SHARPE
Interview at the home of William Sharpe
(edited for clarity and readability)
This is the second interview in our series with founding contributors to the
field of finance. The title of the series is “Masters of Finance”, and I am pleased
to announce that our second master of finance is Dr. William Sharpe. Technical
support for the taping of this interview is being provided by Dimensional Fund
Advisors. We thank them for their assistance. We are taping today in the home
of Dr. Sharpe and his wife Kathryn.
And from their lovely home in Carmel,
California, I bid a welcome to Dr. Sharpe.
Sharpe: It is a great pleasure to be here with you.
You didn’t run away when we showed up.
Buser:
Sharpe: True.
Buser:
Although Dr. Sharpe continues to contribute to a long and distinguished
career, his name will always be identified with the Capital Asset Pricing Model,
He has won a number of awards for his many contributions. In 1980, he was
elected president of the American Finance Association. In that same year he
received an award from the American Assembly of Collegiate Business Schools
for outstanding contributions in business education.
In 1989, the Financial
Analysts Federation honored Dr. Sharpe with the Nicholas Molodovsky Award for
outstanding contributions to the finance profession. In 1990, Dr. Sharpe shared
the Nobel Prize with Harry Markowitz and Merton Miller. Currently, Dr. Sharpe is
Professor Emeritus at Stanford. In fact he is a double Professor Emeritus at
Stanford Perhaps he will explain what that means in today’s interview.
In
addition, Dr. Sharpe remains active in a business of his own and in consulting
activities.
Q.
Let me begin with an obvious question. What is it like to win the Nobel
Prize?
A.
Well as I and many of my friends say, if anybody offers you one, you
should take it. It is definitely worth having. It is incredible. It’s an unbelievably
heady experience, as you can well imagine. You hear from people that you
haven’t heard from for a very long time.
1
Q.
Any asking for loans? A.
Well, you get requests for some really quite
remarkable things. You get letters from time to time from people who want you
to help them because their brains were implanted with electrodes while they were
on airline flights, and they were forced against their will to do various things.
Some real kooks come out of the woodwork.
But you go to Stockholm, and you are treated like royalty.
It is
intellectually, emotionally, and in virtually every sense, an experience that is
outside the range of comprehension for an ordinary academic, such as myself.
Q.
Do you recall where you were when you first heard that you’d won the
prize?
A.
Oh yes.
Everyone does.
We were at an industry and academic
conference in Tucson, Arizona. The phone rang about 4:00 in the morning. I
had not even been paying attention to the fact that this was about the time for the
announcement. The phone rang in the middle of the night There was someone
on the other end saying something with a bit of an accent. There had been a
fellow trying to get me to give a talk in Belgium, and he seemed to have trouble
with time zone differences. He had already called several times at odd hours,
and I thought it’s him again. When I realized it wasn’t, I next thought somebody
is playing a trick on me.
I then very quickly realized it almost certainly wasn’t.
So after the call and jumping up and down and waking up Kathy we turned on
CNN. In about five minutes the first announcement came.
It had about 60
percent of the information right. Then every five minutes they repeated it, and it
got a little bit more accurate. We called for room service, sat on the balcony
outside our room, and watched the sunrise over Tucson. Then all hell broke
loose.
Q.
Were you aware that you were under consideration?
A.
No I wasn’t. There are people who try to follow these things and make
bets on who might get it each year. I had never been in that particular mode. I
believe Harry may have told you this too, but I think Harry and I, and perhaps
others in finance, felt that given who had already been awarded the prize, and
the work for which they had been given it, the committee probably was not going
to include financial economics within the purview of economics for the purposes
2
of the prize. So I , t least felt that my field wasn’t going to be in the running. So
I hadn’t really worried about it.
Q.
What were your thoughts upon learning that you would share the award
with Harry Markowitz and Merton Miller?
A.
Well needless to say, sharing it with Harry was particularly wonderful for
me since it was Harry’s work that got me into finance and started me on the path
that I’ve taken. So to be able to share it with Harry was a very, very special
experience. Merton Miller’s work was in a somewhat different area than my
main line of inquiry, but Mert and I knew each other over the years, exchanged
papers back and forth, and of course to be associated with Merton Miller was
also a very heady experience.
Q.
You mentioned that Dr. Markowitz helped in your career, could we back
up a little bit and tell us how you even got to that point? What was your formal
training, starting at the earliest relevant point?
A.
I started as an undergraduate in a pre-med course because my mother
wanted me to be a doctor. Then I switched to business at UCLA. The first two
courses were accounting and economics. I hated accounting, at least as it was
taught in that course, but I loved economics. I did not know anything about
economics until I took the course. So I switched to an economics major. I got a
bachelors and a masters in economics. Then I went into the service, and when I
came back, I went to work at the Rand Corporation doing research. I also started
a PhD at UCLA and worked in the finance area with Fred Weston .
He
introduced me to Harry’s work, which I fell in love with. I thought this was just
wonderful, beautiful stuff. So that’s how I became conversant with the work.
I started a dissertation on transfer pricing. Jack Hirshleifer came to UCLA,
and since I was starting with his work, it was decided that he should be my chair.
He looked at what I thought was a half-finished dissertation, and he said he just
didn’t think there was much there. So I went to Harry, who was at Rand, and I
asked if maybe there was something I could build on from his work. In some
sense, the rest is history. Harry wasn’t on the faculty at UCLA, but I worked out
an arrangement with Armen Alchian to work with Harry and have Armen be my
dissertation chair.
3
Q.
When I meet Dr. Hirshleifer, I will have to thank him for pointing you in the
direction of finance.
A.
Well I can tell you I’ve thanked him many, many times.
Q.
Did it strike you as odd then, or now, that you would ultimately use similar
tools from transfer pricing? I assume you had been doing optimization problems
with Lagrangian multipliers.
Or perhaps I should just ask, what was the
mechanism that you had been analyzing in transfer pricing?
A.
using
It’s going to take me a little while to reconstruct. But as I recall, I was
a linear programming Input/Output
formulation.
I was working with
Lagrange multipliers, but not in the traditional sense. It was more shadow prices
from linear programming.
Q.
And shadow prices were what I was thinking about. Were you working
with duality problems or things like that?
A.
Exactly.
Q.
You then worked with Dr. Markowitz, who was also working with linear
programming and constraints and—
A.
Well Harry’s work was all quadratic, and the shadow prices were much
closer to Lagrangean’s, or at least Kuhn Tucker conditions.
Q.
So, there wasn’t, it wasn’t as big of a switch as it might have seemed?
A.
No, I was in a group that Rand called the Logistics Department. We were
doing big linear programming problems and using a lot of the then-new
operations research tools. So I was bringing an OR mindset and technology to
economic issues.
Q.
Your first article, which appeared in Management Science, includes an
acknowledgment. And over the years I’ve read a lot of acknowledgments. I have
even written a few. But I cannot recall one as, as sweet or as kind as your
acknowledgment. Do, do you remember it?
A.
Actually it wasn’t my first article.
My first article was in the Naval
Research Logistics Quarterly, on a totally different subject.
Q.
Harry had an earlier article there as well.
A.
Yes. Q.
I stand corrected. In your second article, I wonder if you
would read that part of the acknowledgment to Dr. Markowitz.
4
A.
