In their latest episode of the VALUE: After Hours Podcast Jake Taylor, Tobias Carlisle, and Dan Rasmussen discuss:
- The True Power of Value Investing Lies in Market Unpredictability
- Japan: The Unexpected Treasure Trove for Value Investors
- The “Value Winter” is Thawing? Insights on a Potential Value Comeback
- Guide to Exploiting Predictable Correlations and Volatility
- Risk Assessment: Is China Cheap Enough to Buy?
- From Backwater to Boom? Analyzing Japan’s Stock Market Revival and Future Prospects
- Predictability in the Bond Market: Why Debt Can Be More Reliable than Stocks
- Beat the Market in Crisis: This One Signal Turns “Cheap” into “Goldmine”
- Oil Prices & High Yield Spreads: Inverse Correlation or Economic Indicator?
- Believing in Your Bets: How to Develop Conviction in a Fickle Market
- The Energy Rollercoaster: Can Value Investors Stomach the Ride?
- Decoding 10-K Size: Can Short Docs Predict Better Investments?
- Why Tiny, Illiquid Stocks Can Be Gold: Exploiting Market Inefficiencies with Microcaps
- Is the Party Over for Private Equity? Leveraged Deals Facing Scrutiny
- Small Caps: A Mixed Bag of Opportunity and Pitfalls
You can find out more about the VALUE: After Hours Podcast here – VALUE: After Hours Podcast. You can also listen to the podcast on your favorite podcast platforms here:
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Transcript
Tobias: We are live. This is Value: After Hours. I’m Tobias Carlisle, joined as always by my cohost, Jake Taylor. Our special guest today is Dan Rasmussen of Verdad. How are you, Dan?
Dan: Great. It’s great to be here with you, guys, especially with Jake’s pink sweater.
Jake: [laughs] Welcome, Dan.
Tobias: Off on the right foot.
Dan: [laughs]
Tobias: You’ve been on the show before, but for folks who don’t know, why don’t you just give us a brief outline of who you are and what is Verdad?
Jake: What are you doing here?
Dan: Yeah, what the hell am I doing here? I guess like you, guys, I have a deep and abiding interest in deep value.
Jake: Condolences?
[laughter]
Dan: I know. But Verdad, as hedge fund, we manage a little under a billion dollars, and the assets are spread out about a third of the money is in microcap deep value strategies of which the majority of that money is invested in Japan, which I’m always happy to chat about. Then we have a crisis strategy, which is another third of our capital, and that dumps money into the US market whenever the high yield spreads blow out past 600 basis points, which we first did during COVID, and then the rest of the business is high yield credit. We have a quantitative approach to high yield credit and then we have a multi-strat hedge fund which we just started, which is long, short factor strategies and multi asset class. So, that’s the spectrum of things that we do. Yeah.
Jake: I think I really enjoy all of your guys’ I read it every Monday morning when it comes out, all the research pieces that you guys put out. So, I would just start off the show by saying everyone should sign up for that if they want to keep up on. So much better than doing reading academic papers. Just read Verdad’s stream instead. [chuckles]
Dan: Thank you, Jake. Yeah, we write every Monday. We do a mix of. We do a lot of our own research and share what we’re finding, and then we summarize other people’s research when it’s good and interesting. Yeah, I was just joking with Jake that we’ve been accused of educating people’s biases that perhaps, are the things that we write are too confirmatory of our worldview. But I guess I think that’s probably true of most writers.
Tobias: Well, welcome to the show. That’s what we do.
[laughter]
Jake: Yeah. We change the show’s name to confirmation bias.
Dan: Yeah. [laughs] [crosstalk] After Hours.
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The “Value Winter” is Thawing? Insights on a Potential Value Comeback.
Tobias: Why don’t we start there? I think you and I have fairly similar approaches in the sense that it’s quantitative deep value. A lot of the research is probably US focused. It began in the US. Anyway, just because that’s the longest and best data set.
Dan: Yeah.
Tobias: I think that the question that I have had and that many people have had is that value really seems to have broken down somewhere between– It depends on how you’re counting it. But 2010, 2015 through to 2020, perhaps, I feel like there was a little bit of a recovery. Late 2020, I feel like it’s probably still ongoing, but certainly, last year was weaker for deep value, better for the growthier stuff. Do you think that’s a fair description, and what do you think of the drivers? Why are we where we are?
Dan: Yeah. So, I would say I think the worst period was 2018 to 2020, the value winter, where value just got decimated. And not only did value get decimated, but the opposite of value worked, if you were just long. I think the frustrating thing about the stuff that worked was it was sort of– we all like to think we’re really smart and educated, and we’re thinking meta analytically and we’re analyzing things. And the stuff that worked was just like- [crosstalk]
Jake: Stored or thinking.
Dan: -TV or stuff. It was just like, yeah, I’ve used Zoom the other day and that seems cool, so maybe I should buy Zoom stock. I’ve been getting so many Amazon packages. That must be a great business. Let me start buying Amazon stock, right? It was just frustrating, because you’re like, “Well, that’s not how the market’s supposed to work.” Markets are supposed to be efficient and all that stuff. It’s supposed to be priced in and the glamorous stuff isn’t supposed to work. I’d like to think that doing all this work to find some exotic microcap trading at halftime book that nobody’s ever heard of that’s like a monopoly on in some random industrial part would be rewarded. There’s some like spirit– [crosstalk]
Tobias: It’s got [unintelligible [00:04:41] on a screw that goes into a billion-dollar plane.
Dan: Yeah. And then shot–
[crosstalk]
Dan: Exactly. And yet, instead, the opposite was true. And then in the US, you had a real value recovery after 2020. Really, October, November of 2020 was huge. And then 2021, 2022 were quite good for value. And 2022 was great, because there was like the vengeance of all the stuff that I hate. All got totally obliterated.
Jake: [laughs]
Dan: They even had annoying names and annoying tickers, where the tickers was actually some word like laser or something, and you’re like, “God, this thing has to just burn in hell.”
Jake: [laughs]
Dan: And in 2022, it really did. And then in the US last year, it was all about growth again, all about growth. The growthier and the crappier the growth thing was, the better it seemed to do, frustratingly. And I think the saving grace for us was that internationally, value had a really good year. So, really good year. So, if you were long, deep value microcaps in Europe or Japan, you had a great 2023. And a lot of the growth stuff in those countries– A lot of international growth investors had a lot of money in China, which got hammered. And so, value looked pretty smart internationally. So, it was a little bit different. But yeah, in the US, again, it felt like the deeper value you were, the more you got obliterated relative to the benchmark. Nobody knew it was hard to lose money in investing in stocks last year, but relative to the benchmark, value underperformed last year.
