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  • INTERVIEWER: Today is December 5, 2011.

  • I'm Chris Boebel.

  • As part of the MIT150 Infinite History project, we're talking

  • with Professor Andrew Lo.

  • Professor Lo is the Harris & Harris Group Professor of

  • Finance at the MIT Sloan School of Management and the

  • director of MIT's Laboratory for Financial Engineering.

  • His wide-ranging research interests include financial

  • asset pricing models, financial engineering and risk

  • management, trading technology, computer

  • algorithms and numerical methods, financial

  • visualization, hedge fund risk and return dynamics and risk

  • transparency, and evolutionary and neurobiological models of

  • individual risk preferences in financial markets.

  • His awards include-- to name just a few--

  • the Alfred P. Sloan Foundation Fellowship, the Paul A

  • Samuelson Award, a Guggenheim Fellowship, and multiple

  • awards for teaching excellence.

  • He is a former governor of the Boston Stock Exchange and

  • currently a research associate for the National Bureau of

  • Economic Research, a member of the NASD's Economic Advisory

  • Board, and founder and chief scientific officer of

  • Alphasimplex Group, LLC a quantitative investment

  • management company.

  • Professor Lo received a BA in economics from Yale University

  • in 1980 and a PhD in economics from Harvard in 1984.

  • Professor Lo, thanks very much for coming in

  • to talk to us today.

  • LO: Thanks for having me.

  • INTERVIEWER: So let's just start at the beginning.

  • Where were you born, and where did you grow up?

  • LO: I was born in Hong Kong.

  • And shortly after, I moved to Taiwan for about five years.

  • And then, when I was five years old, I came to the

  • United States.

  • And I grew up in New York City.

  • INTERVIEWER: Tell me a little bit about that transition from

  • a cultural perspective, that educational perspective.

  • LO: Well, it was a fantastic experience in many ways.

  • So I grew up in a single-parent

  • household in New York.

  • And my mother worked pretty hard to put the three of the

  • kids through school.

  • We went through public schools throughout, and the New York

  • City public school systems are among the best in the country.

  • Certainly, they were at the time, and so I feel I got a

  • great education, and met some really, really interesting

  • people during my time there.

  • INTERVIEWER: So you were an urban kid for most of your--

  • LO: I was.

  • We lived in Queens, and I commuted to the Bronx.

  • I went to the Bronx High School of Science.

  • I'm very proud of that.

  • I love that school, and I learned a great deal from my

  • classmates.

  • It was a lot of fun.

  • INTERVIEWER: So do you have very early

  • memories from Taiwan?

  • Or does your consciousness start in New York City?

  • LO: No, we have some memories.

  • I've got a number of things that I remember well from

  • those days: playing with fireworks was one of the

  • favorite activities in Taiwan, but for the most part, my

  • childhood was really in New York.

  • INTERVIEWER: So when did you start developing an interest

  • in economics, math?

  • I'm sort of interested in your entree to your field.

  • Were there early signs?

  • LO: Well, actually, starting in high school.

  • I had always been interested in science, of course.

  • In third grade, my third grade teacher, Mrs. Barbara

  • Ficalora, was wonderfully supportive, and made me the

  • class scientist.

  • And so I got an early introduction to doing

  • experiments.

  • It wasn't until high school that I became exposed to real

  • serious scientific reasoning, and also to the field of

  • economics through a course that I took in social studies,

  • where we read Heilbroner's Worldly Philosophers.

  • And that really changed my thinking about the idea that

  • you could apply interesting mathematical principles to

  • problems in economics.

  • INTERVIEWER: Bronx Science is obviously kind of a legendary

  • high school.

  • Can you talk a bit more about your experience there?

  • What were your career ambitions at that

  • point in your life?

  • And what kinds of things were you really

  • studying in high school?

  • LO: Well, for me, Bronx Science was a really

  • transformative experience, because, up until then, the

  • junior high school and elementary school that I went

  • to was really just local, kind of community schools, where

  • you had a wide mix of kids, some of whom are interested in

  • academics, but most of whom were probably not.

  • And so in that kind of environment, to be doing well

  • in school was to be a bit of an outcast.

  • It wasn't until I got to Bronx Science that it became cool to

  • actually do well in school and to be interested in academics.

  • So for me, it was really like an awakening.

  • I had tremendous friends and activities in Bronx Science

  • that I really couldn't have access to in any of the

  • schools that I went to before that.

  • Also, for me, it was a little bit of an interesting

  • experience in terms of the mathematics at Bronx Science.

  • Right around that time, Bronx Science instituted--

  • as all New York City high schools--

  • the so-called New Math.

  • And if you know the history of it, the New Math was an

  • absolute disaster from the perspective of the majority of

  • the students.

  • But for me, it was actually transformative as well,

  • because up until then, I had a particular learning issue, a

  • slight case of dyslexia that we didn't know

  • until much later on.

  • And so for the longest time, I had difficulty with

  • mathematical concepts, multiplication, and really

  • basic things that other kids had no issues with.

  • I had a hard time memorizing the multiplication table.

  • It wasn't until I got to Bronx Science that, because of the

  • curriculum in mathematics--

  • it was transformed from the basic algebra, geometry,

  • trigonometry to sets, rings, fields, abstract algebra--

  • that I turned from a C student to an A student in math, so

  • for me, that was really an important experience.

  • INTERVIEWER: That's kind of an amazing story.

  • LO: I was one of the lucky ones that benefited from the

  • unfortunate aspects of the New Math that was perpetrated on

  • New York City high school students.

  • INTERVIEWER: At least there was one.

  • So you mentioned your third grade teacher.

  • Were there other mentors, significant teachers,

  • experiences you had in high school or before that time

  • that really pushed you in a certain direction?

  • LO: Oh, a number.

  • One of the things that has always struck me is how

  • important teaching is, because a good teacher can have such a

  • positive influence on a student for the rest

  • of his or her life.

  • And similarly, a bad teacher can have tremendous negative

  • consequences for that student.

  • And so I've been very fortunate in that, during the

  • years, I've had some good teachers, many good teachers,

  • a few bad ones.

  • So I have a good understanding of what's involved.

  • And my third grade teacher, Mrs. Ficalora, stands out.

  • In high school, I had a number of teachers.

  • Bronx Science is filled with really extraordinary faculty.

  • In fact, we don't think of them as teachers.

  • We think of them as faculty.

  • Mrs. Mazen, my calculus teacher.

  • I learned more from her about calculus than I think most

  • college courses would teach their students.

  • So there are a number of very talented instructors that I

  • was very pleased and lucky to have.

  • INTERVIEWER: What were your career aspirations at that

  • point, just before college?

  • LO: Well in high school, I think that most of my friends

  • and I were interested in science and math.

  • So at the time, my presumption was that I would go into one

  • of those disciplines.

  • Being the youngest of three children, and having an older

  • brother and sister that were also academically inclined

  • made it relatively easy for me.

  • My brother is a mathematician at the Jet

  • Propulsion Lab at Caltech.

  • And my sister is a biologist at the University of

  • Pittsburgh.

  • So they both followed very academic careers.

  • And in my household, one had to get a PhD just to measure

  • up to the older siblings.

  • So from high school on, I was very much interested in

  • following some kind of a career path in academia,

  • although my interests were somewhat on the more applied

  • side, as opposed to purely theoretical kinds of issues.

  • INTERVIEWER: You mentioned a single-parent household.

  • Was your mother at all academically inclined?

  • Was it your mother that you were--

  • LO: Yeah, my mother was very much academically inclined,

  • from the perspective of what she valued.

  • She felt that the life of a scholar was among the most

  • important and prestigious.

  • She was a lawyer by training.

  • But she had--

  • as most, I think, Chinese families did-- a deep and

  • abiding respect for academic achievements.

  • And so it was pretty clear, from the kinds of things that

  • she talked about and the values that she held, that

  • developing new knowledge was really important to her and

  • ultimately to all of the children.

  • INTERVIEWER: So at that point in high school when you had to

  • really start seriously thinking

  • about the next steps--

  • going to college, what you might study--

  • tell me about that decision process.

  • You ultimately went to Yale.

  • And then talk a bit about your experience there.

  • LO: Well, I was a little confused about

  • what I wanted to do.

  • My sister went to MIT as an undergraduate.

  • My brother went to Caltech.

  • And so when I talked with my mother about where I ought to

  • go for college, she said, well, maybe you ought to think

  • a little bit more broadly about the kind of things that

  • you're interested in.

  • And so rather than pursuing a somewhat more technical career

  • path, I thought that maybe applying to a general liberal

  • arts college would be a good idea.

  • And I was thinking at that time that I might want to do a

  • combination of mathematics and biology.

  • I did a science project as a senior.

  • I was a Westinghouse Finalist.

  • Intel, I guess, now is what they call it.

  • And I was very much steeped in molecular biology at the time.

  • And so Yale seemed to have a good compromise in very strong

  • humanities, but also very good science programs.

  • So I ultimately decided that that would be, really, the

  • best compromise.

  • I visited the school, and I was really

  • enthralled with the campus.

  • New Haven wasn't so great.

  • But Yale, itself, was a wonderful

  • physical space for students.

  • And so it was a pretty easy decision, after I had gone

  • through and looked at all the various different

  • possibilities.

  • INTERVIEWER: You mentioned the Westinghouse Competition.

  • It's amazing how many of our interviewees have a story

  • about Westinghouse and participating in that.

  • LO: Well, it's a wonderful activity, and obviously not

  • for everybody, but at Bronx Science, most of the students

  • that I interacted with really got into it.

  • And we learned so much from it.

  • I still remember, to this day, every aspect of the

  • experiments that I conducted on the infective pathway of

  • bacteriophage T4.

  • And I actually corresponded with an MIT faculty, who, at

  • the time, I didn't know.

  • But Jonathan King actually had some strains of bacteriophage

  • that I was interested in and was very generous in sharing

  • it with me.

  • So it was a wonderful experience in getting me to

  • understand how research is conducted, and, really, what

  • the academic style of interactions might be.

  • INTERVIEWER: So you chose Yale.

  • You decided that that was the place for you.

  • Tell me a little bit about your time there, how your

  • academic and career interests developed, and just sort of

  • what the experience was like.

  • LO: Well, I had a great time at Yale.

  • It was a really remarkable experience in a number of

  • different ways.

  • When I arrived, I had thought that I was going to be doing

  • math, biology, maybe applied sciences of some sort.

  • But I ended up taking an introductory economics course

  • that was completely different from anything

  • that I had seen before.

  • There was a substantial amount of mathematics involved.

  • But yet the ultimate applications were really quite

  • relevant to day to day experience.

  • And that's quite different from math or physics,

  • particularly at the undergraduate level.

  • So I got very excited about that.

