not a big boom in the manufacturing sector. And it's the level of layoffs that's

are sufficiently low to not put it in a recession. It's a level that allows your so-called right-sizing rather than, I mean, in a recession, everyone tries to right-size, but if everyone does it once, we know that that causes a recession, but you're not seeing that. And also just speak to your view of the overall labor market.

Yeah, yeah, yeah. The overall labor market, if you look at where recessions come from, they come from two sectors. They come from manufacturing and they come from construction. How that happens is you basically have some bad events happen in maybe in the construction sector, they fire a bunch of people. There's so much firing in the construction and manufacturing sectors, it basically sinks the ship for everyone else. That's how a recession typically transpires.

But what's changed over the last few decades is that the manufacturing economy and manufacturing employment is just like not a very big part of the economy anymore. So what they've managed to do is they basically, so far, you know, you don't know how these things are always going to transpire. But so far, what they've managed to do is they managed to thread the needle, which, you know, maybe six months ago, I actually didn't expect them to be able to thread the needle like this, where they've been able to do what you've described as right sizing, where they've reduced their labor force. They've managed to retain their nominal sales.

And they've also got the benefit of being able to refinance at maybe modestly lower interest rates than previously. And so the combination of those things has created a nice kind of backdrop where they can start to recover their profitability a little bit. And at the same time, what may be in the 60s, 80s, maybe even the 90s would have been

definitely recessionary in that, you know, if you fired a bunch of people in the manufacturing sector, it would have turned into a recession for the whole economy. We've basically not had any kind of metastasizing of that firing at all. Yeah, I think that your description of it as the right sizing so far is spot on. Yeah, so the U.S. employs

close to 13 million people in manufacturing. In the 80s, it was 20 million. Now, there are 18 million people who work in healthcare, whereas in the 1980s, it was like 5 million. Honestly, the chart doesn't even go back that

But yeah, there's a huge, huge, huge percentage of people in the labor market who are working in healthcare. And a large percentage of the job gains have actually been in healthcare. Honestly, I'm just seeing, as we record in the middle of May again, what's going on with UnitedHealthcare and maybe the biggest healthcare company in America and perhaps the world.

is being accused of fraud and the stock has been cut in half over the past month, it is possible that that could have macroeconomic consequences. Yeah, and we would see that in the data. I think the real areas of concern today

when it comes to employment data broadly is actually the government data. So the place where we've actually started to see a little bit of slowing and pretty consistent, we started to see openings fall. We started to see the unemployment levels rise is actually in the government data. We do see some amount of weakness also in kind of private sector service jobs, mostly around temporary health and temporary help and related kind of services. But when you look at it,

The things that typically cause a recession and a big meltdown, those sectors, which are basically just two of them, which are manufacturing and construction, those broadly look just fine. Construction in particular, despite not very, very good volumes happening in the construction sector in terms of output, the construction employment has really, really remained pretty robust. And I think the big picture kind of takeaway on the labor market is, yeah, there are some pockets of weakness.

The only way for us to get a recession out of the labor market is to have a new type of recession. Like it's not going to be, if we're going to have a recession today, it would have to be a situation where, you know, information and technology workers are just fired in mass, you know, or government employees get fired in mass because currently the dynamics that are in manufacturing and construction are just like entirely inconsistent with any type of recession we have on record. A lot of the employment over the past four or 45 years has

A lot of the growth in the new employment has been in the government sector. That's definitely a criticism of the previous administration that people make. Speak to just how significant are the potential losses you see from Doge? I know there's a lot of headlines of these massive layoffs. Have you seen that in the

in the data and do you expect to? I think I might not have been super clear on the way I described that, but basically the government data that I was referring to is actually the government jobs data. So like the data on the actual jobs in the government sector. And so that area in total employment data, we don't see a weakening yet. So if you go and look at non-farm payrolls and you look at the government contribution to non-farm payrolls,

That's not weakening. But you do see that the biggest area, jobs growth can come from two places. It can either come from unemployment falling or the labor force rising. Right. And today, basically what you have is a situation where we've not. And those two things are always contributing over time pretty consistently. But the big cyclical variations that come in jobs data is usually from unemployment data.

