Int. w/ Eugene Fama by Richard Roll 1
INTERVIEW WITH PROF. EUGENE FAMA
BY PROF. RICHARD ROLL
August 15, 2008
(edited for clarity and readability)
RICHARD ROLL:
Good morning. The American Finance
Association is conducting a series of interviews with
founding contributors to the field of finance. I am happy
to say that the founding contributor for today is Professor
Eugene Fama of the University of Chicago. He is probably
the most widely cited finance professor ever. So, I’m going
to ask about your research, of course, but first let's talk
about some personal things, like family background. I know
the name Fama was mentioned in the Iliad. I don’t want to
go back that far, but how about a little background about
your parents and grandparents?
EUGENE FAMA: My grandparents emigrated from Sicily to
Boston around the turn of the 20th century. I think my
grandfather’s family had 13 children. They all moved at the
same time. My grandmother’s family also moved at the same
time, and they had 13 children of their own. [LAUGHTER] So,
within 50 years the Boston phonebook was full of Famas.
Everybody lived in Boston. I think I was the first one in
the family, third generation, to go to college. I went to
Tufts, basically, because they had a good athletic
department.
RICHARD ROLL:
You played high-school football, right?
EUGENE FAMA: Yes. My high-school team won the state
football championship. They came in second in baseball, and
the hockey team, I didn’t play hockey, but the hockey team
won the state championship almost every year.
RICHARD ROLL: Was that Malden Catholic?
Hall of Fame there?
EUGENE FAMA:
Right.
You are in the
Athletic Hall of Fame.
RICHARD ROLL: They have a Hall of Fame at Malden Catholic?
I see. And then at Tufts you played baseball too?
EUGENE FAMA: I got less serious about sports at Tufts
because Sally, my wife, and I were married by the time we
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Int. w/ Eugene Fama by Richard Roll 2
were just turning 20. We had a child by the time I was a
junior, and so sports became less important. Getting on
with my life and education became more important.
RICHARD ROLL:
EUGENE FAMA:
RICHARD ROLL:
You were a French major?
For the first two years.
Then what happened?
EUGENE FAMA: I got bored with Voltaire. Reading the same
stuff over and over again just wasn’t appealing to me. I
had taken an economics course. I loved it, and I was
pretty good at it. The professors were reading my exams to
the class. I thought maybe I should stick to this. It was
much more interesting. Then, when I was graduating I was
trying to go off to business school. I wanted to go for a
PhD, and I really didn’t have much of an intention of
working for a living. I wanted something that would allow
me to continue my sports life. [LAUGHTER]
RICHARD ROLL: You mean you thought PhDs didn’t have to do
any work. [LAUGHTER]
EUGENE FAMA: Right. Or at least they could do it when they
pleased. So I went to my professors and said “where should
I apply?” They were all Harvard graduates, and they said
"Go the University of Chicago. Harvard is not intellectual
enough for you, at least not the business school. So go to
Chicago." There’s a really funny story about Chicago.
RICHARD ROLL:
into Chicago.
Yeah?
Tell us the story about how you got
EUGENE FAMA: So, April comes along. It's the end of April,
and I haven’t heard a word. The school was much smaller
then. I called, and the Dean of Students actually answered
the phone. I said, “I haven’t heard anything about my
application”. He’s fumbling around with the papers. He
said, “We have no record of your application.” I said,
“What, I sent this in months ago”. He said, “Well, what
school did you go to?” I said, “Tufts.” He said, “Pretty
good grades?” I said, “Yeah, pretty much straight A’s.” He
said, “Well we just happen to have a scholarship for
somebody from Tufts. Do you want it?” [LAUGHTER]
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Int. w/ Eugene Fama by Richard Roll 3
That’s how I ended up in Chicago. They wouldn’t let me in
the PhD program right away. So Joel Siegel, who was the
director of the PhD program at that time, said to me at the
beginning of the first quarter, “You know, graduate school
is a lot different from undergraduate school. I said,
“Fine.” So at the end of the quarter I went up to him, and
I said, ”You know, you were right, graduate school is much
easier." The competition was much fiercer at Tufts than it
was at Chicago in the business school in those days. So
they let me into the PhD program at that point.
RICHARD ROLL: That was 1960. You graduated from Tufts,
went immediately to Chicago, and you’ve been at Chicago
ever since. Right? So 1960 to 2008. That's 50 years.
When you try something you don’t give up that easily.
Well, your wife too. You mentioned you married Sally when
you were still in college.
EUGENE FAMA:
ranch.
We just had our 50th anniversary, at your
RICHARD ROLL: Right, in fact you’ve stayed in Chicago
except for visiting a couple of places.
EUGENE FAMA:
A year and a half in Belgium.
RICHARD ROLL: A year and a half in Belgium, and I think
you visited out here a couple times.
EUGENE FAMA:
UCLA in the winters for a while.
RICHARD ROLL: But other than that you’ve been at Chicago.
Is there anyone who has been there longer?
EUGENE FAMA: I think I’m the longest serving in the whole
University. I’m not totally sure of that.
RICHARD ROLL:
anytime soon?
They’re not insisting that you retire
EUGENE FAMA: Well, you’re aware that we are classified as
non-essential workers. So, we can’t be forcibly retired.
RICHARD ROLL:
What about your family, your children?
EUGENE FAMA: We have four children, two adult men, two
adult women, and ten grandchildren.
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Int. w/ Eugene Fama by Richard Roll 4
RICHARD ROLL:
EUGENE FAMA:
Los Angeles.
Ten grandchildren!
Split just about evenly between Chicago and
RICHARD ROLL: That’s very productive. It’s not thirteen.
You said you’re grandparents had thirteen. So the Fama’s
are slowing down a little bit.
EUGENE FAMA:
RICHARD ROLL:
Right.
Well, not that much. [LAUGHTER]
RICHARD ROLL: Let’s talk about your research career. I
think that’s the main reason we’re doing these tapings. We
are getting people to talk about what they’ve contributed.
You have published, I think right around a hundred papers,
mostly in the top journals. In The Journal of Finance, I
think you have something like … I counted them … did you
ever count them?
EUGENE FAMA:
No
RICHARD ROLL: There are twenty in The Journal of Finance.
And there are nineteen in the Journal of Financial
Economics. Those are probably the two top journals in
finance. You’ve got about twelve in the Journal of
Business. Nine in the AER. You’ve got the JPE. And you
have published papers in five decades.
EUGENE FAMA: How about with you in the Journal of American
Statistical Association?
RICHARD ROLL: And the Journal of American Statistical
Association. You’ve got something like thirty-five papers
in other miscellaneous journals like the Journal of
Monetary Economics.
EUGENE FAMA: When I was younger it was much easier to
publish in other fields than it is now. They’ve all become
much more technical. They wouldn’t even look at any of my
self now.
RICHARD ROLL: Well, it’s also true that it’s hard to
publish in finance. Isn’t it? You’ve got a lot more people
competing for the slots.
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Int. w/ Eugene Fama by Richard Roll 5
EUGENE FAMA:
Yeah.
RICHARD ROLL: It doesn’t look as if that has slowed you
down, because if you look at the five decades that you’ve
published papers: the sixties, seventies, eighties,
nineties and two thousand. I actually calculated that you
have been publishing a little more than two and a half
papers per year in every decade. How can you keep doing
that with all this increase in competition? Do you have to
keep getting better and better?
EUGENE FAMA: No. You have to pick up somebody like Ken
French, who is a compulsive worker.
RICHARD ROLL:
French?
