Advancing Behavioral Economics with Colin Camerer

Episode Transcript
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Speaker 1 (00:02):
Bloomberg Audio Studios, Podcasts, radio news. This is Master's in
Business with Barry Ridholds on Bloomberg Radio.

Speaker 2 (00:16):
This week on the podcast finally I get Colin Camera
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's been there for almost thirty years.
Is that about right? He's really an interesting guy, not

(00:37):
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 just find what he does fascinating, not just fmyes,

(01:00):
but eye tracking and eg and galvanomic 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 within your body. It's both fascinating and terrifying because
you come to realize what you think is a decision

(01:23):
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 camera.

Speaker 1 (01:40):
Thanks for having me so.

Speaker 2 (01:41):
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 back, which is
kind of astonishing. You get a bachelor's in quantitative studies

(02:05):
from john Hopkins at seventeen, and then an MBA in
finance and a PhD in decision theory from the University
of Chicago at twenty one. That's a lot of school
really quickly. What were the career plans? Were you thinking academia?
Were you thinking finance?

Speaker 1 (02:22):
I was actually kind of not quite sure, So I
got in. I went to Chicago Grad School for PhD
in the now Booth School of Business. Because I had
learned a little bit about finance. I took an independent
study from Carl Christ who's a famous econometrician at Johns
Hopkins when Gene Fama's book Foundations of Finance had just

(02:46):
come out. In fact, I literally worked in the college
bookstore part time, and I remember unpacking the box to
have this Fama book, and so I immediately bought one,
and you know, I was going to do this independent
study and read through. And by the way, it really
is some books often called Foundations of Blank. It really
was Foundations, right, you know, it was the It was
a summary in the nineteen seventy six, right, very early days.

(03:09):
And so Carl christ 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 prelam which
is no which is no small feat that's very selective.
And then I got interested in behavioral science because finance

(03:29):
was really obsessed with market efficiency and you know, there
was no behavioral science, behavioral finance in sight at that time.
But there were other folks at at Chicago.

Speaker 2 (03:39):
Well, if I recall correctly, Dick Taylor was there early
in the behavioral finance or did he end up there later, Yeah,
he came later.

Speaker 1 (03:48):
He came later. So when I came in the late seventies,
a lot of Nobel Prize winners were their Fama, Miller Shoals.
I think Fisher Black might have just left for MIT
and when I came, but it was pre Andre Schleifer
and Ravishni who did a lot of interesting behavioral finance,

(04:08):
and then Dick Taylor came, I think around nineteen ninety five,
nineteen to.

Speaker 2 (04:12):
Six, and you were at cal Tech by then, right,
just correct?

Speaker 1 (04:16):
So yeah, so Dick and I had just passed like
ships in the night, and I regard that sometimes not
having just stayed and you know it's been part of
a new vanguard.

Speaker 2 (04:26):
Well, but you actually are part of a new vanguard
because the work you do in neuroeconomics, which we're going
to get into, especially fMRIs and all the other things
you've done more or less created that space. I mean,
that's pretty foundational. Behavioral finance has a number of fathers,
including Dick Taylor and Danny Kahneman. So well, let's circle

(04:51):
back to the neuroeconomics in a little bit. But I
want to ask what led you into decision making research?
How did you find yourself taking the background you had
in quantitative studies and your PhD and m b a
and and go into decision making.

Speaker 1 (05:11):
So I some of it was when I was in
college at Johns Hopkins. 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 wish squishy.

(05:32):
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, there was I
love that, and there was people right you know, physics
didn't have people, psychology didn't have math.

Speaker 2 (05:47):
Economics was kind of the right mix.

Speaker 1 (05:49):
Exactly exactly. And I think a lot of a lot
of social scientists may feel that way, and the people
who like math lest stay in psychology or go to
sociology or something where the mathematical structure isn't You found
the canon and the foundation.

Speaker 2 (06:03):
So what led you into game theory? You end up
writing a book Behavioral game Theory that was published in
three How does that relate to economics and decision making
and investing?

Speaker 1 (06:15):
So in graduate school when I pivoted away from finance,
there was a couple of psychologist Hilly Einhern and Robin Hogarth,
who were interested in judgment decision making. They were doing
things very similar to konomen and diversity. It was sort
of somewhat mathematical attempts to understand actual human decision making,
not really stylized like Bay's rule and optimization. You know,

(06:38):
those are good things to know, but they were interested
in deviations from those and what that might tell us
and what the practical value. 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

(06:59):
was dominated by price theory supplying demand like Gary Becker,
you know, there was a lot going on. Game theory
just was not flourishing there. But my first job was
as an assistant professor in Northwestern and that happened to be,
through just historical coincidence, a hotbed of great game theory.
Paul Milgram was there, Banked Holmestrom was there, Robert Weber,

(07:20):
who worked on lots of things on auction theory, Dave Barren,
who was interested in political economy, and you know, political
systems as games. So Milgrim 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,

(07:40):
like a incubator like Hewlett Packard and things like that,
where people then went off to do other stuff. And
so I basically learned game theory in my first job
as AISTM professor, and that game theory is similar to
behavor economics. The standard theory that everyone teaches in every
introductory course is people arend and make the best choices

(08:03):
given what they think others will do, and they're correct
guessing about what others do. Like a bunch of people
who played poker with each other, you know, every Friday
night for decades, they kind of know what the tells are.
But we were interested in what happens before you get
to this kind of what's called Nash equilibrium, you know,
where everyone is guessed correctly what everyone's going to do.
And so to me, there was a huge room for

(08:26):
understanding the psychology of strategic thinking in game theory.

Speaker 2 (08:29):
So that's really interesting to me. I always found the
traditional economic homo economists of humans as rational calculating profit
maximizing actors is just complete contradiction of real life experience.
How did you go from your initial interest in behavioral

(08:50):
finance into neuroeconomics, where you're looking at the biological underpinnings
of what happens as people make decisions.

Speaker 1 (09:00):
Yeah, So the neuroeconomics to me was sort of a
natural extension of behavior economics, which was We're going to
grab from 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.
And I'm going to import some psychology or dicktale or
imported from konomon and what is this going to tell

(09:22):
us about fairness and reference points and loss aversion what
have you? And neur economics seem 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 neureconomics was just a chance to do something even
more dramatic.

Speaker 2 (09:43):
And tell us about your patent on active learning decision engines.
What on earth is that?

Speaker 1 (09:50):
So active learning is the commuter scientist term is sometimes
called dynamic adaptive learning. For basically, like if I was
going to try to figure out how much you like risk,
like you were a client, and if 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, you know,

(10:12):
I'd rather go for more, and then 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

(10:33):
one of my colleagues at Caltech at that time, Andreas Krauss,
was studying he was a Gonna Better scientist. So they're
always on the frontier of how to get the truth
faster and subject to computational constraints, like you know, because
sometimes it's not just a question. I'm getting there, but
can you do it in real time so you don't
have to wait half an hour, you know, to ask

(10:55):
the next highly unformative question. And so the patent was
just a a method that Andreas and another guy who
now works like Google, I believe Daniel Goldman and me
had worked on to apply this in a particular way.
And so it was basically a software pattern. There was
an Advazon pattern on an algorithm.

Speaker 2 (11:13):
So you're asking people questions, how do you know they're
giving you honest answers? And I asked that question for
very specific reasons that will be evident in a moment.
How do you know the answers are legitimate?

Speaker 1 (11:27):
Okay, So in experiment economics, one of 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

(11:48):
money twenty bucks, fifty bucks, what we'll do is we
say at the end, we're going to pick one of
the things you said you wanted, and we're going to
actually play that for money. And if you if you
don't tell us what you really wanted, you're gonna get
stuck with something.

