In this episode of The Acquirer’s Podcast Tobias chats with Dr Ben Hunt from Epsilon Theory, which is Second Foundation’s principal publishing brand, a newsletter and website that examines markets through the lenses of game theory and history. During the interview Ben provided some great insights into:
- A Layman’s Version Of Game Theory
- The Narrative Machine & Big Compute
- Recognizing The True Threat Of Coronavirus Before Most
- The Next Time You’re Reading Something Ask Yourself – Why Am I Reading This Now?
- Gell-Mann Amnesia
- A Visualization Of The Narrative World
- We’re At One Of Those Periods When Thinking Differently Matters
- The Genesis Of Epsilon Theory
- Visualizing The Unstructured Data That We Swim In
- Life Has Changed Forever
- Clear Eyes, Full Hearts, Can’t Lose
References in this episode:
Manifesto (Epsilon Theory)
The Narrative Machine (Epsilon Theory)
Gell-Mann Amnesia (Epsilon Theory)
You can find out more about Tobias’ podcast here – The Acquirers Podcast. You can also listen to the podcast on your favorite podcast platforms here:
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Full Transcript
Tobias Carlisle:
I’m not going to go to my hanging crying. I’m going to go laughing. So when you’re ready, sir, let’s get underway.
Dr Ben Hunt:
I’m ready.
Tobias Carlisle:
Hi, I’m Tobias Carlisle. This is the acquirers podcast, special edition, speaking to Dr. Ben Hunt of Epsilon Theory. We’re going to talk about his background, about the site, about the narrative engine, about coronavirus. We’ll be talking to him, right after this.
Speaker 3:
Tobias Carlisle is the founder and principal of Acquires Funds. For regulatory reasons, we will not discuss any of the Acquires funds on this podcast. All opinions expressed by podcast participants are solely their own and do not reflect the opinions of Acquires Funds or for it, for more information, visit acquirersfund.com
Tobias Carlisle:
Hi Ben. How are you?
Dr Ben Hunt:
I’m great. Tobias, how are you? Thanks for having me on.
Tobias Carlisle:
My absolute pleasure. I’ve been reading your stuff for quite a while and I’m absolutely thrilled to be chatting to you. Just so folks can contextualize you a little bit. You’re a Harvard PhD in 1991?
Dr Ben Hunt:
Yeah, I don’t admit that to many people. That’s the old thing. If you went up to Harvard, you say you went to school in Boston or something like that, this situation.
Tobias Carlisle:
A little social science school in Boston. Isn’t that the way?
Dr Ben Hunt:
Yeah, yeah, exactly. And to make matters worse, I got my degree in, well, everyone else calls it political science, this oxymoron of political science. But the really bad thing is that my field was econometrics and statistics, so people get that. But the main thing I worked on was game theory. And of course, that’s the old line these days. Oh, now let’s apply some game theory. So, I can’t even tell people what my real field of study was, without people laughing. But yeah, that was it. That was it.
Dr Ben Hunt:
I was an academic professor for 10 years. Defrocked now, once you leave the university, you can never go back. It really is like leaving a church. There’s a lot to say about that, but, I always had the entrepreneurial bug and I think a lot of your listeners and probably you yourself, understand that, it really is a bug, it’s not a feature, right? You just can’t help yourself.
Tobias Carlisle:
I think it’s factory installed though. I don’t think there’s anything you can do about it.
Dr Ben Hunt:
There’s nothing you can do about it. You were born that way for sure. So I had started a company in grad school. I started a company when I was a faculty member. And finally I just realized I had to succumb to that entrepreneurial virus. And so, I left a tenured spot to start a software company and moved back up here to Connecticut for that. That was in 2000, moved back up here. I’m originally from the South. I’m from Alabama, the heart of Dixie. That’s what it says on our license plates, anyway. And so, I’ve been up here in Connecticut with my family for the past 20 years. We did well with the company. I sold my stake in the software company that we started.
Dr Ben Hunt:
And from there I decided to play the biggest game of them all. The old game theory again, right? But the biggest game in the world is the game of markets, of political markets, of investing. So I had the opportunity to join an asset manager, start a hedge fund there. And we did really well. I don’t know that it was… why did we do well? We did well because there are times in the world where thinking differently matters. And the years leading up to the great financial crisis itself, that was a time when thinking differently mattered.
We’re At One Of Those Periods When Thinking Differently Matters
Tobias Carlisle:
I think Ral Powell, describes that as fat tails approach run.
Dr Ben Hunt:
Yeah, right, right. And we’re at another one of those periods of time I think, where thinking differently really matters. So that’s why I’m so happy to be on your show. And it’s what I do now. I write, I do research and about, I think, I hope thinking differently about investing, but about the way we live our lives.
Tobias Carlisle:
Let me just ask you three quick questions.
Dr Ben Hunt:
Sure.
A Layman’s Version Of Game Theory
Tobias Carlisle:
Can you give us, is there a layman’s version of your game theory that you can, is there some way that you can articulate it for us, without us needing to be John Nash?
