It's not easy to behave rationally
Buffett's wager
One day in the early eighties, Warren Buffett joined a few friends for a game of golf. The men did a lot of betting and at one session, Jack Bryne, Chairman of GEICO, an insurance company in which Buffett's investment vehicle Berkshire Hathaway held a significant stake, proposed a novel side bet. For a "premium" of $11, Bryne would agree to pay $10,000 to anyone who hit a hole-in-one over the weekend. Everyone reached for the cash - everyone, except for Buffett, who coolly calculated that, given the odds, $11 was too high a premium. His pals could not believe that he - by then, almost a billionaire- would be so tight and began to make fun of him for it. Buffett, grinning, noted that he measured an $11 wager exactly as he would $11 million. He kept his wallet tightly zipped.
Stockmarkets are Irrational
Contrary to the popular belief of most academics as well as some investment practitioners that investors are ever-rational and that stock prices are as perfect as possible, Warren Buffett and his partner Charlie Munger believe that like the rest of the world, the stock market is a highly irrational place consisting of participants who behave irrationally. Buffett once remarked that the market is a "semi-psychotic creature, given to extremes of elation and despair."
The secret of success in investment, according to Buffett and Munger comes from rational behaviour. In other words, the ability to bet against the crowd, when the crowd is likely to be wrong. When asked what one quality most accounts for his enormous success, Munger replied, "I'm rational. That's the answer. I'm rational."
Rational behaviour requires objectivity which means stripping decisions of emotions, of hopes and fears, of impatience and self-delusion and all purely subjective elements. Few people have this strength. Another word for objectivity is "cold-blooded." Most people are mere humans who get dizzy when a stock they hold goes up and up. They fear losing their paper profits. So they sell and sometimes they are sorry. At the other extreme, they like an investment but shy away because the consensus says they are wrong. They simply don't have the courage to behave in a contrary fashion.
Skylab is falling!
Ralph Wanger, a highly successful contrarian mutual fund manager once remarked: "Why don't people consider risk in proportion to its true statistical probability?" He gave an example.
In 1979 when NASA's satellite Skylab was breaking up, airline flights were cancelled all over U.S. But had skylab fallen and 500 pieces of scrap metal rained down, the odds of one hitting any American would have been 1 in 20,000. Since NASA had some ability to control the landing area, the correct odds were more like 100,000 to one. Since about 130 Americans are killed in car accidents every day, the chances of being killed in a car was several million times greater than by Skylab.
One answer, according to Wanger for people's failure to understand risk correctly may be that people don't like to do mathematical calculations to figure out the real odds. And, of course, the unusual makes a better media story than the commonplace. But, he says, "the Skylab effect" tells us that there are sound companies with a small risk of trouble that are good buys because the market is too fearful of unlikely disasters. When something bad happens, a stock may go down much more than the news warrants. This has its own Wall Street name: "overdiscounting the bad news." So, as he points out, if you can find a good company when the market is reacting to inflated horror stories, there are profits to be made. In other words, it pays to be contrary.
Daniel Kahneman and Amos Tversky
The observations held by Buffett, Munger, Wanger and many other successful contrarian investors have been confirmed by the research findings of two academic psychologists - Amos Tversky, who died recently, and Daniel Kahneman. These two researchers have convincingly proved that the world is, after all, an irrational place. By posing identical questions in different forms, they found that many people give conflicting answers. In fact, even when people we're trying to be coldly logical, they gave radically different answers to the same problem, when it was posed in a slightly different way.
Tversky's work has particular implications for financial markets -- where the faith in rational behaviour is greatest. Destroying the notion of efficient markets and rational expectations, Tversky showed that people tend to avoid risks when the problem is stated in terms of gains but take greater risks if the same problem is framed in terms of losses.
Here are a few problems some of which were framed by Tversky and Kahneman, that will test your logical reasoning abilities. Jot down your answers to the questions before you read the discussion which follows.
General's Dilemma - How Many will live?
Threatened by a superior enemy force, the general faces a dilemma. His intelligence officers say his soldiers will be caught in an ambush in which 600 of them will die unless he leads them to safety by one of two available routes. If he takes the first route, 200 soldiers will be saved. If he takes the second, there's a one-third chance that all 600 soldiers will be saved and a two-thirds chance that none will be saved. Which route should he take? Most people will urge the to general to take the first route, reasoning that it's better to save those lives that can be saved than to gamble when the odds favour even higher losses. But what about the following situation:
General's Dilemma - How Many will Die?