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The True Power of Value Investing Lies in Market Unpredictability
Tobias: Probably the only place that was a little bit sad were the small and micros. How do you feel about small and micro?
Dan: Yeah. I think the other thing that’s worth noting is the size premium has been fairly negative. I think that when you’re thinking about value, especially deep value, you’re getting a bunch of factor exposures along with your value. If you want to own value, you’re also getting small size, almost inevitably, because that’s where all the really cheap stuff is. You’re also getting low earnings growth, you’re often getting high leverage levels. And so, you’re getting this other mix of factors along with it. I think the size factor, which has, over long periods of time, has been a fairly reliable winner, has also been sharply negative. And so, if you’ve been going outside of the benchmark to own smaller things, you’ve been getting hammered.
I think the smartest thing, as it turned out to have done over the last five years– I think you even think of the smart growth investors who all said, “Hey, look, the index is too overweight, like, seven stocks. And the benefit we provide you as active growth managers is diversifying you out of this top-heavy index.” But actually, the right thing to do is to say, “Hey, the index isn’t top heavy enough. We should own double our benchmark weight in these five stocks, and then we’re going to really kill it.” That was the right answer, and no one did that. I know one guy who did it, but almost nobody else did. And so, you’ve had this sharply negative size factor, which I think has also unintentionally hurt a lot of value investors.
Jake: Dan, if you wanted different ways of imagining reversion to the mean and you have the last 10 years of what kind of worked, and then if you looked back at the last 100 years, those things are like completely opposite of each other. What’s your argument other than just purely reversion to the mean? As an existential force in the universe, what would be your thesis for why we should expect the next 10 years, perhaps to look more like the last 100 and not like the 10 before it?
Dan: Yeah. I’m not a believer in reversion of the mean for reversion of the mean’s sake. I think that we can go on a deeper philosophical level. My deeper philosophical level is that there’s a lot we don’t know about the world. Our vision of what we know really stops when the future starts. It’s really hard to predict the future. Really, really, really hard to predict the future. And if you’re a smart quant and can go back test things, you can put in a lot of ideas and you can see how hard it is to predict the future by looking at how many of your back tests fail or how many of your good ideas don’t work, right?
I think if you think about some very simple rules that you might come up with, you might say, “Gee, I think the US has outperformed last year. So, it should outperform next year.” Or, like, “US stocks always outperform.” You run that through that, you just realize it’s not true. It’s too simple. I think the fundamental reason for this and why value works in my mind is that, one of the things that’s most unpredictable is future growth rates of companies. Future growth rates of companies are totally unpredictable. Right now, it doesn’t seem like that because we have in our mind, Microsoft and Amazon and Facebook. And so we think, “Oh, gee, you know, this has been very stable long-term growers. Surely growth is predictable.” But it really isn’t. Even within the technology sector, revenue growth, earnings growth, it’s not persistent, it’s not predictable. You can test that any which way.
So, if you stop and say, “Well, gee, I don’t know what the future is going to hold on a company level for revenue or earnings.” I think it would be crazy for me to say, I really know that the US market is going to be the best performing market or really to pick any region and just say, “Hey, in 2024, that region is definitely going to be the best.” What’s the logic for that? I think the same with sectors. It’s just really hard to predict what’s going to happen with any fidelity. The world is so unpredictable. And so, then I think if you think about what that implication for that is, like, if you start with a position of future nihilism and say, “Okay, let’s assume I know nothing about the world. I absolutely know nothing, and nothing is predictable and everything is totally random.”
Well, then if you bought a bunch of companies at 5 times earnings and a bunch of companies at 25 times earnings, a year from now, in theory, the multiples should adjust for some other random new set of expectations. And so, everything should be sort of scrambled. And if everything’s scrambled, the cheap stuff is going to be much more likely to be scrambled up and the expenses stuff is more likely to be scrambled down on the random distribution. And so, value is going to work because of this resorting.
I think over time, if you look, and that’s how value works. You take the universe of value stocks and a decent chunk of them end up resorting out of value, and that’s where you make your money. With growth stocks, a big chunk of them resort down out of growth, because the growth doesn’t live up to expectations. And so, I think that, for me, value is a way of betting on unpredictability of saying, “Hey, it’s a humble way of investing.” You’re saying, “Hey, gee, I think there’s a lot we don’t know. I think there’s a lot we could be surprised by.” I don’t think we should feel too confident in our forecasts.
I think to go back to the other side of the trade where people have been very confident and they’ve been saying, “Hey, we really think that large cap US tech is the place to be, and it’s really growing a lot, and that’s going to really reward equity investors.” The frustrating thing is that they’ve been right. And so, they’ve felt that the world is very predictable and that predictability will continue. But even if you look at the predictability of the revenue and earnings growth rates of those companies, they’re really random. They’ve been really high, but they’ve been quite random. They haven’t been necessarily predictable.
And so, I think you come from this place where you say, “Gee, I don’t know what’s going to happen. I think the world is unpredictable. Value is the right way to bet.” I think when it comes to thinking about size, I think of size as, which is obviously interrelated with value. But I think there are a number of ways to think about that. One is to think that there are a lot more small companies than large companies. There’s a lot more randomness associated with it. There’s a lot more volatility. And so, gee, if you’re taking that risk in smaller stocks, you should be more rewarded to the upside when that random occurrence happens than you would in a much more large stable stock, and you’d think that the large stable stock would be more efficient or less volatile, anyway.
So, I think there’s an argument that taking this value risk within small caps gives you this really asymmetric set of outset. And if you just keep making that bet over and over and over again, you’re going to be right, because you’re betting on a fundamental truth about the world, which is, that the future is unpredictable. It just is. [chuckles] You can’t predict the future, and there are very narrow ways you can. But by and large, it’s unpredictable, and value is a way to express that bet.
===
Tobias: Let me give a shoutout to– We get people from around the world, we like to give them a little shoutout. Petah Tikva, Israel. Deano in Townsville. What’s up? Maitland, Florida. Santo Domingo. Winnipeg, Manitoba Canada. Pittsburgh. Norberg, Sweden. Woolloongabba. Really?
Dan: Somebody [crosstalk] Gabba? Right.
Tobias: Good for you.
Dan: Pretty cold right now.
Jake: [chuckles]
Tobias: Podgorica. That’s a tough one. Norwich. Prince George. Toronto. Miami, Florida. Chemnitz, Germany. Valparaiso. Kauai, Hawaii. Or, Kuressaare, Estonia. Hamburg, Germany. Vacaville, Canada Cattown, Ann Arbor. Colorado. Milton Keynes. Milton Keynes. I think I always get that wrong. Nashville, Tennessee. Chippewa Falls. Toronto. Brisbane. What’s up?