How many papers did you published with Ken
EUGENE FAMA: I haven’t counted them, but almost everything
since the late eighties.
RICHARD ROLL: I think it’s about twenty-eight, something
like that. He’s been a good co-author for you.
EUGENE FAMA: Yeah. He has the same work habits that I do.
So we work very well together. We almost never see each
other face to face.
RICHARD ROLL:
What do you mean the same work habits?
EUGENE FAMA: He works seven days a week. I work seven days
a week. He works a full day. I don’t work a full day
anymore. [laughing] I have to go windsurfing or something,
golf in the afternoon. But he works from dawn to dusk
except for a bike-ride in the middle of the day.
RICHARD ROLL: Really, well that explains the fact that I
guess even though you have a lot more people who are trying
to get space in the journals you’ve worked harder and
you’ve gotten him to work. What about some of your other
co-authors like Michael Jensen for instance.
EUGENE FAMA: Jensen and I wrote a couple of papers early
in the nineteen-eighties, and of course, you, he and I have
a very famous paper from the late-sixties.
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Int. w/ Eugene Fama by Richard Roll 6
RICHARD ROLL: But some of the stuff you did with him was
more on agency theory and corporate finance.
EUGENE FAMA: Actually, Mike has one of the most highly
cited papers on agency theory, the Jensen Meckling piece.
My piece in the JPE, without Mike, comes in very high I
think. Which is a shock to me. I never really realized
that until somebody told me it was assigned to lots of
students in economics. Then Mike and I wrote a sequence of
three papers on the theory of organizations, which is
basically agency theory. They have done very well. And I
can tell you, we fought over every word in each of those
three papers. Every word was a three-hour discussion.
RICHARD ROLL: Well that takes a lot of time to fight all
the time, doesn’t it?
EUGENE FAMA:
It does.
RICHARD ROLL: Is that why Ken and you, who go through
fights so much, is that why you are a more productive duo
than most?
EUGENE FAMA: [laughing] Well, the Fama-Jensen papers have
served us very well.
RICHARD ROLL: What about some other people, like Harvey
Babiak, what’s happened with him?
EUGENE FAMA:
RICHARD ROLL:
with him.
Harvey Babiak was a PhD student.
You did a famous paper on dividend policy
EUGENE FAMA: Yeah, dividend policy. Unfortunately he died
shortly after getting his degree. And Jim MacBeth also
died. I have a funny story about Jim MacBeth. I don’t
know if you want me to tell it.
RICHARD ROLL:
MacBeth.
I was going to ask about the paper did with
EUGENE FAMA: Jim MacBeth was a very good PhD student. He
was working for me, and we were working on the Fama-MacBeth
paper. Fischer Black had the office next to mine. Fischer
came in very early in the morning. I came in very early in
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Int. w/ Eugene Fama by Richard Roll 7
the morning, and Jim came in very early in the morning.
Every morning Fischer and I would have a discussion.
Finally after about two weeks Jim MacBeth says to me, “You
know I’m from Kansas, and if people from Kansas talked to
each other that way, some one would end up getting shot. I
said, “This is a good friend of mine, we’re not fighting or
anything, we are just discussing research.” To him it
sounded like we were ready to kill one another.
RICHARD ROLL: We might as well talk about the Fama-Macbeth
paper because that is one of the most widely cited papers,
and it pioneered a technique in finance that was very
unusual at the time.
EUGENE FAMA: I’ll tell you how that came about. Black,
Jensen and Scholes published a paper on testing the CAPM.
And in one of the arguments I had with Fischer, I said,
“You know, Fischer, with that technique where you form
portfolios, all you are doing is running a regression. He
said, “No it’s not that.” I said, “Yes, it is.” “No, it
isn’t.” “Yes, it is.” So, I said. “We are going to write
this paper to show you that is what it does.” The paper
doesn’t really describe it in those terms, but if you read
chapter nine of The Foundations of Finance, it describes it
exactly in those terms. That’s what’s going on. So
basically I wrote The Foundations of Finance in order to
show Fischer in detail that these two techniques were
exactly the same. What the Fama-Macbeth paper does is it
gives you a framework for conducting cross-section tests of
asset pricing models, or anything where you have something
resembling panel data. You can get standard errors that
don’t require you to estimate the covariance matrix of the
residuals. That is very important because the covariance
matrix is typically too big to estimate if you have a cross
section of stock returns, for example. And this technique
produces correct standard errors.
RICHARD ROLL: You mention panel data. I think that at the
time you wrote that paper with MacBeth, nobody had used the
term "panel data".
EUGENE FAMA:
No. And we didn’t either.
RICHARD ROLL: You didn’t use the term, but since then,
it’s been a widely used term in economics. You had a time
series of cross-sections. That used economics as well as
econometrics because the insight about testing the time
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Int. w/ Eugene Fama by Richard Roll 8
series coefficients was that those things were like
portfolio returns. Yours was one of the first papers that
really did that.
EUGENE FAMA:
They are portfolio returns.
RICHARD ROLL: They are portfolio returns, and they should
be independent over time. So you should get a standard
error for that, which is easier to test. That was a major
contribution to the testing of asset-pricing models.
EUGENE FAMA: Well, it’s made its way into cross sectional
regressions of all sorts because of this advantage it has.
RICHARD ROLL: But sometimes the coefficients in the crosssection are not portfolio returns.
EUGENE FAMA:
They don’t have to be.
It doesn’t matter.
RICHARD ROLL: People do it with variances and such. And
that would be exactly the same thing.
EUGENE FAMA: Right. It doesn’t have the same economic
interpretation, but it has the same statistical advantages.
RICHARD ROLL: Let me turn to another line of research.
Your first paper, the very first paper you published, was
called Mandelbrot and the Stable Paretian Hypothesis. That
was, I think, in 63’ or something like that.
EUGENE FAMA:
RICHARD ROLL:
all about?
Maybe earlier. A little before my thesis.
Yeah, before you finished.
What was that
EUGENE FAMA: Well, and this is the period when work on
efficient markets wasn’t called that. Work on stock market
returns was just beginning to take hold. It was more or
less restricted to the University of Chicago and MIT.
Modigliani was at MIT, and Merton Miller was at the
University of Chicago. They were both interested in this.
Harry Roberts was also at the University of Chicago.
RICHARD ROLL:
Harry Roberts, yeah.
EUGENE FAMA: Harry Roberts was very interested in it. He
had written a paper on “random walks” in stock market
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Int. w/ Eugene Fama by Richard Roll 9
prices around that time. So, there was a lot of interest.
Benoit Mandelbrot came and visited for a quarter. He came
periodically thereafter quite a bit. So, I spent a lot of
time with him, and if you look at my thesis, about twothirds of it is on the distribution of stock returns, not
on the time-series behavior.
RICHARD ROLL: Well, you know if you look at his website,
he says you’re his student. [laughing]
EUGENE FAMA: Well, in some sense that’s true. Harry
Roberts and Merton Miller are really important, but I’m
Mandelbrot’s student in the sense that two-thirds of my
thesis was a take-off on his work.
RICHARD ROLL:
So, explain what these distributions are.
EUGENE FAMA: Benoit had spent his life showing that almost
all stochastic variables are fat-tailed. He characterizes
them with this class of stable distributions which we are
all very familiar with. For example the Nile river
overflows way more then you would expect if rain follows a
normal distirbution.
RICHARD ROLL:
EUGENE FAMA:
Or we have market crashes more often.
We have market crashes way more often.
RICHARD ROLL: The crash of 87’ would happen every hundred
and fifty billion years.