I am often accused of putting all my important results in footnotes. Maybe
this is one of them. I’ll skip the first sentence. The remaining text, referring
initially to “the author” reads “His greatest debt, however, is to Dr. Harry M.
Markowitz at the Rand Corporation, with whom he was privileged to have a
number of stimulating conversations during the past year, It is no longer possible
to segregate the ideas in this paper into those which were his, those which were
the author’s, and those which were developed jointly. Suffice it to say that the
only accomplishments, which are unquestionably the author’s are first the
computer program, and then the writing of the article.”
I just noticed that on the other page there is an article by two authors, one
of whom is Marty Leibowitz, now a very close friend. Go figure.
I was certainly hedging my bets with the footnote. One of the things that
has happened, as I’m sure you’re aware, is that financial economics is an old
enough field now that there’s a, there’s a cadre of, of younger researchers — and
some older researchers — who are doing histories of the field. Among other
things they are trying to decide whether or not a particular idea was attributable
to Markowitz, or to Roy, or to some monk from the 13th century. So there is a lot
of dispute, and I am glad I wrote that because at least there, I don’t claim
anything more than I can establish. I definitely wrote the paper. Q. Well
it’s
a
remarkable acknowledgement. Dr. Markowitz thinks that your contribution was a
lot more substantial than the footnote indicates.
A.
Yes he does I think one of the problems that we all have, especially when
we work with PhD students, is taking into account the interchange of ideas. And
this is true with colleagues as well, whether they are formal coauthors or not,
Ideas are ideas. We all know they result from conversations and batting things
back and forth. It always amazes me when people say “ I know that was my
idea, and it was only my idea”. Unless you’re in a garret somewhere, I don’t know
how you can say that.
In particular Harry indicated that he thought a simple
model of security returns would offer a very good way to solve the mechanical
problem of trying to estimate lots of covariances. But he did not realize the great
simplification in the problem that would result, beyond the mechanics of to get
estimates for all of these co-variances. As for the single index model, or the one
factor model itself, it came straight out of Harry’s work.
5
Q.
Do you recall your original phrase? You have mentioned single index and
single factor, but that wasn’t the phrase you used.
A.
No it wasn’t. I called it the diagonal model because, if you take advantage
of the structure, you can write the covariance matrix as a diagonal matrix with
zeroes on the off diagonal and an additional equation At that time, when I was
programming algorithms on the IBM 709 every little bit helped computationally.
Now it seems almost ludicrous that we worried about these algorithmic
simplifications. Now we just solve problems with brute force on our PCs.
Q.
The new computers are amazing, but Harry indicated that one of his
efforts was to try to program [the mean-variance problem] for 25 securities, and
he failed. He had to give up. It was too ambitious (Laugh) for the computer
technology of that era. He had to settle for a ten security application.
A.
Yes
Q.
Well to use a baseball analogy, if your first finance paper was a solid hit,
your next effort was clearly a homerun. I am speaking about your 1964 Journal
of Finance paper, Capital Asset Prices: a Theory of Market Equilibrium Under
Conditions of Risk. How did you come up with that bold idea?
A.
Well it was almost perfectly natural. It started with Harry’s work. Harry
said that if you have estimates or risk, returns and correlations, here is how you
should build your portfolio. It was very definitely a normative model : here is how
to do portfolio choice, as we call it today. My dissertation had three parts. The
first piece was the algorithm you have referenced for solving the portfolio
problem under the single index model assumptions in an efficient way. The
second piece of was again very much normative in tone, but it had a little bit of a
behavioral aspect. Through Fred Weston I made contact with an investment
advisor in Los Angeles.
He and I talked, and I asked him to
think
probabilistically. He asked “How?” He knew about bell shaped distributions, so I
made some grid paper and got him to draw distributions for 30 or 40 stocks, and
to make some other subjective estimates. I then punched all that information on
cards and processed it to show him the implications a la Markowitz of his
estimates. The portfolios that came out typically had something like 60 percent
in a stock called Haloid Xerox. I asked him if he thought they were plausible
portfolios, or if he felt there was something wrong somewhere, either with his
6
estimates of the prospects or with the assumptions I and Markowitz had made to
get the portfolios.
For the third part of the dissertation I did what any well
trained micro-economist would do, I asked if everybody did what Markowitz said
they should do, what would be the implications for
equilibrium in capital
markets? This part was positive economics. It looked at equilibrium using the
single index model as the maintained hypothesis about the way in which
securities related one to the other.
So I got the PhD degree and went to University of Washington. I thought
there were some really nifty results in the third part of the dissertation I had the
capital market line, the security market line, betas, the whole nine yards. But it
all seemed hostage to this very severe assumption about the interrelations of
security returns. So I set about seeing if I could generalize the model It turned
out that it didn’t take much effort to get the same results without the restrictive
assumption. That is how the published version of the CAPM came to be. I had
the greneralization within a few months after finishing the dissertation, but given
the vagaries of publishing and refereeing, it took a while to publish.
Q.
As a former editor of the Journal of Finance, you are being kind. (Laugh)
Authors sometimes use words other than vagaries to describe the review
process. But I understand there was an unfortunate time lag in what turned out
to be a race with other researchers. You said that any good micro economist
would be led to this result. At least three other very good micro economists were
indeed in hot pursuit. At the time, were you aware that you were in a race?
A.
No, not at all. I was rather well cut off from the mainstream. I was at
Rand full time while I did my dissertation, and then I went to the University of
Washington. I just wasn’t in the mainstream of what was going on in the East
Coast. Jan Mossin was working on some of these issues, somewhat later while
he was at UCLA. But, the others, John Lintner and Jack Treynor were on the
East Coast. I just wasn’t in that loop.
Q.
They had that three hour time advantage over you. (Laugh)
A.
That’s true. Versus all of the advantages we had, including climate.
Q.
Or distractions. (laugh) Dr. Markowitz was surprised, and relieved, when I
pointed out to him that he had actually beaten Roy, who he thought of as a major
7
competitor, by a full three months. I would like to go on record by saying that you
beat Lintner by five months. So if Harry’s relieved, you should be even more so.
With the benefit of what is now almost precisely 40 years since the
delayed publication (laugh) of your paper in September of 1964, what is your
current view of what your 1964 paper established?
A.
I like to call it the original CAPM because it was the first of many
equilibrium theories dealing with risk and return, broadly construed, in capital
markets, or more generally the determination of asset prices and how asset
prices relate to future probabilistic forecasts. If you stand back and ask, what
were the two big practical messages that came out of that undertaking, one of
them certainly, if overly trivialized, is to diversify, diversify, diversify. T formal
result is to hold the market proportions of risky securities, and then lever up or
down to suit your risk tolerance. But, the idea that holding a broad portfolio in
market value proportions was an important and sensible investment strategy was
the first big message. The second message was, yes Virginia, there is a reward
in the form of higher expected return for bearing risk. But not just any risk. It is
much more specific. It is the risk, to use the current broader context, of doing
badly in bad times.
Beta was
a measure, in the particular mean-variance
context, of doing badly in bad times. High beta securities are likely to tank in bad
markets. The key idea was that it is not all risk, but the central societal risk that
an efficient capital market is going to reward with higher expected returns.
I think those were the two big messages. The fascinating thing is that
when we go to much more sophisticated, much cleverer and much more detailed
models of equilibrium, those same two messages keep coming through. Sure
there are variations on the theme, but by and large, at least 90 percent of the
time those messages come through in theories that are much richer than the
original CAPM and other models built on mean-variance assumptions.