So what's begun to happen so far is that job openings for job openings and also the unemployment data has started to indicate that government hiring is weakening. And

So far, it's not big enough to actually sink the ship when it comes to total employment in government jobs. But it's something to note because it is definitely one of the weaker areas in the economy in terms of hiring now. And yeah, like we're seeing some effects of Doge, it looks like. If it continues, it could be meaningful. But

I'll say, I'm not sure I'm the best person to ask what the impacts of Doge are. It just isn't consistent with what we do on a day-to-day basis. But at this current rate, it would kind of open us to a weaker labor market, which could see influences from other places and expose us, create a window of weakness. Already, Ahaan, you referenced earnings expectation is a big driver of the S&P 10%.

Tell us how you measure earnings expectations. I mean, there is the earnings expectations that the big banks reports and that goes into an aggregate index, I suppose. But often that's like quite negative looking in the state. Oh, wow, the market just crashed 50%. Surprise, surprise. The earnings expectations went down like after. But the first thing you see is the stock market went down usually. And also how have...

I haven't tracked, to be honest. How has the blue chip, big bank earnings expectations for the S&P, earnings growth expectations, which they've been, how have they changed over the past few months? I mean, the past liberation month. And how has your earnings expectations changed? And what speaks to that delta and how that informs your views? Yeah.

Yeah, that's a great question because we do look at earnings expectations a little bit differently from the way everyone else does. So I think that most of, at least on the discretionary side, most people that look at earnings expectations, basically they grow and grab what, you know, maybe Bloomberg consensus expectations for earnings, or maybe they go grab all the big banks projections and say, okay, they are forecasting X, Y, and Z for EBIT revenue EPS over the next 12 months. Compare that to today.

and say, okay, that price is, you know, the difference between those two is 12%. Consensus earnings expectations is for earnings to rise 12%. And that's fine. It's intuitive and it's helpful to contextualize things. But when you try and apply that over time,

What you'll find is that that measure is basically always positive and is always basically north of 8%. There is very little informational value in the fact that companies are telling analysts that report on the companies that their earnings are going to be up. There's no valuable information in that. What there is valuable information in, according to us, is to take those types of earnings estimates and say,

How are those earnings estimates changing over time? So I can compare today's earnings estimates to yesterday's or maybe a year ago. And what we found is that the changes in those earnings expectations are extremely correlated to what's happening to the economy. And so why are analysts taking their expectations up? They're taking those expectations up because the reporting from the companies and macro conditions are improving, which is improving their outlook.

And of course, they take a lot of signal as well from what's happening in equity prices. And so what we try to do is we try to say, can we predict how earnings expectations are going to change? So are earnings expectations tomorrow going to be a little bit less than they were today and the year previous?

rather than our earnings expectations, right? Like in terms of a level. So we try to focus on the changes rather than the level. That's one. So what do we think drive those changes? We think that the biggest drivers are twofold. There's a combination of financial conditions, which is just a mix of financial assets, which is stocks, bonds, and credit.

When I say financial conditions, that's what I mean. We think that a combination of financial conditions plus a combination of an ensemble of business cycle indicators give you a reliable and very, very modestly leading assessment of which way earnings expectations are likely to go. Because if you think about it on a company by company basis, both the companies themselves and the analysts reporting on the companies are basically synthesizing this information.

Right. Then they're doing it in their own discussion anyway. And they do it. You know, there are a lot of people doing at the same time, which denoises each one's estimate, which actually ends up percolating. So all we're trying to say is, can we do this a little bit faster than them? And what we found is that putting together that type of measure gives you a very kind of timely read on where we're at.

The reason that we think that equities aren't super attractive today is because that measure that we put together into how earnings expectations are going to change is just telling us that there isn't much change likely to happen. And so as a result, we don't think earnings expectations are going to change very dramatically, which means that the earnings expectations

If earnings expectations don't change very dramatically, it also means the future earnings equities are also not going to change very dramatically. And before earnings season in very early April, late March, people were saying, oh, with all these tariff stuff, companies are going to be pulling guidance and or lowering guidance or even pulling guidance. You saw that with some airlines, the first ones to first companies to report. And it seemed like that prediction would come true. But I don't know if that prediction really came true throughout throughout earnings season. Just can you summarize briefly what you saw in earnings season?

