Keep decisions simple when there is uncertainty - The case of coronavirus

"So, in general, if you are in an uncertain world, make it simple. If you are in a world that’s highly predictable, make it complex."

- Gerd Gigerenzer "Instinct Can Beat Analytical Thinking"

The challenge for decision-making and model building is determining whether you are in an uncertain world or a predictable work. Or, as Robin Hogarth has referred to as "kind" or "wicked" learning environments. (See "Kind" versus "Wicked" learning environment - Financial markets are not kind) In a wicked model, the link between between the past and future is unclear or uncertain. It is hard to learn and model in this situation. Your modeling and decision response should be based on the environment you face.

I have investing years trying to think through the problem of using heuristics versus analytics and avoiding behavioral biases and focusing on quantitative rationality. Someone who has not grappled with this issue has avoided the crux of making good decisions under uncertainty. There is a form of comfort with being a model builder. You can avoid the challenges of uncertainty by attempting to increase complexity. There is also comfort with having heuristics because they are fast and simple to implement. Moving between these two extremes may separate the average from the very good investor.

I bring this issue to the forefront because the current focus on the coronavirus is a real world case of dealing with high uncertainty. No one could spell or even cared about this issue a few weeks ago, but now it is driving the financial markets. Someone can derive models for infection rates and shocks to different economies from a potential pandemic. This is rational and makes sense, but this may be a better time for using good heuristics like "one good reason decision-making". 

The one good reason heuristic is simple. There is an unknown risk that can have a large financial impact and is causing prices to fall now; therefore, sell risk exposure and get to the sidelines. There is no big complex model, the trend is down, get out. The risks are not easily measurable and growing, get out. This is a good reason and don't wait for a deeper model answer. As new information is added, the decision can change, but the quick answer may be the best when the inputs for modeling are unclear.