Q.
I have some CAPM trivia questions for you. First, we are accustomed to
thinking about all four letters of the CAPM. I am curious.
When did the M get
attached? The title of your paper, for instance, refers to Capital Asset Prices. I
do not recall seeing the M in CAPM or a reference to a Capital Asset Pricing
Model. Do you remember when that particular term was added?
A.
I’ve always thought it was Gene Fama that first came up with that.
8
Q.
Okay.
A.
And as for the Sharpe ratio, I think it was Treynor and Black who came up
with that.
Q.
You didn’t even come up with the label for your own Sharpe ratio?
A.
No I called it (and I still think it’s a better term), the reward to variability
ratio. But I think it was Gene that first used the term CAPM. And of course, in
that era once somebody at Chicago gave something a name that was it.
For
example, the risk free rate was forever denoted Rf.
Q.
That is also on my list of trivia questions. Do you recall your label for the
risk free rate?
A.
I can’t remember it. …
Q.
You liked rho.
A.
Oh, but that doesn’t work now because we use rho for correlations. So,
in retrospect, that was a bad decision.
In fact many of my decisions about
symbols at that time were determined by my typewriter. I had one of the old
typewriters with keys that came up from a near-horizontal position. I finally
managed to get somebody to alter some of the keys. So I had a lower case
sigma, a lower case mu, and I might have had a rho. But that was as far as I
could go. And then there came a time when somebody stole it from my office at
the University of Washington. I was bereft. It’s hard to imagine now in this era
where we all have scientific word processing
and other ways of using any
symbols we want. It was very awkward then.
Q.
I remember that the Journal of Financial & Quantitative Analysis, just
photocopied whatever you produced.
A.
Yes
So if you had to write in the symbols by hand, which some of us did
because we didn’t have modified typewriters, they just photocopied that. I have
also gone back to look at my dissertation a couple of times, and that whole
dissertation was typed by a typist on velum. You had a translucent piece of
paper and produced a a reverse carbon image. If the typist made a mistake,
he or she had to physically cut it out and then tape in a replacement The graphs
in the dissertation I drew with a ruler and free hand. They are really ludicrous. It’s
embarrassing.
Q.
That was state-of-the-art back then.
9
A.
It was.
Q.
Continuing with our CAPM trivia quiz, over the years some of my students
have wondered if the C and A are redundant. I told them it wouldn’t have made
nearly as nice of a title if we called it the AP-M. We need the C in there. (Laugh)
But what inspired you to call it “Capital Asset Pricing”, and did you mean to
communicate anything other than just asset pricing?
A.
That’s an interesting question. I don’t know the answer. I wasn’t thinking
about acronyms. I think I was trying to connote the fact that we are talking about
assets in capital markets. Whereas with assets, perhaps I was thinking, you
would think of cars and trucks.
Q.
So traded assets?
A.
Yes Securities, perhaps.
Q.
Well, I am glad that you [settled on capital assets]… because the buzz
word is, CAP-M. With securities, it would be SAP-M, or something.
A.
Yes,
or SPAM, I’m not sure what it would have been. But think about my
1970 book, it was called Portfolio Theory and Capital Markets. So I must have
liked the word capital at that time of my life.
Q.
Yes. It was a capital idea.
A.
I think that’s been taken by Peter Bernstein.
Q.
Oh rats. Well that’s never stopped me before so—
A.
True.
Q.
Good things, I steal.
Out of personal curiosity, and I might be the only one in the universe to
have ever worried about this particular turn of events, but you mentioned your
1970s book. I happen to have it here. It was the first book I used to teach a
course in portfolio analysis. In this book you reverse the axes from your paper.
In the paper you have risk on the vertical axis and expected return on the
horizontal axis. I have a picture of that graph, which I will show you. But if I were
to put that on the board today, without labels, nobody would recognize it as
having anything to do with the Capital Asset Pricing Model. This is the Capital
Market Line. [Pointing to a page from the article.] The intercept is way down
here on the horizontal axis, and the graph looks very strange. But this is also the
way Dr. Markowitz oriented the mean and variance portfolio problem.
In
10
contrast, by the time of your 1970 book, only six years later, you have reversed
the graph. Under the now standard orientation, expected return is measured on
vertical axis, and risk, whether it is portfolio risk or ultimately beta risk, is
measured on the horizontal axis. I much preferred that switch.
Do you recall
when and how you made the conversion?
A.
I don’t recall in detail. I remember some time after I did the original piece,
I read Sir John Hick’s work. I can’t remember exactly how he had the axes, but
they were different from Markowitz. As I started to try to teach the material, I
found that the newer way seemed much more natural. People tend to think that
a higher Y value is better. You want to get up in the world. So it seemed to me
to be a good idea to put expected return on the vertical axis. Then expected
return more clearly became a good – more is better. As for risk, I flirted with
reversing the axis so as to read it from right to left. But there was no natural way
to do that. So I figured I was stuck with having the horizontal axis show that
more is bad for risk.
It seemed to me at the time, from experimenting with
students, that this was a better way to present the material. And since Hicks had
done it one way, and Harry had done it another, I figured that there wasn’t, at that
point, a fully standard way. So that is what I chose to do.
Q.
Thank you. That cleared up that, that problem for me, and maybe no one
but myself, but I am glad you did [make the change] because I also found it much
easier and a much more natural way to present [the material]. Students take to it
very naturally.
A.
I think so.
Q.
The next question is also departure from Dr. Markowitz in that you focus
on risk free borrowing and lending, and with some caveats that there may be
restrictions, your presentation of the model is based on an assumption that
individuals can freely borrow and lend at a common risk free rate. How did that
particular inspiration, to take a step beyond your mentor in this case, how did you
come up with that idea?
A.
Well that’s easy. It came from Jim Tobin’s separation theorem, which he
developed looking at a different issue. He was interested in monetary aspects.
But he had shown that if you have a set of risky securities, you can simplify the
11
capital market world to a two-asset case and focus on the problem he was
addressing. I can’t give you the date now, I’d have to look it up.
Q.
1958?
A.
Good for you. He had shown that you could separate the problem into
finding the optimal combination of risky securities, which in today’s problems
would be the maximum Sharpe ratio portfolio, and then allocating your money
between borrowing and lending and that combination. So that was pure Tobin.
And it was very helpful algorithmically. I was able to build an algorithm which
could find that portfolio rather than having to find all of the efficient portfolios.
And that led to the equilibrium results.
Q.
In the equilibrium result, we now think of [the symbol] M as the common
designator for the market portfolio. That particular jargon was not in your 1964
article, nor even in the 1970 book. Do you recall when the notation M for the
tangency portfolio began to emerge and when you started using that?
A.
I can’t tell you that.
It may have been in my dissertation.
Curiously
enough in my dissertation, though it was more specifically about the market
portfolio, that was rather an artifact of the single index model. I was trying to be
general, in the 1964 article. I overreached a bit by trying to have a flat section on
the efficient frontier. Generally it can be very close to flat, and it probably is very
close to flat, but it is not quite flat. But when the portfolio came to be called M, I
can’t tell you.
Q.
For the next bit of trivia, what about the term, beta. We now think of the
Sharpe Capital Asset Pricing Model as a relationship involving beta. Yet [the
term,] beta, was not in the 1964 article, or even in the 1970 book. Do you
remember at what point the world coalesced around the term, beta?
