Dan Rasmussen (02:50):
We would say, for example, that when the high yield spread starts to rise and its 10-year median is about 420 basis points and we’re at about 470 today, so we’d say, “Look, when the high yield spread rises above that 10-year median, you’re in a pretty risky place,” right? When the VIX is this high, when spreads are above their 10-year median, when the S&P and the EFA indices are below they’re moving averages, that’s a risky time, right? Those are times that can see big drawdowns follow. They can also see big recoveries, and I’d say probably are 55% that things recover, about a 45% chance you’ve got this nonlinear downside risk.

Dan Rasmussen (03:24):
So I’d say it’s a very uncertain time, but there’s certainly a lot of downside risk given where most major indices are trading at the moment, but I’d say when you get to a crisis, the unique thing about a crisis is that you really know when you’re in one. You know when you’re in one because the front page of the Wall Street Journal is blaring. Whatever asset classes you’re invested in, probably major fund managers and that asset class are shutting down. We would say another good indicator is when high yield spreads are over about 600 basis points, just about one standard deviation north of the mean, but that’s when there’s real capitulation. We’re not there yet. We’re somewhere in the middle, maybe 60th, 70th percentile, but we’re not in the 90th or 85th or 95th percentile of panic yet.

Trey Lockerbie (04:06):
You brought up the high yield spread, and I want to talk a lot about this because it seems to be a huge indicator for you and your research. I know that you have a very quantitative approach and you do a lot of back testing and have a very data-oriented strategy. I have a lot of questions around this mainly because if I look at the high yield spread, like you said, it’s about 470 today, and I wanted to say, “Okay. What does that mean? Is that relative to what?” Right?

Trey Lockerbie (04:30):
So if I look back 10 years, I’m thinking, “All right. Well, it’s gone as high as 10 so we’re halfway there, I guess. That seems bad,” but then if I look back 20 years, I’ll see it go to 20. It’s depending on whatever time period. It all seems fairly relative. So how do you measure which period to go off, what dataset, what timeframe, that kind of thing?

Dan Rasmussen (04:52):
Yeah. Well, let’s start by talking first about what the high yield spread is and why you should care. The high yield spread measures the difference in the cost that risky borrowers, generally small cap companies or companies that have borrowed too much, pay to borrow relative to the equivalent treasury rate. This is a wonderful indicator for two reasons. One, these are the borrowers on the margin, right? They’re the big borrowers on the margin. So if you think about what the high yield spread rising or falling is telling you, it’s telling you what banks and fixed income participants are thinking about default risk.

Dan Rasmussen (05:25):
So if that spread moves up materially, that means that banks and fixed income investors are saying, “Hey, there’s materially more default risk than there was a month or two ago,” and that’s not a good sign, right? Those people are sophisticated. They’re not thinking about hopes and dreams of the future, right? They’re thinking, “Will I get my money back on this 4% yielding bond?” Right? When that gets repriced, it’s worth looking at because it’s giving you a very clear picture of where those people that are worried about downside risk are pricing that downside risk.

Dan Rasmussen (05:53):
The other reason it’s really useful, and Ben Bernanke did a lot of his doctoral research on this, is that there’s something called the financial accelerator. This is Bernanke’s idea, and the idea is an answer to the question of how small shocks turn into big crises, right? If you’re watching financial markets this year, you’d say, “Well, we’ve had a number of small shocks, right? The fed has started raising interest rates, but they haven’t raised them that much, right?” Russia invaded Ukraine, which is obviously a big deal, but they didn’t invade France or Germany, right? We’re not in a nuclear war, and tech earnings came in slightly worse than we might have hoped. Yet, the market reaction has seemed to be very big. So why does the market sometimes have a big reaction to what seems like small shocks?

Dan Rasmussen (06:37):
What Bernanke says is that the financial accelerator happens when, first, something happens like Russia invades Ukraine or tech earnings coming a little week, and then people in the financial markets reprice risks so the people in the high yield market say, “Gee, maybe we should charge Netflix an extra 100 basis points to borrow or an extra 200 basis points to borrow,” or think about mortgage rates, right? Mortgage rates go up 100 basis points, 200 basis points, right?

Dan Rasmussen (07:02):
Then what happens is that the people that we’re borrowing, those marginal borrowers that might have invested to build a new factory or do a new deal or in the case of the consumer buy a new house or invest in a renovation, they say, “Ah, maybe I should scale back my plans or maybe I should hold off for now until the market clears,” and then the person that was going to build that house or the person that was going to work in that new factory, they don’t get a job or they don’t get a raise, and then they don’t go buy jeans at American Eagle, and then American Eagle stock goes down, and then the value of everyone’s 401(k) goes down, and then people say, “Wow, gee, I used to have 150,000 of savings. Now, I have 120,000. Really, I’m definitely not buying a new car this year.” Then all of a sudden, the auto parts companies go down, right? That’s the financial accelerator. It’s this feedback loop.

Dan Rasmussen (07:47):
That’s why I watched the high yield spread so closely because when the high yield spread starts to rise, as it has of late, it’s a real danger sign, right? The financial accelerator could be happening, right? If spreads continue at this level or widen out further, we’re there, right? We’re at a place where lending is actually constricting the US economy, and we’re there right now, right? Spreads at 470 is not good, right? I mean, that’s not a good market, right? That’s not helpful to businesses. It’s not helpful to the consumer. It’s a sign that the financial accelerator is starting to see some pickup, but when the financial accelerator really blows out and we say 600 is the metric we look at, but 600, if spreads go above 600, they often go much wider. They might go to 850 or 1,000. In 2008-2009 when the market totally froze, they were up over 2,000, but spreads blow through that point, and that’s basically when the market just shuts and everything illiquid gets sold off. Everyone’s panicking. Nobody can get new debt. All of Wall Street shuts down, right? There’s no new deals being done, et cetera. That’s a very, very dire situation.

Dan Rasmussen (08:51):
On the other hand, one that we can analyze discreetly, it’s this unique environment where we say, “Okay. Let’s say high yield spreads are that wide and external financing is essentially shut off from the economy and the financial accelerator is in full swing. What does that mean? What do we do? How do we react?” because those are quite rare and unusual moments.

Trey Lockerbie (09:09):
Now, I want to ask about this, but I do want to go back to the time period because I still am curious about that, but as far as the 600 mark on the high yield spread, some of your latest research was showing that while the number, the nominal number is important as a mile marker, it’s the direction of the spread, either rising or falling, that actually adds value to the strategy. It reminds me a little bit of when I was talking with Brent Johnson recently about the DXY. He said, “As soon as it gets to 97, I get worried,” but it’s actually the rate at which it gets to 97 or the rate it gets to 104, wherever it is now, that is actually more important than the number itself. So can you walk us through why that directional focus adds value to the strategy?