And, you know, what I love about you as well as your most quants is you're not going to focus on one individual company that could be very interesting, but not representative. You're going to speak up of the whole thing. You know, like what did you see during during that time? Yeah, perhaps the way I'll describe it will not be necessarily consistent with, you know, the way people describe it, which is, you know, oh, yeah, we saw a lot of companies re-rating lower or whatever. You know, like that's just not how we look at things. We look at things the kind of the way I described it.

And what we saw is entirely consistent with the framework that I described, which is equity markets absolutely got crushed. And credit markets barely responded. Bond markets did respond quite a bit. Surveys were down a lot, but none of the business cycle data actually responded much. And so when you synthesize all of those things into a single measure, what we saw is that, yeah, like earnings expectations need to come down a bit. Do they need to fall off a cliff?

No. And so when we put that together, we said, okay, like these earnings expectations numbers are probably going to come down. And over the course of earnings season, yeah, like they came down a little bit, right? And as equity markets basically began to rally once again, we thought,

oh, you know, maybe this was a lot of lustre about nothing, which is basically what's ended up happening with earnings across the board. So when we look at like, you know, our measures versus S&P 500, you know, index aggregated earnings expectations measures, they've, you know, our measures indicate, okay, they're going to fall a little bit and then they're going to bounce a little bit. You average the average kind of the noise that comes in and you basically get, oh yeah, they're down a little bit. And that's basically what we saw over the earnings season.

And on something I noticed, and it's going to sound like I'm poking a hole in your model, but I'm really not, is that you said, okay,

Earnings expectations respond to financial conditions. Financial conditions, stocks, bonds, and the credit market, but mainly risk assets, stocks and credit, mainly stocks. You're trying to predict the stock market by looking at earnings expectations. Your model of earnings expectations focused on financial conditions, which includes stocks. There's kind of a...

a recursive, you know, so the snake eating his own tail here thing. And also, is it just really trend following? Does everything come down to trend following? Because if the stock market goes up, that earnings expectations will go up and that will cause the further, you know, is that really just trend following? Yeah. I mean, so like I described, right? Like you want to have a lot of trend following, like you want to have a healthy and good amount of trend following, right? And why? So I think the important thing is like,

It would be concerning if the only indicator that I talked to you about was the stock prices informing the earnings and the earnings informing the stock prices. That would be the concerning thing. What ends up giving us a lot more information is to basically say, hey, what if we add up all of these things, right? And say, is the combination of these things indicative of a good trend?

Right. So when would I want to be most aggressively long equities? I would want to be most aggressively long equities where I have a combination of these things. I have my business cycle indicators telling me that the economy is good. Equity markets telling me that the economy is good. Bond markets also telling me the economy is good and credit telling me that the economy is good.

At the same time, I want to have earnings expectations lagging that measure. So I want to have a gap between my measure of where earnings should be and where earnings expectations are, which basically says that there's more gap for future price increases because you're going to have a re-rating of those earnings expectations. So yeah, it is absolutely a trend following measure in some way, right? That's really important.

it's not the only measure you should use like it's definitely not the only measure you should use and in fact like what i'm telling you in terms of like what's what are in the the prometheus program positions are the opposite of that right that we we think that we're more in a mean reversion kind of environment but what you want to do is you want to say that okay we have a trend following measure but we also want to see how much room that trend following measure has to run and yeah like it's

trend following, but denoised trend following. That makes sense. We can go deeper on that if you want to. Let's go a little bit deeper on that. And let's talk about trend following and something you told me on over dinner, and I believe you, is that some of the greatest investment track records in the world, not Warren Buffett, but a lot of the other legendary investors in the world really were built on extraordinary trend following in the 1970s and 1980s,

which did extremely well. Why did trend following go so well then? Does it work less well now? Does it still work at all? And what can be responsible for that? Yeah, so this is definitely true that trend following used to be one of the best strategies if you could do it and you had identified it. But over the last few decades, it's just not

as commercially viable. So if we wind back to the period around the 60s, maybe 70s, all the way up to the 90s, asset price returns were largely predictable based on what happened to them over the last day, week, and month.