Speaker 2 (12:00):
So you're creating an incentive for them to be somewhat honest.

Speaker 1 (12:04):
Correct.

Speaker 2 (12:05):
The reason I ask we're recording this about two weeks
before the twenty twenty four presidential election. I wrote something
a month ago about why polling errors are really a
behavioral problem because when you ask people who you're going
to vote for, what you're really asking is not just
their preference, but hey, you're gonna get your lazy butt

(12:26):
off the couch and go to the library and vote.
And I assumed, hey, there's an era of five, six
seven percent 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 going to vote, about seventy percent say
they will, In reality, just forty five percent of them do.

(12:49):
That's a massive error of twenty five percent. What value
is there in polls when people have no idea what
they're really going to do?

Speaker 1 (12:57):
Yeah, So I mean I think the best post 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 you say, people, are
you planning to vote? Oh, yeah, I'm planning to vote, Well,
you're going to Are you going to not vote because
it's too Yeah, I may not vote.

Speaker 2 (13:14):
What happens if it rains, what happens if you're busy.

Speaker 1 (13:17):
So you can often get numbers in it up to
more than one hundred percent. Are you having to vote? No,
you have seventy percent. Yeah, I probably won't vote fifty
five percent. That's one hundred and twenty five percent current.
The math doesn't math, and you see it. Particularly. One
of the things we study 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 yes's. And that's one recent new products fail. It

(13:40):
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'd wro'te a few papers
on this, but I don't feel like we exactly crack
the nut was to see if a combination of what

(14:02):
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 can help
us predict when they say, yeah, I'm going to vote,
are they really going to vote or not?

Speaker 2 (14:16):
And neuroeconomics, 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.

Speaker 1 (14:29):
Correct exactly so that so and and by the way,
ephraimri is glamorous and fantastic, but there's lots of other
methode that they are used as well. You know, it's
unnatural because people are in this tube. It's very loud.
You know, if you want to study a phobic, if
you want to study close to probi, you cannot, you know,
because the closer roobics won't go in there. But it

(14:50):
does give you a picture of the whole brain. And
in the in the case of the we need some
experiments where we show people to 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, weak yess. So we get
a four point scale and then we surprise them and say,

(15:11):
now we're going to show you some different products and
these are going to actually buy. So if you say
yes and we choose that one out of this.

Speaker 2 (15:18):
Bin, you get it.

Speaker 1 (15:19):
You have you have to buy it. Well, we give
you some money and we're going to take the price
out and give you the residual money and the product,
and you're going to leave here with this product or
I think some of them we have we mail it
to them at Amazon is something we actually had products
there in a box. And so the question is what's
going on in the brain when they're seriously thinking about

(15:40):
buying something for real versus hypothetical, which is like a survey, right,
And what we found was the tricky part is to
predict when people say yes, hypothetical, but the brain says no,
you know, can you can you see a brain?

Speaker 2 (15:55):
Can you identify that?

Speaker 1 (15:56):
Uh? Modestly well?

Speaker 2 (15:59):
Right?

Speaker 1 (15:59):
And 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 yes, called the mid brain, which
is actually where all of the dopamina drid neurons live
and then and then connect to middle areas of the
brain called basoganglia that are kind of computing reward and value.

(16:21):
And then frontal cortex, which is really putting together the
modern the modern exactly like it's like a thinking cap
on top of the monkey brain. And in the mid
brain there's a stronger signal when they say yes and
they actually do do yes hypothetical and it's a yes reel.
There's a stronger signal than when they say yes hypothetical

(16:44):
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.

Speaker 2 (16:56):
So my general sense of this, and I'm curious as
to how you what the reality is, my sense of
it is, on the one hand, people are social animals
and they want to be agreeable and say yes to people.
On the other hand, we really don't know what the
hell we want, especially if you're talking about something six

(17:16):
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.

Speaker 1 (17:35):
Some of them are undergraduates, although in Caltech they're very
unusual human beings because they're actually useful. They're very useful
labrats who pay for economics because the media and matthe
Is et Is eight hundred, they're the most mathematically skilled except.

Speaker 2 (17:51):
For that's a perfect score, isn't it?

Speaker 1 (17:52):
Like exactly, that's the perfect score, like Harvey mud 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 bounds on rationality. You know that people. We
often get critiques like well, you wouldn't get bubbles if

(18:13):
people were smart enough, Like, well, we have the smartest
people and you get bubbles.

Speaker 2 (18:18):
It's got less to do with the frontal cortex and
intelligence and everything with that, the limbic system and the
lizard brain back.

Speaker 1 (18:25):
Yes, exactly, so they have they have all the things
in the brain they have, they have other skills that
are cordically expressed. But so 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. You know, we we don't
really have a representative sample, although you could, you could

(18:45):
try to get pretty close in southern California, and then
we we we almost always never do a study this
just take outing undergrads because we worry about the robustness
across right, It is true in the case of something
like trying to get brain signals to break when people
will actually buy products. The other type of study we've
used to involves eye tracking and things like that, and

(19:05):
it turns out that when when you ask people hypothetical questions,
would you buy that? You don't really have to buy this,
but would you, they just don't look at the price
that much, 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 going
to really do, it is just something like how much

(19:26):
time they spend looking at the price and looking back
and forth. And there may be other like if if
if it was consumer products company was trying to use
FROMRI 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 eyes looking. So there are there are
things you can do outside of the confines of a

(19:49):
campus lab. I think we would just look for things
that are that are easy, easily seen biomarkers of this
mid brain activity of f MRI, because we're never gonna
be able to do that, you know, at scale in
a shopping mall or something.

Speaker 2 (20:03):
So let's go through each of these. We know what
fMRI is, right, you're in an MRI machine. EEG and SCR.
Tell us what those do.

Speaker 1 (20:11):
So eg's electro and cephalography and it's basically all the
little things on your electrodes. If your ball like me,
that's good for seasons. You know, if you're a supermodel
with big puffy Texas beauty pageant hair, then no good,
no good.

Speaker 2 (20:28):
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 have spect.

Speaker 1 (20:39):
Exactly so the you know, you can put sixteen to
one hundred and twenty eight different electrodes. The signals are
very weak, but the advantage of EG is it's really fast.
So if you want to study something like thinking fast
and slow, you know, like if I show you a
picture of a person, you have a snap reaction that
they're scary or they're someone you want to vote for,
then FRI is too slow because it measures these blood

(21:01):
flow signals that take like one or two seconds to
show up.

Speaker 2 (21:04):
But like one, one or two seconds is too slow for.

Speaker 1 (21:08):
You know, a lot is going on in the in
the first two seconds where people are thinking out of
a decision that's really interesting necessarily you know, which mortgage
to finance, their refinance their house in.

Speaker 2 (21:20):
Or literally system one thinking fast is exactly.

Speaker 1 (21:24):
So it's the term psychologist. Social psychology use is also
called thin slicing, which is that and the thin slices
on the order of meaning a very aggregate, somewhat confident
judgment is made within you know, ten seconds, thirty seconds,
there's a big literature, and we're interviewing about this that,
you know, face to base interviewing. Unless you're really trained

(21:45):
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. At least a lot of
studies indicate that.

Speaker 2 (21:55):
And SCR is what so SCR.

Speaker 1 (21:57):
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 bab, but
it just tells you arousal. You have this detectable increase
in sweating you can measure in the fingers.

Speaker 2 (22:15):
So and in all of these things, you're actually taking measurements,
not asking people things. 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

(22:37):
concept of the subconscious to neuroeconomics.

