Invest Like the Best with Patrick O'Shaughnessy - Dr. Ben Hunt - The Three-Body Portfolio - [Invest Like the Best, EP.73]

Episode Date: January 23, 2018

My guest this week is Dr. Ben Hunt, the chief investment strategist at Salient and the author of the extremely popular epsilon theory. I’ve always enjoyed Ben’s writing style, particularly his use of farm and animal based analogies to describe market phenomenon. In this conversation, we discuss his recent post the three body problem, why growth has been beating value, and why a strategy that he calls profound agnosticism—a take on risk parity—may be the most appropriate investing strategy in what he views as a very uncertain world. We also discuss some of his favorite lessons from the farm.  Please enjoy our conversation!   For more episodes go to InvestorFieldGuide.com/podcast. Sign up for the book club, where you’ll get a full investor curriculum and then 3-4 suggestions every month at InvestorFieldGuide.com/bookclub. Follow Patrick on Twitter at @patrick_oshag   Links Referenced The Three-Body Problem   Show Notes 1:54 - (First Question) – Applying the three-body problem to investing  7:24 – Fundamental view of investing, Profound Agnosticism  8:24 – Why has value done so poorly relative to growth in this framework  11:01 -  Ben’s thoughts on why value has been underperforming for so long  13:52 – Investors should be able to adapt  17:49 – Thoughts on the risk parity approach  23:23 – Ben’s strategy for working with several teams  26:48 – What’s the best way to gain an edge, top down factors vs company/bond individual analysis  28:29 – How do you measure risk amid the large amount of uncertainty that exists in markets  32:40 – How does Ben personally think about investing  34:41 – Ben’s farm and the investing lessons learned by some of the animals  39:55 – How bees can plan out their entire work structure by the angle of the sun  42:58 – Defining basis risk  44:59 – Personal risk vs portfolio risk  49:30 – The concept of fingernail clean and our perception of what eggs are  53:57 – How ETFs are like mass produced eggs  54:56 – Exploring the idea of quality vs scaling  58:39 – What is the current challenge/puzzle that Ben is focused on right now  1:01:59 – What is Ben looking for when looking into game theory and applying it to the words that are published and spoken about investing  1:03:57 – Most memorable day on Ben’s farm  1:05:04 – Kindest thing anyone has done for Ben   Learn More For more episodes go to InvestorFieldGuide.com/podcast.  Sign up for the book club, where you’ll get a full investor curriculum and then 3-4 suggestions every month at InvestorFieldGuide.com/bookclub Follow Patrick on twitter at @patrick_oshag

This podcast is sponsored by CFA Institute, the Global Association of Investment Professionals whose mission is to lead the investment profession by promoting the highest standards of ethics, education, and professional excellence for the ultimate benefit of society. CFA Institute serves a global community of investment professionals working to build an investment industry where investors' interests come first, financial markets function at their best, and economies grow. The chartered financial analyst credential is the most respected and recognized investment management designation in the world.

The views expressed in this podcast do not necessarily represent the views of CFA Institute. Hello and welcome, everyone. I'm Patrick O'Shaughnessy and this is Invest Like the Best. This show is an open-ended exploration of markets, ideas, methods, stories, and of strategies that will help you better invest both your time and your money. You can learn more and stay up to date at investorfieldguide.com. Patrick O'Shaughnessy is a principal and portfolio manager at O'Shaunacy Asset Management. All opinions expressed by Patrick and podcast guests are solely their own opinions and do not reflect the opinion of O'Shaughnessy asset management.

This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of O'Shaunlessy Asset Management may maintain positions in the securities discussed in this podcast. My guest this week is Dr. Ben Hunt, the chief investment strategist as Salient and the author of the extremely popular website, The Epsilon Theory. I've always enjoyed Ben's writing style, particularly his use of farm and animal basis. analogies to describe market phenomenon. In this conversation, we discuss his recent post, the three-body problem, why growth has been beating value, and why a strategy that he calls profound agnosticism, a sort of take on risk parity, may be the most appropriate investment strategy in what he views as a very uncertain

world. Please enjoy our conversation. It's an old problem in physics, and it refers to Henri Poincolet, who's one of the geniuses of mathematics of the last millennium. and it was in the 1800s, and what he was trying to figure out is this, well, I'll back up a second. What he's interested in, this is going to be your connection to bees and actually, I think, to humans and investing and to your original question of what's your fundamental idea about investing. He was wrestling with this question of algorithms, which is a formula, which is a process that you can

apply over and over again, where you put in your values and you turn. the crank of the algorithm and it gives you an answer. What I will tell you is that whether it's human beings, the way we construct our societies and our markets, whether it's bees and the way they construct their hives and the way that they search for honey and or search for pollen and make nectar and make honey, they're all dominated by these algorithms, which are just our simple formulas for making sense of the world. And in my experience that whether you're a value investor or a growth investor or a momentum guy or a quant or whatever you are, in the back of your head, you've got a collection of algorithms for how you make sense of the investing world. And what Pankuay was trying

to wrestle with was one of these classic problems of geometry. He was a geometry nut. And it's related to physics and the three-body problem really takes a problem from physics, which is to imagine you've got you're in outer space and you've got three planets or stars or what have you, three massive bodies. And you know exactly how they interact with each other. Gravity. And you know the laws of gravity. And that's all that acts here. There's no drag from atmosphere. It's just a pure calculation of here's where these different three objects are. You know exactly how gravity works. Now the question is, what's the formula? What's the algorithm? to say where those three bodies will be 10 minutes from now or an hour from now. And again, you know everything about these three bodies.

You know exactly where they are. You know how fast they're moving. And you know how they act on each other. And what Poincol-Carray proved was that, and this is crazy talk, there is no algorithm. There is no algorithm. There is no formula that you can plug in all those starting conditions and turn the crank and say 10 minutes later or 10 years later, here's where all those objects will be.