  • The other thing that I found remarkable about Yale was

  • that, really, for the first time since I started getting

  • interested seriously in academics--

  • for the first time, I actually met people at Yale that I

  • considered to be really smart, but who had no abilities to do

  • mathematics.

  • In high school, certainly at Bronx Science, you very often

  • equated intelligence with technical abilities.

  • You're good at math, physics, biology---

  • you were smart.

  • At Yale, I ran into a number of individuals that were

  • extremely intelligent but were simply not numerate.

  • Their form of intelligence I found really different and

  • fascinating.

  • And that is sort of the beginnings of

  • my interest in economics.

  • I realized that mathematics was not the only way of

  • understanding interactions in a very deep way, and that yet

  • you could actually put the two together in some interesting

  • fashion to come up with some new insights.

  • INTERVIEWER: So was it sort of an immediate click?

  • You mentioned the Intro to Economics class.

  • LO: No, it wasn't.

  • I was very confused for a long time.

  • What ultimately decided it for me was a teacher, a professor,

  • Sharon Oster, who taught a fantastic intermediate

  • microeconomics class.

  • She was spellbinding.

  • She provided intuition, developed some very rigorous

  • mathematical models, and made it all relevant and really

  • interesting.

  • So I found her to be an enormously inspiring teacher.

  • And from the moment I took her course, I took every other

  • course she ever taught, and ultimately asked her to be my

  • undergraduate advisor.

  • And I was a research assistant for her, and ultimately wrote

  • my senior thesis with her and some other faculty at Yale.

  • It was a tremendous experience.

  • And so I think that's really what ultimately made me focus

  • on economics as the field that I went into.

  • INTERVIEWER: Some of those early ideas you've talked

  • about, the relationship or the tension between mathematical

  • models and human behavior, are still present in a lot of what

  • you are interested in, which we'll talk about later.

  • But that's an interesting kind of continuity.

  • LO: Well, it is.

  • And I think it's also a part of my interests even back in

  • high school, with The Worldly Philosophers, but also from

  • the science fiction perspective.

  • I, as a high school student, read Isaac

  • Asimov's Foundation Trilogy.

  • And the notion of using mathematics to predict the

  • course of human evolution, I found completely captivating.

  • And I didn't know it at the time, but economics was

  • probably the closest field to this fictitious psychohistory

  • that Asimov talks about.

  • And so I suspect that that had something to

  • do with it as well.

  • But all of these pieces were really amorphous

  • to me at the time.

  • And only with the benefit of hindsight does some of it seem

  • to make sense.

  • INTERVIEWER: It's funny.

  • I just randomly, for some reason, over the weekend had

  • picked up the first Foundation, the

  • first of the trilogy.

  • I had read it years ago.

  • Were you a science fiction fan?

  • Was that something that kind of drove

  • your interest in science?

  • LO: I was.

  • I read a lot of things in that genre as

  • a high school student.

  • But mostly Arthur C. Clarke.

  • He was one of my favorite writers, Robert Heinlein.

  • But Isaac Asimov was a favorite, not so much because

  • of his writing style.

  • I actually found Asimov's writing style not nearly as

  • pleasurable as Arthur C. Clarke.

  • But the range of ideas that Asimov had in his books were

  • just astonishing, from I, Robot to the Foundation to all

  • of the other short stories that he wrote, his field of

  • vision was really tremendous.

  • And so that got me very much excited about the

  • possibilities of science.

  • And many of his ideas of science fiction have actually

  • become science fact over the last couple of decades.

  • INTERVIEWER: So like so many people at MIT, you had an

  • early interest in science fiction and science.

  • But you chose to really move in kind of a different

  • direction in college.

  • Was it difficult to say goodbye to science?

  • It's not saying goodbye.

  • Maybe that's the wrong term.

  • LO: Well, that's just it.

  • You see, I actually didn't think I was saying goodbye to

  • science, although in many respects, I think

  • I should have been.

  • And we can discuss that later.

  • But my thinking was that economics could be as rigorous

  • a science as the physical and biological sciences.

  • And I remember having many dinner conversations with my

  • elder siblings, who, of course, were scientists, and

  • who, of course, as elder siblings do, spent a fair bit

  • of their time torturing me, asking me

  • to justify my existence.

  • And so I've actually spent a fair bit of time thinking

  • about whether or not economics is or is not a science.

  • I, of course, think it is.

  • And when I was in college, my interest in mathematical

  • economics was probably motivated by that drive.

  • The ability to use formal mathematical and statistical

  • models to make precise statements about economic

  • phenomenon was what I thought I was doing

  • and studying in college.

  • And it wasn't until grad school that I had a bit of a

  • rude awakening to that effect.

  • INTERVIEWER: We'll move on to grad school in just a moment.

  • I just thought I would ask, were there other very

  • formative or important experiences in college that

  • pushed you in a particular direction or

  • helped form your ideas?

  • LO: A couple.

  • One was another professor, Herbert Scarf, who taught a

  • graduate course in economics, microeconomics,

  • and economic theory.

  • And game theorists, Pradeep Dubey and Martin Shubik, I

  • took their courses as well.

  • And during those courses, it became clear to me that using

  • formal models to study human behavior was both a bit of a

  • treacherous exercise-- there is a lot of behavior that

  • doesn't fit neatly into these models.

  • But at the same time, those were the heydays of general

  • equilibrium analysis.

  • And tremendous progress was being made in developing

  • mathematical theorems that would demonstrate the

  • existence and uniqueness of economic equilibrium.

  • So it was a heady time for the literature.

  • And as an undergraduate, I got exposed to some of it through

  • the faculty.

  • Yale's economics program is really tremendous in that they

  • do expose the undergraduate students to graduate level

  • courses if and when they're ready and they're interested.

  • And because they also allow for opportunities to write an

  • undergraduate thesis, you actually can engage in

  • research even at that level.

  • So my senior thesis was on game theory, and ultimately, I

  • actually got it published.

  • So that was a really fascinating process that I

  • enjoyed and it gave me a taste for the academic and a sense

  • that there's a lot that could be done with relatively simple

  • mathematical tools.

  • INTERVIEWER: You decided to pursue graduate studies.

  • You went onto Harvard.

  • You went immediately from undergrad on?

  • Or did you--

  • LO: I did.

  • And in retrospect, that might not have been the

  • best thing to do.

  • But part of it was financially driven.

  • Because we came from a single-parent household and we

  • didn't have very much in the way of financial resources, I

  • actually graduated from Yale a year early.

  • And when I was thinking about what to do, I was actually

  • choosing between law school and graduate school.

  • Because I was also interested in applications and seeing how

  • these ideas could actually affect reality in practice.

  • But then I did a very simple economic analysis.

  • Law school was three years, and the tuition was however

  • many tens of thousands of dollars.

  • And graduate school was, for all intents

  • and purposes, free.

  • Not only was it free, I found that they actually paid you to

  • go to graduate school!

  • They gave you a stipend.

  • And so, to me, the answer was clear.

  • I have got to get a PhD.

  • That, and also the fact that my brother and sister were

  • PhDs, as I said, provided some motivation for me to achieve

  • that level of success from an academic perspective.

  • So I think that ultimately I decided that going to grad

  • school was the right decision.

  • And given that my undergraduate advisor, Sharon

  • Oster herself, received her PhD at Harvard and spoke very

  • highly of the program, that was a very easy

  • decision for me.

  • Actually, MIT and Harvard were the two choices that I had

  • considered.

  • At the time, I really didn't have much of

  • an interest in finance.

  • I didn't know what finance was about.

  • And so, really, for my interest in mathematical

  • economics, I thought that Harvard

  • would be a better choice.

  • INTERVIEWER: Did you know Boston at all?

  • Had you been here?

  • I was actually going to ask if you had been to MIT?

  • You had a sibling who had attended MIT.

  • LO: I have very fond memories of MIT because when I was in

  • junior high school, my sister was an undergraduate here.

  • And so we would come up every fall, and bring

  • her up here by car.

  • And I would stay here for a couple of days to make sure

  • she got settled.

  • And while here, I spent an enormous amount of time in the

  • Student Center playing, at the time, pinball machines.

  • I don't know if they have any pinball machines here now.

  • But I spent a lot of time there and roaming the campus.

  • So I loved it.

  • And I developed early on an affection for MIT.

  • INTERVIEWER: But you went to Harvard, nevertheless.

  • So tell me a little bit about your graduate school years.

  • Again, I'm very interested in

  • significant professors, mentors.

  • LO: Harvard was a bit of a rude awakening

  • in a couple of respects.

  • Probably the most significant was that the faculty member

  • that I was hoping to work with ultimately ended up being on

  • leave the year that I arrived, in 1980.

  • So I ended up taking classes in micro, macro, and

  • econometrics like all the other first year students.

  • And I was hoping that the material that I learned as an

  • undergraduate would be expanded

  • upon in graduate school.

  • I knew that the models that we developed in undergraduate

  • classes were relatively limited, and that with more

  • mathematics and more understanding of economic

  • concepts we could develop more realistic models.

  • So I was actually quite disappointed when, after the

  • first semester of my first year, I realized the models

  • that we developed were pretty much identical to what I had

  • done at Yale, and that there wasn't anything more.

  • It was a bit frustrating for me.

  • In addition, at the time the Harvard economics program had

  • some difficulties.

  • They were going through a transition where some of their

  • faculty were on leave.

  • And the faculty that were there at that time were not

  • really supposed to be teaching in a first year core.

  • So the core was somewhat uneven.

  • And a number of us became quite frustrated with that

  • experience.

  • And so by the end of the first semester, I had actually

  • filled out my application for law school.

  • I thought I had made a bad mistake.

  • And it wasn't until I happened to take a course in the spring

  • semester taught by Bob Merton in finance here at MIT that

  • changed my mind completely about graduate school.

  • That was really the most formative experience for me,

  • realizing that you can actually apply very

  • sophisticated mathematics, but in very practical settings.

  • And that was what was missing from general equilibrium

  • theory and game theory.

  • I didn't feel that the mathematics really brought us

  • to any closer understanding for practical kinds of

  • situations, whereas finance seemed exactly what I was

  • looking for.

  • So after that point, I realized I

  • wanted to do finance.

  • INTERVIEWER: So for the truly ignorant, such as myself, what

  • do you mean when you say finance?

  • I think people tend to gloss economics, finance, even

  • business into one bucket.

  • Talk about exactly what was appealing and what it was.

  • LO: Sure.

  • In fact, they're very closely related, not surprisingly.

  • Finance started out as a branch of economics.

  • But it has gotten to the point where it has become so much

  • more sophisticated in terms of the models and methods that

  • are applied that it has taken on a life of its own.

  • So in a nutshell, finance is simply applying economic and

  • mathematical principles to the study of money, investments,

  • in a world of uncertainty.

  • Uncertainty is really the key, because, for the most part,

  • economics is actually pretty well understood in the case of

  • perfect certainty.