Speaker 1 (22:41):
It's pretty important. So the saying we use is sometimes
you want to ask the brain rather than ask the person,
uh huh. And there's some there's some extreme ways in
which that works. For example, if I show a face
of somebody who's expressing fear but only for thirty milliseconds,
which is one movie frame right right, and then a
mask when you're meeting another face right on top that's neutral,

(23:04):
or in another condition, I show a happy face, very enthusiastic,
and then neutral mask. If you ask people did you
see a happi or fearful face, they say, like, I
have no idea, I didn't see I didn't see either one.
But if you look at amigdal activity, which is a
region that's known to be rapidly detecting potential threats and
including fear, the amignal activity will respond to fear, not

(23:28):
in thirty milliseconds, not not happiness in the same way.
So the brain knows, it's just that it doesn't get
to the like the publicists desk, you know, good consciousness.

Speaker 2 (23:40):
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 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
we just discussing, Well.

Speaker 1 (24:01):
In terms of sheer territory, it's probably not very much.
Four brain, hind brain were prefrontal cortex would be. And
there's a lot of sensory procection 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.

(24:24):
I think it's it's it's genuinely hard to pin down
a number. Like you know, if I read, for example,
it's ninety percent subconscious and ten percent conscious, I don't
know if that's right, and it may vary across life cycle.
So you know, we usually were reluctant to pin down
a number. I think it's fair to say that there's

(24:44):
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.

Speaker 2 (24:52):
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 tell us
a little bit, what does that reveal about our decision
making process.

Speaker 1 (25:05):
So the split brain was actually first explored by Roger
Sperry at Caltech actually in his student Mike Zaniga, you know,
made a big chunk of career over out of it.
And so the split brain patients means they don't have
much communication between left and right hemispheres.

Speaker 2 (25:21):
Corpus colosum is that right, So these are the one
I remember was it was some seizure or epilepsy, and
they found cutting that stop the seizures. But then your
left brain and your right brain don't really communicate anymore exactly.

Speaker 1 (25:39):
So for example, so if you have a breakdown of
corpus closum, the right and left aren't really communicating despite
the right brain left brain. Most modern ner as signists
don't think there's that much specialization. There's some interesting kinds,
but one kind that's pretty rugged is languages mostly in
the left brain and regions called broke because area of

(26:00):
Wernicke'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.

Speaker 2 (26:09):
But the aphasia, yeah, 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
down correct exactly.

Speaker 1 (26:19):
So there are these very localized, pretty well understood A phaseias
that have to do with local damage. So there's there's
often 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 A phaseia,
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 the left region. So,

(26:42):
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 asked the person, if you see this friend

(27:04):
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 because that's the language area. But the left side
doesn't know that the right side saw a friend and

(27:24):
that's why they waved. So the left side makes stuff.

Speaker 2 (27:27):
Up, confabulates an explanation for why they're waiting exactly.

Speaker 1 (27:31):
It's like the publicist for you know, for a very
guilty person and or Mike is not 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

(27:54):
the wave occurred, but the left part of the brain
doesn't know that.

Speaker 2 (27:58):
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 with a computer. When you're
tracking eye movement, asking people about, hey, would you purchase
this product? How big of a tael is it? When
they look at the price and is it something they
just kind of glance at or is it a repeated

(28:20):
and obvious they're focusing on the cost.

Speaker 1 (28:23):
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 going to actually buy something,
we might get say forty two percent right, and with
the eye tracking data it might get up to like
fifty four, you know. So as academics we think that's
kind of a modest effect size. Now, if you're running

(28:44):
a business and you want a two percent lift and
purchase maybe a billion dollars, right, So sometimes we're a
little cautious as academics about is this a big deal
or not? I'm going to where's some of these things?
The same in the world of nudges and so on.
Sometimes a small you know what, a half increase and
get out the vote. If we could do that, you know, scientifically,
may well decide an election. Right anyway, So the lift

(29:08):
is not that big, but the two taels are basically
looking at the price, and the other is refixation, which
basically means not just looking once but going back and forth.
You know. 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.

Speaker 2 (29:29):
Right, usually a good signal exactly tells you the serious Huh.
That's really interesting. 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

(29:50):
can you combine this with other types of neuroeconomics.

Speaker 1 (29:54):
Yeah, So, actually the eye trackers we use, which are
commercially made for some iis basically and sometimes for clinical use,
they use cameras to look at what the where the
eye is looking and 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

(30:16):
pupil dilation. And pupil dilation turns out to be, you know,
the eyes that they went into the soul, so that
the pupils actually generate a lot of information. Although it's
it's crude, what the people 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.

Speaker 2 (30:36):
It's like, so wide pupil is you aroused.

Speaker 1 (30:41):
Exactly exactly? And so I think if you train yourself
and maybe depending on 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 glasses because these unglasses, right, Because the idea is,

(31:03):
if you look at your cards and you have two
ass your people will dilate like 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 people dilation and I tracking to judge
things like cognitive difficulty. A lot of the early studdies
actually were used in game theory because in game theory,

(31:25):
the assumption is if I might want to see what
my opponent's payoff is in order to decide what they're
going to 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 going to do. There's
a lot to look at. And if you ask people
for a self report, they're not going to tell you

(31:45):
exactly what their eyes are during the whole time, they're
probably looking at forty two 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.

Speaker 2 (31:59):
So that's really fascinating that speaking to the brain but
not the person gives you a whole lot more insight
into the decision making process. Speaking generally, what does this
tell us about people, as you know, rational profit seeking

(32:20):
actors in the world of finance and investing.

Speaker 1 (32:24):
I think it's useful to think about, say, young naive investors,
or that they may to be young, but people who
have less knowledge about the markets, and people who spend
a lot more time thinking about estimating fundamentals reading ten K's,
you know, having years of trading experience. Because another important
facts which we try to keep track of and biro

(32:46):
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, to like collect
memories and distill things into into knowledge. So let me
turn to the concept of price bubbles because I think

(33:07):
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 conductive's 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
looks like we can predict a little, but not great.
You know, that's a high mountain to climb. What we
found in our first fMRI study about bubbles was people

(33:31):
trade an artificial asset, so we know the value, the
fundamental value 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 that the
fundamental value is a number that we control, which happens
to be fourteen, and the value the asset comes from
the fact that if you hold at the end of

(33:53):
a period of trading, you get a dividend, or you
can invest currency in risk free bonds, and so the
trade off between the risk free earnings and the value
of the dividends establishes an equlibrium price. It's a very
simple equation, and typically the price starts around fourteen, it
goes up to maybe twenty or thirty and then crashes.

(34:14):
And then in order to bring the experiments to a close,
we have them trade for fifty periods or thirty periods,
and at the end they were able to cash the
assets out at fourteen.

Speaker 2 (34:24):
So what would you pay for an asset that you'll
get fourteen for correct after a series of dividends thirty
or fifty trading periods exactly.

Speaker 1 (34:32):
And so put yourselves in the mind, said of somebody
who in period thirty one the price is sixty, and
you kind of know that in period fifty nineteen periods
from now it's going to be fourteen. So well, unless
you think it's going to go up to seventy five, right,
So it's true. In fact, that's very helpful for me.

(34:54):
So what we found from the brain was that there's
two interesting signals, soh sort 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 is
the smart thing to do. And again, the bubble crash
is not announced. It's something you only see a store
cooking back and of your mirror, right.

Speaker 2 (35:14):
Same in natural markets exactly.

Speaker 1 (35:15):
Just like a national markets, right, bubbles are only shown
in hindsight. Gene Falum has written a lot about this.
That's one reason he's skeptical that we should even talk
about bubbles, you know, as a scientific phenomens.

Speaker 2 (35:25):
Okay, I think it goes too far with that, but anyway, anyway.