Dr Ben Hunt:
Sure. Game theory is strategic interaction. Just like the tango, it takes two to play a game, and all game theory is, is trying to be rigorous. That what you do may well depend on what you think I’m going to do. And what I’m going to do may depend on what I think you’re going to do. And both of us understand that the other one is thinking the same way. Game theory at its core is this understanding that you’re actually, you’re not smarter than the other guy. That we’re all able to think strategically.
Dr Ben Hunt:
And we’re all immersed in this idea of, well, I’ll do this if he does that, but he’ll do this if he thinks I’m going to do this other thing, you would think that might be random or infinitely recursive at least. And it’s not. There are rules to that, rules based on how we as human beings are hardwired, rules based on rationality and information flow. That was probably a more than a thumbnail sketch. But that’s what game theory is. Just trying to figure out those rules.
Tobias Carlisle:
There’s some famous versions of it, right? There’s prisoner’s dilemma, where each one has the incentive to rat the other one out. And so if you play that out to the end, they both rat each other out. And then there’s prisoners revenge, I think, where the gang can find the guy who gets out. And so that changes the dynamic a little bit. And then there’s also, I forget what it’s called.
Dr Ben Hunt:
Chicken.
Tobias Carlisle:
Chicken.
Dr Ben Hunt:
Chicken is a famous as well.
Tobias Carlisle:
There’s one with two lovers, who they’d rather be together than apart. And so, that changes how their incentives are, when they’re trying to decide what they’re going to do. What was your area of study in particular? If that’s not too technical.
Dr Ben Hunt:
No, it’s not technical. We’re all familiar with these, let’s call them two person games, two player games, because they’re fun. We all know examples of them. We all see examples of them in our media, our culture, right? So the prisoner’s dilemma game is at the heart of every police procedural, every CSI, every NYPD show. It’s based on a prisoner’s dilemma. Chicken is also a wonderfully evocative game, because we’re all familiar with it, right? From Footloose, to an older generation, rebel without a cause. These are all good examples of the game of chicken. But what’s really powerful to get back game theory, is it’s not these two person games, as fun as those are to play. Game theory can say so much about how we act as a crowd.
Dr Ben Hunt:
Right? So, what is our crowd behavior? Are there rules to the way investor behavior works? Right? Are there rules to the way that political behavior works? Those are such powerful forces in our lives, right? Are there rules the way our families work? It’s these group dynamics, that I think are so powerful. We tend to wave our hands at these group dynamics and we say, Oh, it’s chaotic or random, or who can figure that out. And the fact is, there are these games that are played as crowds, and trying to figure out those rules, man, that’s at the heart of, I think playing the game of markets, playing the game of the elections. So, that’s what I really try to write about. And what I really tried to study.
Visualizing The Unstructured Data That We Swim In
Tobias Carlisle:
And what did your software firm do?
Dr Ben Hunt:
Well, it was very boring software, which is why I was successful. Right?
Tobias Carlisle:
I love it.
Dr Ben Hunt:
So, we started the company, it was March of 2000, pretty much to the day that the Nasdaq bubble burst, in March of 2000. We started this company and we’re looking for investors. And we were successful because it was boring software. It filled a very specific need for, tell you it’s boring. Construction equipment, rental owners. So Cat rentals or United rentals, construction equipment. It’s like homeless people. Once you start looking for it, you see them everywhere. And there are so many things in life that are like that. We just take them as the fabric of our lives and to our detriment. We don’t notice them. And I can give you a silly example, like construction equipment, which is actually everywhere.
Dr Ben Hunt:
Once you start looking for it, or a non silly example, like homeless people, who are also everywhere and we ignore them, we don’t see them. And that’s that’s a tragedy. And it’s why it’s so important, I think, to open our eyes and to see what surrounds us. But to your question, it was trying to make sense of unstructured data for construction equipment, rental companies. And the unstructured data that they work with are, parts diagrams, schematics, right? Pictures. A picture is a form of unstructured data. Today I work a lot with text and what we say and transcripts of what you hear on CNBC and the like. That’s another form of unstructured data. But this common thread through all of my work, my academic research, a software company, the investment philosophy and research there, is all about to see, literally see, literally visualize, the unstructured data that we swim in.
Dr Ben Hunt:
It’s the water in which we swim. And we don’t pay attention to it, because it’s the water we’re swimming in. We don’t pay attention to all the messages that hit us every day, through media, through our friends, our family, the average human being. You’ve done some work in this, we receive about, it’s some crazy number, 7,000 messages per day, and we don’t count them. It doesn’t really feel like we’re receiving messages, but that’s exactly what’s happening to us. I mean, think about, as you know, how many minutes in the day, waking minutes in the day, are you not hearing some human instantiated message, right?
Tobias Carlisle:
Not many.
Dr Ben Hunt:
If you take a shower, right? Maybe not the shower, maybe even that if you’ve got a radio player, right. It’s crazy when you think about it, but that’s what my research is all about. Trying to visualize, trying to understand, what are the rules then for how this unstructured data impacts us, affects us as a crowd. That’s game theory. That’s unstructured data. That’s what it’s all about.
