Last week’s The Economist magazine (September 23rd-29th 2006) reported that a bunch of investors is now $6 billion dollars or so poorer this week after it emerged that Amaranth Advisors, a hedge fund that had some $9 billion dollars under management, suffered catastrophic losses in a few weeks on the back of falling natural-gas prices.

Apparently, Brian Hunter, a 32 year old Canadian Energy trader, who had made a fortune for Amaranth and himself in 2005 when he bet on natural-gas futures rising, continued to hold similar highly leveraged and insufficiently hedged positions this year. Alas for Amaranth, the surge of gas prices after Hurricane Katrina has reversed its trend and Hunter is blamed for leaving the fund exposed to falling prices. A loss of $6 billion is the consequence.

In 1998 Long-Term Capital Management, a high profile hedge fund, founded by John Meriwether (the former vice-chairman and head of bond trading at Salomon Brothers) folded losing $4.6 billion in less than four months. On its board of directors were Myron Scholes and Robert C. Merton, who shared the 1997 Nobel Prize in Economics. The company prided itself on its use of extremely complicated mathematical models developed to take advantage of fixed income arbitrage deals. Of course the world does not run according to complex mathematical models, no matter how complex they are, and in a massive and unexpected flight to liquidity when the Russian Government defaulted on their government bonds, LTCM hedges failed and it required a bail out of $3.625 billion dollars from the banking system led by the Federal Government. Even though on a rational basis their trading strategies seemed correct, John Maynard Keynes is attributed with warning investors that markets do tend toward rational positions in the long run, but the market can remain irrational longer than you can stay solvent.

LTCM and Amaranth Advisors are obviously not the only two market horror stories we are aware of. The twenty-first century has brought with it financial markets rife with horror stories of mismanagement, negligence, poor checks and balances, massive conflicts of interest, corruption and greed.


A defining feature of modern times is our ability to put the future at the service of the present. Contrary to pre-modern times where the future was in the hands of the gods who supposedly provided capricious and temporary insights to oracles and soothsayers, our ability to define and influence our own futures lies at the heart of contemporary life. In the old days without insurance the death of the bread winner could reduce the family to starvation and destitution. Without credit and a tolerance for risk only the very wealthiest people could afford homes. These are no longer critical features of modern life.

The future is no longer something before which we passively bow our heads. Nowadays the future represents an opportunity the outcome of which we can influence and shape through carefully calculated decisions made in the present. Since the future always includes an element of uncertainty decision making about the future requires both speculation and the assessment of risk. As we shall discuss, speculation and risk management has become the prime driver behind the dynamics of modern society.


The word “risk” derives from the Italian risicare which means to dare. To risk is to make a choice rather than to await fate. Risk is an attitude about the future. We take risks when we can conceive of circumstances where we might influence the outcome of our or others’ decisions. Individuals have different tolerances for risk based not only on their material circumstances but their worldviews about the future.

Human nature has always included the temptation to take a chance. Throughout recorded history gambling has been a favorite past time. The enticement of gambling lies in the adrenalin rush we get as we are put head to head with our fate. We convince ourselves that Lady Luck will be our ally and swing the odds in our favor. Regular gamblers appeal to the law of averages to bring losses to a speedy end and appeal to the same law of averages to suspend itself when they are having a winning streak. As we know the law of averages is stone deaf.

The impetus of the Renaissance that paved the way for the modern period has channeled our human passion for games, betting and taking a chance into economic growth, improved quality of life and technological progress. Developments in calculated decision making and risk taking have vastly improved our ability to allocate wealth, to safeguard public health, to wage war, to determine insurance premiums, to plant corn and to prescribe the use of seat belts.

Our free market economy is all about choices, supposedly free choices for all who participate. Capitalism, as we know, is the epitome of risk taking. Market values are based on forecasting and speculation. Liquidity in the capital and money markets are based on thousands of people willing to take calculated risks. This propensity for risk taking has provided the capital that has fuelled entrepreneurial innovation, technological advancement and rapid economic growth – our benchmarks for human progress.


In order to set the scene for our discussion today, I thought it might be interesting to chart the development of the growing sophistication of techniques of speculation and risk that is part of our decision making armory today.

Prior to the Reformation, the Catholic Church policed the future through managing the distribution of sentences that determined an individual’s place in heaven or hell in the afterlife. Risk management in these times concerned obedience, appropriate penance and payment for indulgences.

The Reformation turned all that on its head leaving the individual to take responsibility for creating his or her own future by making good decisions inspired by a personal relationship with God. So called determinism by fate could now be influenced through an individual’s own decision making activities. Fate no longer had the upper hand.