Speaker 1 (35:28):
Yeah, you know what I mean. So it turns out
the people who are more likely to sell when the
price is at sixty and we know it's going to crash,
but we're not sure when have heightened activity and insular cortex,
which is another region that's involved in emotion and interception.
So interception means.

Speaker 2 (35:46):
Knowing what's going on on the inside of your own body,
like a self awareness exactly.

Speaker 1 (35:50):
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 choke a person a little bit, or you
you know, you cut off the oxygen, not so it's dangerous,

(36:11):
but just to make them uncomfortable. Insula, financial uncertainty, the insula.
And so we think of the insula is the early
warning signal that there's going to be a crash. And
the other interesting brain region is nucleus the cummins, which
is basically a reward center and it's called straightum part
of basoganglia in the very center of the brain, and

(36:31):
that's active in the people who are fueling the bubble.
Like when the bubbles, you know, forming the people who
have the highest nucleus incumbans activity by the most.

Speaker 2 (36:41):
So 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 tails now.

Speaker 1 (36:54):
Number one, we can't tell with exquisite precision. You know,
you can sort of see these groups, and we're only
looking at this X post. 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 real
time from eye measurement that can be done, and it's like, okay,
traders seven, nine and eleven, you know, we think they're

(37:17):
probably going to sell. There the skeptics, they're the bulls
and fourteen, seventeen and twenty one. Their new kidcombanis Activity.
Seems they're really all in. They're going to be forming
the bubble and so on and so on. I mean,
we're a few steps away from be able to do it,
but we see these what we call proofs of concept
like it can be done. It may take a few
million dollars if any donors are listening.

Speaker 2 (37:39):
But it makes perfect sense that that is possible. Different
parts of the brain are responding to different inputs, 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,

(38:00):
they think it's just going to keep going forever and
they pile in. And the flip side of that, there
are people the famous irrational zuberance speech by Alan Greenspan
in nineteen ninety six. You still had a ton of
gains until the March two thousand and top. So some people,
I'm just curious what drives that. Now that you know

(38:23):
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 going to be
participating in one tribe or the other.

Speaker 1 (38:36):
That's a great question. I'll say a little tiny bit
more about that. You mentioned the term irrational exuberance, which
was coined, as I recall, by Bob Shiller in his
book about.

Speaker 2 (38:46):
I think it was from the Irrational Zuberant speech. Schiller
may have helped Greenspan with that speech, if I'm remembering,
because I've seen I've seen both, whether it was Schiller's
phrase or green Span.

Speaker 1 (39:00):
It maybe it maybe, you know, it's kind of some
you know, some apocryphal. You know, we're not sure exactly
who said it first, but certainly there was a kind
of meeting of the minds that this was useful. And
in fact, when we didn't we use 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
USA today or something. But this is the proceedings of
the National Academy of Sciences, you know, And but we

(39:23):
think of this nucleus incumbents activity. That's 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 it crashes fast. So this irrational
is really in there. Literally. But yeah, and and also
we when I present this in academic summers and later

(39:45):
today i'm meeting some Caltech people, we talk about this
famous saying from Warren Buffett. I believe when people are afraid,
be greedy, when people ready be afraid. And this brain
areas like insula is similar to fear and greed and inclusivecumbents.
You know, it's about as close you're going to get
to brain areas matching what Warren Buffett had to say,

(40:06):
which was such a wise thought.

Speaker 2 (40:08):
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,

(40:32):
it turns out there's a lot more things happening than
at least classical economics seems to imply.

Speaker 1 (40:38):
Yes, exactly exactly. And also, this isn't something we've carefully researched,
but I think it's a good speculation for your audience,
which is like when I was going to Chicago in
the late seventies, all my gratitude and friends were also
kind of critics of Nobody liked Bay of economics at
that time, though oh really, oh yeah it was you know,
people said things like I think, you know, I'm worried

(41:00):
you might be ruining your career because you switched out
of finance and well, and what it was was there
was a series 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, Like well, it
seems like that may happen, you know, Or if people

(41:21):
make these mistakes, don't they learn over time not to
make mistakes? That may also happen, and maybe 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 behaval economics, there was
really a lot of hostility about it, and then we

(41:44):
gradually one thing about Chicago, 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 you know,
their ideas. But eventually data went arguments, and there were

(42:06):
you know, there were just so many anomalies and ways
in which investors were making mistakes. And it wasn't just
small investors, you know, who were refinancing their mortgage mistakenly.
It was you know, some of these implicit things maybe
very big, you know, like venture capitalists joked about how
well you know when I think of Mark Zuckerberg and
a hoodie, and that's kind of my template for a

(42:28):
good founder to invest tens of millions of dollars. Hey, like,
that's not as sophisticated, that's not how economics.

Speaker 2 (42:35):
And I recall reading one of the papers Bob Schiller
wrote was looking at divinend yield and saying, if if
markets are fully pricing in all data, why does this
divin and 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

(42:57):
being awarded the Nobel together. It's almost says if the
committee said, look, markets are kind of efficient, and except
when they go crazy, you two guys work it out.

Speaker 1 (43:07):
Yes, yeah, yeah, it was quite a It was kind
of a charming 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 answers they both made made a
lot of progress, you know, in different ways.

Speaker 2 (43:27):
Let's talk about some of the other ways that we
can look inside. 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.

Speaker 1 (43:43):
Yeah, so, actually that's a very good question, Barry. New
economics uses a lot of different methods. The fMRI is
sort of like, you know the movie star and a
family with four sisters, you know, the glamorous one that
everyone pays attention to, but it's actually high maintenance. And
then but all the other siblings are you know, kind
of contributing in some interesting way. So pharmacology is something

(44:05):
people are really interested in.

Speaker 2 (44:07):
Meaning specifically pharmacology drugs that aren't yes, pharmacolo.

Speaker 1 (44:11):
So pharmacology is drugs, but some of those, for example,
el dopa will actually ramp up dopamine levels and you
can see if some interesting things happen.

Speaker 2 (44:20):
El Dopa is a drug you can consume correct in
order to raise your dopamine exactly.

Speaker 1 (44:25):
So it's it's al Dopa's basically administrative. So Parkinson's patients
have a degradation of dopamine and so to kind of
ramp them up to normal levels. Al dopa is often
used in treatment.

Speaker 2 (44:37):
Pharmacology is one what are some of the other forces,
So we.

Speaker 1 (44:41):
Do look at neurotransmitters like oxytocin, argoniine Vasopressint is one
that we've studied.

Speaker 2 (44:46):
Isytocin sounds a lot like OxyContin any correct overlap.

Speaker 1 (44:51):
No exactually, 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

(45:14):
produced after birth and when the mom is first coming,
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 affiliated. It's affiliated. It's this
sort of bio term. So there's a bunch of studies
on oxidosins yesting that improved trust. But there's a cautionary tale,

(45:34):
which is me and some colleagues went back and looked
at those carefully, and it seems that giving people artificial
is giving people oxytocin for a modest dose and then
see what happens, you know, an hour later. It improves
trust a little bit, but it's scientifically very very tricky
and some of the standard results if you do the

(45:56):
same exact experiment over again, you just don't always get
the same result. So we don't know how sturdy oxytocin is.

Speaker 2 (46:03):
What What are some of the other chemicals you mentioned
neurotrano When.

Speaker 1 (46:06):
We studied I'll say a little bit of was argonon vasopressin,
So that's another hormone which is similar to oxytocin, and
that when when animals are bonding in groups, this organon
vasopressant sort of you know, you'll get a surge and
it shows that.

Speaker 2 (46:22):
So 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 suggesting exactly?

Speaker 1 (46:35):
So part of me.

Speaker 2 (46:37):
Wants to say we're just meat sex operating obliviously to
what's going on underneath our skin, where we think it's
free will, But it sounds like there's a lot of
things happening below the surface that's really influencing our decision making.