EUGENE FAMA: A zillion. Even more than that. A twenty
standard deviation event. That’s almost totally unlikely.
RICHARD ROLL: So fat tails means that these very unusual
things happen much more frequently.
EUGENE FAMA: Right. The pencil leaves the paper more often
than you would ever predict under normal distribution. So
he had a substantial influence. But basically it was Harry
Roberts and Merton Miller at that time.
RICHARD ROLL: Those were the people that encouraged you to
work on your thesis, which was on stock return
distributions?
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Int. w/ Eugene Fama by Richard Roll 10
EUGENE FAMA: Well as I’ve said, we had two children by the
time I came along to writing my thesis my third year at the
school. So economics were pressing from another
perspective, and I wanted to get done. I went to Merton
with five topics that I thought I could pursue. He went
through them and said, “No. No. No. No. Do this one.” That
was the thesis. Basically, he said, “Do the distribution
of stock returns.”
RICHARD ROLL: That turned into a famous piece of work, The
Behavior of Stock Market Prices, which is one of the most
widely cited things in finance.
EUGENE FAMA: But if you look in there, there is no clear
statement of what an efficient market is. It wasn’t in any
of the research at that time.
RICHARD ROLL: Later, but not that much later in the early
seventies, you wrote a review paper. By that time, people
had been talking about efficient markets. You gave a
complete analysis of it in that review paper. So, talk
about now, 2008, what does efficient market mean to you
these days?
EUGENE FAMA:
RICHARD ROLL:
EUGENE FAMA:
information.
What does it mean to me?
Yes. What is an efficient market?
Well, in the extreme form, prices reflect all
That model is almost surely false.
RICHARD ROLL: All information that anybody has you mean?
That’s a strong form.
EUGENE FAMA: That’s really strong. It can’t possibly be
true. No model is ever true, but I think it’s a good
approximation for almost every practical purpose I’ve come
across. So I think it was and is a good approximation to
the way prices actually behave.
RICHARD ROLL: Well, for instance, one of the early things
about efficient markets was that Harry Roberts had this
idea that it applies to technical trading rules, those kind
of things, mechanical and costless things. That’s probably
still true, don’t you think, essentially? Are there
exceptions to that?
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Int. w/ Eugene Fama by Richard Roll 11
EUGENE FAMA: What the seventies review paper that I wrote
said was that you couldn’t test market efficiency without
combining it with some hypothesis about what the market is
trying to do. You needed a model of market equilibrium. So
basically you need an asset-pricing model. Then you can
test market efficiency. The reverse is also true. You
can’t test most asset pricing models without testing market
efficiency. There’s always this joint-hypothesis problem,
both in tests of market efficiency and in tests of asset
pricing models. I forgot what the question is.
RICHARD ROLL:
Well, we were talking about technical …
EUGENE FAMA: Technical trading rules. You see, that
doesn’t work anymore because, for example, there’s lots of
work on the predictability of returns. And predictability
of returns isn’t ruled out by market efficiency. Once you
take into account that the expected return is just a price.
The price can vary through time, and it can vary in
predictable ways. All you are looking at is the evolution.
RICHARD ROLL: That’s the evolution of expected returns. Or
maybe the evolution of risk premiums. However, the
deviations about it …
EUGENE FAMA: The deviations about that have to be random.
That’s the definition of efficiency.
RICHARD ROLL: Yes. But would a long-term investor make
extra return if he takes advantage of these time varying
expected returns?
EUGENE FAMA: No, he wouldn’t be able to. In fact, Ken and
I wrote lots of the papers, and I wrote some before I
started working with Ken, on predictability. And I’m really
skeptical of that literature. Enough stuff has come since
then that says there are funny statistical problems
involved in these tests, and that the evidence of
predictability is not that solid. What that says to me in
practical terms is the standard errors are too big. You
are not going to be able to take advantage of it.
RICHARD ROLL: That makes me think back about the stable
distributions too, because you said that Mandlebrot had
this idea that these were a particular class of
distributions. The alternative is that you have non
stationary mixtures which produce these fat tails. One type
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of non stationarity would be changes in means. That won’t
produce fat tails, but variances could do that.
EUGENE FAMA:
Variances could do that easily.
RICHARD ROLL: But those are more predictable probably.
Don’t you think?
EUGENE FAMA:
RICHARD ROLL:
stuff, right?
EUGENE FAMA:
predictable.
I don’t know.
Well, there’s ARCH and GARCH and all that
That stuff says that volatility is more
RICHARD ROLL: But, it’s time varying. So when you
unconditionally mix those things together…
EUGENE FAMA:
RICHARD ROLL:
They can become fat-tailed.
Do you think Mandlebrot is right.
EUGENE FAMA: Jim Press wrote a statistics text book. He
also wrote a couple of papers back in the seventies, I
think, back when he was at the University of Chicago. He
showed that you could generate Mandlebrot’s stable
distributions as mixtures of normals with changing
variances.
RICHARD ROLL:
So that’s a hypothesis.
Which is right?
EUGENE FAMA: Oh empirically, they’re indistinguishable.
Press said you could get the stable class.
RICHARD ROLL:
stable?
Can you test whether it is a mixture or
EUGENE FAMA: No. Well, maybe you could, but you’d have to
have a specific model about the mixture.
RICHARD ROLL: Let’s go to dividends. You mentioned Babiak
and your paper on dividends. First, tell us what that was
about. Secondly, let’s scroll forward to disappearing
dividends and talk about what that’s about. That’s another
paper, by the way, with Ken French, so tell us about that.
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EUGENE FAMA: Harvey Babiak and I wrote this paper back in
the seventies. I forget the exact title. We basically
looked at dividend policies of individual firms. John
Lintner had written his thesis on dividend policy, but all
he had was aggregate data. Compustat came along in the
early seventies. So Harvey and I tested Lintner’s model on
individual companies, and we estimated speed of adjustment
coefficients.
RICHARD ROLL: Lintner’s model was that companies are slow
to change their dividends?
EUGENE FAMA: In Lintner’s model, companies are slow to
change their dividends. They have a target dividend, which
is just a fraction of earnings, but they only adjust
partially to the target. So it was a partial adjustment
model. The statistical issue was to estimate the pay out
ratio.
RICHARD ROLL: Why do companies do that? Are they choosing
that policy for some signaling reason? It reminds me of
another paper.
EUGENE FAMA: [laughing] Right, Fischer’s paper. Why do
firms pay dividends? The answer is three words. I don’t
know.
RICHARD ROLL: Well, there is this idea that firms use
changes in dividends to signal what they think the future
prospects are going to be.
EUGENE FAMA: And people have tried to test that, with
little success.
RICHARD ROLL: Is it true your paper with Ken about
disappearing dividends seems to go back to Fischer’s thing,
in the sense that now firms seem to be cutting dividends
and buying up shares.
EUGENE FAMA: In 1978, so this is five years after we have
CRSP data on NYSE, AMEX and NASDAQ, you get the full
sample. In 1978 I think around eighty percent of companies
on those three exchanges were paying dividends. By 2000 the
number had fallen to something a little less than twenty
percent. I think it might have come back a little bit since
then, but I’m not sure.
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RICHARD ROLL: Those companies are still paying out cash,
they’re just using share repurchases.
EUGENE FAMA: There is lots of work on repurchases.
think much of it overstates repurchases.
RICHARD ROLL:
I
It overstates the extent of repurchases?