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Why Tiny, Illiquid Stocks Can Be Gold: Exploiting Market Inefficiencies with Microcaps
Tobias: So, a couple of good questions in here, Dan, and then I also have some– Trey asks, “What does Dan think about the illiquidity factor vs the size factor? Some research indicates that liquid small does horribly while illiquid small outperforms.”
Dan: Yeah, I think size and liquidity are very correlated. So, where do they become uncorrelated? When you ask like, what are the liquid smaller microcaps? They’re almost all growth stocks. They’re really highly traded growth stocks. And so, yeah, they do suck. But do they suck because they’re small and illiquid? They suck for another reason. I think that my view is that size and illiquidity should, in theory, be competitive advantages for investors that can do it, because large funds can’t trade into these things, and analysts aren’t going to cover them. So, you’re going into a much less efficient part of the market, and where very small changes can drive really big changes in outcomes. So, if you think about where there’s the most asymmetry, it should, in theory, be in the most small and illiquid things.
Tobias: Yeah, I like that answer. I think that we are often measuring symptoms rather than causes. I think size itself is almost probably just a symptom of value, but that’s a little bit beside the point. Here’s a good question. I think this is right in your– [crosstalk]
Jake: Bailiwick?
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Small Caps: A Mixed Bag of Opportunity and Pitfalls
Tobias: Bailiwick. That is a good word. “Why would the size factor work in an environment where companies are staying private for longer than in the past and private equity buys out many of the best small/micro companies?”
Dan: Yeah. So, look, I think there has been a change in the quality of the small cap index, and we’ve written about this. I’d say, more of the problem is actually the introduction of a lot of crap in small companies. Recently, there’s been a lot more biotech IPOs and small tech growth IPOs, which have been really bad. And I think there’s some truth to some of the best small caps do end up getting acquired. But there’s still a really big selection opportunity. So, there’s still, I don’t know, 2,000 stocks in the Russell 2000, and 500 stocks in the S&P 500. So, there are four times as many.
In theory, that should be– whatever it is that you’re looking for, you should be able to find some version of it. And it’s more likely that you’re going to find some version of it in the small cap universe and large cap universe if you’re being selective. So, I think that might be a good argument for saying, “Hey, gee, the quality of the Russell 2000 as a whole is worse.” But is it necessarily an argument for stock selection within the small cap universe? I don’t think so.
I think another thing that’s worth noting is that private equity backed companies in particular are really low quality, as we would think of measuring quality. They tend to have really low profit margins, they tend to have a huge amount of debt, they tend to be smaller than the average small cap by a lot. And so, you’re looking at company– They do tend to grow a little bit faster. Now, some of that’s inorganic, some of that’s organic, but you’re looking at low margin, highly levered microcaps.
And recently, in the past few years, private equity has really focused on two sectors, Trotech and healthcare. So, outside of that, the world’s your oyster. And there are some sectors, like, take biotech or energy, where there are many more interesting public things than there are private things. Now, if you want to buy a microcap software company, yeah, there are no good microcap software companies that trade in the US really, or very, very few. Those are all owned by private equity. And maybe healthcare technology. But those are the real sexy areas, the glamour stocks that are being taken private and own there. Would you really want to own those? I guess a lot of people are saying they should, that you want to put 40% of your money in them. But I take the other end of that trade.
So, I think it’s a mixed bag. I think there’s certainly truth to the degradation in quality within small cap indices, but I think that’s more an indictment of owning the whole index rather than indictment of stock selection, just given how many stocks there are.
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Is the Party Over for Private Equity? Leveraged Deals Facing Scrutiny
Jake: I’m getting flashbacks to one of my favorite talks that you ever gave, which was basically dismantling private equity. [laughs] You pulled no punches. It was hilarious.
Dan: Yeah. Well, they finally had a bad year. 2023 was a bad year for private equity. It’s one of the first times in recent years where you’ve seen them take it on the chin a little bit. We were talking about in the office yesterday, this DocuSign buyout is coming out, and they’re going to pay– I think DocuSign has like $800 million of free cash flow. I think they’re putting on $8 billion of debt to finance the transaction on $800 million of cash flow. And they have all these things. DocuSign is way too much SG&A cost. So, they’re going to dramatically increase margins or whatever it is.
Jake: Synergies, Dan.
Dan: If you think of $8 billion of debt or something and at 10% interest, that’s almost all the free cash flow of the business is going to debt service. Are they going to get 10%? Maybe it’s 10%. $8 billion at 10% for $800 million of cash flow. But gee, think of the risk, right? That’s like a big premier buyout that’s happening right now. And the bigger companies are better in quality, and they have more free cash flow, and they have higher margins than the smaller companies. So, think of that as like a case study and what private equity is doing right now and just say, “How much exposure would you want to have to that?” Gee, it seems pretty risky in this environment. I don’t know, it doesn’t seem like there’s a lot of room for error. It doesn’t seem very humble. It doesn’t seem like it’s anticipating that your Excel model might not be right.
Jake: If you play devil’s advocate on this, like, let’s invert it– Let’s say that I forced you to you could only invest your kids college funds in a private equity market of some kind, what strategy would you think could actually end up doing okay over the next 10 years, net of fees?
Dan: Yeah. Well, I’ve always thought that value times leverage is a good thing, if you like value and you like small cap. But then a marginally levered company with two or three turns of debt isn’t a problem if you pay six times EBITDA for it. I don’t have an issue with that. Generally, a company can pay off. I like old school PE. I think that was a great idea. Obviously, it worked really well, right?
Jake: Yeah.
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Japan: The Unexpected Treasure Trove for Value Investors
Dan: And so, I’d say like, “Well, where can you buy small companies that are cash flow generative at low prices today?” Like, certainly Japan. Japan, everything is cheap in Japan. Now, everything’s public in Japan too. So, most of the bailouts there are take privates. But generally, yeah, you can get great bargains there. I think Europe is still decently cheaper than the US. There’s less capital chasing deals there.
And then I’d say probably within the US, there are sectors that are left for dead. Private equity as an asset class, you see the LP community react as a herd to certain things. And so, there are a bunch of take privates that went bust in 2008. So, then a lot of LPs said, “Please don’t do take privates.” And so, you saw sort of a move away from take privates lasted a few years. And then every private equity firm and their mother got really into energy in 2012 and 2013, and then got totally burned in 2014 and 2015. And then all the LPs said, “Never do energy again.” And so, I would suspect there’s a lot of interesting energy private equity deals out there. I think it’s just a matter of where the value opportunities are, and I think these days it’s anywhere X US tech and US growth where multiples are really crazy. But the minute you get out of that, there’s a huge drop off to everything else.
