The Role of the CAPM and MM Theorems in the Rise of a Scientific
This article studies the history of financial economics during the
1960s. This decade was crucial in the construction of this discipline:
although works in financial economics had existed since the mid19th
century –see volume 1–, this discipline was only included into the
scientific field during these years. Bourdieu defines the concept of
scientific field as follows:
“In analytical terms, a field can be defined as a network, or a
configuration of objective relationships between positions. These
positions are objectively defined in their existence and in the
determination they impose on their occupants, agents or institutions,
by their current and potential situation in the structure of the
distribution of various kinds of power (or capital), the possession of
which demands the access of the specific profits at stake in the
field, and, as a consequence, by their objective relations to the
other positions (domination, subordination, homology, etc.)” (Bourdieu,
et al. 1992, 73).
Scientific field includes all scientific disciplines. Each scientific
discipline constitutes a subfield and imposes its own rules,
behaviors, methods, etc. to distinguish itself from approaches
recognized as non scientific. Relying on Gingras, within the
development of a scientific field, Bourdieu (2004, 50) identifies
two steps: “first, the emergence of a research practice, in other
words, agents whose practice is based more on research than on
teaching, and the institutionalization of research in universities
through the creation of conditions conducive to the production of
knowledge and the longterm reproduction of the group; and, secondly,
the constitution of a group recognized as socially distinct and a
social identity, either disciplinary, through the creation of
scientific associations, or professional, with the creation of a
corporation –the scientists provide themselves with official
representatives to give them social visibility and defend their
The scientific field concept helps to better understand financial
economics and its creation. Here, we will focus on one particular
point: financial economics became a scientific subfield in
consequence of the theoretical explanations given to empirical and
statistical results accumulated during several decades. Indeed,
following Bourdieu (1975, 96), “we have to distinguish the [author]
who has discovered the unknown phenomenon from the one who made it a
new scientific fact integrating it in a theoretical construction” of a
scientific discipline, which accordingly places it within the
scientific field. For instance, during the 1960s, the random character
of stock market prices became a scientific fact about 100 years after
its discovery by Jules Regnault in 1863. It is precisely during the
1960s that several discoveries by financial economists became
The integration of financial economics into the scientific field was
made possible by the synthesis of results. These results belong to
three analytical components that were developed successively:
financial econometrics, modern theory of probability and economic
equilibrium. Efficient market theory, CAPM and ModiglianiMiller
theorems played a key role in this synthesis, and therefore in the
rise of the new scientific discipline. They established links between,
on the one hand, empirical and mathematical results in finance, and on
the other hand, economic equilibrium. These links led to the creation
of theoretical explanations for empirical results, explanations that
were the last step in the categorization of financial economics as a
This article aims to show how these works structured the new
scientific discipline. The format of this article is as follows. Part
1 examines features that show the incorporation of this new discipline
into the scientific field during the 1960s. Part 2 analyzes the
contribution of ModiglianiMiller’s article, CAPM and Efficient market
theory in the construction of financial economics. It shows the key
role of the economic equilibrium in the creation of financial
I. The rise of the financial economics
Before the 1960s, works in financial economics were very marginal in
the scientific field. Milton Friedman’s reaction against Harry
Markowitz’s thesis gives a good illustration. This thesis, defended in
1952, deals with the theory of portfolio selection. It is one of the
first AngloSaxon works in what it is now called financial economics
that was not exclusively empirical. Indeed, at that time, financial
economics works mainly investigated empirically the random character
of stock market prices. In the defense, Friedman declared: “Harry, I
don’t see anything wrong with the math here, but I have a problem.
This isn’t a dissertation in economics, and we can’t give you a Ph.D.
in economics for a dissertation that’s not economics. It’s not math,
it’s not economics, it’s not even business administration” (in
Bernstein 1992, 60).
While Friedman’s reaction could be considered inappropriate or
excessive, given the importance of Markowitz’s work today, it is a
good signal about the situation of financial economics before the
1960s, and more specifically before Modigliani and Miller’s
contribution in 1958: the few existing works did not constitute either
an academic or a scientific discipline yet; there were applied
mathematics and empirical investigations without theoretical
contribution that took place in a scientific or an academic discipline
that already existed. This situation changed with the creation and the
organization of a new community during the 1960s. In other words,
Markowitz’s article took place in a transitional period that ended
with Modigliani and Miller’s publication on “the cost of capital,
corporation finance and the theory of investment” in 1958.
I.1. 19451958: a transitional period
After WWII, authors had access to new mathematical tools from modern
theory of probability. As I mentioned in the introduction, the
construction of the financial economics cannot be separated from this
theoretical corpus. The modern theory of probability led several
authors to take into account uncertainty, in particular after
ArrowDebreu’s works. However, until the 1960s, modern theory of
probability was used to study financial market and corporate finance
in only one way: academics exploited the properties of random
variables in applying them to long existing problems; they did not
provide any new theoretical investigations. We can show that this
situation is true for the analysis of stock price changes as well as
for portfolio management theory.
