# How Investors Fall Into Bias Traps with Economists Richard Thaler & Alex Imas

An episode of [Masters in Business](https://invisiblenetwork.ai/podcast/730188152), 16 Jan 2026, 1 h 26 min.

Audio: https://podtrac.com/pts/redirect.mp3/traffic.omny.fm/d/clips/e73c998e-6e60-432f-8610-ae210140c5b1/4e4cd910-40a1-4619-a5f3-ae2b0012ffff/7f1411cf-f30b-4531-9c59-b3d401130225/audio.mp3?utm_source=Podcast&in_playlist=5873a3cb-298f-40bc-b71f-ae2b0013000d

Barry speaks with Richard Thaler and Alex Imas award winning economists and co-authors of "The Winner's Curse: Behavioral Economics Anomalies". They discuss the psychology of spending at auctions, and the effects of draft picks on NFL team spending. They also discuss the anomalies of human behavior and decision making that challenge classical economic theories. See omnystudio.com/listener for privacy information.

## Transcript

[0:02] Speaker 1: Bloomberg Audio Studios, Podcasts, radio News. This is Masters in
[0:11] Speaker 1: Business with Barry Ritholts on Bloomberg Radio.
[0:16] Speaker 2: This week on the podcast, two extra special guests alex
[0:20] Speaker 2: EMUs and Richard Thaylor. Took Richard's book The Winner's Curse
[0:25] Speaker 2: and really completely rewrote it and updated it for twenty
[0:28] Speaker 2: twenty five. I've been privileged to speak with doctor Taylor
[0:33] Speaker 2: number of times over the past few years. He's been
[0:35] Speaker 2: a guest both here and live in Chicago a number
[0:40] Speaker 2: of times. Always a fascinating conversation. And alex EMUs, is
[0:45] Speaker 2: this really interesting professor who I had no idea I
[0:49] Speaker 2: have used and relied on his previous research. Selling Fast
[0:54] Speaker 2: and Buying Slow is a chapter in my book. Just
[0:57] Speaker 2: an amazing coincidence. Both fascinating people and if let This
[1:01] Speaker 2: conversation was a lot of fun, and I think you
[1:04] Speaker 2: will also with no further ado, alex Amus and Richard
[1:07] Speaker 2: Thaylor on The Winner's Curse.
[1:10] Speaker 3: Thanks Barry, great to be back.
[1:12] Speaker 2: Yes, it's so great to have you. So you started,
[1:16] Speaker 2: you wrote this book. It's thirty years ago already. We're
[1:20] Speaker 2: gonna get to this in a bit. Before we do,
[1:23] Speaker 2: I want to just talk about both of your backgrounds
[1:26] Speaker 2: and how you began collaborating. Richard, you've been called the
[1:31] Speaker 2: godfather of behavioral economics. Take us back to the beginning,
[1:35] Speaker 2: when you were a young economist. How did you become
[1:38] Speaker 2: interested in psychology and decision making? It?
[1:42] Speaker 4: So, when I was in grad school and I was
[1:46] Speaker 4: learning standard economics, I kept pausing and saying, really, because
[1:54] Speaker 4: the models that we were being taught the people, well,
[2:00] Speaker 4: there are no people, and there are agents, and there
[2:05] Speaker 4: are firms, and there are things they call consumers, but
[2:09] Speaker 4: they're not really people.
[2:11] Speaker 3: Homo economists, homo homo economicus.
[2:15] Speaker 4: And I started making a list of dumb stuff people do,
[2:24] Speaker 4: and but that was just to annoy my friends.
[2:29] Speaker 3: But then somebody introduced me to the.
[2:33] Speaker 4: Work of to Israeli psychologists Danny Kahneman and nameds. Tavski,
[2:40] Speaker 4: And when I read their papers, I had this big
[2:44] Speaker 4: Aha moment because what their research showed was not just
[2:51] Speaker 4: that people make mistakes. Of course, we all make mistakes
[2:54] Speaker 4: and I can't remember where we left our keys or
[2:57] Speaker 4: what have you. What they showed was that behavior is
[3:03] Speaker 4: predictably different from the model that economists use. And that
[3:12] Speaker 4: was an AHA moment for me because it meant I
[3:16] Speaker 4: could say, look, the model is wrong and in this direction,
[3:22] Speaker 4: and you can think about that from an investment point
[3:26] Speaker 4: of view. It's fine to say stock prices are wrong.
[3:32] Speaker 4: That's fine, but useless. If you can say which ones
[3:35] Speaker 4: are too high and which ones are too low, then
[3:38] Speaker 4: all of a sudden you're a very rich man. So
[3:43] Speaker 4: if we could say how people are different than this
[3:49] Speaker 4: artificial model, than.
[3:51] Speaker 3: We could be in business. And then.
[3:57] Speaker 4: So I was doing that for a while, managed to
[4:00] Speaker 4: get tenure at Cornell University and spent a year with
[4:10] Speaker 4: Connoman and Tiwski, and then a second sabbatic year with Connoman,
[4:15] Speaker 4: and in nineteen eighty five, the year Alex was born,
[4:24] Speaker 4: I came back from sabbatical and decided to start writing
[4:30] Speaker 4: a series of columns in a new economics journal called
[4:35] Speaker 4: the Journal of Economic Perspectives. That journal, by the way,
[4:40] Speaker 4: here's a free tip. That journal is available free to anyone,
[4:46] Speaker 4: and the articles are written to be understandable, and people
[4:53] Speaker 4: don't know about it. If you're really interested in economics,
[4:57] Speaker 4: go and read some papers.
[4:59] Speaker 2: And the the column you were writing was called anomalies,
[5:03] Speaker 2: which were all of these things that were supposed to
[5:06] Speaker 2: not be possible given traditional economic theory. You mentioned Khonomen
[5:13] Speaker 2: and Tavsky. When you think of psychologists, you don't think
[5:17] Speaker 2: of quantitative, data driven, rigorous models. But really that was
[5:23] Speaker 2: at the heart of what they were doing, wasn't it.
[5:25] Speaker 3: Well, eventually.
[5:29] Speaker 4: Their earlier work you're thinking of prospect theory, which is
[5:33] Speaker 4: nineteen seventy nine. The work they did in the seventies
[5:36] Speaker 4: leading up to that was on predictions or judgments, and
[5:43] Speaker 4: the models weren't very quantitative. They were typically a little
[5:51] Speaker 4: scenario and almost like a thought experiment. You know, there's
[5:57] Speaker 4: a famous experiment about Lynn and they give you.
[6:02] Speaker 3: A description of Linda.
[6:04] Speaker 4: She was an undergraduate active in social movements, went to
[6:10] Speaker 4: lots of demonstrations, blah blah blah. She's now And now
[6:17] Speaker 4: you get a list of occupations and you're asked to
[6:20] Speaker 4: say which is most likely. And one of the ones
[6:25] Speaker 4: is bank teller, and another one is feminist bank teller.
[6:30] Speaker 4: And people think she's more likely to be a feminist
[6:35] Speaker 4: bank teller than a bank teller. Now, obviously that cannot
[6:40] Speaker 4: be true. I shouldn't say obviously, because many people are
[6:44] Speaker 4: now listening and saying, what does he mean? Obviously, obviously
[6:47] Speaker 4: she's a feminist bank teller. She couldn't just be a
[6:50] Speaker 4: bank teller. But that's you know that number theory. They
[6:54] Speaker 4: are going to be more bank teller.
[6:55] Speaker 2: Yeah, bank.
[6:56] Speaker 4: Think of a Venn diagram, right, there's a a big
[7:00] Speaker 4: circle of bank tellers and then a small one with
[7:06] Speaker 4: feminist bank tellers. So that was the kind of things
[7:10] Speaker 4: they were doing. There was a little bit of theory.
[7:14] Speaker 4: So like they had. The idea was that life is hard,
[7:20] Speaker 4: and so people used what they called heuristics rules of thumb.
[7:26] Speaker 3: To make judgments.
[7:27] Speaker 4: One is called the availability heuristic, which is if it's
[7:32] Speaker 4: easier to think of examples of something, it's more likely.
[7:37] Speaker 4: So if you ask people what's the ratio of homicides
[7:40] Speaker 4: to suicides, people think maybe two or three to one
[7:45] Speaker 4: that homicides.
[7:46] Speaker 3: Are more likely. It's just even money, no, twice as
[7:50] Speaker 3: many suicides.
[7:53] Speaker 4: Think about this before you buy a gun, right, the
[7:56] Speaker 4: most likely person to get killed with that gun is
[8:00] Speaker 4: a family member. So but again, notice this is a
[8:05] Speaker 4: predictable mistake. And because why well, there's lots of stories
[8:12] Speaker 4: in the newspaper about homicides.
[8:16] Speaker 3: Suicides tend to be quieter.
[8:18] Speaker 2: There's a wonderful graphic from our world in data, which
[8:23] Speaker 2: was Hans Rosling's work. That shows here's how things are
[8:27] Speaker 2: reported in the media, and then here's their actual percentage
[8:31] Speaker 2: in real life. Very little reporting on cancer, heart disease,
[8:36] Speaker 2: high blood pressure, diabetes. You're fifty thousand times more likely
[8:42] Speaker 2: to suffer from that than homicide, terrorism, or shark attacks,
[8:48] Speaker 2: which they love to uh.
[8:49] Speaker 3: Write shark texts. Don't worry about so.
[8:52] Speaker 2: Chespesralia, especially in Chicago, it's probably not.
[8:56] Speaker 3: A big Yeah, they are very few.
[8:59] Speaker 2: So let's let's bring Alex in. So when Richard started
[9:04] Speaker 2: out in the field, there really wasn't any such thing
[9:08] Speaker 2: as behavioral economics. You have an advantage a few decades
[9:12] Speaker 2: later of entering the field of behavior of economics, where
[9:17] Speaker 2: behavioral economics is a thing. Tell us a little bit
[9:20] Speaker 2: about what brought you into the field and how you
[9:23] Speaker 2: found your way over to booth.
[9:25] Speaker 5: Well, so, behavioral economics was a thing out in the
[9:28] Speaker 5: economics journals, and you know there are people certainly doing
[9:31] Speaker 5: it in various departments, but it wasn't a thing as
[9:35] Speaker 5: an undergrad Like, I don't think there was a single
[9:37] Speaker 5: behavioral economics course offered an Northwestern University while and this
[9:41] Speaker 5: was two thousand, two thousand and three through two thousand
[9:44] Speaker 5: and seven. So even though you know, people were publishing
[9:47] Speaker 5: behavioral economics papers, it was all over the journals. People
[9:51] Speaker 5: generally in the field knew about it as an undergraduate,
[9:54] Speaker 5: it still had not made it into the court three
[9:56] Speaker 5: to seven.
[9:57] Speaker 2: Danny was two thousand and two on the nobelis. Yeah, right,
[10:00] Speaker 2: you would have thought someone might have picked up on that,
[10:03] Speaker 2: And yet.
[10:03] Speaker 5: No, I mean, Western is a big school. You open
[10:06] Speaker 5: up a microeconomics textbook, it's the same textbook from nineteen
[10:09] Speaker 5: seventy three.
[10:10] Speaker 2: Basically today it's still come on, Really, I would have
[10:14] Speaker 2: assumed at this point, open up a textbook Danny Kahneman,
[10:19] Speaker 2: Bob Schiller, Richard Thaylor, how many Nobels have to come
[10:24] Speaker 2: in this space.
[10:25] Speaker 5: Before starts with perfect competition? Uh huh. Then at the
[10:28] Speaker 5: end maybe you learn something about monopolies and that that's
[10:31] Speaker 5: pretty much it. So it's a I Actually I was
[10:34] Speaker 5: pre med. I I'm an immigrant kid from Oldova. So
[10:37] Speaker 5: my parents are like, well, you're going to the medical
[10:40] Speaker 5: school or you're going to fail. Basically, so I had
[10:43] Speaker 5: one option on the table. So I was pre med.
