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Ebook About “Brilliant. . . . Lewis has given us a spectacular account of two great men who faced up to uncertainty and the limits of human reason.” —William Easterly, Wall Street JournalForty years ago, Israeli psychologists Daniel Kahneman and Amos Tversky wrote a series of breathtakingly original papers that invented the field of behavioral economics. One of the greatest partnerships in the history of science, Kahneman and Tversky’s extraordinary friendship incited a revolution in Big Data studies, advanced evidence-based medicine, led to a new approach to government regulation, and made much of Michael Lewis’s own work possible. In The Undoing Project, Lewis shows how their Nobel Prize–winning theory of the mind altered our perception of reality.Book The Undoing Project: A Friendship That Changed Our Minds Review :
I tend to get excited when the best story tellers write a new book, and when the book covers a topic I have been focused on recently this is even more so. Such was the case when Lewis covered the Nobel Prize winning duo of Daniel (Danny) Kahneman and Amos Tversky, two psychologists who developed much of the base work behind behavioral finance. I also see its roots in Robert Cialdini’s books (Influence, Pre-suasion). While Kahneman (Tversky died in 1996 so did not share in the Nobel) wrote Thinking Fast and Slow to share their life work, here Lewis tries to identify why they worked so well together. In fact I don’t recall him talking about thinking fast (immediate response) or slow (long-term investor) at all. It reads somewhere between biography and non-fiction about behavioral finance.Some of the more interesting thoughts in the book have nothing to do with behavioral finance, but have lots to do with psychology. Lewis discusses Daryl Morey, who I would call a basketball sabermatrician. He has been GM for the Houston Rockets since 2007 using tactics similar to those described for baseball in the book Moneyball (also by Lewis). In this same chapter Lewis provides a definition of a nerd – a person who knows his own mind well enough to mistrust it. This sounds like something Charlie Munger would say (high praise).Both Kahneman and Tversky lived in Israel, where everyone serves a stint in the military, and both saw action in the Six Day War in 1967 and the Yom Kippur War in 1973 (when they returned from America to take up arms). Kahneman helped the Israelis design better tools for selecting officers and training pilots. Tversky was a paratrooper. Both were professors at Hebrew University at the beginning of the first war.Our mind tricks us. After the fact, we know exactly why we saw the event coming that no one anticipated (see Taleb’s Black Swan) and surveys weigh more heavily toward events that have recently occurred. The reasons often given relate back to our days as prey on the plains of Africa (thinking fast keeps you alive in that context – you run away from a predator, as fast as you can). One of the ways to catch these inconsistencies is to devise three options, where a person chooses A over B, B over C, and C over A. This violates the law of transitivity, familiar to anyone who has ever studied algebra or logic. Lewis provides many of these examples, as did Kahneman in Thinking Fast and Slow, and I fall for nearly every one. Even after I’ve seen them before (sometimes, occasionally, I remember).K/T developed several heuristics, where laws of chance are replaced by rules of thumb. “We often decide that an outcome is extremely unlikely, or impossible, because we are unable to imagine any chain of events that could cause it to occur. The defect, often, is in our imagination.”• Representativeness – we see a previously developed mental model rather than thinking through the facts as presented (and are generally correct). This creates systematic errors, such as looking at a kid and immediately deciding whether they are athletic. Looking at the negative can help avoid these problems. For example, the WW2 bombs landing in London appeared to target certain areas, but really were random. If you have 23 randomly selected people in a room, the odds are better than half that at least two share a birthday.• Availability – we more easily recall memorable events.• Conditionality – we make contingent assumptions when none are stated. We assume normal operating conditions (e.g., normal distribution, VaR). “…people don’t know what they don’t know, but that they don’t bother to factor their ignorance into their judgments.”• Anchoring (and adjustment) – if you are shown a large (or small) number, for example, then your response is then large (or small).• Simulation – what could happen dominates what is likely to happen – this can lead to analysis paralysis (I find it difficult to overcome this when investing for my personal accounts – it’s hard to pull the trigger).• Recency bias – recent events influence our probability assumptions.• Hindsight bias - once we know how something turns out, our recollection is that we predicted it in advance (similar to Black Swans – Taleb)How do ideas form in our mind? Is it conscious, or indirect? When we study in school, or for a credential, the focus is on repeating the “right” answer. While hard to grade, I’ve always thought it would be better to provide an answer and ask the student to improve it.Who knew that a bad experience could be remembered more fondly if the final part of the event was not so distasteful – the peak-end rule? This was tested using colonoscopies that ended with the medical instruments brought out of the body slowly or quickly. Doing so slowly made it more likely that the person would return for future tests.The risk manager will discover, usually the hard way, that avoiding a risk receives no reward but if you miss a risk then you will get the blame. This is a human bias.Accounting does not consider the impact on the environment, to limited supply, or to emotions. Utility theory overstates the value. Risk aversion is a fee willingly paid to avoid regret. In any case we all prefer to avoid pain more than we want to secure gain. We react more to relative changes than absolute ones, and probability is not straightforward.The benefits of a group often conflict with the benefit to an individual. Antibiotics