The Nobel Prize winning creator of the Capital Asset Pricing Model takes another look at his work.

William Sharpe won the Nobel Memorial Prize in
Economics in 1990 for his contribution to Modern Portfolio Theory.
Sharpe shared the award with Harry Markowitz. Markowitz won the prize
because of his ideas about diversification. Sharpe won it because he
devised the Capital Asset Pricing Model (CAPM), a formula for
determining the theoretically required rate of return-and, therefore,
the price-of an asset when added to a well-diversified portfolio. These
ideas form the basis for Modern Portfolio Theory, and that is the
theoretical underpinning for many of the world's investors, including
many of the smartest independent financial advisors.

So now that Prof. Sharpe has written a book,
Investors and Markets, that adds a new twist on his earlier work, it
raises the eyebrows on some of the most pointy heads in the financial
world. Sharpe says his new ideas do not depart from CAPM and Markowitz,
but add a new tool-State-Preference Theory. Sharpe's use of
State-Preference Theory, which originated in the 1950s at the same time
that Markowitz was doing his research, adds an individual's preferences
to Modern Portfolio Theory. As Sharpe is first to say, these new ideas
may take years for advisors to put into practice. No tools yet exist
for implementing them. But being aware of this new idea is important
for advisors. So are Sharpe's doubts about a permanent premium for
value and small-cap stocks, and his cautionary comments about research
by the two professors whose ideas are responsible for one of the most
successful mutual fund groups used by financial advisors, Dimensional
Fund Advisors.

Gluck: So, what got into you? What made you write the book?

Sharpe: I was asked some years ago to give a series
of lectures at Princeton University. Once a year they'd have somebody
come in and give three lectures on a subject of their choosing, and
then it's turned into a book. It seemed to be a good opportunity to put
together what my thoughts were about the area I've been working in
heavily for many, many, years-asset prices, risk and return,
equilibrium-and to try to get my arms around both what I'd done and
what other people have done, and maybe have some new thoughts. So I
gave the lectures in 2003 and then worked on turning it into a book.
For a number of years, I've tried to think about finance in terms of
this State-Preference approach, to think of the future as one in which
the world can be in a number of discrete states, and each one has a
probability...

Gluck: Sorry to interrupt, but what do you mean by discrete states?

Sharpe: As opposed to continuous. I'm sorry, that's
mathematician jargon. It's either A or B or C or D. The market is
either up 10% or 11% or 12%. It rains or it shines. It's cold or it's
warm, or it's really hot. An easy way to think about it is a
spreadsheet. You've got a column in the spreadsheet, and each row is a
different thing that could happen. Only one of them will happen, but
you don't know which one. The best you can do is say, "There's a 10%
chance it'll be this row and an 8% chance it'll be that row."

That's opposed to the kind of Mean Variance notion,
the traditional paradigm that we've used a lot in finance for a long
time, the Markowitz portfolio theory/Capital Asset Pricing Model
(CAPM), in which you have a continuous probability distribution. The
market could be up 10.12346% or 10.12347%, etc. Which row will it be?
And then you can think in terms of each column. If you end up in row
12, then stocks will do this, bonds will do that, hedge funds will do
this, General Motors will do that, General Electric will do that. You
think about it in that manner, and that has a couple of advantages.
First of all you can be much more general in certain respects than you
can with traditional theories, and second, the math's a lot easier. You
don't have to have very well tuned mathematical and statistical skills
to even approach the subject. So I've tended to think of things in that
way for a number of years, and I've taught some of my courses in that
way. So I thought, let's take that approach and let's think about
broader and more realistic worlds than we usually think about.

Gluck: How is this more realistic than the
traditional way of thinking about investing, the way that you helped
invent, in which you rely on Mean Variance Optimization and the Capital
Asset Pricing Model? How did you go from here to there?