Dan Rasmussen (09:52):
Yeah. So we look at both the absolute level and the direction, right? You can think of our spreads tight, right? So the financial market’s moving, everything’s kind of fine or are they wide where you say, “Gee, the financial market is actually constricting the economy,” right? Generally, we’d say when spreads are tight, you tend to see an environment that’s inflationary, and when spreads are wide, it tends to be deflationary.

Dan Rasmussen (10:14):
One of the calls we would make is, “Hey, spreads are wide enough to be a deflationary force right now,” right? They’re putting downward pressure on inflation, other supply shocks that are competing with that, but broadly, we’d say that the level of the spread is giving you an inflationary or deflationary metric, and it’s also telling you, “Hey, gee, is the economy broadly healthy and working or is the financial accelerator a risk and are we potentially in a crisis?”

Dan Rasmussen (10:39):
Then the direction matters. I think I have a very credit-driven view of the economy, right? I think people buy things on credit. Deals happen because the availability of credit, right? Think of most of the large purchases we make, whether it’s buying a house or if you’re an investor or buying a multi-family apartment building or buying a small private company. You’re going to use debt to do it. In fact, you might fund the majority with debt. So the actual cost of that debt matters. When the price of that changes, it changes the actions of all the participants in the market economy, right? I mean, if mortgage rates go up, people are going to readjust their prices down because they can’t afford as much, and they might even delay purchasing.

Dan Rasmussen (11:17):
However, on the other hand, the spreads are tightening, and people say, “Oh, my gosh! I can get a really cheap mortgage,” or “Mortgages are so much cheaper,” or “The price of debt is so much cheaper. I could really go do a deal that was pretty big right now and get pretty good money to do it.” That’s going to fuel the economy. So we broadly say when spreads are coming in and they’re tightening, that’s a positive thing. It suggests that GDP is growing. Cheaper debt is stimulative.

Dan Rasmussen (11:41):
On the other hand, when spreads are rising and borrowing is getting more expensive, it’s contractionary because there’s just less money to go around. So I think that paying attention about the level and direction is really important. Right now, we’re in this moment where spreads are wide and they’re rising and that’s not a good general scenario for the economy. It’s a very worrisome one on that.

Trey Lockerbie (12:01):
Do you find, I’m just curious because of our level of indebtedness as a country, I mean, you mentioned earlier that the fed has raised rates but not very much, but the counter argument to that would be like, “Well, you have to look at it on a percentage basis,” right? If it’s going from 25 to 50, that’s 100% increase. Well, all this debt out there is financed at the lower percentile and every underwriter has to re-rate that. So I’m curious, are we getting to a place where while the high yield spread has spiked to 10 to 20 in the past, maybe it won’t spike as high because just the incremental amount of increase nowadays will have a greater effect than it did previously?

Dan Rasmussen (12:37):
Yeah. Let’s break that into two questions. First is thinking about rates, right? It’s not everybody’s mind, right? The fed’s starting to raise interest rates, and that seems to be a reason that the market is selling off. So unpacking a little bit, I’d say the first thing from doing a huge amount of quantitative research is that interest rates don’t seem to matter much to asset prices, right? They’re not really that good of a signal, right? Part of the-

Trey Lockerbie (12:56):
Hang on. That’s a big statement.

Dan Rasmussen (12:58):
Let me go a little bit more into why, right? So you’d say, “Okay, gee, interest rate is going up, should put the breaks on the economy,” right? That’s what everyone’s worried about right now. Well, what you typically see is that the fed tends to raise rates when the economy’s doing really well. So the stock market’s doing well and the bond market is doing well and they raised rates and the economy keeps doing well because they said, “Oh, the economy can handle a little bit higher rates. That’s why we’re raising them.”

Dan Rasmussen (13:19):
I think most of the time, if you then back test, raising rates, rising rates tends to be predicting of good economic outcomes, not bad economic outcomes until the end when they raise too much or whatever, right? The same way is true with falling rates, right? People tend to lower rates when the economy’s doing badly. So even though rising rates should be slowing for the economy or contractionary because of when the fed tends to do it, it tends to be during good times, you see very little correlation between interest rates and any asset class in any predictive way. It’s just not all that helpful. Doesn’t even predict the bond market particularly well.

Dan Rasmussen (13:53):
Now, there is one exception to that. So there’s an economist at Stanford, John Taylor, and John Taylor came up with this rule, which just said, “Here’s what the fed reserve rate should be at any given time,” and it’s a little wonky and even I have to go back to the formula every time I look at it because it’s a little confusing, but for the layman, and I group myself in this, not a deep theoretical economist, think of the Taylor rule saying, “Roughly, the federal reserve rate should track nominal GDP.” If nominal GDP is rising, the federal reserve rate should be rising, and it should be call it the nominal GDP rate minus whatever your target nominal GDP rate is.

Dan Rasmussen (14:29):
So if you think GDP should grow 1% a year and inflation should be two, take whatever nominal GDP is and subtract three and that’s roughly where interest rates should be. If John Taylor were listening to this, he’d say that I’d completely butchered it, but it’s good enough for government work. We’ll accept it. What happened is that the Taylor rule rose really sharply at about February-March of last year and the fed didn’t raise rates and it stayed high and the fed didn’t raise rates. The fed didn’t start raising rates until GDP had already started slowing and decelerating. That’s what the market’s upset about, right? They’re saying, “Wait a second. The fed usually raises rates or should raise rates when GDP is growing and now they’re raising rates when GDP is slowing, and that’s not a good thing.”

Dan Rasmussen (15:08):
Actually, historically, when the gap between where the Taylor rule says the reserve rate should be and where the rate is, it gets to this wide, it tends to really foreshadow bad things for the fixed income market in particular because the fed is way behind the curve, they have to raise rates regardless. So they can’t follow their normal good policy of raising rates in good times. They have to start raising rates in a bad time, and that’s what everyone’s really worried about right now, and I think with very good reason.

Dan Rasmussen (15:35):
Now, to answer your question directly, do I really care whether rates are at zero or 0.25 or one or two, right? Not really. It doesn’t back test particularly well. Now, I care roughly where they are relative to where the Taylor rule is because if those get way out of whack, you’re worried.

Dan Rasmussen (15:51):
Then when it comes to the high yield spread, we tend to look at, I’d say, take a 10-year median. That’ll roughly give you where the current cyclically adjusted average would be, and that’s useful for giving you wide or tight, and then just the change is always what the change is, what’s the spread now versus three months ago, and that’s a good indicator.