It does not exist. And that's such a hard thing to wrap one's head around. And you can, if you see pictures of it, you can kind of imagine it. But what it's really saying is that these are, we can use a term like a chaotic system or the like, which is kind of right, maybe not quite right, but for our purposes, right enough. So the three body problem is simply that when you've got these, three entities, there is no formula because the starting conditions you can really end up anywhere. It's not governed by a two-body problem where you've got something orbiting around

something else. They keep messing each other up, three bodies in space, such that there is no formula to ever predict this. And so what's really hard about that for humans is to think, well, Wait a second. Actually, three-body or multi-body problems are kind of the rule in space, not the exception. What if that's true for some of our human systems also, like investing? What does it mean that a new star appeared with massive gravity in the form of central banks buying $20 trillion worth of stuff out of thin air? It's what Jim Grant likes to call about the Swiss National Bank, you know, out of the thin alpine air. You know, it's just a great phrase.

What does that mean for our traditional algorithms and views of what makes a stock work? And what the three-body problem tells us is that it changes it forever. And it changes it in a way that I know you'd like to say that, oh, things will go back to normal, where quality matters or value matters under these conditions. where our algorithms work again. But the fact, the scientific fact is that ain't so, or it might not be so, and we need to understand, well, what does that mean for all of our fundamental views of investing if, in fact, the existence of central banks buying, this isn't going to go away.

You can't unring that bell. It's not like they're going to say, oops, sorry, let's sell everything and no, gosh, we're never going to do that again. No, this is a new gravitational body in our world of investment for better or for worse and to wax and to wane forever and ever amen. And so what that means is that I think we have to question all of our fundamental views about investing. So the big question is, well, where does that end up? Is there a fundamental view of investment? And I come up with something that, again, it's kind of really hard to wrap your head around. And it's what call profound agnosticism, profound doubt that any of our algorithms, any of our fundamental

views are true with a capital T in other than, I'll say, kind of exceptional local circumstances. Maybe we can talk very specifically about some reflections of this idea in this post-financial crisis period. One of the charts you put in there was the growth of the S&P 500 index, and then at the bottom, and sort of a flat line, a long short portfolio of quality metrics, basically showing that higher quality in that same time frame relative to low quality, so no beta in there is flat. Like high quality has not outperformed. And maybe one of your foundational principles is higher quality businesses should deliver better returns

over the longer term. I think that's all of ours. It's probably the most pervasive fundamental view of investment, I think, that all of us have. I would later on there that, you know, obviously price is a key component always. And it's always interesting to look at different kinds of investment factors. You know, that's what we do. That's what we do. That's what we all do. And understand the horizon over which they matter, right? Correct. Quality in the short run can often really not matter at all. In the long run, it has more of an impact. Valuations, for example, matter kind of throughout. So the price you pay up front is a very

good predictor of your future returns. But in this period, so that quality line is flat, if you did the same line for a long short value versus growth portfolio, it's sharply negative. You've gotten killed. You've gotten killed. Because growth has crushed value. So I'm curious how you think about why that new gravitational body resulted in that outcome. Why you think that has, it hasn't given us a flat line. It's given us a sharply negative line. So why has value done so poorly relative to growth with this kind of framework in mind? Because the gravitational pull of central bank purchases has no impact on value and no impact on quality.

In fact, if it has any sort of gravitational impact, it's got an inverse impact. Why? Because the purpose of these large-scale asset prices is not to reward good companies or value-oriented investors or companies with intrinsic value. The entire purpose of large-scale asset purchases, and this isn't, you know, conspiracy theory stuff, this is what Bernanke and Yellen say, right? This is the canon. Large-scale asset purchases are there to force all investors to go farther out on the risk-reward curve than they would otherwise prefer to be. So if you are a U.S. Treasury investor, that's your thing. We're going to push up the price

to your point about the price you pay always matters, we're going to reduce the yield, we're going to push down your expected return on what you pay for those U.S. treasuries to force you to get into a riskier asset. Maybe it's mortgage-backed securities. And for those people who are in mortgage-backed securities, we're going to force you into high-yield.

And if you're in high-yield, we're going to force you to go farther out that risk curve and get into equities. And if you're in equities and you're doing safe stuff, we're going to try to force you into doing risk your stuff. It's pushing every investor farther out on that risk curve than they would otherwise prefer to be. Again, that's not conspiracy. That's not hidden.

That is the overt. That is the written purpose of large-scale asset purchases. One of the things I don't understand is specifically this value growth spread. Now, obviously, you can go and do normal attribution and see the reasons why, and it's, you know, the fang stocks and all the companies that people are talking about have been enormously successful, but you know, you can make the argument that value companies are actually riskier in some cases than gross stocks that are distressed or, you know, whatever else. So I have trouble squaring that, like I understand the pushing out on the risk curve, but I still have trouble

squaring, like if you just were a U.S. equity investor, this has been kind of the longest in the tooth. This is always cyclical, like value underperforms for long periods of time sometimes, but this is about as long a period as we've seen. And I'm just fascinated to hear what you think about that phenomenon. Here's exactly what I think. What I think is that secular growth in a world where central banks are lifting all boats, secular growth is the rarest thing in the world. And so that commands a premium. Why does growth command a premium over value? Because growth has been so rare in this world. Because the other side of the coin of central banks, monetary policy, forcing greater risk in markets, is to reduce risk-taking risk-taking,

in the real economy. It reduces risk-taking in the real economy. And this is exactly what we've seen with the mystery of productivity, flatlining and declining. This is exactly what we've seen with the mystery of companies not spending money on growth cap-ax on plant and equipment and wages to grow their efforts. Why would you, why would you take that risk, your IBM, Why would you take the risk of actually taking the risky action of investing in new plant and equipment, a new idea, a new business line when you can deliver earnings growth, when you can deliver return for your shareholders through purchasing revenue, stock buybacks, and increased dividends through financial mechanics rather than real world risk taking?

So in that sort of world, and you see it in our GDP numbers, you see it in the product, and not just in the U.S. but globally, secular growth becomes incredibly rare. And so that's what becomes rewarded by the market. That's what I think explains that growth value dynamic, that, and again, it's all predicated on this notion that this huge gravitational force of $20 trillion worth of propping up of markets, of buying financial assets, it don't care about any of this stuff.