EUGENE FAMA: Yeah, because companies do a lot of
repurchasing. They buy the stock back. Then it goes
immediately into employee benefit plans, and things like
that. If you try to net it out, it is much less important
than if you look at gross repurchases, where it looks like
everybody’s doing massive amounts. It turns out that most
of the repurchasing is done by the same companies that pay
dividends.
RICHARD ROLL: So the net of this sounds like companies are
just retaining a lot more cash?
EUGENE FAMA:
RICHARD ROLL:
EUGENE FAMA:
Yes. They are retaining a lot more cash.
And why is that?
I have no idea.
RICHARD ROLL: No idea? Do they have better investment
opportunities?
EUGENE FAMA: It’s a good research question, because I
don’t think this phenomenon is observed in other countries.
I have always said I wish you could measure tax effects
some way. I don’t think it’s very easy to measure tax
effects, but here’s a case where you’ll observe that most
countries don’t have double taxation of dividends. The US
does, and dividends have slowly disappeared, whereas they
haven’t in other countries. I think that is important from
a corporate governance perspective.
RICHARD ROLL: Yeah, because they’re accumulating more
cash, and they are spending it. Maybe not so wisely in some
cases.
EUGENE FAMA:
[LAUGHING] Right.
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RICHARD ROLL: One of my favorite papers that you wrote was
on inflation and short-term interest rates as predictors of
inflation.
EUGENE FAMA:
it.
That does have a funny story associated with
RICHARD ROLL: Just to tell the audience about it, at the
time you wrote the paper, there had been a lot of tests of
the Fischer equation relation between inflation and
interest rates, but they had all done stuff like build
models of inflation and use those inflation rates to
predict short-term interest rates. Basically you turned it
around. Tell us how you got that idea.
EUGENE FAMA: This is when personal computers were first
coming out. Bob Graves sent me one. He figured I was a big
mainframe user, and I was poo-pooing this latest box that
had come around. So he sent me one, and it wasn’t good for
anything. I don’t know how many memory locations it had.
So I said, well maybe I’ll just take these two time series
and see how they’re related. The idea was, and I don’t
know how people had missed it, was if you’re looking for
the effect of expected inflation on interest rates, you
want to put the x-post variable on the left, and you want
to put the forecasting variable on the right. Until then
people had run it the other way. They basically didn’t
realize that with a regression you are estimating a
conditional expected value. Conditional expected value on
the left-hand side is a function of the right-hand side
variable. That made it natural to put the interest rate on
the right rather than on the left.
RICHARD ROLL:
there too.
But you had an efficient market idea in
EUGENE FAMA: Well, yeah, the efficient market idea is that
interest rates should incorporate the best possible
forecast of inflation. That is basically all they have to
do plus the expected real rate of return.
RICHARD ROLL: Well, I think that is an important insight
because the way you run that equation, first of all you
know you should put the expectation on the right, secondly
you know that there shouldn’t be anything else on the
right-hand side, if you have the right expected inflation
on it. But you tested that.
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EUGENE FAMA: Right, the test works in those data, which I
call the golden age of the Fischer effect because it’s the
only period in time where the expected real short-term rate
didn’t vary very much. Before that, the short rate was
basically zero from the late thirties to the early fifties,
and after that, the tests I did in that paper-work don’t
work.
RICHARD ROLL:
They don’t give you a coefficient of one?
EUGENE FAMA: No. You need a better model for the expected
real rate of return.
RICHARD ROLL: But, they still work in the sense that the
short-term interest rate does predict inflation. It’s just
that it’s also interesting, and I don’t know haw many
people know this, but if you look at different forecast
horizons, one month, three-months, six-months, the
remarkable thing is the further out you went the better it
predicted. Do you remember that?
EUGENE FAMA: That is a simple phenomenon though. That’s a
mechanical phenomenon. Basically what is happening is that
expected inflation has high auto correlation. I am working
with continuously compounded returns. So the residuals just
add. There is no covariance. But the forecasting part has
all these covariances that are building up. So the
fraction of the variance that you explain actually gets
bigger along the horizons. But the residual variance grows
like the number of periods.
RICHARD ROLL: What about some of the other papers that
followed on term-structure?
EUGENE FAMA: Give me a tool and I’ll use it multiple
times. [LAUGHTER]
RICHARD ROLL: You looked at risk premiums in the term
structure for instance. Let’s talk about that.
EUGENE FAMA: Well, after the inflation papers, I took up
the issue of how well forward interest rates, and forward
exchange rates, predict future spot rates. The technique
was the same. You put the ex post variable on the left.
You put the ex ante variable on the right, and you run a
regression. The interest rate forecasting papers basically
16
Int. w/ Eugene Fama by Richard Roll 17
said that forward interest rates didn’t contain that much
information about future spot rates beyond a couple of
months. So the variation you would observe in the forward
rate is basically variation in expected risk premiums.
RICHARD ROLL:
What about exchange rates?
EUGENE FAMA: With exchange rates, and there are many hedge
funds operating on the same principle. What do they call it
now? The carry or something like that?
RICHARD ROLL:
The carry trade.
EUGENE FAMA: Right. It says that if forward rates don’t
predict future spot-interest rates
RICHARD ROLL:
Exchange rates,
EUGENE FAMA: Sorry, future exchange rates. Then forward
rates are picking up the difference of the expected bonds
of the two countries, and that has worked, I guess.
RICHARD ROLL: Well, that’s the same thing. If the forward
spot rate is the forward exchange rate, if that is a good
predictor, then the carry trade won’t work. But if it is
not a very good predictor, then is that an arbitrage thing?
EUGENE FAMA:
It’s not an arbitrage, no.
RICHARD ROLL: It's speculation. But is it one that beats
the risk involved, the carry trade? People have been doing
this for a while. They make a lot of money for a short
period, and then they get killed. So it’s one of these,
kind of funny distributions.
EUGENE FAMA: Well, it’s basically working under the
hypothesis that purchasing power parity doesn’t hold. And
purchasing power parity may not hold in the short term, but
it is really pushing things to say it’s not going to hold
in the long term. I don’t believe that. I think it does
hold in the long term.
RICHARD ROLL: So, you think the Euro is going to come down
against the dollar? We were just in France eating dinner
at places that were horribly expensive because the exchange
rate is one point six dollars per Euro. That doesn’t sound
like purchasing power parity is holding very well, does it?
17
Int. w/ Eugene Fama by Richard Roll 18
EUGENE FAMA: You’d have to do all the tests. That’s a
different topic. The exchange rate hasn’t come anywhere
near balancing the current account deficit.
RICHARD ROLL: No, of course not. But I don’t know. It
doesn’t seem to me that one point six dollars per Euro
comes anywhere close to purchasing power parity, does it?
EUGENE FAMA:
test it out.
It doesn’t, but I don’t know, I’d have to
RICHARD ROLL: Yeah. (LAUGHTER) How about we go to another
topic? We were talking about inflation. You wrote some
other papers about inflation, one with Bill Schwert, who
was another student at Chicago, later than me. Talk about
inflation and stock prices. That’s a very big topic.
Today we saw the inflation rate was five point eight
percent in the US. It’s not as bad as in Zimbabwe, which
is three billion percent per annum. But what is going to
happen if the inflation rate keeps going up? What is going
to happen to the stock market, and why should stocks go
down when inflation goes up?
EUGENE FAMA:
RICHARD ROLL:
Oh, I think that result disappeared actually.
The Schwert result where you use inflation?