Sharpe: Theory is always an abstraction and a
simplification of reality and, at best, an approximation. You can't get
your arms around enough of reality to do a totally realistic theory. So
with theory, you always abstract and approximate. With the Markowitz
portfolio analysis and CAPM we made a lot of simplifications and
approximations, hoping that we're looking at the essence of the problem
and not missing something really important. Then, over the course of
the last few decades, people have been saying, "What if you think about
the impact of taxes, both on how you choose a portfolio and how the
market will price assets?" There's been this progressive attempt to
bring in more elements of reality and trying to focus on the most
important ones because you're never going to get them all in. I view
these ideas as part of that progression even while it looks like a
paradigm shift...

Gluck: It does look like you've made a major shift in how you look at investing.

Sharpe: Because it's a different apparatus. But it
really isn't a huge shift in thinking. For example, if you take the
simulator, which I'll talk about in a second, and you just tell the
simulator that people have certain preferences, voilà, you get all the
results of Markowitz and CAPM. So it's a more powerful mechanism, which
as a special case gives you all the key results of the traditional
theories. But whereas the traditional theories have been limited
because you can't deal with a lot of complexity, you can deal with more
complexity with this approach. As I was preparing the lectures on this,
I thought I'd really like to have some examples of what happens when
people disagree about the future, because we know people do disagree
about the probabilities of different things. What happens when people
have preferences that are not only different from what Markowitz and
the CAPM assumes, but more like the kinds of things that the
behaviorists are now telling us characterize human beings.

Gluck: What were the preferences assumed, by the
way, by Markowitz and CAPM? And how does the new State-Preference
approach you are now working on differ from the Markowitz/CAPM approach?

Sharpe: Let me be careful, because I'll get in
trouble with Harry (Markowitz) because we have somewhat different
approaches to this. But the crux of the matter is that Markowitz and
the CAPM, in its original manifestation, assumed that people choose
portfolios strictly on the mean of the variance of the portfolio return
distribution-which is to say, you tell me two things about a portfolio
and that's all I need to know. What is its expected return and standard
deviation? That's all I want to know. You give me those two numbers and
I'll choose my portfolio among a set of portfolios based on those two
numbers for each portfolio. Markowitz assumes you are willing to do
that and CAPM assumes everyone is willing to make portfolio decisions
this way. Now why might that be true? There are two conditions under
which it would be true. One is, every single portfolio you can even
imagine has a nice probability distribution, which, if you tell me the
expected return and the standard deviation, I know the whole
distribution, I know the probability of any possible outcome. And the
easiest case for that is everything is bell-shaped distributions, the
normal distribution we learned about in class. So that's one kind of
world in which this would be a great assumption. The other kind of
world in which it would be a great assumption is, "All I care about are
those two numbers. I don't care what the probability of distribution
looks like. You give me those two numbers, that's all I need, all I
care about." Now for this to be the case, I must have a particular kind
of preference, which is called quadratic utility. So you have these two
possible rationales for those approaches. But what we know is people
are increasingly coming up with investment products that have very
non-normal distributions: hedge funds and protected products. You go
down the list. And there are all these exotics, which, partly
intentionally, have weird distributions, what's called tail risk-small
probability of a disastrous outcome. That's the classic hedge fund
approach. So the first rationalization doesn't hold as well perhaps as
it did 40 years ago, at least for some people in some cases. The second
rationalization, the preference assumption, the quadratic utility, if
you look at it, it doesn't seem to conform with how most people really
think about having bad things happen or good things happen. So you're
left with traditional approaches-Markowitz, CAPM are approximations.
And, of course, we knew all along they were approximations. The
question is: Are they good enough approximations or can you do a better
job? And is it worth doing a better job? And ultimately, are they 95%
good enough? Fine, if so. But maybe they're only 85%. Or maybe, at
least for your client, they're only 75% good enough. So what I was
setting out to do was come closer to some aspects of reality. Here is a
way of thinking about it, a way of looking at it. And, as I prepared
the lectures, I wrote a simulation program and I fell in love with it
as a way to really get your arms around the issues. So I spent an awful
lot of time and a huge amount of effort trying to write a program that
people could use for free. Working on the program is one of the reasons
it took me so long to turn the lectures into a book.

