We Study Billionaires - The Investor’s Podcast Network - TIP455: Indicators for Crisis Investing w/ Dan Rasmussen

Starting point is 00:00:00 You're listening to TIP. On today's episode, we have Dan Rasmussen, the founder and portfolio manager of Verdad, which also releases research that I highly recommend you check out. For example, they have a high conviction around using the high yield spread to determine the current macro environment we're entering into, which we discuss in depth. Verdad also focuses on investing through crises and emphasizes a small cap investing approach, and we discuss why. In this episode, you will learn how to use the high yield spread as an indicator and why

Starting point is 00:00:28 it works, what levels indicate a crisis, why you should reconsider using a discounted cash flow model, how to mitigate confirmation bias while using a quantitative approach, Verdad's four quadrant framework, and a whole lot more. I really enjoy speaking with Dan. He's highly intelligent and very thoughtful with his responses. I hope you enjoy it, so here's my conversation with Dan Rasmussen. You are listening to The Investors Podcast, where we study the financial markets and read the books that influence self-made billionaires the most. We keep you informed and prepared for the unexpected. Welcome to The Investors Podcast. I'm your host, Trey Lockerbie, and I'm so excited to have on the show today, Mr. Dan Rasmussen, welcome to the show. Thanks for having me, Andre.

Starting point is 00:01:23 Well, I'm saying I'm excited because I've been loving this research you've been putting out, and you have this focus on investing through crises, which seems very topical at the moment. It might be topical or might not. That's always the problem with investing. Maybe by the time this goes out, we'll be in the middle of a crisis, or maybe Netflix and Tesla will be up 40 percent and we'll be laughing at the people that thought it might be a crisis. We're going to explore exactly that today.

Starting point is 00:01:47 So as investors, we're often taught that you can't time the market. It's a fool's errand, right? Your research is suggesting that you can time the market while a crisis is occurring or maybe has just occurred. The market has been slipping downward for a number of reasons. high inflation, hawkish Fed actions like rising interest rates, tightening, etc. Are these indications of a crisis? And if not, what are the indicators? So I'd say, first of all, it's always much harder to call when you're in a bubble, where the market top is, whether we're heading into a

Starting point is 00:02:21 crisis. I mean, we really don't know. I mean, this could be the end of 2018, where you have a one month freak out and then everything recovers or it could be the beginning of 2000 date. And we really won't know until the future comes. I will say, and those who have done work on trend following will know that when the market starts to go down, sometimes continues to go down a lot more. So you can buy low and avoid selling at the, you know, you can avoid the depths of these crises by trying to use rules like trend following. 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-hield spread rises above that 10-year medium, you're in a pretty risky place, right?

Starting point is 00:03:04 When the VIX is this high, when spreads are above their 10-year medium, when the S&P and the IFA indices are below their moving averages, you know, that's a risky time, right? Those are times that can see big drawdowns follow. They can also see big recover. And I'd say probably are 55% that things recover, but a 45% chance you've got this non-linear downside risk. 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,

Starting point is 00:03:44 probably major fund managers in that asset class are shutting down. And we would say another good indicators when high yield spreads are over about 600 basis points, which is about one standard deviation or the mean. But that's when there's real capitulation. We're not there yet. We're somewhere in the middle, maybe 60th, 70th, 70th percentile, but we're not in the 90th or 85th or 95th percentile of panic yet. 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. And I know that you have a very quantitative approach and you do a lot of back testing

Starting point is 00:04:17 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? So if I look back 10 years, I'm thinking, all right, well, it's gone as high as 10. So we're kind of halfway there, I guess. That seems kind of bad.

Starting point is 00:04:37 But then if I look back 20 years, I'll see it go to 20. It's like depending on whatever time period, it all seems fairly relative. So how do you measure which period to go off of like what data set, what time frame, that kind of thing? 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. and 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. And this is a wonderful indicator

Starting point is 00:05:09 for two reasons. One, these are the borrowers on the margin, right? They're the big borrowers on the margin. And 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. And so if that spread moves up materially, right, 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, like, will I get my money back on this 4% yielding bond, right? Then 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. 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,

Starting point is 00:06:03 and the idea is an answer to the question of how small shocks turn into big crises, right? If you're watching, you know, if you're watching financial markets this year, you say, well, we've had sort of a number of small shocks, right? 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.

