“There is nothing so terrible as activity without insight”
– Goethe

After applying the insights into electronic media of 1960s media guru Marshall McLuhan in an attempt to gain a better perspective on today’s financial markets (“Market McLuhan”, The Analyst, December 2011), it is a logical step to turn to the work of media and cultural theorist Neil Postman, who was greatly influenced by McLuhan as a student in the late 1950s. Postman became a professor at New York University where he taught for 40 years and authored 18 books, one of which, a best-seller in 1985 entitled Amusing Ourselves to Death, warned of the deficiencies of mass media, principally television, in sharing and addressing serious ideas. He wrote that with the advent of electronic media, images have in very large part replaced the written word in our cognitive spheres. thereby reducing and making more difficult the kind of thoughtful public discourse on serious political and economic matters that the organization of the printed word made possible. Modern electronic media avoid complex issues or demean them by presenting them in a superficial and entertaining fashion replete with humour, hyperbole and catching images, sounds and music.

Since Postman first wrote of these issues, the advent and widespread adoption of computers, the internet, the iPhone and the Blackberry have made the electronic screen a nearly constant feature of daily life in all developed (and even many less developed) countries. While the written word is featured on these devices, it is greatly abbreviated and simplified and typically embedded in distracting images and sounds. The ability to read deeply – which is akin to thinking deeply – has been to a large extent sacrificed in the new electronic media. Drawing on McLuhan’s work, Postman argued that different media are appropriate for the communication of different kinds of thought and knowledge and that the loss of the primacy of the written word is leading to the loss of our ability to think rationally and in depth about serious matters and ultimately to address effectively the vitally important issues of our civilization.

The fragmentation of attention spans that has come about as a result of competing electronic media and programming and their intrusion into daily life through their ubiquity and portability have been a further complicating factor in our ability to think at length or profoundly about issues at hand and have a tendency to cause either ill-thought-out actions or a state of confused inaction. Postman also argued that the electronic media of television and the internet generate in large part a top-down transfer of information and lack much of the interactive dimension that is necessary to gain a full understanding of how to interpret and use information effectively. We have become awash with information – facts and figures, much of them useless and distracting, – with little improvement in our ability to solve our problems. For example, who among us still believes that the greatest problems of the world today – global hunger, government oppression, financial system meltdowns – would be any more solvable if we had more facts or figures?

“Too many facts, too short attention-spans hinder out problem-solving abilities”

The world today has many examples of so-called artificial intelligence which it is purported can think and make decisions as well as or more effectively than the human mind. This claim is usually based on the ability of computers to process more information than the human mind. But if the computers’ decision-making has been oversimplified then the artificial intelligence is worse than useless–it can be a danger to our lives because it has the aura of scientific precision when in fact it is stupid and is capable of errors more extreme than any human being would make.

Postman believed that new technology can never substitute for human values and judgment and that modern society relies too heavily on information and not enough on values and judgment to fix its problems. What began as a liberating stream of information has turned into a deluge of chaotic unconnected facts and figures. He argued that the connection between information and effective action has been severed, noting that “information is now a commodity that can be bought and sold or used as a form of entertainment or worn as a garment to enhance one’s status.”

In a later book entitled Technopoly: The Surrender of Culture to Technology (1992) Postman argued the United states and countries that emulate its way of life have become technopolies in which the common beliefs are: 1) that the primary goal of humanity is numerically measured efficiency and 2) that technical calculation is in almost all respects superior to human judgment. Most citizens of such societies have become technophiles who strive to adopt all new technologies as quickly as possible without fully appreciating the costs to their quality of life and to their ability to explore the full range of their human faculties and potential. Postman’s recommended solution to this quandary was to educate human beings as early as possible in the history, social effects and psychological biases of all technologies (including the history of the evolution of the bodies of knowledge of all sciences or other fields of study in tandem with studying those fields) so that people could place the technologies that shape their lives in perspective, gain better control of them and use them more effectively rather than being unconsciously used by them.

All of this is not to say that new electronic technologies do not bring benefits through spreading information, spurring new ideas, and increasing human knowledge. It is merely to emphasize that the new technologies do not in themselves expand our wisdom. Socrates stated that the receipt of too much information without proper instruction in how to use it results in people being thought very knowledgeable when they are for the most part quite ignorant. The distinction between information and intelligence can all-too-often be under-appreciated – even by some of the most intelligent people.*

The securities markets of today are driven by massive applications of relatively new technology. Some of these technologies employ vast amounts of irrelevant, superficial information, including past pricing statistics. that create an illusion of complex understanding that surpasses human intelligence but which in fact represent very narrow superficial perspectives. esult in knee-jerk conclusions and responses, and embody the potential for catastrophic errors.

The belief that tomorrows risks in securities and their underlying businesses or economies can be inferred from yesterday’s prices and price-volatilities lies at the heart of the capital asset pricing model (CAPM) and modern portfolio theory and is a basis for a wide range of quantitative trading techniques. The collapse of Long-term Capital Management (LTCM) in 1998 is an exemplary tale of how past volatility and price relationships are not a guide to future shocks that may lie in wait. Ironically LTCM was designed to minimize risk on the basis of the efficient market teachings of two Nobel Laureates, Robert Merton and Myron Scholes. However, it ended up collapsing because the mathematical models used for hedged investments did not contemplate the effects on capital markets emanating from Russia’s debt default in August 1998. Past price spreads and relationships ceased to prevail in the environment of fear and a broad investor scramble for liquidity that followed this event. Billions of dollars were lost by the LTCM partners in a forced bank bailout supervised by the U.S. Federal Reserve.