The general again has to choose between two escape routes. But this time his aides tell him that if he takes the first, 400 soldiers will die. If he takes the second, there's a one-third chance that no soldiers will die, and a two-thirds chance that 600 soldiers will die. Which route should he take?
In this case, most people urge the general to take the second route. The first, after all, involves the certain death of 400 men. At least with the second route there's a one-third chance that no one will be killed.
The fact that most people come to opposite conclusions about these two problems is somewhat surprising because, as a cursory inspection reveals, they're identical. In both cases, 400 soldiers will die. The only difference is that the first problem is stated in terms of lives saved, the second in lives lost. When faced with problems like these, people split three to one in favour of the first choice when the question is stated in terms of lives saved, but four to one for the second choice when it's presented as a matter of lives lost.
A case of hit-and-run
Imagine you are a member of a jury judging a hit-and-run driving case. A taxi hit a pedestrian one night and fled the scene. The entire case against the taxi company rests on the evidence of one witness, an elderly man who saw the accident from his window some distance away. He says that he saw the pedestrian struck by a blue taxi. In trying to establish his case, the lawyer for the injured pedestrian establishes the following facts: (1) There are only two taxi companies in town, 'Black Cabs' and 'Blue Cabs'. 85 percent of all taxis are black and 15 percent are blue; and (2) The witness has undergone an extensive vision test under conditions similar to those on the night in question, and has demonstrated that he can successfully distinguish a blue taxi from a black taxi 80 percent of the time.
If you were on the jury, how would you decide?
If you are at all typical, faced with eye-witness evidence from a witness who has demonstrated that he is right 4 times out of 5, you might be inclined to declare that the pedestrian was indeed hit by a blue taxi, and assign damages against the Blue Taxi Company. Indeed, if challenged, you might say that the odds in favour of the Blue Company be at fault were exactly 4 out of 5, those being the odds in favour of the witness being correct on any one occasion.
The facts are quite different. In fact, it's more likely the cab was black. To discover why, imagine that the witness sees 100 hit-and-run accidents instead of just one. By the laws of probability, about 85 of them will involve Black cabs and 15 Blue. Of the 85 Black cabs, the witness will mis-identify 20 percent--or 17 cabs--as Blue. And of the 15 Blue cabs, he'll correctly identify only 80 percent, or twelve. Thus, of the 29 times the witness says he sees a Blue cab, he's wrong 17 times--an error rate of nearly 60 percent!
What does Linda do?
Linda is 31, single, outspoken, and very bright. She majored in philosophy in college. As a student, she was deeply concerned with discrimination and other social issues, and participated in anti-nuclear demonstrations. Which statement is more likely: (1) Linda is a bank teller; or (2) Linda is a bank teller and active in the feminist movement.
Most people who respond to this quiz opt for the second statement because they associate Linda's background with the feminist movement. Their conclusion is wrong. The laws of probability state that the likelihood of any two uncertain events happening together is always less than the odds of either happening alone. For instance, the chance of tossing two heads in a row is less than the chance of tossing one. So the odds that Linda is both a teller and a feminist must be less than that she is a teller, regardless of how unsuitable that career may seem for her.
Gains and Losses
Suppose you had to make a choice between: (a) winning Rs 85 thousand outright; or (b) an 85 percent chance of winning Rs 100 thousand. Which one will you choose?
Now let's change the story while keeping the numbers identical. Now you have a choice between: (a) losing Rs 85 thousand outright or; (b) an 85 percent chance of losing Rs 100 thousand. Now which did you choose?
Chances are that in the first case you'd choose (a). After all, a bird in hand is worth two in the bush. And in the second case, chances are you chose (b) because you have a 15 percent possibility of losing nothing. Note, however, that both cases have identical expected values and there is no logical reason for anyone to prefer one option the other.
Hot Hands
Basketball players and fans commonly believe that players tend to shoot in streaks--that during a game, a player has times when he's hot and every shot goes in, and others when he's cold and barely able to hit the backboard. Sportswriters talk about streak shooting; players try to work the ball to the team-mate who has the so-called hot hand, who has made his last three or four shots. Does the hot hand really exist? To find out, Tversky interviewed a famous American basketball team's coach and his players about shooting, and then studied detail records of 48 of their games in the 1980-81 season.
