How we judge · 1

Overconfidence: trading as if we knew more than we do

Most people rate themselves above average at most things, and investing is no exception. The cost shows up in how often people trade. Brad Barber and Terrance Odean followed 66,465 households at an American discount broker from 1991 to 1996: the fifth that traded most earned 11.4% a year, against 16.4% for the average household and 17.9% for the market over the same years. A later study of more than 35,000 households found men traded 45% more than women, and paid for it in lower returns.

With shares: a confident story about where a price goes next, acted on often; switching between holdings that are hard to tell apart; treating a run of good results as proof of skill.

Barber & Odean, “Trading Is Hazardous to Your Wealth”, Journal of Finance (2000); “Boys Will Be Boys: Gender, Overconfidence, and Common Stock Investment”, Quarterly Journal of Economics (2001).

How we judge · 2

Confirmation bias: reading only the case for what we already think

Once we hold a view, we look for evidence that agrees with it, read agreeable evidence less critically, and remember it better. Owning a share makes this stronger: every bullish article about it feels like information, every bearish one like noise.

With shares: following only people who share your view of a company; reading the good lines of a results announcement and skimming the rest; explaining away each piece of bad news on its own until there are many of them.

Our summary of a large literature; James Montier gives the investing case in The Little Book of Behavioral Investing (2010).

How we judge · 3

Anchoring: the number we saw first

In a famous experiment, people spun a wheel that stopped at a number, then estimated the share of African countries in the United Nations: those who saw a high number guessed higher. Amos Tversky and Daniel Kahneman called it adjustment from an anchor — we start from whatever number is in front of us and don’t move far enough from it.

With shares: the price you paid; last year’s high (“it was $40, so $25 is a bargain”); a target someone once mentioned. None of these numbers says anything about what the business is worth now.

Tversky & Kahneman, “Judgment under Uncertainty: Heuristics and Biases”, Science (1974).

How we judge · 4

Availability and recency: what comes to mind easily feels likely

We judge how likely something is by how easily examples come to mind. A dramatic, recent event comes to mind very easily. That is why people insure against floods just after one, and why a market fall that has filled the news for a month feels like the normal state of things.

With shares: expecting last year to repeat; selling after a frightening headline; avoiding a sector because of one memorable collapse.

Tversky & Kahneman (1974), as above; Kahneman, Thinking, Fast and Slow (2011), part 2.

How we judge · 5

Representativeness: a good company must be a good investment

We judge things by how much they resemble a familiar type. A company with a famous brand, rising sales and an admired chief executive looks like a good investment. But a good company and a good investment are different questions: the second depends on the price paid, and the price may already assume everything good about the company.

With shares: buying the company you admire without looking at what it costs; assuming a fast grower keeps growing; treating a few good quarters as the pattern.

Tversky & Kahneman (1974); Shefrin, Beyond Greed and Fear (2000), on “good companies” and “good stocks” (our summary).

How we judge · 6

Hindsight: “I knew it all along”

Once we know how something turned out, we remember having expected it, and we judge it to have been more predictable than it was. Baruch Fischhoff showed this in 1975 by asking people to estimate the chances of outcomes before and after being told which one happened. (Later attempts to repeat his exact study have had mixed results; the wider effect is well documented.)

With shares: after a fall, “it was obvious”; after a rise, regret at not having bought, as if the rise had been knowable. Both lead to the next decision being made to fix the last one.

Fischhoff, “Hindsight ≠ foresight: The effect of outcome knowledge on judgment under uncertainty”, Journal of Experimental Psychology: Human Perception and Performance (1975).

How we feel · 7

Loss aversion: a loss hurts about twice as much

In Daniel Kahneman and Amos Tversky’s prospect theory, people judge outcomes as gains or losses from a reference point, and losses weigh more — in their experiments, roughly twice as much as a gain of the same size. Most people turn down a coin toss that wins $150 or loses $100, though the odds favour it.

“System 1 operates automatically and quickly, with little or no effort and no sense of voluntary control.”

With shares: the reference point is usually the price you paid, so a share below cost feels like a wound to be healed rather than a holding to be judged afresh.

Kahneman & Tversky, “Prospect Theory: An Analysis of Decision under Risk”, Econometrica (1979); Kahneman (2011), part 4 (our summary).

How we feel · 8

The disposition effect: selling winners, keeping losers

Hersh Shefrin and Meir Statman named it in 1985: investors sell shares that have risen too early and hold shares that have fallen too long. Terrance Odean then checked it in the trading records of about 10,000 accounts at an American discount broker and found a strong preference for selling winners rather than losers — one that rebalancing did not explain, and that lowered returns after tax. The shares people sold went on, on average, to do better than the ones they kept.

With shares: “taking profits” on the holding that is working; “waiting to get back to even” on the one that isn’t. In many countries this also means paying tax on gains sooner and claiming losses later than you could.

Shefrin & Statman, “The Disposition to Sell Winners Too Early and Ride Losers Too Long”, Journal of Finance (1985); Odean, “Are Investors Reluctant to Realize Their Losses?”, Journal of Finance (1998).