Dan Rasmussen (16:11):
Then we look at, say, 600 as a level. That’s a little bit arbitrary, but that’s a standard deviation above the long-term median. Generally, when spreads go above 600, I said to my interns, so I had researched this, there’s a Wikipedia page for every time that high yield spreads have gone above 600, right? It’s a major economic event. Now, could you have said 650 or 575? Yes, but as an arbitrary number, that’s a fine one to use.

Trey Lockerbie (16:34):
This is why I was so excited to talk to you because you bring these very contrarian takes that I just want to explore further. So the interest rate to asset prices one, obviously, that’s an effort to debunk something that is so ingrained in what every investor tends to learn from the start. Another thing that investors tend to learn in a similar fashion would be something like the discounted cashflow model. I know that you’ve done some research behind this one as well, and I would love for you to share with us why we might not want to pay so much attention to something like a discount cash flow model.

Dan Rasmussen (17:05):
Yeah. So discounted cash flow model, at its heart, says forecast cashflows into the future and then discount them back to the present based on how risky you think they are. That would be a great idea if you knew what cash flows were going to be in the future and if you knew how risky they were, but the problem is we don’t. If I said, “Hey, Trey. What’s your revenue, your personal? How much money are you going to make in 2027, and then how much are you going to spend in 2027? So what’s your net income? Then what’s your balance sheet? What’s the change from 12/31/2026 to 12/31/2025?” you’d say, “Come on, Dan. You got to be kidding me. How would I know any of those numbers? Maybe I could roughly estimate something, but it’s going to be so far off,” right? I mean, so much could change between now and 2027. It’s impossible.

Dan Rasmussen (17:51):
I’d say, “Well, Trey, you’re the world’s leading expert on you, right? You can talk to every expert on Trey in the world. You can talk to Trey’s banker, Trey’s accountant, Trey’s mom, and get as precise of information over as long of a due diligence period you want, and you’re telling me you’re really not going to be able to nail Trey’s net income balance sheet and cashflow in 2027?”

Dan Rasmussen (18:09):
You’d say, “No. Even after doing all that work, there’s just something about the future that’s mysterious.”

Dan Rasmussen (18:14):
I’d say, “Well, if you can’t do it for yourself when you’re the world’s leading expert on you, how do you think you’re going to do it for Coca-Cola or MasterCard?” I mean, there’s just something that’s a little bit absurd about it. I think, furthermore, I’m thinking about risk, right? Okay. Five years ago, is Microsoft risky? No. Microsoft wasn’t risky at all over the next five years. What about today? Is Microsoft risky over the next five years? I don’t know, right? It’s really big, so probably not, but tech seems to be crashing. So maybe it is, right? I mean, it’s just so hard, right? Discount rate over five years, how risky is a company, I don’t know. We just don’t know, right?

Dan Rasmussen (18:49):
So I think what I worry about the discounted cashflow model, is it theoretically right? Sure, but the problem is that it’s overriding what should be our complete weariness about our ability to predict the future and, I think, acknowledging that we stand behind a veil of ignorance and we look into the future through a glass darkly and that’s about as close as we can get.

Dan Rasmussen (19:10):
I think what I dislike so much about these cashflow models is they replace uncertainty with certainty. They replace rightful caution with some level of informed overconfidence. I think that’s why they’re so dangerous. I think, much more broadly, I think people need to think about different approaches to this that don’t involve this overprecision because I think it’s so dangerous, right? It’s garbage in, garbage out. It’s baking in all these assumptions that tend to be driven by whatever your current biases are at that moment, a lot of trend extrapolation thrown in.

Dan Rasmussen (19:40):
I think often the things that grow the most or that people think are going to grow the most often are the worst performing things in the market because people have gotten too excited about them. So it often leads you in exactly the wrong direction. I think part of my larger campaign is saying, “Gee, we need to have a forecast-free finance or a way of thinking about finance that reduces our reliance on forecasting or is much more precise in how we do forecasting that we’re not relying on these silly models that don’t work.”

Trey Lockerbie (20:09):
So this doesn’t seem to be causation in my mind, but going back to your earlier comment about us being more based on credit. So Richard Duncan, an economist we’ve had on the show, he would say that we’re no longer in capitalism, we’re in creditism. So it’s very similar, I think, to your point. Credit and liquidity are driving the asset performance. If we’re not counting on earnings and discounting them to the future, is something like the fed tightening, have a higher weight in our decision making than a company’s earnings nowadays?

Dan Rasmussen (20:36):
Yeah. I think it’s a really interesting question. I mean, so if you think about what moves market prices, and Robert Shiller came up with this idea in 1980 and he said, “Look, one of the problems is if you take the S&P 500 and you take its earnings for all of history, and then you take what discounts rates have been over time, and you compare the line of what the price of the S&P should have been at any given time with what the S&P actually was at any given time, what you find is that the actual S&P is about 20x more volatile than the theoretical right answer for the S&P, right?

Dan Rasmussen (21:11):
So what is explaining this excess volatility, right? Why do markets move so much, right? Why are markets moving up one and a half and down one and a half every day, right? I mean, it’s not that the underlying cash flows are changing or that the discount rates are changing or certainly not at that magnitude or at that precision. So what is changing?

Dan Rasmussen (21:30):
There’s a Stanford economist, Mordecai Kurz, who came up with this, I think, really elegant and brilliant idea, which is he said, “Well, at any given time, we can all look at the past, and based on the past, we can come up with a different competing view of what might happen that is impossible to disprove, but that fits the historical facts,” right?

Dan Rasmussen (21:48):
So for example, today, someone could say, “Well, buying the dip in tech has worked for the last 10 years, and tech companies are strong and growing so we should buy the dip and look at how well they’ve done.”

Dan Rasmussen (22:00):
Someone else could say, “Well, really what we’re looking at in 2022 is a history rhyming what happened in 1999, 2000, 2001.” Both are citing historical facts. Both have a very plausible, well-thought out view. It just happens that their forecast are dramatically directionally completely opposite to each other, but we don’t know who’s right yet.

Dan Rasmussen (22:21):
So what Kurz says is that there’s no accurate forecast today of the future. There are multiple potentially accurate forecasts, and what creates all the volatility is when the future unfolds in a large percentage of people were wrong and then they have to readjust to a new set of historical data and fit their forecast in a new way, but because there will always be divergent forecasts of what is going to happen, there will always be this excess volatility in markets.