And so it has real world impacts of reducing risk-taking and putting a premium on secular growth. And it has a real world impact, well, a financial world impact of value, sucking win for a long time now. So the responsibility of every active manager is to adapt to changing conditions. And there's no excuse for not trying to figure things out. You're always trying to outperform. Yeah, you know, but I'm going to push back a little bit on that a little bit. Because, yes, all investors, all professional investors should be able to adapt to changing circumstances.

But what I also think is so critically important is that as a professional investor, you have to know yourself. You have to know what makes you tick. I'll mix a lot of metaphors here. But an investor can't change his or her stripes. I think it's almost always a mistake to do that. And so instead of adapting what I think you've seen in so many cases is investors who do know themselves, they say, you know, it's not working. Yeah, a lot of fun shutting down. That's exactly right.

And I think that is the correct way to do it. I think that's the intellectually honest thing to do, that your stripes, your DNA as an investor, aren't working at this time. And this is what, again, what gets me back to thinking about a different kind of DNA, which actually, I think, you know, lends itself to a more systematic approach, this notion of profound agnosticism,

which I think really finds. it's home in terms of how do you how do you operationalize that with what goes under the name of risk parity. But more broadly speaking is the notion of having a risk or volatility budget for the assets you take and having it programmed into your investment strategy that you're going to adjust your portfolio, you're going to adapt to your portfolio, not on your views of what algorithms you've got in the back of your head about what should work, but really mechanistically based on, well, what does work? That as risk goes up and this asset class are that, you reduce

your exposure. As risk goes down, you're going to increase your exposure so that you're taking this, again, what I call a profoundly agnostic approach of, I don't know what asset classes are going to work. I don't know what geographies are going to work. Because I don't trust that algorithms that I've had in my head about what factors work and what factors don't work. Instead, I'm going to take exposure to all of them, at least so long as they are truly diversified, that they're not just correlated one-to-one with each other. But independently active factors, whether that's traditional investment factors or whether it's a geography or whether it's asset class, my answer is, yes, I want all of

them and I want to have a profoundly agnostic view of how I should wait them. To me, I think that for an investor or an allocator who's looking to take what the world gives you, which is what we're looking for with beta. You want to take what the world gets you, gives you, and you want to take it in as a cost-effective way as you can. I think that these risk-balancing strategies of which, you know, risk parity is up, is a kind of specific form of that. I think that is how one copes with and adapts with the three-body problem,

the fact that in this environment, our old moorings don't seem to have a lot of purchase and may never again. So let's take on risk parity a little bit, an interesting concept. So the common criticism would be, assuming you kind of have the normal inputs that people do, stocks, bonds, commodities, maybe some other things, that effectively all risk parity is is a levered-up bond portfolio. Levered bond portfolio. And that, you know, that back tests really nicely because

we've been in a secular declining interest rate environment. And so you lever up bonds and the portfolio looks fantastic. But volatility regimes can change and then be different for a very long time. So how do you think about that typical criticism of the risk parity approach? You know, before I joined Salient, that was exactly my view. In one of the first Epsilon theory pieces I ever wrote was frankly a critique of risk parity strategies. It was right when the tape the taper tantrum was occurring, which was, which was a bad month. It was a bad time for risk parity strategies because think about it, bonds tend to have a much lower volatility than stocks. So if you're trying to have an equal bucket of risk, you're going to have you're going to have to lever up that bond bucket

to get the same level of risk that you would historically have seen in your stock bucket, or your commodity bucket, or your credit bucket, your corporate credit bucket, which is, I like to think of those as being the four buckets, right? So we can think of rates or, you know, government bonds as being that one bucket, which is what really got hurt in the taper tantrum, right? You can think of equities as another bucket. You can think of corporate credit as a third and commodities of the fourth. Now, then importantly, within each of those buckets,

you also want to have that agnostic view in terms of geography. So in equities, you're looking at a developed markets, emerging markets. You want to have diversification within there or markets that aren't strongly correlated to each other. So it's turtles all the way down. You're divvying it. You're getting smaller buckets within each of those buckets. But your main point is that is the standard, I'll say, critique. And it's exactly the place where I started approaching this.

what I didn't appreciate until I got immersed in the managers who actually implement these sort of strategies, two things. First, these risk allocations are, I'll call them barge-like as opposed to motorboat-like, meaning that the other criticism you typically hear is that, oh, well, these will be, if there's a down market, that the selling pressure from these funds as they seek to rebalance, that will just accentuate the crash down and, you know, it just makes these cyclical movements that much more accentuated. That would be true if they were rebalancing and making these big shifts intraday or on a daily basis. They're not. These are typically, like say, barges that change these risk allocations to these large asset classes pretty, pretty slowly. But then that gets to that point that I had earlier, which was that, well, gosh, if you're, if you're, if you're, if you're, you're allocated to bonds in a levered sort of way and you get something like the taper tantrum

and those bond prices really go down, well, you know, your portfolio is going to take a significant hit. And it does. But, and this is the critical thing, there is a, the adjustment mechanism. These are dynamic portfolios, meaning that they don't do it on a daily basis, but they do adjust if you were telling me that we were taking static allocations to stocks, bonds, commodities, and credit, and that we're saying, okay, here's our allocation, here's our static, you know, we're going to have to lever up bonds to get the curve of all we need in this. And by God, that's our allocation for the year or what have you. Yeah, that'd be a mess.

But these barges, they move and they can move quickly enough and carry enough ways. so that if we take anything other than, you know, a monthly time horizon or the like, they really do adjust themselves quite well. And so the dynamic nature of these strategies is what kind of turned me around, at least, to see that, well, actually still for harvesting beta, these do an incredibly good job. I'll take one more point at this. your need to lever up that one bucket is accentuated if all you're doing is stocks and bonds. So to the degree that you are, A, looking at things like commodities, that you are looking at credit,

that you're looking at, like, say, four buckets, to the degree that you're also, again, subdividing each of those buckets into different geographies and factors and classes, is all of that really helps in terms of getting too levered or too weighted to any one thing that gets tagged in any one moment in time. Anyway, that was a long-winded answer to the fact that I know exactly where you're coming from and I used to share that view. But then getting immersed in it and finding, well, how actually dynamic these portfolios are, it really brought me around, particularly when combined with just the fact that since March of 2009, so many of our algorithms, our foundational views on how one should invest, haven't worked.

