1. The Capital Asset Pricing Model – The Sharp-Lintner-Mossin Model
The most celebrated idea of modern portfolio theory (MPT) is the Capital Asset Pricing Model (CAPM).
William F. Sharpe, often cited as the originator of the Capital Asset Pricing Model, published his original
analysis in an article entitled “Capital Asset Prices: A Theory of Market Equilibrium Under Conditions of
Risk,” in the September, 1964 edition of the Journal of Finance. Concurrently, John Lintner published his
similar treatment of the CAPM model in “The Valuation of Risky Assets and the Selection of Risky
Investments in Stock Portfolios and Capital Budgets,” in the February, 1965 edition of the Review of
Economic Statistics. Finally, Jan Mossin’s treatment of CAPM appeared, independently of Sharpe and
Lintner in a January, 1966 issue of Econometrica in an article entitled, “Equilibrium in a Capital Asset
Market.” The CAPM, developed independently by Sharpe, Lintner, and Mossin, uses Tobin's Theorem and
applies it to what economists call a general equilibrium model. Tobin's Theorem is about what happens
when a single individual investor faces the problem of choosing a best portfolio among all of those
portfolios that the investor can afford. CAPM asks the question: if every investor acts like the investor
in the Markowitz-Tobin world, what will be the prices of assets in equilibrium.
What do we mean by equilibrium? The term equilibrium means that (planned) supply equals (planned)
demand. An investor is in equilibrium when he owns the assets he wants to own, given prices and expected
returns, variances and covariances. If each investor is in equilbirum, then the reigning prices of each asset
form a set of equilibrium prices. The Capital Asset Pricing Model is a theory about how assets are
priced in equilibrium.
a. The Relationship Between the Return of An Asset and An Index -- A Preliminary
Exercise
Suppose we have information about the rate of return of some particular asset over a rather lengthy period of
time. We also have information about the rate of return of some group of assets, which, for simplicity, we
shall refer to as an index. What can be said about the relationship between the return of the individual asset
and the return of the index? Are they related and, if so, how? Suppose we have annual data on rates of
return as in the following table:
Year
Asset
Index
1970
1971
1972
......
......
1990
1991
1992
5%
-2%
12%
.....
.....
8%
-5%
2%
8%
1%
10%
....
.....
13%
6%
-4%
How can we take the data in the table and make statements about the relationship between the return of the
particular asset and the return of the index? Suppose we plot the data as in the following diagram:
Return of Individual Asset
Return of Index
Each point in the diagram represents the return for one particular year in our table. The vertical coordinate
is the rate of return of the asset and horizontal coordinate is the rate of return of the index. Notice that we
have drawn a straight line in the diagram. We did that to suggest that perhaps the relationship between the
returns is a linear relationship, i.e. the relationship can be described by a straight line. If the relationship is
linear, what is it?
Suppose we try to find a line that best fits the data. What do we mean best fits the data? In order to answer
this question, we need some way to describe the distance between the various points in the diagram and any
straight line that we might draw in the diagram.
Suppose we begin with an arbitrary line defined as:
y = a + bx
Let y represent the return of the individual asset and let x represent the return of the index. If we have a
specific value of x, say x1978, we can plug that value into the above equation and get a predicted value of
y1978. This predicted value is not generally going to be identical to the value for y1978 that is inserted in
our table or exhibited in our diagram. There will usually be a discrepancy, which we shall call an error and
describe with the letter e1978.
This means we need to rewrite our equation to reflect the implicit potential error in the equation:
y = a + bx + e
The errors are really differences between some arbitrary line and the various points in the diagram. Notice
the errors ei and ej in the following diagram:
Return of Individual Asset
e
e
j
i
Return of Index
If the errors were zero for each observation, that would mean that all the points in our diagram fall along the
straight line. Otherwise the e's will be sometimes positive, sometimes negative, and sometimes zero. The
positives and negatives might even tend to cancel each other out, even though individually the e's might be
very large in absolute value. How well does all of our data fit some arbitrary line like y = a + bx. The e's
measure how well the line fits. But, to avoid having e's cancel each other out, let us square the e's and then
add them all up to get an idea how far from the line the typical point is.
Before we do all this, let us add to our notation. Let yt and xt represent the return to the asset and the return
to the index in year t. We can now talk meaningfully about things like the sum of the yt's, the sum of the
xt's, and their respective (sample) means and (sample) standard deviations. Let x represent the sample
mean of the xt's and y represent the sample mean of the yt's.
Then:

x
1992
t 1970
and:

y
xt
23
1992
t 1970
yt
23
These are sample (of 23 observations) means not the true mean returns. We don't really know what the true
mean return is. We can try to estimate the true mean by calculating the sample mean in this fashion.
Similarly, let sx and sy be the sample standard deviations of the xt's and yt's. Then:

1992
sx 
x
t 1970
t
x

2
23
and:

1992
sy 
_
(y t y ) 2
t 1970
23
Again, these are sample standard deviations, not true standard deviations. We don't have any way of really
knowing the true standard deviation. The sample standard deviation can be thought of as an estimate of the
true standard deviation.
Where is all of this headed? We want to find the line that best fits the data in our table and our diagram.
Why not find the one that minimizes the squared errors? In other words find values of a and b that
minimize the following sum:
1992
1992
1992
2
yt  a 2  b 2 x t 2  2yt  a bx t 








e

y

a

bx

y

a

bx




t
t
t
t
t
t 1970
t 1970
t 1970
t 1970

2
1992
2
Continuing to expand the interior of the parentheses:



 t 1970 y t  a 2  2ay t  b 2 x t  2bx t y t  2abx t  t 1970 a 2  y t  2ay t  b 2 x t  2abx t  2bx t y r
1992
2
2
1992
2
2

Now, bringing the summation sign inside the parenthesis, gives:
  a 2   yt  2a  yt   b2 xt  2ab xt  2b xt yr
2
2
With appropriate substitutions:
e
2
t
 na 2   y t  2any   b 2 x t  2abnx  2b  x t y t
2
2
where n ( = 23) represents the number of observations. So much for the algebra. To minimize the above
sum, we need to differentiate the sum with respect to a and with respect to b and set the resulting equations
equal to zero.
i.
Minimize the Sum of Squared Errors
Mathematically, we intend to minimize the squared errors by appropriate choices for a and b.
We begin by differentiating the squared errors in respect to a and b and set the results equal to zero:

(1.)

a
 et
(2.)
et
2
b
2
 2an  2n y  2bn x  0
 2b  x t  2anx  2  x t y t  0
2
The first equation can be simplified to:
(1.)
y  a  bx
The second equation after substituting in for a using (1.) becomes:

2b



x t  2 y  bx n x  2
2
x t y t  2b

x y
2
x t  2n x y  2bn x  2
2
t
r
0
eliminating the 2's and simplifying:

b
2
x t  n x y  bnx 
2

x t y r b
 x
2

 nx  nxy 
2
t
x y  0
t
t
Separately, consider the following expression and its expansion:
x

