Transcript: Colin Camerer on Neuroeconomics

 

 

The transcript from this week’s, MiB: Colin Camerer on Neuroeconomics, is below.

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This is Masters in business with Barry Riol on Bloomberg Radio

Barry Ritholtz: This week on the podcast. Finally, I get Colin Camerer in the studio to talk about Neuroeconomics Behavioral Finance and really all the fascinating things he’s been doing at Caltech for the past. Gee, he’s been there for almost 30 years. Is that about right? He’s really an interesting guy, not just because he has the mathematical and behavioral finance background, but because he essentially asked the question, what’s going on inside our brains when we make decisions, what’s happening before we even have a degree of awareness of our own decisions? I, I just find what he does. Fascinating, not just f MRIs, but eye tracking and EG and Galvan responses of the skin and just on and on. All these different ways to measure what’s going on with your hormones, what’s going on, pharmacologically it within your body. It, it’s both fascinating and terrifying because you, you come to realize what you think is a decision you’re making very often is a decision your brain is making with or without you. I found our conversation to be absolutely fascinating, and I think you will also, with no further ado, my sit down with Caltech Colin Cameron,

Colin Camerer: Thanks for having me.

Barry Ritholtz: So I’ve been looking forward to having this conversation with you for a long time. Not just because of my interest in behavioral finance, but because of the space you occupy in Neuroeconomics. We’ll talk a little bit about that in a bit. But let’s start with your background, which is kind of astonishing. You get a bachelor’s in quantitative studies from John Hopkins at 17 and then an MBA in finance and a PhD in decision theory from the University of Chicago at 21. That’s a lot of school. Really quickly, what were the career plans? Were you thinking academia? Were you thinking finance?

Colin Camerer: I was actually kind of not quite sure. So I got into, I went to Chicago grad school for PhD in the booth now Booth School of Business, because I had learned a little bit about finance. I took an independent study from Carl Crist, who’s a famous econometrician at Johns Hopkins when Gene Fama’s book Foundations of Finance had just come out. In fact, I, I literally worked in the college bookstore part-time, and I remember unpacking the box. It had this Fama book, and so I immediately bought one and, you know, I was gonna do this independent study and read through. And by the way, it really is, some books are often called Foundations of Blank, and it really was foundations of blank. Right. You know, it, it was the, it was a summary in the 1976. Right. Very early days. And so Carl Crit had said, well, you should think about Chicago. That’s a powerhouse place for finance. And so I started studying finance there and passed the prelim, which is no, which is no small feat. That’s very selective. And then I got interested in behavioral science because finance was really obsessed with market efficiency. And you know, there was no behavioral science, behavioral finance in site at that time. But there were other folks at, at Chicago,

Barry Ritholtz: Well, if I recall correctly, Dick Thaler was there early in the behavioral finance Or, or or did he end up there later?

Colin Camerer: Yeah, he came later. He came later. So when I came in the late seventies, a lot of Nobel Prize winners were their Fama Miller SHOs, I think Fisher Black might have just left for MIT at when I came, but it was pre Andre Schleifer and Rob Vish, who did a lot of interesting behavioral finance. And then Dick Thaer came, I think around 19 95, 19 6.

Barry Ritholtz: And you were at Caltech by then, right? Just correct.

Colin Camerer: Yeah, so Dick and I had just passed like ships in the night and I regret that sometimes not having to stay in, you know, it’s been part of a new vanguard.

Barry Ritholtz: But you are, you actually are part of a new Vanguard. ’cause the work you do in Neuroeconomics, which we’re gonna get into, especially F MRIs and all the other things we’ve done more or less created that space. I mean, that’s pretty foundational. Behavioral finance has a number of fathers, including Dick Thor and, and Danny Kahneman. So, well, let’s circle back to, to the Neuroeconomics in a little bit. But I wanna ask, what led you into decision making research? How did you find yourself taking the background you had in quantitative studies and your PhD in MBA and and go into decision making?

Colin Camerer: So I, some of it was when I was in college at Johns Hopkins, I, I studied physics and math. That was too abstract. And number theory was just too mind blowing, you know, for me. Like, I’m just not going to work at that level. And then I studied psychology and that seemed like just kind of a list of things that happened to people, but there was no unifying principles.

Barry Ritholtz: Squishy.

Colin Camerer: And then economics, which I really only took a little bit of, a lot fewer than my peers I later competed with in grad school, was kind of in between like the three little bears, you know, it was, there was, I love that. And there was people, Physics didn’t have, people, psychology didn’t have math, economics was kind of the right mix.

And I think a lot of, a lot of social scientists may feel that way and the people who like math less stay in psychology or go to to sociology or something where the, the mathematical structure isn’t really found the, the canon and the foundation.

Barry Ritholtz: What led you into game theory? You end up writing a book, behavioral Game Theory that was published in oh three. How does that relate to economics and decision making and investing?

00:06:15 [Speaker Changed] So when in graduate school, when I pivoted away from finance, there was a couple of psychologists, hilly Einhorn and Robin Hogarth, who were interested in judgment decision making. They were doing things very similar to Kahneman Dsky. It was sort of somewhat mathematical attempts to understand actual human decision making, not really stylized like bays, bay’s rule and optimization, you know, those are good things to know, but they were interested in deviations from those and, and what that might tell us and what the practical value is. So that’s what I ended up doing in grad school. Game theory came a little bit later because at Chicago at that time in the late seventies, there was hardly any interest in game theory for peculiar reasons. They were, you know, the economic world was dominated by price, theory, supply and demand. Like Gary Becker, you know, there was a lot going on.

00:07:04 Game theory just was not flourishing there. But my first job was as an assistant professor at Northwestern. And that happened to be through just historical coincidence, a a hotbed of great game theory. Paul Milgram was there, banked Holman was there, Robert Weber, who worked on lots of things on auction theory, Dave Barron, who was interested in political economy and, you know, political systems as games. So Milgram and Holstrom went on to win Nobel Prizes and went to other places. So it was sort of this incubator place that then, you know, like a incubator like Hewlett Packard and things like that, where people then went off to do other stuff. And so I’d basically learned game theory in my, in my first job at assistant professor. And, and that game theory is similar to behavioral economics. The, the standard theory that everyone teaches in every introductory course is people are rational and make the best choices given what they think others will do, and their correct guessing about what others do. Like a bunch of people who played poker with each other, you know, every Friday night for decades, right. They kind of know what the tells are. And, but I, we, we were interested in what happens before you get to this kind of what’s called Nash equilibrium, you know, where everyone has guessed correctly what everyone’s gonna do. And so to me there was a huge room for, for understanding the psychology of strategic thinking in game theory. So,

00:08:30 [Speaker Changed] So that’s really interesting to me. I always found the traditional economic homo economist of humans as rational, calculating profit, maximizing actors as just complete contradiction of real life experience. How did you go from your initial interest in behavioral finance into neuroeconomics where you’re looking at the biological underpinnings of what happens as people make decisions?

00:09:00 [Speaker Changed] Yeah, so the neuroeconomics to me was sort of a natural extension of behavioral economics, which was we’re going to grab for any interesting data and different ways of thinking about humans outside of standard economics and kind of pull it in and try to, you know, generate a kind of hybrid, it was almost like an import export business. Like, I’m gonna import some psychology or Dick Thaler imported from Kahneman and what is this gonna tell us about fairness and reference points and loss aversion and what have you. And Neuroeconomics seemed to me like just another thing to do. Part of it is my personality is kind of like intellectual entrepreneurship. So I liked, you know, doing different things. You know, over the years I’ve worked on lots of different methods and with different groups of people and neuroeconomics was just a chance to do something even more dramatic.

00:09:43 [Speaker Changed] And, and tell us about your patent on active learning decision engines. What on earth is that?

00:09:49 [Speaker Changed] So active learning is, the computer scientist term is sometimes called dynamic adaptive learning for basically, like if I was gonna try to figure out how much you like risk, like you’re a client and a financial advisor is asking, you know, I might start by saying, well here’s a portfolio, is this too risky or not risky enough? And if you say, nah, that’s not risky enough, I’d, you know, I’d rather go for more. And then I would, I would give you a better one that’s a little, has a little more risk in it. And in chemistry it’s called titration. You know, you kind of change the mixture of the chemicals. And so for each person, you’re asking them a dynamic customized set of questions to get to the best answer as quickly as possible. And that’s called active learning. So one of my colleagues at Caltech at that time, Andreas Kraus was studying, he was a computer scientist.
00:10:38 So they’re always on the frontier of how to get the truth faster and subject to computational constraints. Like, you know, ’cause sometimes it’s not just a question of getting there, but can you do it in real time so you don’t have to wait half an hour, you know, to ask the, ask the next highly informative question. And so the patent was just a, a method that Andres and another guy who now works at Google, I believe Daniel Goleman and me had worked on to apply this in a, in a, in a particular way. And so it was basically a software patent. There was an, it was a patent on an algorithm. So,

00:11:13 [Speaker Changed] So you’re asking people questions, how do you know they’re giving you honest answers? And, and I I I ask that question for very specific reasons that will be evident in a moment. How do you know the answers are legitimate?

00:11:27 [Speaker Changed] Okay, so in experimental economics, one of the, the, the main rules like a commandment is we almost always pay people unless we can’t, like with children sometimes or what have you, we almost always pay people money or something we know they value based on the decisions they made. So when we do these kind of risk assessments, again, not with clients, but say in a simple experiment for modest amounts of money, 20 bucks, 50 bucks, what we’ll do is we say at the end, we’re gonna pick one of the things things you said you wanted and we’re gonna actually play that for money. And if you, if you know, if you don’t tell us what you really wanted, you’re gonna get stuck with something you didn’t want.

00:12:00 [Speaker Changed] Right? So you well you’re creating incentive for them to, to be somewhat honest. Correct. The, the reason I ask, we are recording this about two weeks before the 2024 presidential election. I wrote something a month ago about why polling errors are really a behavioral problem. ’cause when you ask people who are you gonna vote for, what you’re really asking is not just their preference, but hey, you’re gonna get your lazy butt off the couch and go to the library and vote. And I assumed, hey, there’s an error of five, six, 7% built into that. And that’s why polls are so bad, researching your work about hypothetical bias. I was shocked the data that you came is when you ask people if they’re gonna vote about 70% say they will, in reality, just 45% of them do. That’s a massive error of 25%. What value is there in polls when people have no idea what they’re really gonna do?