Speaker 1 (46:53):
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.

Speaker 2 (47:13):
To because it's automated.

Speaker 1 (47:14):
Because it's so automated. So the fact that it's actually
grabs a lot of attention is because the automation is
we've completely flipped back in the opposite situation. Let me
tell you Urgan investor Pressen's study. We did. So. There's
a game similar to prison die Lemma, 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 is a very old fashioned name from

(47:37):
the Jean jau Bussau and the sixteen hundreds.

Speaker 2 (47:40):
We're talking about a male elk or deer.

Speaker 1 (47:43):
Yeah, an elk 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
a shoot or something like that, or they cannot 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 animals is you get one point if you

(48:05):
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 it and 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. And so what we found was when you

(48:28):
give people this AVP and it's a crossover design, which
means sometimes they get AVP and sometimes they get a
placebo because there's a well known placebo effect where if
they think maybe they got the a VP, it might
subconsciously affect the 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

(48:50):
likely to choose STAG, which is the socially risky and
beneficial thing. It's like it generates this willingness to join
the group in a way that's going to help better
everybody if another if you people join. And the other
thing that was really nice in this paper was we
also used fhor Mari. So we had two groups of
people with administering a VP, one group of scan and

(49:14):
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 globist palatue, 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 lots over and over in economics like Bezo Ganglia,
A Magdola, Nsula, PFC. But you do see activity globist

(49:38):
paladue when people under a VP are choosing STAG, So
it looks like the the a VP is sort of
promoting this STAG choice.

Speaker 2 (49:48):
But when we see people working cooperatively, you see a
similar neurotransmitter as you do in the.

Speaker 1 (49:56):
Path and it's and it's and it's causal. Right, So
these are the group of people and sometimes they just
get this.

Speaker 2 (50:01):
Drug and it makes them want to cooperate.

Speaker 1 (50:04):
And it makes them want to cooperate in a way
that with this risky it benefits the group. But we
sometimes think of it it overcomes their inhibition to be well,
I don't know if you're going to choose STAGG, and
I don't know if you're going to show up well.

Speaker 2 (50:16):
The prisoner's dilemma is you're always better off throwing the
other person under the bush.

Speaker 1 (50:21):
This is not that because here's the other person helps out,
you want to help out too. It's the best response.
So it's different structurally than the prison's dilemma.

Speaker 2 (50:29):
So I keep coming back every time I read a
new anything about behavioral finance, new economics, anything about this.
I can 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

(50:54):
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's probably certainly in investing.
It seems to be pretty problematic.

Speaker 1 (51:07):
Yeah, exactly. In fact, that's called the evolutionary mismatch hypothesis.

Speaker 2 (51:10):
Oh really, I didn't know it had a name.

Speaker 3 (51:12):
Yes, exactly, So tell us about it, called the Ritholts
if only so, this mismatch is simply we evolve to
adapt on the savannah, and that doesn't help us figure
out which bonds to buy.

Speaker 2 (51:25):
Is it that simple?

Speaker 1 (51:26):
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 financial advertisement. Those are all things that are kind
of tricking or exploiting vulnerabilities in our basic ancestral biology.

(51:48):
Now again, people are smart too, so there's there is
adaptation and kind of plasticity. So over a lifetime you
might or maybe in one mba course or even possibly
a high schoo of course, you might learn some principles
of basic finance that really help you avoid dumb mistakes.
You know, like compound interest really compounds quickly. You know,

(52:09):
the Caveman brain thinks compounding quickly. I have no idea
what that means. My brain can't imagine if I invested
in the S and P one thousand dollars forty years ago,
how much i'd have. You know, I can't compute that number.

Speaker 2 (52:21):
Well, we live in an arithmetic world. Exponential numbers, they
are hard to comprehend.

Speaker 1 (52:26):
The brain is mostly linearizing things that and if they're
not linear, or they're dramatically nonlinear, 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.

Speaker 2 (52:44):
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 a world
of neuroeconomics say about loss of version. I've seen a
few mathematicians claim, oh, it's just a statistical anomaly. I

(53:08):
remain unconvinced that that's the case.

Speaker 1 (53:11):
Yeah, so, actually I know a lot about loss of persion.
We published a meta analysis last year about.

Speaker 2 (53:16):
There's a reason I'm asking this question. It's not out
of left field.

Speaker 1 (53:19):
Right, you came to the right place. So in the
men 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 fishing,
you know, you throw this net out and you get
four thousand studies. Then you win to it down to the
ones that are really just all trying to measure the
same thing, so you can add them up. There was

(53:41):
something like three hundred and seventy estimates of lambda, which
is the Greek symbol that means the ratio of the
disutility of loss to gain. And as you mentioned, two
is sort of a we think it's a little bit
smaller like one point sabin, but you know it's comparable. Yeah,
it's comparable, and it's not one, which which would be
the case in which you're not just finguishing loss and
gain at all. You know, they're just like one scale.

(54:05):
So the evidence is pretty good. Some other fun facts
about loss of version, which is you might think that
loss of version is is some kind of handicap, but
actually we published a paper with two people who have
brain damage and bilateral amigdala, which means neither part of
the amgdala can compensate for the other. There's a very

(54:25):
unusual disease. It comes from a or a bag via
the disease, and they basically the amigdala is kind of
like calcified, so it's it's there, but it's like deep freeze,
you know, just so work.

Speaker 2 (54:36):
These people lose the ability to have these emotional responses
to stimulus.

Speaker 1 (54:41):
Correct correct, and a lot has been known about because
they've been studied. One of my colleagues, Ralphedelps, has studied
several of them for years and they you know, they
come back every so often and do a different.

Speaker 2 (54:52):
Kind of task and let me guess, they're pretty good traders.

Speaker 1 (54:55):
Generally, they're in disability because, uh, the amygdala damage is
not to make they basically take too much risk in
a lot of areas of life.

Speaker 2 (55:05):
So they're risk embracing, not risk averse at all.

Speaker 1 (55:08):
So the idea that that risk and fear are there
to kind of protect you applies to them. Like when
you remove that, like one of the patients, Sam makes
a lot of poor choices.

Speaker 2 (55:19):
Give us examples.

Speaker 1 (55:21):
Well, this example I recall, I hope I'm not getting that.
My memory is 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 you want to go out
with that person again? She said, yeah, yeah, it was fine,
it was fun. You know, she just didn't have this trauma.
The amial was not processing. This is really bad. Run away,

(55:44):
run away, avoid avoid.

Speaker 2 (55:46):
So how does this manifest itself amongst investors making risk
decisions If their ability to process threats process fear is
in present, what happens with those sort of decisions.

Speaker 1 (56:01):
Well, so for these two patients with imigal damage, they
have no loss of version.

Speaker 2 (56:05):
None whatsoever, And so aggressive traders and investors, Well, so.

Speaker 1 (56:10):
Yeah, so the way we measures we give them these
financial simple financial risks, like you could win. Most people
if you say you could win ten, but you might
lose eight or might lose seven, they're kind of just
indifferent because a loss of seven and a gainer ten.

Speaker 2 (56:23):
Or you know, if I could, if I could do
that on a billion dollars, I would, you know, I'd
love to do that.

Speaker 1 (56:28):
But these two so damage the amgala. No more loss
of version. So that's partly a reminder that be careful
what you wish for, right, right, Like you.

Speaker 2 (56:39):
Don't want to react emotionally to everything correct right. The
reason it's so hard to do, what Warren Buffett says,
is when everybody's clamoring to buy, you get most people
get caught up in that enthusiasm where we're social primates,
and when the group is screaming bye bye bye, it's
very hard to go with the other direction. And then

(57:00):
at the bottom, when everybody is selling, the fear is
of the alcohols.