The Genesis Of Epsilon Theory
Tobias Carlisle:
And I’m going to move on to Epsilon Theory in one moment just, but just, could you give a little more detail on the fund? Was it was a short biased of volatility or was it a blowup fund or what were you running?
Dr Ben Hunt:
No, no, no, it was just a long, short, equity focused fund. Started with some employee money at the firm, that we started in 2005. And like I say, they’re periods of time in the world, where thinking differently really matters. And we were able to think differently. I don’t come out of wall street. Right? And there appears a time where that’s a real advantage, because you’re not immersed, you’re not bathed in what wall street is all about, which is selling, and to sell, you have positive news. You’re looking for reasons to buy. And not coming from wall street, I was wired very differently. I was looking for the flaw in things, reasons to sell. And that was the skillset that was so helpful in 2008, 2009, and I think that skillset that’s really helpful today. My favorite comic book character is one of the Inhumans.
Dr Ben Hunt:
So this is in the Marvel universe. The Inhumans, there is mutants, right? And one of them is named Karnak, right? And the conceit with the Inhumans, is that you breathe this gas and it triggers this mutant ability and everyone has one ability, right? And maybe it’s what you’d call count the spot on the wall ability, or I can make a spot up here on the wall, useless. The King is black bolt, right? So his voice, the merest sound that he makes, he this vast destructive, beam of energy, right? So this guys Karnak, and nobody really knew what his power was, and it turns out, his is the most powerful ability of them all. Karnak can see the flaw in all things. Just that, and that’s just the coolest power, right, in a comic book.
Dr Ben Hunt:
I’ve often thought that that’s, that is what it’s like to be a short seller, right? Is everything’s got a flaw, can you identify the flaw in all things? So anyway, I’ve got a big poster of Karnak in my office. That’s my mentality with this stuff.
Tobias Carlisle:
I love that. What is Epsilon Theory and what was the reason for starting Epsilon Theory?
Dr Ben Hunt:
Well, the reason for starting Epsilon Theory is that, my hedge fund stopped working, right? We never lost money for clients. We did great in 05, we did great in 06, we did great in 07, we did great in 08. And then, in March of 09, it’s like you went to the wall and you just flipped a switch on our returns. Our returns flat-lined. Again, we never lost money for clients. And I’m so proud of that. But what we did, no longer worked, right? Our long positions went up. Like everything else went up, our short positions got killed, like everything else. And like I say, we didn’t lose money. But it wasn’t working. It wasn’t working. And what it was, was fundamental analysis, looking for catalysts, all the stuff that we talk about with discretionary investing.
Dr Ben Hunt:
And so we gave all the money back to our clients. And that was the hardest thing professionally I’ve ever done. Frankly, it was probably the smartest thing I’ve ever done, because those clients are loyal for a lifetime. And so, I was trying to figure out, well, how does investing work? How do you invest other people’s money? What works today? So this is at the end of 2011, going into 2012. And so, I went back again to this thread that’s always gone through my research and my life, my professional career. I’m saying, well, what seems to have changed, is the impact of narrative, the unstructured data that we’re hit with. It’s so potent today. And it’s potent, because the ground doesn’t seem steady beneath our feet, meaning the fundamentals don’t seem steady and yet prices are going up. How do we account for that? And so, I started writing this blog, and I grandiosely titled my first piece of manifesto.
Dr Ben Hunt:
I mean, how pretentious is that right? To call it a manifesto? But the name, Epsilon Theory, it goes back to that fundamental econometric formula for explaining portfolio returns. Yeah. What explains the money that you make or you lose? Well, we’ve got alpha, right? That idiosyncratic performance of your portfolio. You’ve got beta, which is, well, that’s your portfolio going up or down with everything else, with markets in general. And most people think, okay, yeah, that’s the formula. It’s alpha and beta. Those are the two components. Well, actually, and this is true for almost all econometric formulas. There’s a third little Greek letter tacked on at the end, Epsilon, and that third little letter tacked on at the end of almost every econometric formula is Epsilon E, for error, right? Epsilon is what’s left over from your alpha and your beta.
Dr Ben Hunt:
Everything else is just in this bucket of rain. It’s like, well, that’s just random error. That’s just, who knows? That’s just, no one can know that. Right? But here’s the truth. Inside that Epsilon bucket, is everything that we talk about when we talk about behavioral economics, is everything that we talk about when we talk about playing the player, every good trader in markets, he or she, they know how important it is, not just to play the cards you’re dealt, but also to play the players, right. And that’s nowhere in alpha, that’s nowhere in beta. It’s all stuck in this bucket of Epsilon for error. And so my manifesto was about, well, let’s dig into this error bucket a little bit, because I think there’s some real rules that can help us understand strategic behavior, playing the player, to use that poker analogy and not just playing the cards. It’s all in that Epsilon bucket. And my job, my goal is to try to pull some of that out.