Jake: Do you feel like that cyclicality though almost makes it not a good candidate for PE, because inherently, you’re going to want to lever it up, which means you need consistent cash flows to sort of make the math work without crashing the whole thing?
Dan: Yeah, I think you have to lever it reasonably.
Jake: [laughs]
Dan: I think, honestly, you just have to get lucky on the sector time.
Jake: You’re not going to get rich levering reasonably.
Dan: Yeah.
[laughter]
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The Energy Rollercoaster: Can Value Investors Stomach the Ride?
Dan: But I think you got to get the timing right. So, if you look, pre-2010, energy was by far one of the best performing buyout sectors for PE, because they’d basically buy stuff when oil was at $20, and then oil will go up to $80 and they’d offload it. And gee, if your revenue went up 4x and you were levered 80%,- [crosstalk]
Jake: Yeah. You look pretty smart.
Dan: -look absolute killing. There were a lot of chemicals deals that followed a similar trajectory. So, I think those volatile areas can work really, really well if you get the timing right. And now how do you get the time? Let’s say, not if you get the timing right, if you get lucky on the timing. And so, having some exposure to those things can more than make up for a lot of losses. But gee, I think as a lot of people, a lot of value investors, myself included, you looked at energy in 2016 and said, it’s cheap. And then you looked at it in 2017 and said, it was cheap. Then you looked at it in 2018 and said, it was cheap. How many years do you have to keep doing? Something it’s getting absolutely smoked and carried out in a coffin. And then by 2020, everyone’s like, “Look at all the cheap energy companies.” And you’re like, “I cannot look at another cheap energy company.
Jake: [laughs] Yeah.
Dan: It never works. Energy is a terrible sector.” And then all of the energy stocks go up like 5x. And maybe you didn’t have as much exposure to it, because you’ve gotten so absolutely schlacked on it for the past five years. And that’s just how markets work. It makes them so challenging, especially as a value investor.
Jake: Yeah, you’re the cat that’s not going to be sitting on that cold stove either after.
[laughter]
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Believing in Your Bets: How to Develop Conviction in a Fickle Market
Tobias: There was a time in the long value winter when– One of the arguments that I heard, that I found pretty compelling– I’m just interested how you think about this. But one of the arguments was, there are so many people who know that value work is a factor. There’s so much money in value as a factor. All of the value stocks are bid up beyond where you should be able to generate any absolute return out of them. And so, the true contrarian is now hunting in the most expensive quintile, decile, whatever. They’re taking from the better companies out of that most expensive Quintile.
There’s a gentleman by the name of Partha Mohanram. I think he’s a Professor of Finance, possibly in Toronto, I think. I think he calls it the growth factor, where it’s essentially the same as Piotroski F-score. I think he called it the G-score. It was the F-score where rather than taking the cheapest and finding the best and the worst and finding the ones that can survive, you take the most expensive and long, short. Traditionally, it had generated most of its returns, probably as you’d expect from the worst of the most expensive. But there was this period of time, through 2019 and 2020, where–
Cliff Asness wrote about this, the fact that things were trading inverse to their fundamentals, which had been a thing that he’d observed in 1999 and 2000 as well. So, they’re trading inverse to their fundamentals. But Partha is saying, “Take the best of the most expensive had these two phenomenal years through that period of time.” I thought at the time, I remember thinking, this is a very compelling argument. Here it is, it does seem to be working. I don’t think it’s gone as well since. But what do you think?
Dan: I think there are other things that work. It’s a matter of your time frame. I think if you look and say, “Hey, I have a new quant strategy where I only look at 2018 to 2023, and that’s where I derive all the lessons.” What would you come up with?
Tobias: I have no idea. [laughs]
Jake: Single day expiry options.
Tobias: [laughs]
Dan: Yeah. Shorting ball. You come up with some random ideas and then you’d say, “Well, how robust is that? Is that going to work next year? Is that going to work out of sample?” It’s like energy, okay? If it didn’t work 2015, 2016, 2017, 2018, 2019, 2020, then I’m certain it’s not going to work in 2021. And then all of a sudden, it does, because the world’s surprising and it never does what it’s supposed to do. I think that as people that are trying to make good investment decisions, there’s this constant tension between what worked recently and what the long-term lessons are. The people that are following the long-term lessons are always wondering, “Has something changed? Am I wrong this time? Or, should I just continue on with what I generally know works or should work?”
I think within that context, the factor that I think both has worked recently and worked over the long-term is the quality factor. That’s why everyone and their mother from the quant world is launching a quality fund or quality ETF. I think GMO just announced it, because it’s smart, it’s reasonable, it’s worked in the long-term, it’s worked recently, and now it’s probably going to stop working randomly right about now because of that. [chuckles] But I think that as value investors, that’s the tension that we’ve been living with. I think, thank God, we had a great value years in 2021 and 2022, and for international value investors in 2023.
But absent that, you start to come to doubt some of these things. And so, I think, for me, how is it that you find the things that you believe in? What are the things that you believe in? How do you come to believe in them? I think for some people, I think there are a lot of investors that say, “If I really know about a company, I can really believe in it. I can learn everything there is to know about Berkshire Hathaway. And then no matter if Berkshire Hathaway is up or down, I’m still going to own it.” And so, I think part of being a good investor is learning about how do you get to belief? Because ultimately to win, you got to stick with something for a very long period of time.
If your strategy is to change your fundamental beliefs every two or three years, you’re definitely going to get destroyed because you’re always going to betting on the thing that worked recently that everyone else is psyched about and that ends up crashing.
Tobias: Just about it’s not working.
Dan: Exactly. And I think for me and I think for a lot of value investors, it’s saying, “Hey, let’s look at this very long time series over multiple markets, and let’s really pressure test this.” And you say, “Wow, the T statistic on these regressions is insane, and the Sharpe ratio on this is a long, short factor is insane. And the reliability of this is so strong.” You come to the conclusion this is like the best thing since sliced bread, which it basically looks like from the quantitative data, and then you live through a period where it doesn’t work.
Jake: You could write a whole book on it.
Dan: Yeah. [laughs]
Jake: Maybe several. [laughs]
Dan: Exactly. I don’t know if anyone here has done that, but yeah, I think that’s where I come to. It’s finding about what it is that you believe in and how it is that you get to belief.