Speaker 1 (57:05):
The fear of school was contagious very much. So right, yeah, yeah, yeah.

Speaker 2 (57:09):
So you lose that risk aversion. Do you have the
ability to just go opposite the crowd because you don't care?

Speaker 1 (57:17):
It could be I mean, I've I have a feeling
successful traders is it's not that they're not loss of verse,
but they managed to inhibit it somehow. Or we did
a such study in this but it's I don't think
the details are all 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

(57:39):
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 other quarter, and managed to kind of shrug
off 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. It leads into another interesting topic
which we've studied a little bit called emotion regular which

(58:01):
is the fact that a lot of our emotions are
sort of involuntary. You know, if there's a loud boom,
you and I are both going to have this fear reaction.
You know, haro, stand up will freeze. But you can
also learn to regulate emotions. I mean kids are learning
that when they learn to, you know, not be too
afraid on the first day of school. As people get older,

(58:21):
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 of
version but not too little, right, because you don't want
to like going crazy. You don't want them to be
immune to loss, just like you don't want your hand
to be immune to pain, right, because you're going to

(58:42):
lean on a hot stoves one day and not notice
that your hand is on fire. Right. So you a
good trader probably has a little less natural loss of version,
and then a really good ability to emotionally regulate, you know,
when too much loss is acceptable or getting you into trouble.

Speaker 2 (59:01):
So the emotional regulation aspect is really interesting. I'm going
to push you a little outside of 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 are these folks

(59:22):
that have put together these really impressive track records? A
surprising number of neuroatypical folks.

Speaker 1 (59:30):
Oh yeah.

Speaker 2 (59:30):
The 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.

Speaker 1 (59:44):
Here.

Speaker 2 (59:45):
In March two thousand and nine, stocks look really attractive,
and I want to be a buyer even though everybody
else is selling. Is there an aspect of that to
those sorts of ya.

Speaker 1 (59:56):
That's a fantastic topic. In fact, it is close to something.

Speaker 2 (59:58):
Oh, it is all right, good, I've been thinking about.

Speaker 1 (01:00:00):
So one thing is I was going to mention from before.
So one of the striking things. I was working on
an economics book and I was reading a lot of
papers on social conformity. It turns out that almost every
study finds the typical paradigm is something very stylized and simple, like,
you know, you see a face and three other people

(01:00:21):
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 there seems to
be a reward activity when you conform to the group.
And these are not we're not super stress testing, so

(01:00:42):
we're not quite something like you know, you're in the
depth of a crash two thousand and eight crash and
everyone's selling, and you know, ethically, it's hard for us
to generate that dramatic an event in the lab. But
even for these mild effects, and a lot of these people,
if you ask them, do you follow the craft, they
would say no, no, no, I kind of go in
my own way. Like if a bunch of people said

(01:01:03):
someone is friendly and you weren't sure, if you thought
they weren't friendly, would you disagree? H Yeah, yeah, I
wouldn't bother me. But study after study, the study shows
there's generally reward value from conformity, which is essentially just
the modern evidence for what you were talking about, which
is that part of being a social animal right.

Speaker 2 (01:01:20):
The evolution of cooperation has has been very successful for us. Exactly,
it started to fight the craft, It.

Speaker 1 (01:01:27):
Did his 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 be people who almost pathologically.
But let's get back to your point about neurotypical people.
So we're actually working at it beginning that a study

(01:01:47):
on autism, so it's autism is called a spectrum disorder,
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.

Speaker 2 (01:01:57):
So you have a little, you could have some, you
could have more, you can have a lot.

Speaker 1 (01:02:00):
Correct, correct, And there's often differences of symptoms like extreme
autism often involves catatonia and severe language deficits and what
have you. And so what people often think about Asperger 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

(01:02:24):
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, they could
have perfect pitch for a sound. They are better at
ignoring some costs, which is a classic Bayer economics. You know,
I spend so much on this dessert. You know, I
came to New York. It is eighteen dollars for some flower.

(01:02:47):
You know, I have to finish it, right.

Speaker 2 (01:02:51):
The autism, the money is spent whether you get the
categories or not.

Speaker 1 (01:02:54):
So the autists have the right idea and.

Speaker 2 (01:02:57):
There is a sweet spot. I'm going to get you
a list of the people who I know in this
field who have that fantastic impressive numbers and have either
stated there on the spectrum or it's kind of obvious hey.

Speaker 1 (01:03:14):
Yeah, yeah, yeah. You could look at film, video or
written statements and you know, machine learned them and say,
this person talks or looks.

Speaker 2 (01:03:22):
I'll ask on Twitter who's on the autism spectrum in
the world of finance and has a good track record.
But I have like two dozen names in my head.

Speaker 1 (01:03:31):
I'll give you a name. Unfortunately, he just died not
too long ago, Charlie Munger. So of course Charlie a
few times, right.

Speaker 2 (01:03:38):
And he doesn't strike me as very spectrumy.

Speaker 1 (01:03:42):
Well, but what one marker of autism is is like
poor conversational turn taking, you know. And so when the
times I met Charlie just twice and if you see
him at the Berkshire Hathaway, I mean, he's amazing. I
think it was like the Mark Twain of finance for sure,
you know, because he was really witty and but also
there's always like a really deep psychological insight in there.

(01:04:04):
You know, it wasn't just funny. It was 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 going to move the train.

Speaker 2 (01:04:19):
And different, just nudge him in different. Right.

Speaker 1 (01:04:22):
Well, you know that reminds me of X boom, and
then he's often discussing X.

Speaker 2 (01:04:26):
I never realized that about him.

Speaker 1 (01:04:27):
So you're saying, that's my non clinical I am not
a transition, but you know, disclaimer. Part of it is
reflected and 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, you know, he may have not made
them because he doesn't get caught up in social conformity,
or because he's very focused on he has good metacognition,

(01:04:50):
like if I don't I don't buy a company I
don't understand, right, you know, that's probably a good strategy.

Speaker 2 (01:04:56):
So I'm working on a new book. I'm almost done,
and Munger is 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 because Ewan and
Warren are so much smarter than everybody else? And his

(01:05:18):
response was, it's not that we're smarter than everybody else,
we were just less stupid, which is such an insightful observation. Hey,
just fewer Charlie Ellis, make less unforced errors, and you'll
do better in tennis or investing than the guy trying
to slam the ace, and most people are not going

(01:05:38):
to get it in. Him and Munger had the two
Charlie's had the same belief system, just be less stupid.
It's really fascinating. So when you've interviewed Munger, what are
some of the takeaways you've had from your conversations with him?

Speaker 1 (01:05:55):
One thing I remember was for so we went and
looked at our neuroimaging center.

Speaker 2 (01:06:00):
Did you ever get him in a machine? No?

Speaker 1 (01:06:02):
I wish. I wish we had. He he may have
gone for it too. He's you know, he's a pretty
interesting person and I think very open minds, scientifically curious
as well as in his financial life. He had gone
to Celtic 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 him to
give money and or at least show.

Speaker 2 (01:06:24):
Up and give a speech something.

Speaker 1 (01:06:26):
Yeah, talk, and so so we showed in 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.
Opioid's the really hard stuff.

Speaker 2 (01:06:48):
You know.

Speaker 1 (01:06:48):
Wait, unless 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.

Speaker 2 (01:07:01):
Let's say it makes sense.

Speaker 1 (01:07:02):
And so he was thinking as a practitioner like I
want I'm going to know what's going to work, as
scientists were 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, but it.

Speaker 2 (01:07:16):
Could be a different combination for each different exactly.