The analysis of stock market prices was relatively recent in North
America during the 1950s and it was exclusively developed through
financial econometrics (see Jovanovic (2004)). The latter started to
develop during the 1930s when, in September 9th 1932, Alfred Cowles
established the Cowles Commission. “Victim” of the crash of 1929,
Cowles “realized that he did not understand the workings of the
economy, and so in 1931 he stopped publishing his market advisory
letter, and began research on stock market forecasting” (Christ 1994,
30). His quest led him to get in touch with the young Econometric
Society, which he sponsored. Two authors, linked to the Cowles
Commission, started, in the United States, the researches in
quantitative finance: Alfred Cowles (1933, 1944) and Holbrook
Working (1934, 1949) who participated to its summer conferences.
Because the 1929 crash had not been forecasted, they considered that
price changes were unpredictable. It is by this mean that the random
walk model was reintroduced to represent price changes, independently
of the works of its two first contributors, Jules Regnault and Louis
Bachelier. The main specificity of these new researches is the
application of new tools, which were provided by econometrics. This
situation still existed until the 1960s. Thus, in 1953, when Maurice
Kendall published a statistical study on the random price
fluctuations, he adopted the same approach: he applied new
developments in econometrics and in modern theory of probability to
financial problems. Neither Kendall, nor Cowles, nor Working provided
theoretical explanation at that time. This situation was similar for
portfolio management theory, the other field in financial economics
that existed in the 1950s.
Markowitz (1952) treats singleperiod returns for various securities
as random variables, and assigns them expected values, standard
deviations and correlations. From this, he suggests the possibility to
calculate the expected return and volatility of any portfolio
constructed with those securities: volatility and expected return are
to be treated as proxies for risk and reward. Out of the entire
universe of possible portfolios, certain ones will optimally balance
risk and reward: this is Markowitz’s efficient frontier of portfolios
on which an investor should select his portfolio. The core of
Markowitz’s idea consisted on using mathematical properties of random
variables to show that shares diversification from a portfolio could
reduce the variability of returns: the expected value of a weighted
sum is the weighted sum of the expected values, while the variance of
a weighted sum is not the weighted sum of the variances. Markowitz did
not give any theoretical demonstration to his mathematical result; he
just operated a financial windowdressing of some mathematical
properties. More precisely, he applied these properties to an old
question which had been already analyzed by several authors. We can
mention, in particular, Marshall Ketchum, a professor at the
University of Chicago, from who Markowitz received advertising when he
started his Ph.D. In his 1947 article, Ketchum had suggested that one
way to protect investments from downward fluctuation in stock prices
was to divide portfolio in two parts: a defensive part based on low
volatility securities and an offensive part based on high volatility
securities (Stabile 2005, 1336). This proposition was a direct
response against the unpredictability of price changes that was
debated at that time.
Obviously, this kind of works, which used modern theory of
probability, stayed marginal until the diffusion of the teaching and
use of this theory at the beginning of the 1960s. Indeed, before the
1960s, hardly any economist and financier used stochastic processes,
because they were not well understood and they were not greatly
diffused. Effectively, the modern theory of probability, which mainly
comes from Kolmogorov’s work, was truly accepted in the 1950s by the
new generation of mathematicians –Mazliak (2003), Chaumont et al.
(2004). Even during the 1960s, few economists or financiers used
them. For instance, Samuelson (1965a, 1965b), who was the first with
Mandelbrot (1966) to substitute the martingale modeli for the random
walk model/Brownian Motion to represent stock price variations, needed
the help of a mathematician to make his mathematical demonstration
(Samuelson 1965b). The use of the theory of modern probability, in
particular through the conception of uncertainty, offered new
perspectives on already existing problems. At that time, however, such
developments were technical and any theoretical explanation did not
exist. In other words, during this period the modern theory of
probability provided new tools that social sciences could exploit,
but, obviously, this is not enough to build a new discipline: a model
does not contain causalities per se, because the choice between
endogenous variables and exogenous variables comes from theoretical
frameworks. Indeed, a theory gives causalities that allow defining the
structure of the model. These new tools from modern theory of
probability cannot provide an explanation to the empirical
environment. Therefore, theoretical frameworks are necessary to
introduce financial economics into the scientific field. Financial
economists naturally quickly focus on the lack of theoretical
I.2. The lack of theoretical explanation before the 1960s
Before the 1960s, no theory was explaining the new results in
portfolio selection or in the random character of stock market prices.
This crucial point illustrates what kept financial economics from
becoming a scientific discipline. This absence characterizes all
existing works written during that transitional period.
Concerning portfolio selection, Markowitz (1952) and Roy (1952)
provided no real theoretical explanation to justify mathematical
results. I explain that Markowitz applied new mathematics to an old
problem. Of course, because he used results from modern theory of
probability –meanvariance model of portfolio choice–, he offered new
perspectives, but the major point is that he did not provide any
theoretical explanation except a mathematical lecture. It was exactly
the problem pointed out by Friedman. Markowitz corrected it by
publishing his book in 1959. Here, he started to give theoretical
interpretation of some of his previous result: he strove to link his
meanvariance criterion with the maximization of the expected utility
of wealth. This theoretical link helps to include his results and
works in academic and theoretical questions debated in economics. As
we will see below, this link with economics was completed with the
CAPM during the 1960s. Therefore, before that book, no theoretical
explanation was made about that subject.