[10:46] Speaker 5: Organic chemistry was real hard, and it was eight o'clock
[10:48] Speaker 5: in the morning. So I took econ to kind of
[10:51] Speaker 5: just boost my GPA. I thought it was kind of fun, right,
[10:54] Speaker 5: and you know, I didn't. And it was interesting because
[10:56] Speaker 5: I was taking these psychiatry abnormal psychology classes learning about
[11:00] Speaker 5: human behavior. I was thinking economics, which is the study
[11:03] Speaker 5: of human behavior, and these were like two completely different worlds. Right,
[11:07] Speaker 5: Economics is these hyper rational utility maximizers had never made
[11:12] Speaker 5: any systematic mistakes, and no, I didn't learn about a
[11:16] Speaker 5: single deviation from that principle in the entire four years
[11:18] Speaker 5: I was there. And so I was thinking, this is
[11:21] Speaker 5: kind of you know, this is fun, but not something
[11:23] Speaker 5: I wanted to do. I'm interested in human beings. And
[11:26] Speaker 5: then afterwards I was applying to medical school, and I
[11:29] Speaker 5: was doing a cross country road trip with one of
[11:31] Speaker 5: my friends to Los Angeles and we were listening to
[11:35] Speaker 5: I think it was NPR, and it turned out ex Post.
[11:40] Speaker 5: I figured this out. Richard was on the radio talking
[11:43] Speaker 5: about something called behavioral economics, and I was like, what
[11:48] Speaker 5: is this? And as soon as I got to Los Angeles,
[11:51] Speaker 5: you know, I went on the internet and I was like,
[11:53] Speaker 5: I got to find out more about this field. So
[11:55] Speaker 5: I within two weeks I had, you know, talked to
[11:58] Speaker 5: my advisors at Northwest. I want to get an EYCONPHD.
[12:03] Speaker 5: If I can do something like this where I could
[12:04] Speaker 5: combine my interest in economics and bring in human behavior
[12:08] Speaker 5: into it, this is what I wanted to do.
[12:10] Speaker 2: So let's talk about that. There's something in the book
[12:13] Speaker 2: and we'll get to that shortly. Where you describe Richard.
[12:16] Speaker 2: You describe an economist developing a new model, a new
[12:21] Speaker 2: calculation for how consumers should behave in response to certain
[12:28] Speaker 2: price incentives. So the first time ever someone creates this
[12:32] Speaker 2: calculation and then immediately afterwards and therefore this is how
[12:36] Speaker 2: all consumers are or should be behaving when nobody had
[12:40] Speaker 2: thought of this previously. How do you square that circle?
[12:43] Speaker 2: How do you square the model? Driven? This is the
[12:46] Speaker 2: right way to do it. I just figured this out,
[12:48] Speaker 2: and therefore everybody should be doing it this way.
[12:52] Speaker 4: Yeah, you know, maybe just a tiny bit of history
[12:56] Speaker 4: will get us there. So economics didn't used to be
[13:00] Speaker 4: that extreme. If you go back and read Adam Smith,
[13:04] Speaker 4: he talks about self control problems and overconfidence, and people
[13:09] Speaker 4: think of him as the father of right wing economics.
[13:14] Speaker 3: That's not the guy.
[13:17] Speaker 4: He did talk about the invisible hand, but he was
[13:21] Speaker 4: a behavioral economist at heart, and economists were pretty reasonable
[13:26] Speaker 4: until about World War two. And then what happened was
[13:31] Speaker 4: people started writing math doing math, and they wanted to
[13:35] Speaker 4: write down models. And if you want to write down
[13:38] Speaker 4: a model, the easiest one to write down is a
[13:42] Speaker 4: rational model.
[13:44] Speaker 3: And that's because.
[13:48] Speaker 4: Anybody, if you've taken high school calculus, you know you
[13:53] Speaker 4: can maximize. You set the first derivet of equal to zero,
[13:57] Speaker 4: and that's the model, right, So writing down a model of.
[14:02] Speaker 3: Some ish is hard.
[14:07] Speaker 4: Then during the seventies and eighties, people started to get
[14:14] Speaker 4: ideas for even smarter behavior, and a norm kind of
[14:21] Speaker 4: developed in economics, which is, if the agents in my
[14:25] Speaker 4: model are smarter than the agents in your model, then
[14:30] Speaker 4: my models.
[14:30] Speaker 3: Better than your model. And that's kind of crazy, but.
[14:38] Speaker 4: That was the way the field was going and there
[14:44] Speaker 4: was no real stopping it.
[14:47] Speaker 3: So around the.
[14:51] Speaker 4: Time that Alex was thinking about going to grad school,
[14:56] Speaker 4: there were troublemakers like me pointing at certain body parts
[15:02] Speaker 4: of this naked emperor. But the field was rushing toward
[15:10] Speaker 4: an extreme version of homo economicus, where Homo economicus is
[15:17] Speaker 4: a genius.
[15:19] Speaker 2: So We were talking a little earlier about the so
[15:22] Speaker 2: called wealth effect, which is something that the economists at
[15:25] Speaker 2: the Federal Reserve love. The higher the market goes, the
[15:33] Speaker 2: wealthier people supposedly feel, and they all go out and
[15:36] Speaker 2: spend money. That's like just such a perfect example of
[15:40] Speaker 2: a model that doesn't reflect the real world. A huge
[15:45] Speaker 2: amount of stocks are owned by the top ten percent.
[15:48] Speaker 2: It's something like fifty two percent of stocks. The average
[15:52] Speaker 2: person doesn't really have a whole lot at stake in
[15:55] Speaker 2: the market. And the reality is people are spending more
[15:59] Speaker 2: money because the economy is doing well. They have jobs
[16:01] Speaker 2: or getting raises, which, by the way, all helps the market.
[16:05] Speaker 2: How often do we run into these correlation causation issues
[16:09] Speaker 2: in economics, Well, we.
[16:11] Speaker 3: Run into them all the time.
[16:13] Speaker 4: Look the big problem with that with the wealth effect.
[16:18] Speaker 4: There's a lot of discussion of that in this book.
[16:22] Speaker 4: One thing economists leave out is what I call mental accounting.
[16:27] Speaker 4: And if you look at an economic model of the
[16:29] Speaker 4: wealth effect, there's some big w for wealth and that's it.
[16:35] Speaker 4: And wealth will include your house and your retirement money,
[16:42] Speaker 4: and money you've set aside for your kid's education, and
[16:47] Speaker 4: then money that you intend to give to charity.
[16:50] Speaker 5: And your future expectations.
[16:51] Speaker 6: And right and all of the money that you start right,
[16:55] Speaker 6: So now the people have defed if they're saying, well,
[17:01] Speaker 6: w goes up, then people spend more. No, it turns out,
[17:06] Speaker 6: for example, if the value of your house goes up,
[17:10] Speaker 6: how much more do you spend?
[17:12] Speaker 4: Approximately zero? Really approximately zero. Whereas if some stock you
[17:22] Speaker 4: own gets bought and you get a check, you spend
[17:27] Speaker 4: a lot of that. If you win a lottery, you spend.
[17:31] Speaker 3: Like half of it and go bankrupt.
[17:34] Speaker 4: So where the money sits has a big effect on
[17:40] Speaker 4: how much of it you spend.
[17:42] Speaker 2: Your response to somebody's question how are you going to
[17:45] Speaker 2: spend the windfall from the Nobel Prize was one of
[17:49] Speaker 2: my favorite answers. You said, do you recall?
[17:54] Speaker 4: Yeah, well I recall. I mean this was at four
[17:57] Speaker 4: in the morning. They call you and wake you up
[18:02] Speaker 4: and then say go get some coffee because you have
[18:04] Speaker 4: a press conference in half an hour. And I had
[18:09] Speaker 4: heard enough of these interviews to know that somebody was
[18:13] Speaker 4: likely to ask me that question, and my instinct was
[18:18] Speaker 4: to say, well, you know, to a real economist, this
[18:21] Speaker 4: is a stupid question, because how am I going to know?
[18:26] Speaker 3: You know, suppose I go out and buy some fancy
[18:30] Speaker 3: new car. Barry likes fancy cars. I don't. I like
[18:34] Speaker 3: fancy wine.
[18:35] Speaker 4: So suppose I go and buy a case of fancy wine.
[18:39] Speaker 4: How do I know that's the Nobel money as opposed
[18:43] Speaker 4: to the money I got from selling a book.
[18:45] Speaker 2: All dollars are fungible.
[18:47] Speaker 3: All dollars are fungible.
[18:48] Speaker 4: And you know, I've realized later that what I should
[18:53] Speaker 4: have done is opened up a special account, the prize,
[18:58] Speaker 4: Nobel Prize money, and a credit card that's linked to that,
[19:04] Speaker 4: and when I want to go buy something stupid, just
[19:08] Speaker 4: take out the Nobel card and life would be more fun.
[19:13] Speaker 2: But the line that you said was as irrationally as
[19:16] Speaker 2: I can.
[19:17] Speaker 3: Yeah, I said, I'll just spend it as irrationally as possible.
[19:20] Speaker 3: Just I knew it would be a memorable line.
[19:23] Speaker 2: So it's so funny because that line led to a
[19:27] Speaker 2: conversation with my CFO about the difference in all of
[19:32] Speaker 2: these you know, the Chase Sapphire card or the X
[19:36] Speaker 2: Platinum card where you get these points and the rational
[19:40] Speaker 2: CFO says, hey, I want the money back each month,
[19:45] Speaker 2: And my response is always it's one hundred, two hundred dollars.
[19:49] Speaker 2: It's lost in your bank account. You don't see it.
[19:52] Speaker 2: When I get the points and want to buy a
[19:55] Speaker 2: fancy cappuccino maker that my wife is going to yell
[19:58] Speaker 2: at me, Why you spending two thousand dollars on a
[20:01] Speaker 2: cappuccino maker, you idiot. My answer is, Oh, no, it's points,
[20:04] Speaker 2: it's free, and she's like, okay, go get it. It's
[20:08] Speaker 2: the exact same concept. If you have that silo, that
[20:12] Speaker 2: mental accounting, you could do as much of rationality as
[20:15] Speaker 2: you'd like.
[20:15] Speaker 4: So you know, but watch out if she listens to
[20:19] Speaker 4: this podcast.
[20:20] Speaker 2: She listens to the first five minutes, and that's this, Oh.
[20:23] Speaker 4: Yeah, so you're safe because so I'll tell you a
[20:26] Speaker 4: story about my daughter Maggie, who lives in Rhode Island,
[20:32] Speaker 4: and one of her neighbors grew up to be a
[20:34] Speaker 4: pitcher for the Mets, and the Mets were playing in
[20:38] Speaker 4: the playoffs the.
[20:39] Speaker 2: First round, so it's a long time ago, yeah, and
[20:43] Speaker 2: this old.
[20:43] Speaker 4: Story, and this guy was going to pitch. So I
[20:48] Speaker 4: called Maggie, Hey, would you guys want to go to
[20:51] Speaker 4: the game?
[20:52] Speaker 3: Let me see if I can get tickets, and she says, oh,
[20:55] Speaker 3: that'd be great. So I go online the game is
[20:59] Speaker 3: like tomorrow, and I find some tickets and there were
[21:03] Speaker 3: a bunch you know, on stub hub or something you
[21:05] Speaker 3: could get tickets. So I text her back and said,
[21:09] Speaker 3: look here, here's the website. It looks like there are
[21:13] Speaker 3: lots of tickets to choose from. How about the tickets
[21:18] Speaker 3: were about three hundred bucks.
[21:19] Speaker 4: I said, how about I'll text I'll send you one
[21:23] Speaker 4: thousand dollars buy the tickets you want, spend the rest
[21:26] Speaker 4: on hot talks.
[21:27] Speaker 2: So you're doing an experiment on your daughter to see
[21:30] Speaker 2: if she buys the cheap tickets or no.
[21:31] Speaker 5: Oh no.
[21:32] Speaker 4: So she texts me back and says, lol, this is
[21:36] Speaker 4: just like in your book. If you send me one
[21:39] Speaker 4: thousand dollars, I'm not going to use it on baseball tickets.
[21:44] Speaker 4: So I've learned my lesson. Recently, she wanted to go
[21:50] Speaker 4: to a concert. David Byrne is on tour and he
[21:55] Speaker 4: was in Providence, where she lives, and she wanted to go.