And I think that taking this perspective of profound agnosticism, it does lend oneself, at least for the beta component of your portfolio, to thinking in terms of a risk-balanced, and risk parity is maybe an extreme version of that, but a risk-balanced approach. We were talking before we began recording about the very interesting structure of your firm salient and how there's a clear focus on things like infrastructure, MLPs, etc. But teams deploying interesting kind of niche into niche asset classes,

given kind of where you sit as the chief investment strategist at the top, I'm always really interested by how you interact with each of these individual teams, what you feel your guiding purposes in those interactions. what are you trying to do for them or on their behalf? And how has that been working in relation to this kind of goofy world? This goofy world. I love this question because what we've tried to do in the firm is an extension of what I just described about being profoundly agnostic about the world. And what do I mean by that?

What I mean is that I would say the typical structure of whether it's an asset manager or a hedge fund tends to be, pretty hierarchical, pretty pyramidal, let's say, where at the top, you've got the chief investment officer, or the head of the firm, the portfolio manager, the guy who has the view and the answer who has in the back of his head a algorithm for what's going to make markets tick, either overall or in his sector or what have you. It's kind of the great man theory of investment, which I would argue has really dominated so much of our structure, the business structure of how this industry has come along. What we tried to do at Salem is, I think, is very different. And instead of thinking of that pyramidal structure, to think instead of a hub and spoke, almost a wheel model, where

therein at the hub, not at the top of a pyramid, but there in the hub, is someone like me, who's actually managed money for a living, who knows intimately how hard it is to manage other people's money. But is there not to give you the answer with a capital T and a capital A, but to be a coach, really, to be a counselor for navigating a world where your internal algorithms, you're the PM of this group or that group, they're not working as well. And so our tendency is to flail out and say, oh, if I'm doing energy infrastructure, I think, well, I'm going to try to predict the price of oil. And that's going to tell me the answer for whether, you know, my company is going to do well.

And so I'm there to say, no, no, no, no, no, I don't know what the price of oil is going to be. You don't know what the price of oil is going to be. what you know how to do is how to analyze bottoms up the companies that you care about. And that's what you've told your investors you're going to do. I know how good you are at doing it. Let's go do it. So it's really being a coach and trying to prevent the very natural tendency we have that when our process isn't working as well as we'd like to, we start flailing and we start looking

for other answers with a capital A. And so this approach of profound agnosticism is to say, no, no, no, we believe in you in your process. You've said what you're going to do. Now let's do what you say. You began as, it sounds like, you know, doing equity by equity, long, short investing. And certainly from your writing, it seems now, not that you're not interested in the bottom up approach anymore, but certainly a lot of thinking, top-down macro-type stuff.

What is that tension like for you today? where do you think there's more value to be, I'll use the word alpha or differentiated return from let's say just like a passive, if you could somehow create a passive global portfolio of all investable securities. So deviating from that, you're trying to earn better returns or different kind of returns. Do you think top down factors are more useful? Or do you still think that, you know, company by company, bond by bond analysis is the way to gain an edge? Yeah, I'm pausing in my answer because I have a different answer for me personally, my company and for our industry.

I'll... I'll... I'll try to go. But I'll go in a kind of reverse order. I'll go for our world of financial advice, financial services first. And what I would say to you there is that Alpha is so rare. It's such a unicorn in public markets today that I think that less effort should be placed

there and that more effort should be placed on. proper risk allocation. Taking the right amount of risk is the most important decision that any investor, institutional, individual can make in our business. And I think that not enough attention in our industry goes to helping investors make that most crucial decision accurately and well, taking the right amount of risk. Do you think that just to pause there for a minute, you've also written a lot about the comparison of risk and uncertainty.

And I've spent a lot of time with some venture capital folks recently, and I think a lot of them would agree that it's the willingness to expose your portfolio and your dollars to uncertainty that results in these kind of occasional enormous returns. And I'm curious, as it relates back to the three-body problem, so getting your risk allocation right is the most important thing. But maybe there's the potential that we can't quantify or measure risk. And the future is uncertain. How do you do that?

Well, what I loved was you, in your introduction, they said you were talking to venture capitalists. And venture capitalist course operate in private markets as opposed to public markets. I absolutely believe, and this is how we're kind of making this transition from what I think in terms of our industry to the company I work for to me individually. We're kind of jumping to what to me individually here. There are absolutely still opportunities for private information, legal private information, hence alpha in private markets. A venture capitalist can know their companies, the companies that they invest in. They can play a direct role in how those companies are managed.

They can see at such a granular level what's really happening in that company's markets, its management and the like, all of which is now essentially illegal information to have about public companies. You cannot have that level of private information about public companies today. So alpha is private information, period, full stop. That's why it's so rare in public markets today. It's still possible if you get a different publicly available and yet not widely disseminated or widely appreciated information source. That source of alpha still absolutely exist in public markets, but it's very tiny.

So to your question about dealing with uncertainty and trying to overcome uncertainty through gaining private information, you're talking with venture capitalists because they can do that. And it's why I think that in your search for alpha, that is best budgeted for your efforts in private markets as opposed to public markets. What about taking into account the behavioral explanation for certain quantitative factors in a salient? It has kind of alternative beta strategies. So I'm sure you thought quite a bit about this. We'll take last year as the example. You know, the momentum factor ripped, right? It had a fantastic year.

And momentum's always an interesting one because it seems so incredibly adaptive. So it doesn't care what's happening in central bank policy. It bought the fangs early and it's held the fangs. And so maybe there's a powerful way around this. And I'm a subscriber to the behavioral reason versus the risk premium reason for why these things work. So how do you think about those things as true and persistent alpha sources? in public markets? I think yes. So I believe that momentum or trend is a thing. And that's the first thing you have to decide with someone. Do you think it's a thing or not? I do. I think it's a thing.

Why is it a thing? Because of fear and greed, because of human behavior. And that makes it a constant in a way that is separate from the gravitational impulses of central banks or this place. player or that player in markets. I think that there are so many of these behavioral aspects that we now have technologies like natural language processing and the like to try to see for the first time. So I think the most promising aspects of alpha capture in public markets is looking for these behavioral aspects of markets. That is exactly where, again, we're talking now personally and a bit for our firm as well. Where does alpha exist in public markets?