How we feel · 9

Myopic loss aversion: looking too often

Shlomo Benartzi and Richard Thaler put loss aversion together with how often people check. Over a day, a share portfolio falls almost as often as it rises; over ten years, much less often. Someone who looks every day sees many small losses, each felt twice as strongly as a gain — and so finds shares more frightening than their long-run record warrants. Their model needed only loss aversion and checking about once a year to explain why shares have historically paid so much more than bonds.

With shares: a price app on the phone’s home screen; checking during a fall; feeling a portfolio is going badly in a year it ends higher.

Benartzi & Thaler, “Myopic Loss Aversion and the Equity Premium Puzzle”, Quarterly Journal of Economics (1995).

How we feel · 10

Mental accounting: money in separate jars

Richard Thaler showed that people keep money in mental accounts — the holiday fund, the “house money” won at the casino, the dividends — and treat each differently, though a dollar is a dollar wherever it came from. Gains are spent or gambled more freely than wages; a loss in one account is not netted against a gain in another.

With shares: taking bigger risks with “profits” than with the original stake; judging each holding on its own rather than what the whole portfolio is doing; treating dividends as spending money and capital as untouchable.

Thaler, “Mental Accounting and Consumer Choice”, Marketing Science (1985).

How crowds move · 11

Herding: safety in numbers

Charles Mackay’s account of the Dutch tulip craze, the Mississippi Scheme and the South Sea Bubble is still read for its picture of how a whole country can come to believe the same thing at once. Being wrong with everyone else feels less bad than being wrong alone, so following the crowd is comfortable even when it is costly.

“Men, it has been well said, think in herds; it will be seen that they go mad in herds, while they only recover their senses slowly, and one by one.”

With shares: buying what everyone at work is talking about; the most-traded list; feeling foolish for holding something unfashionable.

Mackay, Memoirs of Extraordinary Popular Delusions (1841; retitled 1852). Public domain.

How crowds move · 12

Exuberance: how a bubble feeds itself

Robert Shiller, who shared the 2013 Nobel prize in economics, published Irrational Exuberance in March 2000, at the top of the dot-com boom; the 2005 edition added a warning about housing. His definition of a speculative bubble is a description of a feedback loop:

“I define a speculative bubble as a situation in which news of price increases spurs investor enthusiasm, which spreads by psychological contagion from person to person, and, in the process, amplifies stories that might justify the price increase and brings in a larger and larger class of investors, who, despite doubts about the real value of the investment, are drawn to it partly through envy of others’ successes and partly through a gambler’s excitement.”

The book’s title came from a question Alan Greenspan, then chair of the US Federal Reserve, asked in a speech on 5 December 1996: how do we know when “irrational exuberance” has pushed prices too high? Nobody can say exactly when a bubble ends; that is part of what makes one.

With shares: a price rise becoming the reason to buy; new stories appearing to explain why the old ways of valuing don’t apply this time.

Shiller, Irrational Exuberance (2000; 3rd ed. 2015); Greenspan, “The Challenge of Central Banking in a Democratic Society”, 5 December 1996; Akerlof & Shiller, Animal Spirits (2009).

How crowds move · 13

Familiarity: the comfort of what we know

Investors in almost every country hold far more of their own country’s shares than its share of the world market would suggest, and often too much of their employer’s. Familiar feels safe. Sometimes it is — Peter Lynch built a method on investing in what you know — but familiarity is not diversification.

With shares: a portfolio of banks and miners because they are the names you grew up with; a large holding in the company you work for, on top of your salary depending on it.

Our summary of the “home bias” literature; Statman, What Investors Really Want (2011), on the comfort of the familiar.

How luck fools us · 14

Mistaking luck for skill

Nassim Nicholas Taleb’s Fooled by Randomness (2001) is about how often success in markets is luck that looks like skill, and how the survivors write the history. If enough people flip coins, some will flip ten heads in a row and be asked for their method. Funds and investors that did badly disappear from the record; those left look as if the whole field did well.

With shares: following someone because of their last three good calls; a share bought on a tip that rose, taken as proof the tip was good; any record that only counts the survivors.

Taleb, Fooled by Randomness (2001; 2nd ed. 2004) — our summary.

How luck fools us · 15

Judging the decision by how it turned out

Annie Duke, a former professional poker player, calls it “resulting”: treating the outcome as the measure of the decision. A good decision can turn out badly and a bad one well; over a few hands, luck decides. The only fair test of a decision is the information and reasoning available when it was made.

With shares: abandoning a sound approach after one bad year; repeating a reckless one after it happened to work.

Duke, Thinking in Bets (2018), chapter 1 — our summary.

How luck fools us · 16

Trusting forecasts nobody keeps score of

Philip Tetlock spent two decades collecting predictions from experts and checking them. Most did little better than chance; confident, famous forecasters often did worse. A small group — he calls them superforecasters — did consistently better, and what set them apart was habit: breaking questions into parts, updating in small steps, and keeping score.

With shares: price targets, market calls for next year, and confident predictions in the news — almost none of which are ever checked against what happened.

Tetlock & Gardner, Superforecasting (2015) — our summary.