2
t
x 
x
2
t
 x
2
 x  2x t x 
2
t
2
2
 n x  2n x 

x t  nx
2
2
plugging this expression in where appropriate gives us:
(2.)
b
x  x  nx y   x y  0
2
t
t
t
Again, separately consider the following expansion:
x  xy  y  y x  x yx  x   y x  x y  y x  nx y
t
which means that:
t
t
t
t
t
t
t
t
x  xy  y   y x  nx y  n yy  nx y   x y  nx y
t
t
t
t
t
t
Now, making a substitution of this last expression into (2.) gives us:
(2.)
b
x  x  x  xy  y  0
2
t
t
t
Solving (2.) for b yields:
x  x y  y


 x  x 
t
t
2
t
By inspection this expression equals the sample covariance divided by the sample variance of the index
return:


x, y
 2
x
We have switched from b to  to indicate that we have a very specific value of b in mind. We will do the
same with a, converting it to . We conclude with the following two conditions that the best fitting line
must satisfy:
(1.)
y  a  bx
(2.)  

x, y
 2
x
where the 's are sample covariances and sample variances.
ii.
We Have Found a Beta!
Beta, written symbolically as , is the single most widely used piece of jargon in finance theory.
What we have constructed is an empirical beta, not to be confused with the theoretical beta that plays
such a prominent role in the Capital Asset Pricing Model. The beta of CAPM appears to be identical to
the one that we have constructed here, but it is not identical. Later, when we speak of the theoretical beta in
the CAPM context, we shall mean the covariance divided by variance, which seems the same as what we
have here. But the covariance and variance in CAPM is the population covariance and variance, not the
sample covariance and variance. The sample parameters could, of course, be thought of as estimates of the
population parameters, but they are different concepts in principle. We can always calculate sample
parameters. We cannot always necessarily calculate the population parameters, especially the population
parameters that are relevant to finance theory. It is important to consistently maintain this distinction
between sample parameters and population parameters.
What does our beta mean? Beta measures the relationship between an individual asset's return and the
return of some index. Usually, the index is a basket of assets which typically will include the individual
asset of interest. This is not necessary, though. The index can be any arbitrary index and beta will still
attempt to measure the linear fit of the return of the asset to the return of the index.
Notice very carefully what beta is not. Often, when asked, investors say that beta measures the volatility
(which always means variance in finance jargon) of return of an asset, usually a common stock. Such
investors are confusing beta with variance. It is possible for an asset to have a very high variance, but bear
no particular relationship to the index used in the beta calculation. In this situation, the asset return will be
very volatile, but the beta might be zero. Similarly, it is possible to construct examples of assets with high
betas (by suitable choice of index) but relatively low volatility (variance). We conclude that beta is not
volatility or variance and need not be in any way related to volatility or variance.
I.
The Startling Conclusions of the Capital Asset Pricing Model
The Capital Asset Pricing Model is a model that asks what happens when asset markets are in equilibrium.
CAPM assumes the conditions of the Markowitz-Tobin model -- that investors are risk averse and that
assets have known means, variances, and covariances with each other.
CAPM Conclusions:
for every asset i:
ER i   R f  i ,M ER M   R f 
with:
where:
M  1X1   2 X 2   3 X 3 ......  n 1X n 1   n X n  i 1  i Xi
n
M is the market basket containing every asset Xi that is positively priced in equilibrium. The
proportions, i's, of each asset in M, are the percentage of total market value of all assets represented
by the total market value of asset i.
Ri is the return of asset i. RM is the return of the market basket, M. Rf is the return of the riskless
asset. i,M is the covariance between the return of asset i and the return of the market basket M
divided by the variance of the return of the market basket.
What do the CAPM conclusions mean? The first equation:
ER i   R f  i ,M ER M   R f 
has come to be known as the Security Market Line. It says that the expected return net of the risk free
rate for any asset is equal to its beta (with the market) times the expected return of the market net of the risk
free rate.
Consider the expressions
E Ri  R f
=
E RM  R f
Why are we subtracting the risk free rate, Rf, from these expected returns? Taking no risk at all will always
earn us the risk free rate, Rf. Therefore, if we want higher returns we must take some risk. The return that
we gain from taking risk is always relative to the risk free rate. We often call this difference between the
expected return of a risky portfolio and the return from the riskless asset the risk premium. It shows the
additional expected return that an asset must produce to compensate for its riskiness. One way to interpret
the Security Market Line is the following: The risk premium earned by any asset is, on average, equal to
beta times the risk premium earned by the total market portfolio. This is truly a revolutionary conclusion.
Notice that the variance of the ith's asset's return plays no role in accounting for its expected return or
its risk premium. Variance of an individual asset's return does not, in equilibrium, matter at all. What
matters is the relationship between the return of an individual asset and the return of all assets taken together
-- the market basket, M.
Another way of interpreting the security market line is that an asset's return depends upon its contribution to
the return of the overall market portfolio return. No matter how volatile a stock's return might be its
average return will depend solely, in equilibrium, upon its contribution to the total portfolio return of the
entire market as assets. This is the startling conclusion of modern portfolio theory.
II.
Diagramming the Security Market Line
We exhibit the Security Market Line diagrammatically:
Expected Returns
E[R i ]
Security Market
Line
E[R ]
M
Rf
Beta
1
The Security Market Line applies to any asset or portfolio in equilibrium. In particular, the market basket,
which consists of all assets weighted by their relative market values, has a beta equal to one:
CovM, M   M

 2 1
2
M
M
2
 M ,M
It is worth noting that the beta of a portfolio can be calculated by averaging the betas of the individual assets
that comprise the portfolio. The weights used to average the betas are identical to the weights used in the
construction of the portfolio. If a portfolio, P, is defined as:
P  1X1   2 X 2   3 X 3 .....  n 1X n 1   n X n  i 1  i Xi
n
then P's beta can be constructed as follows:
 P ,M 
III.
CovP, M 

2
M
 
n
i 1
i
i ,M
 11,M   2 2,M  .... n  n ,M
The Tobin Theorem Conclusion Re-emerges in CAPM
We have very quietly ignored a major conclusion of CAPM. The Tobin Theorem re-emerges. Each
individual in CAPM owns a portfolio that consists of at most two assets: the riskless asset and the market
basket portfolio. Borrowing and lending stories are exactly analogous to the Tobin Theorem. The only
difference is that the E* portfolio of the Tobin Theorem becomes the market basket, M, in CAPM.
This conclusion, that individuals that wish to take on any risk at all, should own at least something of
everything is not often emphasized in finance theory. I think some feel that this is an unwelcome
consequence of CAPM. The spirit of this conclusion is the same as the Tobin Theorem. Diversification
creates a very efficient mix of assets. Indeed all worthwhile assets are included in the diversification
process. Only those assets of no market value are left out of the market basket, M.
Is this a reasonable conclusion? After all, we do not observe individuals buying a little bit of every asset.
Or do we? Perhaps, this seems more sensible if we attack the problem from a slightly different point of
view. Suppose one individual, in a CAPM world, owns three times as much GM stock as Eastman Kodak
stock. What can you say about the relative ownership of GM and Eastman Kodak stock by other individuals
in the same CAPM world? The answer is the ratio will be the same for all individuals who own any risky
assets at all - three times as much GM stock as Eastman Kodak stock. Indeed it is obvious that according to
CAPM it must be true the GM's total market value must be three times the total market value of Eastman
Kodak. Are these reasonable conclusions? As opposed to what? If CAPM approximates reality, we
should find that the ratios of risky asset holdings are similar across different individuals. This may well be
the case of large asset groups like housing, common stocks, bonds, and so forth. This is an empirical
question and a tough one, but it cannot be immediately dismissed as unreasonable.
The dramatic growth of broadly diversified mutual funds over the past fifty years may well be a testament to
the Tobin Theorem. (The mutual fund industry was in its infancy when Tobin’s Theorem was first
established, so that Tobin’s theorem anticipated the tremendous growth in the mutual fund industry that has
since taken place). But, will we all end up owning the same portfolio?
The crucial assumption in CAPM is that all individuals (or institutions or whatever) see the same assets and
agree on the means, variances and covariances. This clearly isn't true in the real world -- but it may, over
time, be getting to be more true with the increased technology and improved communications that have been
applied to financial markets. As we tend to view assets more nearly the same way, we may end up more
nearly satisfying the Tobin Theorem -- mutual fund conclusion of the Capital Asset Pricing Model.
These remarks are intended to counter the idea that the Tobin Theorem flavor is a wholly unrealistic
conclusion of CAPM. It may be that individuals perceive differences among assets in different ways
through lack of common information. That lack of common information may dissipate as technology makes
the same information available to more persons more quickly. CAPM may be forecasting a future where the
Tobin Theorem holds more broadly for more investors.
i.
The Capital Market Line
Expected Returns