The CAPM is a useful model to use when thinking about capital markets but markets often behave very differently from the model. Markets are not random and traders often follow trends. conditions that do not fit the concept of rational investors in an efficient market. The managers of LTCM knew that their mathematical models were imperfect but they believed the models were superior to human judgment. The models did not come close to representing the complex realities of the marketplace. In physics and engineering models can be tested and results can be used reliably to build safe aeroplanes and bridges, but in economics and finance models do not represent reality but rather a synthetic simplified environment and cannot be completely relied upon with safety. The management of LTCM took on levels of financial leverage which greatly magnified the effects of the mathematical models’ imperfections. They were blinded by the false aura of precision of their own technology. Robert Merton said in the aftermath that he was distraught over the negative reflection on modern financial theory of the failure of LTCM’s models. He advocated the design of more sophisticated models. Investors more focused on the appropriate use technology in investing might question whether any purely formulaic model could ever pose an acceptable level of risk**.

“We live in a technopoly in which it is assumed that technical calculation is usually superior to human judgement”

An earlier example of over-reliance on past statistics that resulted in a financial collapse appeared in the junk bond phenomenon in the US in the 1980s. The hitherto high yields and low default ratios of below-investment grade corporate debt was used by the enterprising investment dealer Drexel Burnham, guided by its then whiz-kid head trader Michael Milken, as a basis for floating billions of dollars of junior debt in already heavily levered companies. This form of financing was used by capital-short entrepreneurs to make acquisitions at inflated prices of a vast array of small and large U.S. companies in a speculative takeover binge described as an egalitarian form of financing that would make corporate America more efficient. At the first signs of a recession in the early 1990s, the new junk debt which had created levels of financial leverage never seen before went into default. Junk debt (also euphemistically named high-yield debt) was revealed to represent in effect the common equity of companies and these companies were in many cases so over-levered that they were unable to withstand the effects of an economic slowdown. The junk bond market collapsed. taking Drexel Burnham with it, and Milken received a jail term for securities and tax violations and paid US $600 million in SEC fines and settlements to investors.

The financial crisis of 2008 presented a very recent example of over-reliance on past statistics as a future guide for future risks. In this case, the low historic default rates on home mortgages in the U.S. including sub-prime mortgages, were used during the 1990s as a basis for advancing excessive mortgage credit and the mathematical risk-models of investment firms were used to package mortgage-backed securities that were then rather glibly rated by rating agencies based on past experiences of default rates and sold in vast quantities to investors. The models used to determine the value of mortgage –backed securities did not include in their expectations the possibility of the disastrous future events which actually occurred. While politics and failures in due diligence among intermediaries compounded the problem, the inclination to take the results of mathematical risk measurements based on past figures rather than making a rational comprehensive judgment about future risk based on evidence of widespread over-building and reckless lending practices was a crucial fundamental error that caused the financial industry to require a massive government bail-out amounting to hundreds of billions of dollars (and still counting) to avoid the collapse of the financial system and brought the country to the brink of an economic depression.

The financial world of 40 years ago –before the computerization of trading, quantitative analysis and program trading, the proliferation of index and commodity funds and derivatives, the boom in hedge funds, the advent of high-frequency trading – was more focused on fundamentals and longer-term considerations. However it can be legitimately criticized for often having been inflexible and unresponsive to economic trends and needs. Today’s freer markets have brought many benefits but experience with them has demonstrated that excessive market freedom and the over-eager adoption of new technologies can create very dangerous dynamics. Free markets are usually sensible but they are not invariably so.

No economic or financial model can free us from the need to apply all of our faculties in thinking for ourselves to solve our problems. The danger lies in assuming that markets will always follow a particular pattern of behaviour that can be programmed with the aid of technology and used as a reliable basis for betting heavily on future performance.

Two defences against the downside of today’s financial world are in the process of being addressed by regulators: 1) limits are being placed on the size, financial leverage and types of securities activities of financial institutions which take deposits from the public and whose failure could by reason of their size, damage the financial system and the economy, and 2) restrictions are increasingly being placed on some of the casino-type activities such as credit default swaps and high-frequency trading. A third measure that investors would do well to impose on themselves would be the refusal to surrender human judgment to any purely technology-based investment decision-making process. Few people would allow a computer to choose their clothing, their houses, their cars or their friends. It is an anomaly that in the field of investment, where people tend to have much more at stake, they are very often willing to do so.

* Larry Page, co-founder of Google, a company which has contributed phenomenally to making people better informed, once said in a speech: “…for us working on search is a way to work on artificial intelligence…” and “Google is trying to build artificial intelligence and to do it on a large scale.”

** Not all Nobel Laureates are inclined to over-rely on mathematical models for investing. In the 1990s this author sat on an ad hoc committee that was formed to review and update the body of knowledge for the Chartered Financial Analysts Institute. Also on the board was Nobel Laureate William Sharpe, one of the originators of the Capital Asset Pricing Model, who created the Sharpe ratio for risk-adjusted investment performance analysis. Always modest about his accomplishments, he was equally modest about the appropriate use of the quantitative tools that he brought to the challenge of managing risks and returns. Sharpe emphasized then that he had devised a model to help in understanding risk and returns – a potentially useful reference tool – not an accurate model for how the markets can be forecast to always behave. Unfortunately over the years many speculators have not paid heed to his qualifying remarks and have treated his theories as precise, highly reliable models for trading purposes.