Probability Theory
We begin our mini history of “risk” with the discovery of the theory of probability in 1654 by Blaise Pascal in partnership with Pierre de Fermat. Probability theory provides us with the ability to forecast the future with the help of numbers. With probability theory no longer is speculation of the future occurrence of an event described as “likely,” or “highly possible.” Now we can assert with confidence that the probable occurrence of an event is 50% or 75%.

As the development of probability theory has advanced beyond the throwing of dice and the winning at crap games, it has become a powerful instrument for organizing, interpreting and applying information. Probability theory is the mathematical heart of the concept of risk to which every insurance professional will certainly attest.
Alert 1: Numbers supposedly provide certainty about uncertainty.

The next major development in estimating the risk of possible outcomes occurring or not occurring was the idea of sampling. We have to make all kinds of decisions on the basis of limited data. Most critical decisions would be impossible without sampling. By the time you have drunk a whole bottle of wine, it is too late to pronounce it undrinkable.

Sampling is essential to risk taking. The question is how representative is our sample on which we base our judgment. The discovery of sampling is credited to an Englishman, John Graunt, who in 1603 took a strange fascination in compiling a book, “Bills of Mortality,” that contained the births and deaths in London. This was the year in which London suffered one of the worst infestations of the plague and John Graunt took a strange delight in analyzing the causes of peoples’ death. His Mortality tables outlined statistics of those who died due to consumption, French-pox, Gripping in the guts, head mould, scurvy, spotted fever, worms and so on; many illnesses that fortunately no longer plague our societies.

The manner in which Graunt analyzed his data laid the foundation of statistics. The word “statistics” is derived from the analysis of the quantitative facts about the state. Graunt realized that the statistics he had gathered in his book represented only a fraction of all the births and deaths that had ever occurred in London. By using what is now referred to as “statistical inference” Graunt drew some profound conclusions about death, disease, and length of life from his raw data. These conclusions he used to forecast demographic developments in London in later years. Graunt supposedly provided the inspiration for Statistics Offices, regular referendums, and demographic analysis.
Alert 2: Who selects the sample and how is it selected?

Life Expectancy Tables
After the development of probability theory and sampling it comes as no surprise that the next development in the measurement of risk is the development of tables of life expectancies. This development is attributed to Edmund Halley (of Halley comet fame) who, in 1693, produced a series of life tables that could be used to reckon the price of insuring lives at different ages. Despite his detailed mathematical calculation of the valuation of annuities the English Government paid no attention and continued to sell annuities at the same price to everyone regardless of age. A costly piece of finance!

Insurance is a business totally dependent on the process of sampling, averages, independence of observations and the notion of normal that motivated Graunt’s research into London’s population. The rapid development of insurance at this time is obviously no coincidence.

Lloyds of London
Throughout Europe, the seventeenth century was a period of burgeoning trade. Ships arrived from the colonies with a profusion of products and new found luxuries – sugar and spice, coffee, tea, raw cotton and fine silks. London and Amsterdam served as the hub of mercantile activity. Newsworthy news concerned the fate of ships at sea, either in pursuit of new lands and new riches, or of those returning laden with exotic treats.

The discussion of breaking news at sea took place in the coffee houses.

The London Coffee house situated at the heart of what is now the City of London was one popular source of news and rumor. Investors, returning ship captains and sailors lingered there to share their news and advise others of dangerous straits and marauding pirates. Edward Lloyd was a thoughtful and insightful coffee shop owner. Taking advantage to his exposure to critical market information, in 1696 he published the “Lloyds List” which was filled with information on the arrival and departure of ships from the London docks and intelligence on conditions abroad and at sea.

So began Lloyds of London, arguably the greatest marine insurance syndicate in the world for centuries to come.
Alert 3: Those who have more information than others may have more power but do not necessarily have the truth.

Then as now, anyone needing insurance would seek out a broker. The broker would then hawk the risk to individual risk-takers gathered in the coffee houses or in the precincts of the Royal Exchange in London. When a deal was closed, the risk taker would confirm his agreement to cover the loss in return for a specified premium by writing his name under the terms of the contract – hence the term “under-writer.”

The gambling spirit of that prosperous era fostered rapid innovation in the London insurance industry. Underwriters were willing to write insurance policies against almost any kind of risk including, house-breaking, highway robbery, death by gin drinking, the death of horses and the assurance of female chastity! All but the last are still insurable!
Alert 4: Our faith in risk management encourages us to take risks we might not otherwise take!