Gluck: And that program is on your Web site?

Sharpe: Yes, and it's available for anybody to use at www.wsharpe.com.
In order to make it free, I had to write it in C and C++ so you could
compile it for free. Anybody who wants to could look at the source code
and documentation and enhance it or modify it and distribute it freely.

Gluck: Had you ever coded some other things like this before?

Sharpe: Oh, I write programs. I've been writing programs probably every day of my life. And I did a little C programming way back when. It's a difficult language for research, but it produces very fast code because you're getting close to the machine level. So it's great if a program will be widely distributed. I use Matlab for most of my work, which is much more research-oriented.

Gluck: Getting back to the theory, you're saying Mean Variance
Optimization and CAPM are all still valid, and your recent work simply
builds on that.

Sharpe: Yes, and what's interesting about this is that there has been a
tendency over the years to say, "Look, the CAPM assumes that everybody
agrees on the probabilities of future possible events, and we all know
that's not true. So to hell with the CAPM and all its implications." Or
people say, "CAPM assumes that everybody cares only about the mean and
variance of the portfolio return and that's not true. So to hell with
CAPM." There's a tendency to say this assumption or that are untrue in
the real world, so forget about the implications of CAPM. The two key
implications I take out of the CAPM are what I call in the book the
Market Risk Reward Theorem and the Market Risk Reward Corollary. The
first says only market risk is rewarded with higher expected return,
where market risk is how badly you do in bad times. And the second is,
if that's true, why take on nonmarket risk? Why don't you just
diversify and expose yourself mainly to the broad risks of the capital
markets? So much of the book and the simulation process says, "OK,
let's agree that people disagree on the probabilities of future states
of the world. Now let's see if those results in whole or in part
survive reasonably well. Of course, what you find is the corollary.
Let's assume people have sources of income outside the capital markets,
which they surely do, and let's assume people's preferences aren't
quadratic, which most of them surely aren't. Does that mean you just
throw away the notion that market risk is at least the major form of
reward? My reading-and people can read the book and run simulations-but
the basic market risk-reward theorem comes through pretty well. It
doesn't hold precisely, but if you're expecting to get a higher
expected return for bearing some kind of risk other than the risk of
doing badly in bad times, you've got to have a pretty good story. And I
think that's really the most important conclusion of the CAPM. I'm
convinced that's still a very strong result. It's not complete, not
perfect. You can create plenty of stories when it's not totally true or
when it's not even predominantly true. But I come out of it saying that
you've got to convince me if you found some sort of a risk to take that
is independent of what's going on with capital markets as a whole, and
we're going to get a reward from that.

Gluck: So then, what you're saying is we knew the CAPM system was
imperfect. And now this is an effort to make it more real-world?

Sharpe: Yeah, that's fair. No theory will be fully real-world. There's
no way you can bring all of the elements of the real world into a set
of equations or a computer program and get it all in there. So the
question is, at what point do you have enough of the real world in your
theory or your computer program so that you're comfortable going ahead
with the implications as a matter of how you run portfolios?

Gluck: How has your real-world experience at Financial Engines influenced your ideas? [Financial Engines, founded by Sharpe, provides expert financial advice for investors, particularly those planning for retirement.

Sharpe: Over the course of the years, we've worked with a lot of people to see how they choose among different investment approaches and help them narrow their choices of investment approaches to alternatives that seem, based on theory and empirical work, to be more desirable. Now I don't do all the day-to-day empirical and analytic work, but seeing what happens when you deal with a real world of tens of thousands of investment alternatives and all the gory details and trying to predict into the future, and then show people those predictions and see how they react to them and what choices they make in terms of their savings, in terms of how they choose among riskier or less risky alternatives. We do that, obviously. We do it online with thousands of people. But we've also, over the course of years, done focus groups and test cases and all the rest. So I've learned a lot. There's no question about that.

