In William Shakespeare’s play Julius Caesar, Caesar is warned to “beware the Ides of March”. On his way to the Theatre of Pompey (where he would be assassinated), Caesar saw a seer who had foretold that harm would come to him not later than the Ides of March.
Many people on the planet subscribe to a view that future is somehow based on the whim of the God. When things do not go someone’s way, it is “bad karma”. When I was at school I do recall being superstitious. I did try and pass off some poor exam results onto a mirror I had broken that year; explaining to my father it was seven years of bad luck so there wasn’t much hope for improvement either.
In times gone past my father might have sighed in sympathy and sent me to the local druid, but this was the 1980s. My father had spent two decades in the world of finance, and he was not about to assign the future to soothsayers. He had moved across the boundary from superstition into risk management.
Risk has always been a topic close to human hearts. Our ability to predict the future determines our very survival. Risk management is at the heart of what it means to be human not just to work in finance. Risk management guides us over a vast range of decision making, from allocating wealth to safeguarding public health, waging war to planning a family, from paying insurance premiums to wearing a seatbelt, from planting corn to marketing cornflakes.
The truth is wherever we look there is a persistent tension between those who assert that the best decisions are based on quantifications and numbers, determined by the patterns of the past, and those who base their decisions on more subjective degrees of belief about the uncertain future.
Over time the controversy between quantification based on observations of the past and subjective degrees of belief has taken on greater significance. The mathematically driven apparatus of modern risk management contains the seeds of a dehumanizing and self destructive technology. In the process of breaking free from the past we face a danger of becoming slaves of a new religion, a creed that is just as implacable, confining and arbitrary as the old.
Our lives teem with numbers, but we sometimes forget that numbers are only tools. They have no soul; they may indeed become fetishes. Many of our most critical decisions are made by computers, contraptions that devour numbers like voracious monsters.
Where does this story begin, how did we arrive in this numbers fueled world?
Gambling has always held human beings in thrall. Pontius Pilate’s soldiers cast lots for Christ’s robe as he suffered on the cross. In Greek mythology three brothers rolled dice for the universe, with Zeus winning the heavens, Poseidon the seas, and Hades going to hell as master of the Underworld.
As Christianity and other religions spread, the future became a matter of moral behavior and faith. The future was not quite as inscrutable as it had been before, although most predictions were confined to the afterlife. Up to the Renaissance people perceived the future as little more than a matter of luck or the result of random variations, and most of their decisions were driven by instinct.
The Renaissance and the Protestant Reformation set the scene for the mastery of risk. The Reformation warned people they would have to start walking on their own two feet and would have to take responsibility for the consequences of their actions. By the time Columbus was seeking a new trade route to the Indies it was a clear that through trade human beings had started to take risk into their own hands. It led to the growth of modern finance and the creation of things like bonds, company stocks and insurance.
The story of numbers in the West began in 1202, when Fibonacci produced Liber Abacim, the Book of Abacas. It showed people that it was a lot easier to count in Hindu-Arabic than Roman Numerals. The notion of modern book keeping made its first appearance.
The first serious effort to develop statistical principles of probability came with Girolamo Cardano. Cardano’s Ars Magna (The Great Art) in 1545, was the first major work to concentrate on algebra. He also produced a treatise on gambling entitled Liber de Ludo Aleae (Book on Games of Chance). It was the first serious effort to develop the statistical principles of probability. Blaise Pascal and his famous triangle also predicted the number of possible sequences of outcomes for the problem of points.
In 1662, John Gaunt published a small book called Natural and Political Observations made upon Bills of Mortaility. It contained a compilation of births and deaths in London raging from 1604 to 1661. Probability had started to be applied to the analysis of raw data.
A coffee house opened by Edward Lloyd in 1687 became a favorite haunt of men form the ships that moored at London Docks. Anyone seeking insurance for a new trade endeavor could go to a broker in the corner of the coffee shop. The coffee shop served from the start as the headquarters for marine underwriters. By the 1770s an insurance industry had also emerged in the American colonies.
Abraham de Moivre demonstrated how a set of random drawings of population data would distribute themselves around their average value. De Moivre’s distribution is today known as the normal or bell curve. The normal distribution forms the core of most systems of risk management (and of much of quantitative market research). It is what the insurance business is all about as life expectancies distribute themselves around a mean.
Moreover, Francis Galton, one of Charles Darwin’s cousins showed that every group no matter how small and no matter how distinct from some other group, tends to array itself in accordance with the normal distribution. Using sweet peas Galton demonstrated what he termed reversion to the mean. Gifted parents are often to be disappointed that their children do not inherit all their powers, more positively neither will they inherit all their weaknesses and diseases.