EUGENE FAMA: The paper about asset returns and inflation
was an off-shoot of the paper about interest rates and
inflation, which we talked about. The economic proposition
is that every asset class should be a hedge against
expected inflation. Not just bonds, but stocks, and
everything you look at. Human capital, real estate,
everything should be a hedge against expected inflation.
So, we ran the regressions of nominal asset returns on,
short term interest rates, one month, three months, six
months. Again, this was during the golden age of the
Fischer effect, and everything produced a slope of one.
Which is saying on average these are pretty good hedges
against expected inflation, except stock returns. They had
a big negative number.
RICHARD ROLL:
That was kind of a puzzle, right?
EUGENE FAMA: It was a puzzle, because what it says is
either the stock market is inefficient and all other
18
Int. w/ Eugene Fama by Richard Roll 19
markets are efficient, which doesn’t make sense to me, or
the hypothesis that the expected real return of stocks is
unrelated to expected inflation is wrong. It’s got to be
negatively related to expected inflation to make that work.
So then I wrote another paper in the AER, about stock
returns. I forget what it’s called.
RICHARD ROLL:
Demand for money?
EUGENE FAMA: There’s two of them. One was about the demand
for money, which basically said you’re going to see high
inflation when real activity goes down relative to money
supply.
RICHARD ROLL:
EUGENE FAMA:
It’s a spurious correlation?
Right.
RICHARD ROLL: But you said it’s no longer true. Would the
Fama-Schwert model still have that negative coefficient on
inflation?
EUGENE FAMA: I’ve had students do papers on this for my
PhD course. What happens now is you can’t tell the
difference between the slope and zero anymore.
RICHARD ROLL:
EUGENE FAMA:
Really?
Right, it’s not that it’s plus one.
RICHARD ROLL: Well, does that have anything to do with the
golden age of the Fischer effect? (LAUGHTER)
EUGENE FAMA: It might have something to do with it. But
what I said in the AER paper was basically, if you account
for expectations of real activity, then that negative slope
went away. That made it plausible that what you were
looking at was time variation in expected returns related
to real activity. At that point I didn’t think it was a
problem anymore.
RICHARD ROLL: We mentioned a bunch of people who were your
PhD students: MacBeth, Babiak, Jensen,
EUGENE FAMA: And you (LAUGHTER)
RICHARD ROLL:
And me.
19
Int. w/ Eugene Fama by Richard Roll 20
EUGENE FAMA:
And Myron.
RICHARD ROLL: And Myron. There have been a lot. Do you
know how many students have you supervised?
EUGENE FAMA:
Oh, no.
RICHARD ROLL: I tried to find something out about that on
the website. Do they keep records?
EUGENE FAMA:
RICHARD ROLL:
had…
EUGENE FAMA:
RICHARD ROLL:
EUGENE FAMA:
Not very good ones.
So every year for forty-eight years you’ve
On average, maybe two a year.
That’s like ninety.
Around a hundred.
RICHARD ROLL: That’s right. A hundred, and most of them
are still practicing finance.
EUGENE FAMA:
Right
RICHARD ROLL: Some of them aren’t professors though.
You’ve had a couple of students who’ve started hedge funds.
EUGENE FAMA: Right. Lots of colleagues have started hedge
funds too. Everybody with a marginal statistical result
comes out with a hedge fund these days. (LAUGHTER) They
lever it up, but that doesn’t change the t-statistic.
RICHARD ROLL:
student?
What about Cliff Asness?
Was he a PhD
EUGENE FAMA: Yes. He was the best student we had in maybe
twenty years. He never published his thesis, but there
were three essays in his thesis that were just first rate.
Now he’s a very successful investment manager.
RICHARD ROLL: So he decided to make money instead of
following the intellectual life. Well, I guess those two
aren’t incompatible.
20
Int. w/ Eugene Fama by Richard Roll 21
EUGENE FAMA:
David Booth is another.
RICHARD ROLL: Yeah. We talked before about your stability.
You went to Chicago, you stayed there. You married Sally,
and stuck with it. How about DFA? You started in '82, and
here you are.
EUGENE FAMA:
Right, I'm still involved. Lots of people
have used my finance ideas over the years. Usually they
don’t pay you. (LAUGHTER) They just use the ideas. But
David Booth and Rex Sinquefield decided it made sense to
have me actually involved with the company. I think it has
worked out well for both sides.
RICHARD ROLL:
Do you want to talk about that?
EUGENE FAMA: Well, basically David and Rex were strong
believers in market efficiency. As strong as anybody I
know, including me. They were convinced that professional
investment managers really couldn’t add any value, and they
started the company, basically on the proposition that
defined benefit pension plans weren’t invested enough in
small stocks. That was an asset class that they could
provide, and there would be a market for it.
RICHARD ROLL:
this…
And that didn’t have anything to do with
EUGENE FAMA: Well, let me finish. When they brought me
along I said, “you’ve come along at just the right time,
because Rolf Banz has just finished his thesis that says,
small stocks have expected returns that can’t be explained
very well by the capital asset pricing model." So that was
a double kicker in getting the business started. It was a
small cap business to begin with. They started some bond
products based upon the research we’ve already talked
about. But it has evolved after the Fama-French stuff came
along. Efficient markets took a long time to make its way
into investment practice. Still now, I think Ken, in his
Presidential paper, estimated less than twenty percent of
money is managed passively. But the value growth stuff hit
immediately. I showed David Booth a cross-section of
expected stock returns. I showed him the output for that
paper on my computer in 1991, and he said, "I have a big
institutional investor I think he would want to buy that.”
This fellow came to my office with Booth. I showed him the
stuff on the computer screen, and he said, “Great. Here’s a
21
Int. w/ Eugene Fama by Richard Roll 22
few billion dollars to invest in a small cap and large cap
versions of that. So this stuff hit the business world
before it was even published.
RICHARD ROLL: We jumped a little ahead because we haven’t
really talked about the three-factor model. But I did want
to get into that. So why don’t you talk about the original
three-factor model you did with Ken and what the factors
were. It’s a multi factor model, but specifically what are
those factors?
EUGENE FAMA: I’ve always thought research has a huge dose
of serendipity associated with it. Ken and I wrote this
paper about the cross-section of expected stock returns
which basically said if you look at all the variables
people have looked at, two seem to do pretty well, marketcap and book to market ratio. Book to market ratio is just
a price ratio, and lots of price ratios work pretty well.
There was nothing new in that paper, nothing new at all. It
was just putting together lots of previous work. Up until
that point there had been a lot of studies that said the
CAPM doesn’t work for this reason, or the CAPM doesn’t work
for this different reason. We just put it all together and
said, “It doesn’t seem to work at all.” (LAUGHTER) And
that somehow, caught the interest of people. And that
paper is, I think, the most highly cited paper in The
Journal of Finance in the subsequent period. Then we said,
ok, you can tell rational stories for that. Or you can
tell irrational stories. So let’s put forward an empirical
asset pricing model that would capture these two premiums.
RICHARD ROLL: What is the rational story, and what is the
irrational story.
EUGENE FAMA: There are higher expected returns for small
stocks over big stocks, and there are higher expected
returns for value stocks over growth stocks. The rational
story is that the size premium and the value premium are
compensation for risks associated with those stocks,
whereas the behavioral story says the premiums are just the
result of mispricing.
RICHARD ROLL: It seems odd. I can understand small versus
large. Small stocks generally do have more risk than large
stocks, but value stocks?
22
Int. w/ Eugene Fama by Richard Roll 23
EUGENE FAMA: That’s not really the issue. The issue is why
isn’t the risk captured by beta?
RICHARD ROLL: Yeah, but why are value stocks more risky
than growth stocks?