Gluck: Could you use your simulation software to make real-world simulations?

Sharpe: No. It's to test ideas. To actually advise somebody as to how to invest a 401(k) plan, you need the fruits of ten years of many, many people's labors and a lot of money.

Gluck: So what are the practical implications that you hope are going to be realized from looking at markets the way you are now and using the State-Preference theory to make investment decisions?

Sharpe: Well, I'm just beginning to explore that. I have a paper on my Web site (www.wsharpe.com) under Working Papers called, Expected Utility Asset Allocation, and I'm working with a fund, a large endowment and university retirement plan fund. We're doing some experiments to try to bring some of these ideas into the asset allocation decision for a large institutional fund. It's in its early days, so I wouldn't predict how practical that's going to work out. We're getting some ideas about how we could actually use this kind of approach. But it's in its early days. As I tried to figure out for whom I was going to write this book, I ended up deciding I was going to write it for academics to try to convince them to change the way they taught finance. In using this approach, you can look at a lot more issues in what are actually simpler ways. I'm trying to influence people who will be teaching MBAs and undergraduates, trying to bring ideas that are taught now at the Ph.D. level down to a broader student body. If that's successful, then hopefully in time the industry will start shifting and implementing ideas that use this approach as well. But that's in the future. A lot of the work in financial engineering already uses the State-Preference approach.

Gluck: This approach is already used at the
institutional level by the rocket scientists at the giant firms, right?

Sharpe: That's right, exactly. In some ways, what I'm trying to
encourage people to bring [is] the rocket science of the Ph.Ds. in math
at the giant firms-and the abstract models used by Ph.D.-level courses
in some major universities-to a broader audience. If it works, that'll
be done in the academy initially and then it'll spread to your
readership.

Gluck: Please explain some of the basics of State-Preference theory. It's been around for some years, right?

Sharpe: It goes back to Gérard Debreu in the '50s, when Harry was writing. Think of that spreadsheet I spoke about. Each row in that spreadsheet is something that could happen in the future. Only one row, however, is actually going to happen, but you don't know which one. What people do a lot in the industry, they get 20 years of history or 40 years or 100 years, and you know each row is a year. Say you've got 50 years of history and each row is a year, and each column is the return on an asset class-bonds, stocks, non-U.S. stocks, real estate, what have you. What people often do is, they take that table and they compute the average return for each of the asset classes and the standard deviation and the correlations, and then maybe they modify them to take into account their current views of the future or something about theory. Then they run it through an optimizer, a là Markowitz. What this approach says is that maybe you want to just leave that table as it is, make your decisions as to how likely you think it is that next year will be like 1939 or instead like 1941, and take into account how you feel about losing 30% of your money and run a different kind of optimizer. That's a different way of using the data that many people already use.

Gluck: And you're using judgment.

Sharpe: And use judgment by saying, in effect, "Well, next year is as
likely to be like 1939 as it is to be 2005." But you could say, "I
think, given my view of the world, that 1939 returns are more likely
than 2005." The great advantage is it allows you more freedom. The
disadvantage is it allows you more freedom. But at least you know what
you've assumed.

Whereas in a traditional procedure that some people follow, you in
effect assume that next year is as likely to be 1939 as it is 2005, and
maybe that's not really what you want to assume. Now you can make those
assumptions and still use the traditional methods. You also assume that
you have a particular view about a really bad outcome vis-à-vis a
really good one. Whereas with this broader view, you can say, "No, no,
no, for me losing 20% is the end of the world. I'll get fired from the
investment committee, my client will go elsewhere and I might get sued.
I don't want to take a chance, however small, of that happening." In
Traditional Mean Variance approaches you can't really do that.

Gluck: But you break these judgments down into different preferences. Could you explain some of that?