00:12:57 [Speaker Changed] Yeah. So I mean, I think the best pollsters are know that, and so they try to phrase the question or gather some other data. But this is often called acquiescence or yes bias, right? So when you say people, are you planning to vote? Oh yeah, I’m planning to vote. Well, are you gonna, are you gonna not vote? ’cause it’s too, yeah, I may not vote.

00:13:14 [Speaker Changed] What happens if it rains? What happens if you’re busy? Exactly what?

00:13:17 [Speaker Changed] So you can often get numbers that are up to more than a hundred percent, you know? Yeah, I’m gonna vote. Nah, you 70%, yeah, I probably won’t vote 55%. That’s 125%. The math doesn’t math. And you see it particularly, one of the things we studied was product purchases. So when you show people new products and say, you know, you think you’d be interested in this, you get way too many yeses. And that’s one reason new products fail is because somebody who’s the product champion inside the firm, like in a consumer products company, looks at this polling date and says, see, see, you know, give me money to roll this out in a test market. So what one of the things we have done is to try to see if we didn’t, we wrote a few papers on this, but I don’t feel like we exactly cracked the nut, was to see if a combination of what people look at, if you measure where their eyes are looking, like, how often they look back and forth between a price and a product. And maybe brain signals could help us predict when they say, yeah, I’m gonna vote, are they really gonna vote or not? And

00:14:16 [Speaker Changed] Neuroeconomics a as as I’ve learned about it through you, is you’re putting people in a functional MRI machine, you’re asking them a series of questions and you’re identifying what parts of the brain are actually lighting up. Correct.

00:14:30 [Speaker Changed] Exactly. So that, so, and, and by the way, FMRI is glamorous and fantastic, but there’s lots of other methods that you’re used as well. It it, you know, it’s unnatural ’cause people are in this tube, right? It’s very loud, you know, if you wanna study

00:14:44 [Speaker Changed] Claustrophobic,

00:14:44 [Speaker Changed] If you wanna study claustrophobic, you cannot, you know, because the Claus aerobics won’t go in there. But it does give you a picture of the whole brain. And in the, in the case of the we that we did some experiments where we show people the consumer good and in one condition, the first part of the experiment we say, you don’t have to actually buy this, but just tell us, you know, if it was on sale for this price, like yes, no strong. Yes, we guess. So we get a four point scale and then we surprise them and say, now we’re gonna show you some different products and these you’re gonna actually buy. So if you say yes, and we choose that one out of this bin, you, you get it, you have, you have to buy it. Oh really? We give you some money and we’re gonna take the price out and give you the, the residual money and the product and you’re gonna leave here with this product. Or I think some of them we have, we have mailed it to them on Amazon something we actually had, you know, products there in a, in a box. And so the question is what’s going on in the brain when they’re seriously thinking about buying something for real versus hypothetical, which is like a survey. Right? And what we found was the tricky part is to, to predict when people say yes hypothetical, but the brain says no, you know, can you, can you see a brain

00:15:55 [Speaker Changed] Signal and can you identify that

00:15:58 [Speaker Changed] Modestly well, right. And it, it turns out the most, there’s two interesting markers. One is there’s a very old area in the brain, old, you know, evolutionary world

00:16:07 [Speaker Changed] Lizard, lizard brain, lizard brain,

00:16:08 [Speaker Changed] Right? Yes. Called the midbrain, which is actually where all of the dopaminergic neurons live. And then, and then connect to middle areas of the brain called basal ganglia that are kind of computing reward and value. And then frontal cortex, which is really putting together

00:16:24 [Speaker Changed] The modern portion

00:16:24 [Speaker Changed] Of it. The modern, exactly like the, it’s like a thinking cap on top of the monkey brain. And in the midbrain there’s a stronger signal when they say yes. And they actually do, do yes hypothetical and it’s a yes real, there’s a stronger signal then when they say yes, hypothetical, no real. So it’s almost like way upstream in the brain. If, if if in that region they say, yes, I’m gonna buy it hypothetically, there’s enough activity, they’re gonna buy it.

00:16:56 [Speaker Changed] So my general sense of this, and I’m curious as to how you, what, what the reality is. My sense of it is on the one hand, people are social animals and they want to be agreeable and exactly say yes to people on, on the other hand, we really don’t know what the hell we want. Especially if you’re talking about something six months from now. I guess the tricky part is how do you get people in MRI machines when you have a question for them? We can’t even get people to pick up their phone to answer polls. How difficult is it to get subjects to go through this process? Or are these all mostly undergraduates and you know, their lab rats, you can do whatever you want to.

00:17:35 [Speaker Changed] Some of them are undergraduates, although at Caltech they’re very unusual human beings. ’cause they’re, they’re actually useful, they’re very useful lab rats for be economics because the median math SAT is 800. Right. They’re the most mathematically skilled people. Wow. Except for some places

00:17:51 [Speaker Changed] That’s a perfect score,

00:17:52 [Speaker Changed] Isn’t it? Like Exactly. That’s the perfect score. Like Harvey Mud and MIT there are other places that have, you know, similarly hyper analytical kids. So if like, if they can’t do something like a computation easily, nobody can. So it’s very useful establishing like balance on rationality, you know, that people, we often get critiques like, well you wouldn’t get bubbles if people were smart enough. Like well, we have the smartest people and you get bubbles.

00:18:18 [Speaker Changed] It’s got less to do with the frontal cortex and intelligence. Exactly. And everything with that something limb limbic system and the lizard brain back there. Yeah,

00:18:25 [Speaker Changed] Exactly. So they have the, they have all the things in the brain. They have, they have other skills that are cortically expressed. But so in, in a lot of these MRI studies, we also use, we work pretty hard actually to get regular folks from the community who and who, you know, are different ages. We, you know, we, we don’t really have a representative sample, although you could, you could try to get pretty close in southern California. And then we, we, we almost always never do a study that’s just take alig undergrads because we worry about the robustness across. Right. It, it is true in the case of something like trying to get brain signals to break when people actually buy products. The other type of study we’ve used involves eye tracking and things like that. And it turns out that when, when you ask people hypothetical questions, would you buy that?

00:19:10 You don’t really have to buy this, but would you, they just don’t look at the price that much. Right. And when they’re really shopping, they really look at the price. So one way to tell whether people are being serious in expressing a genuine what I’m and gonna really do it is just something like how much time they spend looking at the price and looking back and forth. Huh. And there may be other, like if, if if a consumer products company was trying to use FMRI or other methods, there are others that are much more portable like EEG and you can get a pair of glasses, you walk around and it, you know, it records where your eye’s looking. So there are, there are things you could do outside of the confines of a campus lab. I think we would just look for things that are, that are easy, easily seen biomarkers of this midbrain activity and FMRI ’cause we’re never gonna be able to do that, you know, at scale in a shopping mall or something.

00:20:03 [Speaker Changed] So let’s go through each of these. We know what FMRI is, right? You’re in a an MRI machine, EEG and SCR. Tell us what those do.

00:20:11 [Speaker Changed] So e EEG is electroencephalography and it’s basically

00:20:14 [Speaker Changed] All the little things on your head. Yeah. You pace with

00:20:17 [Speaker Changed] Electrodes. If you’re a ball like me, that’s good for science. Right. You know, if you’re a supermodel with big puffy Texas beauty pageant hair, then no good. No good.

00:20:28 [Speaker Changed] So you’re measuring electrical activity in the brain and you could really specify where it is by, you know, just triangulating with all the different leads that you put on your head.

00:20:38 [Speaker Changed] Yes. Basically. Exactly. So the, the, you know, you can put 16 to 128 different electrodes. Wow. The signals are very weak, but the advantage of EEG is it’s really fast. So if you wanna study something like thinking fast and slow, you know, like if I show you a picture of a person and you have a snap reaction that they’re scary or they’re someone you wanna vote for, then f MRI is too slow because it measures these blood flow signals that take like one or two seconds to show up. Right. But

00:21:04 [Speaker Changed] Eeg, so like one, one or two seconds is too slow

00:21:07 [Speaker Changed] For, for, you know, a lot is going on in in the first two seconds where people are thinking out a decision. Huh.

00:21:15 [Speaker Changed] That’s really interesting.

00:21:16 [Speaker Changed] Not necessarily, you know, which mortgage to finance their, refinance their house in or who to for

00:21:21 [Speaker Changed] Literally system one thinking fast. System two thinking slow. Exactly.

00:21:24 [Speaker Changed] So it’s, it’s in the term psychology, social psychology use is also called thin slicing, which is that. And the thin slice is on the order of meaning a a very aggregate, somewhat confident judgment is made within, you know, 10 seconds, 30 seconds. There’s a big literature and in interviewing about this that, you know, face-to-face interviewing, unless you’re really trained to have a comparable interview for different people, you know, the first couple of minutes of the interview you’re kind of making up your mind. Huh. At least a lot of studies indicate that. And,

00:21:55 [Speaker Changed] And SCR is what? So

00:21:57 [Speaker Changed] SCR skin conducted response also called galvanic skin response. And so basically it turns out when people are aroused in any, any direction, it doesn’t tell you good or bad, but it just tells you arousal. You have this detectable increase in sweating, you can measure in the fingers.

00:22:15 [Speaker Changed] So, and, and in all of these things you’re actually taking measurements, not asking people things. And, and one of the quotes that caught my attention, since most of our brain activity goes on without our awareness subconsciously we cannot solely rely on individual’s accounts when analyzing their behavior. How important is the concept of the subconscious to, to neuroeconomics?

00:22:41 [Speaker Changed] It’s pretty important. So the saying we use is sometimes you want to ask the brain rather than ask the person. And there’s some, there’s some extreme ways in which that works. For example, if I show a, a face of somebody who’s expressing fear, but only for 30 milliseconds, which which is one movie frame, right? Right. And then I, I show a mask when you’re meaning another face right on top that’s neutral or in another condition, I show a happy face. Very enthusiastic and then neutral mask. If you ask people, did you see a happier, fearful face? They say like, I have no idea. I didn’t see, I didn’t see either one. But if you look at amygdala activity, which is a region that’s known to be rapidly detecting potential threats and including fear, the amygdala activity will respond to fear not in 30 milliseconds, not not happiness in the same way. So the the brain knows, it’s just that it doesn’t get to the, like the publicist’s desk, you know, good consciousness.

00:23:39 [Speaker Changed] So I’m so glad you said it that way. So don’t ask the person, ask the brain. How do you think of the different parts of the brain? So obviously the amygdala and, and any of the, is it fair to say that’s part of the limbic system? Yes. So when you’re talking about the publicist, what portion of the brain are we discussing?