Starting point is 00:06:29 And yet the market reaction has seemed to be very big. And so why does the market sometimes have a big reaction to what seems like small shocks? And what Bernanke says is that the financial accelerator happens when first something happens, like Russia invades Ukraine or tech earnings come in a little weak. And then people in the financial markets reprice risks. So the people in the high yield markets 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? And then what happens is that the

Starting point is 00:07:03 people that were 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, 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's stock goes down. And then the value of everyone's 401K goes down. And then people say, wow, gee, you know, I used to have 150,000 of savings.

Starting point is 00:07:37 Now I have 120,000. You know, really, definitely not buying a new car this year. And then all of a sudden, the auto parts companies go down, right? And that's the financial accelerator, right? It's this feedback loop. And that's why I watch the high yield spread so closely, right? 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

Starting point is 00:08:01 at a place where lending is actually constricting the U.S. economy. And we're there right now, right? Spreads at 470 is not good, right? I mean, that's not a good, 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 sort of the metric we look at, but 600, you know, if spreads go above 600, they often go much wider. They might go to 850 or 1,000 or in 2008 and 9 when the market totally froze, you know, they were up over 2,000, right? But spreads blow through that point. And that's basically when the market just kind of shuts and everything a liquid gets sold off. Everyone's panicking. Nobody

Starting point is 00:08:42 can get new debt. All of Wall Street kind of shuts down, right? There's no new deals. being done, et cetera. And that's a very, very dire situation. In the other hand, one that we can analyze discreetly. It's this unique environment. Or 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 is in full swing. What does that mean? What do we do? How do we react? Because those are quite rare and unusual moments. 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

Starting point is 00:09:23 as like a mile marker, it's the direction of the spread, either rising or falling, that's adding, 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, you know, as soon as it gets to 97, I get worried, but it's actually the rate at which it gets to 907 or the rate it gets to, you know, 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? 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, you know,

Starting point is 00:10:03 the financial market's actually constricting the economy, right? And 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. You know, one of the calls we would make is, hey, spreads are wide enough to be a deflationary force right now, right? They're putting down more pressure on inflation. Now, there's supply shocks that are competing with that, but broadly would say the level of the spread is giving you a sort of inflationary or deflationary metric. And it's also telling you, hey, gee, is the economy broadly kind of healthy and working, or is the financial accelerator a risk? and are we at this, you know, potentially in a crisis?

Starting point is 00:10:39 And 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 in a multifamily 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 that.

Starting point is 00:10:58 So the actual cost of that debt matters. And 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, fewer people are going to be, you know, people are going to readjust their prices down because they can't afford as much, and they might even delay purchasing. However, on the other hand, the spreads are tightening, right? And people say, oh, my gosh, I can get a really cheap mortgage or mortgages are so much cheaper or, you know, 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. And so we broadly

Starting point is 00:11:33 say, you know, when spreads are coming in and they're tightening, that's a positive thing. It suggests that GDP is growing, cheaper debt is stimulative. And on the other hand, you know, 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. And 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 of them. 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 race, but not very much.

Starting point is 00:12:07 But if you, there's 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. And while all this debt out there is financed at the lower percentile, and that every underwriter has to re-rate that. So I'm kind of 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 is high because the lower, just the incremental amount of increase nowadays will have a greater effect than it did previously? Yeah. Let's break that into two questions.

Starting point is 00:12:39 First, just thinking about rates, right? It's not everybody's mind, right? The Fed's starting to raise interest rates. That seems to be a reason that the market is selling off. And so unpacking a little bit, I'd say the first thing that 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? Hang on.

Starting point is 00:12:56 That's a big statement. Let me go a little bit more into why, right? So you'd say, okay, gee, interest rates going up should put the brakes on the economy, right? That's sort of what everyone's worried about right now. But what you typically see is that the Fed tends to raise rates when the economy is doing really well. And so the stock market's doing well and the bond market's doing well and they raise rates and the economy keeps doing well because they said, oh, the economy can handle a little bit

Starting point is 00:13:17 higher rates. That's why we're raising them. I think the most of the time, right, if you've been backtest, right, raising rates, rising rates tends to be predicting of good economic outcomes, not bad economic outcomes, until sort of the end when they raise too much or whatever, right? And the same way is true with falling rates, right? People tend to lower rates when the economy is doing badly. And so even though rising rates should be slowing for the economy or contractionary, right, because of when the Fed tends to do it, it tends to be during good times, you see very little correlation between interest rates

Starting point is 00:13:46 and any sort of asset class in any sort of predictive way. It's just not all that helpful. It doesn't even predict the bond market particularly well. Now, there is one sort of exception to that. So there's an economist at Stanford, John Taylor, and John Taylor came up with this rule, which is just said, here's what the Fed reserve rate should be at any given time. And it's a little wonky. And even I kind of have to go back to the formula every time I look at it because it's a little confusing. But for sort of 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.