Sharpe: Let's take it now to the financial advisor. If you think about the whole relationship between an investment professional and a client, basically the client has positions, preferences and predictions. I myself have positions-for instance, a house in Carmel and I consult in the investment industry. A lot of my financial situation is different from that of my neighbor. My neighbor was a journalist and he's now retired. Other friends of mine are in different professions and they're different from people who live in France, for example. So we're all different in various important ways.

Gluck: Especially the French.

Sharpe: Especially the French. [Laughing] Viva la difference! So people
are different and every good advisor knows that. So the first thing you
need to do is to mold an investment portfolio to take into account the
differences between your client and sort of the great average client
out there in the world at large. People have different preferences. One
client says, "Look, this is only a small amount of my wealth, I've got
all this other wealth. So let's go for it." Another client says, "I'm
willing to take some risk but I can't take any risk of having less than
this amount, because if I have less than this I have to go to a lousy
nursing home instead of a good one." So I put in preferences.

That's where the client is the expert. The client knows how he or she
feels about various kinds of risk. The client knows what his other
sources of income and wealth are. The client is the expert. On the
other hand, the client typically doesn't know much at all about what's
available in the capital markets: What kind of instruments are there,
what kind of risks are associated, future risks, with this kind of
portfolio or that-what can you reasonably expect to get in the long run
from this kind of portfolio. So the advisor is the expert on the
capital markets and the opportunities, the trade-offs and the ways of
implementing.

The whole idea is to bring the client's expertise, his or her positions and preferences, together with the advisor's expertise about the available opportunities and probabilities. So you bring those two sides together and you get the right answer for that particular client. I think it's really important that you have a model, have a gestalt in your head, as to how those elements can be explicated and how they can be brought together to get the right decision. The book is trying to give you a framework as a professional advisor to think about that, so that you ask the right questions to your client and you get the inputs you need so that you know enough about your client and can bring that together with your professional investment expertise and advise the client.

Gluck: And those factors were never part of investment decisions in your earlier approach?

Sharpe: Well, they were, but we summarized the client. We said Client A
has a risk aversion of this and Client B has a risk aversion of that,
and that's about all we did. But if you look at Mean Variance theory,
if you look at the CAPM, everybody is just a little risk aversion
model: I'm conservative, you're aggressive, someone else is moderate.
That's about it. Now, I'm in many ways trying to bring in to formal
procedures and computational procedures things that every good
financial advisor has known and practiced for years. Is this news to a
good financial advisor? Of course it's not. Yes, we've known this all
along. This is trying to be a little more rigorous about how we do this
process. It's thinking more about how capital markets function and what
the impact might be on the trade-offs available, in terms of risks and
returns.

Gluck: Are there any software products on the market now that are moving in this direction?

Sharpe: Not that I'm aware of, certainly nothing that I'm aware of that
a financial advisor could pick up and use off the shelf.

Gluck: Is there another way to get at it, to maybe approximate it and
do it yourself? Maybe do it with the kind of spreadsheet, the kind of
table you were talking about before?

Sharpe: That's what I'm working on in this Expected Utility Asset
Allocation paper. It is basically a set of recipes. How that will work
in practice, I have no notion yet. But I'm working on it. As a matter
of fact, I've been working on some examples for a talk I'm giving next
month.

Gluck: So it'll give advisors a basic framework?

Sharpe: Yes, but it is a very basic framework. Again, I'm just
beginning to experiment with real data to see what happens when you
actually try to apply this approach, and it's too early for me to
predict it's going to be the be-all and end-all approach. Just as it
took us decades to figure out how to use Markowitz and the CAPM in ways
that would actually give plausible results, it may take a while for
this as well.

Gluck: By the way, State-Preference theory, you said it was around in the early '50s?