[21:59] Speaker 3: And she says, so, some way you could get me tickets.
[22:02] Speaker 3: I said, to the.
[22:02] Speaker 2: Tickets instead of the money, that's so funny. Let's talk
[22:06] Speaker 2: a little bit about the book The Winner's Curse and
[22:09] Speaker 2: I want to start with Alex. So this book has
[22:12] Speaker 2: been out since you were a young kid, and you
[22:16] Speaker 2: go to college, you eventually figure, let me get a
[22:19] Speaker 2: PhD in behavioral economics or finance and economics. How did
[22:24] Speaker 2: you first discover this book? What was your initial response
[22:27] Speaker 2: to it?
[22:29] Speaker 5: So I discovered it. There's not really any textbooks and
[22:32] Speaker 5: behavioral economics, so you kind of get here through the
[22:35] Speaker 5: grape vine. Oh, you should read this, you should read that.
[22:38] Speaker 5: You mostly read journal articles like with if you're thinking
[22:41] Speaker 5: about doing game theory or something like that. There's like
[22:44] Speaker 5: five or six textbooks that you can read with behavioral economics.
[22:47] Speaker 5: There's not a whole bunch. Winner's Curse was one of
[22:50] Speaker 5: those books that almost everybody recommends because the anomalies columns
[22:54] Speaker 5: are just very, very accessible, and then you read the
[22:57] Speaker 5: anomalies columns, they got a bunch of references. You look
[22:59] Speaker 5: through the reference So I had read the original Winner's
[23:03] Speaker 5: Curse I think second or third year at grad school,
[23:07] Speaker 5: and then I got my first job at Cardigi mel
[23:10] Speaker 5: and I had already known Richard for a while at
[23:12] Speaker 5: that point. We met in graduate school. His office was
[23:15] Speaker 5: happened to be right next to mine in San Diego,
[23:18] Speaker 5: and at some point I joined Booth and he called
[23:22] Speaker 5: me up I think like four or five months into
[23:25] Speaker 5: my first year, and said, hey, you know, I got
[23:27] Speaker 5: this opportunity. We want to the published asset to update
[23:31] Speaker 5: the book. I'm thinking of doing a little bit more
[23:33] Speaker 5: than just an update. You know the books from nineteen
[23:36] Speaker 5: ninety two, there's been thirty years of research. Are you
[23:39] Speaker 5: interested in working together on this? So, I mean I
[23:41] Speaker 5: jumped on the opportunity. One, you know, I get to
[23:43] Speaker 5: work with Richard, which is super fun. But two, I mean,
[23:47] Speaker 5: you know, I've been doing behavioral economics research for a while,
[23:50] Speaker 5: and I know how much demand there is for a
[23:53] Speaker 5: book that people can pick up and read and say, hey,
[23:55] Speaker 5: these are the original anomalies. Here's the thirty years of
[23:57] Speaker 5: research that has happened since. Now. I think at that
[24:01] Speaker 5: point we were thinking, like, you know, six months, do
[24:03] Speaker 5: a little update. This is twenty twenty. This conversation happened
[24:07] Speaker 5: in twenty twenty. The book is coming out now. We
[24:12] Speaker 5: you know, basically the two thirds of the book ended
[24:15] Speaker 5: up being brand new. We wrote, we rewrote slightly. Each
[24:20] Speaker 5: anomalies column is kind of the bedrock. But you know,
[24:23] Speaker 5: thirty years of research has happened since, and it took
[24:26] Speaker 5: a while to put all of that together. And essentially
[24:29] Speaker 5: what we showed is, look, the original anomalies, when you
[24:33] Speaker 5: read them, most of the experiments, most of the findings
[24:36] Speaker 5: are from you know, college students sometimes you know, after
[24:39] Speaker 5: a bad night out in the lab for you know,
[24:42] Speaker 5: making decisions over a dollar. And the big kind of
[24:44] Speaker 5: pushback from economists was, look, we don't really care about
[24:47] Speaker 5: these people. We care about you know, institutional investors, CEOs.
[24:52] Speaker 5: We care about people who are in the market with
[24:53] Speaker 5: money on the line, making all these big decisions. And
[24:57] Speaker 5: so what why has behavioral economics become a success? Honestly
[25:01] Speaker 5: largely because of behavioral finance, because of the fact that
[25:04] Speaker 5: behavioral economics behavioral economists said, look, we got access to
[25:08] Speaker 5: this amazing data on people making consequential decisions day in
[25:11] Speaker 5: and day out. They're still making mistakes.
[25:14] Speaker 2: Coming up, we continue our conversation with Richard Taylor and
[25:17] Speaker 2: alex iMOS discussing the book. They have recently updated, The
[25:22] Speaker 2: Winner's Curse Behavioral Economics Anomalies. Then and now I'm Barry
[25:28] Speaker 2: rid Holts. You're listening to Masters in Business on Bloomberg Radio.
[25:43] Speaker 2: I'm Barry rid Holts. You're listening to Masters in Business
[25:46] Speaker 2: on Bloomberg Radio. My extra special guests this week are
[25:49] Speaker 2: Richard Taylor and Alex Amos, both of the Chicago Booth
[25:53] Speaker 2: School Business at the University of Chicago.
[25:57] Speaker 5: I love what.
[25:58] Speaker 2: Danny Konoman wants said. That is, I suffer from all
[26:01] Speaker 2: the same behavioral biases that I identified. You mean to
[26:05] Speaker 2: tell me that we have thirty years of data, all
[26:07] Speaker 2: this research, a handful of books, people still make the
[26:11] Speaker 2: exact same behavioral mistakes they used to. Has there been
[26:14] Speaker 2: any change in behavior?
[26:17] Speaker 3: Essentially?
[26:18] Speaker 2: No, And.
[26:21] Speaker 4: That's not that surprising because the stuff we're talking about
[26:26] Speaker 4: has been true as long as there have been humans. Right,
[26:31] Speaker 4: So we talk about self control problems. It's in the Bible, right,
[26:37] Speaker 4: you know, Homer talks about Odysseus tying himself to the mast.
[26:46] Speaker 4: That's like agreeing to have money taken out of your
[26:51] Speaker 4: paycheck and put into a retirement plan. So human beings, yes,
[26:58] Speaker 4: there's evolution, but evolution and takes thousands of years, and
[27:02] Speaker 4: thirty years is the blink of an eye.
[27:05] Speaker 2: Since you mentioned retirement accounts, let's talk a little bit
[27:08] Speaker 2: about choice architecture. And nudge. Before I arrived here, I
[27:16] Speaker 2: looked up what was the impact of the default setting
[27:21] Speaker 2: that you helped change through choice architecture. People used to
[27:25] Speaker 2: get a new job, sign up for four to one K,
[27:28] Speaker 2: and the money would come into that account and would
[27:30] Speaker 2: sit there in cash. And rather than have the default
[27:33] Speaker 2: be cash, we through your work created a default as
[27:39] Speaker 2: a either a target date fund or a balance fund
[27:42] Speaker 2: something like that, so it's not sitting in cash. And
[27:45] Speaker 2: it turns out there is about four point seven trillion
[27:49] Speaker 2: with a t trillion dollars in those funds, of which
[27:53] Speaker 2: forty percent, according to recent research, was the default setting.
[27:58] Speaker 2: So you get credit for about two trillion dollars in
[28:02] Speaker 2: retirement savings that might have otherwise just been sitting around
[28:06] Speaker 2: in cash. How does the concept of people aren't learning
[28:12] Speaker 2: from their mistakes so choice architecture is so important to
[28:16] Speaker 2: help people make better decisions. How significant is that?
[28:21] Speaker 4: Well, if you think about what was going on in
[28:25] Speaker 4: the in the early eighties, these defined contribution plans like
[28:30] Speaker 4: four to one k's were real new Our parents were
[28:37] Speaker 4: if they If you worked at a big firm, you
[28:40] Speaker 4: had a define benefit plan. My father worked for Prudential insurance.
[28:45] Speaker 4: You know, and his pension was number of years worked
[28:50] Speaker 4: times some function of his final salary. No decisions to make,
[28:55] Speaker 4: kind of like social security and bring in these.
[29:03] Speaker 3: To find contribution plans.
[29:05] Speaker 4: You have to decide whether to join and if so,
[29:08] Speaker 4: how much to defer, and then how to invest it.
[29:13] Speaker 4: And people had no clue and a lot of people
[29:17] Speaker 4: just didn't even join, which is about the dumbest mistake
[29:21] Speaker 4: you can ever make.
[29:22] Speaker 2: If you have a company with a match, you're basically
[29:24] Speaker 2: turning down free money, right, which what economic model says
[29:28] Speaker 2: that's rational? No?
[29:29] Speaker 3: Well, right, so I would say to what ecmmists, look,
[29:32] Speaker 3: you would predict.
[29:33] Speaker 4: No one would make this mistake. But one early study,
[29:39] Speaker 4: half the employees at a company are not joining.
[29:44] Speaker 3: In the first year.
[29:44] Speaker 2: It's amazing.
[29:46] Speaker 4: So how do we fix that? Well, the simplest thing
[29:50] Speaker 4: was to change the default. So we say it used
[29:56] Speaker 4: to be you get a form to fill out a
[29:59] Speaker 4: piece of paper in those days, and if you want
[30:02] Speaker 4: to be in the plan, fill out this form and
[30:05] Speaker 4: say you want to join in how to invest?
[30:10] Speaker 3: Change that to you.
[30:13] Speaker 4: Welcome to Riddlets Management. We have a pension plan. We're
[30:20] Speaker 4: going to enroll you unless you opt out, and we're
[30:26] Speaker 4: going to enroll you into the default fund unless you
[30:30] Speaker 4: choose otherwise. So all of that was not possible in
[30:37] Speaker 4: the early nineties because there were companies were afraid to
[30:43] Speaker 4: do automatic enrollment because they didn't have permission, and target
[30:49] Speaker 4: DAID funds weren't legal. Ironically, in the George W. Bush administration,
[30:58] Speaker 4: one side, they were campaigning to partially privatize Social Security,
[31:05] Speaker 4: but their Labor Department was forbidding companies from investing in
[31:12] Speaker 4: anything that.
[31:12] Speaker 3: Could go down.
[31:14] Speaker 4: So there was a bill passed in two thousand and
[31:18] Speaker 4: six the said, okay, you're allowed to automatically enroll and
[31:30] Speaker 4: have automatically escalate what we used to call sayborn tomorrow,
[31:35] Speaker 4: and invest in some prudent funds.
[31:42] Speaker 3: And what was what you have to give something up
[31:46] Speaker 3: to get that.
[31:48] Speaker 4: So what I suggested to there was a Republican senator
[31:55] Speaker 4: from Utah who was the running the Relevant committee. I said,
[32:01] Speaker 4: how about if companies agree to do all three of those,
[32:06] Speaker 4: they're exempt from some burdensome paperwork of non discrimination rules.
[32:12] Speaker 4: And so that's what the Republicans got was less paperwork,
[32:17] Speaker 4: and people who cared about the workers got something.
[32:21] Speaker 2: And the workers got something, and the.
[32:24] Speaker 4: Workers got something and if they just do nothing, then
[32:29] Speaker 4: they're in and their contributions are going up, and they're
[32:33] Speaker 4: in a sensible.
[32:36] Speaker 3: Investment product.
[32:40] Speaker 2: So this is kind of not just kind of fascinating
[32:43] Speaker 2: because in the Winner's course you talk about things very
[32:46] Speaker 2: much related to what happens in investing. So there's loss,
[32:51] Speaker 2: a version, and the status quo bias and a variety
[32:55] Speaker 2: of different things. Let's talk about what are the issues
[33:00] Speaker 2: that most relate to, as Alex said, behavioral finance as
[33:04] Speaker 2: opposed to behavioral economics. What do we think are the
[33:08] Speaker 2: biggest factors that explain irrational human behavior in stock and
[33:16] Speaker 2: bond markets.