Starting point is 00:14:20 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. So if you think GDP should grow at 1% a year and inflation should be two, take whatever nominal GDP is and subtract three, and that's roughly where interest rate should be. And if John Taylor were listening to this, you'd say that I'd completely butcher it. But it's good enough for government work. We'll accept it. And what happened is that the Taylor rule rules really sharply in about February, March,

Starting point is 00:14:46 of last year, and the Fed didn't raise rates. And it stayed high in the Fed didn't raise rates. And 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. And actually historically, right, when the gap between where the Taylor Rule says the reserve

Starting point is 00:15:12 rate should be and where the rate is, this wide, it tends to really foreshadow bad things for the fixed income market in particular, right? because the Fed is way behind the curve. They have to raise rates regardless. And 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.

Starting point is 00:15:35 Now, to answer your question directly, do I really care whether rates are at zero or 0.25 or 1 or 2? Not really. It doesn't backtest particularly well. Now, I care roughly where they are relative to where the Taylor rule is, because if they just get way out of whack, you know, you're worried. And then when it comes to the high yield spread, we tend to look at, I'd say, you know, take a 10-year median, that'll roughly give you where the sort of current cyclically adjusted average would be. And that's useful for giving you wide or tight. And then just the change is always sort of what the change is, right? What's the spread

Starting point is 00:16:08 now versus three months ago? And that's a good indicator. And then, you know, we look at, say, 600 as a level. That's a little bit arbitrary, but that's a standard deviation about the long-term median. And generally, when spreads go above 600, I said to my intern, 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 there's an arbitrary number. That's a fine one to use. This is why I was so excited to talk to you because you bring these very contrary intakes that I just want to explore further. So the interest rate to asset price is one. Obviously, that's sort of an effort to debunk something that is so ingrained in what every investor

Starting point is 00:16:47 tends to learn from the start. And another thing that investors tend to learn in a similar fashion would be something like the discounted cash flow model. And I know that you've done some research behind this one as well. And I would love for you to kind of share with us why we might not want to pay so much attention to something like a discount cash flow model. Yeah. So the discounted cash flow model, right at its heart, it says forecast cash flows into the future and then discount them back to the present based on how risky you think they are. And 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. And so, you know, if you think, you know, I said, hey, Tray,

Starting point is 00:17:24 what's your revenue, you know, your personal, how much money you're going to make in 2027? And then how much are you going to spend in 2027? So what's your net income? And then what's your balance sheet? What's the change from 1231, 2026 to 1231, 27? 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 it's something, but it's going to be so far off, right? I mean, so much could change between now and 2027. It's sort of impossible. And I'd say, well, Trey, you're the world's leading expert on you, right?

Starting point is 00:17:54 You can talk to every expert on Trey in the world. You'd talk to Trey's banker, Trey's accountant, Trey's mom, right? And get as precise of information over as long of a due diligence period you want. You're telling me you're really not going to be able to nail Trey's net income balance sheet and cash flow in 2027. And you'd say, no, even after doing all that work, even if there's just something about the future that's mysterious. And since I, well, if you can't do it for yourself, when you're the world's leading expert on you,

Starting point is 00:18:17 how do you think you're going to do it for Coca-Cola or MasterCard, right? I mean, there's just something that's a little bit absurd about it. And I think, furthermore, I'm thinking about risk, right? Like, okay, five years ago, is Microsoft risky? Right, 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?

Starting point is 00:18:36 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? And discount rate over five years, like how risky is a company, right? I don't know. We just don't know, right? And so I think what I worry about the discounted cash flow model, right?

Starting point is 00:18:52 Is it theoretically right? Sure. But the problem is that it's overriding what should be our complete wariness about our ability to predict the future and are, I think, acknowledging that we stand behind a veil of ignorance and we look through into the future through a glass darkly. And that's about as close as we can get. And I think what I dislike so much about discounted cash flow models is they replace uncertainty with certainty.