It's in these behavioral aspects. And we do have new technologies now that let us try to capture those and see those in ways that we couldn't before. So I always love the skin in the game question, which is to ask. So all of this considered, we'll keep going on some other avenues, but there's a good point to ask the question. All of this considered, how do you personally think about your investments? So what does your portfolio look like? three things. So it is private investments where I do believe that interesting, smart people can still legally find private information. And look, that can be something like, that's why I own the house

that I do, you know, the farm that I've got it, right? I've got private information about that. And that's a huge portion of my personal portfolio is where I live and where I've chosen to raise my family and how I've chosen to raise the family. That's that's the biggest investment I've got. And I feel like I've got private information on that legal private information, right? Where I think that I want to have a big chunk of my personal portfolio is what we talked about tapping the beta of global public markets. And there I'm not trying to kill it. I'm really not, because I'm not going to. I'm not going to kill it. I don't believe that there is an algorithm that gives me the answer for where public markets are going to be a year from now.

I really don't believe that that exists. What I do think I can do through a philosophy of profound agnosticism through a risk-balanced portfolio is that I can efficiently, i.e. cheaply, harvest those global markets. That's all I'm trying to do, just to cheaply and efficiently take whatever the world is going to give me in those public markets. And the third piece, and this is less of a dollar investment and more of my time investment, I absolutely think there's an opportunity to find alpha in public markets by thinking differently and freshly about these behavioral aspects of individual market behavior.

Let's talk about the farm for a little while. Sure, sure, sure. And the investing lessons that you've gleaned from your interactions with various different types of animals. So I'd love to start with bees. My son has a book, like a really thick, fascinating book that's the history of bees. And I've just always been interested in bees as a species. So maybe tell us a little bit about what got you so interested in bees and maybe pick a story to begin for how you find investing parallels. Well, you know, first of all, we call it a farm.

I mean, I've got to put it in air quotes. I mean, this is 44 acres in Fairfield County, Connecticut. So grapes of wrath material, this ain't, right? I mean, if I have a bad day, I can go to the local, uh, nice, uh, tavern and get my artisanal Craf beer, mezzal, yeah, you know, drown my sorrows, right, with a craft beer. So, uh, grapes of wrath material, this isn't. But as part of this investment in my family and how I want to raise, my wife and I want to raise our children, I think there are so many lessons about life, frankly, that one learns from working

with animals. And I do mean working with animals because a lot of these animals like bees or chickens, you know, they're not pets. They're there to they pay rent. I love animals that pay the rent. So we've got bees, we've got chickens, we've got goats, we've got sheep, we've got horses, dogs. They are part of the family, right? But it's been a magical experience and an important investment for family and the like. But to your point about taking lessons from this for investing, working with animals,

and the land and farms, it gives you such an appreciation for the cyclicality, certainly of nature, as we see in markets where there's cyclicality. It gives you such an appreciating. Land, the nature is very forgiving. And so are markets. The thing you can't do is just, and this is one of the early lessons that I got as a cub investor, you know, in this business is, you know, you always want to live to fight another day in investing. because there always is another day.

There always is another day. You never go all in with an investment. Never, ever, never. You always want to protect your reputation because that's the thing you can't recreate. Once that teacup breaks, you can't glue it back together. It's still a broken teacup.

So you never go all in with investments, and you always have to protect that reputation as your most precious thing. That is exactly what it takes to be a successful, I'll say farmer or anyone who works with the land. And so you see how markets and the land are actually have so many of the similarities. And what I've, I don't know, I've always had a knack for trying to communicate these observations. And I think that they're important observations about markets, but to express it in a way that connects with people.

The real use case for what I write with Epsilon theory, you know, most of the audience are financial advisors, professional financial advisors. And where I think what I do is useful for them is that it, it's not teaching them, telling them something they don't know. I'm not there to, you know, to educate people. I mean, that's a load of hooey. What I think I'm useful in doing is, is arming financial advisors with a way to communicate with their own clients, with a way to take these ideas like risk parity, which can seem so daunting and so, and often is intentionally presented in a daunting way. because the person presenting it to you wants to prove to you that they're smarter than you are. They understand, you know, well, if you look at implied vol on, you know, these asset classes,

surely you'll understand your Markowitz procedures require you to do X, Y, Z. And it's just a lot of BS. The whole notion between risk parity and risk balancing, it's just an old idea. It's an old, good idea with a little bit of a new twist, because we've got some new tools we can apply to it. That's all it is. And so what I find is that by communicating these ideas in terms of, God, sheep are the weirdest animals in the world. And this is how they act and they behave.

Or, man, bees are geniuses and the uses of their algorithms. When I can couch it in those sort of terms, it arms people to have better conversations with their clients. Frankly, it arms people to have better conversations with yourself. Because that's all of us, our real client, when we're talking about investments, the person that we have the most difficult conversations with is not someone else,

but it's always ourselves. It's always ourselves. Because we've got these ideas in our head, the algorithms, these theories of how market should work. And it's so hard to think critically about yourself and to apply that same sort of rigor, intellectual rigor to our own internal conversations.

That's the hardest part about being an investor, but it's the most important, too. And that's what I think I try to accomplish by talking, by couching these stories about markets in terms of what I see in the animals. There's this kind of undercurrent of, in the algorithm idea, specifically when you talked about bees and how bees can notice the day where basically past the solstice that they need, I think it was past the solstice or some point where they need to begin preparing for the winter by watching the sun. Basically, like they're able to calculate.

They can measure the angle, the angle of the sun's rays. Isn't that wild? It's amazing. It's amazing. But that's exactly what they do. It goes beyond their preparations for winter. Actually, the bee's brain and its compound eye is designed to do two things really effectively.

One, it sees motion very effectively. That's what the, the compound eye is amazing for detecting motion. at infinitesimal motion and measuring it really precisely. So whether that's another insect, whether that's the wind, whether that captures motion really effectively. And the other thing it really does well is measure the angle of light. It's just the, you know, this is how the bee's nervous system and an eye evolved is to measure angles of light amazingly well.