00:24:01 [Speaker Changed] Well, in terms of sheer territory, it’s probably not very much

00:24:07 [Speaker Changed] Forebrain hind brain where, where yeah.

00:24:09 [Speaker Changed] Prefrontal cortex would be. And, and, and there’s a lot of sensory prostates and that’s going on, you know, pre-conscious or like before we could say, you know, motion to something or use words to explain what’s going on. I, I think it’s, it’s, it’s genuinely hard to pin down a number. Like it’s, you know, if I read for example, it’s 90% subconscious and 10% conscious. Right. I don’t know if that’s right. And it may vary across lifecycle. So, you know, we usually we’re, we’re reluctant to pin down a number. I think it’s fair to say that there’s a lot of things that are going on, we usually say implicitly that are not, people aren’t explicitly aware of enough, enough to make it very interesting. So,

00:24:52 [Speaker Changed] So whenever I hear people talk about, you know, things happening within the brain that you’re not aware of, I always think of the split brain experiments and bingo. Tell us a little bit, what does that reveal about our decision making process? Yeah,

00:25:05 [Speaker Changed] So the split brain was actually first explored by Roger Sperry at Caltech actually. And his student Mike, you know, made a big chunk of career over out of it. And so this split brain patients means they don’t have much communication between left and right hemispheres,

00:25:22 [Speaker Changed] Corpus callosum, is that right? Bingo.

00:25:24 [Speaker Changed] You’re a

00:25:24 [Speaker Changed] Plus. Very. So, so you’re, you’re you, these are, the one I remember was, it was some seizure or epilepsy and they found cutting that stopped the seizures. But then your left brain and your right brain don’t really communicate anymore. Exactly.

00:25:39 [Speaker Changed] So for example, so, so if you have a breakdown of corpus callosum, the right and left aren’t really communicating despite the right brain, left brain. Most modern neuroscientists don’t think there’s that much specialization. There’s some interesting kinds, but one kind that’s pretty rugged is language is mostly in the left brain and regions called bro’s area, Vern’s area. And we know that because you know, when you have specialized damage in that area, you can see people start to talk differently. Like they can remember, they can’t remember words, but

00:26:09 [Speaker Changed] The aphasia, I remember reading about people who can speak, could write, but couldn’t read. Just all sorts of wacky things happen when, when those two areas are damaged. Correct.

00:26:19 [Speaker Changed] Exactly. So there are these very localized, pretty well understood aphasias that have to do with local damage. So there’s, there’s often a what we call plasticity where another part of the brain will take over. So if you had some damage as a young child, it might be that the aphasia, you know, another, another part of their brain like takes over that function. But if it happens later in life, not so anyway, so language is somewhat specialized to left region. So for example, if someone with a and the sensory systems are contralateral, so the right side of the brain sees the left side of a picture, left side sees the right side. So suppose I show you on the left of a picture, a picture of a friend of yours, and I ask the person, if you see this friend of yours, what might, what, what gesture might you do? Or what might you, if you see a friend here as opposed to a house or a shovel, what would you do? And the person waves their hand and then you ask them, why did you wave your hand? Now the left side of the brain has to answer the question ’cause that’s the language area, but the left side doesn’t know that the right side saw a friend and that’s why they waived. So the left side makes stuff up

00:27:28 [Speaker Changed] Confabulate an an explanation for why they’re waived. Exactly.

00:27:31 [Speaker Changed] It’s like the publicist for, you know, for a very guilty person and or Mike Gaza get calls it the interpreter. So the interpreter says, I don’t really know why, so I’ll kind of make, give a plausible answer and they’ll say something like, oh, I saw somebody I knew walking by out the window outside. So that’s an example of where we know what the brain saw and why the wave occurred, but the left part of the brain, doesn’t it know.

00:27:57 [Speaker Changed] Hmm. That, that’s really, that’s really fascinating. Let’s stay with the idea of tracking eye movement. So you could do this with glasses, you can do with this, this with a computer. When you’re tracking eye movement, asking people about, Hey, would you purchase this product? How big of a tell is it when they look at the price and, and is it something they just kind of glance at? Or is it a repeated and obvious they’re focusing on the cost there?

00:28:23 [Speaker Changed] Yeah, there’s, there’s sort of two interesting markers. For number one, it’s not that big of a tell. So if we try to predict whether they’re gonna actually buy something, we might get say 42%. Right? And with the, the eye tracking data, it might get up to like 54. You know, so as academics we think that’s kind of a modest effect size. Right? Now, if you’re running a business and you want a 2% lift in purchase sure. Maybe a billion dollars. Right. So sometimes we’re a little cautious as academics about is this a big deal or not am gonna, where’s some of these things the same in the world of nudges and so on. Sometimes a small, you know, what a half percent increase in get out the vote. If we could do that, you know, scientifically may well decide in election. Right. Anyway, so the the, the lift is not that big, but the two tells are basically looking at the price and the other is re fixation, which basically means not just looking once, but going back and forth. You know, it’s, it’s, it’s the, it’s the rapid brain equivalent on a one or two second basis of, say a couple who’s shopping for a house, going to look at a second time and a third time, you know, the repeated looking Right.

00:29:29 [Speaker Changed] Usually good signal.

00:29:30 [Speaker Changed] Exactly. Tells you they’re serious. Huh?

00:29:33 [Speaker Changed] That, that’s really interesting. So, so give us some examples of what the studies or the experiments look like. When you’re doing eye tracking, what are you trying to, what parts of the brain are you looking at? Or is it just the eye tracking? Is it, is this by itself or can you combine this with other types of, of neuroeconomics? Yeah,

00:29:54 [Speaker Changed] So actually the eye trackers we use, which are commercially made for science basically, and sometimes for clinical use, they act use cameras to, to look at what the, where the eye’s looking. They sync that up with where on the computer screen you’re looking. And so besides the location of where the eyes are looking, you also measure pupil dilation. And pupil dilation turns out to be, you know, the eyes of the went into the soul. So the, the pupils actually generate a lot of information, although it’s, it’s crude, it, what the pupil dilation is telling you is about cognitive difficulty. Am I having a hard time thinking about this? And arousal, which again may be negative or positive, it’s like something

00:30:37 [Speaker Changed] Traumatic is happening. So white pupil is, you’re aroused Correct. Tight pupil is you’re having a hard time with that.

00:30:41 [Speaker Changed] Exactly, huh. And so I think if you trained yourself and maybe depending on the, the color of the eyes, you might be able to tell, like a poker player might be able to train themselves with a, to notice pupil dilation. But just in case that’s why poker players often will wear Right glasses, dark

00:30:59 [Speaker Changed] Sunglasses. Yeah,

00:31:01 [Speaker Changed] There’s sunglasses, right? Because the idea is if you look at your cards and you have two ACEs, your pupil will dilate. Like, and, and it might be hard to see with the naked eye, but the machines we use can definitely see it. That would be a big jump, you know, a big tell. And so we’re able to use pupil dilation and eye tracking to judge things like cognitive difficulty. A lot of the early studies actually were used in game theory because in game theory the assumption is if I might want to see what my opponent’s payoff is in order to decide what they’re gonna do. And if you ask people what are you looking at on this computer screen? You know, there’s, there’s a four by four matrix of numbers and I’m trying to think of what you’re gonna do. There’s a lot to look at. And if you ask people for a self- report, they’re not gonna tell you exactly what their eyes are doing the whole time. They’re probably looking at 42 different things sometimes very quickly. Sometimes they’re going back and looking again and again and again. They just don’t have conscious access to that process the way that the eye tracking does.

00:31:59 [Speaker Changed] So, so that’s really fascinating me that speaking to the brain, but not the person gives you a whole lot more insight into the decision making process to speaking generally, what does this tell us about people as, you know, rational profit seeking actors in, in the world of, of finance and investing?

00:32:24 [Speaker Changed] I think it’s useful to think about, say young naive investors or that didn’t mean to be young, but people who with less knowledge about the markets and people who’ve spent a lot more time thinking about estimating fundamentals, reading 10 Ks, you know, having years of trading experience. Because an another important fact which we try to keep track of in behavioral economics is that a lot of decisions and structures people have to make are not things that we’re necessarily evolved to be particularly good at, but people are also extremely good at learning and able, you know, able to like collect memories and distill things into, into knowledge. So let me turn to the concept of price bubbles Sure. Because I think that’s a useful one. So we have a couple of one FMRI study on price bubbles and we have some new stuff that includes skin conductors measurement to see if, you know, can you kind of predict when a crash is coming from people’s hands, you know, reflecting nervousness, it, it looks like we can predict a little but not great it, you know, that’s a high mountain to climb.

00:33:27 What we found in our first FMRI study about bubbles was people trade an artificial asset. So we know the value, the fundamental value of the asset, which we never know in, you know, in natural markets. And that the price is completely what they agree upon. So typically what happens is the, the fundamental value is a number that we control, which happens to be 14. And the, because the value of the asset comes from the fact that if you hold at the end of a period of trading, you get a dividend or you can invest currency in a risk-free bonds. And so the, the trade off between the risk-free earnings and the value of the dividends establishes an equilibrium price. It’s a very simple equation. Sure. And typically the price starts around 14 and goes up to maybe 20 or 30 and then crashes. And then, and then in order to bring the experiments to a close, we have them trade for 50 periods or 30 periods. And at the end they were able to cash the assets out at 14.

00:34:24 [Speaker Changed] So what would you pay for an asset that you’ll get 14 for Correct. After a series of dividends, 30 or 50 trading periods in the

00:34:32 [Speaker Changed] Future. Exactly. And so, so put yourselves in the mindset of somebody who in period 31, the price is 60. Right. And you, you kind of know that in period 50 19 periods from now it’s gonna be 14

00:34:44 [Speaker Changed] Sell.

00:34:45 [Speaker Changed] Well unless you think it’s gonna go up to 75. Right? Right. So it it’s true, it’s true. And, and in fact I’m, that’s very helpful for me. So what we found from the brain was that there was two interesting signals. I’ll start with the more interesting one, the other one’s a little more obvious. The interesting signal is people who sold before the bubble crash, which was the smart thing to do, and again, the bubble crash are not announced. It’s something you only see historic looking back just happens after in the rear view mirror. Right.

00:35:13 [Speaker Changed] Same, same in natural markets also announced.

00:35:15 [Speaker Changed] Exactly. Just like in natural markets. Right. Bubbles are only shown in hindsight. Gene Fama has written a lot about this. Right. That’s one reason you’re skeptical that, that we should even talk about bubbles, you know, as a scientific phenomenon.

