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 5% 8%1971 -2% 1%1972 12% 10%...... ..... .......... ..... .....1990 8% 13%1991 -5% 6%1992 2% -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:

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:

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 represent the sample

mean of the xt's and represent the sample mean of the yt's. Then:

and:

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:

sx=∑t=1970

1992( x t−x )2

23

and:

s y=√∑t=1970

1992( y t − y

¿)2

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:

∑t=1970

1992(e t )2=∑t=1970

1992( y t−a−bx t )2=∑t=1970

1992( ( y t−a )−bx t)

2=∑t=1970

1992

(( y t−a )2+b2 xt2−2 ( y t−a ) bxt)

Continuing to expand the interior of the parentheses:

=∑t=1970

1992

( yt2+a2−2 ay t+b2 x

t2−2 bx t y t+2 abxt )=∑t=1970

1992

(a2+ yt2−2 ay t+b2 x

t2+2 abx t−2 bx t yr)

Now, bringing the summation sign inside the parenthesis, gives:

With appropriate substitutions:

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.)

∂∑ et2

∂a =2an−2n y+2bn x=0

(2.)

The first equation can be simplified to:

(1.)

The second equation after substituting in for a using (1.) becomes:

2 b∑ xt2+2 ( y−b x ) nx−2∑ x t y t=2b∑ x

t2+2 nx y−2bn x2−2∑ xt yr= 0

eliminating the 2's and simplifying:

b∑ x

t2+n x y−bn x2−∑ xt yr=b(∑ x

t2−n x2)−n x y−∑ xt y t=0

Separately, consider the following expression and its expansion:

∑ ( x t−x)2=∑ ( xt2+ x2−2 x t x )=∑ x

t2+n x2−2 n x2=∑ xt2−nx2

plugging this expression in where appropriate gives us:

(2.) b (∑ (x t−x )2 )−n x y−∑ xt y t=0

Again, separately consider the following expansion:

∑ ( (xt−x ) ( y t− y ))=∑ ( y t (xt−x )− y (x t−x ) )=∑ y t x t−x∑ y t− y∑ xt+n x y

which means that:

∑ ( (x t−x ) ( y t− y ))=∑ y t x t−n x y−n y y+n x y=∑ xt y t−n x y

Now, making a substitution of this last expression into (2.) gives us:

(2.) b (∑ (xt−x )2 )−∑ (( xt−x) ( y t− y ))=0

Solving (2.) for b yields:

β=∑ (( xt−x )( yt− y ))

∑ ( x t−x )2

By inspection this expression equals the sample covariance divided by the sample variance of the index return:

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.)

(2.)

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 [ Ri ]−Rf =βi , M (E [ RM ]−R f )

with:

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.

What do the CAPM conclusions mean? The first equation:

E [ Ri ]−Rf =βi ,M (E [ RM ]−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

=

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:

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:

β M , M≡Cov (M,M )

σM2

=σ

M2

σM2

=1

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:

then P's beta can be constructed as follows:

βP , M º Cov (P,M )s

M2=∑i=1

nαi β i , M ºα1 β1 , M+α 2 β2, M+ .. ..α n βn , M

III. 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:

slope = μM − R f

σ MThere 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:

μM − R f

σ M =

μP − R f

σ PThe 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 [ Ri ]−Rf =βi , M (E [ RM ]−R f )

with:

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 [ Ri ]−Rf =βi , M (E [ RM ]−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+r t )t+

Div t+1

(1+r t +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 log-normally 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 mid-September 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.