EUGENE FAMA: Well, that story you have told for small
stocks holds better for value stocks, because value stocks
tend to be relatively distressed relative to growth stocks.
RICHARD ROLL:
They’re fallen angels?
EUGENE FAMA: They are. Lots of them are fallen angels. So
it’s reasonable to think they have higher costs of capital
than growth stocks. Whereas the CAPM says the opposite.
Basically growth stocks have higher betas than value
stocks. So that model is saying growth stocks have higher
costs of capital.
RICHARD ROLL: Normally you think of a high beta stock like
a growth stock. The CAPM says it’s more risky. This is
contrary to that.
EUGENE FAMA: Right, but to make full sense of that, you
have to go back to something like Merton’s I-CAPM, or the
APT, or something where there are multiple factors. Then
you have to tell some kind of story about why there are
differential risk premiums per unit of variance. That is
the essence of the multi-factor model.
RICHARD ROLL: If you take the APT model, those things
should be related to the covariance matrix of returns. They
couldn’t be risk premiums if they weren’t related. So are
they?
EUGENE FAMA: They are indeed. If you go back and look at
the original paper by Lakonishok, Shleifer and Vishny, it
basically says that the value premium is an arbitrage
opportunity. You can go long value stocks and short growth
stocks and have a portfolio that has zero variance,
essentially. I remember going to dinner with Andre and
after a bottle or so of wine, I pulled out some output, and
said, “Here’s what happens if you actually do this. The
variance that you get is on the order of the variance of
the market. It doesn’t look like an arbitrage opportunity
to me." Andre said, “Well ok, maybe it looks like a risk
factor, but the risk premium is irrational.” Now at that
23
Int. w/ Eugene Fama by Richard Roll 24
point you’re in a box. You can’t tell the difference
between the rational story and the irrational story. So
that’s basically where it stands today. I think everybody
agrees that the difference between value and growth returns
has a big variance associated with it. They disagree about
the explanation.
RICHARD ROLL: Whether it’s a risk premium or a market
opportunity? But as you have said, if you take a hedge
portfolio, that’s certainly not risk free.
EUGENE FAMA:
No, far from it.
RICHARD ROLL: What about other things in addition to value
growth and size? You use momentum too? What is that?
EUGENE FAMA: Momentum gives me a problem because the
winners and the losers in momentum sorts change so
frequently that if momentum is a risk story, the risk has
to be changing in a very volatile way.
RICHARD ROLL: If you look at prior six-month returns, to
see if the ones that have done better continue to do well,
that changes every month or so?
EUGENE FAMA: This happens around the world, except Japan.
The Japanese are somehow immune to this.
RICHARD ROLL:
EUGENE FAMA:
RICHARD ROLL:
risk.
Well, maybe they’re more rational.
Who knows, right.
(LAUGHTER)
Or maybe less, maybe they don’t care about
EUGENE FAMA: Another way to put it is, I don’t know what
fraction the Japanese market is of the total but the
remaining fraction is basically the one that shows
momentum, and that fraction doesn’t, so the game is still
open. Remember now, what goes on in finance. We have two
tapes, we have CRSP and we have Compustat. There are some
others thrown in there, but you have thousands of finance
professors spinning the tapes, and they all want to get
tenure. Some want to do even better than that. So they
are going to find whatever is there, even if it is there by
chance.
24
Int. w/ Eugene Fama by Richard Roll 25
RICHARD ROLL: Well, that is why your out-of-sample things
tend to be international. I think you mentioned some of
that.
EUGENE FAMA: When we first showed Fischer Black the value
growth stuff, he had a different take on it. Fischer was,
of course, one of the originators of the CAPM. He said,
"The CAPM is right. It just doesn’t work." (LAUGHTER)
Fischer had conundrums like that. Anyway, so he said, “I
think this is just data-dredging. So then we said, “Well,
the classic cure for data dredging is to get out-of-sample
data.” So, we extended the data back to 26’, and we looked
at foreign markets. Everything replicated.
RICHARD ROLL: If you look at foreign markets for value and
growth you generally find it works in most of these other
markets as well.
EUGENE FAMA:
RICHARD ROLL:
well?
EUGENE FAMA:
RICHARD ROLL:
The premiums are all on the same order.
And momentum, is that generally true as
Except for Japan.
What is it about Japan?
EUGENE FAMA: In my mind that raises hope, but it’s just a
hope, that momentum is a result of data dredging.
RICHARD ROLL: Well, it would have to be an incredible kind
of data dredging. These markets are not that correlated
with each other. They are correlated but not that
correlated. They are not completely independent samples,
but they’re quite independent. If you look at twenty
different markets, and it works in every single market
except for one.
EUGENE FAMA: I don’t know about twenty different markets.
I’d say three. You’ve got the US, Britain and continental
developed, and you’ve got Japan. That’s it.
RICHARD ROLL: But other people have looked at momentum in
other markets.
EUGENE FAMA:
Emerging markets?
25
Int. w/ Eugene Fama by Richard Roll 26
RICHARD ROLL: Sure. Indonesia and places like that. It
works there too.
EUGENE FAMA:
Maybe you’re right.
I don’t know that data.
RICHARD ROLL: OK. So what about some of the other FamaFrench papers. You’ve got twenty-eight papers. One of them
is disappearing dividends we’ve talked about. Some of the
others are on industry costs of capital. Do you want to
talk about that?
EUGENE FAMA: Well, that one just uses the CAPM and the
three factor model to try to estimate industry costs of
capital. That gets me into a favorite line of thought of
mine. Basically what we find is that it is almost
impossible to estimate industry costs of capital.
(LAUGHTER)
RICHARD ROLL:
Using the three-factor model.
EUGENE FAMA: Using the three factor model, but the problem
is that the three slopes, the market loading, the size
loading and the value growth loading vary so much over
time, within industries, that using two years of data is
just as good as using twenty years of data. You don’t get
better out-of-sample forecasts by extending the data
period. Now, the regression slopes estimated with two
years of data are basically garbage.
RICHARD ROLL: Well, then how would you estimate industry
costs of capital?
EUGENE FAMA: You know, this is why they don’t let me teach
corporate finance anymore. (LAUGHTER) I used to teach
corporate finance, and when I first started teaching it in
the early nineteen-sixties, I had M & M, which I could
stretch out for two weeks. Then I did cases because there
was nothing else to talk about. Now we have all of these
theories and empirical work. So here is a question I posed
at the beginning of the class. I am going to easily be
able to fill out the ten weeks, but ask me at the end if
you’ve learned any more about the cost of capital. I don’t
think you can estimate the cost of capital.
RICHARD ROLL: But they have to estimate it. If you’re a
CEO of a company in the electric utility industry, you have
to come up with a number. How would you advise them?
26
Int. w/ Eugene Fama by Richard Roll 27
EUGENE FAMA: That’s assuming that discounted cash flow in
a world of uncertainty provides better estimates of value
then some alternative. Let’s say payback. What’s the
evidence on that? There is none. Our use of discounted
cash flow is based on, in my experience, it’s Irving
Fischer. If you want to read something more recent, which
is nevertheless Irving Fischer, read chapters one through
three of Fama-Miller, the Theory of Finance. It’s perfect
certainty. That’s where you can justify that. In a world
of uncertainty it’s much more difficult to justify
discounted cash flow.
RICHARD ROLL: Well, I mean, you’re not saying that’s not
the right way to do it if you can get a good estimate on
the discount rate for expected cash flows. That still
works, right?