In the same way, Cowles (1933), Working (1934) or Kendall (1953)
did not create any theoretical explanation about the random character
of stock market prices. More precisely, the enthusiasm for the new
econometric practices developed since the 1930s clouded the research
for theoretical explanations of the random character of stock prices.
The theoreticians pointed out the absence of theoretical explanation
during the 1950s. This is particularly striking after the
KoopmansVining debate at the end the 1940s, which set NBER against
Cowles Commission over the lack of theoretical explanation and the
necessity to link measurement with theory. This debate dealt with the
kind of analysis to practice on statistical data. The NBER was
claiming the usefulness of a mainly statistical approach which aimed
at measuring the evolutions of economic indices, while the Cowles
Commission, since the beginning of the 1950s, gave less importance to
econometric methods as such and became more oriented toward economic
theory to construct theoretical foundations. This transition is
illustrated by the new slogan of the Cowles Commission: from Science
is Measurement, it became Theory and Measurement.
Kendall published his article just after the KoopmansVining
controversy. This study was accepted with interest even as its
economic contribution was harshly criticized. The most important
critique was the absence of links with economic theories or concepts:
“It may therefore be concluded that Professor Kendall’s investigations
of autocorrelations cannot in principle throw any light on the
possibility of estimating the kind of dynamic economic relationships
in which economists are usually interested” (Prais 1953, 29).
Houthakker, who joined the Cowles Commission in 1952, also explained
that “the evaluation of Professor Kendall’s paper […] is made
difficult by the fact that there is no reference to a theoretical
framework anywhere, nor indeed to work of others which the author may
have had in mind” (1953, 32). About a technical sentence of Kendall,
he added that “this sentence would be correct if it began by the
following sentence: "it was customary twenty or thirty years ago"”
(1953, 32). These remarks are direct echoes to the KoopmansVining
This evolution in economics had a direct influence on the two main
defenders of the random character of prices at that time, Working
(1956, 1958, 1961) and Roberts (1959), who also consistently
highlighted the absence of theoretical explanation and the weakness of
the statistical results. The lack of theoretical explanation was one
of the main challenges since the end of the 1950s.
I.3. The rise of a new scientific community
This challenge gained the support of a new scientific community. Three
features show the emergence of this community during the 1960s: 1)
news academics and researchers appeared; 2) new scientific
publications existed; 3) a new field of investigation was defined.
First, we can notice that at the beginning of the 1960s, a new
generation of economists started their graduate studies and
contributed to the creation of financial economics. This generation
contributed to the creation of a community in financial economics.
Most of these new students were graduated from the University of
Chicago and MIT. In fact, most of academics who studied financial
markets with this new mathematics worked in these 2 places, which
produced the main research and results in the discipline during the
1960s and the 1970s.
At the University of Chicago, research was made at the Graduate School
of Business where Harry Roberts worked with James Lorie and Lawrence
Fisher. In 1960, the latter two professors started an ambitious 4year
program of research on security prices (Lorie 1965, 3). Lorie was
recruited in 1951 at Chicago to revitalize the Graduate School of
Business. “The result was a tremendous change in the school’s fortune
–in faculty and students head count, and in the increasing eminence of
the school. The University of Chicago consistently rates in the top
five business schools in the United States and among the top ten
internationally. In the past 25 years, the University of Chicago has
won or shared eight Nobel prizes in economics –five of them by
scholars affiliated with the Business School– versus one for all other
business schools combined” (Niederhoffer 1997, 264). In fact, a
large part of the main founders of the current financial economics
comes precisely from this Graduate School of Business. Lorie and
Fisher created the Center for Research in Security Prices (CRSP),
which had an important group of Ph.D. students –such as Eugene Fama,
Benjamin King and Arnold Moore– and benefited from a large financial
aid from a financial pool. This centre had the support of one of the
first academic computers to compile statistical data. This centre
aimed to produce statistical data on stock prices and to analyze price
movements and returns. Merton Miller joined them one year later, in
1961ii. The CRSP gave the opportunity to test the random character of
stock market prices as well as portfolio management.
At the same time, MIT opened a new area of research on this topic with
Sidney Alexander, Paul Cootner, Dick Eckaus, Hendrik Houthakker
(visiting professor), Ed Kuhn, Paul Samuelson, and several students,
including Walter Barney, John Bauer, Sidney Levine, William Steiger
and Richard Kruizenga. During the 1960s, Cootner supervised more than
20 theses in financial economics and became an essential figure of the
development of this discipline at MIT. Researches rose in other
universities during the same period, e.g. Columbia, Washington or Los
Angeles, but they had a lesser influence.