M
M
Rf

M
Standard Deviations
The capital market line is pictured in the preceding diagram. It shows the collection of optimum portfolios
that should be selected by any market participant. Depending upon each person’s risk aversion, that person
will select some point on the heavy line that begins at Rf (the risk free rate) and continues in a northeasterly
direction. Those who don’t like risk will choose positions to the left. In the extreme, a very conservative
investor might choose to have all of their wealth in the risk free asset and end up right at the vertical axis at
the Rf point. Between Rf and M, investors are choosing to hold some of the risk free asset and some of M.
To the right of M, investors are holding more M than their wealth. The implicit assumption is that they are
borrowing to the right of M to leverage up additional purchases of M. This assumes that they can borrow at
the risk free rate and buy more M.
Notice the slope of the capital market line:
 M R f
slope 
M
There is a very natural and simple interpretation to this slope of optimally chosen portfolios. As you gain
excess return (return above the risk free rate), you pay for it in increased standard deviation. For any
portfolio that is optimal, the following must, then, be true:
 M R f  P R f

M
P
The above equation says that all optimally chosen portfolios produce the identical per unit (of standard
deviation) excess return, where excess return is return net of the risk free rate. The trade off is a simple
linear function. For a given amount of increased standard deviation you always get the same amount of
increased excess return. Note that this applies to optimal portfolios. This does not apply to assets generally
or to assets that are not optimal portfolios. This is an important distinction between the capital market line
and the security market line which applies to all assets and portfolios whether optimally chosen or not.
IV.
Proving the Capital Asset Pricing Model Results
A Restatement of the Capital Asset Pricing Model:
Assume:
(1.) All investors are risk averse
(2.) The means, variances and covariances of all assets are commonly known to all investors
Conclusions: In equilibrium, it will be the case that:
for every asset i:
ER i   R f  i ,M ER M   R f 
with:
n
M  1X1   2 X 2   3 X 3 ......  n 1X n 1   n X n  i 1  i Xi
where:
M is the market basket containing every asset Xi that is positively priced in equilibrium. The
proportions, i's, of each asset in M, are the percentage of total market value of all assets represented
by the total market value of asset i.
Ri is the return of asset i. RM is the return of the market basket, M. Rf is the return of the riskless
asset. i,M is the covariance between the return of asset i and the return of the market basket M
divided by the variance of the return of the market basket.
Proof:
The Tobin Theorem result with M replacing E* is obvious.
To prove the fundamental equation of CAPM ....
V.
The Roll Controversy
It has been argued by Richard Roll since the mid 1970's that the Capital Asset Pricing Model cannot be
tested empirically and therefore is a vacuous theory. Roll argues that there is no clear way to get at the real
world counterpart to the market basket, M, of the Capital Asset Pricing Model and getting close, Roll
argues, doesn't help. According to Roll, a large proxy basket that contains many assets, but is not M, may
predict, through calculated betas, expected asset returns, buy may not be M-efficient. Similarly, Roll
argues, if you did have an efficient, after the fact, large asset basket, then the fundamental theorem of
CAPM must hold exactly simply due to the mixing algebra of portfolios -- there is nothing to test. Roll
argues that the only true test of CAPM is to test the M-efficiency of the market basket and, of course
that is impossible.
Roll's arguments do not mean that "Beta is Dead," as several articles in the popular press claimed after his
original article was published in the Journal of Financial Economics. Beta is far from dead. Remember that
the major theme of CAPM is that covariances, not individual asset variances, are what matter in determining
the attractiveness to an investor of a portfolio of assets. We saw a taste of this by examining what happens
to an equally weighted portfolio as you continue to add assets. What we found is that, in the limit, the
variance of the portfolio depended only upon the average covariances of the included assets. Individual
asset variances played no role in the limit. From this point of view, Beta will never really be dead. The
shifting of emphasis away from individual asset variances towards covariance relationships will alway be
with us so long as overall portfolio variance matters.
i.
Using the Capital Asset Pricing Model for Performance Evaluation
Recall the fundamental equation of the Capital Asset Pricing Model:
ER i   R f  i ,M ER M   R f 
which holds for any asset, or any portfolio, i. This equation has been used by investment consultants to
assess the quality of the investment managers employed by large institutions. The idea is to calculate the
beta of a portfolio and then use the above equation to determine what it should earn on average. If the
actual earnings exceeds that predicted by the above equation, then performance is judged to be very good.
If the actual earnings fall below that predicted by the equation, then performance is judged to be
unsatisfactory.
Roll's criticism of the CAPM is devastating to the performance evaluation technique described here. Unless
the return used in the above equation is for the market as a whole (which it obviously cannot be), then the
results can end up depending upon which proxy for the market as a whole is used. Using one proxy might
get a satisfactory result; using a different proxy might get an unsatisfactory result. Indeed, investment
consultants often use more than one index for performance evaluation, which effectively exposes their
dilemma.
Using the CAPM for performance evaluation is, by dent of Roll's criticism, unscientific.
ii.
The Sharpe Ratio
A commonly used statistic to appraise a portfolio (or an asset) is the Sharpe Ratio, first mentioned in 1966
by William A. Sharpe, one of the early exponents of the Capital Asset Pricing Model. The Sharpe Ratio
(ex-post, after the fact) is:
Ave Return of the Portfolio – Ave Return of the Market
Standard Deviation of Differential Returns
Or, in symbols:
RP – RM
σP-M
where the symbols have the obvious meaning. “Differential Returns,” or σP-M , means taking the difference
in returns between portpolio P and portfolio M for each time period and then calculating the standard
deviation of this set of data using RP – RM as the mean of the data.
The idea here is to raise the question as to whether the new portfolio, P, should be added to the existing
portfolio, M. A special case arises when M is the riskless asset. In that case:
RP – RM
σP-M
becomes:
RP – Rf
σP
where Rf represents the risk free rate return. In this special case where you are adding a portfolio to an
existing cash portfolio, the correct choice will always be the one with the highest Sharpe Ratio (assuming
that all of the normality assumptions used earlier still apply).
Generally, when the comparison portfolio is something other than the risk free asset, the Sharpe Ratio is not
very important all by itself because the covariance between the new portfolio, P, and the benchmark
portfolio, M, plays a very significant role for all of the usual Capital Asset Pricing Model reasons.
Another frequently cited statistic is the Information Ratio, which is simply the calculated mean return
divided by the standard deviation. This ratio is also of limited applicability since covariance issues are not
taken into account.
iii. Arbitrage Pricing Theory
Steven Ross, in 1978, developed an alternative theory of asset prices, that encompasses the CAPM as a
special case. Ross's theory is not an equilibrium theory. Instead, Ross employs the no-arbitrage principle
that we shall see later in our discussion of the Modigliani-Miller and Black-Scholes theories. Ross's theory
permits the use of economic variables to explain asset prices (and returns). This approach compares to
using solely return covariances (betas) as explanatory variables in CAPM. In Ross’s “Arbitrage Pricing
Theory,” the Capital Asset Model emerges as a special case.
A. The “Efficient Market” Hypothesis
1. EMH Once Ruled The Roost
The Efficient Market Hypothesis (EMH) is the statement that current (asset) prices accurately reflect all
known information. Distinctions are made as to whether “all known information” includes private, perhaps
“inside,” information. The strongest version (most expansive form) of EMH defines all known information
as including private information. The weakest version covers only publicly available information such as
the kind of information a reasonably well informed investor might possess (or be able to possess) by reading
newspapers and keeping up with television and available electronic media sources.
If markets are efficient (if EMH is true), what does that mean and not mean? EMH is often taken to mean
that investors should invest “passively” by purchasing well diversified portfolios and simply hold them and
not trade one stock for another within the portfolios. Those in the money management business take a dim
view of EMH, because EMH suggests that money managers who pick stocks are doomed, in time, to failure.
The EMH has always been a constant source of friction between academics, who mostly believed in it, and
money managers who despised it. Since money managers (who deal with the public) are required by the
SEC (the Securities and Exchange Commission) to fully disclose their results (known as their “track record”
in the industry), it is easy to test the proposition that money managers add value (or that they do not add
value). Most of the empirical work on this subject points to the same conclusion: Money managers
cannot, on average, provide investment returns superior to passively investing in an appropriate index (such
as the S&P500). There is a huge literature on this topic and while, on occasion, an article appears that
seems to make some systematic investment strategies look like winners (see Fama and French, 1992), time
eventually consigns these empirical treatises to the dustbins. More data with the passage of time inevitably
shows money managers or various investment strategies losing out to the mindless investment strategy of
portfolio indexing.
Does the fact that money management is so difficult mean that the EMH is true? Up until October, 1987,
most professional economists (especially finance economists) believed in the EMH. The stock market crash
of 1987 changed all of that.
2. Volatility is “Too High” for EMH
On October 17, 1987, the Dow Jones Industrial Average (the Dow) dropped 509 points from above 2200 to
slightly above 1700, a net decline of 22 percent in a single trading day. What has that drop got to do with
EMH? If prices, on average, are 22 percent lower on Tuesday than they were on Monday (October 17th,
1987 was a Monday), then according to EMH there should have been some important changes in the
information about stocks (or the economy in general or something) that precipitated the decline in asset
prices. There was no such information change discernable to market observers. In fact, for the year as a
whole, 1987 was extremely volatile. The Dow began 1987 just above the 2,200 mark and ended it at about
the same place. Along the way, the Dow average topped 2,700 in July and bottomed in the 1700 area in
October. During all of that volatility, there were not any significant information changes concerning the
economy or concerning most large capitalization stocks. So why did prices change so much?
This question of why volatility is so high relative to information can be seen in a slightly different way.
The simplest way to think of the“fundamental” value of a company is to think of it’s value as the present
value of its future cash streams. Its normal to think of these future cash streams as the dividends payable to
shareholders. Even if these dividends are small, one can envision a future large (sometimes called terminal)
dividend, which gives shareholders back all the cash the company has earned from reinvesting all these
years. Writing the usual formula down, gives us:
Pr ice 
Div t
1  rt 
t