Dan Rasmussen (22:47):
So I think when we look at markets and say, “Well, gee, things are so volatile. Should we really be focusing on cashflows? Should we really be focusing on interest rates?” what you have to remember is that cash flows and interest rates, even if you knew them, would only explain one-twentieth of the volatility of the market, anyway. So I think you have to look at and start to say, “Okay. Well, what do we need to understand about the market to try to price in a little bit more of that volatility or try to explain a little bit more of that volatility? Is there anything that we can use?”

Dan Rasmussen (23:15):
I’d say there are short-term tools that you can use, right. I think you can broadly say, “Gee, when markets are trending down or trending up, there’s some short-term forecast embedded in that that’s useful.” I think you can look at high yield credit spreads, which are much better source of discount rate, much better tool to use for doing discount rates than the actual fed reserve rate because they’re much more volatile and provide much more real information about the economy.

Dan Rasmussen (23:39):
So I think you’re moving in the right direction, but even updating for those better models or you look at GMO or others who say, “Look at the CAPE ratio or market valuations,” and maybe those explain something, but these things, again, none of them really explain all that much, right? You’re moving a little bit and you’re just left with this huge portion that’s just explainable by randomness or excess volatility or something that’s really, really hard to explain, but I think is based on the fact that we can’t predict the future.

Dan Rasmussen (24:03):
So I think what you want to do is pair back to or try to be humble about that and say, “What can we know with more confidence and less confidence?” Try to look for the things that feel more like rocks than sand. That’s what led me to studying crisis investing because I said, “Look, we never know we’re in a bubble. So let’s try shorting everything that’s in a bubble whenever it’s in a bubble.” Horrible strategy because how do you define in retrospect what was a bubble? When do you start shorting it? It’s an impossible problem to solve. Generally, you’re not going to get anything meaningful that works, but if you said, “Hey, let’s isolate periods of time when markets were panicking, and then just look at those periods.” We 100% know the market’s panicking at those times. No one’s going to disagree and say, “Markets weren’t panicking in 2009. That was a bubble,” right? It was obviously not a bubble, right? Obviously, markets were panicking. You’d get no disagreement.

Dan Rasmussen (24:50):
The next time markets are panicking, everyone’s going to agree with you, they’re panicking, too. So it’s something that you can rely on. I’d say what’s really interesting about looking at crises, and there’s been some really interesting academic work, is that all of the academic quantitative factors that Fama and French and others have been developing for years, all seem to work much better during crises. So you have this enhanced predictability in the middle of a crisis. If you think about why that’s the case, to some extent, it’s because you know the forecast that’s embedded in the market, right? Most other times you don’t. Again, I think there’s a lot of people that are very bullish right now. There’s a lot of people that are very bearish right now. There are people that think tech is about to blow up even more, and there are other people that think this is time to buy the dip, but when there’s a crisis, you know that everybody’s panicking, right? Everybody’s liquidating, right? You have a little bit more conviction than about what the market’s going to do over the next 12 months or 24 months, and that’s, I think, what makes it so fun to think about crises in isolation.

Trey Lockerbie (25:46):
Let’s talk about another elegant framework. The one I’m talking about is the four-quadrant approach. So I first came across this through Ray Dalio in one of his books and I’ve seen it something similar in your research as wealth, and it’s applied to multiple things, even the high yield spread. For those who are not familiar, walk us through the four quadrants. You focus on meaning high inflation, low inflation, growing GDP, lower GDP, and which one of those quadrants you think fits the market most today because what you’re saying to me, it sounds like, we’re right in the middle of the crosshair. It’s really hard to say.

Dan Rasmussen (26:19):
Ray Dalio came up with this idea or Bridgewater came up with this idea that you can think of the world in a four-quadrant matrix based on growth and inflation, right? Growth is either rising or falling. Inflation is either rising or slowing. Then you can connect where you are in that four-quadrant grid with how asset prices do. I think one of the underlying insights there is that most asset classes have multiple drivers. For example, with bonds, there is a growth bet and an inflation bet embedded within each bond, right? So if you think of a treasury, the treasury nominal rate, you could almost break down nominal rates into a real GDP component and inflation expectation component. So yields will go up when inflation expectations go up and yields will go up when growth rates go up, right?

Dan Rasmussen (27:06):
So your bet on bonds, if you’re long bonds, you’re betting that growth and inflation will go down or at least that growth will go down more than inflation goes up or that inflation will go down more than growth goes up, but you’re broadly betting against growth and against inflation. On the other hand with equities, equities are really a growth bet more than they are in inflation bet, right? So with equities, you’re really betting on growth, and the smaller the company that you buy, the bigger the bet is on growth.

Dan Rasmussen (27:35):
There are other asset classes that have these linkages between growth and inflation. Take commodities, right? Some commodities, say oil and copper, are very growth-dependent, so they do really well when growth is rising, and they’re also inflation hedges. So they work best when growth is rising and inflation is rising. On the other hand, think of oil, right? Is an oil an inflation hedge? Yes, but inflation’s also driven by global demand. So if global demand is slowing, that’s offsetting the inflation hedge aspect of it.

Dan Rasmussen (28:05):
So you say, “Okay. Well, what do I want to buy when growth is slowing and inflation is high?” Historically, gold has been better because gold is both an inflation hedge and growth doesn’t matter. It’s not like people are using gold to drive their cars. Maybe they will in the future, but not yet. I think starting with that matrix and saying, “Gee, how are different asset classes linked to growth and inflation? What implicit bet am I taking and how is that bet correlated or not correlated?” so that you can come up and say, “Gee, are bonds and stocks inversely correlated?” and you say, “Yeah, absent inflation, they have the opposite linkage to growth,” but you add an inflation and that could screw it up. So if inflation rates are high, your negative correlation between stocks and bonds isn’t going to hold. It’s helping to inform and structure your view about multi-asset or cross-asset class correlations and relationships.

Dan Rasmussen (28:52):
Then what the challenge is, though, is to say, “Okay. Well, what is growth and inflation today? How do I understand where we are in that four quadrants? I get retrospectively that if I looked at periods when growth and inflation were both bound, that bonds probably did well, and indeed, they did, and that’s very statistically significant, but I don’t know now. Is growth slowing or increasing? Is GDP growing or is it falling?”

Dan Rasmussen (29:15):
A place like Bridgewater might have 20 years of now casting models that they’ve built to forecast every individual time series across every country, but for someone who’s just trying to get the big, broad strokes of it, I think the high yield spread provides a really good indicator, right? As I said, when high yield spreads are wide, it tends to be deflationary, and when spreads are tight, it tends to be inflationary. When spreads are falling, tends to be rising growth environments, and when they’re rising, it tends to be falling growth environments.