The second point concerns scientific publications. The creation of a
new scientific community requires that its new members share common
tools, references and problems. This was precisely the role of
textbooks, seminars and scientific journals. Those in financial
economics were developed from the beginning of the 1960s with the
arrival of this new generation of students. It is well known that the
American Finance Association and its journal, the Journal of finance,
already existed at that time. They were however not concerned by
financial economics before the 1960s. Created in 1940, this
association suspended its activities during World War II. Its works
were revived in 1946 with the creation of the Journal of Finance.
However, articles dealt with problems directly linked with the war and
post war difficulties, and none of them were concerned with financial
economics. It is only in 1949 that the Journal of Finance published an
article that dealt with financial markets; and only at the end of the
1950s that these articles began to drop the traditional approach,
which was mainly descriptive and did not use the new mathematics.
Articles became oriented more towards mathematics and modeling, and
specialized in financial economics. This approach was also shared by
the Journal of Business, the other major academic publication that
dealt with finance. For this reason, Stabile (2005, 143) explains
that at the time “statistical methods for analyzing the stock market
had not yet made in into the mainstream of economics”.
In fact, it was in the 1960s that seminars, textbooks and scientific
journals started to develop in financial economics. MIT and the CRSP
organized several seminars. For instance, the CRSP had biannual
seminars, which “were already famous meeting grounds where
practitioners (whose firms sponsored the Center) gathered to hear the
latest academic research before it became public” (Mehrling 2004,
chap. 2). There was also the Quadrangle Club in Chicago where Sharpe
was invited to present his ideas in 1961 in front of Miller, Lorie and
Fama (Bernstein 1992, 193). In addition, these groups had the
support of scientific journals specialized in financial economics,
such as the Journal of Financial and Quantitative Analysis, created in
1965 by the Graduate School of Business Administration of the
University of Washington, the Journal of Business, published by the
University of Chicago, and the Journal of Finance. Although older, the
last two journals changed their editorial policy during this period
and choose articles more oriented towards mathematics and modeling
–see Bernstein (1992, 414 and 129). Moreover, these revues
published several special issues to present the new orientation and
results. In 1966, the Journal of Business published a special issue on
“Recent quantitative and formal research on the stock market”. It was
the means to take stock of the CRSP’s researches for the first time.
The omnipresence of the hypothesis relative to the random character of
stock prices variations can be noticed. In 1968, three years after its
creation, the Journal of Financial and Quantitative Analysis also
published a special issue, which dealt with the application of the
random walk model to stock prices changes.
Finally, it was also during the 1960s that textbooks and collected
articles started to be publishediii. These publications also helped to
define and stabilize a shared culture for the members of this new
community. These two kinds of publications provide an indication about
the evolution of the discipline, in particular the diversification of
the subjects analyzed. Articles are generally published first, and
then collected articles and finally textbooks. During the 1960s,
collected articles in financial economics were published about 5 years
before textbooks on the same subjects. During the first part of this
decade, following the publication of Markowitz’s book in 1959, the
publications of collected articles focused on portfolio selection. It
was only at the end of the 1960s that textbooks on this subject were
published. During the second part of the 1960s, there was a
diversification of subjects, which started to structure the
discipline. In addition to portfolio selection, subjects dealt with
the nature of stock price movements, the investment returns, the
market efficiency and the CAPM –Capital Asset Pricing Model. However,
textbooks on these subjects only started to be published during the
1970s. Among these new collected articles, there is The Random
Character of Stock Market Prices edited in 1964 by Paul Cootner. This
book constitutes the first anthology of articles that analyze random
stock price movements. It has an important place in the history of
financial economics for three reasons. First it contributed enormously
to the diffusion of the random walk model and its interpretation.
Second, it sketched a research program for the future that was largely
followed. This program had two directions. The first one concerned the
random walk model and its empirical tests. The second direction dealt
with the analysis of option prices, for which the random walk model
constitutes a fundamental hypothesis for such an analysisiv. Third,
this book provided the first presentation of historical data relative
to financial economics.
The third feature deals with the definition of a new field of
investigation. Inclusion into the scientific field was not inevitable.
Consequently, to fill a new domain of research and to justify the
usefulness of their new approach, academics had to adopt a strategy to
differentiate from previous approaches. This kind of opposition was
illustrated by articles that dealt with stock price variations.