  • If there is no randomness in the world, we actually

  • understand a lot about supply and demand and how individuals

  • engage in various kinds of economic decisions.

  • The sole aspect of the world that makes finance interesting

  • and nontrivial is the fact that we don't know what's

  • going to happen tomorrow.

  • And uncertainty really underlies all of what

  • financial models are about.

  • So in trying to model the dynamics of financial markets,

  • banks, asset management companies, hedge funds,

  • investment decisions, corporate financing

  • challenges, all of those are problems that ultimately

  • involve economics, but financial economics.

  • And because the tools of finance have evolved so

  • rapidly and so differently from other areas of economics,

  • it has really become almost a separate field unto itself.

  • In fact, most finance research is done in business schools.

  • Many economics departments, including Harvard, have now

  • hired a number of very talented first rate financial

  • economists.

  • But for the most part, the majority of the financial

  • economists are actually in business schools not economics

  • departments.

  • INTERVIEWER: So you had this very, very significant

  • experience taking this course with Bob Merton.

  • Talk about how that influenced your path in grad school.

  • LO: Well, it really changed it completely.

  • Up until then, my focus was really on mathematical

  • economics and game theory.

  • But once I took Bob Merton's course on introductory

  • finance, I realized that there is so much more applications

  • of genuinely substantive mathematics to problems that

  • cannot be solved in any other way, and that yet can bring

  • tremendous insight that ultimately affects practice.

  • That's not something that game theory or general equilibrium

  • theory has really been able to do.

  • So once I took Bob Merton's course in finance, I basically

  • took every other finance course offered at the time at

  • the MIT Sloan School.

  • Fortunately, at the time, and even to this day, Harvard and

  • MIT have a very collegial relationship, where students

  • from one university can cross- register, and almost

  • seamlessly take classes in the other university.

  • So it worked out beautifully, where I was able to take all

  • of my courses in finance at MIT.

  • And when it came time for me to take my qualifying exams at

  • Harvard, I petitioned to create a special field which

  • was finance.

  • At the time, they didn't have a field

  • called financial economics.

  • So I had to petition, and, fortunately, was able to get

  • one of the economics faculty at MIT to examine me in that

  • discipline.

  • INTERVIEWER: So the research you were interested in taking

  • on as a grad student, just talk about it for a bit in

  • light of this new interest that developed in finance.

  • LO: One of the things that I started out with thinking

  • about in economics was investments.

  • I was fortunate to have as one of my main advisers professor

  • Andy Abel, who currently is at Wharton.

  • But at the time, he was a junior faculty at Harvard.

  • And Andy had been working on investment theory, the idea of

  • how capital in the United States and elsewhere get

  • created from various kinds of economic considerations.

  • When you buy a machine, and you invest in it, you plan to

  • use it for many years.

  • What makes you decide to buy a machine, versus renting or

  • postponing?

  • This kind of investment theory fascinated me.

  • But I couldn't understand how the kind of investment in

  • machines translated to investments

  • in the stock market.

  • I knew that the two had to be related.

  • We both use the word investment in those contexts.

  • And yet, the kind of models that were developed seemed

  • really different.

  • My finance courses seemed very different from my

  • macroeconomics courses in that respect.

  • And so I spent a good part of my graduate days trying to

  • reconcile the two.

  • I remember talking with Fischer Black during his

  • office hours and asking him how could it be that, as an

  • economist, we use the word investment to mean purchasing

  • physical capital, whereas in finance, when we think about

  • investment, we talk about

  • purchasing shares of a company?

  • Those two activities ought to be related in some very

  • fundamental way, shouldn't they?

  • And Fischer Black said, yes, they should.

  • And I said, well, but there's nobody who's working on that.

  • How do we reconcile the two?

  • Doesn't this bother you?

  • And he replied that when he runs into contradictions and

  • inconsistencies, that actually delights him.

  • Because he realizes that means that there is work to be done!

  • And so that was a big insight for me, that I shouldn't get

  • frustrated.

  • I should actually be thankful that there was a thesis topic

  • that was emerging.

  • And ultimately, that's what I spent my years working on in

  • my thesis, integrating real and financial investments in a

  • mathematically consistent framework.

  • INTERVIEWER: One thing that I meant to ask you before--

  • I don't want to get sidetracked.

  • But I'm just curious.

  • Maybe you can sort of put it in the context of the work

  • that you're taking on.

  • What is general equilibrium theory?

  • And what are what you saw as its shortcomings.

  • LO: General equilibrium theory is a fascinating idea that was

  • developed centuries ago by French mathematician, Leon

  • Walras, and others.

  • And the idea sounds so simple.

  • But actually, it's quite complicated to work out.

  • The idea behind general equilibrium is that when you

  • look at an economy, you have to focus on all the various

  • different markets that exist, each one corresponding to a

  • different commodity or good.

  • And within each market, you've got individuals that demand a

  • good and individuals that supply the good.

  • And in each market, ultimately the intersection of supply and

  • demand determines the so-called equilibrium price

  • for that market.

  • Well, the fact is that all of these markets are going on at

  • the same time.

  • And so instead of looking at what happens in one market, in

  • order to truly understand how an economy changes over time,

  • you actually have to ask the question, how do all the

  • markets equilibrate together?

  • General equilibrium does exactly that.

  • It says that, given a collection of individuals that

  • all consume certain commodities, and given a set

  • of businesspeople that produce those commodities, there have

  • to be a set of prices for all the goods that are traded in

  • that economy so as to equate all the supply with all the

  • demand across all the markets.

  • Now that seems like a really tall order, to expect that

  • this kind of an equilibrium would occur across all of

  • these different venues and settings.

  • And the idea behind general equilibrium is to determine

  • the conditions under which such a general equilibrium

  • across all these markets could actually occur.

  • Some beautiful mathematics are involved in this.

  • And not only are there interesting mathematics about

  • the existence of equilibrium, there's additional mathematics

  • that say something about whether the equilibrium is

  • unique, and what happens when you're outside of an

  • equilibrium, and how you reach an equilibrium, how you move

  • from one to the other.

  • So it's an endlessly fascinating series of

  • questions that actually relies on some very deep mathematics

  • to understand.

  • But the problem with these so-called theories is that

  • they have become so general, they are so abstract, that

  • they've become divorced from reality.

  • Because in fact, in practice, you actually don't see general

  • equilibrium occurring.

  • In fact, in many cases, as we've seen over the last few

  • years, markets are often in disarray and in

  • disequilibrium.

  • Prices are moving around all the time, trying to

  • equilibrate.

  • And unfortunately, the mathematics and the direction

  • of the literature on general equilibrium hasn't really

  • focused as much on the transitions, the dynamics from

  • one to the other, as opposed to what occurs at an

  • equilibrium.

  • And so in that sense, I think finance has become a much more

  • relevant discipline, because it actually has testable

  • implications that have some very, very practical

  • applications.

  • INTERVIEWER: To return to your graduate work just for a

  • moment, you develop mathematical models to sort of

  • compare investments in stocks, bonds, with goods or

  • machinery, and so on.

  • I'm no mathematician.

  • But can you talk about what kind of

  • relationships you found?

  • And again, if you use your mathematical models it will

  • not mean much to me, I'm afraid.

  • LO: Sure.

  • Well actually, it's pretty straightforward.

  • The results that I developed in my thesis really focused on

  • what kind of investment policies of a corporation

  • would be necessary in order to support the kind of real

  • business activities that it engaged in.

  • And the answer is actually pretty simple, and hearkens

  • back to some research that was done by MIT economist, Franco

  • Modigliani, years ago.

  • In a market where there are no frictions, there's no cost to

  • engaging in issuing stock or issuing bonds--

  • in a frictionless market and a market with no taxes, the

  • answer is that the real economy and the financial

  • economy are pretty much separable.

  • It doesn't matter how you would finance a purchase of a

  • new machine--

  • whether you use debt financing or equity financing--

  • because in a costless world where markets are perfect all

  • the time, you can shift from one to the

  • other pretty easily.

  • And therefore, the financial side is almost an

  • afterthought.

  • But the problem is that as soon as you introduce market

  • frictions, that changes completely.

  • And really, it's the frictions that make things interesting.

  • You have to understand where the frictions are coming from

  • and how they relate to the

  • different sources of financing.

  • And with market frictions, with taxes, it turns out that

  • there actually is an optimal combination of equity and debt

  • financing that will support the kind of growth that a real

  • business activity entails.

  • And so working out the mathematics of it is really

  • what I did in my thesis.

  • And it was done in a dynamic context, so it was not just a

  • static, one-shot kind of a perspective.

  • It was really couched in the framework of a company that

  • was engaged in multiple projects over

  • the infinite future.

  • And so that really gave me a deeper understanding for how

  • to integrate the real and financial sides of the

  • economy, and gave me an appreciation for why it is

  • that frictions really are at the core of

  • what we do in economics.

  • So much of economic theory is the frictionless case.

  • And those are important cases, because you have to understand

  • the frictionless case before you can start seeing how

  • frictions matter.

  • But we often forget that frictions do matter-- because

  • we get so enthralled with a frictionless case, given that

  • the mathematics are so beautiful--

  • that we don't go to the next step, which is to say, let's

  • make it messy again by building in these frictions.

  • And frankly, that's what I've been working on ever since.

  • INTERVIEWER: You mentioned Robert Merton.

  • Were there other significant mentors, influences during

  • your graduate years that we should talk about?

  • I think you've actually mentioned a couple of others.

  • LO: Absolutely.

  • Jerry Hausman was a critical figure in my intellectual

  • development.

  • Jerry is an economist at MIT, an econometrician.

  • And it turned out that I got to know him because I took an

  • econometrics course with him at Harvard.

  • He was on sabbatical from MIT, and he decided to spend the

  • year at Harvard.

  • And so he taught a graduate econometrics course that I

  • took and I did well in.

  • Well, enough that he hired me as a research assistant that

  • summer, and then hired me to TA that course

  • the following year.

  • And I really enjoyed it and enjoyed working with him.

  • And ultimately, he became one of my

  • principal thesis advisors.

  • He was the one who gave me the idea that you could actually

  • use rigorous econometric techniques to apply financial

  • concepts to the data and learn a great deal about how these

  • theories actually worked in practice.

  • And so the field that I ultimately spent most of my

  • early career on, financial econometrics, grew out of my

  • interactions with Jerry, and countless conversations, and

  • free lunches and dinners that Jerry treated me to very

  • generously, during the time that I was his student.

  • INTERVIEWER: We tend to think of graduate students,

  • particularly at places like Harvard and MIT, as being

  • involved within this all-consuming research quest

  • for knowledge.

  • Were there other things going on in your life that were

  • really important to you or significant?

  • Or did you find yourself getting really

  • sucked into the work?

  • LO: Well, no doubt, graduate school was very intense.