Dan Rasmussen (29:40):
So you can use the high yield spread to put you into those quadrants really quickly without having ton all the now casting work that some fancy macro firm might have done. So if you said, “Okay. Well, where are we roughly now?” I’d say, “Well, spreads are above their 10-year median. They’re 470. 10-year median is about 420. So I’d say that’s deflationary.” Again, it’s a controversial call, but that’s what spreads are telling us, right? Spreads are telling us that the credit markets are going to act as a deflationary force. That’s probably going to overwhelm supply shocks.

Dan Rasmussen (30:07):
Second, spreads are rising, and that means growth is slowing and spreads have been rising, by the way, since about November. I’d say the Q1 negative GDP print or at least at GDP print, that was also materially below Q4 of 2021. It was right in line with what the spreads were telling you starting in November, that things were slowing, that credit markets are tightening. I think that those would put us pretty squarely in this quadrant four, which we call it where you have falling inflation and falling growth, which is also the quadrant where you see recessions, right? That’s characteristic of recessions, and that’s one of the reasons why our indicators are at least are pretty perished or telling us something that’s pretty worrisome because things could get worse from here.

Dan Rasmussen (30:47):
Now, about 55% of the time they don’t and things get better, but 45% is a big number, and spreads, I think if you look at 30% plus drops in the S&P 500, every single 30% drop in the S&P 500 has come after. High yield spreads went above 420. We’re in this period where there’s a lot of downside risk because we’re in the period that normally is typical of recessions as defined by the high yield spread. So again, doesn’t mean we’re in a recession. We’re not in one yet, but the chances that we’re going to go into one are materially higher than they are normally.

Trey Lockerbie (31:20):
It’s a great point. I mean, when I look at the data, I was talking to Peter Mallouk, actually, about this. He brought this up where I think the average correction for the S&P 500 is around 14%. I think today or as of yesterday, we were at basically 15%, I think. So we’re right at that threshold of, “Hey, does it going to bounce from here or are we rolling over from here?” This is what makes it so hard.

Trey Lockerbie (31:41):
So to your point earlier, the interpretation of data can be somewhat subjective. It’s in the eye of the beholder, if you will. Given you have this quantitative approach, which I definitely understand the merit of, I just struggle with how to limit confirmation bias. As you said, garbage in, garbage out. It seems sometimes too easy to cherry pick data based on timelines or to see what you want to see, especially when you’re back testing.

Trey Lockerbie (32:06):
So you often hear something, such and such performed X amount during ’89 to 2004, and you’re like, “Why did you choose those dates?” and they’re seemingly arbitrary just to get a point across. So I’m curious. How do you manage data while also solving for confirmation bias?

Dan Rasmussen (32:21):
I’d say first off, it’s not like we have enough data to know much conclusively about the US economy. I mean, how long have we had a robust equity market? How long have we had a modern economy? How long have we had a fixed income market? I mean, the data sources are so … The amount of data we have is not a big enough sample to tell you anything with the degree of confidence that you’d need to know for physics or something, right? It’s just you’re working with imperfect, incomplete data and trying to figure out the best way forward.

Dan Rasmussen (32:52):
I think that’s what leads to this challenge, which is that you can look at some period or you can pick the indicator or pick the period to tell whatever the hell story it is that you want to tell or whatever historical analogy you want to make. You could say, “Wow, look at how much our market looks like the Japan in the 1980s,” right? Are you using data? You’re just making an argument. You’re making an argument with data, which is often even more dangerous, but the argument is what preceded the use of the data, right? You wanted to find another period that looked like a bubble, and you found Japan in the ’80s and now you’re happy.

Dan Rasmussen (33:21):
So I think when we’re designing models or trying to develop frameworks for thinking, which I think what we’re all trying to do, we all have frameworks for thinking, whether we know what our frameworks are or not, but we try to be open about them because everybody has a framework, right? Everybody’s matching the current data. They see against some framework in their head that it translate what they’re seeing into action.

Dan Rasmussen (33:41):
What I think what quantitative investors are trying to do is make that framework explicit. I think in making that framework explicit, you then have to just say, “Well, how do you make that framework reliable or how do you know whether it’s reliable?” I’d say one way you test that it’s reliable is you say, “Let’s take the biggest dataset we can possibly come up with and throw it at the framework and see roughly is the framework telling us something useful, and then let’s look at it, let’s run a bunch of statistical tests,” right? I’ve got an indicator that could either be a one or a zero. If I look at 100% of the time it’s been a one and 100% of the time it’s been a zero, how often do those two datasets overlap? That’s called a confidence interval where you could use a logic regression, and you’re going to say, “Well, how confident are we that based on this indicator being a one or a zero that I’m really going to see something different in the data I’m trying to predict?”

Dan Rasmussen (34:29):
So you want to go through all of these tools and all through those processes and you end up finding, I think, a set of simple things at the end of that, right? So you find a huge amount of things that don’t work, right? Again, I’ve run every single regression you could possibly think of of every major asset class against interest rates, and I’ll tell you the level and direction of the interest rates really doesn’t predict anything. It’s just really hard to make that dataset tell you anything useful.

Dan Rasmussen (34:49):
As a framework, it’s just not a very good one. It’s great for journalists because journalists would prefer to cover politics than markets, and the fed is as close to politics as you can get. So if you’re working at the Wall Street Journal or something, it’s a lot more fun to write about these politicians, “What’s Powell thinking?” than trying to figure out what the heck’s going on with markets. It’s just always inscrutable and too volatile.

Dan Rasmussen (35:08):
I think you come to these much more simple things like the high yield spread, right? Credit spreads are a really powerful indicator across a variety of asset classes. They predict commodity markets. They predict fixed income markets. They predict equity markets, right? Well, level matters and the change matters. I think there are other things that are really significant like simple trend rules, right? When a market falls below its 200-day moving average, that trend really is telling you something. I think there’s some markets that trend more than others like the Nasdaq trends more than the S&P 500 value, but there’s something really meaningful in that data.

Dan Rasmussen (35:42):
So I think of our search as quantitative investors is to go through the process of trying to make our frameworks explicit, test our frameworks, and then find the simplicity of the things that seem to really matter and that are likely, therefore, to be robust because the more you complexify your model, the more likely you’re going to be tricked, and the more likely that you’re layering in your own subjective biases against what should be a relatively objective decision.

Dan Rasmussen (36:07):
So I’m sitting here saying, “Gee, spreads are high and rising,” and so that’s telling me we’re in a recessionary territory and I should be really defensive. Then I go and open up my Bloomberg screen and everything’s green and I say, “Oh, my God, maybe my model’s wrong. Maybe there’s an exception in the model that when it’s the 27th day of the month, that it’s should be bullish.” You can find some data to find something that’s going to tell you something different from a rough model, but the rough model might just be 60% accurate and that’s as good as you’re ever going to get. I think that’s probably the way a lot of these models work, explicit frameworks, well-defined, well-tested produced results that are right at best 60% of the time, and you have to be okay with settling for that. Otherwise, you’re just going back to random subjectivity.