There are a lot of reasons for that. Some of it has to do with the fact that we didn't have a lot of computing power, so there weren't people constantly looking at trends all the time. Today, a retail investor can create a trend ensemble by themselves or has access to any number of trend products. The trend ecosystem has grown very, very dramatically. So a lot of it is just the fact that there's

you know, that's been arbitraged out. The other fact is, you know, back in the day, there were a lot more transaction costs, right? So you can imagine there was slower information dissemination and you had a lot more transaction costs. And so as a result, like you couldn't always just jump on a trend. Like you might try to jump on a trend and find out that, you know, the bid ask is like 20% or something like that. And so there were reasons why trend following was really, really attractive. So a lot of track records, and that's not to take, you know,

anything away from any of the great investors. A lot of track records were built basically directly or indirectly on the back of this property where as long as you could figure out what the trends were,

you could basically predict what's going to happen to the future in terms of asset prices. So you can think about, you know, all the really, really big time macro investors that you know, their philosophies are basically consistent with trend following, right? You know, you talk about Soros reflexivity, you talk about self-reinforcing silos that Ray Dalio used to talk about. A lot of quantitative funds too, you know, have diversified

done really, really well on the back of trend following. But as people started to figure it out and as the industry became more competitive, trend following has, I mean, become as close to arbitraged out as it possibly could be. That's not to say that you can't generate some good returns, but

Particularly, you know, in commodity trend market, in commodity markets trend is really, really is not as attractive as it used to be. In equity markets, it's quite the opposite where you've actually had mean reversion become a much stronger force. And so, yeah, like

Can you still apply measures of trend? You should. You should have some. But I think it's just not the solution that it once was. And that's one of the reasons like we've built our process the way we've built it. We understand that there are these long periods of time where like a specific factor like trend or mean reversion even, which like, you know, if you haven't,

surmised by now. I'm a fan of mean reversion, but any one of these factors can basically get crushed for really long periods of time. And so we want to avoid being biased on any one of these factors. And yeah, that's the thing about people's track records being built on trends. So a lot of great track records were built on trend following. And then you also think what's value investing. It's in part mean reversion because, okay, a stock that has a PE of 10 is going to come up to the average price earnings multiple.

And perhaps a stock that has an elevated price earnings muscle might come down. It's also carry because it has a higher earnings yield. And also back in the day, it wasn't just cheaper earnings yield, which is the inverse of low, the exact opposite of low P ratio. Companies had extremely high dividend yields as well. So I learned that from a few of the other clients I talked to. So when I first heard you on, not in this interview, but prior, that you...

you think that it's the Holy Trinity, not your words, but of is trend following mean reversion and carry. I didn't really see what you meant, but I think gradually I am starting to see that. When it comes to the value versus carry thing, right? So first off, those things are pretty synonymous, right? They're synonymous like conceptually, but your implementation makes a world of a difference, okay? If you implement carry as earnings yield, like the simple way I've discussed here today,

Completely different investment results on track record relative to value investing.

Now, you've got to think about the OG, the GOAT, Warren Buffett. You've got to think about the time when they started their value investing thing. I think Ben Graham started investing in the 20s. At that time, earnings yields were close to 30%. That's a 30% carry that you could earn just for owning stocks. This was post the Great Depression.

Yeah, in Great Depression, I believe that. But in the 1920s, I don't know if you had the average P.E. was three. But yeah, in the Great Depression, I believe that for sure. Yeah, yeah. So post Great Depression, you have these massive... So you can think about the fact that like 30% of your earnings at any particular time. So like the value component and the carry component basically said the same thing. But as you move forward in time, right, value and carry begin to deviate quite meaningfully. Why that happens is basically...

Value is roughly an idea about the mean reversion of prices, right? It's a mean reversion of prices to whatever the earnings trend is. That's what value is. Carry, on the other hand, is very different. Carry is basically saying, this is the yield I earn on the asset that is linearly and directly related to my forward return. So if I have a 3% carry, that is what I earn and that's what I bet on.

Value, on the other hand, is very, very model dependent. So you can basically say that, oh yeah, like I have a 25 PE. What does that mean in terms of forward return? It depends on how I fit that model. If I fit it based on the last year's data, if I fit it based on five years data, if I fit it based on 20 years data. And so what value basically does is it says that, okay, prices are going to mean revert

to some historical level of value. And I want to place bets based on that. That is not the same thing as trying to invest in carry. Investing in carry is basically saying that this is quite literally my linear prediction of what my future expected return is going to be. This is what I want to hold. The last thing I want to ask you, it might cause some stir in the quantitative world, in the macro world, but let's talk about it. It is what you term a macro myth.

