Trying Too Hard: The Case for Systematic Decision Making

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Information about Trying Too Hard: The Case for Systematic Decision Making
Finance

Published on March 2, 2014

Author: empiritrage

Source: slideshare.net

Description

Everyone makes mistakes. It’s part of what makes us human. Because humans understand their actions are sometimes flawed, it was perhaps inevitable that the field of psychology developed a rich body of academic literature to describe why it is that human beings often make poor decisions. Although insights from academia can be highly theoretical, our everyday life experiences corroborate many of these findings at a basic level: “I know I shouldn’t eat the McDonalds BigMac, but it tastes so good.” Because we are aware of our frequent irrational urges, we often seek the judgment of experts, so we can avoid being our own worst enemy. We assume that experts, with years of experience in their particular fields, are better equipped and incentivized to make unbiased decisions. But is this assumption valid? A surprisingly robust, but neglected branch of academic literature, has studied the assumption that experts make unbias decisions for over 60 years. The evidence tells a decidedly one-sided story: systematic decision-making, through the use of simple quantitative models with limited inputs, outperforms discretionary decisions made by experts. This essay summarizes research related to the “models versus experts” debate and highlights its application in the context of investment decision-making. Based on the evidence, investors should de-emphasize their reliance on discretionary experts, and should instead approach investment decisions with systematic models. To quote Paul Meehl, an eminent scholar in the field, “There is no controversy in social science that shows such a large body of qualitatively diverse studies coming out so uniformly in the same direction as this one [models outperform experts].”

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