The Narrative Machine & Big Compute
Tobias Carlisle:
That’s fascinating. One of the interesting visualizations that you put on Epsilon Theory and you discuss it regularly, the narrative machine or the narrative engine as that’s reflected in that graphic. Could you explain to us what that is and what is the purpose of it? What’s its function?
Dr Ben Hunt:
Sure, sure. Well, as I described earlier, what I really want to do in my research is, visualize, and I mean that literally, visualize the unstructured data that surrounds us, the water in which we swim. And this is an idea. It’s not original to me by any stretch of the imagination. So, when I was doing my dissertation research, and I wasn’t applying it to investing, I was applying this to public opinion being mobilized for countries that were going to start a war. And the idea was, well, we should be able to see some signs of governments making this effort, to try to rally public opinion before they start shooting at someone.
Tobias Carlisle:
They demonize the other side.
Dr Ben Hunt:
Exactly, exactly. There’s got to be a reason, even if you’re a dictatorship or the like, you still care, you still want public opinion to be on your side, before you start something risky, like start a fight. And so, we should be able to see that in newspaper editorials, right? So, places where governments are able to get their opinion out there. And so again, this isn’t a new idea, and again, it wasn’t original to me, it’s been out there for a long time. The problem we had though with visualizing this, with applying, I’ll say science to this, was that, until recently, it was just so hard to measure. Measure is the wrong word.
Dr Ben Hunt:
It was so hard to collect. When I was doing this research, 30 some odd years ago, I would hire undergraduates to go into the bowels of Widener library and read microfiche. And then translate these editorials written in Spanish or German, and then I would write out the code for this on a digital equipment mini frame. I think I used Pascal. And all these words I’m using will be jibberish to half of your listeners here. Right? Pascal? What’s that? Right? I would have used for triad, but anyway, that’s the long story.
Dr Ben Hunt:
I mean I was doing this pit stop before R was around. It didn’t exist. Today, not only do you have big data, meaning I can tap into Dow Jones, I can tap in to Thomson Reuters, I can tap into LexisNexis and everything that was published in the world is available to me. Boom. Like that. It’s all there. It’s all there. Right? Even more importantly though, it’s not big data, it’s big compute, because at the core of how you visualize, how you measure, how you analyze vast quantities of text, that’s quantities of unstructured data. Frankly it’s not AI, it’s not machine learning. it is brute force computing, processing power, which we now have available to us in unlimited capacity. Right?
Dr Ben Hunt:
So, for me to be able to just, plug into the wall and get as many flops and processes as I need from AWS or from Azure, I mean, that’s what makes this possible, because what we call natural language processing, again, it’s not complicated, right? Here’s what you’re doing. You’re taking a bag of text, right? A bag of words, an article, a transcript, what have you, and you want to compare every what we call an engrams, a word or a phrase, every word or phrase within that bag of texts. And you want to compare it to every word or phrase, every engram and another bag of text, and to another and another and another. Again, it’s a simple comparison, right? But the numbers, because this is a factorial becoming incredibly large.
Dr Ben Hunt:
So for example, let’s say I’ve got a thousand articles, each article has a thousand words or units of meeting, a thousand engrams. That’s a thousand factorial. That’s half a trillion calculations. And I need to be able to do that like that, and a thousand articles with a thousand words, that’s small, right? We’re dealing with 10,000 articles, each with, unknown, a lot of words in them. So it’s not just big data. What’s even more important and this is what’s really been available to us. Just sort of the last three or four years and changes everything, is big compute. Because once then you create these giant matrices, which are all the connections. And that’s what we’re measuring. We’re measuring the connections between all of these bags of text, all of these collections of unstructured data.
Dr Ben Hunt:
Once you’ve got this gigantic matrix of all these connections, from there, as the kids would say, it’s just math, right? It’s matrix algebra, to measure the structure of these giant matrices. And you can visualize it. You’ve got some measurements of the structural aspects, you can do time series, you can compare it then to structured data sets, like price, like volume, all the stuff that we care so much about in investing, that’s at the heart of it, right? And what you’re talking about, the visualization is just, call it a graph, right? A map. You’re basically taking this multidimensional matrix and you’re flattening it, into two dimensions. So you can actually see the clusters of relationships, the articles that are similar to other articles, not because I’ve read all 5,000 articles and can tell you what they mean, but the computer processor, it doesn’t know what this stuff needs. It’s just showing us here are the relationships, here’s the gravity of words.
A Visualization Of The Narrative World
Dr Ben Hunt:
It’s just so cool to see the world, what I like to call narrative world. And when you see it for the first time and you think, Oh wow, I’m finally seeing this ocean that I know that I swim in all the time and now I can actually see it. Man, it changes the way you see the world. It really does.