00:35:25 [Speaker Changed] Okay. I I think he goes too far with that. But anyway, anyway,

00:35:28 [Speaker Changed] Yeah. You know what I mean? So it turns out the people who are more likely to sell when the price is at 60 and we know it’s gonna crash, but we’re not sure when have heightened activity and insular cortex, which is a another region that’s involved in emotion and interception. So interception means

00:35:45 [Speaker Changed] Knowing what’s going on on the inside of your own body. Like a self- awareness. Exactly.

00:35:50 [Speaker Changed] So perception is the outside world. Interception is the brain’s like the body’s ambassadorship to the brain, you know, knowing if I’m nervous or, and it’s often activated by, particularly by negative emotions. So if you see something disgusting insula, if you, if you choke a person a little bit or you, you know, you cut off the oxygen, not so it’s dangerous, but just to make them uncomfortable, insula really financial uncertainty insula. And so we think of the insula is the early warning signal that there’s gonna be a crash. And the other interesting brain region is, is nucleus accumbens, which is basically a reward center in what’s called striatum, part of basal ganglia in the very center of the brain. And that’s active in the people who are fueling the bubble. Like when the bubble’s, you know, forming the people who have the highest nucleus accumbens activity by the most.

00:36:41 [Speaker Changed] So you, you have a run of traders participating in this and you could tell by the brain activity who’s contributing to the bubble and who’s saying, this is getting crazy, I want to take my chips off the table.

00:36:53 [Speaker Changed] Yes. Now, in number one, we can’t tell with exquisite precision, you know, we, you can sort of see these groups and we’re only looking at this expost. So I think it’s, it’s conceivable but challenging to do this in real time, you know, so there’s, you’re watching the market unfold, you’re doing realtime FI measurement that can be done. And, and it’s like, okay, traders seven, nine, and 11, you know, we think they’re probably gonna sell. They’re the skeptics, they’re the, the bulls and 14, 17 and 21, their cus activity seems they’re really all in, they’re gonna be forming the bubble and so on and so on. I mean, we’re a, we’re a few steps away from being able to do it, but we see these as what we call proof of concept. Like it can be done, it may take a few million dollars if any donors are listening,

00:37:39 [Speaker Changed] But it makes perfect sense that it is possible. D different parts of the brain are responding to different inputs and, and it’s consistent with what we’ve observed amongst Sure. You know, just various investors and traders. There are people with, as the, you know, in the latter stages of a bull market, they think it’s just gonna keep going forever and they pile in. And the flip side of that, there are people, the famous irrational exuberance speech by Alan Greenspan in 1996. You still had a ton of of gains Yeah. Until the March, 2000 top. So some people I, I’m just curious what, what drives that now that you know what to look for and how to measure it in traders in real time. What do you think is the underlying drivers of whether a person is gonna be participating in one tribe or the other?

00:38:36 [Speaker Changed] That’s a great question. I, I’ll say a little tiny bit more about that. You, you mentioned the term irrational exuberance, which was coined as I recall by Bob Schiller in his book about,

00:38:46 [Speaker Changed] I think it was from the irrational exuberance speech. Oh no. Malin Schiller may have helped Greenspan with that speech, if I’m remembering. ’cause I’ve seen Could be, yeah. I’ve seen both, whether it was Schiller’s phrase or Greenspan speech. Yeah,

00:39:00 [Speaker Changed] It may be what it may be. You know, it was kind of

00:39:01 [Speaker Changed] Combination. Yeah, yeah. Some,

00:39:03 [Speaker Changed] You know, it was some apocryphal. We, you know, we’re not sure exactly who said it first, but certainly there was a kind of meaning of the minds that this was a useful, and in fact when we didn’t, we used the phrase in our paper, but we didn’t put it in the title, it just seemed a little too unscientific. It’s okay for a USA today or something, but this is the proceedings of the National Academy of Sciences, you know, and but we think of this nucleus accu activity that’s the, that’s the measure of irrational exuberance. And the irrational part is, you know, when it’s too high, you’re gonna end up paying a high price for something that crashes fast. Huh. So this, the rational is really in, in there, literally. But yeah, and, and also we, when I present this in ac academic seminars and later today I am meeting some Caltech people, we talk about this famous saying from Warren Buffett, I believe when people are afraid, be greedy, when people are greedy, be afraid. And in the these brain areas like insulates similar to fear and greed and nucleus accumbens, you know, it’s about as close as you’re gonna get to, to brain areas matching what Warren Buffett had to say, which was such a wise thought.

00:40:08 [Speaker Changed] So, so you really kind of answered the question I was about to ask, which is why has behavioral economics been so successful describing decision making where traditional economics seems to have faltered? But what you’re really saying is we don’t know what’s going on in our brain when we’re making decisions as individuals. And when you look underneath the hood, it turns out there’s a lot more things happening than at least classical economics seems to imply.

00:40:38 [Speaker Changed] Yes, exactly. Exactly. And and also this isn’t something we’ve carefully researched, but, but I think it’s a good speculation for your audience, which is when it, like when I was going to Chicago in the late seventies, all of my graduate student friends were also kind of critics of, of nobody liked behavioral economics at that time.

00:40:55 [Speaker Changed] Oh really? Oh

00:40:56 [Speaker Changed] Yeah. It was, you know, people said things like, I think you know, where you might be ruining your career because you switched out of finance and Well, and what it was was there was a series of, of critical questions which were, but if people make all these mistakes, couldn’t someone profit from, you know, arbitrage or from selling them crappy goods? I’m like, well, it seems like that may happen, you know, or if people make these mistakes, don’t they learn over time not to make mistakes? That may also happen. It may be that there’s a sucker born every minute, but there’s a, you know, a generational process and markets are always filled with some combination of new investors or, you know, sovereign funds of people who aren’t very savvy about markets or something like that. So early in the history of behavioral economics, there was really a lot of hostility about it.

00:41:44 And then we gradually, one thing about Chicago and, and the economics profession in general is data do win arguments. So ideology will often persist. Like for Gene Fama for example, he’s, he’ll always be skeptical about behavioral finance for his own reasons and, and you know, the, their ideas. But, but eventually data went arguments and there, there, you know, we, there were just so many anomalies in ways in which investors were making mistakes. And, and it wasn’t just small investors, you know, who were refinancing their mortgage mistakenly. It was, you know, some of these implicit things may be very big. You know, like a venture capitalist joked about how, well, you know, when I, I think of Mark Zuckerberg and a hoodie, and that’s kind of my template for a good founder to invest tens of millions of dollars. Right? Right. Like, that’s not a sophisticated, that’s not home economic is, and

00:42:35 [Speaker Changed] That’s big economics. And I recall reading one of the papers Bob Siller wrote was looking at dividend yield and saying, if, if markets are fully pricing in all data, why does this dividend yield swing around so much? It should be much more consistent than this. Correct. But apparently it’s not. I just, I was very amused by Fama and Schiller being awarded the Nobel together. It’s almost as if the committee said, look, markets are kind of efficient and except when they go crazy, you two guys work it out. Yes.

00:43:07 [Speaker Changed] Yeah, yeah. It was quite a, it was kind of a charming, and I, and I think sensible award for that reason. And the, you know, the journalist said like, well, is there, you know, one person says A is true, one says A is not always true. Like, how could you give that award? The answer is they both made, made a lot of progress, you know, in, in different ways.

00:43:27 [Speaker Changed] Let’s talk about some of the other ways that we can look inside are, are we looking at things like adrenaline or dopamine or any of the sort of hormones that seem to affect our behavior when, when we’re trying to analyze decision making?

00:43:43 [Speaker Changed] Yeah, so actually that’s a very good question, Barry. The neuroeconomics uses a lot of different methods. The FMRI is sort of like, you know, the movie star in a family with four sisters, you know, the, the glamorous one that everyone pays attention to but is actually high maintenance. And then, but all the other siblings are, you know, kind of contributing in some interesting way. So pharmacology is something people are really interested in. Meaning

00:44:08 [Speaker Changed] Specifically pharmacology, drugs that are in your system. Yeah. Pharmacology or

00:44:11 [Speaker Changed] Hormones. Pharmacology. So pharmacology is drugs, but, but some of those, for example, l-dopa will actually ramp up dopamine levels and you can see if some interesting things happen to you.

00:44:20 [Speaker Changed] L-dopa is a drug you can consume Correct. In order to raise your dopamine. Exactly.

00:44:25 [Speaker Changed] So it’s, it’s ba l-dopa is basically administered. So Parkinson’s patients have a degradation of dopamine. And so to kind of ramp them up to normal levels, l-dopa is often used in treatment.

00:44:37 [Speaker Changed] Pharmacology is one. What are some of the other four systems?

00:44:41 [Speaker Changed] So we, we do look at neurotransmitters like oxytocin, arginine, vasopressin is one that we’ve studied.

00:44:47 [Speaker Changed] Oxytocin sounds a lot like Oxycontin. Any correct overlap? No.

00:44:51 [Speaker Changed] Okay. No, exactly. So oxytocin is, is sometimes called as like an affiliation hormone. So for example, if you get a really pleasurable massage, you might feel a surge of oxytocin. When my wife was giving birth, they often to induce labor, they often give somebody synthetic oxytocin. And oxytocin is also produced after birth. And when the mom is first coming with the baby, and probably the dad, although maybe less, you know, it’s this very pleasurable thing that makes you want to like hug somebody and feel, feel affiliated affiliated as this sort of bio term. So there’s a bunch of studies on oxy doses suggestion that improve trust. Hmm. But there’s a cautionary tale, which is we, me and some colleagues went back and looked at those carefully. And it seems that giving people artificial, giving people oxytocin for a, a modest dose and then seeing what happens, you know, an hour later it improves trust a little bit. But it’s, it’s scientifically very, very tricky. And some of the standard results, if you do the same exact experiment over again, you just don’t always get the same result. So we don’t know how sturdy oxytocin is. What,

00:46:03 [Speaker Changed] What are some of the other chemicals you mentioned? Neurotransmitters you

00:46:05 [Speaker Changed] Mentioned. So when we studied, I’ll, I’ll say a little bit, it was arginine. Vasopressin. And so that’s another hormone which is similar to oxytocin. And that when, when animals are, are bonding in groups, this arginine vasopressin sort of, you know, you’ll get a surge and it shows that.