Sharpe: It's evolved. In the '50s Harry said, "Here's a way to advise a
client as to what portfolio to hold. Here's a way to choose a portfolio
when you have predictions of risks and correlations and expected
returns." Harry's focus was, "You get your predictions from wherever
you get them and here's how you use them to come up with a good
portfolio." It's what I call normative economics, meaning that it tells
you, "Here's what you should do." It's advice-oriented. Ken Arrow and
Gerard Debreu were asking a different question. In an efficient market,
what determines the prices of financial assets and therefore the risks
and returns? It was what I call positive economics.

Here is how the world would work in this abstract kind of world. Those
of us that worked in the CAPM were in the Arrow-Debreu camp, in the
sense that we were asking how the world worked, positive economics. Of
course, the trick is to give your advice with a gestalt as to how the
world works. In other words, Harry said, "Wherever you get your
predictions, here's how to use them to give advice." CAPM, and before
that Arrow-Debreu, said, "Well, here's what the predictions ought to
look like because they come from a capital market." Then, the trick is
to say, let's get predictions that make sense and use them using
something like Harry's approach, or this broader expected utility
approach. So there are both sides of the coin. Ken and Gerard were very
much in an equilibrium economics context, and not even in a heavily
financial sense. The financial aspect, the uncertainty aspect, was kind
of a page or two at the end of Ken's article and four pages at the end
of Gerard's book. But over the years economists and financial
economists sort of started developing the Arrow-Debreu approach and
bringing it more and more to the point where you have what you have now.

Meanwhile, of course, the mainline in the investments industry was working off Harry's Mean Variance approach, the CAPM, which built on that, and all the developments that came thereafter. So you had these parallel tracks. Meanwhile the financial engineers are coming up with things that are basically State-Preference but coming at it in a different way, and in many cases not even knowing that philosophically they're in the same camp. One of the things I was trying to do in the book is to show that all the Mean Variance can be thought of as a special case of this broader State-Preference approach and try to get an integration of some sort.

Gluck: So the investment advice industry developed Markowitz and CAPM. But academia did not discard State-Preference.

Sharpe: What happened was State-Preference was growing mainly in the economic departments and the finance departments and the business schools were coming predominantly from the Mean Variance tradition-until in the last decade or two, at which point the advanced research tended to move over to the State-Preference side.

Gluck: Will advisors be able to utilize this book?

Sharpe: Some of the reviews of the book have said absolutely correctly,
"Well you know this is too hard for practitioners and it's too verbose
for academics. Academics would have much preferred the formula, the
math, instead of all this verbiage. They're absolutely right. I was
trying to say, "Look, Ph.Ds. and finance professors teaching Ph.D
courses, this is a way of doing something differently when you go to
the MBA classroom and the undergraduate classroom. You can bring these
ideas to the MBAs and the undergraduates and here's the way to do it."
And so to some extent, I'm trying to illustrate how easy it is to make
these ideas understandable. So the book has this strange, ambivalent
focus.

Gluck: One of the points you make late in the book is that advisors are good.

Sharpe: You better believe it. I like to differentiate it and
trivialize investing versus betting. Investing is saying, "You are my
client. You are a unique individual with a unique situation, a unique
family and so on. If you're coming to me because I can find you a hot
stock or a way to beat the market, forget it. That's not what I do. But
I know how the markets work, and I can find the way to invest your
money so that it fits your situation given what you can get in the
capital markets." I call that investing. It's really important for
everybody concerned to know where the investing is and where the
betting is. I think most personal financial advisors would say their
main function is the investing function, helping clients understand how
to use the capital markets to fit their personal situation. That's a
remarkably valuable function.

Gluck: Getting people to use Financial Engines has
been a challenge, from what I can surmise, and you changed your model.
Why?

Sharpe: We changed to a management model. With the original model,
every employee with an account online could get his or her predictions.
They could experiment with different portfolios, and we gave them our
advice. We still do all that. For a certain part of the work force,
this is great. They love it, they use it. But you sort of peak at some
point. With some companies it's with 70% of the employees, and with
other companies it's 20% of employees. We wanted to reach more than
even 70%. We wanted to provide something that would work for everybody.