Div t 1
1  rt 1 
t 1

Div t  2
1  rt 2 
t 2
 .............
Div t  n
1  rt n t n
where the price is equated to the discounted sum of dividends for the next n periods of time. (t+n is the
expected liquidation date with Divt+n representing the liquidating dividend).
Lets take a closer look at the right side of the above equation. There are basically two sets of variables:
future dividends and future interest rates. Both sets of variables are expectations since those dates are in the
future. How much do such expectations move around, change from day to day? Short term interest rates do
move around from time to time, but do expectations of future interest rates change much? Not much. If
future rate expectations are volatile, that fact should be exhibited in the volatility of the long term treasury
bond, since that issue would be most vulnerable to fluctuations in the expections of future interest rates.
What about expected future dividends? Do the expectations of future dividends change much day to day,
week to week, month to month? Surely, the answer must be no. Dividend expectations are sticky and
subject to change only occasionally and certainly not week to week or month to month.
What this means is that the variables on the right hand side of the above equation are not very different from
one day to the next (the expectations of the variables on the right hand side we mean). If that is so, then the
left hand side should not permit of much variation either. But, in practice, the left hand side, price, is much
more volatile than the information that seems to determine the price.
We conclude that stock price volatility is probably too great to be consistent with the Efficient Market
Hypothesis. A number of articles in the finance literature in recent years have made this same point in a
more detailed fashion. The originial articles on this topic were those of Robert Shiller (American Economic
Review, 1981, pages 421-438) and S. LeRoy and A. Porter (Econometrica, 1981, pages 555-574). Two
excellent surveys of this literature are: 1.) John Cochrane’s article in Journal of Mathematical Economics,
1991, pages 463-485; 2.) Steven LeRoy’s article, “Stock Price Volatility,” in Statistical Methods in Finance,
Vol. 14, 1996, edited by G. S. Maddala and C. R. Rao.
3. If EMH is not true, then what?
If EMH is false, does that mean that the money managers are right? Does a false EMH mean that the
market can be beat and that money management is a value added activity? The good news is that the market
is, in principle, beatable because EMH is probably not true. The bad news is that the overwhelming
preponderance of the evidence continues to demonstrate that money managers cannot beat the market.
4. Why can’t money managers beat the market averages?
If the market is beatable in principle, then one would suspect that it is probably beatable in practice. Why
don’t money managers do better than they do? Here are some potential reasons that money managers might
perform poorly (relative to indexing):
a. Money managers tend to buy stocks that are popular
The risk of buying an “unpopular” stock is that if the stock performs poorly, the money manager will be
subject to more criticism (and potential loss of business). If you’re going to be wrong, it is best to be wrong
in a crowd, not all alone. End of quarter “window dressing” is an activity at the end of each quarter, where
money managers buy stocks that have done well very recently. They may have just bought them, but their
customers may not realize that and will be appreciative of the fact that their managers “own” the winners.
VI.
Money managers tend to invest in “ways” that are popular
The risk of investing in the wrong way is similar to the risk of buying unpopular stocks. Money managers
have “styles.” For example, one manager might be a value manager, another might be a growth manager.
Another manager might specialize in small cap stocks (stocks with relatively small market capitalization),
while another might be a large cap value manager. These styles can be mixed and matched endlessly. To
be in the wrong “style” can prove fatal (to the the business of a money manager). There is some effort to
correct for this by having performance measurement compare a manager to others with the same style. But,
if that style, as a whole, is doing poorly relative to other styles, the money manager will be in more trouble
than if the manager is in a style that is doing relatively well (from a performance standpoint).
VII.
Money managers tend to be “closet” indexers
How do you decide whether a money manager has done well or done poorly? After all, if the stock market
goes way up all money managers are likely to very well. The usual way of assessing performance in the
money management industry is to assign a “benchmark” to the manager for comparison purposes. In the
simplest situation, imagine that a manager’s objective is to beat the S&P500. That manager will be judged
on how his/her results compare to the results achieved by the S&P500 index during the same period.
Because managers’ results are compared to an index, like the S&P500, they will be reluctant to stray too far
from that index. In other words they buy stocks with an eye to matching the index for the most part with
relatively small deviations designed to improve performance. This practice has led some observers to refer
to most money managers as “closet” indexers.
VIII.
Money managers charge fees
The most common fee arrangement is to charge a flat percentage of assets on a per year basis. For example,
a money manager might charge 50 basis points to manage $ 100 million for a pension fund. That 50 basis
points would translate to $ 500,000 per year in management fees. The actual fees paid would depend upon
the average amount of money under management during the course of the year. Suppose the manager had a
great year and that there was $ 150 million of assets built up by year end. Then, the average amount of
assets might have been $ 120 million during the year and 50 basis points on that amount would be $ 600,000
annually. There is some incentive built in here, but note that the fee goes up even if performance is terrible.
Imagine in this example that the market was up 100 percent during the year, while this manager was only up
50 percent. Nevertheless, the fees paid will rise simply because the assets under management rises.
IX.
Active money management involves transactions costs
Unlike a simple index, money managers frequently buy some assets while selling others. Each time a
money manager does this there is a cost associated with the transaction. This cost is not easy to identify
because it is not simply the commission charges that are tagged on by the executing brokers. An additional
cost, more important than commission charges, is the spread between bid and offer that makes transactions
in any asset market costly, with or without agency fees. (The real estate market is an example, though most
people do not seem aware of this rather large cost).
In practice, an index fund will also have transaction costs as the fund attempts to track an ever-changing
index (the relative proportions of various stocks owned is constantly changing in an index). These costs are
important but do not normally constitute as big an issue for an indexer as for an “active” money manager.
X.
Most money managers are not as well diversified as the indices that serve as the basis for comparison
The most commonly used “benchmark” for measuring investment performance by money managers is the
S&P500 index. A money manager measured by that index will normally own between 50 and 150 stocks.
Almost by definition, that money manager will not be as well diversified as the index that the manager is
measured by. To the extent the themes of the Capital Asset Pricing Model are valid, you would expect the
less diversified portfolio to perform (for the same level of variance) at a lower expected return.
5. Summarizing the current status of EMH
The Efficient Market Hypothesis, then, is no longer widely held to be valid. Indeed, the consensus is that no
version of EMH is valid due to the enormous observed volatility of the stock market. This is small
consolation to the money management industry, since the empirical work on the money management
industry continues to conclude that money managers are consistently bested by the indices that they are
supposed to be beating.
Logically, if someone was really able to “beat the market,” you have to wonder why they would go into the