  • But it was a fun intense, in the sense that it was, for the

  • first time, an experience where I was surrounded by

  • people that were all interested in the very same

  • relatively narrow field that I was.

  • So that was a new experience and a very enjoyable one.

  • At the same time, I was also working as a research

  • assistant and as a tutor, because financially, it was a

  • bit challenging for my family.

  • And so I learned about the real economic life of making

  • money for supporting myself.

  • I was also dating a girl who ultimately I married.

  • My wife, who, at the time, was an

  • undergraduate at Yale still.

  • And so we had a long distance relationship

  • for my days at Harvard.

  • And I remember spending enormous amounts of money on

  • phone bills.

  • And it was really then that I got into the habit of staying

  • up late at night, because after 11 o'clock,

  • the rates went down.

  • And even so, had we been able to avoid these long night

  • phone calls, we probably could have purchased two cars by the

  • end of my graduate school days.

  • So that was probably the most significant other activity

  • that I was focused on during that time.

  • INTERVIEWER: So you're a newly minted PhD.

  • What's next?

  • LO: Well, when I went on the job market, my wife---

  • my girlfriend at the time--- was a graduate student in a

  • PhD program in finance at the Wharton School at the

  • University of Pennsylvania.

  • So I was fortunate enough to be interviewed by them.

  • And they flew me out to give a job talk, and made me an offer

  • the next day.

  • And I accepted the next day after.

  • So by the middle of January I was actually done with

  • recruiting because my girlfriend was there.

  • And so it was pretty easy.

  • Also, the Wharton School is renowned in the area of

  • finance, and it was a bit of a new thing at the time for an

  • economist to be hired by a business school.

  • At the time, most business school faculty were hired from

  • business school PhD programs.

  • And there was some crossover, but not a lot, and certainly

  • not a lot of crossover in finance.

  • Finance was really a field unto itself at the time: that

  • was really more a business school activity.

  • And economics departments were only really beginning to start

  • thinking about offering classes in finance, never mind

  • concentrations in that field.

  • So when Wharton made an offer, to me, it

  • was an ideal situation.

  • My girlfriend was there.

  • It was a bona fide and very well respected finance

  • department.

  • And my only fear was whether or not I was going to be able

  • to measure up to a finance department where I was an

  • economist, an outsider.

  • INTERVIEWER: Did you ever think twice about pursuing an

  • academic career, as opposed to Wall Street or other options?

  • LO: Well, I did a little consulting when I was a grad

  • student because the summer between college and grad

  • school I was a summer intern at a

  • company called Data Resources.

  • It's a software company started up by

  • some Harvard faculty---

  • Otto Eckstein, Dale Jorgensen, and others---

  • and at DRI, I actually was working on developing software

  • for engaging in a variety of economic analysis.

  • Maximum entropy spectral analysis was my

  • project that summer.

  • And so I did a bit of consulting for DRI during my

  • years as a grad student.

  • So I thought a little bit about going into industry.

  • But because I was so fascinated by the kind of

  • questions that came up in my thesis and I wanted to

  • continue on, and, I think, because the family upbringing

  • that I had clearly valued the academic lifestyle--

  • my brother and sister were both academics at the time--

  • it really was clear to me that I wanted to

  • follow an academic path.

  • INTERVIEWER: Let's talk a little bit about

  • your years at Wharton.

  • What were your research interests?

  • What kinds of things were you engaged in?

  • And also talk a bit about teaching as a

  • young faculty member.

  • LO: It was a very interesting mix of experiences that I had,

  • even in my first year at Wharton.

  • When I started in Wharton in 1984, I was 24 years old,

  • which is relatively young for a business

  • school faculty member.

  • In fact, I remember very clearly my very first day of

  • class, I was clearly younger than most of the students in

  • that introductory finance class.

  • There must have been 100 people in the room.

  • Wharton has quite a large program, and

  • they have big classes.

  • And before I actually began lecturing, literally the very

  • first day of class, a student raised his hand.

  • And so not knowing any better, I called on him and the

  • student said, Professor Lo, before you begin, we just have

  • three questions.

  • And I should have known right away, when they use the royal

  • we, this could not have a good ending.

  • He said, first, can you tell us whether you have ever

  • taught this course before?

  • Second, can you tell us what kind of consulting experience

  • you have in this area?

  • And third, can you tell us how old you are?

  • And not knowing any better, I answered the questions.

  • I said, no, this is my first year.

  • I've never taught this course before.

  • I have no consulting experience,

  • really, to speak of.

  • And I'm 24,

  • at which point literally half the class got up and walked

  • out of the room, because they decided that they wanted to go

  • to another section with more experienced faculty.

  • And I guess I can't really blame them.

  • They're paying a lot of money for their tuition.

  • But that was a sobering experience.

  • And it only went downhill from there.

  • So I was baptized in fire, in terms of MBA teaching.

  • And so that was a very important experience, a

  • formative experience for me.

  • But on the bright side, the experience at Wharton was

  • tremendously productive for me and the other junior faculty,

  • because it turned out that in that year Wharton hired nine

  • assistant professors just in the finance department, so I

  • was one among nine.

  • And the good thing about it was that because we came in en

  • masse, we became very close very quickly, the nine of us,

  • socializing with each other after hours, basically hanging

  • out all the time, because as an assistant professor,

  • there's not much else to do anyway.

  • None of us had families at the time.

  • Some of us had girlfriends or wives.

  • But we didn't have any children.

  • So we spent a lot of time together.

  • As a result, the department had to get used to us more

  • than we had to get used to the department.

  • And that was an incredibly important experience because

  • it allowed us to ask really interesting research questions

  • without the concern that some tenured faculty member would

  • disapprove.

  • Because frankly, the tenured faculty members weren't even

  • around to interact with us, given their priorities and

  • activities.

  • So we spent a lot of time interacting with each other,

  • challenging each other, talking with each other about

  • ideas, and ultimately one of the most fruitful

  • collaborations that I had in my career started in that year

  • with Craig MacKinlay, who was another assistant professor

  • from the University of Chicago.

  • INTERVIEWER: Presumably, your experience with the students

  • got better from that low point?

  • LO: It did get better.

  • And as I said, I learned very quickly that MBA students are

  • very demanding, and with good cause.

  • They are spending a lot of money on their tuition, and

  • they obviously have to start thinking about paying it back

  • in many cases with student loans afterwards.

  • It became clear to me that relevance was really key.

  • But, more importantly, that there was a certain impatience

  • among MBA students with respect to abstract theories

  • that may or may not lead to some very specific practical

  • implications.

  • And in time I learned to appreciate that perspective,

  • and begin to take it more seriously myself.

  • Not to say that academic theories are devoid of

  • practical consideration.

  • But there is a very important divide

  • between theory and practice.

  • And I don't think that academics necessarily

  • appreciate that as much as perhaps they might or that

  • they would if they, themselves, were placed in

  • kind of a practical environment.

  • INTERVIEWER: How did your research interests evolve as a

  • young faculty member?

  • LO: That was a wonderful thing about Wharton: it's that we

  • didn't really have any particular directions that we

  • were expected to take as junior faculty.

  • And so we were pretty much free to think about whatever

  • it is that appealed to us.

  • And my thoughts as a first year faculty member were

  • really in the direction of this notion of market

  • efficiency, and the ability for the real and financial

  • sides of the economy to engage in pretty much separate kinds

  • of directions.

  • As an econometrics student in Jerry Hausman's econometrics

  • course, one of the things that I looked into was the ability

  • of testing the random walk hypothesis using a particular

  • statistical procedure.

  • Really, it was just an exercise at the time to see

  • whether or not one could use fancier statistical methods to

  • test the age-old idea of whether or not you could use

  • past stock market prices to predict future

  • stock market prices.

  • One of the foundations of efficient markets hypothesis

  • is the notion that all the information about the future

  • of a company is actually contained

  • in its current price.

  • And if that's true, that means you can't use past price

  • realizations to forecast future

  • directions of the market.

  • And as a student in Jerry Hausman's econometrics course,

  • I developed an idea for using a statistical test to capture

  • that hypothesis.

  • So when I got to Wharton, I started

  • talking with Craig MacKinlay.

  • He and I had lunch pretty much every day.

  • And over lunch I would tell him about these ideas.

  • And he would say, well, we can actually take it to the data.

  • In my thesis, I spend a lot of time testing various ideas,

  • but I hadn't really done much with stock

  • market data at the time.

  • So he and I began to work on this.

  • And shortly thereafter, we came up with a rather

  • startling conclusion.

  • Using the tests that we developed and applied to the

  • data, we came to the conclusion that US stock

  • market prices actually don't satisfy this random walk

  • hypothesis.

  • Stock prices aren't actually purely random.

  • And at first, we thought that we had made

  • a programming error.

  • But in fact, after several repeated attempts to explain

  • away these findings, we came to the conclusion that this is

  • exactly what the data had to say.

  • And so we tried to get the paper published, and when we

  • presented it at a conference we were completely trashed by

  • our much more senior and well-respected discussant who

  • simply didn't believe the results.

  • His view was that markets could not possibly be that

  • inefficient, and that somehow you must have made a

  • programming error, which in our business, is worse than

  • calling your mother a four-letter name.

  • So we got very excited and agitated, and went back to our

  • computers and reprogrammed, and looked at the results.

  • And ultimately, we were vindicated in the sense that

  • this really was a feature of the data and from that point

  • on, for about a period of 10 years, Craig and I wrote a

  • number of papers to try to explain this anomaly, and

  • ultimately published a book that collected all of our

  • papers to try to understand this phenomenon.

  • INTERVIEWER: How long were you at Wharton?

  • And then how do you ultimately move on and come to MIT?

  • LO: I was at Wharton for four years, from 1984 to 1988.

  • In 1988, my wife graduated.

  • She finished her PhD; she got a job in Boston, and so we

  • were able to move.

  • That same year, I gave a talk at MIT and the faculty offered

  • a position to me.

  • Given my interests and the role that Bob Merton played in

  • my career, and Jerry Hausman, it was a very easy decision.

  • I accepted the offer pretty much immediately.

  • And we moved up to Boston in '88.

  • INTERVIEWER: Let's talk a little about MIT in 1988 or

  • the late 1980s.

  • Your experience obviously stretched back before that as

  • a graduate student.

  • What was it like then?

  • Have you seen significant changes--

  • in either the study of finance or in the student body--

  • in the culture of the place?

  • LO: Well, certainly some things have changed.

  • But I think a number of things have stayed the same.

  • And the things that have stayed the same are really the

  • reasons that drew me to MIT.

  • I guess probably the most important draw for me was that

  • I believe that modern finance, finance as a scientific

  • endeavor---

  • really began at MIT.

  • It began decades ago with Paul Samuelson.