So that's what they use actually to navigate. They have pretty amazing memories. And they, you know, they have the famous bee dance that they used to communicate these observations to other bees. But, you know, to go from the hive to the water source or from the water source to a clover patch, it's all calculated based on light angles. And so kind of trivially, basically for bees, because they can remember this, they've got a simple algorithm for when they need to start preparing for winter. And that algorithm is the sun is at the highest point in the sky, northern hemisphere on June 21st.

So every day, every B, sees that angle of the sun. And if today the maximum angle that the sun achieves during the day is less than the maximum angle yesterday, we are now past the summer solstice, which means that summer is on the way out. So their entire repertoire of behaviors, hardwired behaviors to start preparing the hive for winter begins precisely on that day. It's crazy, but that's exactly what they do. It strikes me as like in some ways a risk mitigation strategy that they don't overextend themselves. They start preparing at the right time. That's totally what they are.

They're risk managers. Yes. They're amazing risk managers. And they have, you know, other algorithms so that if you get an Indian summer, you know, where the, summer lasts longer than you expect or if it comes earlier, they have ways to take account of temperature and wind patterns and stuff like that to adjust their trade. Because they're making a trade based on the summer solstice. And they manage the basis risk of that trade.

Can you define basis risk for anyone that's unfamiliar with that? Oh, sure, sure, sure. That's what I tried to do in the note. So again, basis risk is one of these $10 phrases that we use in a date. Something very simple. It means something very simple, right? All basis risk means is if you've got you've got something that's related to something else. A derivative. A derivative. So I really care about the what we call the underlying thing, you know, the price of the stock. But I think I've got in my mind that there's a relationship between the price of a stock and something else, a derivative, a signal.

The basis is simply the strength of that relationship. And so basis risk, means that, well, I shoot, I thought that those things would, you know, move hand in hand or hand in glove. But actually, oh, it's a little bit tenuous. That means you're suffering basis risk there. So in the case of the bees, it would be, you know, what they really care about is the temperature. Yeah. They're using the change in light as the indicator of the change in temperature. But that, that relationship could be off year to year. Yeah, yeah. But it's not going to be off a lot. It's a manageable basis risk. So in Connecticut, cold weather. going to start hitting, call it October. And so you've got from June 22nd to October,

maybe the first freeze comes a week early, maybe it comes a couple of weeks late. That's basis risk, whether it's a little bit early or a little bit late, but it's manageable basis risk. What we have an investment so much today is a unmanageable basis risk because it's basis uncertainty. We don't know if winter's coming or not, right? We don't know if quality is ever going to matter again. And it's like the Game of Thrones, where winter can last for five years, where the weather patterns are so unpredictable. It'd be really hard for bees to survive in that environment. And that environment, that Game of Thrones weather environment is what we as investors find ourselves in today.

I love this concept of, I've been thinking quite a bit about risk and investing versus personal risk. And one question I love to ask is for the time or times that you have, you feel as though you've been most personally at risk or put the most on the line, felt the most exposed, hopefully in a good way, with some decision that you've made where sometimes, you know, taking big personal risks is better than taking huge portfolio risks. I'm curious if you, curious if you agree with that idea and then to hear an example of a time that you felt like you took a huge personal risk. So I'll give you two. And they're both connected with the business. of investing, the business that we find ourselves in. The first would have been in September of 2008. And I'm running my long short fund.

I said, we killed it in 2008. We're long short. We're actually net long for the whole year, and we were up 20-something percent. 20-sund percent in 2008. And what we did, and so in September, and I discovered credit default swaps. You know, it was a broken instrument then.

it's a broken instrument now. But when you're short something, which is being long or credit default swap, you're shorting the credit of that company. Being short is all about timing. If you're wrong on timing and you're short, you're just wrong. But if you're right on timing, well, you're right. And I just nailed it. So the positions we had taken, we were just where everyone else is in crisis around us. And, you know, this is at a big long only shop.

You know, in our fund, I mean, we were absolutely. absolutely killing it in September of 08. And I remember thinking one day, you know, it's, you know, what you do, you're thinking about, oh, what I made the returns a day, you know, if this happens, we're going to make this much more money. And, you know, that's the calculus that all of us go through in our heads in this business. Because we had taken a big position and all this. And that's when it kind of hit me, which is that, well, shit, if the whole system goes down, I'm not going to make any money.

I'm not going to collect anything. And this was, you know, I think why Warren Buffettly famously sold all these naked puts on the S&P 500, right? Which is that, well, they don't bail me out. If they don't bail the system out, none of this is going to matter anyway. And I remember what a chastening moment that was because I had gotten so wrapped up in the success we were having in our own fund. and but but you know kind of stepping back to think that pressing that position here was essentially betting that the whole system would collapse and if the system collapses well your fun doing well won't make what matter right it it reminds me of people you know who want to own physical gold

which i understand the impulse i mean hell i'll you know have a farm right but if we're at a point where that's what matters where physical gold matters right I don't want to have physical goals. I want to own bullets and seeds. You know, that's what I want to own. So there was that moment that I talk about kind of personal risk and and kind of rethinking the bigger picture of what we're all doing here.

And the other example I'll give, it seemed like a huge risk at the time. And that's the point where we gave all the money back in the fund because it just wasn't working. and I needed, you know, again, we weren't losing money for clients and the way our business works. If you hit the ball down the middle of the fairway, you can do well in our business. But it wasn't honest. And I thought I was taking an enormous personal risk by winding down, you know, a successful business.

In truth, it was the best thing I did could have done. You know, you give your money back to your clients before they lose money. When you're honest with them and yourself that there's something not right here and it's not working. And so I often try to tell that story to people who are coming in the business or the like. And it gets back to this notion of your reputation is the one thing that if it gets broken, you can't put it back together again. So whatever risks you think you're taking to protect that, it's in a bigger scheme. It's not a risk at all, or it's certainly the smart play. Let's come back to the farm for a minute.

Yeah, sure. And this idea of fingernail clean. I loved this analogy. Oh, thanks. Thanks. Yeah, that comes from our chickens and our eggs. One thing you learn from living in the farm is that you see the way that you've lived in the past. things you've taken very much for granted.