[33:18] Speaker 5: So I think there's a few things that kind of
[33:22] Speaker 5: people documented in the late nineties early two thousands that
[33:26] Speaker 5: have just replicated and just became bigger, if anything. So
[33:31] Speaker 5: the disposition effect was one of them. So the disposition effect,
[33:34] Speaker 5: this is Scheffern and Statman. They came up with a
[33:37] Speaker 5: paper nineteen eighty five documenting it. Originally, Terry O. Dean
[33:41] Speaker 5: has this giant data set that he published in nineteen
[33:44] Speaker 5: ninety nine documenting in a bit of a larger sample,
[33:46] Speaker 5: and then now it's been replicated in Finland, all over
[33:49] Speaker 5: the world and it's this tendency for people. You know,
[33:52] Speaker 5: when I buy a stock it goes up in price,
[33:55] Speaker 5: what do I do? I sell it? I want to
[33:58] Speaker 5: realize my gains. Same stock was down in price. You
[34:02] Speaker 5: know this is now a loss? What do I do?
[34:04] Speaker 5: Hold on to it? So it's this tendency to realize
[34:07] Speaker 5: your gains and hold on to your losses.
[34:09] Speaker 2: Peter Lynch, by the way, forty years ago, used to
[34:12] Speaker 2: call that cutting your flowers and watering your weeds. That
[34:16] Speaker 2: was his expression for it. So it was it was
[34:19] Speaker 2: visible to a guy running a fund at Fidelity in
[34:22] Speaker 2: the nineteen eighty.
[34:23] Speaker 5: Yes, and it's and this is just talking about like
[34:26] Speaker 5: are people learning? I mean apparently not, because it's like
[34:29] Speaker 5: it's again you I bet you you download Robinhood data
[34:32] Speaker 5: from today, you're going to see it show up. So
[34:35] Speaker 5: that's the the And this is kind of the tendency.
[34:38] Speaker 5: You know what feels good when you're when when when
[34:41] Speaker 5: you own a stock selling it at a gain, and
[34:43] Speaker 5: you know, telling your friends, hey, you know I bought
[34:45] Speaker 5: that thing for ninety it's one twenty. I just I
[34:48] Speaker 5: just made a lot of money. You know, it feels
[34:50] Speaker 5: worse telling your friends I bought it ninety and I
[34:53] Speaker 5: sold it at sixty, So you just kind of hold
[34:55] Speaker 5: on to it hoping something happens. Maybe some people even
[34:58] Speaker 5: double up buy more share is just to break even.
[35:02] Speaker 5: So the disposition effect this kind of tendency for individual
[35:04] Speaker 5: behavior to uh, you know, realize gains avoid losses. The
[35:08] Speaker 5: other thing is, in my view, this is kind of
[35:11] Speaker 5: the bigger uh, the bigger principle is limited attention. So
[35:16] Speaker 5: you know, there's a lot of stocks out there, which
[35:19] Speaker 5: ones are people buying? And this is not just retail investors,
[35:22] Speaker 5: this is this is bigger institutional investors too.
[35:25] Speaker 3: Uh.
[35:25] Speaker 5: It's the ones that are covered in the news. We're
[35:27] Speaker 5: talking about availability bias earlier. What are the things that
[35:31] Speaker 5: are coming to mind, Things that that have recently been covered,
[35:34] Speaker 5: maybe you heard an earnings announcement call or something like that.
[35:36] Speaker 5: These attention grabbing stocks that are much more likely to
[35:39] Speaker 5: go into people's portfolios. It's because people don't, you know,
[35:43] Speaker 5: aren't evaluating the entire uh, the entire universe of stocks
[35:47] Speaker 5: whenever they think they're thinking about something to buy.
[35:49] Speaker 2: So let's address that. Because the United States, happens, of
[35:54] Speaker 2: all countries, not only has such a large stock market,
[35:58] Speaker 2: but the home country buys is so acute here, and
[36:03] Speaker 2: you don't hear a lot about foreign companies all that.
[36:06] Speaker 2: Often you mostly hear about local companies, local CEOs, local products.
[36:12] Speaker 2: How significant is that sort of bias in people's portfolios
[36:16] Speaker 2: being not only overloaded with their own country, but hey,
[36:22] Speaker 2: if you're in New York, you can have more finance companies.
[36:25] Speaker 2: If you're in San Francisco, you have more tech companies.
[36:27] Speaker 2: If you're in the Midwest you can have more manufacturing companies.
[36:30] Speaker 5: It's more extreme than that. If I'm working for a
[36:32] Speaker 5: specific company, I have more of that stock.
[36:34] Speaker 2: When, if anything, you should have right.
[36:38] Speaker 3: Yeah. I think one campaign that has been moderately successful
[36:44] Speaker 3: is I think fewer companies are foisting stock of their
[36:48] Speaker 3: own company onto the workers. It used to be the
[36:52] Speaker 3: match was often paid in company stock.
[36:56] Speaker 2: Well Ge was notorious and they lost a trillion dollars
[37:01] Speaker 2: of employee investments because of their match.
[37:05] Speaker 3: Well and Uh and run and Ron.
[37:09] Speaker 5: One of my one of my friends their their their father.
[37:12] Speaker 5: He was working at Enron. He was a risk manager.
[37:16] Speaker 2: F Yi and UH just not a very good one, huge,
[37:21] Speaker 2: huge persu although it could be the greatest risk manager there.
[37:25] Speaker 2: The busses were not listening to you.
[37:27] Speaker 4: Right, But they compounded it by putting their employees money
[37:33] Speaker 4: in the four one k into and run stock. So
[37:36] Speaker 4: they get fired and their retirement money goes puff unbelievable.
[37:43] Speaker 5: But you know, looking back at what people were owning,
[37:46] Speaker 5: I mean there is that, you know, people in the
[37:48] Speaker 5: four oh one k element, but people who were working
[37:50] Speaker 5: there were freely buying and ron stock. Right, according to
[37:56] Speaker 5: economic models, you should be diversifying. You already have a
[37:59] Speaker 5: bunch of ron stock in your four one k. You
[38:01] Speaker 5: shouldn't be taking your discretionary spending and buying more and
[38:04] Speaker 5: ron stock. And that's exactly what was happening.
[38:06] Speaker 4: You know, this home bias applies all around the world,
[38:12] Speaker 4: at least the US is a big country. I wrote
[38:15] Speaker 4: a paper once about the Swedish social sort of four
[38:21] Speaker 4: to one k plan. This was a risky move because
[38:24] Speaker 4: I was making fun of it and there was some
[38:27] Speaker 4: award that might happen. But anyway, Sweden is one percent
[38:35] Speaker 4: of world.
[38:35] Speaker 2: GP tiny tiny, GDP tiny, and.
[38:38] Speaker 3: They were putting most of their money in Swedish stocks.
[38:41] Speaker 2: It's crazy they ignored the other ninety nine percent of
[38:44] Speaker 2: the world. But that just goes to show you the bias.
[38:48] Speaker 2: So the obvious question is if you two were advising
[38:52] Speaker 2: a portfolio manager, what sort of behavioral principles would you
[38:56] Speaker 2: emphasize for them to build a robust portfolio.
[39:01] Speaker 4: Well, as you know, I one hat I have is
[39:07] Speaker 4: I'm involved in a company that does.
[39:09] Speaker 2: This that has also has your name on the door.
[39:11] Speaker 4: It also has my name on the door fuller and
[39:14] Speaker 4: fail or asset management. And now let me say I
[39:20] Speaker 4: cannot name a single stock WHEELWN and no one at
[39:26] Speaker 4: the firm would think it's a good idea for me
[39:30] Speaker 4: to be making suggestions. Were buy small cap stock, so
[39:35] Speaker 4: it's you know, if we owned Apple or Tesla, I
[39:38] Speaker 4: might know it, but we don't buy any big stock.
[39:41] Speaker 3: So they're mostly companies you've never heard of, and I've
[39:45] Speaker 3: never heard of them.
[39:46] Speaker 2: But this is because you've identified a behavioral issue that
[39:51] Speaker 2: is now reflected in the model that they use to purchase.
[39:54] Speaker 3: Right, So we're not.
[39:58] Speaker 4: We're not a quatch shop, which is a little unusual
[40:02] Speaker 4: for a firm that's run by some academics. But each
[40:07] Speaker 4: strategy is based on a bias. So there's one that's
[40:12] Speaker 4: based on overreaction, there's one that's based on underreaction. So
[40:15] Speaker 4: we are we try to find stocks that we think
[40:22] Speaker 4: the rest of the market is making a mistake about,
[40:26] Speaker 4: and then we forbid the portfolio managers from forecasting earnings because.
[40:34] Speaker 3: That they're going to be You know, do we think with.
[40:38] Speaker 4: Our thirty employees that we're going to make better forecasts
[40:41] Speaker 4: than fidelity. It's crazy, but we think we have an
[40:46] Speaker 4: advantage because we're trying to predict something else. We're trying
[40:49] Speaker 4: to predict the mistakes. It's like you're a baseball fan.
[40:54] Speaker 4: If there's a picture that is a sinker ball pitcher,
[40:59] Speaker 4: so the alex this means the ball goes down as
[41:03] Speaker 4: it approaches the plate.
[41:05] Speaker 3: These foreigners.
[41:06] Speaker 4: But you know, if there's a sinker ball pitcher, you
[41:11] Speaker 4: and I can predict batters are going to hit ground
[41:14] Speaker 4: balls because they are fooled. The ball drops, and if
[41:19] Speaker 4: you hit it slightly above the center, the ball goes down.
[41:23] Speaker 4: So you don't have to be able to hit a
[41:25] Speaker 4: ball to know it's going to go down, And so
[41:30] Speaker 4: we don't have to be able to forecast earnings to
[41:33] Speaker 4: predict that other people are going to be predicting too high.
[41:36] Speaker 2: I want to bring this back to the book because
[41:39] Speaker 2: one of the concepts underlying the book was, Hey, there's
[41:43] Speaker 2: a reproducibility issue in social sciences. How well have these
[41:48] Speaker 2: anomalies and the theories you built around them, How well is
[41:52] Speaker 2: this held up? How robust and reproducible are these findings?
[41:56] Speaker 2: And it turns out very talk to us about what
[42:00] Speaker 2: but what you guys discovered when you were revisiting all
[42:03] Speaker 2: of these principles that were first written about twenty thirty
[42:07] Speaker 2: years ago.
[42:08] Speaker 5: Yeah, so, as you mentioned, there's a some might call
[42:11] Speaker 5: crisis of reproducibility and social science more broadly, so this
[42:14] Speaker 5: is psychology, some sociology, et cetera. And the worry is
[42:20] Speaker 5: that you know, these anomalies that were published in the
[42:22] Speaker 5: eighties and nineties, these are the bedrock of the entire
[42:24] Speaker 5: field of behavioral economics, and you might be worried, like, look,
[42:29] Speaker 5: maybe these things don't reproduce. And there's two ways that
[42:32] Speaker 5: they can't. They don't reproduce. One, you run the same
[42:35] Speaker 5: experiment again and doesn't work. It was p hacked, as
[42:38] Speaker 5: I said, like small sample sizes, no incentives. The second
[42:42] Speaker 5: way my not reproduce is that it literally only reproduces
[42:45] Speaker 5: in the exact conditions it was run originally with college
[42:48] Speaker 5: students at low stakes. You go out in a different
[42:50] Speaker 5: population with people who are a bit more sophisticated, know
[42:53] Speaker 5: what's going on, and you know it doesn't work. So
[42:56] Speaker 5: what we did in the book was to say, look, first,
[42:58] Speaker 5: let's take the exact same experiments and run them again.
[43:01] Speaker 5: Everybody knows about, you know, the original anomaly, So maybe
[43:07] Speaker 5: they don't work because people are like, ah, this is
[43:09] Speaker 5: a loss of version experiment. I know what's going on.
[43:12] Speaker 5: I'm not going to do this. This is the endowment effect.
[43:15] Speaker 5: I'm not going to do this. So we just replicated
[43:17] Speaker 5: them directly on a completely different platform. So we used
[43:20] Speaker 5: an online crowdsourcing platform called prolific. Basically, everything works. Everything works,
[43:27] Speaker 5: and we you know, you don't have to take our
[43:29] Speaker 5: word for it. If you go on the website of
[43:31] Speaker 5: the book, we posted all of the results of our replications,
[43:34] Speaker 5: but also instructions on how you can do it yourself.