Tobias Carlisle:
For folks who haven’t seen it, you need to go to epsilontheory.com, and have a look at it. But it’s something like a coral growth maybe with different colors and it shows collections of these different narratives I guess. And so I just want to ask you, in terms of interpreting it, you look at these, there are these narratives that become obvious, because the same expressions are being used and they’re trying to push a point of view. Well, let me just ask you, how you interpreted first, and then a second question would be, at a second level, do you interpret it as being, some of those stories are being put into that, to influence public opinion? Some of them are just clearly picking up those things because they agree with that point of view. But is that… just those two questions? Sorry Ben, I know that’s quite-
Dr Ben Hunt:
No, no, no, and those are really at the core of all of this, what are we looking at? What does it mean? And how does it get here, right? What’s the life cycle of it? How does it get here? The way I like to think about these graphs, I like to think of them is like, I call them a star chart, right? It’s like looking at a galaxy, because distance and gravity is what we’re really measuring here, right? So you look at these pretty pictures, right? You can turn them upside down, you can flip them up or down. None of that matters. What matters is distance. What matters is centrality, right. There’s no, again, human intervention here. It’s called an unsupervised search. And so, what you were seeing here is a representation of just the computer telling you through this brute force mechanistic comparison.
Dr Ben Hunt:
Oh, these articles, we’ll call them nodes, the little dots, each little individual star in the star chart, right? If they share a lot of language, right? A lot of grammar, a lot of phrasing, they’re going to cluster it together, right. It really is the visualization, it really is the same. It’s a gravity formula. It really is. Right? And if they don’t share language, if they don’t share ideas and words, well, they’re going to be very distant, and there’s going to be no connective tissue between them. That’s the first thing to get square, when you’re thinking about this, it’s centrality, right? Because if you’re in the center of this map, then you’re exerting gravity on everything, right? You’re at the core of what meaning there is for whatever it is you’re searching on or you’re looking at.
Dr Ben Hunt:
And the second, is to think of the clustering here. And how, either everything gets tightly clustered, everything is about one topic. They all have this shared language or you’ve seen this lot of times, this indicates complacency in markets. It’s usually a cluster is off to itself, very few connections between the different clusters on something around international trade or something like that. What works for investing is very different, right? For those different States of the world. Now this gets to your second question, right? Which is like, well, are these clusters of meaning, the shared language, a meme? Think of it as a meme, right? A narrative can be like a meme, and these things have a life cycle, right? You can see them grow, you can see them reproduce, maybe merge and ultimately they die. You see them fade away. And so, the question is, well, how does that work? Right? Did they just come, out of the ocean in which we swim, by luck, by chance, some global event creates it.
The Next Time You’re Reading Something Ask Yourself – Why Am I Reading This Now?
The game theory here, I cringe every time I say it, right? I still cringe when I say, oh, let’s think about the game theory here. The game we’re talking about is what’s called the common knowledge game. How do we react as a crowd to what we think the crowd knows? And the fact is that, what drives the common knowledge game, is what we would call missionaries. famous people who have a well subscribed podcast or can we get behind the camera at CNBC, or a podium somewhere, and then what they say, the crowd believes that the entire crowd has heard it. That’s what drives common knowledge. So my view, I used to be of the view that very little of these narratives was that were actually created. My view today is that almost all of these narratives are created, not in the sense of, I’m going to… although sometimes, sometimes, right.
Dr Ben Hunt:
Somebody will say, let me pick a name. His last name, rhymes with Muffet. Right. So, Warren Muffet, he’s got an investment in some industry, and wow, I’m scheduled to go on CNBC, just talk about really whatever I want to talk about. I want to talk about this thing I just invested in, that we just put a big stake in. I want to get people thinking about my theme here, my ideas for this. And so, a lot of that happens, a lot of that happens, particularly in politics, particularly in markets. But the other source of this, is less, I was going to call it conspiratorial.
Dr Ben Hunt:
Let’s say you’re, I don’t know, you’re a stringer for the wall street journal, and you’ve got to write an article on whatever your beat is, whatever it is. You’re going to try to use words and language to make your article popular, right? And the better you are at your job, the more you will say, Oh, well I can pull from here and there, you’ll have an instinct for creating a narrative that has legs, right? That other people read and say, Ooh, that’s an interesting idea. I’ll write something similar to that.
Dr Ben Hunt:
The business of media, the business off communications, the business of filling the ocean in which we swim with messages, the business model of wall street, the business model of politics. It all revolves around supplying these narratives. That’s what wall street does, right? You’re not going to buy, unless you have a reason to buy. What’s your reason to buy? Oh, here’s an idea, here’s an idea. So what I think we must always ask ourselves when we read something in the newspaper, why am I reading this now? It’s not to say, Oh, I’m going to dismiss it. It’s to have some distance with what you’re reading, to think critically, not just about the content, but the entire act of presenting that to you on a plate.
Dr Ben Hunt:
Say, here sir, here ma’am, here’s what you need to know right now. You need to ask yourself, well, why am I reading this now. Again, that’s one of those things that once you start looking for it, once you start seeing the world in that sort of way, it really changes everything. And I think in a way that makes it less likely that, I’ll use another poker analogy, the less likely you end up being the sucker at the table.