money management business anyway. A moderate dose of leverage would turn even a moderate stake into
a fortune into a few years, so why bother with customers. That’s a question that institutions who hire
money managers should ask. Unfortunately, they don’t
Major institutions, such as pension funds, endowments and foundations continue to hire active money
management even though the evidence is overwhelming that hiring money managers is foolish, expensive
and counterproductive. A simply indexing strategy would have made all of these funds much larger today
than they are. In just a handful of years, an indexing strategy can lead to twice the size fund that can
normally be produced by an active management strategy.
Indexing is on the rise, but active management is still the predominant investment strategy among major
institutions.
B. Some Recent Controversies in Finance
1. Should Long Term Investors Own More Equities?
It is almost folk lore that investors with longer term investment plans should assume more risk and therefore
place a larger proportion of their assets in common stock than investors with shorter term horizons. This
folk lore was countered many years ago directly by Professor Paul Samuelson (the first American Nobel
Prize winner in Economics). Samuelson argued in 1963, “Risk and Uncertainty: A Fallacy of Large
Numbers,” (Scientia, April-May, 1963) that nothing in the Capital Asset Pricing Framework suggests that
longer term investors should take on more risk. The probability distributions for assets that are normally
assumed in CAPM operate in a roughly proportional fashion so that, if several time periods are taken into
account, the appropriate means, variances, and covariances are appropriately scaled counterparts of the one
period means, variances, and covariances. (Technically, the usual assumption is that stock prices are lognormally distributed. This means that the percentage changes in stock prices follow the pattern of a normal
(bell-shaped) distribution). This means that the simple diagrammatic exposition of CAPM follows through
in precisely the same manner for a thirty year period as for a one year period – you still end up owning the
same proportion between the risk free asset and the market basket regardless of the length of the time period
over which you are calculating your various statistics. Samuelson’s result is unsettling.
a. a. Stocks Surely Outperform Risk Free Assets Over Time
What makes Samuelson’s result unsettling is the following example:
Suppose there are only two assets – the riskless asset and a risky asset. Give these assets some return
characteristics. Suppose the riskless asset has an expected return of 4 percent per annum with no variance
and that the risky asset has an expected return of 12 percent per annum with a 16 percent variance. What is
the likelihood that a portfolio consisting only of the risky asset will underform a portfolio consisting only of
the riskless asset? The answer depends upon the time period over which the question is posed.
Steven R. Thorley took this example (and more) and provided the answers. The probability of
underperformance in one year is 30.9 percent. In five years, the probability that the risky asset will
underperform the riskless asset drops to 13.2 percent. In 20 years, the probability falls to 1.3 percent; in 40
years the probability of underperformance is less than .1 percent. Its worth noting, as Thorley did in his
article, “The Time Diversification Controversy,” in the Financial Analysts Journal (May-June, 1995), that in
20 years the risk free asset portfolio value is $ 2,226 while the expected value of the risky asset portfolio in
20 years is $ 14,239. In 40 years, the expected returns are $ 4,953 and $ 202,755 respectively. Given these
indisputable facts (they follow from the simple arithmetic of normal distributions), why would any rational
person own much of the risk free asset if the planning period is long enough? Thorley’s demonstrations
seem very convincing and they buttress the long held intuition that longer term investors should own riskier
portfolios because, in the sense indicated here, they aren’t as risky when your horizon is longer term
(because the probability of underperformance is so low).
Does this analysis mean that Samuelson is wrong? Both Samuelson and Thorley are simply producing
mathematical correct statements. They are both correct but apparently in, at least intuitive, conflict.
XI.
Insuring Against Underforming The Riskless Asset is Expensive – Very Expensive
Zvi Bodie has strengthened Samuelson’s case by raising the question of the price of insuring against
underperformance in the simple example posed in the Thorley procedure. Bodie’s argument, presented in
“On the Risk of Stocks in the Long Run,” (Financial Analysts Journal, May-June, 1995) uses Black-Scholes
analysis to estimate the value of prepaid insurance against underperforming many years into the future.
Bodie shows conclusively that the cost of insurance, as the length of the horizon is extended, tends to be
equal to the total amount of the original money to be invested – obviously a prohibitively large insurance
premium. Bodie argues that “..the probability of a shortfall is a flawed measure of risk because it
completely ignores how large the potential shortfall might be.” Bodie’s result, which is a straight-forward
application of Black-Scholes option pricing theory, implies that insuring an increasingly (with time)
extremely low probability event can get increasingly expensive. Bodie’s result seems paradoxical, but the
analytic argument is unassailable.
XII.
Jeremy Siegal – Stocks for the Long Run
Jeremy Siegal has taken the position, with much documentation of past market history, that stocks have
outperformed bonds and that long term investors should not own bonds. Siegal and Peter Bernstein
maintain this pro-stock view in their recently revised edition (1998) of Seigal’s book entitled Stocks for the
Long Run. James K. Glassman and Kevin Hassett created a stir in early 1999 their book, Dow 36,000, in
which they maintain the proper current value of the Dow Jones Industrial Average is 36,000. The
appearance of these two books heralded the end of the long bull market in stocks.
XIII.
Irrational Exhuberance?
Federal Reserve Chairman Alan Greenspan referred to the bull market of the 1990’s as an example of
“irrational exhuberance,” suggested that bull market may not be based on a sound footing. Greenspan’s
comments came in 1996, after which the market doubled in value again in the next three years. It made
Greenspan look like a poor forecaster, but many others shared his views. Then after the first quarter of 2000
the great bull market of the 1980s and 1990s seemed to have ended. The Dow Jones reached the lofty
pinnacle of 12,000 only to fall back to a low of 7,100 mid day low in September of 2002. The NASDAQ
fared even worse after a peak of 5000 in early 2000, the NASDAQ slipped to a low in the 1100’s in midSeptember of 2002. These were mighty declines from the bull market highs. Were they warranted?
Robert Shiller, a Yale Economics Professor known for his work in behavioral finance, published a book in
April of 2000 entitled Irrational Exhuberance. Shiller had excellent timing (although he had actually been
extremely bearish for years) with his book, as its publication date coincided with the peak of the bull
market. Shiller argued that stocks were grossly overvalued and that future stock returns would be virtually
non-existent.
XIV.
Growth Optimal Investing – A Different Paradigm
Somewhat hidden in the background of the modern finance literature is the notion of growth optimal
investing. This literature asks how should one invest if you wish to be “almost certain” to have your
portfolio grow as fast as possible. Growth optimal investors with long horizons are reluctant to hold much
in the way of the risk free asset because it limits their long run growth rate by too much. This literature,
interestingly, implies a significant role for diversification for some of the same (engineering type) reasons
that drive the Capital Asset Pricing Model. The growth optimal investing paradigm is interesting mainly for
its implications for longer term horizon investing and it reaches the conclusion that equities should be more
significant (and treasury bills less significant) the longer the planning horizon. One of the earliest
discussions of Growth Optimal investing is by Henry Latane, “Criteria for Choice Among Risky Ventures,”
Journal of Political Economy 67, 1959.
2. Does Value Investing Beat The Market?