[43:37] Speaker 5: So if somebody is like, don't I don't know about
[43:39] Speaker 5: these guys, run them yourself. And you know, people are
[43:43] Speaker 5: still loss of ours. They still have the endowment effect.
[43:48] Speaker 5: Things like the conjunction fallacy, the Linda problem that Richard
[43:51] Speaker 5: was talking about all works.
[43:52] Speaker 3: Though.
[43:54] Speaker 5: The second part is this external validity part. Does anybody
[43:57] Speaker 5: other than college students display these these effects? And that's
[44:01] Speaker 5: kind of the updates part of the book, and the
[44:03] Speaker 5: answer is yes. You know, the loss of version has
[44:06] Speaker 5: been in the myopic loss of version part that's been
[44:09] Speaker 5: used to explain the equity premium puzzle that's still reproducible.
[44:13] Speaker 5: We also do a bunch of out of sample tests
[44:15] Speaker 5: of the anomalies that didn't use experimental data, and you
[44:22] Speaker 5: know that replicates out of sample too, so people aren't
[44:24] Speaker 5: learning the psychology is the same.
[44:27] Speaker 3: You know.
[44:28] Speaker 4: One of the columns was about the equity premium puzzle.
[44:31] Speaker 4: We didn't include this in the book because it's a
[44:33] Speaker 4: little wonky, but the equity premium is just the difference
[44:37] Speaker 4: in returns between stocks and bonds. The equity premium puzzle
[44:42] Speaker 4: is how big it is, and theory says it should
[44:46] Speaker 4: be like less than one percent, and historically it was
[44:50] Speaker 4: about seven percent. And the article about that was in
[44:55] Speaker 4: the early eighties, so we've had forty years of data
[44:59] Speaker 4: since the puzzle was announced.
[45:02] Speaker 3: The equity premium.
[45:03] Speaker 4: Exactly the same, it's only one percent lower, so and
[45:08] Speaker 4: that's what.
[45:08] Speaker 3: We see basically everywhere everything's the same.
[45:12] Speaker 2: So one of the concepts that people have challenged is
[45:16] Speaker 2: not being very reproducible. Has been the concept of priming
[45:20] Speaker 2: to sometimes anchoring is similar, but that seems to be
[45:25] Speaker 2: more reproducible. But when I hear Linda the bank teller story,
[45:30] Speaker 2: that feels like the framing of that is very much
[45:33] Speaker 2: a priming, when you hear about her as politically active
[45:39] Speaker 2: and being involved in what how do you distinguish when
[45:43] Speaker 2: you have these theoretical overlapping biases that all kind of
[45:48] Speaker 2: interact with each other.
[45:49] Speaker 5: So priming is actually a huge literature and cognitive psychology.
[45:54] Speaker 5: Basic priming is very robust. So it's the idea of
[45:58] Speaker 5: you know, I say a bunch of words that start
[46:00] Speaker 5: with the K. What comes to mind a word that
[46:01] Speaker 5: starts with the K that's going to reproduce any day
[46:04] Speaker 5: of the week. There's a special subset of priming research
[46:08] Speaker 5: that was done kind of in the nineties early two
[46:10] Speaker 5: thousands that kind of took this to an extreme, which
[46:14] Speaker 5: is so here's an example. Let's say you're doing word
[46:16] Speaker 5: search and there's a bunch of words that have to
[46:20] Speaker 5: do with like oranges, palm, trees, hot weather, like vaguely
[46:24] Speaker 5: related with Florida, right, and then that's supposed to prime
[46:28] Speaker 5: in your brain old people. And the result, the dependent
[46:32] Speaker 5: variable was that those subjects who had those words, they
[46:35] Speaker 5: walked a little slower out of the lab.
[46:37] Speaker 2: Right.
[46:38] Speaker 5: I mean that's it's a little crazy, right, kind of
[46:40] Speaker 5: tough to measure. Also, yeah, so I mean it relied.
[46:44] Speaker 5: There's a lot of degrees of freedom the researcher can
[46:46] Speaker 5: be looking in a certain direction, you know, and those
[46:49] Speaker 5: tend to tend to not reproduce the sort of priming
[46:53] Speaker 5: that something like the Linda problem, for example, has. That's
[46:59] Speaker 5: more in that kind of cognitive psychology wheelhouse of like
[47:02] Speaker 5: what do you think about when I describe a person
[47:05] Speaker 5: who takes part in radical rallies? What comes to mind?
[47:07] Speaker 5: This is this is a basic concept and memory.
[47:11] Speaker 2: Right.
[47:11] Speaker 5: So that and the second part that that I wanted
[47:14] Speaker 5: to to say is that priming, as far as like
[47:17] Speaker 5: looking at the behavioral economics research, priming is a really
[47:21] Speaker 5: small part. It was actually not really featured much in
[47:23] Speaker 5: the book. But the type that is that was used
[47:27] Speaker 5: by uh, you know, uh Firsky and Konnoment. It's much
[47:31] Speaker 5: more in the Wheelhouse or just basic cognitive psychology.
[47:34] Speaker 2: More like anchoring. Does anchoring still hold up? Oh yeah,
[47:37] Speaker 2: very well?
[47:37] Speaker 5: Oh yeah, yeah yeah yeah.
[47:39] Speaker 4: And look, one of the things when when I was
[47:42] Speaker 4: writing those columns, the I could pick anything. I picked
[47:48] Speaker 4: big effect sizes and some of the problem.
[47:53] Speaker 3: You know, we talked.
[47:55] Speaker 4: Earlier about the norm and economics to make models smarter
[48:00] Speaker 4: and smarter. I think there was a norm in psychology
[48:05] Speaker 4: for results to get cleverer and cleverer.
[48:08] Speaker 2: Well, I thought Alice's paper where you randomly sell versus
[48:11] Speaker 2: what was actually sold, that was a very clever set
[48:14] Speaker 2: up for a paper.
[48:16] Speaker 3: It was clever, but it wasn't.
[48:19] Speaker 4: What I was deriding is a norm that the models
[48:24] Speaker 4: assume people are being clever as opposed to designing a
[48:27] Speaker 4: clever paper. Got we're all for clever papers, Okay, we
[48:32] Speaker 4: like clever papers. So when I was choosing what columns
[48:36] Speaker 4: to write about, I picked big stuff. And think about
[48:42] Speaker 4: there's a well known company that makes cinnamon buns and
[48:49] Speaker 4: has the strategy of pumping the smell of that out
[48:54] Speaker 4: into the airport. Now, let's say you're on a low
[48:59] Speaker 4: carb diet. Just hypothetically, you know, if you walk by
[49:05] Speaker 4: that thing that's that's priming, and that works.
[49:11] Speaker 3: And it's not clever, it's just right. It's a big
[49:15] Speaker 3: effect size.
[49:17] Speaker 4: So there are and so everything I wrote about was big,
[49:23] Speaker 4: and it's because I wanted to pick things that I
[49:27] Speaker 4: thought were well established and so, you know, I think
[49:34] Speaker 4: if I had looked for cute little things, then some
[49:39] Speaker 4: of them would have failed to replicate.
[49:41] Speaker 5: You also pick things that people were actively attacking and
[49:44] Speaker 5: adversarially trying to replicate at the time that you were
[49:47] Speaker 5: writing it.
[49:49] Speaker 3: Yeah, I mean, look, take take the ultimatum.
[49:52] Speaker 4: Yeah, that's one of the original columns and one that
[49:57] Speaker 4: we include in the book. The game is very, very simple.
[50:01] Speaker 4: I give Barry one hundred dollars. I say, share it
[50:05] Speaker 4: with Alex. You can give whatever proportion of the hundred
[50:10] Speaker 4: you want to Alex. He says yes or no. If
[50:15] Speaker 4: if he says yes, he gets whatever you offered.
[50:19] Speaker 3: And you get the rest. If he says no, you
[50:21] Speaker 3: both get nothing.
[50:23] Speaker 4: Now, the standard economic model at the time predicts that
[50:30] Speaker 4: Alex will accept anything, because something is better than nothing.
[50:35] Speaker 4: Barry knows that Alex will accept anything, and so he
[50:41] Speaker 4: offers him a dollar and Alex accepts. Now, real people
[50:48] Speaker 4: only an economist would think that that's a really good prediction.
[50:53] Speaker 3: Anybody who's not an economist is going to say, what
[50:56] Speaker 3: are you kidding.
[50:57] Speaker 4: I'm not going to take a dollar and give you
[50:59] Speaker 4: ninety You didn't do anything to deserve that ninety nine.
[51:04] Speaker 4: So if you run that experiment, if you offered less
[51:10] Speaker 4: than twenty percent, you're going to get rejected. And the
[51:15] Speaker 4: profit maximizing offer is about and most people offer half. Okay,
[51:24] Speaker 4: Now there were big fights. There was a professor from
[51:32] Speaker 4: britt who was saying this was challenging game theory, and no,
[51:43] Speaker 4: it wasn't challenging game theory. It was challenging the idea
[51:48] Speaker 4: that the agents only care about money and don't care
[51:54] Speaker 4: about being treated fairly.
[51:57] Speaker 2: So let's address that. Because of the evolutionary biology of this,
[52:05] Speaker 2: humans were cooperative social primates. We have neither fangs nor claws,
[52:10] Speaker 2: so we had to come up with some way to
[52:12] Speaker 2: stay alive, and it turns out cooperating in a tribe
[52:16] Speaker 2: is very useful survival tactic. It seems that an inherent
[52:21] Speaker 2: sense of fairness is somewhat built into all of us,
[52:25] Speaker 2: as well as social status seeking. So how much of
[52:31] Speaker 2: this issue in economics derives from not understanding a little
[52:37] Speaker 2: bit of evolutionary history.
[52:40] Speaker 4: You know, it's a tricky thing. Obviously, we have evolved
[52:45] Speaker 4: to be who we are. There are some people who
[52:49] Speaker 4: then say, well, that means whatever we do is optimal.
[52:54] Speaker 3: Well maybe maybe not. No, that's stupid. I mean we
[52:58] Speaker 3: evolved on the savannah.
[53:00] Speaker 2: Right, right, nothing about picking muni bonds from a larger site.
[53:05] Speaker 3: You know.
[53:06] Speaker 4: Amos Tversky was famous for one liners, and he had
[53:11] Speaker 4: a one liner about loss of version, which was there
[53:16] Speaker 4: may have been species that did not exhibit loss of version,
[53:21] Speaker 4: and they're now extinct. Right, So if you're at subsistence,
[53:27] Speaker 4: it's really smart to be worried about.
[53:29] Speaker 2: Losing It's an existential threat.
[53:31] Speaker 3: Right.
[53:32] Speaker 4: But you know, none, the three of us, we could
[53:37] Speaker 4: go several days without eating, some more more things than others, right, right,
[53:44] Speaker 4: so we're not at subsistence, and yeah, we have Managing
[53:50] Speaker 4: our own portfolios is something people have been doing for
[53:54] Speaker 4: thirty years, right, Yeah, the rich people, but they had
[53:59] Speaker 4: their oker do it, right, So there's no evolutionary history
[54:05] Speaker 4: of how to manage a portfolio, and even saving for retirement.
[54:13] Speaker 4: People didn't live long enough to worry about that. And
[54:17] Speaker 4: if you were unlucky enough to reach my age. Then
[54:22] Speaker 4: you hope your kids would take care of you, and
[54:25] Speaker 4: they lived nearby. You know, then people started scattering and penicillin,
[54:33] Speaker 4: and you know, so now we live long and our
[54:38] Speaker 4: kids are scattered and they have no interest in having
[54:42] Speaker 4: us move in with them. So people had to learn
[54:46] Speaker 4: a very new thing and they needed some help.
[54:51] Speaker 2: Really really fascinating, So we didn't talk about the where
[54:56] Speaker 2: that from? Whence the title of the Winner's Curse comes from?
[55:00] Speaker 5: Before we get to the future.
[55:01] Speaker 2: Of behavioral finance, let's talk about the Winner's Curse.
[55:05] Speaker 5: Tell us where the name comes.
