We try to avoid risk and often miscast uncertainty for risk. While they're both a fact of life, it's valuable to understand the difference between the two. Uncertainty and risk are related concepts in economics and the stock market.
The concepts are related, but not the same. You cannot avoid risk, every act of creation involves it. Even not doing anything has a risk component. But you can learn to move away from uncertainty, especially when you're called to make important decisions.
Dynamic nature of risk
Since risk is defined as unknowns that have measurable probabilities, we can insure against it. But not all risks are insurable. Because uncertainty involves unknowns with no measurable probability of outcome.
Risk has odds, while uncertainty doesn't. Causation is the dimension of risk we need to factor in our thinking, along with the behavioral pattern or risk frequency and severity. How often and how bad is it?
In risk management we have a simple framework we use to evaluate risk along three dimensions of risk classification:
1. Financial and non-financial — can we measure it in monetary terms?
2. Pure and speculative — is the outcome always a loss, or could there be a gain?
3. Fundamental and particular — what is the relationship of cause and effect? Who causes it?
Within this classification, however, things change all the time. Because risk is not static, it's dynamic by nature. Frequency and magnitude factor in the calculations. Where you are and the environment around you make a difference.
Data on risk frequency and severity helps insurance companies figure out predictability of future events. It also helps the individual figure out the cost to insure. Severity or the answer to, “could this be catastrophic?” drives whether to insure or not.
What happens when we confuse risk and uncertainty
In The Signal and the Noise: Why so Many Predictions Fail – but Some Don't, Nate Silver summarizes the difference between risk and uncertainty:
Risk, as first articulated by the economist Frank H. Knight in 1921, is something that you can put a price on. Say that you'll win a poker hand unless your opponent draws to an inside straight: the changes of that happening are exactly 1 in 11. This is risk. It is not pleasant when you take a 'bad beat' in poker, but at least you know the odds of it and can account for it ahead of time. In the long run, you'll make a profit from your opponents making desperate draws with insufficient odds.
Uncertainty, on the other hand, is risk that is hard to measure. You might have some vague awareness of the demons lurking out there. You might even be acutely concerned about them. But you have no real idea how many of them there are or when they might strike. Your back-of-the-envelope estimate might be off by a factor of 100 or by a factor of 1,000; there is no good way to know. This is uncertainty.
Risk greases the wheels of a free-market economy; uncertainty grinds them to a halt.
The context Silver used for his comparison is the alchemy the rating agencies performed leading up to the financial crisis of 2008. They spun uncertainty into what looked and felt like risk. We lived the consequences of those decisions.
When risks become hazards
In thinking about risk as dynamic, we look at probabilities. Frequency and severity are typically inversely proportional. Some things happen frequently but are not severe, some are severe but happen seldom.
However, there is a type of risk that happens frequently with enough severity to warrant noticing. There are conditions or situations that are likely to increases the chances of a loss from a peril we've identified. We call this a hazard.
Physical and moral hazards influence the likelihood or a poor outcome from risk. Hazards are like fuel — they can accelerate the gravity of a situation. Since we can identify physical hazards, we can insure against their variables.
But what happens when we're talking about moral hazard? Character, integrity and mental attitude are not easy to measure. Behaviors can be unintentional or not consciously bad and still remain hazardous.
There are rules and regulations that govern insurance to risk. But we've seen what happens when we overreach and accumulate too much risk. A collapse of confidence followed the last financial crisis that was catastrophic for many.
Why complexity requires new thinking
To improve the quality of our decisions, we need also to understand the dynamics that surround risk and uncertainty.
Our attempts to predict the future are too reliant on linear thinking based on past experience#. In a complex world, past data may not be as useful to forecast risk, things change fast. We're also limited in our ability to handle probabilities.
Retired economist and Singaporean government official Lam Chuan Leong# says we can classify the way we think and manage events in a two-by-two matrix by combining the findings from Behavioral Economics and Complex Systems.
Time and complexity are the vectors. When we're called to make decisions but have little time, we behave differently than when we have more time. In our daily activities, we decide using our intuitive system, automatically and quickly.
Give us more time, and we can reflect on decisions. We use reasoning and analysis. In economics terms, this is the Rational Man Model of thinking. But this may not be enough. Cause and effect are not as consistent in complexity.
Lam Chuan Leong outlines the four modes of thinking that apply to many of our decisions in business and are influenced by time and complexity:
“We have to make sense of the problem by probing, experimenting, creating environments conducive to the generation of new ideas and new interactions, and responding to emerging patterns and behaviors,” he says.
This in turn has changed how we manage in a complex world.
Challenges require critical thinking
As we're increasingly called to probe, sense and respond, we need to create an environment and experiments where innovative patterns can emerge. The increased levels of interaction and communication should be designed to generate ideas and options.
Leaders are setting boundaries, barrier and incentives to encourage patterns to grow into coherence and general acceptance instead of merely executing the plan.
But with managing risk there are also cognitive and behavioral challenges:
Key biases include our desire to rationalize into a story when we want to explain a decision, even though emotion is involved in decision-making, and anchoring — for example, start with a high number, and you're now willing to pay a higher price.
We also have confirmation bias, we see what we want to see, and ignore evidence that contradicts our beliefs. People react to a particular choice in different ways depending on how it is presented — e.g., as a loss or a gain.
While in the past we could rely on analysis and control of risk, we need new ideas and innovation to solve future problems. When we think about issues, we should take into account the environment where we operate and its complexity.
Beyond recognizing our cognitive biases and acknowledging our time constraints, we need to take into account how emotions connect to outcomes in decision-making.