A.
I think I was trying to avoid beta, because in statistics, that term
designates a scaled covariance. Of course, that particular scaled co-variance is
what you would call beta in a regression equation if you have chosen to label the
intercept alpha and the slope beta. But other folks began calling it beta at some
point, and so I caved.
Q.
You caved?
A.
That’s, that’s as close as I can give you specifics.
12
Q.
You had the characteristic line early on. So you were you were using
beta.
A.
Yes, the covariance between return and market return divided by the
variance of market return was the slope of a regression line.
I was trying,
especially in the dissertation and I think in the 1964 article, to keep people
focused on the future.
And so yes it is a regression line.
But I wanted to
emphasize that it is a regression line that is fitted to points, each of which
corresponds to a possible future outcome. I was trying to avoid the trap that
almost everybody, including sometimes myself, fell into, saying \ that this is a
theory that says if you look at historic measures of beta, through statistical
analyses of whatever sort, that it will tell you something about, not only historic
average returns, but also future expected returns.
The theory doesn’t say
anything about the relationship between history and future prospects. The theory
says something about expected future returns and future measures of covariance with the market.
Q.
Okay. How about the, the jargon security market line? [The term] capital
market line is all over your 1964 paper, [but the term] security market line is not.
The elements are in the 1964 paper, but that particular jargon again didn’t show
up in that paper, do you remember when that began?
A.
That is interesting. I think that jargon was in my 1961 dissertation. I think
both of them were in the 1961 dissertation.
Q.
We will blame the editors of the Journal for that.
A.
Perhaps. Q. Well, if you do let me know because these trivia issues,
maybe other people don’t care, but as the amateur historian, I am just curious to
know how things [got started], that are now commonplace and everyone uses
them, and it seems to me that they are brilliant. Somebody deserves credit, and
probably it is you, for these brilliant breakthroughs.
A.
Let me beg to differ with you. I don’t see either of those terms very much
anymore – the
Capital market line or security market line. You see them in
textbooks from time to time.
But the thing that does frustrate me is that in
practice it is common for a consultant to justify estimates of expected returns by
showing you a graph with expected return on the vertical axis and standard
deviation on the horizontal axis, where each dot is an asset class. They draw a
13
line and show that the points are pretty close to a straight line. Of course, in the
original CAPM they are not supposed to be close to a line in that space, they are
supposed to be close to a linein E-beta space. Consultants almost never show
that, partly because they don’t really think about a world market portfolio, which is
what you ought to be using as the base for your betas.
Q.
I didn’t mean to accuse [practitioners] of using the academic world…
A.
Fair enough. Q.
I had mentioned that the terms “security market line”,
“capital market line” and “market portfolio” were in your 1970 book but were not
in your 1964 paper. Now that you have checked your dissertation, are those
terms in your dissertation?
A.
I can find the security market line. I haven’t looked yet for the capital
market line. But, but there is the security market line as we said earlier, with the
axes reversed, but the text says this is the equilibrium in the security market.
This was in 1961.
Q.
The same picture is in the 1964 article. So we’re just talking about jargon
as opposed to substance.
A.
Yes. And, and again I haven’t looked for the words “capital market line”,
but you’ve convinced me now that those came about somehow or other between
the 1964 article, which actually was written in 1962, and the book in 1970.
Q.
The next thing [on my list is that] we are accustomed to seeing the
security market line [as an equation]. How about the equation? If I were to ask
my students, “What is the Capital Asset Pricing Model”, most of them would
probably respond with a equation, expected return as linear [function of] the beta
for the security. Do you remember the first time you used the equation or saw
the equation written out rather than a verbal description of the picture you
showed me?
A.
Well, some version is in the dissertation in 1961.
Q.
It’s in the dissertation as well. Okay, then moving on to empirical tests. It
is bold, I think, for any micro economist to presume that some theory they have
discovered might actually describe the real world.
Yet very quickly you
published, in 1966, a study of mutual fund performance where you looked at
average return and [historical] beta. Did you expect to find confirmation of the
security market line and your Capital Asset Pricing Model?
14
A.
I don’t know if I did or not. I guess as I look back, not only on my own
work, but on other work that was done in that period, I am struck with how
incredibly naïve I and some otheres were about empirical work. The idea that
somehow or other you could look at a swatch of history and look at average
realized returns and think that those were really good estimates of ex ante
expected returns, was as , if anything, extremely naïve. Historical measures of
risks and correlations are not too bad as estimates of future risks and future
correlations. But average returns, as we now know and as we should have
known then, can be pretty awful indicators of expected returns.
I think we
expected we could do a better job testing ex ante theories using ex post data
than we had any right to believe. I think most of the people who did those early
tests, including myself, although I did only a very small number of them and did
them very crudely, thought
we were getting a lot of corroboration for our
theories, not only the original Capital Asset Pricing Model, but for extensions of it
and other theories. Later we went through a period in finance where we began to
use more powerful techniques and concluded that, while under the maintained
assumption that historical means are good proxies for expected returns, the
historic data are not consistent with this theory or that theory. But hopefully, now
most people understand that you have to take historical data with a lot of grains
of salt, when you use them to test an ex ante theory of any kind.
Q.
Are you referring to the later studies by Black, for example, where they
broke the periods down into essentially before you discovered the CAPM and
subsequent to discovery?
A.
Well, as a classic case in point, if you take individual securities, or even
groupings of individual securities and look at relationships between historic
average returns and historic measures such as beta and expect that you are
going to get a really crisp indication of what, at any given time during that historic
period, the relationship was between ex ante expected return and ex ante beta,
you are kidding yourself. You don’t even have enough data to measure whether
or not there was an overall market risk premium with any high degree of
confidence, let alone measure things down to those miniscule levels. I think we
expected, and some still expect, far more out of empirical work using historic
15
results than historic results can provide for us.
There just isn’t enough
information in the historic recotd to sort out some of the subtleties.
Q.
When you wrote your 1970s text on portfolio theory and capital markets, I
assume you used it in classes that you were teaching at the time?
A.
I did.
Q.
I used it as well. It is the first text I used for this.
A.
That’s at least two of us that bought it. And our students bought it.
Q.
I was under the impression that [there were] no competitors at the time.
So that was it for the subject matter. There were papers available, and you could
put packets together. Dr. Markowitz had a book, but it really wasn’t geared as an
instructional vehicle. Did you have any idea that you would be able to write a
successful textbook, which is a very different skill from fundamental research?
A.
Well, I hoped I would. I was very fortunate to have been at UCLA and
Rand.
At UCLA, I took a course in economic history. Warren Scoville, the
instructor, required us to write a two page paper once a week on a specific
subject.
He edited our papers as much for style as for substance, and he
insisted that we learn how to write so that somebody could understand what we
were saying. At Rand, all of the papers we produced had to go through an editor
who took out every passive verb and changed it to an active verb, cut every long
sentence into two or three, struck out redundancies, etc., meticulously. What we
produced was readable and not just “academic”. So I was very fortunate to learn
something about how to write in a way that could communicate ideas to people. I
guess I thought I had written enough at various levels that I might be able to write
a successful textbook. And certainly given the interest in a book covering those
subjects at that time, the book was quite successful.
Q.