a. Value Means Low Price/Earnings or Low Price/Book Ratios
Arguably the most famous book every written about stock market investing is Security Analysis by
Benjamin Graham and David L. Dodd. This book, originally published in 1934, argues that investors
should focus their attention upon the financial statements of companies. One of the central themes of
Graham-Dodd analysis is that value is best measured by a careful consideration of book value, earnings, and
other financial variables. In modern parlance, the message is that investors should buy low P/E (market
price/earnings) stocks and stocks with high book value to market value ratios. There is considerable
evidence that this strategy worked over the intervening 60 years better than simply buying the entire market
and holding it. An article by Eugene Fama and Kenneth French, “The Cross Section of Expected Stock
Returns,” published in the June, 1992 issue of The Journal of Finance provided substantial support to the
thesis that “firms that the market judges to have poor prospects, signaled here by low stock prices and high
ratios of book-to-market equity, have higher expected stock returns.”
This surprising apparent contradiction of the efficient market hypothesis is reported along with numerous
other anomalies in The Winner’s Curse by Richard Thaler, 1992. The interest in these paradoxical
observations has spurred an entire new area of finance that has been dubbed behavioral finance. Advocates
of behavioral finance argue that traditional finance theory ignores widespread evidence that investor
behavior is often not rational in the sense assumed by most of finance theory. Thaler’s book is a good
source of these ideas and contains references to much of this literature. For alternative views, see an
unpublished article by Eugene F. Fama, “Market Efficiency, Long Term Returns, and Behavioral Finance,”
Graduate School of Business, University of Chicago, 1997 as well as Chapter 4 in Stephen Ross’s
“NeoClassical Finance, Princeton University Press, 2005.
The idea that stocks with a high book value to market value ratio should outperform the broad stock market
averages is a way of capturing the notion that stocks that are generally perceived unfavorably by the market
will outperform stocks that are generally perceived favorably. What has this got to do with book
value/market value ratios? If a stock is perceived unfavorably by the market, then it’s price will be very low
relative to its accounting value – book value (about which we have more to say in the next section). If a
stock is generally viewed very favorably by the market, its stock price will tend to be higher than you might
expect by simply calculating the stated value of its assets – the book value of the company. The ratio of
book value to stock price, then, is a kind of proxy for perception. The higher this ratio the higher the
perception that the stock (or the company) will not be a good performer. Put simply, the stock market tends
to discount the value of companies that are out of favor. The result is that stocks out of favor tend to have
low prices relative to their book values. The interesting fact is that it is precisely this group of out-of-favor
stocks that have historically provided the best investment returns. The converse proposition is also true:
stocks that the market favors (as measured by high stock prices relative to current book value) tend to
underperform the general stock market. The message is to buy stocks that people hate and sell stocks that
people like. This strategy appears to have done better over the past several decades than any other broad
based equity investment strategy.
How does the price/earnings ratio fit into this story? Let’s suppose that you have two stocks whose earnings
are $ 1 million annually. Let each of these stocks have one million shares outstanding so that the earnings
per share amount to $1. How do you interpret the fact that one stock might have a price of $ 8 per share
while the other has a price of $ 20 per share? Obviously, there could be many factors that could account for
this difference. Usually this kind of discrepancy in price/earnings ratios (which in this case are 8 to 1 and
20 to 1 respectively) is based on difference between how the market perceives the two companies’ future
prospects. The stock with a 20 to 1 price earnings ratio is the stock that the market thinks has a great future
(in terms of future earnings growth) as compared to the stock with an 8 to 1 price earnings ratio.
When you analyze the actual data for earnings, book value and prices and their interaction, it is not really
possible to disentangle the separate impact of low P/E and low Market Price/Book effects because stocks
with low P/E’s tend to be the same stocks that have low price to book ratios. Both of these measures – low
P/E and low Market Price/Book ratios – are taken as measures of high relative value. Buy these stocks and
you will do better than broad market averages says the evidence. That evidence, however, weakened in the
date over the 1995-2001 period and then re-emerged in the data from 2002 – 2006. All of this suggests that
sometimes it works and sometimes it doesn’t.
XV.
Markets Tend to Overreact
Part of the explanation for the apparent success of value investing is that markets overreact. Specifically, if
a company has disappointed the market for some reason, the price of the stock drops ultimately by more
than it should. Similarly, if a company has done well the market builds a large premium for past successes
into the current stock price. This idea that markets overreact has been advanced in two, perhaps related,
contexts. The first context is the present discussion of value investing. The second context is the mean
reversion hypothesis. The mean reversion hypothesis argues that stocks have a mean return and whenever,
for a period of time, they have higher returns then their true mean return, then they will later revert back to
their true mean return by exhibiting lower returns. Similarly, periods of lower returns will mean that later
there will be periods of higher returns so that returns ultimately revert back to their (true) means. The mean
reversion hypothesis is statistically difficult to properly test, although some claim to have done so. It is
supportive of the notions that markets tend to overreact. Mean reversion is not inconsistent with the views
of those advocating value investing.
XVI.
Wherein Lies the Truth
If only we knew. But, our best guess is the following: That probably during the post World War II period
value investing has done better than other strategies. Had we known this then, well…..terrific….we could
have made a lot of money. Does it help to know it now? Probably, the answer to this question is no. Our
data sample, ninety years, really isn’t much data from which to draw very many conclusions. These
markets, in their modern form, are too new. We have too small a set of observations to reliably conclude
that value investing meets any statistically significant tests for performance. Even if it did, it probably lacks
any relevance to the future since everyone knows how well it has done in the past. Following the logic of
the value investing crowd, since value investing is now a popular investment strategy, it probably won’t do
very well in the future.
3. Enron, Corporate Governance, Post-2000 Scandals
Beginning in mid-2000, there erupted a wave of corporate scandals, the most famous of which was the
Enron debacle. Enron, at its peak, was the fifth largest corporation in the world with a market capitalization
in excess of $ 150 billion. Within six months in 2000, Enron, slowly at first and then more rapidly,
collapsed into bankruptcy, amid a wave of announcements that revealed that Enron had been misleading its
shareholders for a long period of time and to an incredible extent.
a. What happened at Enron?
Enron was a company that grew out of a small natural gas and pipeline company headquartered in Houston,
Texas. By the early 1990s, under the leadership of its Chairman, Kenneth Lay, Enron began to develop a
trading and market making expertise in all areas of energy including natural gas, oil, electrical power, and
coal. The trading and market making activities came to dominate Enron’s earnings and their public
persona.
For various reasons, the Enron business model was not one that could survive the competition that was sure
to come from Goldman Sachs, Merrill Lynch, Morgan Stanley and other Wall Street trading and market