  • His interest in finance sparked the interest of one of

  • his most productive and most talented students, Paul

  • Samuelson's student Bob Merton, who joined as a

  • graduate student in 1969, and became immediately Paul's

  • close companion in rewriting the entire corpus of finance

  • theory from the ground up.

  • To me, that was just a tremendous draw and the MIT

  • finance tradition that developed subsequently.

  • And the many other faculty members that were drawn to

  • this environment, including Stew Myers, Fischer Black,

  • Myron Scholes, Franco Modigliani, John Cox, any

  • number of--

  • Steve Ross.

  • We have tremendous faculty here that have really built

  • the edifice of modern finance theory.

  • So for me, it was an easy decision.

  • What's changed over time is that we now have a deeper

  • understanding of the kind of limitations that the early

  • theories exhibit, and are now more and more aware of and

  • open to alternatives to explain those departures.

  • The '70s, '80s, and '90s were a terribly exciting time for

  • MIT for the traditional finance paradigm: efficient

  • markets, rational expectations, and all of the

  • various ideas and products.

  • The multi-trillion dollar derivatives industry really

  • came out of ideas that Samuelson, Merton, Black and

  • Scholes, Cox and Ross pioneered.

  • And so that was an incredibly exciting time for that

  • literature.

  • But over the course of the last decade or so, we're

  • beginning to see the emergence of some new ideas that really

  • demonstrate that not only are there limitations to the

  • existing theories, but there are ways of extending them so

  • as to be able to develop a more rational, more internally

  • consistent perspective on how markets succeed and fail in

  • different circumstances.

  • INTERVIEWER: Turning now to your research interests, as I

  • mentioned at the beginning, there's a very almost

  • intimidating array of topics that you've tackled.

  • But there are also some consistent themes throughout

  • that we've already touched on.

  • Thinking specifically about the work that you've done

  • since coming to MIT, what are some of the most important

  • themes, from your perspective, that you've attempted to

  • grapple with?

  • LO: I think that there's actually a pretty clear

  • direction and evolution in my research agenda, which really

  • grew out of the work that I did as a grad

  • student and at Wharton.

  • And that's really to try to understand the dynamics of

  • financial markets.

  • When I got to MIT, I was still very much in the midst of this

  • notion of a random walk and whether or not one could

  • create profitable trading strategies from historical

  • information.

  • And it took me quite a few years here at MIT to try to

  • understand exactly what all the nuances are of the various

  • different types of activities that financial

  • investors engage in.

  • And ultimately, I came to the conclusion that, really, you

  • could not explain a way these anomalies as simply being

  • exceptions that prove the rule.

  • There were just too many of them.

  • And they were too stark and significant from both a

  • statistical and economic perspective.

  • And so that got me to try to take a little bit more

  • seriously the kind of departures from rationality

  • that people in the industry observe all the time.

  • What made it frustrating, though, was that the

  • alternative to the traditional economic and financial

  • paradigm of rational expectations and market

  • efficiency was so-called behavioral biases that

  • psychologists and experimental economists documented.

  • The problem is that, in my view, it takes a theory to

  • beat a theory

  • and the anomalies literature, which was really just getting

  • off the ground at the time, doesn't constitute a theory.

  • They're a collection of counterexamples, and very

  • important, by the way, but they're not really an

  • alternative to the traditional paradigm.

  • So really, much of my work after concluding that markets

  • really don't follow random walks and that you have to

  • take these exceptions as very serious challenges to the

  • received wisdom, much of my work has been trying to

  • understand how to reconcile these two contradictory

  • schools of thought.

  • INTERVIEWER: And how do we do that?

  • LO: INTERVIEWER: Well, it actually took me a while to

  • come up with the answer.

  • In fact, at first I thought you couldn't.

  • You just had to pick.

  • Pick your favorite flavor, and then stick with it.

  • But ultimately, because I spent more time thinking from

  • a number of different disciplines and perspectives--

  • including psychology, the cognitive neurosciences, and

  • evolutionary biology--

  • that I've actually finally come to a

  • reconciliation of the two.

  • And in a way, it seems almost simple to me now, even though

  • to this day it's certainly not received wisdom, by any means.

  • It's still fairly controversial.

  • The reconciliation that I came to is the recognition that

  • economic phenomenon and economic institutions are

  • creations of human activity in much the same way that an ant

  • hill or a beaver dam are creations of living creatures

  • that are adapting to a particular set of challenges

  • in their environment.

  • And viewed from a biological perspective, everything is

  • different, everything looks different.

  • Rather than arguing about whether or not behavior is

  • rational or irrational, a much more productive perspective is

  • to ask what kind of adaptations have emerged in

  • the face of certain societal, cultural, economic, and social

  • challenges.

  • And so it's really the confluence of evolutionary

  • biology with the revolution that we've had in the

  • cognitive neurosciences that has been able to allow me to

  • put together these different pieces because, ultimately,

  • we're focusing on human behavior.

  • That, I think, is the key.

  • It's that all of the different disciplines that I've

  • ultimately ended up learning about-- in order to answer the

  • question, why do people behave the way they do in economic

  • contexts?--

  • are studying the same thing: human behavior.

  • We may be focusing on different elements of it, but

  • we're all studying humans.

  • And because of that, our theories should be mutually

  • consistent.

  • They may not be focusing on the same thing, but as the

  • great evolutionary biologist, E. O. Wilson, wrote in his

  • book, Consilience, these facts have to be mutually consistent

  • with each other, because we're explaining the same

  • phenomenon.

  • And so, really, that's what my recent work has been about.

  • It has been about using different aspects of human

  • behavior to try to understand the whole, to create an

  • integrated theory of human behavior that spans the

  • various different contexts and activities that we are likely

  • to engage in.

  • INTERVIEWER: Let's drill down just a little bit and maybe

  • focus on some examples or an example or two.

  • LO: Sure.

  • INTERVIEWER: I'm an economic actor.

  • We all are.

  • I make irrational decisions all the time.

  • I'll confess.

  • What's the theoretical explanation for that?

  • Why would I make really, really bad investments that

  • can be sort of demonstratively bad, or make

  • bad financing decisions?

  • LO: To answer that question, we should first ask the prior

  • question, which is, how do decisions get made?

  • Or how does behavior emerge?

  • And obviously, we trace much of behavior to the brain.

  • So we need to spend a little bit of time talking about

  • neuroanatomy, and ask the question, what are the

  • components of the brain that neuroscientists have been able

  • to identify that are linked to specific actions?

  • Well, we know a few things at this point.

  • We know, for example, that there is a part of the brain

  • that is relatively primitive from an evolutionary

  • perspective, the so-called midbrain or the amygdala, and

  • the structures surrounding it.

  • This part of the brain is really focused on relatively

  • instinctive kinds of activities, so-called fight-

  • or- flight response, fear, greed, sexual attraction,

  • and we know that this part of the brain focuses on those

  • activities through imaging techniques that

  • neuroscientists have conducted.

  • So that describes one set of activities.

  • Another set of activities that neuroscientists have also

  • deduced as focusing on a different part of the brain is

  • higher thought functions that we would normally associate

  • with humans uniquely; things like language ability,

  • mathematical ability, logical deliberation.

  • That part of the brain is, from an evolutionary

  • perspective, the newest part, and it is given the name

  • neocortex to indicate that.

  • One of the things that we know from the neuroscience

  • literature is that these two components, the amygdala

  • versus the neocortex, in many cases they work together.

  • They're obviously connected in many different ways.

  • But in other contexts they work antagonistically, to the

  • point where when an individual is faced with very strong

  • emotional response that will actually physiologically

  • restrict the flow of blood to the neocortex.

  • I illustrate this with my students by asking them to

  • think back to periods in their lives when they were dating,

  • and they were trying to meet very attractive partners, that

  • ultimately they concocted a relatively staged kind of a

  • scenario in which to talk with them for the very first time

  • and ask them out on a date.

  • And when that accidental meeting arrives, you would

  • think that they'd be able to charm this other individual

  • into going out on a date with them.

  • But more often than not, when the moment occurs, we end up

  • becoming tongue tied, hopelessly and embarrassingly

  • inarticulate, and unable to impress this individual.

  • Why does that happen?

  • Well, it happens because strong emotional stimulus---

  • which includes sexual attraction---

  • can actually reduce the flow of blood to your neocortex.

  • It makes it harder for you to use that part of your brain.

  • For all intents and purposes, love makes you stupid!

  • And that's an example of a constraint, a biological

  • constraint, that has some very reasonable evolutionary

  • underpinnings.

  • Obviously, when you are getting chased by a

  • saber-toothed tiger, it's more important for you be scared

  • and run like heck than for you to be able to solve

  • differential equations, even if you're at MIT!

  • And as a result, these kinds of neurophysiological

  • constraints have a very strong implication

  • for financial markets.

  • When we are subjected to strong emotional stimulus, we

  • will react in predictable ways.

  • We will have difficulty in using the logical faculties

  • that, for the most part, we're able to make use

  • of for other decisions.

  • But under extraordinary circumstances, those mental

  • faculties are not available to us.

  • And this has to do with another basic evolutionary

  • principle about diversity.

  • Typically, when we think about markets in general--

  • the journalist, James Surowiecki, wrote a book

  • describing them as the wisdom of crowds, the idea that when

  • you have a crowd, and if the crowd is relatively

  • independent in its thinking and evaluations, then by

  • pooling the collective evaluations of this crowd, you

  • get some very, very wise decisions.

  • For the most part, financial markets, and most economic

  • markets work in that manner.

  • Two things can violate this principle of

  • the wisdom of crowds.

  • One is if you don't have a crowd: small number of

  • individuals.

  • But second and most importantly, if the crowd is

  • not independent, if they all think alike, if we all think

  • exactly the same way we don't get the wisdom of crowds.

  • We get the madness of mobs.

  • And the distinction between the two is really one of

  • diversity---

  • diversity of thought.

  • If we are all thinking exactly the same thoughts, if we all

  • want to get out of a crowded theater because of a fire, we

  • know that the exits are going to be a real constraint.

  • That's going to create problems.

  • If we are all thinking alike, and we want to get out of the

  • stock market at the same time, that's going to create a stock

  • market crash.

  • And so the key to understanding periods of

  • financial market dislocation and so-called irrationality--

  • and that's a very loaded term.

  • It's not at all clear that it's irrational to get out of

  • a crowded theater if you smell smoke--

  • the fact is that those periods, when we all think

  • alike, when we don't have the wisdom of crowds, but we have

  • the madness of mobs, we react very differently.

  • And economic theory, the way it has been developed, really

  • goes out the window.

  • We need to develop a better theory that takes into account

  • these periods of coordination and correlation, and I think

  • that that can be done through understanding a bit more of

  • the neurophysiology of decision making and then some

  • of the evolutionary dynamics of diversity.

  • This is one of the reasons why biodiversity is such an

  • important part of the environmental movement.