So our typical engagement now is, everybody gets on paper the
personalized forecasts, recommendations, etc. at least once a year.
Everybody has access to an online account of the traditional sort. And
those who choose can just check a box and we will manage their account
for them. It turns out the managed accounts are a major part of our
business model. So we can reach everybody, one way or the other. We're
much happier with that, and employers are much happier with that.

Gluck: In your book, you raise doubts going forward about value and
small-cap stocks, and comment about Eugene Fama and Ken French's work.
I thought it was interesting that you were taking that on and being out
front with that.

Sharpe: Are there times when value really does better than growth? Yup.
Are there times when growth does really better than value? Yup. So, are
value and growth factors in terms of risks and correlations in the
markets? You better believe it, and I did a paper on this myself many
years ago. We've known this for many, many years. Barr Rosenberg, I
think, probably was the first to really identify that. So are
value-growth risk factors, is that a risk factor, is small-large a risk
factor? Yup. Absolutely. So that's one element, and there's nothing
inconsistent with the standard theories or new theories of that. The
controversial part is somehow or other can you expect to do better with
a value tilt or a small tilt than you "should."

Gluck: Permanently.

Sharpe: Yeah, is there some sort of a premium here, and in the future?
Will there be, in the future, a premium for tilting towards value
and/or tilting towards small? If the answer is yes, why would that be?
There are two approaches. One is "Well, because you get the higher
expected return from value, because there's something about value that
a lot of people don't like." Like maybe if there's a real depression
all those companies, or most of those companies, are going to disappear
from sight, in which case it's a rational reward for a kind of risk
that doesn't manifest itself very often and maybe hasn't been seen
since the early '30s. That's one possibility. If so, fine.

The other alternative is, well, you know, people are dumb. The markets are screwed up. Value stocks are stocks, many of which have very low prices and they're too low, and ultimately the market will wake up and say, "No, no, we overdid it on that one," and the price will rise. So the question is whether this is a market inefficiency or just a manifestation of a risk, which you know is remote but there. And again, different people have different approaches. I'm very cautious about saying there is a free lunch out here. Here's a reward for which there's no commensurate risk. What I tried to point out in the book is if you look at the evidence from the Fama and French empirical studies, it's really evidence that comes from a very small part of the market. The way they did their studies, basically, most of that result comes from 10% or 5% of the value of securities out there. The idea that value investing is a free lunch, I would be reluctant to advise my clients to operate on that premise.

Gluck: And how about small-cap advantage?

Sharpe: What we found is that small cap appears to
have a lower premium than the value premium. I was on the board of some
mutual funds that had value tilts in the '90s, and we were having our
head handed to us. It was a terrible place to be in the industry. It
turned out all right, but what you've seen in the last couple of years
is, everybody has discovered value investing.

Well, it's been a great run for value stocks, but
there have been periods that have been terrible runs for value stocks
and you know there are definite risks in that. It's just more
comfortable to predict that the long-run rewards for value investing
will be more commensurate with plausible estimates of the risks. If you
want to bet on them, fine, and if you want to invest in them, fine. But
at least know what you're doing, and what you're assuming about the
extent of which the markets are dumb or smart.

Gluck: It's interesting because so many advisors,
including many of the smartest advisors that I know, are big fans of
the DFA funds.

Sharpe: Well DFA certainly advocates value, and to
some extent small investing, and if you read what they put out publicly
it sounds as though it's something for nothing-to me, as I read some of
those things. But if you talk to some of the principals, they'll say,
"Well no ... it could well be that this is just a premium that you're
going to get 95% of the time, but there is a 5% or a 2% or a 1% chance
that you could get really wiped out. Again, I find that it seems to me
that they're pushing this as something that is-it's not something for
nothing, it's a pretty attractive deal. And again, I think there's a
difference between the views of some of the people connected with DFA
and other people connected with DFA as to whether it's a free lunch or
not.