Trey Lockerbie (36:52):
I appreciate that because let’s talk about one more exception. Another example would be, say, March 2020, where the market declined 30% and there was no prospect for an economic recovery insight. There was a lot of fear, I think, than most fear I’ve seen in my lifetime. The fed injected $3 trillion of liquidity into this market, which hasn’t happened before in history, and all of a sudden, the market bounces back and it’s right at new all time highs within a couple of months. The high yield spread went to 10, 10 and a half. So we’re well into crisis territory, but then yet, growth stocks like Amazon performed best. You would think in the crisis territory, things like small caps would do well or value comes back, the cyclical rotation, but we saw growth actually perform in that scenario. So what are some ways to diversify safe? We’re largely focused on small cap, which I think you are, then how do we protect against those outlier events where it might be in almost black swan?

Dan Rasmussen (37:50):
Yeah. So if you think about March 2020 and you said, “Okay. What was a sign that the crisis was moving into recovery?” I would say, “What happened to the high yield spread?” High yield spread started dropping a March 23rd, right? You had a pretty clear signal coming from the spread that you were switching from a recessionary period into the recovery period early, really early, right? It started swinging on March 23rd. Now, we’d say, “Gee, you probably want three months of data or something,” right? So let’s call it. You’re getting into May now, right? You just say, “Okay. Starting in May of 2020, I started to be really bullish,” and I did. I was bullish in on March 20th and 23rd, but I was also bullish in May because when I looked at where spreads were, I said, “Gee, spreads over 600. That’s a really good crisis indicator. What’s likely to work out of these crises?”

Dan Rasmussen (38:35):
I’d spent two years studying every crisis since 1970. I published this massive study of crisis investing. I called it in January of 2020, and then COVID hit. So it was this realtime chance to say, “Gee, was I just subjectively assembling random time periods that Trey would say, ‘Well, gee, Dan, that was just a subjective amalgamation of random time periods that confirmed your underlying thesis or was there any actual external validity to it that we can test by actually betting on it in March or April or May of 2020?'”

Dan Rasmussen (39:02):
What you saw happen during COVID is actually textbook what happens in a crisis. So liquidity froze up. What sold off worse? Well, what sold off worse was the less liquid things, so small cap, micro cap sold off, right? Mid cap sold off more than large caps. Small cap sold off more than mid cap, and micro cap sold off more than small cap.

Dan Rasmussen (39:21):
If you look then 12 months later, which did the best one? Micro cap did better than small cap, which did better than midcap, which did better than large cap. This is normal, right? When spreads go really wide, I like to think about it as the tide going out on a beach, and small or micro caps are the top part of the beach where the tide only touches once a day, and large caps are the deep part of the ocean where it’s six feet deep at high tide and three feet deep at low tide, right? When liquidity flows out of markets, when the tide leaves the beach, the micro and small caps, you get absolutely hammered, right? The percentage reduction in water is huge versus the deeper part of the beach, where the percentage of reduction of water is much smaller. Same thing happened in fixed income markets. The things that sold off worse were high yield bonds, and think of BDCs or loans sold off even worse, and then when markets returned, when liquidity flowed back in, it was the exact reversal.

Dan Rasmussen (40:09):
Now, the other thing that worked really well was value, actually. So if you went and bought value stocks two or three months after spreads went wide, the value factor worked remarkably well over the subsequent year or two, right? Look at someone like AQR and Cliff Asness or me or anyone else that was betting on value. You got so burned coming into 2020, but ever since March 2020, everybody on the value side’s been very happy that the value factor’s been working again, and that’s also somewhat predictable.

Dan Rasmussen (40:38):
If you think about why a value matters in the time of crisis, it’s because most value stocks tend to be cyclical and GDP-linked. So when people panic about GDP, they sell value stocks, and then conversely, the only time an auto parts manufacturer grows faster than Amazon is in the 12 to 24 months following a recession where their profits rebound and their revenues rebound, et cetera.

Dan Rasmussen (41:01):
Now, tech is really the exception this time because tech was a beneficiary of the recession. There’s a beneficiary of COVID, right? People switched their consumption from physical to digital. So even though the rest of the economy was in recession, tech was actually benefiting. That continued, I think, really in an interesting way. You’d had the 2010s was a period defined by technology stocks where technology stocks were the things that worked. It worked the best and it worked the best because their corporate earnings grew a lot. Corporate earnings grew a lot, their multiples increased, and by 2019, 2020, I think, there were a lot of people saying, “Hey, we’re in some sort of tech bubble. This is insane.”

Dan Rasmussen (41:40):
Then COVID happened and, holy smokes, their revenue and profits doubled again and their multiples doubled again. So tech had just an unbelievable year. At the time when probably anyone that was looking at the valuation numbers thought they were due for a horrible year. Now, I think what you’re seeing happen is this hangover, where you saw a big pull forward, right? People talked about this big pull forward or acceleration of digital growth that people are switching into digital goods or digital services faster. They’re accelerating five years of growth or 10 years of growth into one.

Dan Rasmussen (42:09):
Well, what happens in year two of that, right? Well, obviously, growth slows or maybe even growth declines, and look at Peloton being the prime example of this or Netflix. When there was no other option but to be at home and watch Netflix and chill, that’s what you did, but when you could go out to a movie theater or go for a bike ride or something, you may not do quite as much Netflix. So that’s changing right now and that’s also changing at a time when value has started to work.

Dan Rasmussen (42:32):
So we’re at this very interesting juncture in markets where you’ve had this tech boom slash bubble and you had COVID crisis, which rescued or not just rescued, but took tech from success to super success, and then COVID and the recovery from COVID really rescued the value factor and small caps in a big way. Now, you’re seeing what I would argue is this hangover from COVID where the tech stocks are seeing this massive deceleration and coinciding with that, a big drop in their multiples because people are less optimistic. On the other hand, you have small and value and international and all these things that have been out of favor for so long showing some degree of relative outperformance.

Trey Lockerbie (43:13):
Let’s talk about some other ways to diversify. When you’re using a small cap value approach, let’s say, how does that translate from the US’s to other markets like in Europe or just other international markets? How do you think about investing outside of the US as part of your diversification?