EUGENE FAMA: I don’t know because you’re dividing by a
random variable.
RICHARD ROLL:
EUGENE FAMA:
Of course, we know the reciprocal.
If the number came down from heaven?
RICHARD ROLL: That’s what I’m saying. If you had a really
good estimate, there’s nothing wrong with discounted cash
flow, right?
EUGENE FAMA:
Right.
RICHARD ROLL: Except that you can’t figure what to put
into the equation.
EUGENE FAMA:
In either the numerator or the denominator.
RICHARD ROLL: Numerator or denominator? Is that a general
conclusion? What do you think of corporate finance? It
sounds like you say they don’t let you teach it anymore.
Is there anything in corporate finance that you do like?
You are talking to the American Finance Association. They
had a hundred papers in the last issue of The Journal of
Finance. So, what is in those papers?
EUGENE FAMA: Well, I think there is a lot of interesting
research on capital structure. What determines capital
27
Int. w/ Eugene Fama by Richard Roll 28
structure?
students.
But I don’t think that’s much help for MBA
RICHARD ROLL:
What determines capital structures?
EUGENE FAMA: We have various theories. We also have lots
of stylized evidence about stuff, and it doesn’t conform to
any of the theories. M & M looks as good as the target
capital structure models, or the pecking-order model.
RICHARD ROLL: M & M, had several papers. Then finally
Miller had dividends and taxes and debt and taxes that
basically said what you are saying.
EUGENE FAMA: The bottom line from debt and taxes and
dividends and taxes is we don’t know what the tax effects
are. When I was teaching corporate finance I said, now the
first question in corporate finance is, what marginal tax
bracket is built into the pricing of debt and equity, so
that you could at least tell me about the tax advantages of
one or the other. There are no convincing papers on that
topic.
RICHARD ROLL: What about international data? You mentioned
the fact that dividends, for instance, are double-taxed in
the US. Wouldn’t that offer some opportunity to try and
estimate…
EUGENE FAMA: It might, I haven’t seen anybody do it in a
convincing way.
RICHARD ROLL: So there’s a research topic your next PhD
student could work on. But you might think it’s hopeless
and not advise them to do this.
EUGENE FAMA: I don’t know. I’d have to look and see if
there’s any hope when you assemble the data, that you could
get something that was within the range of standard errors
that was likely to come out of it.
RICHARD ROLL: One obvious question in an interview like
this is what are you going to work on next? You’ve got a
bunch of working papers. I’m not talking about them. What
is something that is not a working paper yet?
EUGENE FAMA:
I never plan.
28
Int. w/ Eugene Fama by Richard Roll 29
RICHARD ROLL: So you have an efficient markets idea on
research as well. You don’t know what you’re going to do
until you do it.
EUGENE FAMA: Totally unpredictable. That makes it more
fun. That's the way I’ve always worked. Interest rates and
inflation is a good example. You have what seems like a
small idea and it just keeps growing on its own. You just
keep pursuing it. I think the Fama-French stuff is another
good example. We pushed that in lots of different
directions.
RICHARD ROLL: When you are doing empirical work, which is
mostly, but not everything, are you always surprised
because stuff appears you don’t expect?
EUGENE FAMA:
RICHARD ROLL:
You never end up where you started.
It’s good to just do anything?
EUGENE FAMA: Do It!
RICHARD ROLL: We should mention how important CRSP was.
It fostered a lot of research. Jim Lorie, I guess was the
guy that first got the grant from who, Merrill Lynch, to
put together CRSP with Larry Fisher. Tell us a little
about that.
EUGENE FAMA: I think finance had a very simple beginning.
It was basically the coming of the first computers that
made it possible to do large-scale empirical work. Jim
Lorie, who was a marketing professor at that time, went to
Merrill Lynch and said, you know, you don’t really know
what the stock return was historically. You don’t have a
very good estimate of it, and we will put together a tape
that will give you the background numbers that you can use
to calculate the return on the NYSE. He got Larry Fisher to
do all of the development of the project. Larry thought
about everything. I don’t know how he did it. He thought
about everything that could possibly be relevant for making
the data perfect. What you needed to calculate, every
detail, all the capital structure, all the capital changes
you had to take account of.
RICHARD ROLL:
And all the things like name changes?
29
Int. w/ Eugene Fama by Richard Roll 30
EUGENE FAMA: Name changes. Everything. He thought of all
of that in advance. Eventually they put together a tape
from 1926 to I think 1960 was the ending date on the first
tape. Then they came out with this number, which was the
return on the NYSE from 1926 to 1960. I think it was a few
basis points away from the S & P return, but it was very
accurate.
RICHARD ROLL: It was a pretty big number, too, Merrill
Lynch took out a…
EUGENE FAMA: Merrill Lynch took out a full-page add in the
Wall Street Journal trumpeting this number as the reason
why you should be investing in stocks.
RICHARD ROLL: People are still trumpeting this number.
Stocks in the long run. People are still talking about it.
But then, you don’t think the number is the size it was
from '26 to '60. Or do you. It’s the average return of the
stock market. I mean this is like the risk premium in
equity-return.
EUGENE FAMA: I think the equity-premium, historically in
the US is a little high relative to the expected value.
RICHARD ROLL:
How high?
EUGENE FAMA: That’s difficult to say.
bias in effect. The market survived.
There’s a survivor
RICHARD ROLL: You’re talking about the US as one of the
markets that was a successful survivor?
EUGENE FAMA: Right. That tells you that you’ve got a
higher realized return, probably higher than expected.
RICHARD ROLL:
EUGENE FAMA:
RICHARD ROLL:
But you don’t know how much higher?
Well, Ken and I wrote a paper on…
Is it two percent?
EUGENE FAMA: Is it two percent higher? Yeah, that’s
probably not a bad number. I always think of the number,
the equity premium, as five percent.
30
Int. w/ Eugene Fama by Richard Roll 31
RICHARD ROLL: Five percent is the excess return of the
market over the risk-free rate?
EUGENE FAMA:
RICHARD ROLL:
EUGENE FAMA:
data.
Right
Before it was seven percent.
That’s the number presented before in the
RICHARD ROLL: Anyway, go back to CRSP, in 1960 Larry put
the tape together, then what happened in finance.
EUGENE FAMA: Well, you know what happened in finance. Lorie
became nervous. Merrill Lynch gave us this massive amount
of money to develop this tape, two hundred and fifty
thousand dollars, to develop this tape. And two hundred
and fifty thousand dollars was real dollars back in 1960.
But how do we know anybody is going to use it? So Lorie
said, why don’t you do a study of stock splits? That’s
where the study of stock splits came from.
RICHARD ROLL: Well, we did have splits on the tape.
That’s one thing that Larry collected.
EUGENE FAMA:
RICHARD ROLL:
We didn’t have the actual date, right?
No, we had the month of the split.
EUGENE FAMA: Right, we didn’t have the announcement date.
Eventually the announcement date got on there. But that
became, as you well know, became a very famous paper. That
was the birth of event studies basically. And again, who
knew at that time whether that was going to be a big deal.
I don’t know if you remember, but, where did we publish
that?
RICHARD ROLL: The International Economic Review, some
obscure place.
EUGENE FAMA:
RICHARD ROLL:
Franco was the referee it turns out.
Was he? I didn’t know that.
EUGENE FAMA: He didn’t say a word. He said, “This paper’s
perfect, just publish it.” [LAUGHTER]
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Int. w/ Eugene Fama by Richard Roll 32
RICHARD ROLL:
We should have sent it to the AER.