making power houses. These firms had been slow to enter the energy trading market, but were headed that
way by the mid-1990s. This posed a serious threat to Enron’s dominance of these markets.
As a result, Enron management and their accountants began to devise ways to make earnings appear greater
than they really were. A series of “off-the-books” partnerships were created, starting in 1997, that did two
things: 1) served to enrigh key Enron employees at the expense of shareholders; and 2) exposed the
company to risks that were not disclosed nor apparent to shareholders. That the Enron Board of Directors
sat idly by while these things occurred was a testament to the very poor state of corporate governance that
prevailed, and probably still does, in corporate board rooms, not only in the United States, but throughout
the world.
As the Enron saga unfolded, other similar corporate shenanigans began to be uncovered and regulatory
authorities including the Securities and Exchange Commission, Federal and State law enforcement agencies
(especially the attorney general of New York), and the self-regulatory agencies of the financial industry
itself (the New York Stock Exchange, the NASDAQ, etc.) took a greater interest than had heretofore been
the case in the broader issues of “corporate governance.” Soon Tyco and World Com were to join Enron as
a household names, signifying corporate greed and misuse of shareholder trust. Even Europe was not
immune as the Italian firm, Parmalat, suffered a multi-billion dollar fraud and was dominating the news in
early 2004. In 2005, the collapse of REFCO added another name to the list of corporate governance
disasters.
Law enforcement agencies in the United States began to indict senior corporate management officials and
the “perp walk” became a common staple of evening television news. (A “perp walk” depicts the accused
perpetrator who has been arrested and is “walking’ through the doors of the criminal justice system). The
film clips of arrested perpetrators being arraigned by civil and criminal authorities has come to be known as
the “perp walk.”).
The trial of Kenneth Lay, former CEO of Enron, is scheduled to begin in early 2006. It should be
interesting.
XVII. The Mutual Fund Scandal – Market Timing of Mutual Funds
In 2003, a new financial scandal erupted – one that involved many major mutual funds as well as the
growing hedge fund industry – the “market timing” scandal.
i.
a. What is “market timing” as applied to the mutual fund scandal?
The phrase “market timing” refers to the practice of buying (or selling) unit shares in a mutual fund with
information that is not contained in the pricing. For example, a mutual fund that owns only American
stocks sets its prices every night based upon the 4:00 PM EST closing prices of each of the individual
stocks. If you are a typical mutual fund buyer or seller, you enter an order to buy or sell during the day
(before 4:00 PM EST) and the price you pay or receive is determined by the stock prices in the fund as of
4:00 PM EST.
In “market timing,” you might wait until after 4:00 PM when the price of the mutual fund unit is known and
observe how the markets trade between 4 PM and 6 PM. Then at 6:00 PM, after observing that individual
stock prices have gone up since the 4 PM close, you then enter an order to buy at the lower, earlier
established, prices from 4:00 PM. The market is now, at 6 PM, higher, so you could sell a futures contract
(or sell the stocks in the mutual fund unit in the proportion to which they are owned in the mutual fund) and
lock in a profit with no risk. Obviously, this practice should be illegal. It is certainly unethical.
Nevertheless, numerous brokerage firms, mutual funds, and hedge funds actively participated in this
practice to the detriment of mutual funds shareholders, including to the detriment of most of the small
investor community in the United States.
The loser in “market timing” is the unknowing unit shareholder in the mutual fund. In effect, market timers
are stealing from the passive shareholders who play by the rules. The series of exposes on market timing
first broke in 2003 and continues to make headlines in early 2004.
ii.
b. Market Timing – what is the solution?
This is an example where simple enforcement of the law seems to work wonders. Since the rules for
buying and selling mutual funds are spelled out in the prospectus’s for these funds and because they
uniformly spell out the price determination process that governs the purchase and sale of unit interests, then
the activities of so-called “market timers” should be considered fraud – both from a civil as well as a
criminal point of view -- and the law should be enforced accordingly. To the extent these activities are not
illegal (which is doubtful), then they should be made a violation of federal law as soon as possible.
There seems to be little advantage to additional regulatory scrutiny of mutual fund behavior since the net
effect of such additional scrutiny is likely to simply increase the costs to unit shareholders with little or no
added protection.
XVIII. The New York Stock Exchange – The Saga of Dick Grasso
Richard Grasso was the Chairman of the New York Stock Exchange until 2003. His overall pay package,
including deferred items from earlier years, surfaced in the press in late 2002 as in excess of $ 170 million.
(This was not one year’s compensation, but a pay package that was, part past pay deferrals, part current
income and part future payments). This report created shockwaves among the investing public and kept the
financial news media abuzz for months.
The reaction to Grasso’s pay package by both the public and the financial press was loud and negative.
This reaction was conditioned by the two prior years of scandals that had rocked the corporate boardrooms
of America. Grasso had spent most of his adult life at the New York Stock Exchange and had risen from
from the floor, literally, to become the head of the exchange. He had been widely viewed and applauded as
a strong and effective leader of the exchange, especially through the periods of market turmoil in the late
1980s and some well publicized crises during the mid to late 1990s. All of this good will for Grasso was
quickly disappated when the details of Grasso’s compensation begin to seep out into the public domain in
2002. As 2006 unfolds, the New York Stock Exchange Board continues extensive litigation with Grasso
over compensation issues as regulators look on.
XIX.
Noise on the pension fund front
As the various scandals of 2001-2003 began to dominate the headlines, some of the larger pension funds in
the United States to begin to create headlines of their own. Pension fund leaders in New York State, North
Carolina, and California began to clamor for more respresentation on the public corporate boards. The
Council of Institutional Investors, purporting to represent major pension funds, endowments, and
foundations began to add their voice to the chorus asking for more board representation by major
institutional funds.
In the context of at least one the scandals, this proved somewhat embarrassing. Carl McCall, the
comptroller of the state of New York (and the principle fiduciary for all of the New York state’s pension
funds) was also, interestingly, the Chairman of the Compensation Committee of the New York Stock
Exchange at the time the wampum pay package was awarded to Dick Grasso. In the heat of the publicity
surrounding Grasso’s pay package, McCall quietly resigned from the NYSE Board of Directors and thereby
quietly removed himself from the NYSE Compensation Committee as well. McCall, who had been one of
the loudest voices decrying boardroom scandals suddenly became very quiet on these topics.
The other major pension funds, however, continued their criticisms of the NYSE and of corporate
boardroom misbehaviour with no letup. Their major recommendation to deal with these mishaps seems to
be to put themselves individually on these boards and then all will be righted. The problem with that
argument is there considerable reason to believe that these self-same pension funds – California, North
Carolina, New York – are hardly the first place one would look for reform of corporate America. The folks
that run these pension funds, the Trustees, tend to be political appointees, or are politically connected in
important ways (many actually campaign and are elected to their positions on the boards) and are not likely
to be immune to pressures that surface regularly in the boardroom. There is no reason to expect pension