And you say, oh, I took that, that's not where meat comes from, you know, right? It's not, it doesn't just appear magically in a, uh, cellophane wrapped, you know, little package all neatly, you know, with no blood. And like, no, that's, that's not really where, where meat comes from. And again, this is part of how I wanted to, to raise our kids so that they really saw the underpinnings of, of, of our world for all, you know, warts and all. Right? I'm a meat eater, but I own it. I think that's the most important thing about whether it's raising kids or how you interact with others is do what you're going to do, but own it. Own it.

And that's true for so many things, but the example I wrote about to try to illustrate this example of how we've come to think of so many things as normal and natural when there's anything but is the notion of the egg. What's a good egg? All of us, or most of you, we buy our eggs at the supermarket. And it's wonderful. They come in these, these packages. They're all so clean, just, just scrubbed clean and they're all nice and cool and refrigerated. And so we think, well, that's what an egg should be. It should be just scrubbed clean and cool to the touch. Of course, that's what, that's what a good egg should be. And that's absolutely untrue, absolutely untrue. So a fresh egg, an egg that's laid

that morning, it's got some dirt on it. And by dirt, I mean chicken poop on it. Right. And, you know, my kids do all the works. They collect the eggs in the morning, bring them in. And there's nothing better than that fresh egg. There, there's nothing better. It just, I don't have to describe all that to you. But you don't refrigerate a fresh egg. You keep it out on the counter, because you don't need to refrigerate a fresh egg. You also don't need to scrub and wash a fresh egg. In fact, you don't want to do that. Because when, when eggs are laid, they have a thin antimicrobial film on it called the bloom. You know, this is, this is how nature works. It's incredible. It's incredible. Because you don't, if the egg were to hatch, you don't want that

baby chick coming out into some, you know, bacteria infested shell that it comes through. You don't want the chick to be sick. So, so nature has that protection. They have an antibacterial film on freshly laid eggs. Well, if you scrub it, you wash it really, really clean, it washes that all off. And then you do have to refrigerate your egg because it can get bacteria and other stuff growing on it. Now, I don't want chicken poop on the eggs I've got either. So what you do is, you know, maybe you get a little bit of wet on the most soiled areas, but use your fingernail. You just get it fingernail clean. You just scrape it off. And then you keep it on your kitchen counter and it can stay that way for six weeks. And it's going to be the best egg you ever

had. So why do we have refrigerated scrubbed eggs? Because our eggs come to us from factories, from from egg factories, where you have tens of thousands of chickens that are kept in their one square foot area and never move, never leave. The food comes to them. They lay the eggs there. There are horrible diseases in bacteria there. The temperatures for storing the eggs for transport later can get really high. So yes. it is industrially required to scrub those eggs and get the dread diseases that you get in a protein factory off of them. And it is required to refrigerate them because that's the only way you're going to keep them from decaying before they're delivered to the supermarket. So this freshly scrubbed, cool to the touch egg, it's not there because that's what makes for a good egg.

it's because that's what's required for mass-produced industrially sufficient egg production. And so that was my example. You know what else is like that? ETFs. ETFs are an industrially necessary thing. They're convenient. It's like going to the supermarket and I can buy my carton of wonderful eggs. but an exchange traded fund to put a fund so that it can trade daily like this.

This was not invented because it's good for investors. It's invented because it makes money for market participants. My God, right? You know, it's, and again, I use ETS all the time. They're wonderfully convenient. Like I'll still go to the grocery store. The hens didn't lay enough. I got to buy some eggs.

But we make this mistake all. the time, whether we're thinking about our educational system, whether we're talking about our political system, whether we're thinking about our market system, where the things we take for granted and the things we think are natural and correct are merely industrially necessary. It makes me think that perhaps one marker of the measure of potential quality is things that can't or don't scale, right? Amen, brother. That's right.

If it can't scale, it doesn't mean it will be high quality, but maybe that it can be high quality. And it makes me wonder back to our discussion on quality factor itself. I think about this a lot as a quant. So we're not dealing in really in individual securities. Of course, that's the unit of expression of a factor. But we have to build baskets of these factors. And people are more and more aware of these factors. And it's a really interesting question. Like does awareness destroy alpha? In certain cases, I would argue the answer is no, it won't because of behavioral reasons. Because of behavioral reasons. Like we were talking about earlier. But quality is super interesting because actually, I don't want to own high quality stocks because empirically they haven't done well,

not just in this period, but on a much longer term basis. I definitely don't want to own the absolute worst quality stocks. Those seem to do quite poorly. But the highest quality stocks, maybe there's no just simple one formula that can capture that. Maybe it really does require, and I'm certainly not an advocate of fundamental discretionary stock picking. In fact, I think it's terrible. But perhaps to find the diamond in the rough and find the quality, it can't scale. It can't be a neat packaged ETF or formula. You know, Patrick, what I think is a hallmark of, I'll call it the modern economy, particularly when we're talking about publicly traded securities, is the need,

the absolute requirement of these companies to have enormous scale. And I'm talking about our business, too. I'm talking about our business of financial services as well, that it's never been more crucial to have scale, scale for the sake of scale. is the only way to survive, I think, in so many aspects, even of our business, certainly the asset management business. I think it's different to your point about quality not scaling. There are aspects where quality can be rewarded and where it doesn't scale, like in a direct relationship with a client, right, with a financial advisor as a very good close relationship, a quality relationship with their client. that doesn't scale. And it means typically that that's not going to be a multi-billion dollar business,

which means it's not going to be a public listed company, but it being a great private business. And this gets back to this notion of where I think alpha opportunities, quality opportunities, are mostly in private markets as opposed to public markets, because you have to have scale to succeed in public markets today. or rather it's just so difficult to survive if you're not. And I think it absolutely goes hand in hand with this notion of quality, that quality, at least the way, quality like beauty is in the eye of the beholder, so much of what I think about quality and I think you're the same way, it doesn't scale.

It doesn't scale. It's a good business lesson even in scaled up business models or businesses. Yes. That just doing things that maybe only you can do because of a unique set of abilities or skill set, it seems like it's always a good bet. And we tend to do things. We tend to be imitative species, right? Do stuff because other people are doing it. Just ate what other people are doing. It's a great algorithm. Yeah, it's a great algorithm for basic survival. But not so great if you want to differentiate yourself in any interesting way in your business. Correct. That's exactly right.