  • It's because having a diverse set of species will allow you

  • to be much more resilient in changes to the environment.

  • That same principle, literally--- the same

  • principle---

  • applies to thought.

  • By having a diverse group of individuals, diverse in their

  • thinking, we are much more likely to survive changes in

  • our economic environment and be able to move on in a

  • somewhat more rational manner.

  • But without it, without that kind of diversity, we are

  • risking the same kind of punctuated equilibrium that we

  • see in evolutionary biology.

  • INTERVIEWER: You mentioned a couple of minutes ago that

  • love can make you stupid.

  • Is the idea that money can make you stupid too?

  • LO: In a different way, yes, that's right!

  • So again, neuroscientists have done experiments where they've

  • imaged to individuals' brains while they receive certain

  • kinds of monetary reward.

  • They play certain games where they win small cash prizes.

  • And what they've identified is that the neural mechanisms for

  • financial gain are very much the same as

  • for drugs like cocaine.

  • Your brain is stimulated to releasing dopamine into the

  • nucleus accumbens, the pleasure center of the brain.

  • Certainly not as much, and not as intensely, as when you are

  • on a drug like cocaine, but nonetheless, the mechanisms

  • are actually one and the same

  • and so it's easy to see how, over periods of great

  • prosperity, during bull markets, people can get

  • addicted to that kind of an experience.

  • The more money you make, the more money you want.

  • You would think that after earning $10, $20, $30 million

  • that should be enough.

  • But in fact, it has nothing to do with the amount.

  • It has to do with the experience and the kind of

  • pleasure it generates in the brain.

  • And so all of these elements actually come to play in

  • developing ideas about how economic decisions get made.

  • It's not just pure mathematical deliberation that

  • will guide individuals in their decision making; it's a

  • much more complex amalgam of different decision making

  • components.

  • And by understanding how the components work together--

  • sometimes in tandem, sometimes antagonistically--

  • we have a better chance of coming up with a more

  • realistic theory of financial market dynamics.

  • INTERVIEWER: I was very interested in preparing for

  • this interview, also, to read some of the things that you've

  • written about risk and uncertainty and how that

  • drives human behavior, or how human behavior changes in

  • those circumstances.

  • Can you talk about that a bit?

  • LO: Sure.

  • First of all, let me explain that by most dictionaries and

  • thesauruses, risk and uncertainty

  • are considered synonyms.

  • But in fact, from the economist's point of view,

  • Frank Knight--- the University of Chicago economist---

  • distinguished the two by calling risk the kind of

  • randomness that one can parameterize, for example,

  • mortality tables for life insurance or the odds of

  • winning in a lottery.

  • What he called uncertainty was the kind of randomness that

  • you actually couldn't put numbers on, that

  • you couldn't quantify.

  • And he argued originally that uncertainty really explained

  • why it was that certain entrepreneurs, like Bill Gates

  • would become multibillionaires, whereas

  • others who don't take that kind of bet, actually, only

  • end up earning normal economic profits, nothing nearly as

  • outsized and grandiose.

  • But there's a very important emotional underpinning to this

  • distinction that Knight really didn't focus on, but now, with

  • the benefit of decades of research in the cognitive

  • neurosciences, we understand much better and that really

  • has to do with fear.

  • The fact is that the most potent form of fear is the

  • fear of the unknown and so if we can't put a statistical

  • probability on certain events, if we can't quantify them in

  • some manner, then we are actually not dealing with

  • well-defined randomness, namely risk.

  • We're dealing with completely unknown kinds of outcomes and

  • so as a result, people tend to be much more averse to

  • uncertainty than they are to risk.

  • The case in point is the recent experience that we've

  • seen in the stock market.

  • Clearly, people are happy to take on the riskiness of the

  • stock market because, for many years, the stock market has

  • done just fine with a certain level of volatility and a

  • certain level of expected return.

  • But over the last five years, the stock market has been

  • extraordinarily erratic.

  • And erratic particularly in terms of its level of

  • volatility, because during the fourth quarter of 2008, when

  • Lehman Brothers went under, the volatility of the US stock

  • market hit a spike of something like 60 percent per

  • year, and on an intradaily basis even higher.

  • At that level of volatility, most investors would say, cash

  • me out, I really don't want to be part of this anymore!

  • And the fact is that the volatility of volatility in

  • the US stock market has been tremendous over the last few

  • years to the point where we're seeing a lot of individual

  • investors having taken most of their life savings out of the

  • stock market and putting them into cash, which is ultimately

  • not a very successful way to plan for their retirement.

  • But that's an example of the fear of the unknown.

  • If you don't know what the rules are, if you don't know

  • whether the house is going to confiscate all of your

  • earnings at any point in time, then your simple decision will

  • be not to play.

  • And I think we're seeing that played out now on a much

  • bigger stage over the course of the last few years.

  • INTERVIEWER: So obviously here, nearing the end of 2011,

  • these kinds of conversations are not just academic.

  • We witnessed the financial meltdown in 2008.

  • We're now seeing a really significant

  • crisis brewing in Europe.

  • Talk about these kinds of massive crises that sweep

  • through the markets, through the sort of global financial

  • structure, in terms of some of these things that we've been

  • talking about.

  • LO: Well, I think that's part of a much larger theme that

  • one can only really see from the perspective of

  • evolutionary biology, and that is that I think crises of all

  • sorts are the manifestation of the combination of

  • technological advances and human behavior.

  • In particular, over the course of the last 12,000 years, the

  • human population has grown really dramatically.

  • If you take a look at typical estimates of population during

  • that time period, and you plot it on a graph, you see that

  • the prototypical hockey stick exponential growth applies

  • perfectly to the population of humans.

  • The way that we've been able to reproduce so successfully

  • in an otherwise hostile environment is through

  • technology---

  • through the collective intelligence that we've been

  • able to develop over hundreds of thousands of years of

  • evolution to tame our technology to

  • our physical needs.

  • And those technologies--

  • whether they're agricultural, or information technologies,

  • or manufacturing technologies, or financial technologies--

  • they often have unintended consequences.

  • For example, DDT was a tremendous technological

  • advance for agriculture, but it led to birth defects.

  • Automobiles were a wonderful invention, but

  • they led to air pollution.

  • And of course, industrial activity now seems to be

  • responsible for climate change, global warming.

  • And I would argue financial technologies--

  • things like securitization, insurance contracts,

  • derivatives--

  • are wonderful inventions, wonderful advances in

  • technologies that also can lead to unintended

  • consequences.

  • And these unintended consequences really are the

  • result of the fact that the technologies provide us with

  • much greater power in certain domains.

  • But the greater power oftentimes is not controlled

  • properly because human behavior has not changed that

  • much in the last 60,000 years.

  • We are still very much wired the same way we were back at

  • the time when we first became fully sentient, and our

  • neocortexes developed into what they are today.

  • And as a result, the fact that we're dealing with, in many

  • cases, relatively ancient, hard-wired brains, but we're

  • dealing with technologies that allow us to do things that we

  • were never intended to do in our original environment, has

  • led to some challenges.

  • Those challenges can be dealt with.

  • But the way that we're going to deal with them is by

  • developing smarter technologies, more advanced

  • technologies.

  • Humans may not have been meant to fly the way that we fly

  • now, but air traffic control and safety measures allow us

  • to do so relatively safely today.

  • And I think that we are now at a stage where financial

  • technologies have become so advanced that we can now do

  • things that we were never able to do.

  • We need to develop the safety mechanisms to prevent us from

  • doing the things that we ought not to do with those powerful

  • technologies.

  • INTERVIEWER: Are you saying that it's a bit-- and I don't

  • know if this analogy captures it, but--

  • sort of this idea that we all crave things like sugar, salt,

  • saturated fats, that we've evolved to crave.

  • And they end up killing us, because they're

  • no longer so scarce.

  • And we just take too much of them.

  • LO: Exactly!

  • So for example, certainly sugar was present in the diets

  • of humans 60,000 years ago.

  • But they were few and far between.

  • Occasionally, you would run into a fruit tree.

  • And you would have a pear or an apple.

  • And that was enormously attractive,

  • but it came on occasion.

  • That's very different from being able to eat deep fried

  • Twinkies every other day, which I don't believe we were

  • adapted to do.

  • Now maybe if we keep doing that, over the course of the

  • next 50,000 or 100,000 years, we will have the ability to

  • process that kind of a sugar intake.

  • But our current biologies are not wired to engage in these

  • kinds of activities.

  • And a good case in point is the internet.

  • The internet is really a relatively new invention, just

  • a matter of a couple of decades.

  • And if you think about what we can do now on the internet--

  • well, for one thing, at this point in time we are able,

  • with a click of a mouse, to wipe away half of our

  • retirement investment in a bad investment decision.

  • That has never been possible in the history of financial

  • markets; it is possible today.

  • And so if you think about the power that individuals have to

  • do good and to do harm, they're both magnified by

  • technology.

  • And so we need to develop the guardrails, the safety

  • mechanisms that will prevent us from doing the kind of

  • damage that we are now able to do with the very advanced

  • technologies that we have at our disposal.

  • INTERVIEWER: So let's talk a bit about those guardrails,

  • because I'm very interested in asking you about the

  • relationship between these kinds of theories, this kind

  • of thinking, and policy making, and prescribing

  • solutions for some of these intractable problems.

  • What do you see as your role?

  • And how do we go about doing it?

  • LO: I have to admit that for much of my early academic

  • career I wasn't interested in policy at all.

  • In fact, I was much more focused on the dynamics of

  • private markets, and really never even thought about what

  • was going on in the public arena, simply because my

  • presumption was that policy was being formulated by the

  • experts in policy making, and that the challenges, the

  • intellectual challenges, were really in trying to understand

  • the dynamics of private markets.

  • It didn't occur to me until relatively recently that there

  • are challenges in the policy arena that are at least as

  • great and if not greater in terms of affecting a much

  • larger group of individuals.

  • And so over the course of the last 10 years, I've spent more

  • time thinking about the interplay between policy and

  • private activity.

  • The first thought that I've been spending time on is

  • really the underpinnings of policy making to begin with.

  • Economists and policy makers formulated a number of policy

  • prescriptions with the implicit assumption that

  • individuals, and therefore institutions,

  • are rational actors.

  • The efficient markets hypothesis or rational

  • expectations have been applied to macroprudential regulation

  • as well as to financial markets.

  • And the first observation that I think needs to be made is

  • that the same limitations that we found to the kind of

  • investment theories that private financial markets

  • exhibit really have to be applied to more

  • general policy settings.

  • In other words, the kind of madness of mobs that we see in

  • financial markets have to be applied much more broadly to

  • economic settings in formulating policy.

  • And there are a number of policymakers now that do have

  • that perspective, but not nearly enough.

  • And certainly not enough to really affect yet the

  • direction of policy.

  • I think that's the first insight, to begin with.