are such an example. In total, limiting antibiotics is better because viruses have less chance to mutate successfully. For an individual, antibiotics are either useful or neutral. There is no downside to an individual to being treated with antibiotics.One of the fascinating revelations in the book (for me, at least) was the need to invert. “How do you understand memory? You don’t study memory. You study forgetting.” As we study other topics we should look for opportunities to utilize this strategy.While much of the interest in this branch of psychology is applied to investment strategies, K/T worried more about geopolitical biases and the series of avoidable mistakes that could be made by political leaders relying on gut feel. They thought that intelligence reports written as essays should be replaced by probabilities. Telling a story is not helpful in this context, but politicians tend to be afraid of numbers. We have seen evidence of this recently as briefings to the US president are said to be focused on charts and short sound bites.As you read about financial economics, this should not be your first book. I believe it is more useful to someone already familiar with the concepts from other sources. For someone starting out on this topic I personally like Why Smart People Make Big Money Mistakes and How to Correct Them by Gary Belsky and Thomas Gilovich to start and then Thinking Fast and Slow by Kahneman before reading the Lewis book. This is one of Michael Lewis’s best books yet. The challenge is to tell the story in a way that describes the behavioral biases without the need for technical discussion. Lewis accomplished this fairly well.Early in the book he covers the challenge of scouting players in professional sports leagues. He notes the popularity of the halo effect, where scouts see favorable single attributes and let that impression impact the assessment of other attributes. This is later more broadly categorized as representativeness, one of several heuristics individuals use to make decisions with limited information. Representativeness involves the premature characterization and categorization of an object/event/individual based on some attribute that can be easily identified. Other heuristics mentioned include anchoring, when one takes new information and simply makes adjustments to their initial judgement; availability, when one assigns too much weight to the information readily available to them; and simulation, an emotional bias involving the ease with which one can mentally simulate alternatives to reality. While it is acknowledged that heuristics are often times helpful rules of thumb, they can occasionally lead to systematic error.Representativeness is explained using the ‘Linda problem’, which asks whether it is more likely that Linda is a bank teller or a bank teller and a member of a feminist organization, when all you’re told is that Linda is a feminist. Many respondents chose the latter option, even though the first option contains the second option via a less restrictive description. In other words, if the probability of Linda being a bank teller is 10%, and the probability of her being in a feminist organization is 99%, then the first option has a 10% chance of being correct, while the second has a (10% x 99%) chance of being correct (which is less than 10%). Availability bias is similarly explained using a problem that asks whether a particular book has more words with the form _ _ _ _ ing or _ _ _ _ _ n _. Since words ending in ‘ing’ are easily thought of, respondents chose the first option, ignoring the fact that the second option includes all words that also meet the first option. Availability is explored further, as Lewis explains how Kahneman and Tversky attack practitioners for over-extrapolating from small sample sizes.Consumer decision biases are touched on as well. First, it is explained how individuals do not appear to update probabilistic outcomes using a Bayesian process in real world decision-making. Experimentation has also uncovered the fact that human consumption decisions do not follow laws of transitivity. In other words, if a consumer prefers A to B and B to C, they may sometimes also say they prefer C to A. They ultimately explain this by breaking A, B, and C down into individual features, and analogize a person purchasing A to them really purchasing a bundle of features represented by A. In so doing, they realized that not only are small preferential differences in particular features virtually ignored, but exact comparison is often not possible since different objects have different bundles of features. Additionally, they found that individuals exhibit an endowment bias in exchange transactions, assigning more value to items that they already own simply because they already own it.Perhaps the greatest achievement of Kahneman and Tversky was challenging and offering an alternative to Bernoulli’s utility theory. Utility theory effectively explained certain behavior by labeling individuals as either risk tolerant, risk neutral, or risk averse. If faced with choosing between $50 for free or taking a 50% chance of winning $100 or $0, a risk neutral individual would be indifferent to the decision. A risk averse individual would take the free $50 and avoid the odds, since the utility they get from the first $50 is higher than that of the second $50. Thus individuals do not rely on pure probabilistic payoff odds. However, utility theory has not held up under centuries of scrutiny. Kahneman and Tversky added to this topic with the concept of regret aversion, where individuals place undue weight on potential negative outcomes, and then again with loss aversion, where individuals will actually be willing to take more risk (as a risk tolerant individual would in Bernoulli’s framework) when faced with the same decision as above but with losses instead of gains. In other words, if choosing between an assured $50 loss or taking a 50% chance of losing $100 or $0, an individual who is risk averse on the gains side may choose to be risk tolerant on the loss side.The above discoveries are detailed along-side an interesting story about Kahneman and Tversky’s long personal and professional history together. Overall, very enjoyable. 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