Academics chose to open several debates between their new approach,
mainly based on mathematical models and tools –in particular the
random walk model–, and previous approaches that studied stock prices
changes, in particular Chartism and business cycles –as those defended
at the NBER. These debates generally took place in specialized
journals and newspapers, such as Business Week or the Financial
Analysts Journal, in which academics popularized their results and
opposed them to professional practices. To justify the new approach,
academics used a Manichean presentation of each approach. For
instance, Cootner introduced one work by saying that:
“these academic studies have proven to be more skeptical about the
folklore of the market place than those of the professional
practitioners. To several of the authors represented in this volume
the "patterns" described by some market analysis are mere
superstitions. […] it is hard to find a practitioner, no matter how
sophisticated, who does not believe that by looking at the past
history of prices one can learn something about their prospective
behavior, while it is almost as difficult to find an academician who
believes that such a backward look is of any substantial value. The
essays in this book are exclusively of the academic type” (1964,
As other defenders of the random walk model and the new ideas, Fama
(1965, 59) presented his results as a challenge to practitioners,
who had to justify the usefulness of their practice:
“In sum the theory of random walks in stockmarket prices presents
important challenges to both the chartist and the proponent of
fundamental analysis. For the chartist, the challenge is
straightforward. If the randomwalk model is a valid description of
reality, the work of the chartist, like that of the astrologer, is of
no real value in stockmarket analysis. The empirical evidence to date
provides strong support for the randomwalk model. In this light the
only way the chartist can vindicate his position is to show that he
can consistently use his techniques to make betterthanchance
predictions of stock prices. It is not enough for him to talk
mystically about patterns that he sees in the data. He must show that
he can consistently use these patterns to make meaningful predictions
of future prices” (1965, 59).
Hoffland’s article also gives a good summary of the presentation at
“Folklore is a body of knowledge incorporating the superstitions,
beliefs and practices of the unsophisticated portion of a society […].
Folklore is distinguished from scientific knowledge by its lack of
rigor […]. The Dow theory is often used as an example of a crudely
formulated stock market "theory"” (1967, 85).
As we see, the most important argument was the scientific claim: new
academics argued that their approach was based on scientific criteria,
while Chartism would be based on folklore and would have no scientific
foundation. Financial economics was supposed to drill above and beyond
previous folkloric practices, and the random walk model was presented
as the uniquely available scientific analysis of the character of
stock price changes. The vocabulary used was intentionally clearcut
to convince the reader: “scientific”, “folklore” or “challenge”. In
addition, academics chose to call the new discipline modern financial
theory to insist on its novelty, and they often underlined that only
scientific tests can separate the folklore from their scientific
approach. Chartists and professionals were not the only targets. Many
authors used the publication of textbooks as opportunity to express
their dissatisfaction with textbooks available before, especially
because their lack of analytical content and their heavy emphasis on
descriptive material. After the 1960s, once financial economics was
permanently embedded into the scientific field, these debates
disappeared: they lost their significance, because the scientific
community and many financiers permanently recognized and adopted
These new seminars and publications contributed to the creation of a
truly homogenous community, which shared common problems, tools and
language, scientific journals and courses in universities. The use of
the theory of modern probability, in particular through the conception
of uncertainty, offered new perspectives on already existing problems.
At that time, however, such developments were technical and any
theoretical explanation did not exist. In other words, during this
period the modern theory of probability provided new tools that social
sciences could exploit, but, obviously, this is not enough to build a
new discipline: a model does not contain causalities per se, because
the choice between endogenous variables and exogenous variables comes
from theoretical frameworks. Indeed, a theory gives causalities that
allow defining the structure of the model. These new tools from modern
theory of probability cannot provide an explanation to the empirical
environment. Therefore, theoretical frameworks are necessary to
introduce financial economics into the scientific field. More
precisely, it was necessary to link the new approach with an existing
science or with the criteria of conventional acceptancev of that time.
The use of the contemporaneous scientific method –the tests and the
hypotheticodeductive method– already constituted an important link.
However, during the 1960s, the crucial step for the creation of the
financial economics was the construction of theoretical explanations
based on concepts from economics.
Finally, during the 1950s and the 1960s, the main features of
financial economics were set: 1) there is an academic community with
students; 2) financial econometrics was more and more used; 3) modern
theory of probability provided new tools to analyze old problems; 4)
and more crucial, theoretical explanations started to emerge. The
second part will focus on that last point: Modigliani and Miller’s
article, CAPM and Efficient market theory had set the theoretical
bases of financial economics that allowed the creation of this
II. The links with economics: the specific place of Modigliani and
Miller’s theorem and the CAPM.
This problem of the lack of theoretical explanation was closed since
1958. New tools, new models, new researchers and students were
existing yet; and the last step was the construction of a theoretical
corpus that can be recognized as scientific. This last step was
allowed thanks to economics, which was already accepted as a
scientific, as well as academic, discipline. Here, Modigliani and
Miller’s article, CAPM and Efficient market theory played a key role
in the creation of financial economics. By linking empirical results
and new mathematical results with economic equilibrium, these works
gave the first theoretical contents to the new discipline.
II.1. Modigliani and Miller’s article
Modigliani and Miller (1958) used stochastic processes, developed
thanks to the modern theory of probability, to analyze the old problem
of capital structure of the value of the firm. Their main theorem
states the value of a firm is independent of its capital structure. It
can actually be thought of as an extension of the "separation theorem"
originally developed by Irving Fisher (1930)vi. ModiglianiMiller
extended this proposition thanks to the arbitrage argument. They
assume there are two otherwise identical firms (that is, with the same
total future cash flows from assets), one unlevered and one not. They
then show that if the sum of the current values of the stock and bonds
of the levered firm were not equal to the current value of the stock
of the unlevered firm, there would be an arbitrage opportunity.