So great advice on the idea of quality. I'm curious what in markets in general can be anything. Has you most interested other than the kind of three-body problem, which I know is a of recent interest. What one other topic are you crunching through? You mentioned we started the whole conversation with this love of puzzles. What is what is the current puzzle that has you most interested? Understanding the role of narrative figuring out the rules, the computational rules of narrative. And so this goes under that heading of natural language processing. And unfortunately, not unfortunately, I'll back up a second. There's another, you know, big buzz phrase in our business today, any business, artificial intelligence. I'm very excited about that. And I think there's a big

opportunity here because I think it's largely misunderstood in our business. So I'll put it this way. Artificial intelligence will not make your regressions run any faster. Right. If your business model is to find these arbitrage opportunities that are increasingly vanishingly small, either in time or in price, behind this data series and that data series, this structure data series and that structure, data series, artificial intelligence doesn't help you. Neither is machine learning or any of this other stuff. So when you're, when you take these vast computational arrays and you try to apply it, this gets back to the three body problem, when you try to apply it to historical data to look for the answer or the pattern or the algorithm, you're going to be disappointed. You're not going to

find it. But artificial intelligence, where it is useful is for is usefulness and it's in looking at unstructured data, like the ocean of words that we have, all the things that they're going to say on CNBC today, all the things that are going to be printed in the Wall Street Journal today. Classifying stuff. Yeah. In Game Theory, we talk about missionaries, about, you know, a famous investor like Warren Buffett and how what he says, how that narrative or that story, how it rolls through markets, or how what Janet Yellen says or, you know, the latest Fed governor comes out, what they say, how it rolls through markets. So what I'm saying where there's not trusting the algorithms in my head,

I don't mean that there aren't patterns to the world into nature. I think that we've got, though, this new technology through artificial intelligence and natural language processing to actually start seeing some of these patterns that we've kind of waved our hands at in the past and actually start trying to understand them. not for crunching through structured data, not from finding patterns in historical price or volume or series, but for finding forward-looking behavioral patterns, again, that's where I think alpha can still exist, that's driven by the way we are impacted by, the way we are hardwired to respond to the things that people say and tell us. I've written a good bit about this,

but that's where I'm really excited about the new technologies that are available. It's like when they, Leuvenhook, you know, invented the microscope and put a slide of dirty river water underneath it for the first time and saw this whole new world, this microscopic world, or applying a telescope and looking at the sky, I think that what artificial intelligence does is it allows us to see these oceans that we swim in, of words and communications and lets us visualize that and make sense of it really for the first time.

That's what I'm excited about. Really fascinating. It's crazy stuff. How personally do you approach trying to understand that problem? And what are you optimizing for? What are you trying to come away from it with? A tool that you can use in the investing world or just an understanding of the world? What's the outcome that you're after?

Here's what I'm not after. What I'm not going to come up with is a formula. I'm not going to build a regression analysis of structured data out of this. That's not how it works. That's not how game theory works. It's frustrating. It's really frustrating about game theory because most games have multiple equilibrium, multiple outcomes. And, you know, if you give me a game and there are a couple of equilibria and you say, okay, what's going to be the outcome?

You know, what's going to happen in markets tomorrow? And it's like, I don't know. I know it's going to be one of these multiple equilibrium. about I don't know which one. And game theory cannot tell you what the outcome is going to be. It's not part of the game. But what it can tell you is how is the dynamics of the game. It is a tool for looking forward and not way forward, but tomorrow or, you know, next week for understanding the human dynamics of a system.

So it's never going to give me that I now have. have the answer where I'm going to invest in X, Y, and Z, and, you know, in six months, I'll knock down these profits, right? It is going to make me a better investor, though, because I'm going to understand as it unfolds, and I'm able to talk to my clients and the people I care about, about the process and the dynamics of what's happening. Again, it's part of being adaptive and agnostic, but that doesn't mean that I'm going to just stick my head in the sand and say, well, I'm just going to give up. I do think we have these tools and these technologies to see how is it playing out and be adaptive enough to react to that. So two closing questions for you.

Yeah, sure. The first is to ask what the most memorable individual day was on your farm. Frankly, it was a sad day because that is one of the things that you think you know intellectually that animals live and they die, but you don't know it emotionally. And it, and it's, And I wrote about it in a piece because it's similarly with our investments. I mean, we have a hard time saying goodbye to our investments. But investments have a life cycle also. And we've got to be not just intellectually aware of that, but come to grips with that emotionally. So the hardest days on the farm are always when one of the animals dies.

And there have been a couple that have been particularly, you know, unpleasant because that's how life is. It's messy. but you have to own it, right? And you have to deal with it and treat the animal as well in death as you did in life. So that's the hardest days on the farm. And it's the hardest days in our investments also. But we've got to own it and we've got to take grips, come to grips when things don't work as well as when things do. My closing question, which is the same question for everybody, is for the kindest thing that anyone's ever done for you.

They're kind of easy answers. like when my wife said yes, you know, you know, that was very kind of her. You know, I can, I can also think of things like the tough love kindnesses, but, but frankly, and it's, it's, you know, I've had this, these, I think we've all lived with these situations in both business and in, in our personal lives. And again, there are a couple of these moments. The kindest moments, the most human moments are when you are forgiven. And, you know, those are very special and very human. And it's important, I think, to remember in our actions towards others that that's the greatest

grace we can give is to forgive. Fantastic. Great place to close. Such an interesting conversation on quality and all these great ways of looking at markets kind of through analogy. This has been edifying. Thank you. Well, my pleasure.

Anytime. Thanks for having me. Hey, everyone. Patrick here again. invest like the best, go to investorfieldguide.com forward slash podcast. If you're a book lover, you can also sign up for my book club at investorfield guide.com forward slash book club. After you sign up, you'll receive a full investor curriculum right away, and then three to four suggestions of new books every month. You can also follow me on Twitter at Patrick underscore

Oshag, OSHAG. If you enjoy the show, please leave a quick review for us on iTunes, which will help more people discover invest like the best. Thanks so much for listening.