00:46:21 [Speaker Changed] So when, when you say bonding in groups, I’m thinking of a wolf pack or a hyena pack where yes, they’re cooperative species that work together and there are chemicals that contribute to that. Is that, is that what we’re Exactly, exactly. So, so part of me wants to say we are just meat sacks operating obliviously to what’s going on underneath our skin, where, where we think it’s free will. But it sounds like there’s a lot of things happening Oh yeah, yeah. Below the surface that’s really in influencing our decision making.

00:46:53 [Speaker Changed] Yeah. Oh, absolutely. I mean, think about things like breathing. You know, breathing is so automatic. Then when we stop and do sort of breath work and try to think about it like the Navy seals might have a breathing exercise to calm down before a terrifying thing they have to take, you know, it actually takes a lot of executive function to think about breathing because we never have to

00:47:13 [Speaker Changed] Because it’s automated. Right.

00:47:14 [Speaker Changed] It’s ’cause it’s so automated. So the, the fact that it’s actually grabs a lot of attention is because the automation is, is we’ve completely flipped back in the opposite situation. Lemme tell you ine vasopressin study we did. So there’s a game similar to prison dilemma, but not the same called the stag hunt game. And the idea is two people decide to show up in the morning and hunt for a stag. It, it’s a very old fashioned name from the jeano in the 16 hundreds. We’re

00:47:40 [Speaker Changed] We’re talking about a a a male elk or deer. Deer, yeah. An elk

00:47:43 [Speaker Changed] Or deer. Yeah. The point of the stag is it’s so big that no one person can’t catch themselves. One person has to spot and the other shoot or something like that. Or they, they can not show up in the morning at the appointed spot and just hunt for rabbits on their own. And so the structure of the game when we do it with money or reward with with animals is you get one point if you just go for rabbit, if you both hunt for stag, you get two if you hunt for stag. But if you show up by yourself prepared to hunt for stag, you can’t catch any, you get zero. And so the choosing a rabbit is choosing one and not helping your friend. Both showing up for stag is better for the both of them, but they have to somehow coordinate that activity.

00:48:26 And so what we found was when you give people this a VP and it’s a crossover design, which means sometimes they get a VP and sometimes they get a placebo because there’s a, you know, well known placebo effect where if they think maybe they got the A VP, it might subconsciously affect the right behavior. So we always control for placebo effects, just like in drug trials, you know, the same thing, very routine. When you give them a VP, they’re more likely to choose stag, which is the socially risky and beneficial thing. It’s like, it’s like it generates this willingness to join the group in a way that’s gonna help everybody if another, if another people join. And the the other thing that was really nice in this paper was we, we also used FMRI. So we had two groups of people administering a VP. One group was scan and one was not scan, which is just to see, like to replicate, do you get the same behavioral thing if they’re not, you know, boom, boom, boom in the scanner. And in the scanner you see activity in globus palus, which is known to be, it’s a small region, it’s not one of the more familiar areas, you know, that show up a lot over and over in neuroeconomics like bazo ganglia, amygdala, sula, PFC. But you do see activity in globus palus when people under a VP are choosing stag. So it looks like the, the A VP is sort of promoting the stag choice,

00:49:48 [Speaker Changed] But when we see people working cooperatively, you see a similar neurotransmitter Correct. As you do in the pack hours. Exactly.

00:49:56 [Speaker Changed] And it’s, and it’s, and it’s causal, right? So these are the, a group of people and sometimes they just get this drug

00:50:03 [Speaker Changed] And it makes them want to cooperate

00:50:04 [Speaker Changed] And it makes them wanna cooperate in a, in a way that, that’s risky but benefits the group. But we sometimes think of it, it it overcomes their inhibition to, to be, well I don’t know if you’re gonna choose stag and I don’t know if you’re gonna show up.

00:50:15 [Speaker Changed] Well the prisoner’s dilemma is you’re always better off throwing the other person under the bus.

00:50:21 [Speaker Changed] This is not that. And

00:50:22 [Speaker Changed] This is the opposite.

00:50:23 [Speaker Changed] The other person helps out, you want to help out too. Right. It’s the best response. So it’s different structurally than the p dilemma. So,

00:50:30 [Speaker Changed] So I keep coming back, every time I read a new anything about behavioral finance, new economics, anything about this, I, I can’t help but come back to the conclusion that all of our evolutionary biology has led us to a state where we’re so well adapted to adjusting to changes in the natural world. And all of those things that have developed over the millennia really don’t help us in the modern world. If anything it, it’s prob certainly in investing it seems to be pretty problematic.

00:51:06 [Speaker Changed] Yeah, exactly. In fact, that’s called the evolutionary mismatch hypothesis.

00:51:10 [Speaker Changed] Oh really? I didn’t know it had a name. Yes, exactly.

00:51:12 [Speaker Changed] So,

00:51:12 [Speaker Changed] So tell us about, we

00:51:13 [Speaker Changed] Can call, we can call it the riol hypothesis

00:51:16 [Speaker Changed] If, if only So, so this mismatch is simply, we evolved to adapt on the savanna and that doesn’t help us figure out which bonds to buy. Is it that simple?

00:51:26 [Speaker Changed] Exactly, exactly. So another way to think of it is, is institutions, sometimes it’s families, it’s political advertisement. It might be fine print about fees in a, you know, in a, in a financial advertisement. Those are all things that are kind of tricking or, or exploiting vulnerabilities in our basic ancestral biology. Now again, people are smart too. So there’s, there is adaptation and kind of plasticity. So over a lifetime you might, or, or maybe in one MBA course or Right. Even possibly a high school course, you might learn some principles of basic finance that really help you avoid dumb mistakes. Right. You know, like compound interest really compounds quickly. Right. You know, the, the, the, the caveman brain thinks compounding quickly. I, I have no idea what that means. My brain can’t imagine if I invested in the s and PA thousand dollars 40 years ago, how much I have, you know, I can’t compute that number. Right.

00:52:21 [Speaker Changed] Well, we live in an arithmetic world, exponential numbers are exactly hard to comprehend.

00:52:26 [Speaker Changed] Yeah. The the brain is mostly linearized things, right. That, that, that, and if they’re not linear or they’re dramatically non-linear, like pandemic compound interest, we can learn to overcome it. But we need these kind of external tools. It’s almost like exoskeleton, you know, whether it’s education advisors and so on.

00:52:44 [Speaker Changed] So let’s talk a little bit about risk aversion, which has been this behavioral finance concept. People dislike losses twice as much as they enjoy gains. What does the world of Neuroeconomics say about loss aversion? I’ve seen a few mathematicians claim Oh it’s just a statistical anomaly. I, I remain unconvinced that that’s the case.

00:53:11 [Speaker Changed] Yeah. So actually I know a lot about loss aversion. We, we published a meta- analysis last year about,

00:53:16 [Speaker Changed] There’s a reason I’m asking you this question. It’s not out of left field. Right.

00:53:20 [Speaker Changed] You came to the right place. So in the meta-analysis, we looked at hundreds of studies, basically every study we could find, you know, using informatics. And nowadays you can really do this, it’s like a industrial phishing, you know, you throw this net out and you get 4,000 studies. Then you winow it down to the ones that are really just all trying to measure the same thing. So you can add ’em up. There was something like 370 estimates of Lambda, which is the Greek symbol that means the ratio of the dis utility of loss to gain. And as you mentioned, two is sort of a, we think it’s a little bit smaller, like 1.7, but you know, it’s comparable.

00:53:55 Yeah, it’s comparable. And it’s not one which, which would be the case in which you’re not distinguishing loss and gain at all. You know, they’re just like one scale. So the evidence is pretty good. Some other fun facts about loss aversion, which is, you might think that loss aversion is, is some kind of handicap, but actually we published a paper with two people who have brain damage and bilateral amygdala, which means neither part of the amygdala can compensate for the other. There’s a very unusual disease, it comes from a erba vita disease, and they basically, the amygdala is kind of like calcified. So it’s, it’s there, but it’s like deep freeze, you know, it just doesn’t work.

00:54:35 [Speaker Changed] So you, these people lose the ability to have these emotional responses to stimulus. Correct?

00:54:42 [Speaker Changed] Correct. And a lot has been known about, because they’ve been studied. One, one of my colleagues, Ralph Ado, has studied several of them for years, and they, you know, they come back every so often and do a different kind of task. And so,

00:54:53 [Speaker Changed] Let me guess, they’re pretty good traders.

00:54:55 [Speaker Changed] Generally they’re in disability because, um-Huh? The amygdala damage is enough to make, they basically take too much risk in a lot of areas of life. Huh. So,

00:55:05 [Speaker Changed] So they’re risk embracing, not risk averse at all.

00:55:07 [Speaker Changed] Exactly. So the, so the, the idea that that risk and fear are there to kind of protect you, it applies to them. Like when you remove that, like one of the patients, sm makes a lot of poor choices.

00:55:19 [Speaker Changed] Give us examples.

00:55:21 [Speaker Changed] Well, this example I recall, I hope I’m not getting that. My memory’s not mangling it too badly, is she went on some kind of a date and the person was very sexually aggressive and she ended up okay. And then somebody said, well, would, do you want to go out with that person again? She said, yeah, yeah, it was fine. Sure, it was fine. You know, she just didn’t have this trauma. The, the amygdala was not processing. This is really bad. Run away, run away. Avoid, avoid.

00:55:45 [Speaker Changed] So, so how does this manifest itself amongst investors making risk decisions if their ability to process threats, process fear isn’t present. What, what, what happens with those sort of decisions?

00:56:01 [Speaker Changed] Well, so, so for these two patients with amygdala damage, they have no loss aversion.

00:56:05 [Speaker Changed] None whatsoever. None. In fact. So aggressive traders and investors. Well,

00:56:09 [Speaker Changed] So yeah. So the way we measure is we give them these financial, simple financial risks. Like, you could win most people, if you say you could win 10, but you might lose eight or might lose seven, they’re kind of just indifferent because a loss of seven and a gain or 10, or, you know, it’s

00:56:23 [Speaker Changed] One and a half. If I could, if I could do that on a billion dollars, I, I would, you know, exactly. I’d love to do that. Yeah. Yeah, yeah, yeah. But,

00:56:29 [Speaker Changed] But these two, so damage the amygdala, no more loss aversion. So that’s partly a reminder that be careful what you wish for. Right, right. Like,

00:56:38 [Speaker Changed] You don’t wanna react emotionally to everything. Correct. Right. The, the reason it’s so hard to do what Warren Buffet says is when everybody’s clamoring to buy, you get, most people get caught up in that enthusiasm where, where social primates and when the group is screaming, bye bye bye. It’s very hard to go the other direction. Yes. And then at the bottom, when everybody is selling, the fear is palpable. Exactly. It’s,

00:57:05 [Speaker Changed] The fear is almost contagious. Much, almost

00:57:07 [Speaker Changed] Like Yeah, very much so. Right?

