The Undoing Project

New Orleans author Michael Lewis’ new book “The Undoing Project” is bringing new attention to the scholarship of Daniel Kahneman and Amos Tversky.
 
Researchers at Hebrew University’s psychology department, Kahneman and Tversky’s work focused on human irrationality. They showed that human judgment is biased by irrelevant information that makes us inconsistent intuitive statisticians.
 
 By shedding light on these biases, Kahneman and Tversky hoped to improve human decision-making, particularly in areas where statistics can inform our actions. Their insights are particularly relevant to investors. Indeed, they form the intellectual foundations of Verdad’s approach to investing.
 
In this note, we wanted to explore three of the biases that most commonly afflict investors: representativeness bias, availability heuristic, and loss aversion.
 
The Representativeness Bias
 
Linda is 31 years old, single, outspoken, and very bright. She majored in philosophy. As a student, she was deeply concerned with social issues of discrimination and social justice, and she also participated in anti-nuclear demonstrations.
 
Now, decide if Linda is more likely to be, option A or option B.
 
Option A: Linda is a bank teller.
Option B: Linda is a bank teller and is active in the feminist movement.
 
If you chose option A, congratulations, you’ve avoided an alluring logical fallacy. If, however, you chose option B, fear not, roughly 85% of study participants (mostly university students and doctors) made the same mistake. The fallacy lies in the fact that option B is completely contained in option A.
 
Our minds tend toward option B, however, because Linda is specially designed to demonstrate traits of a stereotypical feminist. Our minds latch on to these tantalizing details and form a narrative about Linda that clouds rational evaluation. Kahneman and Tversky termed the beguiling characteristic, “representativeness.”
 
In investing too, we may be tempted to subconsciously latch onto irrelevant data points that are representative of a model for success or failure we currently have in our minds. The problem is that, often, our convenient or intuitive mental models hinder our ability to clearly evaluate probabilities and result in convenient, but unfounded, predictions.
 
Many investors fall into a similar trap when they evaluate companies, overweighting salient information about new products and market growth while underweighting statistical information contained in the historical financials and valuation.
  
The Availability Heuristic 
 
The “availability heuristic” is a mental shortcut useful for answering a complicated question intuitively. For example, if I were asked, “What’s the probability that the newspaper company, McClatchy, goes out of business in the next year?” my intuitive mind would race through all the news stories about failed analog newspapers and highly weight any examples of failing local newspapers I might have encountered personally.
 
The problem, of course, is that my anecdotal experience and stories about specific failed papers give no pertinent information about newspapers or their current rate of failure. I would be tempted to estimate the chance of failure much higher than it might actually be based on my personal exposure to high-profile failures.
 
Kahneman and Tversky found that humans employ this heuristic to almost every probabilistic evaluation. For the most part, the heuristic is beneficial, allowing people to make unimportant decisions quickly. However, when the stakes are higher, the availability heuristic can be highly damaging.
 
Investors, dedicated to rigorous research are less likely to base a decision wholly on their biased intuition, but their first assessment often drives their research to find a specific outcome. For example, researching why X newspaper is likely to fail rather than seeking to understand the base rate of similar newspaper failures.
 
The availability heuristic drives irrational pessimism, particularly in certain industries whose struggles are highly salient.
 
Loss Aversion       
 
Kahneman and Tversky pioneered the idea of loss aversion through a clever set of gamble-experiments. They discovered that participants would typically only accept a fifty-fifty gamble if the potential gain was roughly twice that of the potential loss.
 
Our extreme loss aversion is due to the marginal utility of gains. Figure one shows the general utility curve. Because each additional dollar in the gains domain offers less utility than the last dollar earned, we perceive a loss of one dollar more painful than the pleasure of gaining one dollar.
 
Figure 1: Pleasure vs. Pain

Source: Thinking Fast & Slow
 
The pain associated with loss often prevents investors from adhering to what might be a winning hypothesis. This is one reason why the risk premium for holding stocks is so high: Investors hate losses so much that they flee volatile asset classes in favor of lower-returning but less volatile strategies.  
 
Conclusion
 
These biases may create systematic opportunities in markets. Investors who use systematic, base-rate driven approaches can bet on stocks that other investors are overly pessimistic about due to availability and representativeness biases. Investors with a long time horizon could beat the market by not responding to volatility in the way most loss averse investors do.
 
True arbitrage opportunities are rare, but flaws in human decision-making are so prevalent that betting on other investors’ misunderstanding probability and being driven by irrational human biases could be a smart bet.
 
The famous American-Canadian Economist and 1950s Harvard Professor, John Kenneth Galbraith, once quipped that given that the future is unforeseeable, “There are two kinds of forecasters: those who don’t know, and those who don’t know they don’t know.”  Verdad seeks to bet against those who don’t know they don’t know.