I particularly liked your personification of people with certain types of utility
functions. I am going to show you a couple that I have reconstructed and ask if
you recall the names of the two individuals that had these particular shaped utility
functions.
A.
The first was probably something like chicken.
Q.
The first was Mr. Chicken.
A.
Good.
Q.
And the second was Mr. Fearless.
16
A.
They were both male. Isn’t that embarrassing?
Q.
I was going to mention that. By giving names to these individuals, you
gave life to a topic that was very dry and very difficult to teach. Students got a
chuckle out of Mr. Chicken, but they always remembered this shape. They could
also easily understand why Mr. Chicken would choose the minimum-variance
portfolio. (Laugh) It allowed me, and others, to teach the algebra of the minimum
variance portfolio, which we couldn’t have gotten away with without it. I did make
one addition. I always wished that you had also identified a person who would
have chosen to put everything in the market portfolio, the tangency portfolio. I
elected to name that person, Ms. Egalitarian. She was a women, in deference to
the women’s movement that was gaining momentum at that particular point in
time, and she was egalitarian because she was willing to trade off expected
return and variance. In your entire book, that was the only change I would have
recommended making. (Laugh)
A.
Let me just suggest that you need to modify that a little bit because there
is a school of thought that argues that cap weighted portfolios are inefficient, and
you ought to weight equally. So I would not want to call her Ms Egalitarian now
out of concern people might think I am advocating equal weighting.
Q.
Okay. (Laugh) Let’s change her last name.
But she would be Ms
something, for sure.
A.
We could do it in French. Actually, I still have that characteristic in the
equilibrium simulators that I am working with now. I insist on naming all my
actors. I either use names from the Social Security registry of the most popular
names, or I come up with names of my own. I have a behaviorist with a kinked
utility function, and I named him Daniel in honor of Danny Kahneman. So if you
look at my current work, you will see that all of the people have names. But they
are not all names designed quite as explicitly to reflect their utility functions.
Q.
Well, it was a very clever strategy. Things just seemed to fall in place [for
teaching] this theory using this approach.
A.
Thank you.
Q.
You have talents beyond your normal academic talents, as a lot of
students that couldn’t have learned the material otherwise can attest.
A.
You are very kind. You are going to make me blush.
17
Q.
Well we’ll just think it’s a suntan here…
A.
Okay.
Q.
You did a lot of early work on portfolio performance, and then you revisited
it, and had another block buster idea with your performance attribution work. I
guess I come back to the same question, how did this epiphany overtake you?
[What made you realize] there was something to be done in this area?
A.
You are talking about returns-based style analysis?
Q.
Yes.
A.
Well, this was born out of necessity.
In 1986 I was interested in the
problems of traditional pension funds. For many years I had given seminars and
worked with pension fund people. It seemed to me that there were some really
interesting issues in that area. Some of the problems could be addressed by
bringing to bear existing theory from finance. Others needed some new theory,
and new empirical work. I wanted to get my arms around those issues a bit more
efficiently than I thought I could as an academic. So my wife and I set up a
research and consulting firm. We worked with people on the staffs that ran
pension funds for AT&T, General Motors, Hewlett Packard, and others, , learning
what their key problems were, and then seeing what could be done to help them.
It became fairly clear early on that what we needed was a single
factor model
that could deal with all the pieces of the fund, the bond portfolios, the stock
portfolios, the Lord knows what portfolios.
Q.
By single you mean integrated as opposed to the one factor?
A.
Yes. I’m sorry. A multiple factor model, but just one model. There were
at that time stock factor models, bond factor models, this factor model, that factor
model. But for high level decisions, which involved asset allocation, manager
selection, manager performance, etc., what you needed was one model with a
reasonably parsimonious number of factors, 10, 15, 20 maybe. If you could map
every single piece of that portfolio onto one or more of those factors, everything
would add up, and you could get the desired addition, subtraction and
aggregation properties.
The question was how we were going to do this. There was no way I was
going to be able to look at all of the securities. A couple of the funds I was
working with at that time had a hundred managers who collectively might have
18
held 3,000 to 10,000 securities. There was no way I was going to look at each
security and figure out how it mapped onto up to 15 different factors. That just
wasn’t going to be feasible.
The question was how to create and implement this grand edifice in a nice
neat consistent way, without doing empirical work which was impossible for me.
I thought initially, ah ha, regression analysis. Let’s regress the historic return for
a particular investment manager’s portfolio on 15 factors, large value stocks, long
bonds, whatever. I did that with some test data and got mostly garbage. So that
was the end of that. Then I realized that one of the reasons it was garbage was
that I was getting estimates such as that a given manager is minus 300 percent
in treasury bills, minus 400 percent in small stocks, plus 900 percent in large
stocks and so on. And I knew that wasn’t true. So what do we have as prior
information to use when we do the analysis? Well, we knew that most of the
managers at that time had no net short positions in any asset class. Well that is
easy. Put lower bonds at zero. In some cases, we also knew they had certainly
no more than 50 percent in a particular asset class. If we knew that, we could
put an upper bound of 50 percent.
That was also easy.
The result was a
quadratic programming problem, and I had quadratic programming algorithms
lined up all around the office for other purposes. So I started trying that with the
data, and voila, I got sensible results.
When I say sensible, I mean this. I would go to the pension fund folks and
say my analysis indicates manager X-Y-Z’s style is like 20 percent of this and 30
percent of that and 50 percent of this other thing. What do you think? And then
they would say yes, I think that’s right on. Perhaps it was the power of suggestion
but probably not Then maybe we would go to the manager. Or we would get a
case where it did not seem quite plausible, and then we would go to somebody,
the manager or the sponsor, and we would figure out that from an economic
viewpoint it was plausible. We got all this corroboration as we started applying
the technique, so we applied it to more managers with more sponsors. It turned
out to be very useful. Was it perfect? No. Could you improve on it with more
detailed information in many cases?
Yes.
But it turned out to be a very
inexpensive, very easily implemented procedure, which could do a very good job.
It is good enough, to give you an indication. For r some of the large pension
19
sponsors with whom I still work, the technique is giving -- out of sample so no
cheating -- R squares in the high 90s.
Q.
Wow.
A.
This is at the fund level. I am not saying I get every single manager right.
But at the fund level, I am explaining a huge amount of the month to month
variation in performance. So it is really a very useful technique. It is a technique
that combines data with priors, or with information from other sources than the
data at hand. For example at Financial Engines, where we use the procedure
routinely across a large group of managers and mutual funds, we use other
information, and not just zero-one bounds.
Q.
You had previously worked with industry, including some early work with
Merrill Lynch on beta methodologies. How did that relationship develop?
A.
Actually, there were some things even earlier than that. At Rand, I did a
lot of practical research as well as theoretical research and application of theory.
So I had been very much in the mode of theory and practice. Theory is good for
practice, and practice is good for helping you figure out what theory to work on
and whether a theory is useful.
So I had been very much in the sort of
ambidextrous state of having a foot in each camp. Sometimes I had one more
weight on one foot, sometimes more on the other. When I first started teaching
full time, I continued to do work for RAND on the economics of computers,
pricing of aircraft landing spots for commercial airliners, etc. I also did a little half
day consulting assignment for IBM implementing my diagonal algorithm on one
of their very early machines.
The Merrill Lynch liaison came about when I was at the University of
Washington. I was approached either by Gil Hammer or maybe Jack Treynor
who asked “Would you like to work with us”. I of course said yes, and I went to
New York once a month for a couple of days, over a numbers of years.