00:57:08 [Speaker Changed] Yeah. Yeah. Yeah.

00:57:09 [Speaker Changed] So, so you lose that risk aversion. Do you have the ability to just go opposite the crowd? ’cause you don’t care? It, it

00:57:17 [Speaker Changed] Could be. I mean, I’ve, I have a feeling successful traders, it’s, it’s not that they’re not loss averse, but they managed to inhibit it somehow. Or we, we did a such study in this, but it’s, I don’t think their details are all that interesting for your readers, but, or they’re able to do what we call bracketing or kind of portfolio view, which is to say, you have bad days and good days, and at the end it’s my, you know, it’s my p and l at the end of the month or at the end of the year or the end of the quarter, and manage to kind of shrug off a, a loss. Now, I don’t think that’s that easy to do if you have intact amygdala. Right, right. So it’s, it’s almost, it’s, it, it leads into another interesting topic, which we’ve studied a little bit called emotional regulation, which is the fact that a lot of our emotions are sort of involuntary.

00:58:04 You know, if there’s a loud boom, you and I are both gonna have this fear reaction, you know, hair will stand up, we’ll freeze, but you can also learn to, to regulate emotions. I mean, kids are learning that when, when they learn to, you know, not be too afraid on their first day of school, as people get older, they learn to regulate emotions. It’s a pretty important skill. And so I think successful trading is probably some kind of cocktail of either a little less natural loss aversion, but not too little. Right. Because you don’t want it to like going crazy. You don’t want them to be immune to lost, just like you don’t want your hand to be immune to pain. Right. Because you’re gonna lean on a, on a hot Right. Stoves one day and not notice that your hand is on fire. Right. So you, you, a good trader probably has a little less natural loss aversion, and then a really good ability to emotionally regulate, you know, when too much loss is, is acceptable or getting you into trouble.

00:59:00 [Speaker Changed] So, so the emotional regulation aspect is really interesting. I’m gonna push you a little outside of your, your normal, I think of your normal research area. One of the interesting comments that have come up when discussing who’s a great fund manager, who’s a great trader, who, who are these folks that have put together these really impressive track records? A surprising number of neuro atypical folks? Oh yeah. Reason I asked you this is, it seems like not only is there a little bit of ability to manage the emotions, but there’s that ability to step outside of the crowd and say, I don’t care what the rest of the primates are doing here on in March, 2009, stocks look really attractive and I want to be a buyer, even though everybody else is selling. I, is there an aspect of that to those sorts of, of traders?

00:59:55 [Speaker Changed] Yeah, I think that’s a fantastic topic. In fact, it is close to something. Oh,

00:59:58 [Speaker Changed] It is. All right, good.

00:59:59 [Speaker Changed] We’ve been thinking about, so one thing is, I, I wanna, I was gonna mention from before, so one of the striking things I was working on in Neuroeconomics book, and I was reading a lot of papers on social conformity. It turns out that almost every study finds that typical paradigm is something very stylized and simple. Like, you know, you see a face and three other people see the same face, and you’re asked to say, is this person friendly or unfriendly? And in the conformity case, the other three people say friendly and some other subject, the other three see unfriendly. And people see people, there seems to be reward activity when you conform to the group. Right. And the, these are not, we’re not super stress testing. So we’re not quite something like, you know, you’re in the depth of a a, a crash 2008 crash, and everyone’s selling.

01:00:49 And, you know, ethically, it’s hard for us to generate that dramatic right. Of an event in the lab. But, but even for these mild effects, and a lot of these people, if you ask them, do you follow the crowd? They would say, no, no, no. I kind of go my own way. Like if a bunch of people said someone was friendly and you weren’t sure if you thought they weren’t friendly, would you disagree? Yeah, yeah, yeah, yeah.

Yeah. I wouldn’t bother me. But study after study study shows there’s generally reward value from conformity, which is essentially just the, the modern evidence for what you were talking about, which is that part of being a social animal. Right.

01:01:20 [Speaker Changed] The evolution continued to go along. Evolution of cooperation has a, has been very successful for us. Exactly. Did it job. And it’s hard to fight the crowd.

01:01:27 [Speaker Changed] It did its job. Yeah, exactly. Huh. So I thought that was quite striking. Again, if you were, if you wanted to study anti-authoritarian personality, it might be a way to get into that. That there, there may be people who almost pathologically, but let’s get back to your point about neurotypical people. So we’re actually working on it beginning the a study on autism. So it’s autism is called a spectrum disorder. Right. Which basically means it’s not like you have it or you don’t like schizophrenia. So, you know, statistically it’s, it doesn’t look like two humps. Right.

01:01:58 [Speaker Changed] You have a little, you could have some, you could have more, you can have a lot. Correct.

01:02:01 [Speaker Changed] Correct. And there’s often differences of symptoms like extreme autism often involves catatonia and severe language deficits and what have you. And so when people often think about Asperger’s syndrome, which is something that’s called high functioning autism, right. Which is basically you just, just socially awkward and hard to understand what people do. But a lot of these pathologies or disorders, I should say pathology is not the right word. A lot of these disorders are accompanied by some enhancement. So for example, Asperger’s patients have, are more likely to have perfect pitch for a sound. They are better at ignoring some costs, which is a classic behavioral economics thing. Right. You know, I, I spent so much on this dessert. I, you know, I came to New York, it was $18 for some flower, you know, flowerless cake, I have to finish it. Right? Right. The are

01:02:51 [Speaker Changed] Like, the money is spent, whether you get the calories or not.

01:02:54 [Speaker Changed] So the ought have the right idea. Right.

01:02:57 [Speaker Changed] And there is a sweet spot, I, I’m gonna get you a list bingo of the people who I know in this field who have put

01:03:04 [Speaker Changed] Up that would be

01:03:05 [Speaker Changed] Fantastic. Impressive numbers. Yes. And have either stated there on the spectrum or it’s kind of obvious, hey. Yeah,

01:03:14 [Speaker Changed] Yeah, yeah. You, you could look at film, video or written statements and cla you know, machine learn them and say, this person talks or looks

01:03:22 [Speaker Changed] Like I’ll ask on Twitter. Yeah. Who, who’s, who’s on the autism spectrum in the world of finance and has a good track record. But I, I have like two dozen names in my head.

01:03:31 [Speaker Changed] I’ll give you a name. I, unfortunately, he just, he died not too long ago. Charlie Munger, of course. So I got meet Charlie a few times, right. And he, he

01:03:39 [Speaker Changed] Doesn’t strike me as a very spectrum me well,

01:03:42 [Speaker Changed] But one marker of autism is, is like poor conversational turn taking, you know? And so when I, the times I met Charlie just twice, and if you see him at the, the Berkshire Hathaway, I mean, he’s, he’s amazing. I think it was like the Mark Twain of finance for sure. You know? ’cause he was really witty and, but also there’s always like a really deep psychological insight in there. You know, it wasn’t just funny, it was like funny and true and often something other people didn’t want to say. But when I met him, he was just like a freight train. And so you had to interrupt. And I realized the goal is to not have a conversation. You’re just gonna move the train in different

01:04:20 [Speaker Changed] Directions, just nudge him in different directions. Right. It’s like, exactly. Well, you

01:04:23 [Speaker Changed] Know, that reminds me of x boom and then he is off discussing XI never

01:04:26 [Speaker Changed] Realized that about him. So you’re saying, but

01:04:28 [Speaker Changed] Anyway, that, that’s my nonclinical. I am not a trained clinician. Like, you know, disclaimer, part of it is reflected in why he was successful. You know, he, he saw himself as an average person who wasn’t making the dumb mistakes other people make. But some of those dumb mistake people make may, you know, he may have not made them ’cause he doesn’t get caught up in social conformity or because he’s very focused on, he has good metacognition. Like, if I don’t, I don’t buy a company. I don’t understand. Right. You know, that’s probably a good

01:04:55 [Speaker Changed] Intuition, good strategy. Yeah. So I’m working on a, a new book. I’m almost done. And Munger is Oh, great. One of the two people I dedicate the book to. And the quote of his, that very much informs the, the theme of the book is someone once asked him, was Berkshire successful? ’cause you and and Warren are so much smarter than everybody else else. And his response was, it’s not that we’re smarter than everybody else, we were just less stupid. Which is such an insightful observation. Yeah. Hey, just fewer Charlie Ellis make less unforced errors. Yeah, yeah. And you’ll do better in tennis or investing Yeah. Than the guy trying to slam the ace in. Most people are not gonna get it in him. And Munger had the, the two trolleys had the same belief system just be less stupid. Absolutely. It’s, it’s really fascinating. Yeah. Yeah. Totally. So, so when you’ve interviewed Munger, what are some of the takeaways you’ve had from your conversations with him?

01:05:54 [Speaker Changed] With, one thing I remember was for, we, we, so we went and looked at our neuroimaging center. He, did

01:06:00 [Speaker Changed] You ever get him in a machine?

01:06:01 [Speaker Changed] No. I wish we, I wish we had. He, we, we may, he may have gone for it too. He is a, you know, he’s a pretty interesting person and I think very

01:06:09 [Speaker Changed] Open-minded to crazy stuff. Right? Yeah.

01:06:11 [Speaker Changed] Scientifically curious as well as in, in his, in his financial life. He had gone to Caltech for a while. So he was, we got to run into every so often. Of course we’re always people like that. They’re always trying to get them to give money and Right. Or at least show up and

01:06:25 [Speaker Changed] Give a speech something. Yeah.

01:06:26 [Speaker Changed] Talk. And so, so we showed him the brain scanner. He had a really interesting thought, which I didn’t quite appreciate till later, which was, he said, what you guys should be doing is if you’re trying to change behavior, like let’s say you’re trying to get somebody to vote or to wear a mask or, you know, quit smoking opioids, the really hard stuff, you know, weight loss. He said, what you should really do is rather than doing one little thing, you should go for a Lollapalooza, you know, like basically try to add in six different things to get the biggest ability to get people to quit smoking, let’s say.

01:07:01 [Speaker Changed] Makes sense.

01:07:02 [Speaker Changed] And so he was thinking as a practitioner, like, I want, I’m gonna know what’s i’s gonna work. As scientists, we’re often thinking piecemeal. Like if we put six different things in and it works, we don’t know which of the six is the active ingredient.