Consequently, arbitrage enforces that the value of the firms to be
identical, whatever the composition of the firm's financial structure.
According to the construction of financial economics, the most
important contribution of Modigliani and Miller’s article is not to be
found in its result about financial structure, but the use of an
“arbitrage proof” for their demonstration. Although Modigliani and
Miller were not the first to apply arbitrage proof in finance
(Rubinstein 2003), their article allowed to popularize it for 2
reasons: 1) their article is one of the firsts to use modern theory of
probability to analyze a financial problem –i.e. it is embedded into
the theoretical mainstream of the time–; 2) these authors had a strong
academic anchorage because they made their research at MIT and at the
University of Chicago, the two major universities that developed
financial economics at that time. Following this publication,
financial economists have used arbitrage arguments to examine a
variety of other issues involving asset pricing (Efficient market
theory, Black and Scholes model, etc.). It can be noticed that one of
the major advances in financial economics since the 1960s has been the
clarification and the formalization of the exact meaning of “no
arbitrage”. Many important results of financial economics are based
squarely on the hypothesis of no arbitrage, and it serves as one of
the most basic unifying principles of study of financial markets.
Moreover, the arbitrage proof is an extension of the economic law of
one price in perfect capital market: the forces of competition will
ensure that any given commodity will be sold at the same price. By
this way, Modigliani and Miller’s demonstration is an implication of
equilibrium in perfect capital market, which provides a direct link
with economic equilibrium. Therefore, Modigliani and Miller’s article
created a first link between economics and financial results.
II. 2. CAPM
The CAPM –Capital Asset Pricing Model– is directly concerned with the
equilibrium of financial markets. It allowed including Markowitz and
Roy’s portfolio selection model into the scientific field. It was
developed by Treynor (1961), Sharpe (1964), a Markowitz’s Ph.D.
student, Lintner (1965) and Mossin (1966). The CAPM extended
Markowitz's portfolio theory to introduce the notions of systematic
and specific risk. In fact, in 1958, James Tobin expanded on
Markowitz's work by adding a riskfree asset to the analysis. This
made it possible to leverage or deleverage portfolios on the efficient
frontier. Tobin introduced the notions of a superefficient portfolio
and the capital market line. Through leverage, portfolios on the
capital market line are able to outperform portfolio on the efficient
frontier. The CAPM proves that Tobin's superefficient portfolio must
be the market portfolio. All investors will hold the market portfolio,
leveraging or deleveraging it with positions in the riskfree asset
in order to achieve a desired level of risk. The CAPM decomposes a
portfolio's risk into systematic and specific risk. Systematic risk is
the risk of holding the market portfolio. As the market movements,
each individual asset is more or less affected. To the extent that any
asset participates in such general market movements, that asset
entails systematic risk. Specific risk is the risk which is unique to
an individual asset. It represents the component of an asset's return
which is uncorrelated with general market movements. According to the
CAPM, the marketplace compensates investors for taking systematic risk
but not for taking specific risk. This is because specific risk can be
diversified away. When an investor holds the market portfolio, each
individual asset in that portfolio entails specific risk, but through
diversification, the investor's net exposure is just the systematic
risk of the market portfolio. Systematic risk can be measured using
beta. According to CAPM, the expected return of a stock equals the
riskfree rate plus the portfolio's beta multiplied by the expected
excess return of the market portfolio.
The CAPM is built using an approach familiar to economists for three
reasons. First, one assumes some sort of maximizing behavior on the
part of participants in a market; second one investigates the
equilibrium conditions under which such markets will clear; third,
markets are perfect. While the CAPM is based on unreasonable
hypothesis for practice, it has a theoretical value: it gave the
standard finance paradigm for market equilibrium under uncertainty.
II.3. The links with economics through the construction of efficient
The last theory that was built during the 1960s and that linked
financial econometrics results with economics is the efficient market
theory. With their recognition of the absence of theoretical
explanation for the random walk model, Working (1956, 1958, 1961)
and Roberts (1959) were also the firsts to make links with the
economic theories in order to give theoretical foundations to the
random walk character of stock price fluctuations. They made it
through the arbitrage proof and proprieties of economic equilibrium.
