On the nature of risk: putting ideas into context
As two sides of the same coin, return and risk not only interrelate, but they are in essence the same. We can define return as a profit obtained from assuming a risk. Conversely, we can define risk as the cost assumed when trying to achieve a return. Both definitions are highly explanatory in their simplicity. Having answered why, the next question is how much. How much risk are we prepared to assume to obtain a return? Are we satisfied with the return obtained given the risk we assume?
This is where everything becomes considerably more complicated.
All good economists always keep a pair of rabbits in their hat. We can take one out, and talk about Sharpe and his CAPM (Capital Asset Pricing Model), which estimates the return required from a particular financial asset. We can also talk about the Markowitz efficient frontier, which draws a set of optimum return and risk combinations for a portfolio of financial assets.
We can complicate the models even further and talk about pair trading, arbitrage and relative value. But these definitions, though very useful (and that is why Sharpe and Markowitz won the Nobel Prize for Economics for them), are limited to the reality of the financial markets.
We could talk about the numerous risks that financial institutions or companies assume. Over the last thirty years there have been numerous efforts designed to measure, control, manage and communicate the risks assumed by financial institutions. First, toward the end of the 1980s, with the measurement of market risk; then progressing with Basel II mid-way through the last decade, and continuing with Basel III and the numerous steps taken by the different regulators.
But metrics and management systems do not only exist in the financial word. All branches of activity have to tackle risks. The energy sector, as an intermediary between supply and demand prices, has to match the interests of generators, distributors and retailers. Pharmaceutical companies have to decide whether to commit years to the development of a drug, then wait to see whether it will be authorized and sold; and whether it can generate a return that can compensate both the development costs and the loss of exclusivity after a certain number of years. There are many more examples.
All these risks can be measured. They are managed, controlled and, with a great deal of effort, mitigated as far as possible. We can fall into the trap of thinking that risk is any potential loss that we can measure.
If we want to go beyond the models and understand the very nature of risk, we have to look for an even deeper understanding.
Because risk is something more than the result of a mathematical knowledge. And what about the decisions taken by a family concerning its capacity for indebtedness? How should we measure the risk of choosing the wrong degree course after finishing high school, or of deciding to study one language rather than another? How do we value the risk of making a mistake, or of not achieving the objectives we want? Here we are not talking about uncertainty, at least in the terms expressed by Knight. We are talking about seeing risk from a broader perspective.
Return and risk underlie many everyday decisions. Even the concept of opportunity cost is a manifestation of return/risk. If we want to go further into the profound implications of valuing return and risk we should enrich these definitions and move beyond mere figures.
We have to look at people.
Talking about people means talking about psychology, sociology, neurology. About irrationality and contradictory results. About explanations that do not match the most basic assumptions on which economic science is based.
It is on this marshy ground that one of the most promising branches of economics is being constructed; one that will be indispensible for us if we want to continue to investigate deeper into the nature of risk.
Continue reading here.