  • And from that point on, all other policy implications will

  • follow very readily.

  • And changes in policy, more importantly, will be suggested

  • by this kind of a different perspective.

  • If we look at markets not as static, stable, physical

  • systems that have underlying laws that are immutable, but

  • are actually biological institutions that can evolve

  • over time and as a function of market conditions, I think

  • we're much more likely to formulate policy prescriptions

  • that are themselves adaptive and much more likely to

  • succeed in a variety of different environmental

  • conditions.

  • INTERVIEWER: It's obviously a very hot political issue right

  • now, just what exactly the role of governments

  • are in all of this.

  • What's your view on that?

  • LO: In my view, government is, itself, an evolutionary

  • adaptation.

  • Without a doubt, the institution of government is

  • critical for resolving a number of challenges that we

  • face as a society because markets cannot work perfectly

  • by themselves.

  • They do break down from time to time.

  • And actually, implicitly, I think we

  • already recognize that.

  • For example, in this studio, there are a number of laws

  • governing the fact that there have to be sprinkler systems,

  • there have to be well-lit exit signs, the fact that there

  • have to be certain protections for all of

  • us, in case of fire.

  • Why do we institute such expensive features of this

  • particular setting?

  • It's because we recognize that we can't leave it to the

  • discretion of the builders of any institution to put these

  • in place, because, left to the choice of a real estate

  • developer, they will almost never choose the more

  • expensive option if they can avoid it.

  • The probability of fire seems relatively low.

  • And if you allow people to choose whether they want to

  • build a building with fire protection versus another

  • building without, they will choose the cheaper

  • alternative, unless there's an absolute demand for the more

  • expensive one.

  • And for most days, there isn't an absolute demand.

  • That absolute demand occurs right about

  • when there's a fire.

  • Of course, by that time it's a little late.

  • We know this about ourselves.

  • We know human nature.

  • We know that we will not gladly pay a higher rent for a

  • facility that has fire protection if

  • we are given a choice.

  • And so after a number of very severe fires with many, many

  • casualties, we as a society decided to institute a law by

  • government that says that all buildings have to have fire

  • protection if they have a particular

  • function to the public.

  • And so this is an example of how laws and how government

  • takes into account human frailties in a

  • very explicit way.

  • Well, if we understand this about something as basic as

  • fire protection, it has now come time to make that same

  • leap of understanding for all sorts of contexts, including

  • financial ones.

  • We now have to build in financial protections that

  • prevent us from doing the things that we know we're

  • going to want to do, particularly after extended

  • periods of prosperity.

  • After many, many decades of the economy growing rapidly

  • and financial markets generating lots of value added

  • for all the market stakeholders, at some point,

  • we're going to say to ourselves, you know what, we

  • don't really need as many protections as

  • we had in the past.

  • It's time for us to perhaps loosen up some of these

  • protections that have been reducing the growth rate of

  • our economy.

  • We don't need seat belts anymore.

  • We don't need leverage restrictions anymore.

  • We don't have to have constraints.

  • That's a natural reaction from decades of no car accidents or

  • no big financial meltdowns.

  • And that kind of human tendency is something that we

  • have to recognize.

  • We do recognize it in limited context, like fire protection.

  • We don't yet recognize it in economic settings.

  • INTERVIEWER: Libertarians see all of this, of course, in

  • terms of maximizing individual freedom, as opposed to

  • restricting or regulating that freedom.

  • What's your thinking or your response to that kind of

  • approach, which seems to be very, very different?

  • LO: Well, in fact, I would say that individual freedoms are

  • absolutely critical.

  • And one of the unique aspects of Homo sapiens is the fact

  • that we can actually choose how we wish to live our lives.

  • And I think that that's an absolutely fundamental aspect

  • of human society.

  • There are very few societies that are so regimented across

  • the board that will actually last--

  • even totalitarian regimes will ultimately fall, because

  • humans want to be free.

  • However, freedom doesn't necessarily mean that any

  • action and activity should be permitted; because of a very

  • important aspect of human society, which is what

  • economists call externalities.

  • If my activities have negative consequences for you and your

  • family, then we have a problem.

  • We have a challenge that we have to resolve.

  • And so because of the success of population growth, we are

  • now at a point where a number of activities that we have

  • previously engaged in have externalities,

  • or spillover effects.

  • When the economy is relatively small the kind of spillover

  • effects that we're talking about today are really remote.

  • But when the economy gets big enough, when human society

  • gets to where we are today-- seven billion people, as of

  • the end of this year--

  • these externalities become much more significant.

  • So we have to balance the human drive for libertarianism

  • with the acknowledgement that individual actions very often

  • have much broader consequences.

  • And ultimately, that's really the political process.

  • That's what we really rely on politicians to resolve.

  • They haven't been doing such a great job lately.

  • But eventually, they will and they must be able to come to

  • terms with these very difficult decisions.

  • And ultimately, by understanding the dynamics,

  • the spillovers, the externalities, we actually

  • have a better chance of creating a much more palatable

  • solution for all stakeholders involved.

  • INTERVIEWER: I also wanted to ask you about financial

  • education for, I guess, what I'll call the layperson.

  • I am a relatively unsophisticated investor.

  • How much education should a person who's not a business

  • person, not particularly interested, frankly, in those

  • kinds of issues have?

  • And what is the role of making people more sophisticated and

  • more aware of these things?

  • LO: I have to confess that to someone with a hammer

  • everything looks like a nail.

  • So if you're going to ask an academic how much education

  • they should have, the answer is, lots and lots.

  • But I think that this is actually part of a much

  • broader trend that we see across all aspects of our

  • existence today.

  • Life has gotten more complicated in many ways.

  • It's obviously also gotten simpler in yet other ways.

  • But the fact is that, with various advances in the

  • sciences, we now know a lot more about all aspects of our

  • day- to- day existence.

  • And therefore, we can make more informed choices.

  • Take for example, diet.

  • In the 1950s, the advice that most people received from

  • their parents was eat to your heart's content.

  • There was no discussion of cholesterol, or carbohydrates,

  • or various kinds of health issues that we now understand

  • to be quite significant and that we can do quite a bit

  • about by watching our diets.

  • And so the advances that the medical sciences have offered

  • have, in many cases, made our lives simpler.

  • We now can take a flu shot and be assured that there will be

  • relatively minor consequences of a bad flu season.

  • But it has also made our lives much more complex in that now

  • you have to decide how much fiber you're going to have,

  • how much protein, how much carbohydrates and are you

  • taking enough vitamins and minerals each day?

  • So we have each had to become a little bit

  • more expert in diet.

  • By that same token, I believe that we have been given

  • tremendous opportunities to engage in a variety of

  • different investment activities that would have

  • been impossible to us even 10 years ago.

  • Now you can buy an ETF that invests in many different

  • countries, whereas in the past, you would have had to go

  • to various different brokers to engage in those kinds of

  • transactions.

  • So in that respect, our financial

  • lives have gotten simpler.

  • We have had more access to investment opportunities.

  • But those additional opportunities mean that we

  • have more complex decisions that we have to make.

  • So I think that in the short run investors really should

  • spend a lot more time thinking about their investment

  • portfolios.

  • Typically, an investor will think about their portfolio

  • maybe four times a year, once a quarter, certainly once a

  • year when they have to do their taxes.

  • But if you think about that level of attention to your

  • financial health, that's actually a pretty limited

  • amount of time that you spend compared to how much time you

  • spend on your physical health.

  • You have a check-up of annually, but you'll have

  • other visits that involve various different specialties.

  • So we spend more time now thinking about our physical

  • health than we do before, because we know more.

  • By that same token, we need to spend more time thinking about

  • our financial health than we have before.

  • I believe that over time as economists, particularly

  • financial economists, make greater strides in taking into

  • account human frailties in various different financial

  • products, eventually we'll be able to

  • develop smarter products.

  • In the same way that an iPhone almost eerily knows what you

  • want to do when you want to do it and makes it simple for you

  • to do, we need an investment- kind of an iPhone device that

  • will allow us to reach our ultimate financial goals

  • without having to spend too much time thinking about it.

  • We're not there yet.

  • And until we get there, we need to spend more time

  • understanding how financial investments work and how they

  • may or may not be consistent with our ultimate goals.

  • INTERVIEWER: I know that teaching is, in fact, a very

  • important part of what you do and a big part of your life.

  • Talk a little bit about that.

  • And also, how do you balance it all?

  • LO: Teaching is important.

  • And I have to say that early on, because of my experiences

  • in third grade with Mrs. Ficalora and throughout, I

  • realized the benefits and tremendous costs of having

  • good and bad teachers.

  • Having an inspiring teacher can open your life to an

  • amazing series of discoveries and pleasures that would never

  • have been possible.

  • And similarly, a bad teacher could close a mind forever to

  • a subject, which I think is just a crime.

  • I think that teachers are underpaid--

  • particularly at the elementary, middle school, and

  • high school levels--

  • because if we could measure their impact on society, if we

  • could really measure the impact of having a good 11th

  • grade trigonometry teacher on what that individual does 15

  • years from that point on, we would pay these

  • teachers a lot more.

  • We would be a lot more careful about tenure.

  • We would be a lot more focused on developing good teachers at

  • that level because that's where minds are opened and

  • where minds are shut.

  • So to me, teaching is one of the most important activities

  • that we can do because that's the way that we replenish the

  • stock of intellectual capital in our society, the way that

  • we encourage collective intelligence, and frankly, the

  • way that we're going to solve the challenges of society for

  • the next few decades.

  • The future scientists, and engineers, and economists that

  • cure cancer, and fix global warming, and find new sources

  • of energy, they are our students today.

  • And so if we think in those terms, I think we'd take

  • teaching a lot more seriously than we do now.

  • INTERVIEWER: What's it like teaching MIT students?

  • LO: That has just been a real pleasure.

  • One of the constants that drew me and many of my colleagues

  • to MIT is the quality of our students here.

  • And it's really noticeable.

  • I really view teaching our students here as a privilege,

  • not a burden.

  • We all like teaching students that are good students, that

  • are excited to learn, and that have a certain degree of

  • creativity and energy.

  • Well, MIT students have that tremendously.

  • They are not only creative, but they have this

  • entrepreneurial spirit that really makes them

  • extraordinary students to teach because they don't take

  • concepts for granted.

  • They will take an idea and work out five different

  • implications, and really challenge the teacher to

  • really think about these ideas from a much deeper level.

  • So I have to say that I've learned more from the students

  • here than I think I've taught them because of the challenges

  • that they've thrown out, the creativity that they bring to

  • the process, and ultimately the energy that

  • they have for learning.

  • Our students are absolutely hungry for knowledge.

  • And they drink it up at an amazing rate.

  • So it's really a tremendous environment for faculty.

  • INTERVIEWER: Speaking of entrepreneurial spirit, I also

  • wanted to shift gears a little bit and ask you about some of

  • your forays into that world.