Speaker 1 (01:07:18):
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 Fallow it's definitely
the wrong word. One of the products from Beata economics
was this idea of a nudge that often because people
are often sensitive to very subtle things like opt in
versus opt out, you know there may be a low cost,
light touchway to change behavior a little bit.

Speaker 2 (01:07:41):
Well just look at the four oh one k exactly,
making the default go to just some specific investment as
opposed to it just sits there in cash for god
knows how long. Seems to have really had a big impa.

Speaker 1 (01:07:59):
Yes, exactly that that was definitely the poster child for
the simplest nudge, and we kind of understand the psychology
of it anyway. So now what a lot of people
are thinking about nudge. This is exactly this lollapaloosa idea
of Munger's, which is, if we want to get people
to get out the vote, rather than try six different things,
we should be trying like six combinations of three things. Statistically,

(01:08:22):
it's messy because you'll never really end up knowing which
of those is the active ingredient. But to just get results,
that's useful information, it's useful formation. So the Nudge Enterprise,
which I've been connected to a little bit, is moving
somewhe in that direction that Munger mentioned many years ago.

Speaker 2 (01:08:39):
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?

Speaker 1 (01:08:54):
So Katie Molkman's podcast Choiceology is one that I've been
on that I think is quite good. It's basically the
beaval economics podcasts. There are quite a few others, but
Katie is a real expert on this and is a
great interviewer and has.

Speaker 2 (01:09:07):
Had good guests choice Ology. Choice Ology tell us about
your mentors who helped to shape your fascinating career.

Speaker 1 (01:09:15):
So two people who were on my thesis committee, Robin
Hogarth and Hilly Einhorn were two and there's an interesting story.
So Robin was Scottish, very verbal, every sentence started with howsoever. Therefore, notwithstanding,
Hilly was a very blunt jew from Brooklyn, and it

(01:09:37):
was the exact opposite so Hilly would mark up my
thesis and put in all these fancy Hilly would rather
would take out the whatsoevers and the howevers and that
thereforece and he was like put in more like boom,
like short sentences, no sema colons, but like he had
one punctuation mark period. That's it right, Like you know,
he like about a million periods at a store, and
like I'm not likely to use those. And Robin was

(01:09:59):
the way around, Oh, this really need to do summa colon,
you know, let's plump this. And at one point I
was going back and forth, you know, near the completion
of my thesis with the two of them were co advisors,
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

(01:10:20):
how you want to write it. And I realized they
were kind of waiting for me to find my voice,
like they say in writing, you know, like and one
of the love tables and then 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 bilingual? So I

(01:10:40):
basically became kind of bilingual in terms of how I
was thinking. It's night. That was very helpful. The other
person probably is Dick Taylor, 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 very unusual because for career reasons and stuff, you

(01:11:03):
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.

Speaker 2 (01:11:15):
He's one of my favorite people in the world. I
got to interview I don't know half a dozen times,
only once since he won the Nobel Prize, but I
always find him so informative and entertaining, and I just
loved his response to winning the prize. What are you
gonna do with the money? His answer is, I'm going
to spend it as irrationally as I possibly can, just

(01:11:38):
so so him he enjoys life. He very much does
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?

Speaker 1 (01:11:50):
I am reading Emma Klein a book called The Guests,
especially for neworlcus in your audience. It's about a very grifty,
sketchy woman who goes to the Hamptons and kind of
cons her way around the Hamptons. It's really it's almost.

Speaker 2 (01:12:05):
Like a very didn't we have kind of a real
life thing like that happening a year?

Speaker 1 (01:12:09):
Yes, exactly. It may be loosely inspired by Anna deel
Vi in Manhattan or some similar cases. It's basically almost
like a nineteenth century novel about class, because she's very
conscious of not belonging in the Hamptons, but she's very
beautiful and kind of charming in this sort of man
eater femvatal way. And I'm almost done with that. It's

(01:12:30):
really delicious. The other thing, 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 known. I got onto him. Lee Child, who
who I.

Speaker 2 (01:12:45):
Love life reads all of his books plow through all
of it exactly. Yeah, and that did that include the
Reacher series.

Speaker 1 (01:12:52):
The Reacher series, that's what he is most famous for,
the Lee Child. But so Jim Swain was blurbed by
Lee Child, saying, Jim Swain's 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's
you know, I'm going to use recycle this and you're
very shortly for you. But basically there are procedurals about

(01:13:16):
how to cheat a casino, but in the end if
you get caught. There's also this sort of socio psycho
political 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

(01:13:38):
to them, and they're going to trade off. They're not
going to send me to jail. But if I give
them this gift. So there's a lot of layers of
This is not Dostoevski, It's not brilliant. This is not
sum but for me, 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.

(01:14:01):
They hire a lot of ex cheats, you know, to
tell them what to look for, and then these cheaters
who know you know, so truly, there's arms series of
who's gonna win? I found those really interesting.

Speaker 2 (01:14:11):
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. Carlhassen was a reorder
for the Miami Herald Prime Reporter and then just one
after another, these series of novels and his one of

(01:14:34):
his more recent books is now a TV series on
Apple Plus Bad Monkey, but all of his books it's
Bad Monkey in the I think the sequel is 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

(01:14:56):
good people in the heart of the story and it's
how do they navigate? It's just endless sea of treachery
and corruption. And he's just a delightful, entertaining writer. If
you you could randomly pick any of his books and
they're just all they're great beach reads.

Speaker 1 (01:15:13):
You know. Le Me also mentioned The Wire because I
grew up in Baltimore County and a 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 may have been Baltimore, Britimore.
And The Corner is like this beautiful I think it

(01:15:34):
was a precursor to the Wire. But it's basically about
a corner in West Baltimore everyone buys drugs, and it's
about drug addiction and all the things that's surrounded. So
as somebody who you know, one of the things we
study in behavioral economics is habits and addictions, and you know,
and the 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

(01:15:56):
Wire is almost like a documentary and it has all
this Baltimore stuff, as well as all my accents where
you have people are talking about talking like this, and
it has Tommy Garcetti is this political character who's sort
of inspired by Tommy Delsandro, whose daughter is Nancy PELUSI.

Speaker 2 (01:16:12):
Oh really, that's amazing. I found the series the Wire.
It's a tough watch. It's a great show. It's brutal. Yeah,
gritty is mild. I mean some of the stuff that
goes on, and the show is.

Speaker 1 (01:16:26):
Just like, yeah, there's a famous scene with the nail
gun you're which if your listeners have the stomach, that's
pretty classic.

Speaker 2 (01:16:34):
Similar in the Jack Reacher series, there's a really something
not that far off. Yeah, they toned it down for television,
but the book is is really brutal. All Right, we're
up to our final two questions. What sort of advice
would you give to a college grad interested in a
career in filling the blank neuroeconomics, behavioral finance, or even

(01:16:57):
just investing.

Speaker 1 (01:16:58):
For somebody who say it doesn't want to get a PhD.
That's a different track and probably of less interest. And
there's you can get a lot of guests 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, because even though game theory is

(01:17:19):
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 do I know
that they don't know it? 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

(01:17:40):
this term, and there's a lot of data from sports
about whether sports activities are like equilibrium responses to other players,
So you can actually there's there's a lot of sources
of data besides just say the lab experiments. I talk
about my book from two thousand and three, Sneaking the
Plug in Cognitive science is something I would study too.

(01:18:00):
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
a mismatch. But they are 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

(01:18:23):
be rational if you only have so much working memory,
or you're under time pressure, or you're tired. It's also
closely related to the way economists would think about mistakes,
which is they may be optimal given some constraint, 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,

(01:18:48):
whether in turning or I'll tell you a story about
what worked for me, which was when I was twelve
years old in Cockeysville, Maryland, August, there was a one
month month racing program at a small racetrack called Timonium, Maryland,
and it was a five eighths of a mile tracks.
It's like a you know, small I would go with

(01:19:09):
my dad and a friend of his who was a stockbroker,
and we would also go to the big tracks like
Pimlico where the preak mistakes is. But if you go
to Timonium, you get to see all the horses. There
was so much interest. You learned so much about markets.
Number one. It gives you, I think, a respect for
market efficiency.

