Good investment decisions focus on making good predictions or inferences. Improving these predictions is all about learning from the information available and past investment decisions. Unfortunately, learning is hard because the environment for making decisions is often complex. Most investors think it is hard because there has to be “sweat equity” to improve. That is false or at least only a part of the story. Learning issues and the path for improved decisions are associated with the type of environment faced.
Learning is easy if there is a close well-defined link between action and results. There is a close link if the setting for gathering information is the same as the one faced when the decision is made. This learning problem is placed in a useful framework by one of the most eminent professors in decision science, Robin Hogarth, along with some of his collogues in the paper, “The Two Settings of Kind and Wicked Learning Environments”. (See Current Directions in PsychologicalScience vol 24 (5) 2015 pp.379-385.)
The paper breakdowns decisions into two settings, the learning or acquired information setting, and the applied or predictions setting. These two setting define the learning environment. The learning environment can be described as either being kind or wicked. If the learning environment is kind, then the information in the acquisition setting will be similar to information in the prediction setting. There can be accurate inferences because in simple terms, “what you see is what you get”. When the acquiring setting does not match the prediction setting, there will be mismatches between what is perceived and what is actually faced. This a wicked learning environment. What you think you know is not the reality faced.
Think of two simple decision environments, a well-defined game versus the investment decision game. A gaming environment with well-defined rules is a kind environment because mistakes can be defined, feedback given, and learning acquired. In the trading and investment game, players change, behaviors change, the economic structures and rules change. Given there is no specific end, it is hard to acquire feedback and effectively learn. The first environment is kind. The second environment is wicked.
In a kind learning environment, hard work will be properly rewarded. A player may not always be rewarded, but there is a close link between, information, decision, action, and feedback. This will not be the case with a wicked environment where in many cases the feedback received could wrong. The sample of information acquired may not be helpful for explaining the action taken. Probability judgments in a kind environment means the favorable odds can be found and exploited. In a wicked environment, it is hard to distinguish between skill and luck.
A kind environment has plentiful and accurate feedback. Positive feedback will be harder to find in wicked environments, so mistakes are more likely. In a kind environment, statistical relationships from the past can be used to make accurate predictions on the future. Test or training sets will match prediction sets. There is a strong positive covariance between the past and the present.
Decisions can be placed within two settings, the learning and the target setting where the decisions are made. The framework can be effectively explained through Venn diagrams. When the learning and target settings closely match, the world is kind. Judgments are easy. When learning and target settings do not match, the environments are wicked, and judgments are harder to make and any improvement in decision-making is harder.
Creating the wrong learning setting through using bad information or forming biased use of information will mean predictions will be poor and there will be errors in judgments. Investors have to recognize the environment they are facing and what they can do to better match learning with predictions. First, realize that a given environment is wicked. Second, protect against bad judgments through focusing on the form of the feedback generated. Third, always work to improve your information setting through gathering more information or eliminating noisy information. Fourth, don’t confuse skill with luck. You are likely not as good as you think.