The Concept of Utility
The notion of utility is attributed to Daniel Bernoulli. Bernoulli emphasized decision making rather than the intricacies of probability theory. He proposed that “the satisfaction derived from a specific increase in wealth would be inversely related to the quantity of wealth previously possessed” has provided the underpinning of the theory of supply and demand to this day. Bernoulli emphasized the humans had both values and experience that influence their decisions and these affect their perception and appetite for risk. He explained that a decision involves the strength of our desire for a particular outcome as well as the degree of our belief about the probability of that outcome. The strength of our desire for something came to be known as utility. This insight led to a new understanding of how markets behave and how buyers and sellers reach agreement on price. Utility became the dominant paradigm for explaining human decision making and theories of choice based on the behavior of the rational person.
Alert 5: The concept of utility is dependent on the notion of a rational person! Do they exist?

The Law of Large Numbers
Daniel Bernoulli’s uncle Jacob takes us further along the road of probability and risk. Jacob focused on the fact that in real-life situations it is rare that we can determine the probability of an event occurring before the event occurs. In most cases we have to estimate probabilities after the fact. He suggested a solution to this problem by stating that one must assume that under similar conditions, the occurrence or non-occurrence of an event will follow the same pattern as was observed in the past. This is a giant assumption and is one we continue to pay for as our predictions are invariably wrong!

We know that the past is only a fragment of reality and that the future, the one certainly before us at this time is radically discontinuous. We also never have full information. Reality also comprises a series of connected events that are seldom if ever totally independent of one another.

Jacob Bernoulli’s theorem for calculating probabilities after the fact is known as the Law of Large Numbers. What the law of large numbers tells us, say in the case of tossing a coin, is that the average of a large number of throws will be more likely than the average of a small number of throes to differ from the true average by less than some stated amount. The Law of Large Numbers does not guarantee that heads will come up 50% of the time if you throw the coin 100, 1000, or 1 million times. What it does tell us is the variance from the true mean. Through a variety of experiments Jacob’s law became the vehicle for attempting to measure uncertainty and to calculate the probability when an empirically determined number is close to a true value even when the true value is unknown.

The Normal Distribution
Next we come upon Abraham de Moivre, a gloomy, frustrated Frenchman. During 1730 De Moivre decided to work on the mathematical project of how a sample of facts might represent the true universe from which the sample was drawn. Drawing on a variety of mathematical techniques he demonstrated how a set of random drawings distribute themselves around their average value.

De Moivre’s distribution is known today as the normal distribution or the bell curve. The shape of the curve enabled de Moivre to calculate a statistical measure of dispersion around the mean. This measure we now know as the standard deviation, a measure critically important in judging whether a set of observations comprises a sufficiently representative sample of the universe of which they are just a part.

The normal distribution forms the core of most systems of risk management. One popular question is how closely do changes in stock prices resemble a normal distribution?
Alert 6: We will do whatever we can to ensure our sample is normally distributed.

Regression to the Mean
Let me fast forward to 1875 and Francis Galton. Galton, Charles Darwin’s first cousin, whose hobby was measurement and a keen interest in heredity. His primary goal was to understand how talent persists through generation after generation in certain families.

He was very interested in the concept of deviation from the average. Galton was interested in differences and not similarities. Through his study of heredity features, Galton discovered the idea of “regression to the mean” and ultimately led to the concept of correlation which is the measurement of how closely any two series vary relative to one another.

Whenever we make a decision based on the expectation that matters will return to normal we are employing the notion of regression to the mean.
Alert 7: Identifying correlation between variables overlooks more complex systemic factors.

In 1952 Nobel Laureate, Harry Markowitz demonstrated mathematically why putting all you eggs in one basket is an unacceptably risky strategy and therefore in order to reduce risk one must diversify. Diversification reduces risk in a greater proportion than it does the average return. Diversification is a kind of free lunch as long as you minimize covariances or correlations among the returns of the various securities.

That insight revolutionized corporate finance, put Wall Street on the skids and effects business decisions around the world to this day.

Alert 8: Identifying correlations is a far more difficult and uncertain business than is often realized.

Derivatives are the most sophisticated of financial instruments. Derivatives have no value of their own – they derive their value from the value of some other asset.

In a sense they are a system of side bets based on computerized calculations designed and monitored by computer wizards using abstruse mathematical formulas even they do not understand!

Alert 9: Barings, Long Term Capital Management, Amaranth Advisors, Enron and so on…


What does this brief trot through history and our 10 Alerts do for us? First it reminds us that in a systematic and unequivocal way we have reduced the world and reality to a system of mathematical numbers.

Second, our system of numbers has given us the ability to “trade our futures”, pun intended, whereby we are continuously speculating about tomorrow without really understanding today. This phenomenon has led to thousands if not millions of people rushing to yoga classes and bookstores to buy books and tapes on how to be in the present moment, because they no longer know where to find the present never mind experience it.

Third, we have replaced one determinism, relegating our destiny to the hand of God, for another, slavery to probabilities and statistics. We still have no more freedom than before! We make policies based on statistics, allocate wealth, or withhold it, according to statistics, define intelligence according to statistics, and make complex decisions that all involve human factors based on statistics. Keynes insisted that risk management does not make us free; uncertainty does!