Jake: I think that’s such wise advice because you’re going to be tested on your beliefs. And so, if you don’t understand yourself enough to figure out why is this something that you can stick by, why the market will absolutely call your bluff on that.
Dan: Yeah.
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From Backwater to Boom? Analyzing Japan’s Stock Market Revival and Future Prospects
Tobias: Just changing tac a little bit. Japan has been cheap for a very long time. It’s been attractive to value investors, probably for a decade or so. But there’s been some recent changes where I don’t know who the– I don’t actually know who is driving these changes, but there’s a requirement that they trade above book value. They undertake some buybacks. Do you want to let us know what those are and has they impacted it?
Dan: Yeah, this is my favorite thing ever. Like, the government has identified there’s a problem, and the problem is that Japanese stocks are too cheap. And the solution is that they’re getting really mad at all the companies that are stocks are too cheap and they have to publish plans that are going to not be so cheap in the future. And if they stay cheap, they’re going to delist them or they’re threatening to delist them. I doubt they’ll actually delist anyone. So, I just love it. It’s just fantastic. It’s like, I totally agree. Everything that trades at below book should trade at least at book.
Jake: [laughs]
Dan: I’m 100% with it. Now, if the US government could pass a mandate, the New York section is that everything that trades above five times book had to trade down to five times book [laughs] to restore rationality to the US market, then I’d really be with it. [crosstalk]
Jake: You wanted a catalyst? I give you the Ministry of Finance, Japan. [laughs]
Tobias: Yeah, exactly. And then you look at, can they achieve that? Can these companies actually get to book? And the answer is, yeah, they can just increase dividends. They have a lot of room to increase dividends, a lot of room to increase buybacks. They have a lot of cash on the balance sheet. There’s a pretty clear path. Will it happen? I don’t know. Probably, not perfectly. Nothing’s predictable. But gee, if you’re wrong and you bought a big basket of stocks that trade at halftime’s book, you’re not going to get hurt falling out of the basement window. I said right before something terrible happens.
[laughter]
Jake: Can’t lose.
[laughter]
Dan: I can’t lose until tomorrow when you find out that you did lose, because that’s the way markets for. I think that’s a really interesting phenomenon. I think the other thing that’s worth noting is if you look at– We talked about the decrease in quality of US small caps. If you look at any quality metric in aggregate among Japanese small caps, like dividend yield, return on assets, it’s like this, and it’s like the last three years or so. Everything is going in an upward trajectory. Margins are rebounding, return on assets is increasing, dividend yields are rising. Like, everything is going in the right direction right now in Japan for a whole variety of reasons. So, I think that the– [crosstalk]
Jake: The baseline was so bad.
Dan: The baseline was so bad. Yeah, exactly. And so, there’s a lot of room to run. So, I think there’s a great reason to be excited about Japan and to feel more comfortable there. It’s a great place for microcap investors because half the market, if not more, is microcap. It’s very illiquid. And so, there’s a lot to like about it from my perspective.
Jake: A company could get to one times price to book tomorrow if they wanted by– You could borrow money and then do a dividend of that exact amount and you move your book value down to exactly where your market cap mean.
Dan: Yeah. Given that debt is free and there’s basically no bankruptcy in Japan, there’s pretty much a path for every company to do that.
Tobias: My impression was it was having some positive effect that companies were doing these things, doing the buybacks. I thought that there was some take privates too, where basically– It was like the US 1980s in Japan 2023, 2024, where basically there are guys who are buying out all of the external shareholders with the cash on the balance sheet of the company, which is like, “That’s my whipped cream.”
Jake: Yeah, corporate raiders.
Tobias: Find something like that too. [laughs]
Dan: Yeah, there’s a lot of that going on. So, it’s an exciting place to be. And finally, after years of Japan being a boring backwater, maybe finally it’ll start– Well, it has been working the last two years, and I think there’s reason to think it’s going to keep working.
Jake: I’ve read that some Chinese investors are actually getting money out of China to buy Japanese stocks, which is an interesting low.
Dan: Yeah. I think of, where’s your money safe internationally? We have a colleague who’s a marine, and I joke, “If there’s a US marine base in the country, you’re probably going to get your money back.”
Jake: [laughs] Yeah.
Dan: Japan’s got it in a nice big marine base. We can feel pretty safe in most European countries, you’re going to get your money back. Japan, you can feel pretty good. China? I don’t know.
===
Risk Assessment: Is China Cheap Enough to Buy?
Jake: Yeah. How do you feel about China? Definitely, certainly a lot cheaper than it was two years ago or three years ago. I think it’s 50% off from then.
Dan: Yeah. So, we did this big Emerging Market Crisis Investing Research, and we found that when a country’s equity market has dropped 50%, it tends to be a pretty good investment, most of the time. Now, we then bifurcated that further and said, “Gee, there are, what we call, idiosyncratic crises, and there are global crises.” Idiosyncratic crises, it’s just that country like. Everyone else is doing fine and just that country is blowing up for some reason. And the results are materially worse in those situations. Now, the base rates are still good, but a lot riskier. Whereas the global crises, it’s a lot safer.
Tobias: You want a global crash. Everything’s getting cheaper because everybody’s panicking rather than there’s a coup.
Dan: You got it. Or, they just voted in a new constitution that confiscates property or something. Like, not a good outcome for you. And so, I think I would say, with China, like now, the market has dropped 50%. It’s pretty clearly interesting. Now, I think the fact that it’s the only country that’s down 50% right now, or one of two or three, makes me nervous because it’s self-inflicted. The people that inflicted this could inflict more. There’s no reason to think that’s going to stop. So, I don’t know. I think I went from being extremely bearish and never put a dollar in China to more neutral to saying, “Eh. I don’t know.” I think it’s probably worth the risk to risk.
Let me put it differently. The risk is probably fairly priced right now. That doesn’t mean it’s a perfect investment or a total slam dunk. You’re no longer looking at a market where you say, “Hey, nobody’s taking into account the risk that this X, Y or Z could happen. It’s like, “No, I think people are right. It’s probably fair.”
Jake: And maybe they’ve overreacted even a little bit relative to the existential risk that truly exists.
Dan: Right. And I think probably on a US dollar basis, are Chinese company revenues going to grow more than us company revenues? Probably. There’s probably more growth there, I’d imagine.
===
Decoding 10-K Size: Can Short Docs Predict Better Investments?
Tobias: JT, you got veggies for the people? And then I want to come back to a little bit more crisis. [crosstalk]
Jake: The People’s Republic of– laughs] I do.
Tobias: On US troughs.