Starting point is 00:19:15 They replace rightful caution with some level of informed overconfidence. And I think that's why they're so dangerous. And I think much more broadly, I think people need to think about different approaches to this that don't involve this sort of 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. And I think often the things that grow the most or the people

Starting point is 00:19:42 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. And I think it's just, I think part of my larger campaign against saying, gee, you know, we need to have sort of 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 sort of silly models that don't work. Let's take a quick break and hear from today's sponsors. All right. I want you guys to imagine spending three days in Oslo at the height of the summer. You've got long days of daylight, incredible food, floating saunas on the Oslo Fjord,

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Starting point is 00:23:59 sign up for your $1 per month trial today at Shopify.com slash WSB. Go to Shopify.com slash WSB. That's Shopify.com slash WSB. All right. Back to the show. 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 and economists we've had on the show, he would say that we're no longer

Starting point is 00:24:29 in capitalism, we're in creditism. So it's very similar, I think, to your point. Credit and liquidity are driving the asset performance. And if we're not counting on earnings and discounting them into the future, is something like the Fed tightening have a higher way in our decision making than a company's earnings nowadays? Yeah, I think it's a really interesting question. I mean, I think that, so if you think about what moves market prices, and this is Robert

Starting point is 00:24:53 Robert Schiller 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. So what is explaining? this excess volatility, right? Why do markets move so much, right? And 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 with that precision. So what is changing? And there's a Stanford economist, Mordecai Kurtz, who came up with this, I think, really elegant and brilliant idea, which is he said, well, at any given time, right, 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, right?

Starting point is 00:25:54 That is impossible to disprove, but that fits the historical facts, right? 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. And someone else could say, well, you know, really what we're looking at in 2022 is history rhyming what happened in 1999, 2000, 2001. both are citing historical facts, both have a very plausible, well-thought-out view.

Starting point is 00:26:24 It just happens that their forecasts are dramatically, directionally, completely opposite to each other. But we don't know who's right yet. And so what Kurt says is that, you know, there's not one right, there's no accurate forecast today or the future. There are multiple potentially accurate forecasts. And what creates all the volatility is when the future unfolds and a large percentage of people were wrong.

Starting point is 00:26:44 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. And so I think when we look at markets and say, well, gee, things are so volatile, should we really be focusing on cash flows? 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 1.20th 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 understand to try to price in a little bit more of that volatility

Starting point is 00:27:20 or try to explain a little bit more of that volatility. Is there anything that we can use? And 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, right? There's some short-term forecast embedded in that that's useful. I think, you know, you can look at high-yield credit spreads, right, 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. So I think you're moving in the right direction. But even updating for those better models or like you look at GMO or others who say look at the CAP ratio or market

Starting point is 00:27:58 valuations and maybe those explain something. Right. 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 it's based on the fact that we can't predict the future. So I think think what you want to do is sort of pair back to or try to be humble about that and say, what can we know with more confidence and less confidence, right? Try to look for the things that feel more like rocks than like sand. And that's what led me to study in crisis investing. Because I said, look, you know, we never know if we're in a bubble. So let's try saying

Starting point is 00:28:32 shorting everything that's in a bubble whenever it's in a bubble, horrible strategy, right? Because how do you define in retrospect what was a bubble? When do you start shorting it? It's like an impossible problem to solve. And generally, you're not going to get anything meaningful it works. But if you said, hey, let's isolate periods of time when markets were panicking, and then just look at those periods, right? We 100% know the markets panicking at those times. No one's going to disagree and say, markets weren't panicking in 2009. That was a bubble, right? It's obviously not a bubble. Right. Obviously, markets were panicking. You're going to no disagreement. And the next time markets are panicking, everyone's going to agree with you.

Starting point is 00:29:03 They're panicking too. So it's something that you can sort of rely on. And 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. And so you have this enhanced predictability in the middle of a crisis. And 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.

Starting point is 00:29:39 and there are other people think this is time to buy the dip. But when there's a crisis, you sort of 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. 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.

Starting point is 00:30:05 And I've seen it something similar in your research as well. and it's applied to multiple things, like 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 kind of right in the middle of the crosshair, you know? It's really hard to say.

Starting point is 00:30:30 Ray Dalio came up with this idea, or Bridgewater came up with this idea, right? That you can think of the world, a four quadrant matrix based on growth and inflation, growth is either rising or falling, inflation is either rising or slowing. And then you can connect where you are in that four quadrant grid with how asset prices do. And I think sort of 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. So you think of a treasury, the treasury nominal rate, you can almost break down nominal rates into a real GDP component and inflation expectation component.

Starting point is 00:31:09 And so yields will go up when inflation expectations go up, and yields will go up when growth rates go up, right? 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. In the other hand, with equities are really a growth bet.

Starting point is 00:31:36 more than they are an inflation bet, right? So with equities, you're really betting on growth. And the smaller, the company you buy, the bigger the bet is on growth. And 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.

