Editor’s note: This is a very good one – it is long – make sure to bookmark it!
Are you trying too hard? The case for systematic decision-making1 2
- By Wesley R. Gray, PhD., Author, Quantitative Value: A Practitioner’s Guide to Automating Intelligent Investment and Eliminating Behavioral Errors
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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 would develop a rich body of academic literature to analyze 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 recognize our frequent irrational urges, we often seek the judgment of experts, to avoid becoming 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, for more than 60 years, the assumption that experts make unbias decisions. 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].”
Section 1: Introduction
“If you do fundamental trading, one morning you feel like a genius, the next day you feel like an idiot…by 1998 I decided we would go 100% models…we slavishly follow the model. You do whatever it [the model] says no matter how smart or dumb you think it is. And that turned out to be a wonderful business.”
–Jim Simons, Founder, Renaissance Technologies3
I should probably admit something up front: I once believed I was going be the next Warren Buffett. As a child, I raised animals and sold them at the county fair to make money. And with my growing savings came decisions—what to do with the money? To jumpstart my learning, my Grandmother gave me a copy of Benjamin Graham’s The Intelligent Investor, which describes the philosophy of value-investing. I was 12 at the time and instead of being overwhelmingly appreciative, I was secretly depressed I didn’t get a Nintendo. Nonetheless, I read the book and loved it. I was hooked on value-investing. Over the next 10 years I devoured books on value investing and eventually put my hard-earned “skills” to work, investing in value stocks and special situations.
Part of my investing education included matriculating in the finance PhD program at the University of Chicago. The first two years of the program were similar to drinking from a high-powered fire hose, which spewed sometimes unintelligible information and math equations from the leading scholars in finance. It was not always the most enjoyable experience. However, I persevered and met Professor Nick Barberis4 , who was researching the intersection between financial economics and psychology, a growing field that has since come to be known as “Behavioral Finance.” I took Professor Barberis’ PhD seminar and read over 100 academic papers on behavioral finance. Although I wasn’t sure how I could apply my new knowledge, I recognized that psychology was a powerful force in understanding financial economics.
Simultaneous with my exposure to behavioral finance, I was managing a small amount of money I had raised from my family and friends. I soon realized that the “irrational, emotionally involved, overconfident traders” Professor Barberis was referring to in his course weren’t just theoretical investors dreamed up in the ivory tower—this crazy investor was me! I realized that no matter how many times I foolishly told myself that I was as smart as Warren Buffett, I would never actually be Buffett. I would always succumb to my innate cognitive biases. I guess sometimes it takes getting a PhD to realize you really don’t know it all.
I also understood that I am not the only one capable of illogical thought—we all can succumb to bias. Figure 1 highlights this point5. Stare at box A and box B in the figure. If you are a human being you will identify that box A is darker than box B.
Then ask yourself:
“How much would I bet that A is darker than B?” $5? $20? $100?”
We know how a human approaches this question, but how does a computer think about this question? A computer identifies the red-green-blue (RGB) values for a pixel in box A and the RGB values for a pixel in B. Next the computer tabulates the results: 120-120-120 for box A; 120-120-120 for box B. Finally, the computer compares the RGB values of the pixel in A and the pixel in B, identifies a match, and concludes that box A and box B are the exact same color. The results are clear to the computer.
Now, after taking into consideration the results from the computer algorithm, would you still consider A darker than B? I don’t know about you, but I still think A looks darker than B—call me crazy. (See Figure 2). But then that’s what makes me human.
The sad reality is the computer is correct, and our perception is wrong. Our mind is being fooled by an illusion created by a vision scientist at MIT, Professor Ed Adelson. Dr. Adelson exploits local contrast between neighboring checkers, and the mind’s perception of the pillar casting a shadow. The combination creates a powerful illusion that tricks every human mind. The human mind is, as succinctly stated by Duke psychology professor Dan Ariely, “Predictably irrational.”
That may seem to be a strong statement. Perhaps the illusion above has convinced you that our minds may not be perfect in certain isolated settings. Or perhaps it has only persuaded you to believe that while a subset of the population may be flawed, you still possess a perfectly rational and logical mind. Don’t be too sure, as a well-established body of academic literature in psychology demonstrates conclusively that humans are prone to poor decision making across a broad range of situations.
But are experts beyond the grip of cognitive bias? We often assume that professionals with years of experience and expertise in a particular field are better equipped and incentivized to make unbiased decisions. Unfortunately for experts, the academic evidence is emphatic: systematic decision-making, or models, outperform discretionary decision-making, or experts.
Section 2: Are Experts Worthless?
To be clear: I am not making the claim that human experts are worthless in the decision-making process. Experts are critical, but only for certain aspects of the decision-making process. Students of decision-making break the decision-making process into three components (see