Taking control of risk

By Barb Clapham
Illustration: Cathy Pentland

A look at the history of risk can Help your clients make the right investment decisions

Humans generally lack the ability to accurately measure risk and reward. Behavioural finance studies show that emotions and cognitive errors can affect the decision-making process of even the most rational of investors and result in poor investment decisions. Advisers who understand the basic mathematical underpinnings of risk management and appreciate their clients’ perceptions about risk have an advantage in helping them make the right decisions. Recognizing the dilemma, many companies have developed risk-controlled investment products that may provide your clients with the risk control they seek as well as the potential return they desire.

The theoretical foundations for nearly all the risk management tools we use today were developed during the latter half of the 17th century and the first part of the 18th century.

Theory of probability 1654 – Blaise Pascal and Pierre de Fermat answered a question that had puzzled gamblers for more than 150 years: how should two players divide the stakes in a game of chance if they stop before the game is finished and one player is ahead of the other? Pascal and de Fermat suggested the two players divide the stakes on the basis of the respective probability that each would win the game and showed how to calculate that probability. A major step forward, probability theory allowed people to evaluate risks using a systematic method instead of reverting to tradition and superstition.

Statistical sampling and statistical significance 1662 – John Graunt showed how to draw larger conclusions based on a sample of statistics, a concept known as “statistical inference.” Using fragmentary statistics, Graunt estimated the population of London.

1693 – Edmund Halley (yes, of comet fame) revisited statistical significance and showed how life tables could be used to determine the appropriate cost of life insurance, a breakthrough in the world of risk management (although it would be 100 years before insurance companies took probability-based life expectancies into account).

Utility theory 1738 – Daniel Bernoulli introduced the idea of utility; when someone makes a decision involving risk, he or she considers the value of the outcome as well as calculations of probability. Two centuries later, John Von Neumann and Oskar Morgenstern applied utility theory to business and investing and outlined how we should make decisions when we know only the probabilities of some events.

Normal distribution and standard deviation 1733 – Abraham de Moivre derived the normal distribution: the pattern that a series of variables distribute themselves around an average. From this, he developed the concept of standard deviation: the amount variation in performance that an investment is expected to have from year to year. The higher the standard deviation, the greater the volatility risk of an investment. Two major principles of risk management came later.

Regression to the mean 1885 – Francis Galton, cousin of Charles Darwin, studied the height of individuals and came to the conclusion that in general tall people tend to have tall children (although not as tall as they are), and short people tend to have short children (although not as short as they are). Whenever we make a decision based on the expectation that things will return to normal, we are using regression to the mean. Strategic asset allocation and rebalancing are based on this notion. After stock prices rise sharply, the general expectation is that this trend will reverse.

Diversification 1952 – Harry Markowitz introduced Modern Portfolio Theory in his landmark paper, “Portfolio Selection.” He presented the concept of diversification and demonstrated how, through diversification, risk can be reduced, not eliminated, without changing expected portfolio return. In 1990, he received the Nobel Prize in economics for his work. Mathematical concepts of risk management assume that investors use all available information to make rational decisions. In the real world, investors are also influenced by many behavioural factors.

Behavioural finance
In the early 1940s, Amos Tversky and Daniel Kahneman, pioneers in the field of behavioural finance, investigated apparent contradictions in human behaviour. They discovered that when offered a choice phrased one way, subjects might display risk aversion, but when offered essentially the same choice phrased in a different way, they might display risk-seeking behaviour. Kahneman cites the example of people who will drive across town to save $5 on a $15 calculator, but won’t drive across town to save $5 on a $125 coat. Kahneman and Tversky called their studies of how people manage risk and uncertainty Prospect Theory (for no good reason other than that they liked the sound of the name). Key concepts addressed by the theory include:

• Loss aversion People place different weights on gains and losses; they are more distressed by losses than they are happy by equivalent gains. Individuals also respond differently to the same situation depending on whether it is presented in the context of a loss or a gain. On the whole, people make financial decisions based on the fear of losing rather than the hope of winning.
• Regret aversion Investors act to avoid the pain of regret resulting from a poor investment decision. It is not just financial loss they regret; it is also the feeling of responsibility for the decision that gave rise to the loss. Regret aversion also causes herding behaviour. Investors tend to seek comfort in crowds and invest in the same firms. That way, if the stock price falls, they can eliminate one part of regret aversion — feeling responsible for the poor decision. How can everyone be wrong?

Mental accounting
Human beings compartmentalize their lives into separate mental accounts. As a result, investors tend to treat each element of their investment portfolio separately, a propensity that can lead to inefficient decision-making. For example, an individual may borrow at a high interest rate to buy a car while earning a low interest rate on his or her retirement fund. Mental accounting has implications for portfolio rebalancing as well; investors may be unwilling to sell a losing investment because its account is showing a loss.

• Overconfidence  People tend to be overconfident in their own abilities, including their skill at predicting the markets. Overconfidence also applies to professional analysts, who often are reluctant to revise an opinion on a stock’s prospects, even when confronted with new information.
• Representativeness People tend to make judgments based on common traits or stereotypes; that is, to see patterns where none may exist. With respect to forming expectations, representativeness leads investors to assume that recent events will continue into the future. This is why investors chase hot stocks and shun stocks with poor recent performance.

The future of risk management 
In Irrational Exuberance, published in 2000, Robert Shiller discussed how stock markets were propped up by investor irrationality rather than value and predicted the collapse of the bubble. He continues to study risk management and sees new, innovative ways of managing risk in the investment world and in our changing society. In The New Financial Order: Risk in the 21st Century, Shiller describes techniques to manage risk as livelihood insurance and home equity insurance.

The field of risk management keeps evolving, but risk is a moving target that can never be completely mastered. Peter L. Bernstein, author of Against the Gods: The Remarkable Story of Risk, says, “Few people feel the same way about risk every day of their lives. As we grow older, wiser, richer or poorer, our perception of what risk is and our aversion to taking risk will shift, sometimes in one direction, sometimes in the other. Investors as a group also alter their views about risk, causing significant changes in how they value the future streams of earnings that they expect stocks and long-term bonds to provide.”