[55:07] Speaker 4: From the concept. I should say the title of the
[55:11] Speaker 4: book comes from the title of one of the chapters,
[55:15] Speaker 4: and I picked it as the title back then because
[55:18] Speaker 4: it's sort of a fun phrase and a bit intriguing,
[55:22] Speaker 4: and the concept itself is interesting and important. The idea
[55:27] Speaker 4: is this, suppose you have a lot of people bidding
[55:31] Speaker 4: for some object that's worth the same to everybody, and
[55:36] Speaker 4: it could be. When you do this as a demonstration
[55:40] Speaker 4: in the class, you fill up a jar of jelly
[55:43] Speaker 4: beans or coins and say it's ten cents for each
[55:49] Speaker 4: jelly bean, and it's one hundred dollars in the jar.
[55:54] Speaker 4: Now we're going to auction it off. High bid or
[55:57] Speaker 4: wins the one hundred dollars. But they don't know what
[56:00] Speaker 4: they don't know it's worth one hundred dollars. All they
[56:02] Speaker 4: see is a lot of coins or jellybeans. What happens, well,
[56:08] Speaker 4: the average bid is less than one hundred dollars because
[56:11] Speaker 4: people are risk averse. But the winning bid is always
[56:16] Speaker 4: above one hundred dollars if you have enough people, because
[56:22] Speaker 4: the most optimistic forecast is likely the highest bid and
[56:27] Speaker 4: it's too high. Now, this was not discovered by psychologists
[56:33] Speaker 4: in the lab. It was discovered by engineers at Atlantic
[56:38] Speaker 4: Richfield Arco, the energy company. The energy company who discovered
[56:44] Speaker 4: they were bidding for oil leases in what I continue
[56:50] Speaker 4: to insist on calling the Gulf of Mexico. And they
[56:55] Speaker 4: realized that the leases they won had less oil than
[57:02] Speaker 4: they expected.
[57:04] Speaker 3: And they said, we thought we had world class geologists.
[57:08] Speaker 3: What's going on? Are they dummies? And then they realized
[57:13] Speaker 3: that it's quite subtle that the the what you're trying
[57:19] Speaker 3: to do is make a bid that will make you
[57:23] Speaker 3: money if you win, and that if you win part
[57:30] Speaker 3: if there's one hundred people bidding, gee, do I really
[57:34] Speaker 3: want to win because maybe I misunderstood something right. So
[57:39] Speaker 3: that's the winner's curse, and.
[57:44] Speaker 4: It was found and replicated on bidding for oil leases.
[57:51] Speaker 3: It's relevant in book publishing.
[57:54] Speaker 2: When they're bidding contests for books for yes, yes, So
[57:57] Speaker 2: let me see if I can clarify the way you're
[58:02] Speaker 2: describing the winner's carse. So we're bidding for oil leases,
[58:05] Speaker 2: we don't know exactly how much oil is going to
[58:07] Speaker 2: come out of this hole for or area for the
[58:10] Speaker 2: next ten to twenty years, and when there's many people bidding,
[58:15] Speaker 2: all of which are advised by geologists. If you make
[58:18] Speaker 2: a conservative bet, the odds are you're going to lose.
[58:21] Speaker 2: But if you make a bet that's high enough that
[58:24] Speaker 2: you're gonna win, the odds are it's not going to
[58:27] Speaker 2: be a moneymaker.
[58:28] Speaker 3: Right.
[58:28] Speaker 2: Coming up, we continue our conversation with Richard Taylor and
[58:32] Speaker 2: alex EMUs discussing the book. They have recently updated the
[58:37] Speaker 2: Winner's Curse behavioral economics anomalies. Then and now, I'm Barry Ritholtz.
[58:43] Speaker 2: You're listening to Masters in Business on Bloomberg Radio. I'm
[59:06] Speaker 2: Barry ridolts You're listening to Masters in Business on Bloomberg Radio.
[59:10] Speaker 2: My extra special guests this week are Richard Taylor and
[59:14] Speaker 2: Alex Emos, both of the Chicago Booth School Business at
[59:17] Speaker 2: the University of Chicago. I shared with you an article
[59:22] Speaker 2: I saw recently. Some real estate group did a study
[59:26] Speaker 2: of tens of thousands of home transactions where there was
[59:30] Speaker 2: a bidding war, and they found something very similar. The
[59:34] Speaker 2: winners of the bidding war ended up paying much more
[59:38] Speaker 2: than the subsequent home value was determined by looking at
[59:42] Speaker 2: comparable homes in the neighborhood. So is the purpose of
[59:47] Speaker 2: an auction to identify something at a fair value where
[59:52] Speaker 2: it's profitable for you, or is the purpose of an
[59:54] Speaker 2: auction to win at any cost?
[59:57] Speaker 4: Well, two interesting aspects of that. One is suppose you're
[1:00:04] Speaker 4: these engineers and you've discovered this, what should you do?
[1:00:09] Speaker 4: And if you're losing money every time you win an auction,
[1:00:14] Speaker 4: you could not bid, But then you don't have any
[1:00:16] Speaker 4: places to drill. And what did they decide to do.
[1:00:20] Speaker 4: It's really clever. They decided to write a paper.
[1:00:24] Speaker 2: In order to get people to stop overbidding.
[1:00:26] Speaker 3: Yeah, now that's different than what the owners of Major
[1:00:32] Speaker 3: League Baseball did.
[1:00:33] Speaker 2: I was going to say, why didn't they just moneyball? Itt,
[1:00:36] Speaker 2: Why didn't they just start looking at ugly but productive.
[1:00:40] Speaker 4: Well, what the Major League Baseball owners did is they colluded, right,
[1:00:47] Speaker 4: and they said, look, let's not bid anymore.
[1:00:50] Speaker 2: Well, the salary caps that are in all.
[1:00:52] Speaker 3: These no, no, there was just outright collusion when baseball
[1:00:56] Speaker 3: players first became free agents. Uh huh, or said hey, we're.
[1:01:00] Speaker 4: Losing money on these crazy auctions, let's just not bid,
[1:01:05] Speaker 4: and then they got slapped down, right, So what can
[1:01:11] Speaker 4: you do?
[1:01:14] Speaker 3: You can tried.
[1:01:16] Speaker 4: A good strategy is to bid very low on every site,
[1:01:23] Speaker 4: and in the data there were lots of sites that
[1:01:27] Speaker 4: you could have gotten for a dollar.
[1:01:29] Speaker 2: Really, and because because the consensus was is no, they're
[1:01:35] Speaker 2: there and were any of them productive? And any of
[1:01:38] Speaker 2: these really? So now let's bring this back to sports,
[1:01:42] Speaker 2: because you've written papers on NFL drafts.
[1:01:48] Speaker 3: So the NFL draft. Every year there's.
[1:01:54] Speaker 4: They have a draft for new players. The first pick
[1:01:58] Speaker 4: is given to the team with the worst record the
[1:02:00] Speaker 4: previous year, with the idea that that's going to be
[1:02:05] Speaker 4: a big advantage to them and will help them improve.
[1:02:09] Speaker 4: Cade Massey, one of my former students. He and I
[1:02:12] Speaker 4: wrote a paper showing that the first pick is actually
[1:02:20] Speaker 4: not the most valuable because the league has a salary,
[1:02:26] Speaker 4: the first player gets paid the most. And you can
[1:02:29] Speaker 4: trade the first pick for the seventh and eighth picks
[1:02:34] Speaker 4: or for five second round picks. And what we showed
[1:02:39] Speaker 4: is if you trade the first pick for lower picks,
[1:02:44] Speaker 4: you get more.
[1:02:47] Speaker 3: Value.
[1:02:48] Speaker 2: So now this is known like the Arco engineers publishing
[1:02:52] Speaker 2: by paper, and yet there still seems to be this
[1:02:55] Speaker 2: frenetic war for top top one, top ten, three, top
[1:03:00] Speaker 2: five picks. Has the NFL learned any lessons from the research?
[1:03:07] Speaker 3: Almost nothing.
[1:03:09] Speaker 4: They so they have learned that you should they only
[1:03:14] Speaker 4: trade up to get the first pick to pick a quarterback.
[1:03:19] Speaker 4: So that's smart because the quarterbacks are more valuable than
[1:03:26] Speaker 4: any other player.
[1:03:26] Speaker 2: Well, of course you want that first pick, so you
[1:03:28] Speaker 2: could get a Tom Brady.
[1:03:30] Speaker 4: Yeah, except Tom Brady was taken with one hundred and
[1:03:33] Speaker 4: ninety ninth pick. And all the listeners who are football
[1:03:38] Speaker 4: fans can have their list of people who were taken
[1:03:43] Speaker 4: with the first pick and turned out to be busts.
[1:03:46] Speaker 4: The Chicago Bears seemed to specialize in that. Although let's
[1:03:50] Speaker 4: hope this current guy.
[1:03:54] Speaker 2: Is so new one, So how much of this like
[1:03:57] Speaker 2: I'm seeing this through the lens of my book, which
[1:04:00] Speaker 2: I don't want to talk about. But how much of
[1:04:02] Speaker 2: this is just how difficult it is to predict the future,
[1:04:07] Speaker 2: to to have truly expert judgment about these very complex,
[1:04:13] Speaker 2: very variable so selecting quarterbacks, identifying oil leases like it
[1:04:22] Speaker 2: seems that supposed expert advice ain't all that expert. How
[1:04:27] Speaker 2: much of this is? Aren't we better off just being
[1:04:30] Speaker 2: a little more humble about our Let's give up the
[1:04:33] Speaker 2: top pick and have five second round. Somebody in that
[1:04:36] Speaker 2: five is likely to be half decent? Yeah?
[1:04:37] Speaker 4: Right, So let me stick to the sports for one second,
[1:04:42] Speaker 4: because there's one statistic from our paper, and we've just coincidentally,
[1:04:48] Speaker 4: we've been in a process of replicating.
[1:04:50] Speaker 3: That study, so I have the new data. But here's
[1:04:53] Speaker 3: the statistic.
[1:04:54] Speaker 4: Take all the players at a given position, say quarterback
[1:04:58] Speaker 4: or cornerback or running back, rank them in the order
[1:05:02] Speaker 4: in which they're picked, and now ask the fourth guy,
[1:05:08] Speaker 4: what's the chance he's better than the fifth guy? So
[1:05:12] Speaker 4: for the for the whole thing, so what's the chance
[1:05:15] Speaker 4: the earlier player is better than the next one?
[1:05:19] Speaker 2: One over two, ten, over eleven, five, over six?
[1:05:22] Speaker 4: Now, if they're perfect it'll be one hundred percent. If
[1:05:26] Speaker 4: they're coin flipping, it'll be fifty percent. What do you
[1:05:31] Speaker 4: think it is.
[1:05:32] Speaker 2: I think it's less than fifty percent.
[1:05:33] Speaker 3: I think negative. They they know less than nothing, right.
[1:05:37] Speaker 2: That's right. I think it's in the thirties or forties.
[1:05:40] Speaker 4: Well, they're not that bad, right, I mean, because if
[1:05:43] Speaker 4: they were, then you could just you know, you no, no,
[1:05:48] Speaker 4: you'd want to what the George Costanza. You wanted to
[1:05:51] Speaker 4: be opposite, right, So, so no, they don't have negative knowledge.
[1:05:58] Speaker 4: They have a tiny little bay. So but that's your point, really,
[1:06:05] Speaker 4: which is they think they know this guy is the
[1:06:09] Speaker 4: next Tom Brady, and there's only a fifty three percent
[1:06:14] Speaker 4: chance that he's better than the next one. And you know,
[1:06:20] Speaker 4: Patrick Mahomes, Josh Allen think none of these were first.
[1:06:24] Speaker 2: Right, right, So Mahomes kid is gonna be pretty good one.
[1:06:27] Speaker 3: I think he might make it.
[1:06:29] Speaker 2: He's got some potential, right.