Jake: I’ve been saving this segment just because I knew Dan was coming on, and it’s a little bit more academic. But it originally came from me sitting there one day, basically staring at my navel and wondering like, “Do simpler businesses with shorter 10-Ks actually produce better investment results as a base rate as opposed to 800-page proxy that you have to dig through?” I did some searching with the help of my friend, Peter, and we discovered that, interestingly enough, 10-K file size per se has no return predicting power. However, the change in 10-K file size significantly and negatively predicts future stock returns. So, if the 10-K size bumps up a bunch, there’s more earnings surprises and more cash flow surprises to the downside that happen.
This comes from a May of 2022 International Review of Finance paper called The information content of 10‐K file size change. And it’s by two, I believe, Chinese researchers, and I’ll attempt their names and I’m going to butcher it. But it’s Quan Gan and Buhui Qiu. Again, I apologize. What they found was that the median length of the annual 10-K report that provides the comprehensive disclosures, including the automate financial statements, is more than doubled over the past 10 years. So, that’s interesting. Already, our 10-Ks are twice as long as they were 10 years ago. I don’t know what to make of that exactly. Any ideas if that’s good or bad for your civilization? [laughs] More shit to dig through.
Tobias: Anytime there’s a new disclosure, it’s not like COVID. So, now there’s a disclosure for COVID and every single thing– It’s not like any other disclosure had to be taken out. It just keeps on accumulating over time.
Jake: Yeah. These legal barnacles in the 10-K.
Tobias: Yeah. Exactly. Right.
Jake: So, the authors, what they wanted to empirically investigate, does this disclosure length benefit shareholders? They sorted the US stocks into quintile portfolios yearly from 1994 to 2014, according to their most recent 10-K file size changes. Then calculated a time series average of equally weighted quintile portfolio returns over the next 12 months. So, that’s the methodology. And it turns out that it’s broadly consistent with the managerial disclosure obfuscation explanation, which is basically, you know that dreaded Friday evening dump, where they’ll just crap out some big material changes and try to hide it in the news flow.
Typically, managers, they tend to release good news in a timely manner and then hide bad news in these vague and noisy disclosures. The more lengthy it is, the more likely it is that there’s obfuscation and reducing the readability. They looked into that as well. And basically, you’re burying signals of bad news in large amounts of distracting information. So, there you go. There is a little bit of correlation– [crosstalk]
Tobias: Right. It’s confirmed.
Jake: Well, yeah, probably.
===
Beat the Market in Crisis: This One Signal Turns “Cheap” into “Goldmine”
Tobias: I feel like that’s right. Tell us a little bit about your crisis strategy. What’s the signal that turns it on?
Dan: Yeah. So, we look at when high yield spreads go over 600 basis points.
Tobias: This is that OAS option adjusted spread that the Fed publishes?
Dan: You got it. Yeah. [crosstalk]
Tobias: How often do you see that? So, that seems to be, it’s a coincidence indicator. It blows out as the crisis gets going and winds on. And so, when, typically, do you get over 600 basis points?
Dan: Got to be a lot of stress. COVID was the last time it happened. And then prior to that, in 2015, during the energy blow up. And then 2011, 2012, the eurozone debt crisis. And then 2008. So, those are the recent times that’s blown out. I think there’s some really interesting things when spreads blow out that much.
One thing we’ve actually just been looking at is equity momentum as a factor. And if you bifurcate or trifurcate the history into three states of the world, when high yield spreads are below 600, when they’re 600 to 1,000, or where they’re over 1,000, when spreads are below 600, momentum behaves really normally. It’s really positively correlated. Stocks that have been doing well continue doing well. When you go over 600 basis points, momentum stops working. There’s just no impact of momentum from 600 to 1,000. And then from 1,000 over, it’s like a massive [crosstalk].
Jake: Yeah.
Dan: Massive. Like 4x the power of what it was under 600 on the other end.
Jake: Interesting.
Dan: So, there’s just huge reversals when spreads go over 1,000. And so, generally, what you’re seeing is when spreads go over 600, they tend to blow way through 600. 600 is just a waypoint and they end up going up to 1,000 or 2,000 in the case of 2008. And then you start to get these interesting effects and you get these big reversal effects that start to happen. You get a huge illiquidity premium, because the high yield spread is just a direct measure of illiquidity premium, essentially, or the small size premium, because high yield bonds are the small cap value bonds, the small cap value equivalent in bonds. So, when the spreads are blowing out, you’re just getting a direct indicator of like, “Wow, value and size are really cheap right now.” There’s a really big premium.
And so, if you think that the world’s going to come back to normal, which probably will, then you can make a huge killing buying the cheapest, most beaten up stocks, when spreads have really blown out. And it’s quite reliable in a way that’s much more reliable than normal times.
Jake: Do you wonder about the– or at least I wonder, you’re using this mechanism to turn it on and off. I think of this like spring that over time started out pretty long. Treasuries at 15%, and now the spring has been compressed down to treasuries at 0%. I know that the six is the delta, but does the significance of the six change as the spring compression changes at all?
Dan: Yeah, nothing that I can observe. You could Z score it or something, but I think you’re still going to find that 600 is one standard deviation north and always has been.
Jake: Okay. Makes sense. I really like that most recent you guys did on. I thought that was a really clever inversion of, what does 7% bond yield buy you as far as credit quality goes? I feel like that’s something like Buffett would have done at some point and written about.
Dan: Thank you, Jake.
Jake: Just to show the deterioration and the changes over time of credit quality for that same 7% yield. Very, very interesting.
===
Predictability in the Bond Market: Why Debt Can Be More Reliable than Stocks
Dan: Yeah. Yields are a funny thing. It’s like, everyone believes in efficient markets, and then you tell them about bonds, and then their heads go nuts, and they stop realizing that they should be skeptical of anything. And someone says, “Gee, do you want to buy this 13% yielding bond?” And you say, “Wow, Treasuries only yield 5%. Great. Sign me up. I would love to get a 13% yield.” And then the person selling, it’s like, “And it’s a contract. So, you’re guaranteed to get your money back.”
Jake: Yeah. It’s printed on the coupon.
Dan: Everybody always honors their contract. [laughs]
Jake: It tells you exactly how much you’re going to get. [laughs]
Dan: You say, “Well, if efficient market theory were true, shouldn’t all bonds, no matter the yield, have the same expected return?” Let’s have a little bit of skepticism here. But again, normally smart investors, for whatever reason, often lose their heads when it comes to bonds. So, I think the message we’re trying to get across is like, target a credit quality or target the exposure you want. Don’t get focused on the yield. It’s going to mislead you. You’re going to make bad decisions, if you just start thinking in terms of yield. But you look at the private credit industry and they’ve realized that people are suckers for big promised yield. But you look at past instances where people have offered very high yield products. It’s not like, how many billionaire pawn shop payday lenders do you know versus how many billionaire PIMCO type people do you know? It turns out it’s a lot better to buy the less risky bonds than the really, really, really, really risky ones.