Tobias Carlisle:
I think it’s incredibly powerful. And I had that down as one of the things I wanted to talk to you about because it is a great tool just for thinking through things when you’re reading them. Why am I reading this now? I learnt that from you and I’m very grateful for it. I’ve always been skeptical, but I think it’s a very good tool for asking.
Gell-Mann Amnesia
Dr Ben Hunt:
Tobias, it’s so hard for us to undo, not just our training as human beings, but the way we’re hardwired. And here’s what I mean. So the most searched for term, and we’ve written about it, four or five times on the Epsilon Theory site, is, the name we give to it, it’s called Gell-Mann amnesia, right? And it’s named after Murray Gell-Mann, the physicist who discovered the quark. And it was popularized by Michael Crichton. So, Michael Crichton, if you remember, his first big book was the Andromeda strain, which is way before your time.
Tobias Carlisle:
I’ve read all of them. I finished the great train robbery last night.
Dr Ben Hunt:
Wonderful. Wonderful. So, Michael Crichton, he invented the scientific thriller, right? So, Jurassic park, all of that-
Tobias Carlisle:
Airframe.
Dr Ben Hunt:
Airframe, yeah. That’s all Michael Crichton.
Tobias Carlisle:
Dragon’s Teeth.
Dr Ben Hunt:
So, he went Hollywood, right? So, he became a producer and a director, and he was giving a talk one day, and he said, look, I got to tell you, this really struck me. He said, I was talking with my buddy, Murray Gell-Mann, for some reason they were friends. And that’s why I called it Gell-Mann amnesia. And here’s the phenomenon. It’s that, well, you’ve probably had this experience. You read in the newspaper about something you know a lot about, right? Maybe it’s a company you work for, that’s happened to me before, where there’s an article in the wall street journal about a company that I worked for, and you read that article and you think, Oh my God, how can I get this retracted? Everything about this article is wrong. Right.
Dr Ben Hunt:
They’ve missed the facts. They’ve missed the reasoning. They’ve missed the origin. They’ve missed the outcome. Literally everything.
Tobias Carlisle:
Conversation is that different.
Dr Ben Hunt:
Yeah, yeah, exactly. Right, right, right. And so, Crichton said, he said, I call these articles wet streets cause rain, right? That’s what he calls his articles. And you’ll read it and you think, Oh my God, this is horrible. And this is the amnesia part. We turn the page and we read an article about something that we don’t know anything about. And Crichton said, in my case, let’s call it an article about Palestine. And I’ll read that article on the next page and I’ll go, huh, that’s interesting. And God, this happens to me every day. I’m sure it happens to you as well. It happens to all of us.
Dr Ben Hunt:
We are hardwired to respond positively with a missionary, which can be a newspaper article writer, someone who speaks from a position of authority to us, we’re hardwired to respond positively to that. And that’s why narrative is always so powerful, particularly today, when everyone is in on the act, right? Everyone’s figured this out, right? From central bankers, politicians always knew this, but now central bankers know it. CEOs know it, everyone in media knows it. And you combine that with the fundamentals not being sturdy beneath our feet. That’s why it’s so important I think for us to be able to visualize it, to see it, to think critically about what we’re accepting. Because again, not to deny it, but to give us some distance, so that we’re not the sucker at the table.
Tobias Carlisle:
Yeah, I couldn’t agree more. I like to follow. I said the great Twitter account Rudy Harvestein.
Dr Ben Hunt:
Oh, Rudy, is the best.
Recognizing The True Threat Of Coronavirus Before Most
Tobias Carlisle:
I like to follow the conspiracy theorist. It’s like that scene in men in black, when he says, he likes to go and read the truth and he picks up the national Inquirer. I know you’re going to be wrong in a lot of things, but I just want to see an alternative point of view, so I can make up my own mind about what messages are being shoved down our throats. And I think, to give you credit for this, you were way ahead on coronavirus and the risks of that. And I think it was you and Chris Cole and a few other guys that alerted me early enough. So, we were well and truly prepared, as prepared as we could possibly be. So, how did that come to your attention and how did you recognize so early on, the risks and the threat there?
Dr Ben Hunt:
So, it was really from a Reddit thread, I still don’t know who it was, he was talking about, okay, here are the confirmed cases, the caseload numbers that are coming out of China. And there were a lot of mistakes in that original data, right? Let’s, figure out the R-squared of this, just stuff that doesn’t mean anything, but the central insight was exactly correct. And that central insight was, these numbers can’t be right. This is not how a disease works. Right. And if it’s not right, well, why wouldn’t it be right? And the answer, and this is, again, this has been my professional careers, trying to understand numbers and statistics, and then understand why governments have this vested interest in making up their own story to explain something.