Roberts suggested linking the random character of stock price with the
absence of profit: “if the stock market behaved like a mechanically
imperfect roulette wheel, people would notice the imperfections and by
acting on them, remove them” (1959, 7). Here Robert used the
“arbitrage proof” argument, updated by Modigliani and Miller’s
article. In his 1960 article, Cowles (1960, 9145) makes a first
reference to a competitive market and uses the demonstration by no
arbitrage opportunity. This article constitutes the beginning of a
connection with the standard economic theory that progressively led to
elaborate the efficient market theory. Two years later, Cootner
(Cootner 1962, 25) suggested the idea of the efficient market
theory, although he did not use the expression. This suggestion to
link the random walk model, information, and the economic equilibrium
was used, and then diffused, by several students of Cootner. It also
interested researchers at the University of Chicago Graduate School of
Business, most notably a young graduate student, Eugene Fama. In his
Ph.D. thesis, defended in 1964 and published the next year in the
Journal of Business, Fama synthesized empirical work and gave his
first formulation of the efficient market theory:
“An "efficient" market is defined as a market where there are large
numbers of rational, profitmaximizers actively competing, with each
trying to predict future market values of individual securities, and
where important current information is almost freely available to all
participants. In an efficient market, competition among the many
intelligent participants leads to a situation where, at any point in
time, actual prices of individual securities already reflect the
effects of information based both on events that have already occurred
and on events which, as of now, the market expects to take place in
the future. In other words, in an efficient market at any point in
time the actual price of a security will be a good estimate of its
intrinsic value” (1965, 56).
This kind of market is characterized by the equalization between the
price of a security and its equilibrium value –i.e. the intrinsic
value. The major point is that price is equal to the value of the
security, which is determined by using the whole information. In his
1970 article, Fama formulated the definition of the efficient market
that is generally used: “a market in which prices always "fully
reflect" available information is called "efficient"” (1970, 383).
According to efficient market theory, if the model of equilibrium does
not use all available information to evaluate the value of the
security, it will be possible to make an arbitrage. Thus, on an
efficient market, the equalization between the price and the
equilibrium value means that all available information is included in
the price. Consequently, it is not possible to use past information to
predict the future changes of the prices: present and future prices
are independent from the past prices. For this reason, in an efficient
market, stock price changes must be as random as the arrival of new
information. In other words, according to this theory, the random walk
model can simulate the dynamic evolution of equilibrium prices in a
competitive market. As a result of this link with economic
equilibrium, the efficient market hypothesis allowed the introduction
of financial economics into the scientific field.
Bernstein, Peter L. 1992. Capital ideas : the improbable origins of
modern Wall Street. New York and Toronto: Free Press; Maxwell
Macmillan Canada; Maxwell Macmillan International.
Bourdieu, Pierre. 1975. La spécificité du champ scientifique et les
conditions sociales du progrès de la raison. Sociologie et sociétés
(Montréal) 7. 1: 91118.
. 2004. Science of science and reflexivity. Cambridge:
Bourdieu, Pierre and Loïc J.D. Wacquant. 1992. Réponses. Pour une
anthropologie réflexive. Paris: Éd. du Seuil.
Chaumont, Loïc, Laurent Mazliac, et al. 2004. L'héritage de Kolmogorov
en mathématiques. Paris: Belin (forthcoming).
Christ, Carl F. 1994. The Cowles Commission's Contributions to
Econometrics at Chicago, 19391955. Journal of Economic Literature
XXXII. March: 3059.
Cootner, Paul H. 1962. Stock prices: Ramdom vs. systematic changes.
Industrial Management Review 3. 2: 24.
Cootner, Paul H. 1964. The random character of stock market prices.
Cambridge, Mass.: M.I.T. Press.
Cowles, Alfred. 1933. Can Stock Market Forecasters Forecast?
Econometrica 1. 3: 309324.
. 1944. Stock Market Forecasting. Econometrica 12. 3/4:
. 1960. A Revision of Previous Conclusions Regarding Stock
Price Behavior. Econometrica 28. 4: 909915.
Dimson, Elroy and Massoud Mussavian. 1999. Foundations of Finance.
Aldershot: Dartmouth Publishing Company.
Fama, Eugene F. 1965. Random Walks in StockMarket Prices. Financial
Analysts Journal 21. 5: 559.
. 1970. Efficient Capital Markets: A Review of Theory and
Empirical Work. Journal of Finance 25. 2: 383417.
Fisher, Irving. 1930. The theory of interest as determined by
impatience to spend income and opportunity to invest it. New York:
Fredrikson, E. Bruce. 1965. Frontiers of investment analysis.
Scranton, Pa.: International Textbook Co.
. 1971. Frontiers of investment analysis. Scranton, Pa.:
Intext Educational Publishers.
Hoffland, D. L. 1967. The Folklore of Wall Street. Financial Analysts
Journal 23. 3: 858.
Houthakker, Hendrik S. 1953. Discussion on Professor Kendall's Paper,
The Analysis of Economic TimeSeries. Journal of the Royal Statistical
Society 116. 2534.
Jean, William H. 1970. The analytical theory of finance; a study of
the investment decision process of the individual and the firm. New
York: Holt, Rinehart.
Jovanovic, Franck. 2004. The Construction of the Canonical History of
Financial economics. Presented at History of Economics Society
Kendall, Maurice George. 1953. The Analysis of Economic TimeSeries.
Part I: Prices. Journal of the Royal Statistical Society 116. 1125.
Lintner, John. 1965. The Valuation of Risk Assets and the Selection of
Risky Investments in Stock Portfolios and Capital Budgets. The Review
of Economic Statistics 47. 1: 1337.
