Essay on Financial Economics and Nobel Laureates
Fallacies of the Nobel Gods
Beware of false prophets, who come to you in sheep’s clothing but inwardly are ravenous wolves.
Pure mathematics consists entirely of assertions to the effect that, if such and such a proposition is true of anything, then such and such another proposition is true of that thing.... Thus mathematics may be defined as the subject in which we never know what we are talking about, nor whether what we are saying is true.
The madness that characterized the Great Bubble had among its intellectual cheerleaders the most honored financial theoreticians on the planet – economists that boasted Nobel Prizes in Economic Science.
Commonsense notions of value and financial prudence were vanquished by this new priesthood and their acolytes.
In five decades, an army of irrationally exuberant zealots slowly ground down and recycled the practical and folksy wisdom of traditional Wall Street, spewing theories of utter nonsense, while sprinkling the crowd of Lesser Fools with the holy water of arcane mathematics.
Statistical methods had been used to solve industrial problems since the nineteenth century, when engineers like Frederick W. Taylor and Henry L. Gantt laid the basis for 'scientific management'.
These early pioneers had to battle to have their ideas accepted, since businessmen paid little attention to suggestions from inexperienced theoreticians.
Taylor and Gantt observed workers on assembly lines and used statistical methods to measure their behavior. Scientific techniques helped increase productivity and turned America into the leading industrial power
In the 1930s, two young PhDs produced writings that had a profound effect on Wall Street.
Benjamin Graham and John Burr Williams said that the intrinsic value of securities should be based on facts and commonsense. Both Graham and Williams had been security analysts before putting thoughts on paper.
Many young economists who earned their credentials during the 1940s and 1950s were fascinated with the possibility of applying higher mathematics to practical problems of investment and corporate finance.
The extraordinary fawning attention given economists during Roosevelt’s New Deal spawned a class of academics with sufficient hubris to believe that they were qualified to dictate, ex cathedra, operational norms for business.
During World War II, the government called on mathematicians and consultants, like the RAND Corporation, to break enemy codes, calculate artillery trajectories, and improve hunting techniques for submarine warfare.
The authorities brought together a variety of specialists to work in teams, merging skills of practitioners with academics.
After the war, these people returned to civilian work, eager to apply advanced quantitative methods to business. Young men like Robert McNamara rose from modest jobs in the Department of War to key positions in industry, introducing management by numbers.
In the universities, during the 1950s, economists turned to higher mathematics to solve problems of investment and corporate finance.
However, unlike Benjamin Graham and John Burr Williams of the 1930s, these new gurus rarely had experience in capital markets or in running finances of corporations.
Their writings arose from mathematical models and arbitrary assumptions, rather than scientific observation of investor behavior or intimate knowledge of the workings of market institutions.
Their proofs were abstract, not experimental, and their footnotes did not refer to actual observations but rather to writings of other economists, who relied on similar mathematical proofs and the writings of still other economists.
The government goes to extreme lengths to assure that drugs are not sold to the public without years of rigorous experimentation, testing, and proof so that no one will be harmed. However, investors have no similar protection against the quackery of 'economic science'.
The mathematical scribbling of this group of self-acknowledged experts contained ideas that gradually changed behavior of Wall Street. A common theme was that risk was good and must be embraced to ensure progress and economic well-being.
In 1967, McGeorge Bundy, president of the highly conservative Ford Foundation, preached the new philosophy of risk to fellow endowment fund managers:
We have the preliminary impression that over the long run caution has cost our colleges and universities much more than imprudence or risk taking.
( Ford Foundation, 1966 Annual Report.)
According to this new doctrine, risk could be measured precisely. With the proper tools, people could 'manage risk' and maximize returns with efficiency.
Risk could be sliced and diced, diversified, spread, and traded, until everyone ended up with their appropriate share, thanks to a perfect market with rational players.
The race to apply abstract mathematics to investment markets produced six Nobel laureates who, with a great many others, provided the intellectual underpinnings for the Great Stock Bubble of the 1990s.
The first of these men was Harry Markowitz who, with no practical knowledge of securities markets, wrote a doctoral thesis on portfolio selection. This was published in the Journal of Finance in March 1952 and became the foundation of Modern Portfolio Theory (MPT).
Markowitz had never worked as a portfolio manager. His exposure to the securities market seems to have been limited to discussions with two investment officers at Yale University.
He proposed that in designing a portfolio of securities, practitioners should use mathematical techniques that were distinct from the skills needed to select the securities in the portfolio. Like Keynes, Markowitz assumed the goal of investment was to maximize total return from year to year.
He defined risk as variance in total return (dividend yield plus capital gains) on specific securities, measured against returns of the broader market.
In case the reader missed the point that investment was equivalent to gambling, he illustrated his mathematical thesis with explicit drawings of a carnival wheel of fortune.
Markowitz said that an efficient portfolio was one that provided maximum returns with minimum short-term variance.
The problem with this approach, however elegant the mathematics, was that it depended on the assumption that historical data on stock prices was useful in projecting risk.
In the next five decades, capital gains gradually became the largest portion of stock returns, as dividends diminished. By the 1990s, portfolio analysts routinely used betas – a statistical measure of covariance in stock prices – as a proxy for the risk of owning stocks.
Modern Portfolio Theory became a tool for fund managers engaged in competing for the yearly Short-Term Total Return Prize, but it failed to deal with the risk that a portfolio might not provide investors with dependable cash income in the long run.
An important aspect of Modern Portfolio Theory is that it defines efficient portfolios in terms of relative, not absolute risk. In other words, if an investor’s portfolio declines fifty percent, while the market falls fifty-one percent, a practitioner of Modern Portfolio Theory might classify the portfolio as being on the efficient frontier.
It is as if soldiers manning a string of forts on the frontier of the Old West were to declare the redoubts to be efficient, as long as defenders of each garrison were wiped out in the same proportion in all Indian raids.
An inefficient fortification would be one in which relatively more soldiers were killed than in other strongholds. Obviously, to long-term investors seeking to preserve their life savings, notions of relative safety and mathematical efficiency offer little comfort.
The next two Nobel laureates who made their mark on financial markets were Merton H. Miller and Franco Modigliani who published 'The Cost of Capital, Corporate Finance, and the Theory of Investment' in the American Economic Review in 1959.
Two years later, they wrote a follow-up, 'Dividend Policy, Growth, and the Valuation of Shares,' for the Journal of Business. This work became known as the Miller-Modigliani Theorem – the M&M Theory, for short.
The M&M Theory was that:
Under certain limiting circumstances, the capital structure of a corporation was irrelevant. Financial managers could ignore the source of financing when investing.
Decisions about the asset side of the balance sheet should not be influenced by the composition of corporate liabilities.
Furthermore, dividends were irrelevant to investors.
The practical effect of these strange hypotheses was that they gave company managers a theoretical basis for justifying excessive debt and for skipping dividends.