Speaker 2 (01:19:27):
Couse, the odds are actually not that bad. They were
extremely pretty pretty dead on exactly.

Speaker 1 (01:19:32):
And so you see, you know, eight horses come out,
they all look pretty similar. You know, 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 fifty e d chance to win. A
number six, who looks pretty good too, is like seventy
to one, and they're mostly right. So you know, part

(01:19:55):
of why I got into economics and psychology was thinking
about episodes like that, how does the market put this
information together? And are the mistakes? Like how do you
beat the market?

Speaker 2 (01:20:07):
So Fama turns out to be more or less right about.

Speaker 1 (01:20:09):
You about twenty in Maryland. And there were other interesting
lessons too, like so on the if you go with
like around the third race. You know, I was I
was a kid, so I just broke and my poor mom,
my irish mom, was worried I was going to you know,
lose too much money. I kept telling you, it's tuition, mom,
it's tuition. But if you go in the third race,

(01:20:30):
there were these people who would sell tip sheets for
like five dollars, right.

Speaker 2 (01:20:33):
And you know, because because they know what's going to happen,
they're selling the tip sheets, not making the bets.

Speaker 1 (01:20:37):
Exactly the customer's yachts exactly. But if you go like
in the you know, the third or fourth race, they
would quit selling them. They would just give them to
you really well, like a lost leader. Maybe you'll you'll
maybe next time you'll buy it. And so I'm sitting here,
here's my little cynical twelve thirteen year old brain thinking,
why are you giving away for free tips that you

(01:20:59):
claim can make me money? Like this does not the
math does not math. And I think that's a good lesson,
like for markets. Right yeah, but you know, just just
to clear away like the most naive, you know, immunize
yourself to the most naive schemes.

Speaker 2 (01:21:16):
You know, you would think if the tips were valuable,
rather than waste your time printing it up and selling them,
you would just bet on the wing horses, especially in.

Speaker 1 (01:21:25):
A peramutual system, right because you know, the more the
more your tip sheet buyers are betting on your horses.

Speaker 2 (01:21:33):
The lower guts right exactly.

Speaker 1 (01:21:35):
They're betting against.

Speaker 2 (01:21:38):
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 nineteen eighties.

Speaker 1 (01:21:50):
You know, I'll answer that like a politicial answer a
question I have a better answer for, which is about
behavioral finance.

Speaker 2 (01:21:55):
Sure, so either or be fire or sure?

Speaker 1 (01:21:59):
I got it. So in your economics, I don't think
we made too many mistakes. I think I wish we had.
You know, we got a lot of grand support. Caltech
was very supportive. I got to know a lot of
interesting people who are generous with their time, who were
kind of my tutors on neuroscience. I never took any formal,
you know, coursework on it. It was came way, way
way after my original rad training. So thank you everyone.

(01:22:23):
I wish we had. We have not had much impact
in academic economics particularly, and 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
nineteen seventy eight, Mike Jensen published a very influential paper.
It was an intruction to a special issue, and one
of the first sentences is the market efficiency apothesis is

(01:22:46):
one of the most well established empirical regularities in economics.
But but that was like the high water mark, and
the special issue was about there's some things that are anomalists,
like earnings drift. He got a weird earnings announcement. The
market reacts, but then the market reaction drifts up for it.
It takes a couple of weeks, almost like food for

(01:23:07):
the market so so absorbed it should not take a
couple of 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 ba Heybalk finance was ferocious.

Speaker 2 (01:23:28):
That's a big word at that time. It was that
so late seventies, early late.

Speaker 1 (01:23:32):
Seventies, early eighties, and so that's when I was kind
of deciding do I want to stay in finance or
mix it with and I remember having a discussion. I
don't know if Jeane 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 this sense.
Even though I didn't end up doing work that was close,
you know, he was he was really relentless and very
empirically driven, and he had a really good idea. When

(01:23:54):
he started, people were thought he was crazy 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 would like,
what be dividends at all? You just like take money
from one bucket and put it in the other.

Speaker 2 (01:24:11):
Well, back in the early days of widows and orphan stocks,
you people lived on.

Speaker 1 (01:24:15):
Their digiti Yeah, exactly because of the liquidity.

Speaker 2 (01:24:17):
Right, you don't want to sell do you want to
hold on to it?

Speaker 1 (01:24:20):
And then the dividends, you know, it is enough to
live on.

Speaker 2 (01:24:22):
Now the theory has shifted towards uh, it's more efficient
return of capital to shareholders doing buybox than dividends. But
that's only total return. If you're looking for that income stream,
buybacks don't necessarily help you.

Speaker 1 (01:24:37):
Right, right exactly. So that's and that's also where the
hero economic comes in with you know, why can't you
just like create whatever income stream you want by borrowing
and selling, right, 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
if I had known behavioral finance, would it didn't take

(01:24:59):
off quickly. From nineteen seventy eight, which is Jensen nineteen
eighty one, I graduated nineteen eighty five was the failure
in DeMont paper about January effects. And even that was
published as a It was in the Proceedings issue, which
meant that the President of the of the AFA could

(01:25:19):
pan pick papers. So the preceding issue had the most
radical papers that were the foundation of aper economics. Fisher
Black wrote a paper called Noise Traders. I thot it
might have just been called noise. And then Dick Roll
wrote a paper got R Squared, and he said, you know,
if only news moves the market, right, then the R

(01:25:39):
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
you in the beginning, Days with big news, big obvious
news and hardly any news move about the same.

Speaker 2 (01:25:57):
The assumption being by the time it's in the front
age of the new York Times, it's already reflected the.

Speaker 1 (01:26:03):
Markets, right, But also there may be things that are
not newsy at all, Like in October eighty seven crash,
you know, the Bundesbank moved rates by a quarter of
a point or something.

Speaker 2 (01:26:13):
Who cares? That was the big news, right, but you know,
you never know when that last straw breaks the camels correct.

Speaker 1 (01:26:19):
But but so all those ideas now that that we
we you know, we feel like we have an understanding
and examples. There was a lot of hostility to that.
So 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, Mike? And psychology is Boston accent? You know.

(01:26:42):
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 moved.

Speaker 2 (01:26:48):
They don't know why, right, Well, no one wants to
admit it's fairly random day to day. We're very humans
are very I know that humans are very uncomfortable.

Speaker 1 (01:26:58):
And we're good at pattern right.

Speaker 2 (01:27:01):
We make up patterns. We come up with a narrative
to explain it. I recall Dick Thaylor quoting maybe it
was Max Planck, who's talking about physics scientis one funeral
at a time. Taylor said the same thing about behavioral finance,
and he also said, I'm bypassing the current generation and

(01:27:22):
going right to the kids so they'll adapt a 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 seems to have worked. Oh yeah, no, absolutely, Colin,
thank you so much for being so generous with your time.
This has been absolutely fascinating. I'm glad we finally managed

(01:27:44):
to do this. We have been speaking with Professor Colin
Camera of California Institute of Technology. If you enjoy this conversation,
well check out any of the five hundred previous interviews
we've done over the past ten and a half years.
You can find those at iTunes, Spotify, YouTube, Bloomberg, wherever

(01:28:04):
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.

(01:28:25):
I would be remiss if I now to 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 Ridhelts. You've been listening
to Masters in Business on Bloomberg Radio.

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