Dr Ben Hunt:
And in the case of China making up the numbers, that’s the only explanation for the numbers we were getting, was that they were making them up right. Directionally were they correct? Maybe, kind of, sort of, right. Really. Maybe, kind of, sort of. But what was then clear was that, not only was there this concerted effort to downplay the virulence of this disease, for domestic political reasons in China, for bureaucratic reasons with the World Health Organization, for again, domestic political reasons and every other country in the world. But we also had good now analysis pretty early on, again from, doctors sponsored by the World Health Organization to say, no, actually here’s what we’re estimating, the unknown value, the reproduction rate of this virus actually is. Here’s what we’re seeing, in terms of survival when hospitals are functioning well and the doctors aren’t sick.
Dr Ben Hunt:
And here’s what we’re seeing, when hospital systems are overwhelmed. And it was that combination of, I think, again, being very attuned to frankly the lie that China was promoting with its numbers, the lie that was accepted at face value and then promoted by the World Health Organization, the lie that was accepted by the United States and other governments, again, for their own reasons to try to, we don’t want to scare anybody. That’s what got me on it early, and again, it’s one of those periods in time where thinking differently and maintaining some distance between your own mind and the official story, it makes all the difference in the world.
Tobias Carlisle:
I remember, I was in Austin airport and I saw a tweet from somebody with that Reddit thread, where they said, it looks like they’re using some sort of, there’s some sort of underlying formula to generate these numbers. And these numbers are just following this formula, as in they’re just the next day, they’re just running the formula again and it gives them another set of numbers. And then if you look at the behavior, they’ve quarantined this entire city, there’s something much worse that’s actually happening here.
Tobias Carlisle:
And then, everybody should be aware that one of the great threats that the world faces is some sort of a pandemic that we don’t have. Honestly, I thought it was going to be something that we had developed antibiotics for, that had just stopped working. And so, but a flu is an incredibly dangerous virus. And there are lots of precedent for it, killing lots of people in a hundred years ago. And with the Spanish-
Dr Ben Hunt:
It’s the Andromeda strain, all over again. We were just talking about Michael Crichton. Yeah. Here we go, all over again.
Life Has Changed Forever
Tobias Carlisle:
So, given that you’ve had some time to think about, what should we be doing? What are we doing? Where does it go? Where do we go to?
Dr Ben Hunt:
I think the new information, and by that I mean, that we could only now know that, from having observed the spread and the behavior of both people and the virus outside of China. It seems very clear that the real impactful spreading, happens with asymptomatic carriers of the disease. Right? So that the advice, if you’re feeling sick, stay home. Right? If that’s what you’re doing, you’re too late. Right? You’re not going to catch the people who are really spreading this stuff. And to do that, we have to engage in, by whatever means necessary, the social distancing. No large crowds. That’s it. Just no crowds.
Dr Ben Hunt:
Of course, the problem with that is, until a vaccine is developed, you can’t sound the all clear and say, okay, go back to having crowds again. Right. So, that’s very problematic. But that really is, what we have to do. It’s not just, the people who are experiencing it, but it’s everyone, because it’s the asymptomatic carriers that are doing most of the damage. We don’t have to get the, are not down to zero. Right. You don’t have to stop it cold, we just have to get it below one. Right. We just have to get a point where it’s not spreading. The problem with that of course, is that unless you take very draconian measures, which are even more difficult in the West, and are impossible to enforce in many areas of the world. You can’t even do that, you can’t even get it below one. So I’m not optimistic about the longterm trajectory here.
Dr Ben Hunt:
I think, what we have to do is we have to protect our healthcare system at all cost, is something I think we’ve been poor at to date, because we haven’t taken seriously the notion of asymptomatic transmission. I think we’re getting there. I think that what has changed, I can’t emphasize enough how important this change is. It’s really just happened over the last week. The complacency narrative, which was there at the highest levels of certainly American government, is gone. It’s over, right? I mean, I still cringe when I hear Trump gives a speech or a press conference, but the difference today from the difference a week ago, is night and day, right? Nobody’s saying it’s just the flu. Everyone is taking this seriously and understands the threat that it is. That’s one, and that’s so important. Here’s the other really important thing. Today, we have wheels turning in the private sector and at the local level, that weren’t turning a week ago.
Dr Ben Hunt:
I don’t hold out a lot of hope, hope’s the wrong word. I don’t have a lot of faith in national governments to save us. Right? What I have enormous faith in, is my neighbor, what I have enormous faith in, is the ingenuity of the human animal, as expressed in private companies and private associations. I think this really will be our finest hour, to crib a line from Churchill. But it’s a war and it will absolutely be a struggle. I feel so much more hopeful today than I did a week and a half.
Tobias Carlisle:
Yeah, I couldn’t agree more. I was more panicked before everybody else started panicking. And when everybody else started panicking, I thought, now we might be able to actually solve this problem. Even though I think the trajectory looks like it really gets more frightening over the next few weeks at least. And then perhaps we’ll start to look like it’s being got under control beyond that, I’m hopeful.