Jake: Bull’s yield, as you’ve called it before.
Dan: Exactly.
Jake: Yeah.
Tobias: How do you implement the high yield credit? Is that the way that you’re doing it?
Jake: He promises 13%.
[laughter]
Dan: He promises 13%. We raise as much money as we can. [laughs]
Tobias: I like it so far.
Jake: Two terms of leverage.
Dan: Yeah. We add a little leverage on top, and then if it stops working, we raise a new fund and buy the bad debt from the old fund.
Tobias: At a discount, so far so good.
[laughter]
Dan: So, basically, I think it’s like factor investing anywhere else, except you’re given the value. Like, right away you’re given that. So, what you really want to know is controlling for the yield, what’s the quality? And so, you’re just inverting it in some way, what you do in equity world. It turns out that in terms of bond market, some of these things, it’s actually a little bit simpler. So, one of the key things that you want, you really want in credit is size at a given yield. So, if you have two bonds that both yield 7%, and one of them has a billion dollars of market cap and one of them has $15 billion of market cap, you really want the company with $15 billion in market cap. It’s much more likely to get upgraded to investment grade. It’s much less likely to go bankrupt. And similarly, return on assets, for example, or gross profit to assets, those types of metrics.
Jake: It’s quality.
Dan: If you have the same yield, gee, you’d much rather choose the company with a 10% ROA than a 2% ROA. And if you stack up a few of those pretty simple, pretty obvious metrics, and then you just rank the bonds by yield, and then– So, you take all the bonds at a given yield bracket, rank them by quality, you’re going to get a really good, clean premium relative to the index. And that’s what we do. It’s a very simple approach, but it’s very powerful.
I think one of the things that’s interesting about credit is it’s more predictable than stocks. These things work more reliably in debt than in equities. And so, I think you can see these factor premiums more reliably there.
Tobias: It’s an equity type approach to bonds. Higher credit more equity than bonds. Sorry, JT.
Jake: I was just going to say, and this is like a sweet spot at, like double B. Is that–
Dan: Yeah, exactly.
Jake: Do you remember that, right?
Dan: There’s a level at which yield. So, increasing yield improves your total return up until the low end of double B, and then increased yield actually decreases your total return, which we call fool’s yield. Like, it’s this triangle where a 15% yielding bond actually returns worse than a 6% yielding bond on average. So, you find that sort of fulcrum point where you’re maximizing total return, not maximizing yield. And then at that yield point, you sort by quality. That’s essentially our strategy. But this fool’s yield concept is really fascinating. It turns out that no one really knows how to price an 18%. If someone says, “It’s an 18%. What’s the bankruptcy risk? Is it 33% or 28%?”
Jake: Strong to quite strong.
Dan: Yeah. It’s just like it’s probably going to go bankrupt, and probably there are too many idiots that thought, “An 18% yield sounds really good. I’m going to go buy that.” And so, it ends up being that that stuff ends up ending up with shitty outcomes, whereas the much higher quality stuff is just more consistent does better over time.
===
Guide to Exploiting Predictable Correlations and Volatility
Tobias: This might be a state secret, but how does Dan get the data for all of his bonds?
Dan: You can get a lot of data from Capital IQ. It has the 10 ten years of bonds pretty well. And then anything other than that, Bloomberg is the only really reliable. You kind of have to trade bonds, you really need Bloomberg.
Tobias: Do you want to tell us a little bit about the multi-strat fund? That’s launched or that’s just launching?
Dan: Yeah, we launched it about two years ago. We’ve changed it. We tried some things that didn’t work and then we’ve really been improving the model. But what we’ve come to is that, I think a lot of investors are very focused on expected return. You want to maximize your expected return. But expected return is also really hard to predict, as we’ve talked about. It’s really hard to know. If you take every stock and try to rank them by expected return, which is what all equity investors are trying to do, it’s really, really hard. And if you look at the R squared on factors, how well factors predict the expected return for stocks, you’re getting in the 5% to 10% R squared range. Like, it’s a real edge, but it’s a lot of noise.
Jake: It’s not much though. Yeah.
Dan: It’s a lot of noise. It’s not much. It’s really hard to predict. What we’ve learned is that, actually, what’s much easier to predict is correlations and volatility. So, if you just take a weighted average correlation matrix, you say, “Hey, let’s give it a half-life of a month or three months, and look at the correlations between stocks and bonds and oil and value and size,” and whatever, that that correlation matrix is pretty stable. It changes over time, but you can predict next month’s correlations pretty well with that weighted half-life type history of recent correlation matrices, such that the R squared on that might be– It’s hard to think of what an R squared means for a correlation matrix. But if you think of some equivalent, you’re probably getting into like 70 or 80% R squared. Like, you can really predict correlations pretty darn well by relying on [unintelligible [00:50:59].
And then volatility is also really predictable. So, last month’s volatility, you take in the VIX and you take in recent, like last month’s volatility, you can get a 40% or 50% R squared predicting next month’s equity volatility. And if you try to predict bond volatility and oil volatility and whatever, you’re going to get pretty good at that too. It’s just pretty auto correlated. It moves a lot, but it’s auto correlated. So, if you say, “Well, gee, let’s imagine, I can’t say I have no view on expected returns.” I think stocks return what they long-term averages. I think bonds return long-term average. I think oil returns long term average. Everything just has a long-term average return. So, I think the market follows a random walk. I have no view of anything.
But I think that volatility and correlations move around a lot. You run that through an optimizer, you’re going to get very different portfolios every different month, because if stocks and bonds are really highly correlated, gee, you’re going to take down your exposure to one or the other, because you don’t need both. And if stock volatility goes up a lot and you have the same expected return forecast, then your forecast of Sharpe dramatically went down. So, you’re going to say, “Well, gee, I want to take down my equity allocation, not because I have any negative view on equities, I have the same expected return view.” But for that volatility, they’re just less of a good buy right now. I’m just getting less Sharpe for the same products, I’m going to reduce my weight, and maybe I’ll take it up in something that’s less volatile than normal.