Starting point is 00:32:00 So they work best when growth is rising and inflation is rising. On the other hand, you know, think of oil, right, is a major. oil and inflation hedge, yes, but inflation is also driven by global demand. And so if global demand is slowing, that's offsetting the inflation hedge aspect of it. So he said, okay, well, what do I want to buy when growth is slowing and inflation is high? Historically, gold has been better, right? 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 helping, starting with that matrix and saying, gee, how are different asset classes linked to growth and inflation? What

Starting point is 00:32:36 implicit bet am I taking? And how is that bet correlated or not correlated so that you could come up and say, are bonds and stocks inversely correlated? And you say, yeah, absent inflation, right? 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. And then what the challenge is, though, is to say, okay, well, what is growth in inflation today, right? How do I sort of understand where we are in that four quadrants, right? I kind of get retrospectively that if I looked at periods when growth and inflation were

Starting point is 00:33:15 both bound, that bonds probably did well. And indeed they did. And that's very statistically significant. But I don't know now, like, is growth slowing or increasing, as, you know, is GDP growing or or is it falling? And, you know, a place like Bridgewater might have, you know, 20 years of like 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 high yield spread provides a really good indicator. As I said, when high yield spreads are wide, it tends to be deflationary. And when spreads are tight, it tends to be inflationary.

Starting point is 00:33:45 And spreads are falling, it tends to be rising growth environments. And when they're rising, it tends to be falling growth environments. And 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. And so if you said, okay, well, where are we roughly now? I'd say, well, spreads are above their 10-year median, right? They're at 470. 10-year median is about 420.

Starting point is 00:34:05 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. And second, you know, 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, at least the GDP print that was also materially below,

Starting point is 00:34:29 you know, Q4 of 2021, was right in line with what the spreads were sort of telling you starting in November, that things were slowing, the credit markets are tightening. And I think that those would put us pretty squarely in this quadrant four, you know, what you 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 now. About 55% of the time, they don't. Things get better. But 45%'s a big number and spreads, I think if you look at 30% plus drops in the S&P 500, every single 30% drop in

Starting point is 00:35:10 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. And 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. It's a great point. I mean, when I look at the data, I was talking to Peter Malook actually about this, he brought this up where I think the average correction for the S&P 500 is around 14%.

Starting point is 00:35:40 And I think today or as of yesterday, we were at basically 15%. I think so we're like right at that threshold of, hey, does it get to bounce from here or are we rolling over from here? And this is what makes it so hard. And so to your point earlier, the interpretation of data can be somewhat subjective. It's sort of 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, like garbage in, garbage out. It seems sometimes too easy to cherry pick data based on timelines or to see what you want to see, right? Especially when you're back testing. So you often hear, you know, something, such and such performed X amount during 89 to 2004.

Starting point is 00:36:21 And you're like, why did you choose those dates? And they seemingly arbitrary just to get a point across. So I'm kind of curious, how do you manage data while also solving for confirmation bias? Let's say, first off, you know, it's not like we have enough data to know much conclusively about the U.S. economy. I mean, how long have we had a robust equity market? How long have we had sort of a modern economy? How long have we had a fixed income market, right? 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

Starting point is 00:37:00 to figure out the best way forward. And I think that's what leads to this challenge, right, which is that you can kind of look at some period or some, you can pick the indicator or pick the period to tell whatever the hell story it is that you want to tell, right? Or whatever historical analogy you want to make. You could say, well, look at how much our market looks like the Japan or the 1980s, right? Are you using data? You know, 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. And so I think when we're designing models are trying

Starting point is 00:37:34 to develop frameworks for thinking, which I think what we're all trying to do, we all have frameworks for thinking, whether we know them, know what our frameworks are or not, but we should 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 to translate what they're seeing into action. And what I think where quantitative investors are trying to do is make that framework, explicit. And I think in making that framework explicit, you then have to say, well, what do you want to, you know, how do you make that framework reliable or how do you know that it's reliable? And I'd say, one way you test that it's reliable is you say, let's take the biggest data set we can possibly

Starting point is 00:38:09 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, right? How often do those two data sets 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? And so you want to kind of 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

Starting point is 00:38:46 that. So you find a huge amount of things that don't work, right? Like, again, every single regression you can possibly think of every major asset class against interest rates. And I'll tell you at the level and direction of the interest rates really doesn't predict anything, right? It's just really hard to make that data to tell you anything useful. 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, right, it's a lot more

Starting point is 00:39:11 fun to write about these politicians. What's Powell thinking, right? But then trying to figure out what the heck's going on with markets, just always inscrutable and too volatile. But I think you come to these much more simple things, right, like the high yield spread, credit spreads are really powerful indicator across a variety of asset classes. They predict commodity markets. They predict fixed income markets.