01:07:15 [Speaker Changed] But it could be a different combination for each different person. Exactly.

01:07:18 [Speaker Changed] So Exactly. But, and so the reason I was thinking about that was nowadays one of the fallouts, or one of the products, I should say from fall, it’s definitely the wrong word. One of the products from behavioral economics was this idea of a nudge that often, because people are often sensitive to very subtle things like opt-in versus opt out. Right. You know, there may be a low cost light touch way to change behavior a little bit.

01:07:41 [Speaker Changed] Well just look at the 401k Exactly. Making the default go to just some specific investment as opposed to it just sits there in cash. Correct. For, for god knows how long seems to have really had a big impact.

01:07:59 [Speaker Changed] Yes, exactly. That, that was definitely the, the, the poster child for the simplest nudge. And we kind of understand the psychology of it anyway. And so, so now what a lot of people are thinking about nudges is exactly this Lollapalooza idea of mungers, which is, if we wanna get people to get out the vote, rather than try six different things, we should be trying like six combinations of three things. Statistically it’s messy. ’cause you, you, you’ll never really end up knowing which of those is the active ingredient, but to just get results that, that’s useful information, that’s useful information. So the nudge enterprise, which I’ve been connected to a little bit, is moving somewhat in that direction that Munger mentioned many years ago.

01:08:38 [Speaker Changed] Huh. Really interesting. All right. I only have you for a limited amount of time. So let me jump to my favorite questions that I ask all of my guests. Starting with what are you watching or listening to these days? What’s keeping you entertained?

01:08:54 [Speaker Changed] So Katie Milkman’s podcast Choice ology is one that I’ve been on that I think is quite good. It’s basically the, the Behavioral economics podcast. There, there are quite a few others, but Katie’s a real expert on this and is a, a, a great interviewer and has had good guests

01:09:08 [Speaker Changed] Choice ology,

01:09:09 [Speaker Changed] Choice ology.

01:09:10 [Speaker Changed] Tell us about your mentors who helped to shape your fascinating career.

01:09:15 [Speaker Changed] So two people who were on my thesis committees, Robin Hogarth and Hill Einhorn were two. And there’s an interesting story. So Robin was Scottish, very verbal. Every sentence started with Howsoever, therefore, not withstanding Hilly was a very blunt Jew from Brooklyn. Right. And it was the exact opposite. Right? So Hilly would mark up my thesis and put in all these fancy, hilly, rather, would take out the whatsoever and the howevers and the therefores. And he was like putting more like boom, like short sentences, no semicolons, but like he had one punctuation mark, period. That’s it. Right? Like, you know, he bought, he like, he bought a million periods at a store and like, I’m gonna use those. And Robin was the other way around, oh, this really needs to do semicolon, you know, let’s plop this in. And at one point I was going back and forth, you know, near the completion of my thesis where the two of them were co-advisors.

01:10:10 And I got so frustrated and I said, how should I write this? And we had this, this kind of like grasshopper moment of it’s your thesis, you figure out how you wanna write it. And I realized they were kind of waiting for me to find my voice, like they say in writing. Right. You know, like, and one of them love tables and the other love graphs. So the drafts of my thesis was the table and a graph were exactly the same thing. And I had to decide was I a graph person or a table person, or was I kind of like a

01:10:39 [Speaker Changed] Bilingual, right?

01:10:40 [Speaker Changed] So I basically became kind of bi bilingual in terms of how I was thinking about science. That was very helpful. The other person probably is Dick Thaler because he, he’s a very good writer. He did exactly what so many academics aspire to, and we always ask for more of, which is to write a small number of extremely high quality papers. It’s, it’s very unusual because for career reasons and stuff, you have to get tenure and right. And Dick just couldn’t really write a bad paper. I don’t write as many great papers as him and I, as a result, I write too many okay. Papers. But that’s something I think is useful for everyone.

01:11:15 [Speaker Changed] He, he’s one of my favorite people in the world. I, I got to interview, I don’t know, half a dozen times, only once since he won the Nobel Prize. But I, I always find him so informative and entertaining and I, I just loved his response to winning the prize. What, what are you gonna do with the money? His answer was, I’m gonna spend it as irrationally as I possibly can. Yeah. It’s just so, so him.

01:11:40 [Speaker Changed] He enjoys life.

01:11:41 [Speaker Changed] He very much does just, he’s just also a fascinating, fascinating, charming guy. Let’s talk about books. What are some of your favorites? What are you reading right now?

01:11:50 [Speaker Changed] I am reading Emma Klein, a book called The Guest, especially for New Yorkers in your audience. It’s about a very drifty, sketchy woman who goes to the Hamptons and kind of cons way around the Hamptons. It’s really, it’s almost like a very,

01:12:06 [Speaker Changed] Didn’t we have kind of a real life thing like that happening a co a year or two

01:12:09 [Speaker Changed] Ago? Yes, exactly. It may, it may be loosely inspired by Anna Delvy in Manhattan or some, or some similar cases. It’s basically a, almost like a, a 19th century novel about class because she’s very conscious of not belonging in the happens, but she’s very beautiful and kind of charming in this sort of man eater, fenal way. And I’m almost done with that. It’s really delicious. The other thing I I, I love movies and books about capers and heists and grift, which includes Emma Klein, the guest. So I’m reading these books by Jim Swain, who’s not well known. I got onto it. ’cause Lee Child, who I, who I

01:12:45 [Speaker Changed] Love, my wife reads all of his books. Yeah. Plowed plow through all of them. Exactly. Yeah. And, and, and that, did that include the Reacher series?

01:12:52 [Speaker Changed] The Reacher series? Yeah. Yeah. That’s what he is most famous for. The Lee Child. But, so Jim Swain was blurbed by Lee Child saying, Jim Swains the best at what he does. And what he does is he writes about a very sophisticated cheater in Las Vegas who cheats casinos. And it, you know, I’m gonna use recycle this in your, in the very shortly for you. But basically there are procedurals about how to cheat a casino. But in the end, if you get caught, there’s also this sort of sociopolitical thing of, you know, if I make up a story about why something happened, like if there’s a murder in a casino and I make up a story about it that helps them act like the murder was freakish and won’t drive away customers, I’m actually delivering a gift to them and they’re gonna trade off. They’re not gonna send me to jail if I give them this gift. So there’s a lot of layers of this is not doki, it’s not Right. Brilliant. This is not hybrid

01:13:48 [Speaker Changed] Literature. This is a fun summer beach reading it sounds like.

01:13:49 [Speaker Changed] Yes. But for me, there, there’s a lot of like psychology and you know, in a way it’s a game theory. What if there’s an arms race between the Vegas Gaming Commission and each of the individual casinos who are very sophisticated, they hire a lot of ex cheats, you know, to Right. To tell ’em what to look for. And then these cheaters who know, you know, so it’s really this arms race of who’s gonna win. I found those really interesting.

01:14:11 [Speaker Changed] If you like books on griffs and cheats and corruption, I’m gonna recommend pretty much anything he’s written. I’ve been a fan of his for years. Carl Hesen was a Oh yeah. Reporter for the Miami Herald, the Prime Reporter, and then just one after another, these series of novels. And, and his, one of his more recent books is now a, a TV series on Apple plus Bad Monkey, but Oh, is it?

01:14:41 [Speaker Changed] Oh

01:14:41 [Speaker Changed] Yeah. But all of his books, it’s Bad Monkey and the, I think the sequel’s called Razor Girl. But all his books take place in Florida. Everybody’s corrupt. The police are corrupt, the building inspectors are corrupt, the politicians are corrupt. And there’s always one or two good people in the heart of the story. And it’s how do they navigate? Right. This just endless, endless sea of treachery and corruption. And he’s just a delightful, entertaining writer. If you, you could randomly Yeah. Pick Yeah, I read a any of his books and they’re just all, they’re great beach reads.

01:15:13 [Speaker Changed] Yeah. Let me also mention The Wire. ’cause I grew up in Baltimore County and I read the series. Yes. And David Simon’s book The Corner is a kind of a precursor. I mean, he’s a very interesting person. He was a reporter and I think he made in

01:15:28 [Speaker Changed] B in Baltimore. Is that right? In Baltimore?

01:15:29 [Speaker Changed] Yeah. And the Corner is like this beautiful, I think it was a precursor to The Wire, but it’s basically about a corner in West Baltimore where everyone buy buys drugs and it’s about drug addiction and all the things that surround it. So it’s somebody who, you know, one of the things we study in behavioral economics is habits and addictions and you know, and neuroscience of course is fascinating along the way. And that one is great. And The Wire having grown up in Baltimore County, which is not Baltimore City, the wire’s almost like a documentary. And it has all this Baltimore stuff as well as Baltimore accents where you, you know, people are talking about talking like this. And it has, Tommy Garcetti is this political character who’s sort of inspired by Tommy Deandro, whose daughter is Nancy Pelosi.

01:16:12 [Speaker Changed] Oh really? That’s amazing. I I found the series The Wire. It’s a tough watch. It’s a great show. Yeah, yeah. It’s, but it’s brutal. Yeah. Gritty is, is mild. I mean, some of the stuff that goes on in the show is just like,

01:16:26 [Speaker Changed] Yeah, there’s a famous scene with a nail gun. You’re, which if your listeners have this stomach that’s pretty classic,

01:16:34 [Speaker Changed] Similar in the Jack Reacher series, there’s a Oh really? Something not that far off. Yeah. Oh, they toned it down for television. But the book is, is really brutal. Alright, we’re up to our final two questions. What sort of advice would you give to a college grad interested in a career in fill in the blank Neuroeconomics behavioral finance, or even just investing

01:16:58 [Speaker Changed] For somebody who would say doesn’t wanna get a PhD that’s a different track and probably of less interest. And there’s, you can get a lot of guess advice on how to do that. I would study not just finance, like straight asset pricing and derivatives, but also behavioral economics, game theory, I think. ’cause even though game theory is usually like two players or small numbers of players, it really sharpens the logic of, you know, when do I know something another person doesn’t know and, and do I know that they don’t know it? You, you know, you have to really relentlessly think about the math underlying that. And then there’s a lot of experimental and real world data. One of my, I just got a text from our students this term, and there’s a lot of data from sports about whether sports activities are like equilibrium responses to other players.