Q.
And you helped them estimate betas?
A.
Well, I helped them with the structure of their beta service, and their
performance measurement and attribution service. I was helping apply, and to
some extent develop, procedures. I am not an econometrician. They had some
very good statisticians and econometricians there, so I didn’t get down and dirty
20
with the details of things like windsorizing the data. I dealt with economics and
the finance theories.
Q.
Early on, they estimated betas for up markets and betas for down
markets. Did you have anything to do with that?
A.
We were all involved with that, speculating about it, playing with it, and
trying to understand what it told us. It was a very cooperative effort.
It was a
very good group.
Q.
You also worked early on with Wells Fargo in the development of products
that we now take for granted, index funds among others.
How did you get
started with that?
A.
I am not entirely sure. Bill Foss and I probably knew each other from
other venues, but when I first went to Stanford, I remember inviting Bill down to
talk to my class.
We talked, either then or later, and felt that we could do
interesting things together. So I started working with Bill and with the folks at
Wells Fargo.
Q.
Did you help them develop products like index funds?
A.
Well they did develop them, and I had a little role in that. I had a call from
a fellow from Samsonite. I think he was the son of the president. He had just
finished an MBA at Chicago. He called me to say he had read, heard about, and
had been taught some of my work. He was thinking they should invest in the
market portfolio, or something of that type. I put him in touch with Bill Fouse, but
the fund
wasn’t actually implemented the right way.
It was closer to equal
weighst than market weights. In any event I believe the first Wells Fargo index
fund was the Samsonite fund. So I had a little there as a marriage counselor.
Q.
In the early days, we did not have passively managed index funds, but we
were still trying to teach MBA students to assume that prices were determined by
investors who held the risk free asset and the market portfolio. There were no
good proxies for the market portfolio early on, and at least my MBAs thought I
was teaching them pie in the sky theory that would never become viable because
the instruments did not exist. They had difficulty thinking that holding 8 or 9 or 10
different stocks could proxy for holding the market portfolio. What did you teach
back in those days?
21
A.
At that time, I did a couple of things. First, I would point students towards
the most diversified equity mutual fund I could find and say, well that’s at least
pretty diversified. Then I would draw a graph, which I am a little sad that I
promulgated in the world, which had portfolio risk on the vertical axis and number
of securities on the horizontal axis. The curve went down and flattened out. You
can look at it and say, ah 20 is enough, and 30 is certainly enough. So I would
make the argument that the thing to do is to be as highly diversified as you could
be and that kind of took care of the market portfolio aspect. In retrospect, of
course, that graph is very deceptive because it assumes equal proportions and
no industry factors, etc., etc.
So it substantially overstates the amount of
diversification you get from 20 or 30 stocks. I think most of us would now say 20
or 30 is not enough, and equal weighting is not the right way to do it. But at that
time, the idea was that there is a way that allows you to get tolerably close to a
market portfolio, perhaps.
As for borrowing and lending, you could certainly put money in the bank,
even if it was not a great interest rate.
You could also certainly borrow on
margin, although I am not sure at the time you could do it for mutual funds. In
some sense, there is is a constant tension between a positive theory and a
normative theory. We now know you can argue, fairly convincingly perhaps, for
the security market line.
You can argue that you ought to use the market
portfolio, possibly with leverage of one sort or the other. But we certainly can not
argue that people do this because most people do not. So if you want to hold
your positive theory up as a theory not only of asset pricing, but also of how
people, in fact, choose portfolios, it obviously fails right out the chute. It is hard,
as you know and as we all know, to convince students to adopt the asset pricing
aspect of the theory when the portfolio choice implications are clearly
inconsistent with observed behavior. In my current work, I build equilibria with
people who have different predictions, different this, different that, different other
things.
What is interesting, and what I think will be helpful to the extent people
adopt this as a pedagogical device, is showing that asset pricing theory results
can hold up even in a world in which people’s portfolio choices are very diverse
and only a minority buy the market portfolio.
22
Q.
On the normative side, are you still a defender of the market portfolio? Is
that something people should pursue if they have no specialized expertise in
security markets?
A.
It is more subtle than that. I believe it is very helpful, at least to a first
approximation, to assume that asset prices probably reasonably reflect publicly
available information, that is that there is semi-strong form market efficiency.
You do not have to hold a hundred percent of the market portfolio. 90 percent
would be good. Then you have to ask yourself if, at least for the bulk of my
portfolio, am I going to adopt the premise that prices reflect people’s predictions?
If so, what does that imply for what I ought to do? The way in which I like to think
about it now is that people come to the market with what I call positions, your
house, your job, your preferences, your utility function, and much more. If you are
really trying to be broad about it, horizon, what have you.
predictions.
Then you make
It seems to me that it is useful to counsel people to not make
decisions based on predictions that are wildly different from those of the average
investor as reflected in market prices. I am being very loose here. I have tried to
be much more careful as I have written about this. But you live in Ohio, I live in
California. You have one kind of income, I have a different kind of income. So
there is no reason we should hold the same portfolio, even if we are four square
with each other in terms of
predictions – about the probabilities of different
outcomes in the future. You need to take the other differences into account,
however. For that reason alone, I am not going to hold what you hold, and
probably neither of us will hold the market portfolio. Similarly with preferences, I
may have one horizon. You may have a different horizon. There are all kinds of
reasons for people to hold different portfolios despite the almost religious belief
that you should not expect to get something for nothing. If you think something is
wildly mispriced in the market in an equilibrium sense, you may well be wrong.
Q.
If someone were to ask you for advice about how to construct the market
portfolio, is that something you could do for them?
A.
Only with difficulty and error. I am on this big campaign to get people in
the industry to provide ongoing, at least monthly, estimates of the market
capitalizations of US stocks, French stocks, US bonds, French bonds, venture
capital, private equity, institutional, quality real estate not already reflected in the
23
stock values, etc. Some of those data are available. Some you can tease out on
the Internet from one place or the other. But most of the data you have to get by
begging and pleading with various people in the industry who do not make the
inforrmation public. They may make the returns public. Wilshire makes the
return on the Wilshire 5000 stock index public every month. But they do not
make available the market capitalizations for those securities, although they have
them, of course. So that’s my current campaign.
There are other big issues, such as what to do about] human capital and
owner occupied real estate, or whether government debt is part of the market
portfolio, or if it just an asset for you and a liability for me as a taxpayer. These
are huge conceptual issues. But certainly the market portfolio is not just the S&P
500; it is not just the Wilshire 5000; and it is not just the US stock and bond
markets. There is a lot more there. Once you get to that point, to go back to
some of our earlier discussion, you have got to think about an equilibrium in
which there are French people and American people, there are Euro people and
dollar people. You need to think about a much more complex equilibrium in
which people’s positions have to do with, among other things, not only where
they live, but in what currency they tend to buy most of their goods, and what
their consumption baskets are. Increasingly we need to think much more broadly
than the wildly simple version of the Capital Asset Pricing Model which assumed
away huge swaths of the real issue. That being said, all theories assume away
huge swaths of real issues.
The test of the theory, as always, is have you
included enough of what really matters to give you something that leads to better
decisions and better understanding than you would have had otherwise. We
have obviously come a long way since the original Capital Asset Pricing Model.
Q.