Starting point is 00:39:30 They predict equity markets, right? The level matters and the change matters. And I think there are other things that are really significant, right? Like simple trend rules, right? When a market falls below its 200-day moving average, that trend really is telling you something. And I think there's some markets that trend more than others, right? Like the NASDAQ trends more than the SMB500 value. But there's something really meaningful in that data.

Starting point is 00:39:52 And so I think of our search as quantitative investors is to kind of 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. So I'm sitting here saying, gee, you know, spreads are high and rising. And so, So that's telling me we're in sort of recessionary territory and I should be really defensive. And then I go and open up my Bloomberg screen and everything's green and I say, oh my God, maybe my model's wrong. Like maybe there's an exception in the model that, you know, when it's the 27th day of the month, that it 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

Starting point is 00:40:45 ever going to get. And 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 sort of random subjectivity. 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 because the most fear I've seen in my lifetime, the Fed injected $3 trillion of liquidity into this

Starting point is 00:41:21 market, which hasn't happened before in history. And all of a sudden, the market bounces back. And we're at new all-time highs within a couple of months. The high-yield spread went to 10, 10-and-half. So we're well into crisis territory. But then yet growth stocks like Amazon perform best. You know, you would think in the crisis territory, things like small caps would do well or, you know, value comes back, the cyclical rotation. But we saw growth actually perform in that scenario. So what are some ways to diversify, say if 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 an almost black swan? Yeah. So if you think about March 2020 and you just said, okay, what was a sign that the crisis

Starting point is 00:42:05 was moving into recovery? I would say, what happened to the high yield spread? High yield spread started dropping on 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 spring 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? And you just say, okay, starting in May of 2020, I started to be really bullish. And I did, I was bullish on March 20th and 23rd, but I was also bullish in May, right? Because when I looked at where spreads were, I said, gee, you know, spreads over 600. That's a really good crisis indicator. What's likely to work

Starting point is 00:42:43 out of these crises? And I sort of randomly had, 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 real time chance to see, gee, was I just subjectively assembling random time periods that Trey would say, well, gee, 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. And what you saw happen during COVID is actually textbook what happens in a crisis.

Starting point is 00:43:17 So liquidity froze up. What sold off worse. What sold off worst was the less liquid thing. So small cap, microcap sold off. Mid cap sold off more than large cap. Small cap sold off more than midcap and microcaps sold off more than small cap. And if you look then 12 months later, which did the best? Well, microcap bit better than small cap.

Starting point is 00:43:35 to better the midcaps, to be about the 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 microcaps 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. When liquidity flows out of markets and the tide leaves the beach, the micro and small caps, you know, 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. And the same thing happened in fixed income markets.

Starting point is 00:44:10 The things that sold off worst were high-yield bonds and, you know, think of BDCs or loans sold off even worse. And then when markets returned, when liquidity flowed back in, it was the exact reversal. Now, the other thing that worked really well was value, actually. So, and 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 Asnus or me, right, 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. And if you think about why a value

Starting point is 00:44:50 matters in the time of crisis, it's because most value stocks tend to be cyclical and GDP linked. And so when people panic about GDP, they sell value stocks. And then conversely, the only time, you know, an auto parts manufacturer grows faster than Amazon is in the, the 12 to 24 months following a recession where their profits rebound and their revenues rebound, et cetera. Now, tech is really the exception this time, right? Because tech was a beneficiary of the recession. There was a beneficiary of COVID, right?

Starting point is 00:45:20 People switched their consumption from physical to digital. And so even though the rest of the economy was in a recession, tech was actually benefiting. And that continued, I think really in an interesting way, you'd had the 2010s was a period defined by technology stocks where technology stocks are 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. And then COVID happened. And holy smokes, their revenue and profits doubled again. And their multiples doubled again. And so tech had just an

Starting point is 00:45:58 unbelievable year. And at the time when probably anyone that was looking at the valuation numbers thought they were due for a horrible year. And now I think what you're seeing happen is this hangover, right, where, you know, 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. You know, they're accelerating five years of growth or 10 years of growth into one. Well, what happens in year two of that, right?