  • Talk about that a bit.

  • And why has it been important for to do it?

  • LO: As I mentioned, when I started in economics my

  • interest was very much on the applied side.

  • I love seeing ideas put to work.

  • And one of the fascinating things about Isaac Asimov and

  • the Foundation series was that some very abstract mathematics

  • was applied to some very practical situations.

  • And so from the very beginning, my interest was in

  • seeing ideas implemented.

  • And so during the period where I was studying the dynamics of

  • financial markets, the random walk hypothesis, it nagged me

  • to no end that here we were teaching our students that

  • markets are efficient, it's impossible to beat the market,

  • you should focus on risk and reward, and I had actually

  • never taken any of these ideas that I had

  • developed into practice.

  • I had never tried to see how it is that these investment

  • ideas did or did not work in actual settings.

  • And so in 1999, I decided to start my

  • own investment company.

  • I took a two- year leave of absence from MIT, and worked

  • with some of my former students and consulting

  • colleagues, and created a company to try to undertake

  • some of these ideas from a more practical setting.

  • And over time, I've learned an enormous amount about how

  • markets really work from trying to use these ideas in

  • practice, and seeing how they succeed and fail over various

  • different kinds of market environments.

  • INTERVIEWER: Maybe just to follow up, what kinds of

  • things have you learned?

  • I can imagine that that might seem like an obvious question.

  • LO: Well, there are few things that I think I discovered

  • quite to my surprise.

  • One is that it's very painful to lose money.

  • But it's a lot more painful to lose other people's money than

  • to lose your own.

  • That aspect of human nature, I think, is something that we

  • don't really spend enough time talking about in our

  • investment classes.

  • I do now.

  • But before I engaged in this activity I didn't realize just

  • how important that emotional aspect is, and why it's so

  • important for investors to engage in third party

  • financial advisors.

  • In a way, it's much like the medical practice of never

  • allowing a doctor to operate on his or her own family

  • members, because you're too emotionally invested.

  • And in many respects, managing your own wealth can be a very

  • challenging activity, unless you are trained to think

  • somewhat more remotely, somewhat more objectively

  • about these kinds of decisions.

  • Managing other people's wealth has that very

  • same feature to it.

  • You don't want to disappoint others.

  • You don't want to engage in practices that are too risky.

  • But at the same time, you are stewards of their wealth.

  • And so they're expecting you to be able to make good

  • investment decisions.

  • So the processes by which you can provide that type of

  • stewardship and the emotional toll that that can take on an

  • individual is something that I learned about firsthand.

  • And I found it very valuable.

  • And ultimately I think it's reflected in the research that

  • I've done and what I teach my students now about how they

  • might engage in these kinds of activities somewhat more

  • productively and with somewhat more preparation for the kind

  • of challenges.

  • INTERVIEWER: Thinking a bit more about MIT, as we sort of

  • start to wind down, the MIT economics, finance

  • departments--

  • it's obviously a legendary a group of people.

  • We've touched on some of your colleagues

  • over the last 20 years.

  • Who are some of the other luminaries that you would like

  • to talk about?

  • And are there any really interesting stories that we

  • could gather?

  • LO: There are so many.

  • One of the things about MIT that I love-- but it's also

  • something that one has to get used to--

  • is that there are so many superstars that are here that

  • nobody really feels like they need to be catered to or

  • treated any differently.

  • This kind of an egalitarian ethic is actually very

  • different and unique, I believe, to MIT.

  • I have been a student at Harvard, a student at Yale, a

  • faculty member at Wharton.

  • I have visited most of the major business schools and

  • economics departments over the last few decades giving talks.

  • And I have to say that MIT is really unusual in the ethic

  • that has developed over the years, particularly in the

  • economics department and in the Sloan School.

  • And the ethic is really that we are all part of the same

  • college of ideas

  • and you're judged by the clarity of thought and the

  • creativity of your research.

  • It's really that kind of motivation that keeps us

  • young, and it keeps us thinking.

  • And there's very little in the way of formalism that we

  • engage in so we interact in a very open

  • and collegial manner.

  • That's one of the things that I value most about MIT.

  • In that setting, I have to say that there are a number of

  • individuals that I've learned a great deal from in a variety

  • of different departments.

  • One of the things that I discovered early on was that

  • MIT is really like, for me, the world's biggest candy

  • factory in that there are so many different interesting

  • things going on in different departments.

  • In particular, in addition to the Sloan School and the

  • finance group, I've interacted with individuals in the

  • economics department, with the brain and cognitive sciences

  • department, with electrical engineering, and computer

  • science, with the AI Lab, years ago when it was called

  • the AI Lab, and now the CSAIL, the computer science and AI

  • Lab together.

  • All of these individuals, I think, have really contributed

  • to a better understanding of human behavior from my

  • perspective.

  • So it's hard for me to name any one or two individuals.

  • But certainly in the pantheon of greats, Paul Samuelson, Bob

  • Merton, Franco Modigliani, Patrick Winston, Noam Chomsky,

  • Marvin Minsky, and Tommy Poggio, all of these

  • individuals, I think, I've learned tremendous amounts

  • from over the years.

  • And many more who have contributed to my education.

  • INTERVIEWER: That's quite a list.

  • LO: There are a lot of impressive people here at MIT.

  • INTERVIEWER: So thinking ahead just a little bit, maybe just

  • give us an assessment, as we wind down, on what you feel

  • your impacts might have been as a researcher, as a thinker

  • in finance.

  • And where do you want to take your work?

  • Obviously, the world is full of challenges right now, in

  • particular, in this area.

  • And where do you want to go?

  • LO: In terms of where I've been, let me start with that,

  • and then talk about where I hope to go.

  • The early phase of my career was really focused on applying

  • rigorous concepts of econometrics and statistics to

  • financial models to develop the field of financial

  • econometrics.

  • And I believe that that field is now very

  • healthy and well- developed.

  • And we now understand that it's critical to use the

  • proper methods of inference for understanding the

  • empirical anomalies that we identify in financial

  • circumstances.

  • Those empirical anomalies leave a lot of room for

  • innovation and creativity because they illustrate that

  • the traditional paradigm is simply not satisfactory.

  • There are missing pieces of the puzzle.

  • And over the last 10 years of my career, I focused on trying

  • to fill in those pieces of the puzzle by bringing ideas from

  • evolutionary biology and the neurosciences to provide a

  • deeper and more nuanced

  • understanding for human behavior.

  • Where I think I'd like to go over the course of the next

  • decade or so, if I'm lucky enough to continue being

  • active, is to take those ideas and work out their

  • implications for human behavior writ large.

  • In other words, I'd like to develop a complete theory of

  • human behavior.

  • And by complete, I mean one that

  • applies across all contexts--

  • social, cultural, political, and economic.

  • Because we are not so compartmentalized that on one

  • day you're an economist, on another day you are a

  • psychologist, on another day you're a biologist, in terms

  • of the way you act.

  • We're talking about humans.

  • And human behavior cuts across all of these siloed

  • disciplines.

  • And so what I've been spending time on recently is trying to

  • understand how to integrate all of these different silos

  • in a more complete theory of human behavior to the point

  • where we understand so much about human behavior that we

  • can actually create it artificially.

  • This might seem like a program in artificial intelligence.

  • But in fact, it's much broader than that.

  • I think it was Marvin Minsky who said that he didn't want

  • to create a computer that he could be proud of; he wanted

  • to create a computer that could be proud of him.

  • And I think that that's a very important insight because it

  • says that the notion of behavior is something much

  • deeper than simple actions.

  • We can now automate lots of behaviors.

  • There are wonderful factories that have very few human

  • actors and are extraordinarily efficient.

  • But somehow we don't consider them to be human.

  • And the behaviors, frankly, are very stupid in the sense

  • that they're highly stylized and they are not robust to

  • changing environments.

  • Going forward, what I'd like to be able to do, what I think

  • we now have the wherewithal to do, is to develop a theory of

  • behavior that allows us to replicate human interactions,

  • human decision making in the way that humans

  • actually make them.

  • So the Turing test is a well-known idea, pioneered by

  • Alan Turing, who said, that if at some point by typing

  • messages back and forth with another party, you can't

  • distinguish between the responses you get from that

  • individual and the responses that you get from a human,

  • then that computer is for all intents and purposes

  • intelligent and human.

  • I actually think that that's a relatively low threshold for

  • what we need to achieve.

  • I actually think that a much more relevant test for whether

  • we have achieved an understanding of human

  • behavior is to create a computer that can engage in

  • activities to such an extent that seems to replicate humans

  • that, at some point, if someone were to decide to

  • terminate that machine, a number of us would object on

  • moral and ethical grounds.

  • That, to me, is the ultimate Turing test of human behavior.

  • If we can create behavior that can actually mimic not just

  • the look and feel of human behavior, but actually the

  • mechanisms by which behavior adapts to new settings and can

  • develop its own type of creativity, at that point I

  • think we will have achieved something spectacular.

  • INTERVIEWER: So this has been really wonderful.

  • Is there anything else you'd like to add that we haven't

  • talked about?

  • LO: It's been very complete and wide-ranging.

  • Social responsibility?

  • INTERVIEWER: Sure.

  • We have a few minutes, if you'd like to--

  • LO: The financial industry has obviously undergone a great

  • amount of turmoil over the last few years.

  • And it has received many black eyes at this point in terms of

  • the behavior that we have observed.

  • But I think that we are at the risk now of throwing out the

  • baby with the bath water when we start to engage in

  • regulations that will ultimately hamper financial

  • market development.

  • Because ultimately, while there may have been excesses

  • and even crimes that were committed during the financial

  • crisis, the fact is that financial markets are critical

  • for all aspects of society, and that some of the biggest

  • challenges that we have in front of us--

  • things like cancer or global warming or the energy crisis--

  • ultimately, those are going to be challenges that we will

  • face collectively.

  • And we're only going to be able to overcome them if we

  • can unite in some coordinated fashion.

  • And one of the most important aspects of that kind of unity

  • is to be able to create proper incentives.

  • The financial system is designed to do just that.

  • I believe that to some of the biggest challenges of society

  • can be addressed with the right kind of financial

  • structures, and that they will be virtually impossible to

  • address without them.

  • So we need to have more and smarter individuals involved

  • in the financial sector.

  • We certainly should not relegate that to the

  • financiers because we know what they might do with it,

  • and we know that excesses will occur.

  • Instead, we need to spend more resources studying these

  • issues, becoming much more nuanced in how we construct

  • the appropriate financial structures to be able to

  • support innovation.

  • And I think that if we can do that, if we can find the right

  • structures to create the wisdom of crowds and to

  • support the kind of innovation that we desperately need, we

  • can face virtually any societal challenge

  • successfully with those kind structures.

INTERVIEWER: Today is December 5, 2011.

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