Regression to the mean motivates almost every variety of risk taking; “what goes up must come down”. History tells of us many legendary investors who made fortunes by betting on regression to the mean, by buying low and selling high. The track records of professional investment managers are also subject to regression to the mean. The hot manager of today is often the cold manager of tomorrow.
But as any stock picker will tell you, regression to the mean can be a frustrating guide to decision making. It sometimes proceeds at a slow pace, that a shock can disrupt the process. Often things fluctuate widely about the mean, and the mean itself can change, yesterdays normality maybe supplanted today by a new normality we know nothing about.
As is clear from recent events in global markets, despite advances in probability we often just don’t have all the information to hand to apply the laws of probability. We never can be sure how good our sample is and whether we have all the pieces of information.
Nobel Laureate Kenneth Arrow was convinced that most people overestimate the amount of information they have available to them. The failure of economists to comprehend the causes of the Great Depression at the time demonstrated to him that their knowledge of the economy was very limited. His experience as an Air Force weather forecaster during the Second World War prompted him to add; “To me the knowledge of the way things work, in a society or in nature, come trailing clouds of vagueness. Vast ills have followed a belief in certainty”
At the turn of the last century, the study of probability gave way to tackling the mysteries of uncertainty. The rational optimism of the Victorians was snuffed out in the senseless destruction of human life on the battlefields of World War I. When Einstein showed imperfection lay below the surface of geometry and Freud showed revealed irrationality below the surface of everyday human behavior, both men became celebrities over night. During the Great Depression in the 1930s, John Maynard Keynes noted, ”the whole is not equal to the sum of the parts, comparisons of quantity fail us, small changes produce large effects, and the assumptions of a uniform and homogenous continuum are not satisfied”.
What do you do when a decision leads to a result that was not even contemplated in your set of probabilities? Or when low-probability outcomes seem to occur more frequently that they should? Don’t the patterns of the past always reveal the path to the future?
In 1937, Keynes summed up his view, “The prospect of European war is uncertain the price of copper and the rate of interest twenty years hence or the obsolescence of a new invention…About these matters, there is no scientific basis on which form any calculable probability whatever. We simply do not know!”
In 1952 a paper appeared in the Journal of Finance which became the backbone of much modern wealth management. Harry Markowitz had turned our attention on “portfolio selection”, or the management of the total wealth. His main theme was that a portfolio of securities is entirely different from holdings considered individually. Markowitz rejected the notion of betting the house on the best bet. Diversification seemed a sensible strategy for selecting a portfolio which best suits an investors taste for aggressive or defensive objectives.
But the truth remained as to how sensible or rational human beings are anyway? The classical models of rationality are based on decisions which people should take in the face of risk.
Psychologists Daniel Kahneman and Amos Tversky showed the comings of classical models. Emotion often destroys self control. People don’t always fully understand what they are dealing with. Losses always loom larger in our mind than gains. Moreover more information can make us less informed in making decisions. Psychology was showing repeated patterns of irrationality, inconsistency and incompetence in the ways in which human beings arrive at decisions. Studies have shown that most of this is indeed played out in the behavior of investors.
The human brain cannot follow a stylized trade off of risk and return. Our emotions push us to resort to tricks and dodges. Most investors simply spread their eggs across several baskets to ensure they pick up winnings somewhere. Past performance is often a frail guide to the future. Even the most successful investors have long periods of underperformance. Winning strategies also tend to have a brief half life. Capital markets as active and liquid as ours are so intensely competitive that results from testing ideas on past data are difficult to replicate or sustain in future.
Discontinuities, irregularities and volatilities seem to be proliferating rather than diminishing. New financial instruments and new markets are turning up at a bewildering pace. Global interdependence makes risk management increasingly complex.
Wars, depressions, stock-market booms and crashes, ethnic massacres come and go, but they always seem to arrive as surprises. Surprise is endemic to the world of finance. The science of risk management creates new risks even as it brings old risks under control. Our faith in risk management encourages us even encourages us to take risks we would not otherwise take. The uncertainty that Keynes sniffed was a consequence of the irrationalities that Kahneman started to map out.
Nothing is more soothing than the computer screen, with its imposing arrays of numbers, glowing colours, and elegant graphs. As we stare at the show, we tend to forget that the computer only answers questions, it does not ask them. Those who live only by the numbers may find that the computer has simply replaced the druids of the past.
At the same time we must avoid rejecting numbers which often show more accuracy than intuitions and hunch, where we know inconsistency of thinking and myopia also exist. In truth, the quantitative achievements of the past 500 years give us the ability to outperform the Gods of the past.
Against the Gods: The Remarkable Story of Risk by Peter Bernstein (1998)