fund chieftans, based on the record, to have any more interest in protecting shareholder interest than the
current lineup of “friends and family” of management that seem to effectively dominate the corporate
boardroom of most large corporations.
Indeed, there is some reason to doubt that the interests of pension fund leaders are in line with the interests
of shareholders. Pension fund leaders, and especially those who have been most vocal on the topic of
corporate reform, are the same people who have joined the class action lawsuits against corporations. These
lawsuits, when successful, are targeted at shareholders. In effect, these pension funds have been filing civil
lawsuits against shareholders, who are largely unaware that they are being sued. When Enron gets sued,
that means the shareholders of Enron are being sued. How this strategy is of benefit to shareholders is not
made clear (and probably cannot be made clear). But most large pension funds, as well as the Council of
Institutional Investors is in the forefront of this absurd, anti-shareholder practice. It is essentially
equivalent, in the aggregate, to suing yourself. So much for looking to the pension fund world for help in
dealing with the problems of corporate mismanagement.
XX.
Are There Solutions to Scandals in the Corporate Boardroom?
What should be done? The essential problem is that directors do not do a good job of representing
shareholders. The reason for this probably has to do with incentives. Directors generally have no incentive
to look out for the interests of shareholders, but a very large incentive to look after the interests of
management. After all, management normally selects the board members and arranges their compensation.
Management is normally in a position to remove recalcitrant directors whenever they feel like doing so. It
is only natural, then, that directors would be beholden to management but pay only lip service to the
interests of shareholders. It might be a good idea to limit outside directors (those who are not part of
management) to one term, albeit a long term (perhaps 10 to 12 years for a single term, but no
reappointment possible).
One way of dealing with this problem would be to change the compensation structure so that directors’
interests might be better aligned with shareholders. Currently most directors are paid in cash and stock
options. These forms of compensation line the interest of directors up with management not with
shareholders. A better way might be to pay directors in “deferred stock.” This means that directors would
be given stock that cannot be sold until some period after the directors are no longer on the board.
Eliminate cash compensation and stock option compensation for non-management directors (so-called
“outside” directors).
It would also make sense for corporations to adopt a rule that prohibits outside directors from selling
shares in the company on whose board they sit while they are directors. There should even be a waiting
period, perhaps two years, after someone leaves a director position before they can commence selling stock
in the company.
By adopting these reforms, outside directors will have their economic interests more clearly aligned with the
shareholders. (One problem with this proposal is that if the deferred stock is a significant part of the
director’s net worth, there could be some incentive on the part of the director to want the corporation to
diversify its earnings. This would not be in the best interests of a normal shareholder, who is free to
diversify by the simple expedient of owning other common stock. Diversification of corporate earnings is
normally not in the best interests of shareholders).
It would probably be a mistake for the Securities and Exchange Commission or the New York Stock
Exchange to mandate any of these proposals as different companies operate differently. Instead, companies
that wish to adopt corporate governance reforms could consider these reforms and adopt them as they see
fit. Investors could then choose which firms they wish to own stock in and which firms they don’t with to
own stock in. It is generally a mistake for the regulatory bodies to mandate rules by which companies are to
be governed. It is far better economics and public policy to let companies adopt good corporate governance
procedures as they see fit.
An exception to the laissez-faire approach suggested in the preceding paragraph are the rules for disclosure.
The SEC, correctly, in early 2006 released new rules regarding the disclosure of management compensation
by boards of directors in their public filings. It has long been difficult by reading the SEC filings of public
companies, to figure out what the highest paid employees at public companies receive in compensation.
The SEC has recently stepped in to require better disclosure of executive pay by public companies. This
move by the SEC should be applauded. As we shall see below, other efforts to regulate public companies
have not had such salutary effects, especially the notorious Sarbanes-Oxley legislation, enacted in 2002.
XXI.
The Sarbanes-Oxley Act of 2002
The aftermath of the Enron, Tyco, and WorldCom boardroom scandals resulted in the enactment of
legislation by the Congress of the United States in 2002 that set out to deal with corporate misbehavior.
This legislation is called the Sarbanes-Oxley Act. It is essentially a major amendment to the Securities Act
of 1933, that is the main law that governs the way that public companies must disclose information about
their activities to the public.
The act creates the Public Company Accounting Oversight Board, which is supposed to oversee the
accounting rules and regulations for public companies. This part of the act was in reaction to perceived
accounting irregularities attached to the scandals of Enron and others.
Probably, the most significant part of Sarbanes-Oxley is the famous (or infamous) Section 404. Section 404
requires the outside auditor to certify that the company’s management has “effective internal controls and
procedures.” This vague wording creates the ever-present possibility, as a practical matter, that the outside
auditor may not be able to make such a certification in a timely manner (the requirement is that the
certification be in place shortly after the company’s fiscal year ends…which means much of the work must
be done prior to the end of the fiscal year). This provision has proved to be extraordinarily expensive for
most public companies. 2004 will be the first year of its implementation and it will be interesting, as we get
further into 2005, to see how many companies are not able to achieve the auditor certification by the
appropriate deadlines. Failure to achieve certification does not mean that there is anything wrong with the
company’s internal controls and procedures. It simply means that the auditor, for whatever reason, may not
be in a position to make the certification in a timely manner.
Section 404 seems to do little good and much harm. The costs are enormous and will force many smaller
public companies to convert to private company status to avoid the high costs of compliance with 404. For
other public companies, it will simply represent one more ongoing cost to shareholders without much
apparent offsetting gain.
Other parts of Sarbanes-Oxley are less damaging to the operation of public companies, but will represent,
generally, an increase in accounting and compliance costs for all public companies. This, effectively, makes
all public companies are worth less, on an ongoing basis, than they would be in the absence of such costs.
Unfortunately, nothing in Sarbanes-Oxley is likely to make outside directors do a better job of policing the
management of public companies. So, from a corporate governance point of view, no real improvement can
be expected from this legislation. The market, however, has the ability to enforce its own disciplines. It
denies additional funding to companies with poor accounting practices and management excesses. That sort
of discipline will reign in, and has already reigned in, the most blatant of corporate governance abuses.
SOX, as Sarbanes-Oxley is known, is just an additional cost element with little promise to provide better
management of corporations. One could easily argue that SOX, because competent people with significant
assets will avoid corporate board service in the future, will only make boards weaker in the future and less
able to resist management.
It is likely that SOX will be amended, in the future, to be more shareholder-friendly, than it has been thus
far.