And that is what people may have heard of. It's called the term premium. I still, to this day on, don't understand the term premium. I can recite to you the definition of it. I'll do so shortly, but I really don't know how it is calculated at all. And that's where you come in. The term premium, people will say it is the reward that you get for holding long duration assets relative to

to cash. So a longer term bond term is time, duration is more volatile. And as such, you need to earn a higher rate of return on that relative to cash. So for a lot of the time, especially in the 1980s, 1990s, term premium was positive, meaning you're getting rewarded for holding duration. Not surprised when the 10 year was at 15% or 8% or even

even 6% relative to the cash rate. But from 2015 to maybe 2022, I don't know, you tell me, a lot of the term premium was negative. And, Ahan, as you know, people, investors, I mean, chief economists at huge firms who I've interviewed talk about the term premium at

as if it's a real thing. And I believe it's a real thing, or I used to before I started talking to you. So are you saying the term premium is fake? Walk us through your thing. And is this a huge misunderstanding within the entire macro world that you think people really aren't seeing things very clearly? So I think, look, I work with some really, really sophisticated bond investors. And so I have a serious appreciation for

the concept of term premium and its rigorous application. But what I think is happening a lot on macro podcasts and in lots of macro strategist research and stuff like that is a bastardization of what

you know, a rigorous implementation of that actually is, you know, just to kind of, you know, to, to, to kind of give you the definition of term premium, a term premium is basically just what is the excess return over on a bond over just rolling a bunch of short term, short, short term notes or short term bills. Right. And that concept is good. It allows you to evaluate whether the bond is attractive relative to the bill or not.

What is not good, right, is the way people are using publicly available measures to quantify this. Why is it not good? So there are maybe two models that are really, really popular, okay?

There's something called the ACM term premium and there's the KW term premium. And what these models basically do is they use, maybe to pick on the most popular one, which is the ACM one, what they do is they basically use measures of the yield curve to infer what interest rate expectations are in a bond. So what they do is they apply a bunch of fancy statistical techniques, but they take the yield curve and say, okay,

What does that mean? What is the yield curve telling me about the expectations for policy rates over the next 10 years? And they basically create an interest rate expectation. The term premium is quite literally just the difference between the 10-year bond and this estimate. Now, what is super important to understand is that that estimate of future interest rate expectations

is about negative 90% correlated to the shape of the yield curve. So your term premium number co-moves exactly almost with the yield curve. You are getting no additional informational value really from the term premium numbers other than some amount of potential modeling error.

So why is this important for people to know, right? There are other factors that you can add in to say these are the long-term expectations of interest rates. So you can add in growth numbers, inflation numbers, inflation expectation surveys, all of that type of stuff. And that's good. I know professional investors that try to do that. You should continue doing that. That's great. But the publicly available measures, KW and ACM, right?

They want design for macro timing. That's not what they're for. They're academic estimates of what term premiums are. And both of those measures are extremely, extremely correlated to shapes in the yield curve. Now, why it's not good to necessarily use those things is because one, the yield curve in itself is actually tradable. And short-term interest rates are actually observable.

you cannot trade the ACM term premium. There is no way for you to possibly use that. And so all you're introducing when you start looking at term premium and saying, this is the fair value of term premium, is one, you're introducing modeling error. And two, you're basically just using the yield curve. And so what I would say to most investors that aren't super sophisticated using very, very complex modeling tools is,

Just use the thing that's adequately, that is readily available, doesn't require extensive modeling and can actually be traded as opposed to something that sounds really fancy to say on a podcast. It is, but Aaron, it is the fanciest thing. I mean, it's a lot. It's just, I hear it all the time. I get questions about it often and it's just something I feel strongly on.

I appreciate your sharing your views. And you know, not everyone, not many people have strong views on term premium and how it's calculated. It's a joy to get you on. People again can find in the description or on YouTube, a link to a discounted access to your research service. So people should really check that out. People can find you on Twitter at Ahan Prometheus. I'm on Twitter at Jack Farley. And

96. And people can leave a rating or review for monetary matters on Apple podcast or Spotify. And also please like and subscribe to the YouTube channel monetary matters network. Your likes don't matter all too much. You're gonna like it or not, but the subscribe that's what really matters. All right. Thanks again, Ahan. Until next time. Thank you. Just close the door.