Fourth, we have converted or should I say contorted decision making into a science subject to algorithms and mathematical proofs. Henry Mintzberg, in his book Managers not MBAs, argues that management decision making is not a science. Management applies science. Managers need all kinds of knowledge to be effective, but management is more an art and craft than a science. Good management comes from practice in continuously changing, inter-connected and ambiguous circumstances. Causes are muddy and circular rather than clear and linear. Most MBA education is about analysis rather than creativity and synthesis.10

Fifth, as John Maynard Keynes claims, probabilities have little relevance to real life situations. We know this because the one thing we can be sure of is that we will probably get it wrong. An objective probability of a future event does not exist. Extrapolating from the past into the future ignores changes for the better or the worse. There is no such a thing as homogenous events and rarely if ever are there independent events. Volatility in the stock market is a reflection of the expected failing to happen – that is why the stock market is so risky – we keep on getting it wrong!. Capital markets have been and always will be volatile because they trade in nothing more than bets on the future which is always full of surprises.

Sixth, there is no such a thing as predictable rational behavior. If there were we would all be programmed machines devoid of whim, emotion, habit, humor or compassion.


The information you have is not the information you want

The information you want is not the information you need

The information you need is not the information you can obtain

The information you can obtain costs more than you want to pay


In his article Bad Management Theories Are Destroying Good Management Practices, the late Sumantra Ghoshal argues that the theories put out by Business faculty have played a significant role in creating Enrons

He argues that
“By propagating ideologically inspired amoral theories, business schools have actively freed their students from any sense of moral responsibility.” page 76

Management research has been led increasingly in the direction of making excessive truth claims based on partial analysis and unrealistic and biased assumptions 77

The dependence on finance mathematics and statistics as the back bone of decision analysis provides a false sense that CEO s and managers free themselves from ethical and moral responsibility

Treating business studies as a science means the denial of moral or ethical considerations in our theories and prescriptions of management practice

It fosters a false ideology of liberalism aimed at solving the negative problem of restricting social costs that arise from human imperfections. People should behave rationally or else they spoil our sample, normal distribution, or correlation analysis!

We do not take into account anything for which we cannot create a mathematical algorithm or solution

Tokenism of adding a course on ethics or social responsibility will not infuse a concern for ethics and for responsible management

Finally he argues we need to re-include pluralism into our intellectual agenda


The question I would like to place before us this evening is: how do we educate our MBA’s for the future? Have we too fallen into the trap of treating management as a science and people as a statistic?

We claim our mission is to educate our students in wisdom. Wisdom is about judgment and discernment. Wisdom relates to practical reason. Wisdom does not come from weighing probabilities but from using experience, intuition, emotional intelligence, thoughtfulness and rational assessment. Wisdom also includes faith, hope and humility in face of the mystery of the future. Wisdom depends on the inter-relationship between mind, heart and soul Do we educate our students and ourselves to make wise rather than scientific or statistical choices? When and how?


Bernstein, Peter L. Against the Gods: The Remarkable Story of Risk. New York: John Wiley & Sons, Inc., 1998.

Ghoshal, Sumantra. Academy of Management. Learning & Education, Volume 4 Number 1, March 2005.

Mackay, Charles and Joseph De La Vega. Extraordinary Popular Delusions and the Madness of Crowds & Confusion de Confusiones. New York: John Wiley & Sons, Inc., 1996.

Mintzberg, Henry. Managers Not MBAs: A Hard Look at the Soft Practice of Managing and Management Development. San Francisco; Berrett-Koehler Publisher, Inc., 2005.

Moore, G.E. Principia Ethica. Revised Edition. Cambridge, Massachusetts: Cambridge University Press, 2000.

Ross, Westerfield, Jordan. Fundamentals of Corporate finance. Fourth Edition. New York: Irwin McGraw-Hill, 1998.

(Posting date 19 October 2006)

HCS readers are invited to view other articles about SNHU or business ethics at our extensive, permanent archives under the Business Ethics section at the URL or the Christos and Mary Papoutsy Distinguished Chair in Business Ethics at Southern New Hampshire University at

The purpose of the distinguished chair in ethics is to promote and enhance students and community members awareness of ethics in personal and professional settings through teaching, community lectures and conferences. These events will foster understanding and assist in the application of lessons taught by current and classical ethicists to 21st-century settings.The chair serves as the cornerstone for an integrated university program in business ethics that encompasses the undergraduate and graduate levels. For more information about these events or about the ethics chair, contact Jane Yerrington at SNHU (603-668-2211 x2488) or visit the webpages of the ethics chair at

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