Starting point is 00:46:22 Well, obviously grow slows or maybe even growth declines and look at Peloton being the prime example of this or Netflix or 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 might not do quite as much Netflix. And so that's changing right now. And that's also changing at a time when value has started to work. And 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

Starting point is 00:46:59 rescued the value factor and small caps in a big way. And now you're seeing what I would argue is sort of this hangover from COVID where the tech stocks are seeing this massive deceleration and convers and sort of coinciding with that a big drop in their multiples because people are less optimistic. And 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. Let's take a quick break and hear from today's sponsors. No, it's not your imagination. Risk and regulation are ramping up, and customers now expect proof of security just to do business. That's why VANTA is a game changer. VANTA automates your

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Starting point is 00:51:05 about value first, value is as a factor is one of the most replicated findings you can find. You can 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. And I think if you think about why that's the case, it's a systematic expectation errors that we're talking about, right? Everybody has different forecasts. Those forecasts tend to be wrong.

Starting point is 00:51:33 And 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 tend out to be as bad and those forecasts tend to be wrong. 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 hoped for. And so value tends to replicate really well across markets.

Starting point is 00:51:56 And 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 U.S. Now, there's a lot of dispute about size, right? Why is small cap matter? Why do people talk about small cap value? Why is that important? And I think there's two elements to small cap.

Starting point is 00:52:11 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. And so any sort of extreme than 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, right, a fairly large percentage of those might be tiny, tiny little things. Now, that's why when I say small, that's why I like to talk about.

Starting point is 00:52:41 I got small cap value because small cap value is the extreme of the factor. And so if you want to bet on value as, say, Fama and French define it, right, what you're really buying is the extreme of value and the extreme of value is very disproportionately smaller microcaps. Now, the negatives of small and microcab stocks and that intersection of small microcap with value is that small microcaps are much more volatile than large caps. And so there's a big drawdown. Small caps will almost always be worse.

Starting point is 00:53:07 And 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 kind of true in the case of small caps. But over time, that's where the biggest part of the premium has been. And so that's why I am sort of 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? So if you think about small cap value, which is the extreme of the value factor, right? These the cheapest stocks across the markets. Again, it tends to work really well across most major markets. Now, I have a soft spot

Starting point is 00:53:45 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 is a really big small cap market, second, Japan is super cheap. And 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 and other markets is much less present in Japan than anywhere else. That's fascinating. I always think of this quote from Warren Buffett. Brent Bishore told me this when he was having dinner with Buffett, who was drilling Buffett with,

Starting point is 00:54:18 you say all these folksy things that are so simplified, but like, really? Like, what is it really? And I guess Warren, like, put his fist down. He was like, price is my due diligence. And I just love that quote. I mean, that 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,

Starting point is 00:54:36 Or when we're in a recessionary period and companies get strapped, you might look at things like distressed debt or something, you know, and thinking that gets super cheap in periods of high uncertainty. But why is this maybe not the case? Yeah. So I think that things are cheap for a reason sometimes. And I think actually if you look sort of on a one year forward basis, cheap stocks tend to have worse revenue growth and worse earnings growth than expensive stocks.

Starting point is 00:55:01 So in some sense, the market is kind of 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. And if you think of what's embedded in the multiples, a forecast of the future, really what's sort of happening is that the market is so pricing in sort of the near term, right? They're saying the near term, this company is sort of on the decline.

Starting point is 00:55:32 and then they're extrapolating that that'll be true next year. But it turns out that life changes, right? Sort of like that example we had earlier of like, what's your balance sheet going to be in 2027, right? Who knows? But people get too overconfident, but the part of it is that they do have kind of real data about next year, or there's some level of trend or short-term forecasting

Starting point is 00:55:51 that actually kind of 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 gross stocks tend to mienervert down. And so I think with bankruptcy in particular, which is the big exception, right, 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.

Starting point is 00:56:14 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, right, where you have to screen out the stuff that actually is about to go bankrupt. And the guy that sort of made this famous was this guy, Joseph Petroski, who's another professor at Stanford, who has basically developed a pretty simple quantitative way of defining quality and a way that is kind of quantitatively meaningful. But I think that's where you really do, don't just buy the small cheap stuff, buy the small cheap stuff that's not going bankrupt. That's a really good strategy. Find the small cheap stuff is still pretty good, but buying the small cheap stuff that's not going bankrupt is even better. 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

Starting point is 00:57:03 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 everything I just told you, by sheep, by small, by quality, just basically led you down a horrible, horrible road for two or three years. And I think now it's all coming back. And so we're all feeling

Starting point is 00:57:32 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.