The players estimated that they were about 25 percent more likely to make a shot after a hit than after a miss. In fact, the researchers found, the opposite was true. The players were six percent more likely to score a miss than a hit. Overall, the number of hot or cold streaks for this team and three other teams studied by Tversky was about what would be expected to occur by chance. "There are plenty of excellent reasons why the hot hand could exist," Tversky says. "The only trouble is, it doesn't."
Then why is belief in it so widespread? Tversky says it's because people forget that random sequences often contain streaks of one sort or another, simply by the laws of probability. For example, there's only a one-in-16 chance of tossing a coin four times and coming up with heads every time. But there's almost a 50-50 chance of getting four heads in a row on any series of 20 tosses, a 25 percent chance of five in a row, and a ten percent chance of a streak of six.
Since the average NBA player shoots around 50 percent from the field, he has reasonable odds of making streaks of four, five, even six shots in a row if he takes--as an offensive star often would--20 shots in a game. His apparent hot hand will actually just be due to the laws of chance. In other words, Tversky proved that a player on a hot streak is no more likely to make his next shot than at other times. Nonetheless, players work to get the ball to a "hot" player. Why? The answer to that is that people are eager to see patterns in random events. Stock-market chartists beware.
Mental Accounting
Imagine you are on your way to see a movie for which you have bought tickets worth $40. When you arrive at that movie hall, you discover you have lost your ticket. Would you pay $40 for another one?
Now suppose instead that you plan to buy the ticket when you arrive at the movie hall. As you approach the ticket window, you find that you have $40 less in your pocket than you thought you had when you left home. Would you still buy the ticket?
In both cases, whether you lost the ticket or lost the $40, you would be out of a total $80 if you decided to see the movie. You would be out of only $40 if you abandoned the show and went home. Kahneman and Tversky found that most people would be reluctant to spend $40 to replace the lost ticket, while about the same number would be perfectly willing to lay out a second $40 to buy the ticket even though they had lost the original $40.
"Our story is that you set up a mental account for going to the movie and, in the first problem, have already charged forty dollars," said Tversky. "If you buy another ticket, your movie account is now eighty dollars, perhaps more than you're willing to spend. But in the second problem, you merely charge the forty dollar loss to some other mental account. You can take it out of next month's lunch money or next year's vacation."
Another example of flawed mental accounting: If an investor owns two stocks, both of which are currently quoted at Rs 20, but one of which he bought at Rs10 and the other at Rs 25, he might not sell the latter one (even if its price was falling) because he did not want to suffer a loss. If he thought about the combined value of the two shares, however, he might be happy to sell both, as that would produce a net gain.
Original Cost Syndrome
Assume that an investor owns shares in a lousy company A that he bought for Rs 300, but which are now selling for Rs 200. The investor knows, he's made a mistake but he finds it impossible to sell at a loss. He is waiting for the price to go up to Rs 300 when he would sell. Assume further that the investor knows of a great company B whose shares are selling at a bargain price of Rs 200 per share but are actually worth at least Rs 600 per share. The rational decision for this investor would be to sell shares in A and buy equal number of shares in B. But chances are that he will wait for shares in A to go up to Rs 300 before he sells them. But it is also likely that when shares in lousy company A go up to Rs 300, shares in great company B may have zoomed to Rs 600. Earlier, the cash raised from sale of A would have bought equal number of shares in B. Now, that cash would buy only half as much. The investor's irrational behaviour has cost him real money.
What's your life worth?
This one is designed by Richard Thaler, a Chicago economist. Here are two questions. Answer the first one before reading the second one. (1) How much would you be willing to pay to eliminate a one-in-a-thousand chance of immediate death? and (2) How much would you have to be paid to accept a one-in-a-thousand-chance of immediate death?
A typical answer to the first question was in the range of $200. But when the same people were posed the second question, which in fact is identical to the first but stated in another way, most refused to accept even $50,000 for assuming the extra risk!
The above examples were given as incidents where educated and knowledgeable people behaved irrationally. And irrational market participants create irrational market prices. On the other hand, a rational person who has the courage to act opposite to the irrational crowd becomes rich. That is the way it has always been and that is the way it will continue to be.
Here are a few more questions with contrary answers that, I hope, would get the reader to think:
Note
This article is submitted by Sanjay Bakshi who is the Chief Executive Officer of a New Delhi based company called Corporate Investment Research Private Limited.
© Sanjay Bakshi. 1997.