EUGENE FAMA: Never again did I have that experience. But
looking back on the paper, and I’m sure you have, is there
anything that strikes you in there?
RICHARD ROLL:
EUGENE FAMA:
RICHARD ROLL:
was.
No what do you mean?
There’s not a single standard error in there.
Oh no. We didn’t know what a standard error
EUGENE FAMA: I know, I looked at it and said, “This is
perfect.” It’s just totally flat. We don’t need a
standard error.
RICHARD ROLL: When I first saw that pattern, when we got
it out of the computer, I thought we had an error in our
computer code, because I didn’t think anything could look
like that. But then what you realize after the fact is that
it had to look like that, or else markets weren’t working
well.
EUGENE FAMA: Well, you know, for many years that paper was
the most highly cited paper in accounting.
RICHARD ROLL: Yeah, well there are so many event studies
in accounting.
EUGENE FAMA: Merton Miller always said, “Accounting is
event studies.” [LAUGHTER] Assets equal liabilities and
then event studies.
RICHARD ROLL: But you know when CRSP came along, and the
data were available, in the form they were available, and
the computer becoming much easier to use, that really made
finance what it is today.
EUGENE FAMA: With the way data are organized and the way
you can search through data, you can do in an afternoon
stuff that would have taken months with the initial
computers.
RICHARD ROLL:
Sure.
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Int. w/ Eugene Fama by Richard Roll 33
EUGENE FAMA:
'60s.
RICHARD ROLL:
Chicago?
EUGENE FAMA:
OK, so ask about the state of finance in the
OK, what was it, 1960, when you went to
I went to Chicago in 1960.
RICHARD ROLL: Was there finance in 1960? Who did you look
up to as a graduate student as being a great scholar in
finance? Or maybe I’ll put it the other way, who did you
not want to emulate?
EUGENE FAMA: I didn’t take any finance courses.
RICHARD ROLL:
Were there any finance courses?
EUGENE FAMA: Yeah, there was a course in security
analysis. There was a course on money and banking, which I
didn’t take because I took it in the economics department.
And that was it. So, there weren’t any finance courses.
RICHARD ROLL:
EUGENE FAMA:
RICHARD ROLL:
Was Markowitz being used at that time?
Markowitz was not being used.
That was earlier. That was the fifties.
EUGENE FAMA: Markowitz was 53’. And it was a thesis in
the economics department, which he had trouble getting
through.
RICHARD ROLL:
economics.
Because Friedman didn’t think it was
EUGENE FAMA: He didn’t think it was very good. Shows you
what he knew. [LAUGHTER]
RICHARD ROLL: Well, we can say that now since he’s no
longer around.
EUGENE FAMA: Anyway, when I finished my thesis and Chicago
hired me, I went to Miller. I hadn’t had a course from
Miller, he hadn’t taught. To attract him from Carnegie I
think they gave him a year or two off. So although I’d
worked with him on my thesis, he still hadn’t taught there.
So I had never had a course from him.
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Int. w/ Eugene Fama by Richard Roll 34
RICHARD ROLL:
EUGENE FAMA:
But, the first M & M paper was 58’?
58’
RICHARD ROLL: So that was just two years before you got to
Chicago, and he was not teaching that first year.
EUGENE FAMA: Well, no this was just 62’. So he came and he
didn’t teach that first year or two.
RICHARD ROLL:
Chicago?
EUGENE FAMA:
Markowitz.
RICHARD ROLL:
So you taught the first finance course at
I taught the first finance course that used
Used Markowitz, huh.
EUGENE FAMA: Right, and it had three numbers in those
days. It had an MBA number, an advanced MBA number, and a
PhD number. At that point it was just Markowitz, because
the CAPM wasn’t…
RICHARD ROLL:
Yeah, that was 64’.
EUGENE FAMA: Then the CAPM came out. So, when I went to
Miller and asked him what I should teach, he said, “Look,
we hired you to teach the new stuff. You have to do it.”
That’s how that course came about, which I’ve been teaching
ever since.
RICHARD ROLL:
EUGENE FAMA:
RICHARD ROLL:
EUGENE FAMA:
RICHARD ROLL:
So you’ve been teaching the same course?
I’ve added a few things. [LAUGHTER]
You’ve added a few things?
[LAUGHTER]
It’s all Fama-French now. [LAUGHTER]
It’s the same course number though.
EUGENE FAMA: No, the course numbers have changed across
the whole University. Anyway, we had at that time, there
weren’t good finance departments anywhere, and Chicago, for
whatever reason, attracted the best PhD students. We had a
group of PhD students. You, Myron, Mike Jensen, and a few
34
Int. w/ Eugene Fama by Richard Roll 35
other people who went off to other Universities and started
first rate finance departments. Finance has kind of grown
out from that base. And very quickly, people like Steve
Ross and Bob Merton came along who turned out to be giants
in their own right.
RICHARD ROLL: Well, you know Ross, for example, I know why
he switched to finance. He was at Wharton. He was an
economist from Harvard who didn’t know anything about
finance. Then he went to a couple of seminars, and decided
he was going to switch over to the field. A couple of
Chicago people went to Wharton. But yeah, people that
Chicago graduated and sent out went to start all these
other places.
EUGENE FAMA:
Marshall Bloom went to Wharton for example.
RICHARD ROLL: Marshall Bloom went to Wharton. Chicago was
kind of the center of the whole finance world.
EUGENE FAMA: It certainly was at that time. I think it
still is. We have very little trouble attracting new PhDs
to join our faculty. We rarely lose to other schools when
we are hiring people. And even if they don’t make it at
Chicago, they always go off to great new jobs. So, there’s
almost no downside to it, but there are good departments in
lots of places.
RICHARD ROLL: When you went to Belgium back in 1975, was
there anybody in Europe who knew much about finance?
EUGENE FAMA:
No. Well, there were a couple.
RICHARD ROLL: A couple.
in the US and London.
EUGENE FAMA:
But usually they had been trained
Right
RICHARD ROLL: Now if you go to Europe there are lots of,
well all over the world. I mean it’s not just a US
phenomenon.
EUGENE FAMA: In my view, biased obviously, finance is the
most successful area of economics. It came from nowhere.
Before Markowitz there was nothing. And in that halfcentury, empirically it’s clearly the most successful.
35
Int. w/ Eugene Fama by Richard Roll 36
RICHARD ROLL:
Well, it has better data than anything.
EUGENE FAMA: The data is better, and it is used in a very
careful and logical, sensible way. I’m not sure we know a
lot more than we did then, but we know why we don’t know.
[LAUGHTER]
RICHARD ROLL: You are saying there’s still plenty of room
for discovering answers to questions that we don’t know
about. Like leverage, cost of capital, and stuff like that.
EUGENE FAMA: Right. Cost effects, risk and return, the
three-factor model.
RICHARD ROLL:
Asset pricing.
EUGENE FAMA: Yeah, the three-factor model galls the purists
in asset pricing because it is empirically motivated. It
doesn’t come out of consumption data or anything like that.
RICHARD ROLL:
regularity?
EUGENE FAMA:
It comes because you observe an empirical
And you work backward from there.
RICHARD ROLL: Backward from there. But a lot of things do
that. Theorists are just waiting for some new empirical
discovery so they have something to exploit.
EUGENE FAMA:
Right.
RICHARD ROLL: That’s basically the way the science works.
So thanks you very much Gene.
EUGENE FAMA:
Thank You.
RICHARD ROLL: I enjoyed it. I hope you did too. And thanks
everybody for watching.
36