In his latest book – Noise: A Flaw in Human Judgment, Daniel Kahneman provides a simple method that will help investors make significantly better ‘noise-free’ decisions. Here’s an excerpt from the book:
There is a limit to the accuracy of our predictions, and this limit is often quite low. Nevertheless, we are generally comfortable with our judgments.
What gives us this satisfying confidence is an internal signal, a self-generated reward for fitting the facts and the judgment into a coherent story. Our subjective confidence in our judgments is not necessarily related to their objective accuracy.
Most people are surprised to hear that the accuracy of their predictive judgments is not only low but also inferior to that of formulas. Even simple linear models built on limited data, or simple rules that can be sketched on the back of an envelope, consistently outperform human judges. The critical advantage of rules and models is that they are noise-free.
As we subjectively experience it, judgment is a subtle and complex process; we have no indication that the subtlety may be mostly noise. It is difficult for us to imagine that mindless adherence to simple rules will often achieve higher accuracy than we can —but this is by now a well-established fact.
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