This article is the first in a series of tutorials about the techniques of post-modern securities analysis. Click the RSS button in the sidebar to get a free subscription to the whole set.

Definition of “Security Analysis”

Security Analysis is the study of facts about negotiable instruments for the purpose of determining whether a particular instrument is appropriate for a specific investor at a particular time and the intrinsic value of the security compared to its market price, if any.

This analysis is usually conducted by gathering facts about the legal jurisdiction governing the security, the terms and conditions of the issue, data on the organization issuing the security, and information on operations, laws, rules, and other factors related to the instrument or the issuer.

The determination of the appropriateness of a security is made by a critical evaluation of a wide range of facts about the instrument in terms of the current price and the needs of a specific investor. More »

In August 1952, the famous Benjamin Graham published an article in “The Analysts Journal” entitled, “Toward a Science of Security Analysis”. The article was sufficiently important to be republished in “The Financial Analysts Journal” in January 1995.

Ben Graham definitely did not say the security analysis was a “science”, but his comments implied that he would like to have the discipline move in that direction. He specifically made comparisons to the use of mathematical techniques in “actuarial science” and suggested that the practice of bond ratings was somehow scientific in nature.

By the time of the Crash of 2008, the emanations of “science” had cast a cloak of statistical pretense over the profession of securities analysis, as this abstract of the article, “The Statistics of Sharpe Ratios” (Andrew W. Lo, Financial Analysts Journal, July 2002), indicates:

The building blocks of the Sharpe ratio—expected returns and volatilities—are unknown quantities that must be estimated statistically and are, therefore, subject to estimation error. This raises the natural question: How accurately are Sharpe ratios measured? To address this question, I derive explicit expressions for the statistical distribution of the Sharpe ratio using standard asymptotic theory under several sets of assumptions for the return-generating process—independently and identically distributed returns, stationary returns, and with time aggregation. I show that monthly Sharpe ratios cannot be annualized by multiplying by √12 except under very special circumstances, and I derive the correct method of conversion in the general case of stationary returns. In an illustrative empirical example of mutual funds and hedge funds, I find that the annual Sharpe ratio for a hedge fund can be overstated by as much as 65 percent because of the presence of serial correlation in monthly returns, and once this serial correlation is properly taken into account, the rankings of hedge funds based on Sharpe ratios can change dramatically.

Now this sounds very “scientific”, especially if one has no knowledge of the scientific method and tends to believe in astrology. However, on examining the underlying assumptions of Modern Portfolio Theory (see: Fallacies of the Nobel Gods), under the harsh prism of the scientific method, problems with this approach become evident.

The above abstract seems to criticize the use of the Sharpe ratio, as a serious subject, but would a real scientific journal waste time evaluating the tenants of Medieval Astrology?

Many non-scientific practices are useful

We take our automobiles to the repair shop when they break down and are thankful for the skill and knowledge of an honest, professional mechanic who can get the machine running again. However, few would consider the auto mechanic to be a scientist.

Actuaries calculate the life expectancy of classes of individuals, based on mortality tables, but would not attempt to predict how long a specific individual will live (unless the subject is already falling from an airplane).

Much of security analysis has the purpose of determining whether the value of a security in the future will be higher or lower than the current value. A honest, competent security analysts will make such estimates based on careful and laborious study of relevant facts, and present conclusions properly hedged as to the general impossibility of predicting the future (in a non-scientific field of endeavor).

This is a valuable and useful service in itself and does not need to be dressed up in the pretense of science to become more useful.

In fact, scientific pretense can actually mislead investors (and analysts themselves).

Where pseudo-science harms investors

Leading up to the Great Crash of 2008, millions of hours of analyst time were wasted on drawing up tables with betas, Sharpe ratios, and other mathematical gimmicks that did not actually contribute to the understanding of an issue, but instead gave investors (and analysts) a false sense of security.

I would argue that this time (and many more hours) could have been better served digging up the facts about specific issues and examining operational and legal details under the cold light of common sense.

For example, would billions have been lost on auction rate securities if analysts had spent more time carefully researching the details of these issues and asked hard “what if” questions about the actual functioning of the Dutch Auctions on which their liquidity was based?

The principal problem with the pseudo-scientific approach to security analysis is that the methods often give analysts an excuse to avoid the much harder research work of going back to original sources of information and digging and digging for more facts until all relevant issues have been examined.

See: A security analysts greatest challenge: Laziness

Illustrations: Wiki Commons: The first illustration is from the Aurora consurgens, an illuminated manuscript of the 15th century in the Zurich Zentralbibliothek (MS. Rhenoviensis 172) — a medieval alchemical treatise that contains thirty-eight miniatures in watercolor.