01:17:48 Hmm. So you can actually, there’s, there’s a lot of sources of data besides just say the lab experiments I talked about in my book from 2003, sneaking the plugin. Cognitive science is something I would study too. So cognitive science is a modern brand of cognitive psych that has more math in it. And a lot of it actually goes back to something we spoke about like evolutionary mismatch. But they’re quite interested in what they call resource rationality, which means a lot of the mistakes people might make, like anchoring on one number and being influenced by that. A famous anchoring adjustment heuristic may actually be rational if you, if you only have so much working memory or you are under time pressure or you’re tired. It’s also g closely related to the way economists would think about mistakes, which is they may be optimal given some constraint.

01:18:36 Like what is that constraint? And can we test that experimentally? So I think there’s a lot of stuff you could learn there that will help you think about markets. The other thing I would say is get experience thinking about markets, whether interning or, I mean, I’ll tell you a story about what worked for me, which was when I was 12 years old in Coville, Maryland. Every August there was a one month racing program at a small racetrack called Timonium Maryland. And it was a five eighths of a mile track. So it’s like a, you know, small, I would go with my dad and a friend of his who had is a stockbroker. And we would also go to the big tracks like Pimlico, where the preak, the stakes is. But if you go to Timonium, you get to see all the horses. There was so much interest. You learn so much about markets. It, it, number one, it gives you I think a respect for market efficiency because

01:19:27 [Speaker Changed] The odds are actually not that bad.

01:19:29 [Speaker Changed] They’re, they’re extremely good. They’re

01:19:30 [Speaker Changed] Pretty, pretty dead on.

01:19:31 [Speaker Changed] Exactly. And so you see, you know, eight horses come out, they all look pretty similar. You know, they’re, the jockeys are all, you know, the same size and they’re all pretty good. There’s a lot of statistics you can see, but somehow the crowd has decided that number three is even money favorite, which is a 50 d chance to win. And number six, who looks pretty good too, is like 70 to one. And they’re mostly right. So, you know, part of why I got into economics and psychology was thinking about episodes like that. How does the market put this information together and are there mistakes? Like how do you beat the market? So, so

01:20:07 [Speaker Changed] Fama turns out to be more or less right about the efficient market.

01:20:10 [Speaker Changed] He was right about Tony in Maryland. Right. And there were other interesting lessons too. Like, so on the, if you go like around the third race, you know, I was, I was a kid, so I was broke. And my poor mom, my Irish mom was worried I was gonna, you know, lose too much money. I, I kept telling it’s tuition, mom, it’s tuition. But you, if you go in the third race, there are these people who would sell tip sheets for like $5. Right. And it, you know,

01:20:34 [Speaker Changed] If you go, ’cause they know what’s gonna happen. They’re selling the tip sheets, not making the bets.

01:20:37 [Speaker Changed] Exactly. The customer’s yachts. Exactly. But if you go like in the, you know, the third or fourth race, they would quit selling ’em and they would just give them to you. Oh,

01:20:46 [Speaker Changed] Oh, really? Like,

01:20:47 [Speaker Changed] Well, like a loss leader, maybe you’ll, you’ll maybe next time you’ll buy it. And so I’m sitting, you know, here’s my little cynical 12, 13-year-old brain thinking, why are you giving away for free tips that you claim can make me money? Right. Like, this does not, the math does not math. And I think that’s a good lesson in life for markets. Right? Yeah. You know, just, just to clear away like the most naive, you know, immunize yourself to the most naive schemes, you know, you, you

01:21:16 [Speaker Changed] Would think if the tips were valuable, rather than waste your time printing it up and selling them, you would just bet on the Exactly. On the winning horses. Right. Why, why, why?

01:21:25 [Speaker Changed] Especially in a permut system. Right. Right. Because you know, the more, the more your tip sheet buyers are betting on your horses,

01:21:33 [Speaker Changed] The lower the eyes you can make. Right. Exactly. Right.

01:21:35 [Speaker Changed] Because you’re betting against

01:21:36 [Speaker Changed] Yourself. Counterproductive. Our final question, our final question. What do you know about the world of Neuroeconomics today might have been helpful when you were first getting started back in the 1980s?

01:21:50 [Speaker Changed] You know, I’ll answer that. Like a politician will answer a, a question I have a better answer for, which is about behavioral finance. Sure. So,

01:21:56 [Speaker Changed] Well either or bfi or, or Neuroeconomics.

01:21:59 [Speaker Changed] Sure. Yeah. Got it. So in Neuroeconomics, I don’t think I, we made too many mistakes. I think I wish we had, you know, we got a lot of grant support. Caltech was very supportive. I got to know a lot of interesting people who were generous with their time, who were kind of my tutors on neuroscience. I I never took any formal, you know, coursework on it. It was came way, way, way after my original grad training. So thank you everyone. I wish we had, we, we have not had much impact in academic economics particularly. And I, that’s something we’re kind of working on. Maybe we can do better behavioral finance. I think I started graduate school in the late seventies. In 1978, Mike Jensen published a very influential paper. It was an introduction to a special issue. And one of the first sentences is the market efficiency hypothesis is one of the most, well-established empirical regularities in economics.

01:22:50 But, and the, the, but that was like the high watermark, right. And the special issue was about, there’s some things that are anomalous, like earnings drift. Right. You know, you get a weird earnings announcement, the market reacts, but then the market reaction drifts up for it takes a couple weeks almost like food for the market to so absorb it should not take a couple weeks. Right, right. There were other things where we see, you know, like one within one hour markets are repricing really well. But despite this Jensen article, the hostility to behavioral finance was ferocious

01:23:28 [Speaker Changed] Fero. That’s a big word. At that time it was, it was that, so late seventies, early eighties, late

01:23:32 [Speaker Changed] Seventies, early eighties. And so that’s when I was kind of deciding do I wanna stay in finance or mix it with, and I remember having a discussion, I don’t know if Gene remembers it the same way with, I had to write a paper for Eugene Fama’s course who was also kind of a mentor in the sense that even though I didn’t end up doing work that was close, you know, he, he was, he was really relentless and very empirically driven. And he had a really good idea when he started, people were thought he was crazy. Right. Because there was all this stuff on, you know, there was even, he wrote some papers on dividends, like, well, the optimal dividend payment policy. And of course Miller and him was like, what? Pay dividends at all. You just like take money from one pocket and put it in the other. Well,

01:24:11 [Speaker Changed] Back in the early days of widows and orphan stocks, you people lived on their dividends. Yeah,

01:24:15 [Speaker Changed] Exactly. ’cause of the liquidity, right.

01:24:17 [Speaker Changed] Because you don’t wanna sell, do you wanna hold onto it? You just

01:24:20 [Speaker Changed] Right. And then the dividends is, you know, is enough to live on. Yeah.

01:24:23 [Speaker Changed] Now the theory has shifted towards it’s more efficient return of capital to shareholders doing buybacks than dividends. But that’s only total return if you are looking for that income stream buybacks don’t necessarily help you.

01:24:37 [Speaker Changed] Right. Right. Exactly. So that’s, and that’s also where the behavioral economic comes in with, you know, why can’t you just like, create whatever income stream you want by borrowing and selling, you

01:24:47 [Speaker Changed] Know? Right.

01:24:47 [Speaker Changed] That’s right. And if, you know, if you’re really liquidity constrained or credit constrained, you can’t. But for most people, that’s not a big deal. Anyway, so, so if I had known behavioral finance would, it didn’t take off quickly. So from 1978, which is Jensen, 1981, I graduated, 1985 was the failure and devant paper about January fx. And even that was published as a, it, it was in the proceedings issue, which meant that the president of the, of the a FFA could pan pick papers. So the proceedings issue had the most radical papers that were the foundation of behavioral economics. Fisher Black wrote a paper called Noise Traders. In fact, it might have just been called Noise. And then Dick Roll wrote a paper called R Squared. And he said, you know, if only news moves the market right then the r squared on days with no news, you know, you shouldn’t have any volatility. And of course, days with big news and small news, similar to the story you were telling in the beginning days with big news, big obvious news. And hardly any news move about the same.

01:25:57 [Speaker Changed] The assumption being by the time it’s in the front page of the New York Times, it’s already reflected. It’s not moving the

01:26:03 [Speaker Changed] Markets. Right. But also there, there may be things that are not newsy at all. Like in the October 87 crash, you know, the Bunes bank moved rates by a quarter of a point or something. Right. Who cares? That was the big news,

01:26:14 [Speaker Changed] But Right. That, but you know, you never know when that last straw breaks the camel’s back. Correct.

01:26:18 [Speaker Changed] Correct. But, but so all those ideas now that, that we, we, you know, we feel like we have an understanding and examples there, there was a lot of hostility to that. So I, the, I remember asking Gene, I’d like to study market psychology, like what do you know about market psychology? And he said, what’s that? I like Mike Psychology. There’s Boston Accent. You know, he’s, I I, and I think it’s just a word they use on the news, like in Bloomberg, it’s just a word they use on the news when the market moves and they don’t know

01:26:49 [Speaker Changed] Why. Right. Well, no one wants to admit it’s fairly random day to day. Yeah. We’re very, humans are very, I know that humans are very uncomfortable and

01:26:58 [Speaker Changed] We’re good at pattern sense making. Right.

01:27:01 [Speaker Changed] We make up patterns. We come up with a narrative to explain it. Yeah. I, I, I’m, I’m, I, I recall Dick Thaler quoting, maybe it was Max Plank, who was talking about physics, science

01:27:14 [Speaker Changed] Progresses

01:27:14 [Speaker Changed] One, one funeral at a time. Thaylor said the same thing about behavioral finance. And he also said, I’m bypassing the current generation and going right to the kids. So they’ll adapted wholesale. And literally he said, I’m teaching grads and undergrads this, so we don’t even have to wait for the funeral. And it, it seems to have worked.

01:27:34 [Speaker Changed] Oh yeah. No, absolutely.

01:27:36 [Speaker Changed] Colin, thank you so much for being so generous with your time. This has been absolutely fascinating. I’m glad we finally managed to do this. We have been speaking with Professor Colin Kamara of California Institute of Technology. If you enjoy this conversation, well check out any of the 500 previous interviews we’ve done over the past 10 and a half years. You can find those at iTunes, Spotify, YouTube, Bloomberg, wherever you find your favorite podcast. And be sure and check out my new short form podcast at the money short single subject conversations with experts about issues that affect your money earning spending, and investing it at the money in the Masters in Business podcast feed, or wherever you find your favorite podcast. I would be remiss if I not thank the crack team that helps with these conversations together each week. John Wasserman is my audio engineer. Anna Luke is my producer. Sean Russo is my researcher. Sage Bauman is the head of podcasts at Bloomberg. I’m Barry Ritholtz. You’ve been listening to Masters in Business on Bloomberg Radio.

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