And so, what we started is basically building this giant database of every single stock categorized by factor, bonds, both sovereign and corporate with factors, and then commodities, oil, copper, gold and currencies, the major tradable currencies, and saying, “Hey, let’s run an optimizer where we look at their volatility and correlation structures.” You take some rough bench regularized to some rough 60-40 like benchmark and then say, “Gee, can I improve outcomes, because I’m really good at predicting volatility and correlations?” And the answer is, “Gee, yes, you can.” You can really, really dial up Sharpe and you’ll take bets that you might be really–
For example, right now we’re quite short the Mexican peso. We have no view on the Mexican peso. In fact, our model is told that the Mexican peso is a 0% expected return, always. We never have a view. It just happens that right now the Mexican peso is really negatively correlated with a lot of bets that we want to take. So, we like value, and it turns out that the Mexican peso– When value does well, the Mexican peso does badly or something. So, it ends up loading up on the Mexican peso to diversify our value long. And you’re like, “I never would have thought of that. That’s totally nuts to me.”
Tobias: [crosstalk] It’s what I’ve been missing.
Dan: It’s what we’ve all been missing, clearly. But when you think of why it did that, it actually makes a lot of sense. It actually works decently well. And then we’ve said, “Okay, well, gee, now what if we could actually predict, have some edge in expected return? Is there some way where we can make better expected return forecasts?” We looked at everything we could try to predict. Can we time value? Can we time size? Can we time Treasuries? Can we time high yield? And for 90% of things, we found that we couldn’t. There’s no ability. Nothing we came up with, we threw the kitchen sink at it. Nothing worked out of sample. Just all a failure. Like, we have no ability to predict whether Japan is going to do better in the US next month. We have no ability to predict the US equity intercept.
But for some things they are predictable or more predictable. So, momentum, I just described to you how equity momentum works really well under 600 basis points, not well between 600,000 as reversals over 1,000. You plug that in, you’re actually a big improvement in your ability to forecast momentum returns. And then you can apply a similar logic. One of the logic we talked about high yield spreads is size. When high yield spreads go– When they’re going widening, blowing out, size does worse. When they’re coming in, size does better. When spreads are really wide, size does better. When they’re really tight, size does worse. And then, gee, you can actually get a 10% R squared in predicting the size premium, for example.
And then oil is another example, where oil is really driven by high yield spreads. When high yield spreads blow out, oil sells off. When high yield spreads come in, oil does well. When high yield spreads are just bumping around, oil just goes randomly oscillates in a dramatically unpredictable way. But you start to layer on all of these things, and you accumulate all of them into rules, and you write software to trade them, that’s what we’re trying to build, is to try to build all these insights into, basically, software that can trade all of these ideas and understand the volatility and correlation matrix across 39 correlation pairs. That’s the essence of what we’re trying to do, which I’m pretty excited about. It’s been a huge, huge research effort, both building out the infrastructure to do it, doing all the research, and then learning how to actually trade it and how to make it work.
===
Oil Prices & High Yield Spreads: Inverse Correlation or Economic Indicator?
Jake: Did you say that the higher oil prices correlate with high yield spreads, or is it the other–? Is it positive or negative correlation?
Dan: It’s the change in spreads predicts changes in the price of oil. So, when spreads are widening out, oil sells off. And when they’re tightening–
Jake: Interesting. I would have probably thought the opposite of that, actually. I’ve heard the idea that oil is perhaps its own Fed funds rate. So, when it spikes, that’s often kills the economy, when oil price spikes.
Dan: Yes. So, we’re saying the same thing. When high yield spreads blow out, the economy is doing badly. It’s predicting the economy is doing worse. Growth is slowing, and that’s when oil starts to sell off and do really badly. I think we’re saying the same thing.
Jake: Well, I was actually, a spike in oil prices precedes–
Dan: You’re saying it’s causal.
Jake: Yeah. Like, it precedes an economic hiccup.
Dan: Yeah. I’ve tried that, and I didn’t see that– [crosstalk]
Jake: [laughs] Couldn’t get to work it.
Dan: Strong relationship, but the opposite, that oil as a contemporaneous thing. When the economy starts to slow or do badly, that oil sells off, which makes a total sense that it would. And that actually makes it a really good hedge against equities, because it’s one of the things that you can short oil. When high yield spreads start blowing out, and it’s really a beautiful, beautiful hedge.
Jake: Do you have any worries about with all these correlations, call it Taleb’s turkey kind of problem, where it seems like these things are all working and then you have a huge reversal that give back 10 years’ worth of it working.
Dan: Yeah. I don’t know. I think that from what we’ve seen, correlations are pretty stable. They change, but they’re auto correlated. They’re pretty auto correlated, right? And relying on last month’s correlations to predict next month’s correlations seems pretty reasonable. So, then the question is, are there big jumps where correlations-
Jake: Just continuous.
Dan: -dramatically change? One way to test that is to use the VIX to predict a correlation matrix or something. I think what you find is that you don’t really need to do that, because the markets– Even during COVID, the correlations are changing, just even adjusting on a weekly basis, you’re going to be fine, if you’re reacting to those variables in other ways.
Jake: Right.
Tobias: The same thought occurred to me, but I was wondering whether it was something you can deal with the way that you’re allocating your assets to the extent to which you have leverage and you have derivatives that have got leverage in them, you can probably find a way to construct it without that that being concerned. But that was the thought that I had. There’s no free lunches. I think it’s just probably the first rule of finance that there’s a cost somewhere, and it may be that it’s something that has that behavior that Jake described.
Dan: Yeah.
Tobias: Taleb’s turkey– [crosstalk]
Dan: I think that’s probably the right risk to be thinking about. But I think fundamentally, if you’re just saying, “Hey, I’m diversifying across multiple asset classes.” And the other thing that I’m doing is that when volatility spikes, I reduce my exposure, because I think the Sharpe ratio has changed, I’m very humbled by my expected return forecasts. Most of those discontinuities should be accompanied by spikes in vol. And so, if you have a model that really dramatically de-risks, every time vault spikes– Probably, I think there’s less risk of getting totally destroyed, especially if your bets are diversified across multiple asset classes. But we’ll see.
Jake: [laughs]
Tobias: We’ll find out.
Jake: We’ll find out together.
[laughter]
Tobias: And on that note, Dan, we’ve just come up on time. So, if folks want to follow along with what you’re doing or get in contact with you, what’s the best way of doing that?
Dan: My Twitter, @verdadcap, and you can sign up through my Twitter bio to our weekly research.
Jake: I would encourage that.
Tobias: It’s Dan Rasmussen, Verdad Capital, thanks very much for your time today. Thanks everybody else too, JT. We’ll be back next week. Same bet time, same bet channel. See you, folks.
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