Dan Rasmussen (43:29):
Yeah, small cap value. If you think about value first, value is as a factor is one of the most replicated findings you can find. You can test value across markets, across geography, across time, and generally buying cheaper stuff that people are pessimistic about tends to work better than buying things at expensive prices that everyone’s optimistic about. I think if you think about why that’s the case, it’s the systematic expectation errors that we’re talking about, right? Everybody has different forecasts. Those forecasts tend to be wrong. So it turns out that buying things where everyone’s very confidently pessimistic, you tend to just do better over the time because things on average turned out to be as bad and those forecasts tend to be wrong.

Dan Rasmussen (44:10):
Whereas if you systematically bought the things that everyone’s excited about, you’re going to be wrong just as often, but when you’re wrong, the outcome’s going to be much worse because things just aren’t going to be as good as you hope for.

Dan Rasmussen (44:20):
So value tends to replicate really well across markets. So you can do value in EM. You can do value in Japan. You can do value in Europe. You can do value in the US. Now, there’s a lot of dispute about size, right? Why does small cap matter? Why do people talk about small cap value? Why is that important? I think there’s two elements to small caps. One is that there are many more small caps than large caps. So if you’re looking for I want to see every value stock in a market, there might be 400 small cap value stocks and 50 large cap value stocks.

Dan Rasmussen (44:51):
So any extreme then you choose and I said, “Well, I want to show not just the cheap stuff, but the really cheap stuff,” well, there might be 200 small caps and five large caps in that bucket, and of the 200, a fairly large percentage of those might be tiny, tiny little things.

Dan Rasmussen (45:05):
Now, that’s why I like to talk about small cap value because small cap value is the extreme of the factor. So if you want to bet on value as, say, Fama and French define it, what you’re really buying is the extreme of value, and the extreme of value is very disproportionately smaller micro caps. Now, the negatives of small and micro cap stocks and that intersection of small and micro cap with value is that small and micro caps are much more volatile than large caps. So there’s a big draw down. Small caps will almost always be worse.

Dan Rasmussen (45:34):
Second, there is some element of which bankruptcy rates are materially higher for small companies than big companies. So you are actually getting more risk. So that volatility is telling you something that’s actually true in the case of small caps, but over time, that’s where the biggest part of the premium has been. So that’s why I am an extremist. I mean, I like the extreme of things. It’s just more interesting, and you get something that’s more meaningfully diversifying, and if you’re not an extreme, why not just own the index, anyway?

Dan Rasmussen (46:00):
So if you think about small cap value, which is the extreme of the value factor, it’s the cheapest stocks across the markets, again, it tends to work really well across most major markets. Now, I have a soft spot for Japan. I love Japanese small cap value in particular, and probably most excited about Japanese small cap value, and that’s largely because Japan is this, first, it’s a really big small cap market. Second, Japan is super cheap. Third, we talked a little bit about bankruptcy. There’s actually almost no bankruptcy in Japan. So the normal risk that coincides with small caps in other markets is much less present in Japan than anywhere else.

Trey Lockerbie (46:36):
That’s fascinating. I always think of this quote from Warren Buffett. Brent Beshore told me this when he was having dinner with Buffett, who was drilling Buffett with, “You say all these folksy things that are so simplified, but really, what is it really?” I guess Warren put his fist down and he was like, “Price is my due diligence,” and I just love that quote. I mean, sometimes things are cheap for a reason. So for example, you mentioned an exception earlier. I’m going to bring up another one. When things are cheap or when we’re in a recessionary period and companies get strapped, you might look at things like distressed debt or something, and thinking that gets super cheap in periods of high uncertainty, but why is this maybe not the case?

Dan Rasmussen (47:16):
Yeah. So I think that things are cheap for a reason sometimes. I think, actually, if you look on a one year forward basis, cheap stocks tend to have worse revenue growth and worse earnings growth and expensive stocks. So in some sense, the market is right. They’re saying, “Hey, these are the less good companies,” but what’s also true is if you fast forward a year and you look at the multiples, the stuff people were excited about that did grow better, their multiples come down and the cheap stuff that didn’t grow as much, their multiples go up. If you think of what’s embedded in the multiples of forecast of the future, really, what’s happening is that the market is so pricing in the near term, right? They’re saying, “In the near term, this company’s on the decline,” and then they’re extrapolating that’ll be true next year, but turns out that life changes, right?

Dan Rasmussen (48:06):
Like that example we had earlier of what’s your balance sheet going to be in 2027. Who knows? People get too over confident, but the part of it is that they do have real data about next year or there’s some level of trend or short-term forecasting that actually works, and the market’s pretty good at sussing that out. They’re just really not good at sussing out what happens a year later, which is why value stocks tend to mean revert and grow stocks and mean revert down.

Dan Rasmussen (48:29):
So I think with bankruptcy, in particular, which is the big exception, bankruptcy risk is not compensated. So going and buying things that look like they’re going to go bankrupt, you’re just going to end up with a lot of bankrupt things. It’s not a good value strategy, which is why most people that do value investing, especially small cap value investing say, and you’ll hear almost anyone in this space talk about the importance of some level of quality screen, where you have to screen out the stuff that actually is about to go bankrupt. The guy that made this famous was this guy, Joseph Piotroski, who’s another professor at Stanford, who has basically developed a pretty simple quantitative way of defining quality in a way that is quantitatively meaningful, but I think that’s where you really don’t just buy the small cheap stuff, buy the small cheap stuff that’s not going bankrupt. That’s a really good strategy. Buying the small cheap stuff is still pretty good, but buying the small cheap stuff that’s not going bankrupt is even better.

Dan Rasmussen (49:22):
Now, those are all things that are true over the long term. I think we can’t go on too long talking about small cap value as a small cap and value investor without saying, “FYI, everything I just talked about didn’t work for a pretty long period, culminating in a really horrible period from 2018 to 2020.” So I think these are truths that are true over very long periods of time and they’re very logical. They make sense, but we did live through a period where the exact opposite worked and the everything I just told you, buy cheap, buy small, buy quality just basically led you down a horrible, horrible road for two or three years.

Dan Rasmussen (49:56):
I think now that it’s all coming back, and so we’re all feeling vindicated and great, and I can go on your podcast and tell you this stuff is true and it works, but I think it’s important to know that it doesn’t always work and there can be periods when it works really horribly, and that’s part of, I think, having a system or having a systematic approach or making your framework explicit is that if you’re honest, almost any framework about how the world works is wrong sometimes for years, sometimes for months, sometimes a period where it really just matters, but I think the advantage of a framework is you keep repeating it, and if you’re right 60% of the time and you’re right 60% of the time reliably over the course of your life, you can end up with very, very positive outcomes.