On the cover of the July 18, 2009 edition of “The Economist” is a picture of a book labeled “Modern Economic Theory” melting down, with the sub-title, “Where it went wrong — and how the crisis is changing it.”

One of the tenets of Capital Flow Analysis is “Follow the horsemen“, referring to the “Five Horsemen of the Investment Apocalypse”, one of which is “New Economic Theory”.

Just because “The Economist” has finally figured out that something is radically wrong with “Modern Economic Theory”, doesn’t mean that a New Economic Theory has been born that will replace the old, nor that lecture fees for Nobel laureates in “Economic Science” will suddenly dry up.

I would say that it might take another twenty years before “Modern Economic Theory” is completely dead — and that would be an optimistic estimate.

“Economic Science” — the oxymoron

One of the most revealing paragraphs in the lead editorial of “The Economist” starts as follows:

But economists were hardly naive believers in market efficiency. Financial academics have spent much of the past 30 years poking holes in the “efficient market hypothesis”.

Now, what is interesting about this comment is the idea that it is necessary to “poke holes” in a hypothesis. If economics were really a “science”, the proper order of things would be:

1. Someone advances a “hypothesis” — an idea based on some facts, but not yet “proved”. It is the job of the promoter of the hypothesis to try to provide the proof.
2. After a “hypothesis” is extensively tested against real world evidence, it advances to the level of being called a “theory”. At this stage, scientists from across the globe turn their withering skeptical gaze on this newcomer, calling for further evidence and proof.
3. Finally, after a “theory” has been extensively tested and no “holes” can be found, it is accepted as being “true”. If it is of sufficient importance, it may even be called a “law”.

Now, the “Efficient Market Hypothesis” never went through this process.

Instead, it jumped from the paper of a doctoral candidate to being generally accepted, without any proof whatsoever.

Although it continued to be called a “hypothesis”, it was treated as a “law” and incorporated into the development of further hypotheses by other economists and major real world applications (like Index Funds).

Economics as a religion

Most of modern economics is not really a science, but rather a belief system, like a religion.

There are different “schools” of economics, like various branches of a church — each claiming to know the “truth” based on the writings of some earlier economic prophet, like John Maynard Keynes, Joseph Schumpeter, or Ludwig von Mises.

Some years ago, I was speaking at a seminar in Washington DC on the topic of capital market development. After the lecture, a young academic came up to me, eagerly asking, “How does what you say square with the paper of Dr. Goobledegook on the Reverse Potential of Hysterical Demand?” Of course, since I didn’t have the foggiest idea of what he was talking about, I politely declined to criticize the illustrious Dr. Goobledegook. Furthermore, I had only made, what seemed to me the obvious point, that it is difficult to create liquid markets in jurisdictions with very small populations.

But that is how “Modern Economics” works. Rather than appeal to real world evidence or commonsense, the economist is trained to base his or her “proof” on the writings of other economists.

The futile search for “economic laws”

In the final analysis, economics is a social “science” related to the constantly changing behavior of large populations.

It is one thing to document such behavior and try to understand how certain things came about. It is another to assume that society is somehow constant — like the number of protons in a gold atom — and that a universal law may be derived from the behavior of people in Southern France in 1913.

The problem that economics faces is that Nobel prizes are given not to those who merely observe and document economic history, explaining how and why things happened at a particular point of time, but rather to those who sit in ivory towers, spinning fanciful theories based on theories spun by other inhabitants of similar towers.

In general, Modern Economics seems to rush to draw conclusions based on insufficient evidence and faulty data, and then to vigorously defend such conclusions on purely theoretical grounds.

One might say that Economic Science is to Real Science what Creationist Theory is to the Theory of Evolution.

The failure of Modern Economics is nothing new

Paul Omerod published “The Death of Economics” in 1994 — over a decade ago — stating that modern economics was largely “an empty box”.

Initially shunned by mainstream economists, his thoughts are now echoed by Nobel laureates like Paul Krugman, who was quoted in “The Economist” article as saying that much of the past 30 years of macroeconomics was “spectacularly useless at best and positively harmful at worst”.

Of course, Professor Krugman does not advocate any real change in the direction of “economic science”, only a return to the writings of John Maynard Keynes.

On this website, there are numerous essays decrying the failure of modern economics, including “Fallacies of the Nobel Gods“, published in 2004.

However, as already stated, the death of one set of erroneous beliefs (perhaps prematurely declared) does not portend substitutions by new and better beliefs.

We shall have to see what emerges as a substitute for “Modern Economic Theory” before celebrating.