Staying with practical advice, have you thought about might be
appropriate for a young investor with $100,000 to invest, who has no specialized
knowledge about securities and just wants to have a reasonably diversified
portfolio?
A.
The first practical advice, of course, I would say go get help. Until not too
many years ago, it would make no sense for somebody with $100,000 to get help
because it would cost them $50,000 to get the help, or at least $10,000. Now
24
you can get good help electronically from a number of sources for very nominal
amounts of money. That is what I would start with.
But that is not the way you wanted to frame your question. So let me
restate your question. Assume that someone can’t go get help, and I have to tell
him in a paragraph or two what to do. That’s it, and I can’t ask any questions. All
I know is here is this young person who is 30, you said young, so we will call it
30. He has $100,000, and I really don’t know much more. If you had said this is
a person who is average in every respect—
Q.
Let’s change the question to average in every respect.
A.
Oh that’s easy. World market portfolio, thank you very much, I’m done.
Q.
But how do you do that?
A.
Oh, then you buy as best you can estimate what the market proportions
are for the major assets that are out there, and you can find an index fund
typically for each of the broad classes. For example, you can get the Vanguard
total stock market fund, which covers the US stock market very well. You can
get the total market value bond fund, or whatever it is called, which covers the
US bond market very well. There is also a Vanguard fund that is a 60/40 fund.
So you can either do that or invest in the two funds separately. Do the same for
international stocks. Buy highly diversified low cost index funds with low turnover
and low management fees, to give yourself exposure in those areas, and do it in
basically world market proportions.
Of course, a young person is not average. An average person is middle
aged If you weight by dollars or weight by dollars, Euros, and such, an average
person is probably more than middle age because after all, in the market, dollars
vote, not people. There are more dollars representing old people. So market
prices tend to be set by older people and richer people, partly because richer
people are older. Price are also set by both Euro people and dollar people. So it
is a bit of a cop out to say that an average person should hold the world market
portfolio because I have never met an average person. So unless you happen to
be a citizen of the world, and you are just the right age the market portfolio is not
likely to be the best choice. For example if this person is younger than average
maybe that involves a tilt with a little bit more aggressive stance. I would also]
25
like to know about his or her job. Is this a person with tenure or a person who
works in high tech in Silicon Valley? It makes a difference.
Q.
Fair enough. So you are really going back to the advice, and you are
uncomfortable giving advice without knowing the particulars.
A.
Precisely. Just like a doctor. Without knowing what the symptoms are,
you don’t want to prescribe a standard drug.
Q.
I can understand that. You mentioned that [it matters] if you live in the
United States, or in France, or Euro country, or non-Euro international country.
Do you think a certain amount of home bias is appropriate in investments, a tilt
toward your own domestic consumption bundle, or is that not appropriate?
A.
If you play with the data a bit and assume either that currency risk is an
issue, or that getting rid of it is costly, then what seems to come out of the data,
at least as I’ve looked at it, is that home bias in the bond area makes a lot of
sense. The advantage of diversifying your bond portfolio abroad is not sufficient
to significantly overcome either the currency risk or the cost of getting rid of the
currency risk. So in the bond area I think home bias makes a lot of sense. In the
stock area, the advantages of international diversification remain pretty
substantial. The advantages are possibly not as much as they used to be, with
globalization, although one can read those data in different ways. But there are
still some pretty big advantages. So I would think that home bias on the fixed
income side, for sure. On the equity side, there probably should not be a lot of
home bias. But at the end of the day, it really depends on your consumption
bundle.
Q.
On the same general theme, assume that a young couple is probably
going to buy a house in the near future but they do not own any housing right
now. In effect they are short housing in some sense. Should they have a tilt
toward more real estate, such a REITs?
A.
Well, again it depends on whether you think of a lifetime portfolio including
human capital, etc. I haven’t really thought through the issue of what to do if
you’re going to buy a house. I’ve thought through the human capital issue at
some length, but I beg off on this question.
Q.
That’s fine.
And you may want to beg off on this one too, the baby
boomer generation is about to hit retirement age. Presumably many are looking
26
at a change in housing, and perhaps even moving into a retirement home. If they
have that in contemplation, should they tilt their portfolio toward, I don’t know if
there is such a thing as a retirement real estate REIT, but sunbelt type housing
for people from Columbus, Ohio or even colder climates. Is that something they
should be thinking about as they approached retirement?
Or is that again
something off the radar screen for you?
A.
Now you are talking about my new field. I have declared that when I get a
few other things wrapped up, I am going to become a researcher in retirement
economics. You can take that either way, if you will. It seems to me, and I’m
sure it seems to you, that as we get to the point where we think about precisely
the things you’re describing, that the economics profession hasn’t really started
modeling big elements of the decisions you face at a later age. I’m thinking of
annuities, long term health care issues, housing, etc., etc. There are some big
issues there. I am playing around with a state preference tree structure and a
pricing kernel view.
I haven’t gotten to the point where I can answer your
question, but I will tell you what my neighbors, next door here have done, which I
find fascinating.
They live in Carmel. Their daughter lives in Pittsburgh. Not
Pittsburgh, California, Pittsburgh, Pennsylvania. And they are determined they
are not going to end their days in Pittsburgh. So they bought a unit in a three
stage retirement community out in Carmel Valley, which has independent living,
assisted living and skilled nursing. They pay the dues, which cover three meals
a day, but they still live here. They go out there one day, have dinner and stay
overnight, and then they come back. They view this as basically an insurance
policy. It is an insurance policy that is not generic, but specific. They know that
they will always be able to get in there whether they go into independent living, or
into assisted, or skilled nursing. They have basically bought forward for that
stage of their lives, which is very interesting. Being financial types, we tend to
think about buying a contract of some sort that will pay money so you can buy
later. But very often there is an adverse selection issue for anything of that sort.
You may have the money, but they won’t take you if you are too feeble or if you
are really need heavy nursing. Q. If you have enough money they’ll take you
(laugh).
A.
Well that’s true. That’s true.
27
Q.
A feeble versus money trade-off frontier perhaps?
A.
Yes. And, of course, they are bearing a risk that the outfit will go under
so. So I think those are big issues for people of a certain age. And partly
because most of the people doing research in finance are not of that age, I don’t
think those issues have been sufficiently addressed.
Now with all the baby
boomers coming to the point where they are going to be facing those issues, I
think we are beginning to see some serious research activity in this area. I think
we will see more. These are tough issues, really tough. So I plan to play around
with them some more.
Q.
What advice would you give to a young researcher just starting out, a
young Bill Sharpe?
A.
If you can, arrange to have been born in 1934 (. There weren’t very many
of us, and good economists had not spent a lot of time on the economics of
uncertainty. So there was a lot of low hanging fruit. It was rather easy. It is
much harder now. You never know how much of this is just old age talking –
thinking it was better when we were kids. But I think financial economics has
become so sophisticated, and there are so many first class people looking at a
huge range of issues.
As with anything else, get lucky. That’s another obvious piece of advice.
But I think it’s A) more fun, and B) potentially higher risk, with higher expected
return to try to look at problems that have been under-researchedOr just look at
things in totally different ways. I find that however practically is a lot of the
edifice that we in academics and the industry have built on mean variance
foundations, the state preference approach is superior in many ways. A) It is
simpler, and B) you don’t get in some of the strange blind alleys that you get in
with continuous distributions and perhaps continuous time. But it is very hard for
me to know what makes sense for somebody starting out.