Trey Lockerbie (50:36):
That consistency is key. I was curious about that, actually, because these strategies do underperform for periods of time. I wonder, I mean, obviously, I know the answer, but it’s so tempting to create this Swiss army knife approach where you’re like, “Okay. We’re in this quadrant, so therefore, this is my strategy.” So the last 10 years, for example, you could have easily become a momentum trader. You probably would’ve done really great, but post-crisis, as we may be entering into, that dynamic changed pretty quickly and momentum doesn’t work anymore. So if you know that and you know you’re in a certain quadrant, do you shift gears at all? It sounds like from what you’re saying, it’s better to stay rigid and systematic and just take your human biases, well, your human, I would say, overriding capability off the table.

Dan Rasmussen (51:24):
I think maybe, in my view, the process that I try to go through is, What is my human bias telling me? What am I thinking?” You’ve been in markets, I’ve been in markets. I come up with an idea. I’m like, “Okay. Well, gee, I want to go buy oil stocks right now,” and then I think, “Why do I want to go buy oil stocks?” and you’re like, “Well, because they’ve been going up a lot and everything else has been going down.” Then you go back and you say, “Okay. Well, is that logic good? What if I just bought the best performing sector and held it for three months?” I ranked every sector, bought the best performing sector and held for three months. Would that have been a good strategy? You find, “Yeah, it’s okay, actually. It’s not the worst strategy in the world. You’re basically getting this thing called trend following and trend following kind of works. So it’s not the worst strategy, but let’s be explicit about why you’re doing it.

Dan Rasmussen (52:09):
So if energy doesn’t work for the next three months and it’s trending down, you should probably sell it because the whole reason you bought it was because it had been doing well. Three months from now and it’s doing really horribly and real estate stocks are doing really well or whatever, to be consistent, you’d go and buy real estate stock. Your idea of going to buy energy stocks was really an idea about buying things that have been doing well, and that idea of buying things well can be systematized, and then you can do that consistently.

Dan Rasmussen (52:35):
I think that’s the process that I like. It’s just making your subconscious frameworks or your individual decision, you’re broadening it out and saying, “Why am I making this individual decision? What’s motivating? Would that work as a universal rule?” and you’re trying to avoid the more idiosyncratic elements of investing, which could drive you to sell all your stocks in March 2020 and then go buy Zoom stock a month later and then sell that a year later when it stops doing well.

Trey Lockerbie (53:00):
So going back to your contrarian take earlier about interest rates not really driving asset performance, I’m certainly curious if you have another contrarian take on bonds because it’s now, with rates rising, it’s now actually a good time to invest in bonds, and if so, why?

Dan Rasmussen (53:16):
So I think there’s a big pro and a big con. The big pro, like why you’d want to own bonds right now is because it’s where credit spreads are. Typically, when credit spreads get this wide, it’s telling you something bad about both growth and about inflation. If both growth and inflation are going to come in meaningfully lower than people think, well, in fixed income, especially treasuries are going to do really well because treasuries are a bet that growth is going to be worse than expectations and inflation’s going to be worse than expectations. So credit spreads are telling us growth and inflation are going to be worse than expectations. So that’s telling you a great time to go by treasuries.

Dan Rasmussen (53:51):
On the other hand, the Taylor rule versus where the reserve rate is is one of the widest we’ve ever seen, right? So we’ve only been really two big periods of time when the gap between the Taylor rule and the reserve rate were where they are, and that was the early 2000s and the ’70s, and both of those periods were just atrocious for fixed income, right?

Dan Rasmussen (54:11):
So you’d say, “Well, gee, when the Taylor rules is this wide, fixed income’s atrocious because the fed has to raise rates and they probably are going to raise rates more than they should or need to,” but when they do that, they’re also going to start at some point. They’re doing that in order to bring inflation down, and usually, growth is collateral damage. So at some point, the fed raises rates enough that it causes the economy to go into a recession and then bonds work. You could say maybe it’s a matter of timing, right? The Taylor rule is really wide. So at some point, bonds will work, but do they need to peak out? Does the 10-year yield need to peak out at 300 or does it need to peak out at 400? I don’t know.

Dan Rasmussen (54:47):
So I’d say at some point, if things continue trending worse, if spreads keep rising, if growth and inflation keep falling, now is already the time to buy bonds. Perhaps if things trend, maybe the worst you could say is maybe we should start buying bonds or lengthening duration a few weeks from now or a few months from now. On the other hand, we could have a soft landing and the fed could come in and we could be just way too early, right? The 10-year yield might need to top at 500 or 600, and you could be in for continued horrible pain in the bond market.

Dan Rasmussen (55:19):
Now, balancing those two, I’d say I rely more on spreads because there’s so many examples, right? You can look at the spread where high yield spreads were every month from now and back to 1950. Whereas these periods where the Taylor rule is really wide are so isolated and rare that you’re making a very idiosyncratic special argument about how now is different. I think unbalanced, I’m pretty pro bonds. I’m certainly more pro-bonds than most people, but I was also, I think, have to acknowledge that this is a time when there’s a higher risk that that’s wrong than usual.

Trey Lockerbie (55:54):
All right. So as we’re nearing the last month of Q2, what’s the over, under, on if we’re actually in a recession?

Dan Rasmussen (56:02):
I don’t know. I think I’d say there’s a 45% chance we are, but yeah, isn’t that a horrible answer? I’m really going out on a limb.

Trey Lockerbie (56:10):
I love it. Well, hey, Dan, we’ll circle back. I mean, I have to now. We have to have you back on and review this. This is such an interesting inflection point in time. This great experiment, this great monetary experiment we’re in, I’m really eager to see how it’s playing out in the next few months. So I really enjoyed this. I find your takes and your research very refreshing and always a great counterpoint to a lot of other things I read. I highly encourage everyone to go check out your work. Before I let you go, I want to give you the opportunity to hand off to the audience where they can find that research and more about you and your fund and any other resources you want to share.

Dan Rasmussen (56:43):
Great. I write a weekly research piece, which I try to be controversial and interesting and data-driven. You can find that on our website, www.verdadcap.com, on my Twitter, @VerdadCap, and you can subscribe to that mailing list. We publish every Monday morning. I think if you enjoyed this conversation, you’ll love our weekly research dives.

Trey Lockerbie (57:03):
Dan, thank you so much. Let’s do it again.

Dan Rasmussen (57:05):
Thank you, Trey.

Trey Lockerbie (57:07):
All right, everybody. That’s all we had for you today. If you’re loving the show, don’t forget to follow us on your favorite podcast app. If you’re ready to start learning how to invest, be sure to check out the resources we have for you at theinvestorspodcast.com or just Google TIP finance. Lastly, you can always reach out with feedback. You can find me on Twitter, @TreyLockerbie. With that, we’ll see you again next time.

Outro (57:26):
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