[1:06:31] Speaker 4: So, And I think that is so getting off of sports,
[1:06:36] Speaker 4: I think that your general point is exactly right that
[1:06:40] Speaker 4: people are look overconfidence. Danny Codeman used to say that's
[1:06:45] Speaker 4: the mother of all biases. And we fall into these
[1:06:51] Speaker 4: traps because we think we know more than we do,
[1:06:57] Speaker 4: and if we add some humility, maybe if we listen
[1:07:03] Speaker 4: to our spouses more often, because at least in my house,
[1:07:10] Speaker 4: my wife doesn't think that I know anything, so she's
[1:07:15] Speaker 4: always bringing me back to fifty percent right, and she's
[1:07:20] Speaker 4: usually right.
[1:07:21] Speaker 2: My wife is from the same cut, from the same cloth.
[1:07:24] Speaker 2: So I want to bring Alex back into this. So
[1:07:27] Speaker 2: when we're thinking about the future of behavioral economics and
[1:07:33] Speaker 2: what this means for investors or regular people making financial
[1:07:39] Speaker 2: decisions or in significant decisions, what direction are we moving in.
[1:07:44] Speaker 2: Are are we learning from all of this knowledge that's
[1:07:49] Speaker 2: been accumulated, or are we just destined to make the
[1:07:52] Speaker 2: same mistakes over and over again.
[1:07:55] Speaker 5: I don't think we're destined to do anything. I think
[1:07:58] Speaker 5: it's a choice to take, you know, read papers and
[1:08:03] Speaker 5: look at papers on kind of published and financial journals
[1:08:07] Speaker 5: where people are making mistakes, and then to choose to say, like, look,
[1:08:10] Speaker 5: I actually can correct this by having a particular decision
[1:08:13] Speaker 5: aid or asking my spouse what to do, or something
[1:08:17] Speaker 5: like that. So you know what a paper you mentioned earlier,
[1:08:21] Speaker 5: we published this actually just last year, called Selling fast
[1:08:25] Speaker 5: and Buying Slow. And in that paper, basically we look
[1:08:28] Speaker 5: at institutional investors, So thinking about who in the economy
[1:08:33] Speaker 5: are least likely to be exhibiting beha role of biases.
[1:08:36] Speaker 5: You know, maybe retail traders they're like, you know, drinking
[1:08:38] Speaker 5: beer in their basement while trading stocks on robin Hood.
[1:08:41] Speaker 5: Maybe this is not the sophisticated people we want to
[1:08:43] Speaker 5: be looking at. But you know, institutional investors, the average
[1:08:47] Speaker 5: portfolio on the data set was like six hundred million,
[1:08:49] Speaker 5: seven hundred million dollars or something like that. We had
[1:08:53] Speaker 5: a data set where we actually saw every single they
[1:08:56] Speaker 5: think they did over something like a twelve or thirteen
[1:08:58] Speaker 5: year period far as what they're buying or what they're selling.
[1:09:02] Speaker 5: And what we found is because the data is so rich,
[1:09:05] Speaker 5: we can actually construct these counterfactual portfolios. We can say, look,
[1:09:08] Speaker 5: I see what you're buying. What if you bought something else,
[1:09:11] Speaker 5: So it could be something else from your portfolio, you
[1:09:13] Speaker 5: can top something up, or you can buy something new
[1:09:15] Speaker 5: from the from the universe. On the other hand, we
[1:09:18] Speaker 5: could say, look the same thing for selling. I saw
[1:09:21] Speaker 5: you sold Apple, I saw you sold Samsung. Let me
[1:09:25] Speaker 5: sell something else instead. How how would that perform relative
[1:09:28] Speaker 5: to what you actually did. And what we found is
[1:09:31] Speaker 5: that on the buying side. People actually did really well.
[1:09:35] Speaker 5: I mean, these guys are they.
[1:09:37] Speaker 3: Happen really well? But better better than.
[1:09:39] Speaker 2: Random Fund managers create some value in their stock selection
[1:09:44] Speaker 2: when they're making purchases, yes, but the flip side of
[1:09:46] Speaker 2: that not so much.
[1:09:48] Speaker 5: No, not so much. We had we really wanted to
[1:09:50] Speaker 5: be conservative. We didn't want to, you know, say, compare
[1:09:54] Speaker 5: them to the benchmark or something like that. We said,
[1:09:56] Speaker 5: let's throw a dart at your portfolio and sell that
[1:09:59] Speaker 5: instead of what you act.
[1:10:00] Speaker 2: So instead of selling what the manager wants to sell,
[1:10:03] Speaker 2: you would sell something else randomly from the rest of the.
[1:10:06] Speaker 5: Portfolio, a random selling.
[1:10:07] Speaker 2: And the performance difference was how significant?
[1:10:11] Speaker 5: Basically same difference but in the opposite direction, meaning they
[1:10:15] Speaker 5: were losing a ton of money.
[1:10:17] Speaker 2: So one hundred two hundred basis points on a random
[1:10:20] Speaker 2: cell better, Yes, performance exactly. And you know the way
[1:10:24] Speaker 2: when I read that paper and wrote about it, the
[1:10:27] Speaker 2: way I rationalized it, or tried to conceptualize it was
[1:10:32] Speaker 2: they're bringing a very objective, quantitative approach to the stock
[1:10:35] Speaker 2: selection issue, but it seems that their cells are filled
[1:10:40] Speaker 2: with biases and squishy decision making.
[1:10:43] Speaker 5: Is that a fair description? Yeah, exactly. So we found
[1:10:47] Speaker 5: no evidence for heuristics on their buying decision, Like, we
[1:10:49] Speaker 5: couldn't find anything, Like they just seemed to be very
[1:10:52] Speaker 5: disciplined and principled about what they're buying. But on the
[1:10:56] Speaker 5: selling side we found literally the same biases that we
[1:11:00] Speaker 5: found in the lab.
[1:11:01] Speaker 2: Has there been any evolution or improvement in this recently?
[1:11:06] Speaker 2: That's the question that I keep coming back to. It
[1:11:09] Speaker 2: seems that Richard, you've figured a lot of these things
[1:11:13] Speaker 2: out twenty five thirty five years ago. Are we any
[1:11:17] Speaker 2: better at making unbiased decisions? Or are we still subject
[1:11:21] Speaker 2: to the same voibles.
[1:11:23] Speaker 5: I think you need something extra right. You can't just
[1:11:25] Speaker 5: say I'm not going to do this and I have
[1:11:28] Speaker 5: decided not to listen to my psychology. That's what it
[1:11:30] Speaker 5: would look.
[1:11:31] Speaker 2: Like to be choice architecture of building, exam guardrails and
[1:11:36] Speaker 2: but this is a fault.
[1:11:37] Speaker 5: This is where overconfidence comes in. When you read a
[1:11:39] Speaker 5: paper about somebody doing something silly, your first reaction is
[1:11:43] Speaker 5: not me right, that's the blind spot. This is called
[1:11:47] Speaker 5: the bias blind spot exactly. So this is a well
[1:11:50] Speaker 5: replicated finding. When you ask people to what extent do
[1:11:53] Speaker 5: you exhibit a bias? I don't obviously I'm a smart person,
[1:11:57] Speaker 5: but to what extent to other people. Of course people
[1:12:00] Speaker 5: are bad at selling. I'm really good. But in order
[1:12:02] Speaker 5: to adopt choice architecture to help you out when making decisions,
[1:12:06] Speaker 5: you actually have to be have some You have to
[1:12:09] Speaker 5: have a lot of humility to say, look these institutional investors,
[1:12:13] Speaker 5: to say, look, looks like I'm not really doing so
[1:12:16] Speaker 5: well on selling. I'm going to adopt some choice architectures
[1:12:20] Speaker 5: so I don't suffer from these biases. Maybe I'll hire
[1:12:22] Speaker 5: somebody else to help me out. Maybe I'll think longer,
[1:12:26] Speaker 5: or use the same sort of research technology for my
[1:12:29] Speaker 5: selling as I'm doing for my buying. And because that
[1:12:32] Speaker 5: requires humility, which most people don't have a lot of,
[1:12:36] Speaker 5: that's really hard to do. So I think that's why
[1:12:38] Speaker 5: we're seeing a lot of these biases just be perpetuated
[1:12:42] Speaker 5: forward to the point where we're running the same analysis
[1:12:46] Speaker 5: now as we did thirty years ago and finding the
[1:12:47] Speaker 5: exact same thing.
[1:12:49] Speaker 2: So the question that since we were talking about sports
[1:12:52] Speaker 2: and lack of knowledge, and then you mentioned Robin Hood,
[1:12:57] Speaker 2: one of the things that's a little concerning is how
[1:13:02] Speaker 2: some companies are putting our knowledge of biases and bad
[1:13:06] Speaker 2: behavior to work for their own profit. So when we
[1:13:09] Speaker 2: see the gamification of investing with Robinhood or just the
[1:13:14] Speaker 2: incredible rise not just of sports books and gambling, but
[1:13:18] Speaker 2: you could bet on every play, it's reached a point
[1:13:20] Speaker 2: where it's ridiculous, and there is a robust evidence that,
[1:13:25] Speaker 2: especially young men, are having all sorts of how can
[1:13:29] Speaker 2: we how can we deal with what seems to be
[1:13:33] Speaker 2: not a good use of choice architecture, but a bad
[1:13:36] Speaker 2: use of choice choice architecture, at least as far as
[1:13:40] Speaker 2: the public is concerned.
[1:13:41] Speaker 4: Yeah, it's a very good question, Barry, and one to
[1:13:44] Speaker 4: which I don't have a pad answer. I mean, it's
[1:13:48] Speaker 4: tempting to say, look, all these sports betting apps and
[1:13:55] Speaker 4: the gamification of investing are bad for people. On the
[1:14:00] Speaker 4: other hand, people like doing it. They're mostly adults, and
[1:14:08] Speaker 4: you know, prohibition basically didn't work. So I think some
[1:14:15] Speaker 4: disclosure would help. It's difficult to find out what the odds.
[1:14:23] Speaker 3: Are and a lot of these things. But it's a
[1:14:28] Speaker 3: tough question.
[1:14:30] Speaker 4: I had a conversation on this book when Nate Silver
[1:14:35] Speaker 4: a couple of weeks ago, and we talked a lot
[1:14:38] Speaker 4: about sports gambling. He's a professional gambler and he spent
[1:14:44] Speaker 4: a year betting on NBA games and basically broke even.
[1:14:48] Speaker 4: So you know, if Nate can't make money doing this,
[1:14:53] Speaker 4: chances are you can't. And you know, my advice would be, look,
[1:14:58] Speaker 4: if you really think you doing this, do it on
[1:15:03] Speaker 4: a small scale.
[1:15:05] Speaker 3: You know, don't bet the house list, you don't write.
[1:15:09] Speaker 3: And the same with weekly options or daily.
[1:15:12] Speaker 5: That's one of the most popular. One of our colleagues
[1:15:14] Speaker 5: at University of Chicago she did an analysis of what
[1:15:17] Speaker 5: retail traders are actually doing on Robinhood and one of
[1:15:20] Speaker 5: the most popular products, which because it's pushed by Robinhood,
[1:15:24] Speaker 5: is weekly options.
[1:15:26] Speaker 2: And there's now end of day options where it expires
[1:15:30] Speaker 2: you have till four o'clock to either make money or not.
[1:15:34] Speaker 3: So you know, if you want to risk one month's
[1:15:37] Speaker 3: pay on.
[1:15:38] Speaker 2: That, fine, not just not every month.
[1:15:42] Speaker 3: No, yes, yeah, that's in your lifetime budget and when
[1:15:47] Speaker 3: it goes to zero, switch to something else.
[1:15:51] Speaker 2: I'm a big fan of the cowboy account, where you
[1:15:54] Speaker 2: take three or four percent of your portfolio and if
[1:15:57] Speaker 2: you want to fool around with options, whatever, knock your
[1:16:00] Speaker 2: out and if it makes money, great, But like we've
[1:16:03] Speaker 2: seen you mentioned Apple, if it was your whole portfolio.
[1:16:06] Speaker 2: You would never have been able to ride it to
[1:16:09] Speaker 2: be a five extra tenants. You would have taken I'm
[1:16:11] Speaker 2: up twenty bucks. I'm taking the money off the table.
[1:16:14] Speaker 3: Yeah yeah.
[1:16:14] Speaker 4: So you know, people long ago would adopt the strategy
[1:16:20] Speaker 4: of bringing a certain amount of money to the casino, right,
[1:16:24] Speaker 4: and then of course the casinos put ATM on the floor.