Dr Ben Hunt:
Yeah. One of the ways that reminds me so much of 2008, in the financial crisis, and I know it’s a totally different application, but let me describe to you the similarity in my gut and what I’m feeling about crowd behavior. So, in March of 2008, markets were killed, just slammed, right? And at the end of March, Bear Stearns, which was a stock, where was Bear Stearns, I think it’s $120, it was taken out in the street and it was shot in the head. That’s really what happened, because they were okay, we’re going to make an example out of you Bear Stearns, took it out, shot in the head, sold the carcass to JP Morgan and they started a new narrative and that narrative was, mission accomplished, systemic risk is off the table. We had a bad apple with Bear Stearns, but you saw what we did, we took it out on the street, we shot it in the head, by may of 2008 markets had recovered entirely.
Dr Ben Hunt:
They were back at their highs. And then we had the summer of 2008, where, again, is obvious if you’re paying attention to it, systemic risk wasn’t off the table, right. It was more pervasive than you could dream of. And I’ll tell you as a short seller in 2008, that was a frustrating time, that recovery, that narrative, that, Oh, well it’s all fine now. I see something similar to that happening, everybody wants it to be a quick V-shaped recovery where, okay, yeah, we can shut down for a couple of weeks. All right, we can do that. And then it’s going to be fine, right? Then we go back to normal. And my point is, we don’t go back to normal, right? This is with us now forever. It’s going to change things forever, even after we get a vaccine.
Dr Ben Hunt:
So, that doesn’t mean necessarily being bearish. I mean, look, at this point, there’s not a lot to be done by being bearish about markets. I want to be constructive and hopeful about what sort of society we can can construct on the other side of this, not just in our investing, in our market lives, but in our political, in our social lives. I think this is an opportunity for us to come together and help our neighbors and shed this, it’s not just a veneer, the shell of financialization that has hollowed out, our society and our markets. I am hopeful that we come out of this with a much more human and real response to life. That’s my hope, and I’ll keep doing everything I can do, to speak what I think is the truth about this. But I think that’s what we all have to do.
Clear Eyes, Full Hearts, Can’t Lose
Dr Ben Hunt:
Clear eyes, see the world for what it is, and then act with full hearts. Clear eyes, full hearts can’t lose. That’s high school football in Odessa, Texas, and it’s a good phrase for living your life too.
Tobias Carlisle:
I do like that. It’s a little reminiscent of my friend Chris Cole has this, he says that volatility is an instrument of truth, and he says you can bend the narrative away from the truth for a very long period of time, but ultimately the difference between the two has to collapse, because the truth ultimately wins out. So I do think, you’re doing a great deed by telling the truth as you see it out there.
Dr Ben Hunt:
Thank you. I appreciate that. That’s all any of us can do. It really is.
Tobias Carlisle:
So just in practical terms, what do you hope to see beyond this and what do you expect to see in terms of our response to this and other things?
Dr Ben Hunt:
The way that society changes is never from the top down, right? Society will not change because someone new is elected president. Society will not change because some billionaire says this or some billionaire says that, the only thing that changes the world is bottom up activity by, what I’d call packs, right? People who treat each other not as a means to an end, not as an instrument, but treat each other as an end in themselves. And your pack may be limited to your family. Your pack may be as big as a circle of friends. Your pack may be an association you’re in, right? It’s whoever you feel those bonds of loyalty and willingness to sacrifice. Your pack is not your company. Your pack is not your political party. And we’ve been fooled into believing that they are.
Dr Ben Hunt:
What I think comes out of this, what I am extremely hopeful comes out of this, and I really believe will come out of this is a realization that all of these narratives that we’ve been told, which are to use Chris Kohl’s language, all shortfall narratives, right. These events give the lie to all of that. And it forces us to confront what we all know is true and has been true for thousands of years, is what I like to call the small L liberal virtues of, freedom, Liberty, particularly a thought, autonomy. It’s also the small C conservative values of honor, of community, sacrifice. These are values that they’re not gone, but they’ve been pushed down, right? They’ve been pushed down by the small other, the shortfall narratives of what I like to call the nudging state in the nudging oligarchy, to use some of that terminology.
Dr Ben Hunt:
Yeah. There’s a strength that comes out of a shared experience, a shared experience of pain, which we are going to, in loss, which we’ll have with this virus. But I’m really confident, really more than hopeful that we can all come together on this.
Tobias Carlisle:
I couldn’t have said it better myself and I think that that’s an ideal sentiment to leave it on. If folks want to get in contact with you, if they want to follow along. How do they do that Ben?
Dr Ben Hunt:
I’m so easy. So it’s at EpsilonTheory on Twitter. It is epsilontheory.com. As you can tell, I love talking about this stuff, so send me an email, we call ourselves a pack and I really mean that. It’s changed my life, because I started writing for a pretty dark place, the fact is you’re not alone. We’re not alone. There are hundreds of thousands of us, young, old, men, women, every country in the world. You just don’t know it. You don’t know if they’re sitting next to you at the office. It’s like fight club. Right. Except the first rule here is, it’s okay to tell somebody about it. Yeah. So epsilontheory.com. That’s the place.
Tobias Carlisle:
That’s great. Dr. Ben Hunt. Thank you very much.
Dr Ben Hunt:
My pleasure. Thank you.
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