Naturalistic decision-making

The first graph is from work on decision-making. The second graph is from a US Forest Service decision-making tool presentation. Both look at how decisions can be characterized.

I am a strong believer in systematic trading. It eliminates or certainly reduces behavioral biases and it provides a consistent framework for repeatable success. It takes the stress out of money management and allows for focus on consistent relationships in prices and fundamentals. However, there also has to be an awareness that all decisions cannot follow a disciplined script. The framework can be structured, but we have to accept that non-repeatable events may need another framework. We work under different time constraints and information rules and we have to accept that this means different decisison tools or approaches have to be employed.

The first graphic looks at the issue of decision-making under time stress. All investors are faced with this type of stress in moving markets. When time stress is high, we will revert to simple pattern matching. As time stress decreases we can focus on a more detailed approach. A systematic approach is a way of dealing with time stress and information overload problem. It leaves time for those problems that need more time and thought.

The second graphic table shows another way that problems can be addressed based on its level of stress and information requirements. A simple level 1 problem is just a matching problem. Every time we see same types of events we just react. We have a lot of experience with these types of problems. The second level is where there needs to be some diagnostic work to assess the type of problem and a form of categorization. The third level requires evaluation and modification which is the most difficult. 

If markets are fast paced, it is hard to have the time to conduct all of the analysis. There needs to be a way to sort problems into different levels and a way to act accordingly. We cannot evaluate all problems in the same way. A simple catogorization can help with that prcoess.