Biased Risk Decisions
The information is all there. We have just wrapped it in so many technical terms that perhaps we forget what it is referring to.
Behavioral Finance explains exactly how people tend to make decisions without models. They call them Biases and Heuristics.
This link is to one of my absolute favorite pages on the entire internet. LIST OF COGNITIVE BIASES Take a look. See if you can find the ways that you made your last 10 major business decisions there.
Now models are the quants ways to overcome these biases. Quants believe that they can build a model that keeps the user from falling into some of the more emotional cognitive biases, such as the anchoring effect. With a model, for example, anchoring is avoided because the modeler very carefully gives equal weight to many data points instead of more weight to the most recent data point.
But what the quants fail to recognize is that models strengthen some of the biases. For example, models and modelers often fall under the Clustering illusion, finding patterns and attributing statistical distributions to data recording phenomena that has just finished one phase and is about to move on to another.
Models promote the hindsight bias. No matter how surprising an event is at the time, within a few years, the data recording the impact of the event is incorporated into the data sets and the modelers henceforth give the impression that the model is now calibrated to consider just such an event.
And in the end, the model is often no more than a complicated version of the biases of the modeler, an example of the Confirmation Bias where the modeler has constructed a model that confirms their going in world view, rather than representing the actual world.
So that is the trade-off, between biased decisions with a model and biased decisions without a model. What is a non-modeling manager to do?
I would suggest that they should go to that wikipedia page on biases and learn about their own biases and also sit down with that list with their modeler and get the modeler to reveal their biases as well.
Fortunately or unfortunately, things in most financial firms are very complicated. It is almost impossible to get it right balancing all of the moving parts that make up the entirety of most firms without the help of a model. But if the decision maker understands their own biases as well as the biases of the model, perhaps they can avoid more of them.
Finally, Jos Berkemeijer asks what must a modeler know if they are also the decision maker. I would suggest that such a person needs desperately to understand their own biases. They can get a little insight into this from traditional peer review. But I would suggest even more than that they need to review the wiki list of biases with their peer reviewer and hope that the peer reviewer feels secure enough to be honest with them.
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