Lorie, James Hirsch. 1965. Controversies on the Stock Market. Selected
Papers, Graduate School of Business of the University of Chicago.
Lorie, James Hirsch and Richard A. Brealey. 1972. Modern developments
in investment management: a book of readings. New York: Praeger.
Mandelbrot, Benoit. 1966. Forecasts of Future Prices, Unbiased
Markets, and "Martingale" Models. Journal of Business 39. 1, Part 2:
Mao, James C. T. 1969. Quantitative analysis of financial decisions.
[New York]: Macmillan.
Markowitz, Harry M. 1952. Portfolio Selection. Journal of Finance 7.
. 1959. Portfolio selection; efficient diversification of
investments. New York: Wiley.
Mazliac, Laurent. 2003. Andrei Nikolaievitch KOLMOGOROV (19031987):
Un aperçu de l'homme et de l'œuvre probabiliste.Cahiers du CAMS.
Mehrling, Perry. 2004. The Price of Risk: Fischer Black and the
Revolution in Finance. Wiley, forthcoming.
Modigliani, Franco and Merton H. Miller. 1958. The Cost of Capital,
Corporation Finance and the Theory of Investment. The American
Economic Review 48. 3: 261297.
Moore, Basil J. 1968. An introduction to the theory of finance ;
assetholder behavior under uncertainty. New York,: Free Press.
Mossin, Jan. 1966. Equilibrium in a Capital Asset Market. Econometrica
34. 4: 768783.
Niederhoffer, Victor. 1997. The education of a speculator. New York:
John Wiley & Sons.
Prais, S. J. 1953. Discussion on Professor Kendall's Paper, The
Analysis of Economic TimeSeries. Part I: Prices. Journal of the Royal
Statistical Society 116. 2534.
Roberts, Harry V. 1959. StockMarket "Patterns" and Financial
Analysis: Methodological Suggestions. Journal of Finance 14. 1: 110.
Roy, A. D. 1952. Safety First and the Holding of Assets. Econometrica
20. 3: 431449.
Rubinstein, Mark. 2003. Great Moments in Financial Economics: II.
ModiglianiMiller Theorem. Journal of Investment Management 1. 2:
Samuelson, Paul A. 1965a. Proof that properly anticipated prices
fluctuate randomly. Industrial Management Review 6. 2: 4149.
. 1965b. Rational theory of warrant pricing. Industrial
Management Review 6. 2: 1340.
Sharpe, William F. 1964. Capital Asset Prices: A Theory of Market
Equilibrium under Conditions of Risk. Journal of Finance 19. 3:
Stabile, Donald. 2005. Forerunners of modern financial economics : a
random walk in the history of economic thought. Northampton, MA:
Edward Elgar Pub.
Treynor, Jack L. 1961. Toward a Theory of Market Value of Risky Assets.Unpublished
manuscript: reprint in Dimson and Mussavian (1999).
Working, Holbrook. 1934. A RandomDifference Series for Use in the
Analysis of Time Series. Journal of the American Statistical
Association 29. 1124.
. 1949. The Investigation of Economic Expectations. The
American Economic Review 39. 3: 150166.
. 1956. New ideas and methods for price research. Journal
of Farm Economics 38. 142736.
. 1958. A Theory of Anticipatory Prices. The American
Economic Review 48. 2: 188199.
. 1961. New Concepts Concerning Futures Markets and
Prices. The American Economic Review 51. 2: 160163.
Wu, HsiuKwang and Alan J. Zakon. 1965. Elements of investments. New
‡ Département des Sciences économiques, Université du Québec à
Montréal (UQAM), 315 St. Catherine St. East, Montreal H3C 3P8, Canada.
Email: [email protected]
i A sequence of random variables Pt adapted to ( ) is called a
martingale if . This means that the better estimation of the
security’s price at the time t+1, Pt+1 with the available information
at the time t, Φt, that we can do at the time t is the security’s
price at the time t, Pt. Thus the expected profit, y, between two
periods, considering the available information at the time t, Φt, is
ii This center was also managed by Fisher Black, whose successor was
Myron Scholes. Both elaborated the pricing options model, which was
published in 1973.
iii For instance, Cootner (1964), Fredrikson (1965), Wu and Zakon
(1965), Fredrikson (1971) or Lorie and Brealey (1972) published
collected articles, while Moore (1968), Mao (1969) or Jean
(1970) published textbooks.
iv It is known that, during the 1960s, the analysis of options gained
an important interest.
v I consider that the acceptance of a theory or a theoretical model
does not only depend on empirical validation; there are also the
criteria of conventional acceptance. The conventional acceptance
concerns the conventions –postulates, beliefs, etc.– that a theory (or
a model) must respect in order to be accepted as a scientific result
of a discipline.
vi Fisher had argued that with efficient capital markets, the
production decision of an entrepreneurowned firm ought to be
independent of the intertemporal consumption decision of the
entrepreneur himself. In other words, the profitmaximizing production
plan of the firm will not be affected by the borrowing/lending
decisions of its owners, i.e. the production plan is independent of
the financing decision.