[1:16:28] Speaker 3: So it's a battle. But mental accounting.
[1:16:32] Speaker 4: You have a gambling account, but that's it.
[1:16:37] Speaker 3: Yeah. I mean it would be better if it were zero, right,
[1:16:40] Speaker 3: but otherwise set it up.
[1:16:43] Speaker 4: That's something you can afford to lose. And when you've
[1:16:46] Speaker 4: lost it all.
[1:16:47] Speaker 5: Your stump, don't go to the ATM.
[1:16:49] Speaker 3: That's right.
[1:16:50] Speaker 2: So I only have you for a few more minutes.
[1:16:52] Speaker 2: I want to ask two of my favorite questions that
[1:16:55] Speaker 2: I want to ask each of you, that I ask
[1:16:57] Speaker 2: all of my guests, starting with what sort of advice
[1:17:01] Speaker 2: would you give a recent college grad interest in the
[1:17:04] Speaker 2: career and either behavioral finance or economics. Alse you're the
[1:17:08] Speaker 2: more recent grad, what would you what would your advice be?
[1:17:12] Speaker 5: Get tacked up? Really get tacked up. I think that's
[1:17:16] Speaker 5: the biggest kind of difference between even when I was
[1:17:18] Speaker 5: in graduate school and when I'm seeing hiring preducts and
[1:17:21] Speaker 5: ras the sort of work that you're doing in modern
[1:17:24] Speaker 5: behavioral economics, modern finance, it just requires a different level
[1:17:28] Speaker 5: of analysis.
[1:17:29] Speaker 2: So is this learning to code or is this becoming
[1:17:31] Speaker 2: a prompt engineer for AI?
[1:17:33] Speaker 5: What? I think you still got to learn to code.
[1:17:35] Speaker 5: I think you know where I work in the Applied
[1:17:39] Speaker 5: A I group at booth, you know, you still got
[1:17:42] Speaker 5: to learn to code. And a lot of this sort
[1:17:44] Speaker 5: of modern analyzes that people are doing, particularly as behavioral
[1:17:47] Speaker 5: finance behavioral ekon has moved out of the lab into
[1:17:50] Speaker 5: the field. These data sets are huge machine learning AI tools.
[1:17:55] Speaker 5: The type of people who are getting hired are doing
[1:17:58] Speaker 5: sophisticated analys So it's still.
[1:18:00] Speaker 2: Basically STEM groups science, technology, engineering, and math for people
[1:18:05] Speaker 2: who don't know the acronym, but applied specifically to the Feeah.
[1:18:09] Speaker 5: Yeah, And like you know, you take your economics courses,
[1:18:11] Speaker 5: you take your finance courses, take some CS courses on
[1:18:14] Speaker 5: the side. Those are this is what I wish I
[1:18:18] Speaker 5: would have done. Right when I was getting my PhD.
[1:18:20] Speaker 5: It wasn't on my radar to take, you know, a
[1:18:22] Speaker 5: coding class in the CS department. People coming out now
[1:18:25] Speaker 5: the ones who are really successful, you have to have
[1:18:27] Speaker 5: good ideas. That's a necessary condition. It's not a sufficient condition.
[1:18:33] Speaker 5: You still you got you need to be TechEd up
[1:18:36] Speaker 5: to a level that I don't think we were seeing
[1:18:38] Speaker 5: when I was graduating.
[1:18:39] Speaker 3: Really interesting.
[1:18:40] Speaker 4: I'll reinforce that with the following. I think you need
[1:18:44] Speaker 4: some practical experience. Yeah, because the part that you don't
[1:18:48] Speaker 4: learn in a textbook is you you get this gigantic
[1:18:53] Speaker 4: data set and it's noisy, and there are errors and
[1:18:59] Speaker 4: so so learning how to clean up a data set.
[1:19:06] Speaker 3: You got to learn that through experience.
[1:19:08] Speaker 2: Really interesting. And our final question, what do you know
[1:19:12] Speaker 2: about the world of behavioral economics today, would have been
[1:19:15] Speaker 2: useful back in the nineteen seventies and eighties when you
[1:19:19] Speaker 2: were getting started, and in the two thousands when you
[1:19:22] Speaker 2: were getting started.
[1:19:24] Speaker 3: So I think if we go back.
[1:19:26] Speaker 4: We talked about the changes that I helped make in
[1:19:31] Speaker 4: the retirement plans, and what I wish I had been
[1:19:37] Speaker 4: able to accomplish more of is making retirement saving at
[1:19:43] Speaker 4: the workplace available to the possibly forty percent of American
[1:19:48] Speaker 4: workers whose firms don't offer that option. And there were
[1:19:55] Speaker 4: plans around and they didn't get passed.
[1:20:01] Speaker 3: I think.
[1:20:03] Speaker 4: The system they have in the UK is a reasonable model,
[1:20:07] Speaker 4: which is there's a requirement that any firm with more
[1:20:12] Speaker 4: than I'm not show the number, say twenty employees, has
[1:20:17] Speaker 4: to offer a plan and automatically enroll people into the plan,
[1:20:25] Speaker 4: and the government has like a generic plan they can use,
[1:20:29] Speaker 4: like the government thrift program. So and this is useful
[1:20:35] Speaker 4: because big firms like Fidelity and Vanguard don't really want
[1:20:39] Speaker 4: tiny accounts, so make it easy for an employer. They
[1:20:46] Speaker 4: don't have to do anything. They just have to let
[1:20:49] Speaker 4: their employees enroll in this and then when they change
[1:20:53] Speaker 4: jobs they can keep it there. Because the real problem
[1:20:58] Speaker 4: is they go to war for a while at this
[1:21:02] Speaker 4: firm and they worked there for a year and they've
[1:21:05] Speaker 4: saved six hundred dollars and then they leave and.
[1:21:08] Speaker 3: They take the cash out.
[1:21:10] Speaker 4: So we need automatic roll over. So that's the piece
[1:21:16] Speaker 4: of the puzzle that I don't know whether I could
[1:21:20] Speaker 4: have done anything about, but it's what I wish we
[1:21:23] Speaker 4: could work on now.
[1:21:24] Speaker 2: So related to that, what do you think of these
[1:21:26] Speaker 2: new baby accounts? Every newborn in America next year gets
[1:21:30] Speaker 2: one thousand dollars has to be invested domestically, which you know,
[1:21:34] Speaker 2: we can have an argument. We were talking about home
[1:21:37] Speaker 2: country bias, but still you're starting every infant off with
[1:21:41] Speaker 2: a portfolio. What are your thoughts on that.
[1:21:45] Speaker 3: I don't know the details of how that's going to work.
[1:21:47] Speaker 3: You could.
[1:21:50] Speaker 4: My friend and sometimes colleague when I'm in Berkeley, Ulrica
[1:21:55] Speaker 4: Melmendie has made a similar proposal in Germany, where she's
[1:21:59] Speaker 4: on the German Council of Economic Advisors.
[1:22:03] Speaker 3: I think the idea is to give kids.
[1:22:08] Speaker 4: Some experience with the stock market, and I think that
[1:22:13] Speaker 4: could be useful. I don't know how this is going
[1:22:19] Speaker 4: to wash out and all of these things end up
[1:22:23] Speaker 4: being tilted toward the rich. I mean, there were big
[1:22:28] Speaker 4: reforms made recently to the retirement plans. One of the
[1:22:33] Speaker 4: reforms was to let you wait longer to start making withdrawals.
[1:22:39] Speaker 3: Who do you think that helps people who.
[1:22:41] Speaker 2: Are wealthy, healthy and going to have a longer lifespan.
[1:22:44] Speaker 4: Right, So most people start taking the money out at
[1:22:50] Speaker 4: fifty nine and a half. Raising the data at which
[1:22:54] Speaker 4: you have to start from seventy to seventy two doesn't
[1:22:59] Speaker 4: help anybody that's in any trouble.
[1:23:01] Speaker 2: Yeah, that makes a lot of sense, Alex, What do
[1:23:04] Speaker 2: you know today about behavioral finance that you wish you
[1:23:07] Speaker 2: knew when you were getting started.
[1:23:10] Speaker 5: I think what I when I was getting started, I
[1:23:13] Speaker 5: wasn't really thinking about kind of target being able to
[1:23:16] Speaker 5: target these big institutional investors and thinking about getting data
[1:23:21] Speaker 5: sets on smart money in the economy. So I think
[1:23:26] Speaker 5: when I was starting out, I was really focused on
[1:23:28] Speaker 5: lab experiments. I was really focused on kind of the
[1:23:30] Speaker 5: data that's that was available. And if I was starting
[1:23:34] Speaker 5: out now, I would I would start my PhD trying
[1:23:37] Speaker 5: to get trying to get data sets that I eventually
[1:23:39] Speaker 5: was able to get because the types of as far
[1:23:42] Speaker 5: as like looking at my research, what has had the
[1:23:44] Speaker 5: largest impact, what has had you know, people in finance
[1:23:48] Speaker 5: in the professional world calling me up and saying, hey,
[1:23:51] Speaker 5: what do you think about this? Or that it's been
[1:23:54] Speaker 5: looking at the population that people are actually interested in,
[1:23:57] Speaker 5: which are you know, the smart money in the economy.
[1:23:59] Speaker 5: So I think and this is I think, you know,
[1:24:04] Speaker 5: you have this analogy of looking under the spot under
[1:24:08] Speaker 5: the street light, where is a lot of behavioral finance
[1:24:11] Speaker 5: for the missing exactly? You know where are you're looking? Oh,
[1:24:14] Speaker 5: it's where the data sets already are. So you know,
[1:24:17] Speaker 5: Terry o'dean had this genius idea in ninety eight when
[1:24:20] Speaker 5: he published his paper. What did he do? He made
[1:24:22] Speaker 5: that big data set available. Now it's easy to just oh,
[1:24:26] Speaker 5: I got an idea, Why don't I look at Terry's
[1:24:28] Speaker 5: data set. Terry's data set is great, but it's three
[1:24:30] Speaker 5: years in the nineties with you know, a couple hundred
[1:24:33] Speaker 5: retail traders, and that tells you about that's specific population.
[1:24:37] Speaker 5: But you can't have a field evolve looking at three
[1:24:41] Speaker 5: years of retail traders with ten thousand dollars portfolios. So
[1:24:44] Speaker 5: I think if I was going to going into the
[1:24:46] Speaker 5: field now and thinking about, you know, what have I learned?
[1:24:50] Speaker 5: It's the power of getting data sets and running analyzes
[1:24:54] Speaker 5: on on populations that are important for the economy and
[1:24:59] Speaker 5: for finance.
[1:25:00] Speaker 2: Really really fascinating. Gentlemen, Thank you so much for doing this.
[1:25:03] Speaker 2: We have been speaking with Richard Taylor and Alex Emos,
[1:25:07] Speaker 2: both of the Booth School of Business, about their updated
[1:25:11] Speaker 2: version of The Winner's Curse. Strong recommendation if you enjoy
[1:25:15] Speaker 2: this conversation, well check out any of the five hundred
[1:25:18] Speaker 2: and ninety two we've done over the past twelve years.
[1:25:22] Speaker 2: You can find those at iTunes, Spotify, Bloomberg YouTube, wherever
[1:25:27] Speaker 2: you get your favorite podcasts, and be sure to check
[1:25:30] Speaker 2: out my new book, How Not to Invest The ideas, numbers,
[1:25:33] Speaker 2: and behavior that destroys wealth and how to avoid them.
[1:25:37] Speaker 5: I would be remiss if.
[1:25:38] Speaker 2: I thank the Crack team that helps put these conversations
[1:25:41] Speaker 2: together each week. Alexis Noriega is my video producer. Sean
[1:25:46] Speaker 2: Russo is my researcher. Anna Luke is my producer. Safe
[1:25:50] Speaker 2: Bauman is the head of podcasts here at Bloomberg. I'm
[1:25:54] Speaker 2: Barry Ritolts. You've been listening to Masters in Business on
[1:25:58] Speaker 2: Bloomberg Radio.
[1:26:00] Speaker 5: Brast transud to reco

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