Q.
All right. Next question. You have read a lot of papers in your career.
Are there any that you really enjoyed so much or just were thrilled with so much,
that you secretly wished you had been the one to write them?
A.
Oh many, many, many . Q. What’s at the top of your list?
A.
I don’t know. I haven’t thought about that question. I think in many ways
the most beautiful papers in the entire field, by my definition of the field, are Ken
28
Arrow’s incredible paper originally written in French and then in English. Q.
Did he write it in French or was it translated for him?
A.
I think it was translated. He was invited to give a talk at a conference in
France, which I think he told me he gave in English.
Q.
I have one paper in French too, but I can’t read it.
A.
Yes. Well, I think Ken actually has quite a bit of French, but I don’t think
he wrote it completely. But in that paper, which in English was 9 pages or 11
pages, he laid out the whole basic state preference approach. Then Gerard
Debreu, in a very small book did the whole theory. Then he said, well there is
uncertainty to deal with, so I’ll write a chapter on uncertainty.
I believe the
chapter was four pages long. M of financial engineering that came, although the
financial engineers may not know it, from those two bodies of work. If you think
about how much of what we do every day and teach every day can be
understood and taught better with that paradigm than with some of the
paradigms we use, you have to conclude that those are without question some of
the most brilliant pieces in terms of their implications and their sweep.
Q.
Well, you at least got to come close because you had a very early
contribution on the binominal option pricing model, did you not?
A.
Well, it wasn’t as early as their work, but it certainly, it usedthe state
preference approachQ.
That didn’t satisfy you fully?
You still wish you’d
written the Arrow & Debreu work?
A.
Oh no. I’m happy having written what I wrote.
Q.
Okay.
A.
I was taking your question somewhat more broadly, what do I think were
among the most brilliant things and the most seminal pieces in the whole area of
financial economics. And it’s got to be Arrow-Debreu, and I am not going to
differentiate between the two of them.
Q.
You answered the question very well, and I think you may have answered
my next question as well. You just got to it ahead of schedule. You anticipated
the question perhaps.
But are there any unsolved problems that you look
forward to, at least trying to solve or, or wish you could solve?
A.
Well I’ve been working on a number of things in the last couple of years.
In more academic pursuits, I have been trying to get my arms around asset
29
pricing and portfolio choice. So what else is new? But I’ve been using a state
preference approach and dealing with the equilibrium situations where people do
differ on positions, preferences, and predictions. In particular I’ve tried to actually
get serious about people not being in agreement on probabilities. And looking to
see the extent to which some of our conclusions from models such as those
using representative investors either are or are not robust. In particular, I’ve
been directly looking at issues that arise when people have preferences that are
not mean variance, and possibly not of the standard constant relative risk
aversion variety that we sometimes use. I’ve been bringing in some of the ideas
from prospect theory and behavioral finance, and using, as I mentioned briefly
earlier, an equilibrium simulation approach where I create people. give them
positions, preferences, predictions and initial holdings, and then let them trade
with each other until they do not want to trade anymore. Then I investigate the
properties of the resulting equilibrium. That is a new technology -- certainly for
me, and I think pretty much for the profession. I think it has real promise as a
pedagogical device.
I also think it has real promise as a research device
because you can look at much more complex systems than with closed form
models. It has the disadvantage that it’s very hard to know when you’ve really
got a result rather than just an artifact of a particular simulation. So you have to
keep giving the simulator different initial conditions and different situations until
you can convince yourself perhaps that you have a general result. I have also
found this kind of approach useful as a sort of a theorem producer. You play
around with cases, you see results, and then you say, I wonder why that result
came out? Sometimes you can figure out why and that might lead you to a
stylized closed form approach.
I love computers, I love computer programming, and I think we can do a lot more
with them. People are doing a lot with, Monte Carlo simulations. They are doing
a lot with numerical solution procedures, and I think building equilibrium
simulators is a very useful undertaking. If hope to get my code to the point where
somebody else can use it, Then I can try to make it available on the Internet and
see
if
anybody
agrees
with
me.
And retirement economics. Don’t let me forget retirement economics.
30
Q.
I would like to mention three names, and after each name just give me
your reaction, short or you can even pass on it if you don’t have a reaction for
me. The first is Harry Markowitz.
A.
Well as I was enthusing about Arrow-Debreu, I thought in retrospect --
whoops. Harry Markowitz basically started the field. He started all that has come
from mean variance. And he started at least half of what is now standard practice
in sophisticated investment shops in the world as well as in corporate finance
groups and others. If you think about impact on practice as wekk as impact on
academics, it is very hard to think of anybody else. Obviously Arrow, over a wide
range has had a huge impact, but I Harry started the deluge. He’s up there at
the top of the pantheon in finance and financial economics.
Q.
Next name. Merton Miller.
A.
Merton Miller and Franco Modigliani. In terms of their seminal work they
are sort of [interchangeable]. Making an arbitrage based argument. Think about
how that changed people’s thinking and teaching. Go back to the finance
textbooks that preceded their work. They are downright embarrassing by today’s
standards. Mert and Franco just shook the finance field as it was then, corporate
finance aspect in particular, to its foundations. They made people rethink. And
then, of course, Mert did huge amounts of work in a number of other areas. He
was up there at top. It’s not the field in which I have done most of my work. But
if I were in corporate finance I would be saying about Merton Miller, and Franco
Modigliani what I just said about Harry Markowitz.
Q.
If only because of the big announcement today, but thinking specifically
about the contribution on the equity premium puzzle, what are your thoughts
about Edward Prescott?
A.
Well I must admit I don’t know more than a couple of his pieces. And I
haven’t looked at those for a long time. And I don’t think I have ever met him. I
think of him as a macro economist who has done a considerable amount of work.
I looked at his bibliography just before we sat down and it is overwhelming. But I
only know a small piece of his work. The piece I know is very good, and very
important. I don’t think we are yet quite clear whether the puzzle exists, because
it could be an artifact of the data. I go back to some of the things we said earlier
about how hard it is to even tell from data, in the very long run over many
31
countries, what the premium is let alone why it is. It might also an artifact of too
narrow a construction of the utility functions that drive the markets. There are a
number of possible explanations. It may be that we don’t measure the complete
market including human capital. Who knows? There is a plethora of purported
explanations for the puzzle. But if nothing else, just raising the puzzle and saying
you can’t keep using the simple models you were using in a world in which the
premium seems to be in the nature of 5 or 6 percent, or 8 or 10, whatever it was
when he, they wrote the paper, was a huge service. But I don’t know enough
about his entire body of work to give you a good assessment. I’m sure if I did, if I
were in macro economics I’d probably say what I said about Harry Q.
Well
that’s the last of my questions. Is there anything you would like to add for the
audience, American Finance Association?
A.
Well only to say that
finance is a wonderful field. It
it is marvelous
because it has some of the toughest intellectual problems that you can come up
with, and yet it has all sorts of practical applications. To the extent we can
understand these things better, we can help ordinary human beings figure out
how to arrange their lives so that they are as well off as they can be. It’s got
social value. It’s got commercial value. And it’s got intellectual value. It’s a great
field. I’ve had a great ride in it, and I recommend it to whomever is watching.
Q.
On that note I think we will conclude the interview.
A.
Thank you. It has been a great pleasure.
32