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Investing Driving You Crazy? Maybe Its Because You Already Are! (Part 2)
by Kurt Box (Write for us!)
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In part one of this series on investor biases and behavioral
finance we discussed the two major investor biases (cognitive and emotional). We recognized that both cognitive and emotional biases result in irrational decisions, with cognitive biases stem from faulty reasoning and emotional biases originating from impulsive feelings or intuition (as opposed to conscious reasoning). We then laid out some types of cognitive biases (anchoring, adjustment, availability, representativeness, selective memory , overconfidence and mental accounting) and emotional biases (regret, lack of self-control, loss aversion, hindsight, denial and herding or groupthink). In this article we will give examples of some common cognitive errors so that you can determine if you are guilty of some of these biases in your own investment (and otherwise) dealings.
Anchoring and Adjustment
Anchoring can best be explained through the following experiment by Amos Tversky and Daniel Kahneman. They set up a wheel with 100 numbers on it (similar to those used on T.V.). They then spun the wheel and asked the subjects an extremely difficult question (a question to which no one would know the answer). The subjects were asked the percentage of African nations in the United Nations. They were then asked to first state whether or not the percentage was above or below the number on the wheel and second to give their exact answer. Remarkably, Tversky and Kahneman found that the subjects answer was substantially influenced by the number on the wheel. For example, when the wheel stopped on 10, the median answer given was 25% but when the wheel stopped on 65 the median answer was 45%! Remember that the subjects understood before the question that the number on the wheel was completely random and should have had no emotional significance.
Another example: At the height of the Japanese stock market bubble in 1989, Yale University Economics Professor Robert Shiller found that 14% of poll respondents expected a market crash. However, right after the market actually did crash, 32% of those polled said that they now expected a crash!
In making judgments about the level of stock prices, the most likely "anchor" will be the level of recent prices. In other words, the market is rationally valued today because it is close to the value of yesterday (without giving thought to whether or not yesterday’s value was rational). Applied to individual stocks this could be anchoring to other stocks and the market. This would help explain why overall movements in the stock market have such an effect on individual stocks and why market indices are as volatile as they are.
Representativeness Bias
Representativeness is another mental shortcut that causes us to give too much weight to recent evidence (such as short-term performance numbers, recent price increases, etc.) and too little weight to the evidence from the more distant past. The result is that we give too little weight to the real odds of an event happening (one aspect of overconfidence). According to Shiller, “people tend to make judgments in uncertain situations by looking for familiar patterns and assuming that future patterns will resemble past ones, often without sufficient consideration of the reasons for the pattern or the probability of the pattern repeating itself.”? Sound familiar? These patterns often result in significant asset price bubbles (i.e. Internet stocks in 2000 or price of housing in San Diego today).
Availability Bias
An availability bias occurs when we overweigh evidence that comes easily to mind. This could be recent evidence, (ties closely to representativeness) or what we perceive as meaningful events. As an example, suppose you were in a car accident later on today. It would be a natural tendency for you to drive more carefully for the next couple of weeks or months; as time passes, however, your driving would return to normal. Unfortunately, we are also overly influenced by attention grabbing information (can you say MSNBC?) that is likely not even pertinent. It causes us to think that events that receive heavy media attention are more important than they really are. Availability bias causes investors to over-react to market conditions whether they are positive or negative. Witness the tech bubble in the late 1990’s and the “death of stocks”? in 1982 (as headlined on many newspapers and financial publications that year).
Anchoring and Adjustment
Anchoring can best be explained through the following experiment by Amos Tversky and Daniel Kahneman. They set up a wheel with 100 numbers on it (similar to those used on T.V.). They then spun the wheel and asked the subjects an extremely difficult question (a question to which no one would know the answer). The subjects were asked the percentage of African nations in the United Nations. They were then asked to first state whether or not the percentage was above or below the number on the wheel and second to give their exact answer. Remarkably, Tversky and Kahneman found that the subjects answer was substantially influenced by the number on the wheel. For example, when the wheel stopped on 10, the median answer given was 25% but when the wheel stopped on 65 the median answer was 45%! Remember that the subjects understood before the question that the number on the wheel was completely random and should have had no emotional significance.
Another example: At the height of the Japanese stock market bubble in 1989, Yale University Economics Professor Robert Shiller found that 14% of poll respondents expected a market crash. However, right after the market actually did crash, 32% of those polled said that they now expected a crash!
In making judgments about the level of stock prices, the most likely "anchor" will be the level of recent prices. In other words, the market is rationally valued today because it is close to the value of yesterday (without giving thought to whether or not yesterday’s value was rational). Applied to individual stocks this could be anchoring to other stocks and the market. This would help explain why overall movements in the stock market have such an effect on individual stocks and why market indices are as volatile as they are.
Representativeness Bias
Representativeness is another mental shortcut that causes us to give too much weight to recent evidence (such as short-term performance numbers, recent price increases, etc.) and too little weight to the evidence from the more distant past. The result is that we give too little weight to the real odds of an event happening (one aspect of overconfidence). According to Shiller, “people tend to make judgments in uncertain situations by looking for familiar patterns and assuming that future patterns will resemble past ones, often without sufficient consideration of the reasons for the pattern or the probability of the pattern repeating itself.”? Sound familiar? These patterns often result in significant asset price bubbles (i.e. Internet stocks in 2000 or price of housing in San Diego today).
Availability Bias
An availability bias occurs when we overweigh evidence that comes easily to mind. This could be recent evidence, (ties closely to representativeness) or what we perceive as meaningful events. As an example, suppose you were in a car accident later on today. It would be a natural tendency for you to drive more carefully for the next couple of weeks or months; as time passes, however, your driving would return to normal. Unfortunately, we are also overly influenced by attention grabbing information (can you say MSNBC?) that is likely not even pertinent. It causes us to think that events that receive heavy media attention are more important than they really are. Availability bias causes investors to over-react to market conditions whether they are positive or negative. Witness the tech bubble in the late 1990’s and the “death of stocks”? in 1982 (as headlined on many newspapers and financial publications that year).
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