Starting point is 00:58:10 That consistency is key. And 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 like Swiss Army knife approach. We'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 have done really great. But post-crisis, as we may be entering into, that dynamic change pretty quickly and

Starting point is 00:58:38 momentum doesn't work anymore. So it's like, so if you know that and you know you're in a certain quadrant, do you shift gears at all? But it sounds like from what you're saying, it's better to stay rigid and systematic and kind of just take your human biases. Well, you're human, I would say like overriding a capability off the table. Or I think maybe in my view, the process that I try to go through is what is my human bias telling me, right? Like, what is, what am I thinking?

Starting point is 00:59:04 You've been in markets. I've been in markets. And I come up with an idea, right? I'm like, okay, well, gee, you know, I want to go buy oil stocks right now. And then I think, why do I want to go buy oil stocks? You're like, well, because they've been going up a lot and everything else has been going down. And then you go back and you say, okay, well, is that logic good, right? what if I just bought the best performing sector and held it for three months?

Starting point is 00:59:26 And I ranked every sector, bought the best performing sector and held for three months. Would that have been a good strategy? And you find like, 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. And so it's not the worst strategy, but let's be explicit about why you're doing it. And so if energy doesn't work for the next three months and it's trending down,

Starting point is 00:59:46 you should probably sell it because the whole reason you bought it was because it'd been doing well. And three months from now, 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. And 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 it? Would that work as a universal rule?

Starting point is 01:00:20 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. 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 is now, with rates rising, is now actually a good time to invest in bonds. And if so, why? So I think there's a big pro and a big con.

Starting point is 01:00:52 The big pro, like why you'd want to own bonds right now is because where credit spreads are. And typically when credit spreads get this wide, it's telling you something bad about both growth and about inflation. And so if both growth and inflation are going to come in meaningfully lower than people think, well in fixed incomes, especially treasuries, you're going to do really well because treasuries are a bet that growth is going to be worse than expectations and inflation is going to be worse than expectations. And so credit spreads are telling us growth and inflation are to be worse than expectations. So that's telling you a great time to go by treasuries. On the other hand, the Taylor Rule versus where the reserve rate is, is one of the widest we've ever seen.

Starting point is 01:01:30 So we're going to have really two big periods of time when spreads the gap between the Taylor Rule and the reserve rate where they are. And that was the early 2000s and the 70s. And both of those periods were just atrocious for fixed income, right? And so you'd say, well, gee, when the Taylor Rules, this is. wide, fixed income is atrocious because the Fed has to kind of 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

Starting point is 01:02:00 growth is collateral damage. And 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 rules really wide. And so at some point, bonds will work, but do they need to peak at, does the 10-year yield need to peak out at 300 or does you need to pick out at 400? I don't know. And 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. And perhaps if things trend, maybe the worst you could say is maybe we should start buying bonds or lengthening duration a year, a few weeks from now or a few months from now. In the other hand, we could have a soft

Starting point is 01:02:42 landing and the Fed could come in and we could be just way too early, right? And the 10-year yield might need to top out at like 500 or 600 and you could be in for continued horrible pain in the bond market. 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 rules really wide, you know, are so isolated and rare that you're sort of making a very idiosyncratic special argument about how now is different. I think on balance, I'm pretty pro-bonds. I'm certainly more pro-bonds than most people. But I was also, I think, you know, have to acknowledge that this is a time when there's a higher risk that that's wrong than usual.

Starting point is 01:03:27 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? I don't know. I think I'd say there's a 45% chance we are. Yeah, isn't that a horrible answer? I'm really going out on a limb. 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.

Starting point is 01:03:48 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 like 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.

Starting point is 01:04:16 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.fordadcap.com on my Twitter at fordadcap. And you can subscribe to that mailing list. We publish every Monday morning. And I think if you enjoyed this conversation, you'll love our weekly research dives. Dan, thank you so much. Let's do it again. Thank you, Trey. 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 the Investorspodcast.com or just Google TIP Finance. And lastly, you can always reach out with feedback. You can find me on Twitter at Trey Lockerby.

Starting point is 01:04:57 And with that, we'll see you again next time. Thank you for listening to TIP. Make sure to subscribe to Millennial Investing by the investors podcast network and learn how to achieve financial independence to access our show notes transcripts or courses go to the investors podcast.com this show is for entertainment purposes only before making any decision consult a professional this show is copyrighted by the investors podcast network written permission must be granted before syndication or rebroadcasting

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