Behavioral pitfalls

The  page is divided into two sections. The first section introduces and defines the most common pitfalls. The second section introduces theory and background for those who want to expand their knowledge in the area of behavioral economics.

Introduction and definitions
“Your investing brain does not just add and multiply and estimate and evaluate,” says Jason Zweig in his book, Your Money and Your Brain. “When you win, lose, or risk money, you stir up some of the most profound emotions a human being can ever feel.”

Understanding and avoiding behavioral pitfalls will ultimately have a greater impact on investing success than any other factor. Since emotions and subsequent behavioral pitfalls are frequently associated with miscalculating risk tolerance and asset allocation, the new investor should be aware of behavioral pitfalls before making asset allocation decisions.

“Financial decision-making,” says psychologist Daniel Kahneman in Zweig’s book, “is not necessarily about money. It’s also about intangible motives like avoiding regret or achieving pride.”

Overconfidence
Being overconfident in your investing abilities can lead to big investing losses. A main reason is that, in the short run, the ups and downs of the stock market are random happenings. Such unpredictable variations mean that intelligence, skill, and knowledge give you no edge, and thinking they do can be “hazardous to your wealth.” “The only way to achieve everything you’re capable of is to accept what you are not capable of,” says Jason Zweig.

Loss aversion
Loss aversion is the emotional tendency to strongly prefer avoiding losses over acquiring gains. As an example, loss aversion implies that one who loses $100 will feel twice the emotional pain as another person will feel satisfaction from receiving $100. Common indications include checking your portfolio on an almost daily basis, selling funds before you intended to lock in profits, or selling when you didn't intend to in order to avoid further losses.

Herd behavior
A human instinct that causes individuals to mimic the actions of a larger group rather than decide independently based on their own information. For example, in a bull market, an investor joins the crowd to avoid being the only one to miss out; in a bear market, he gets out to avoid being the only one to lose. In both cases, he abandons his own reasoning and concludes the majority must be right. Herd investors often don’t have a sound investment plan and they listen to market noise.

Anchoring
Basing decisions or estimates on events or values already known (the “anchor”), even though these facts may have no bearing on the actual event or value. Investors will tend to hang on to losing investments by waiting for the investment to break even at the price at which it was purchased. Thus, they anchor the value of their investment to the value it once had, and instead of selling it to realize the loss, they take on greater risk by holding it in the hopes it will go back up to its purchase price.

Confirmation bias
A tendency to seek information that confirms one’s existing opinions and overlook or ignore information that refutes them. For example, when researching an investment, an investor might inadvertently look for information that supports his or her beliefs and fail to see information that presents different ideas. The resulting one-sided view can result in a poor investment choice. “In short, your own mind acts like a compulsive yes-man who echoes whatever you want to believe,” says Wall Street Journal columnist Jason Zweig.

Gambler's fallacy
In common gambling scenarios, the gambler's fallacy is a belief that a coin somehow knows about, and will try to fix, the fact that a long coin flipping streak of the same value (such as heads) must end by changing to the other value (tails).

A similar perception can happen when a stock trends in a certain direction. The investor incorrectly detects this as a pattern and guesses it will next go in the opposite direction. The investor has fallen for gambler's fallacy, incorrectly detecting patterns of market behavior and projecting them into the future.

For example, an investor may wish to sell a stock because the price has risen the past 5 days and he thinks it's now "due" for a drop. Or, he might want to hold onto a stock because the price has dropped the past 5 days and he now thinks it can't possibly get any lower.

Recency bias
The tendency to draw conclusions about the future behavior of an investment from only the recent past. This leads to investors chasing performance and then buying high and selling low. “When funds go on a streak of high returns, investors tend to get in right before the peak; then, when the hot streak goes cold, too many shareholders bail out at the bottom,” explains Jason Zweig

Regret aversion
A theory that says people anticipate regret if they make a wrong choice, and take this anticipation into consideration when making decisions. Fear of regret can play a large role in dissuading or motivating someone to do something. In investing, the fear of regret can make investors either risk averse or motivate them to take greater risks. For example, suppose that an investor buys stock in a small growth company based only on a friend's recommendation. After six months, the stock falls to 50% of the purchase price, so the investor sells the stock at a loss. To avoid this regret in the future, the investor will not invest in anything his friend recommends until he has independently researched it first.

Mental accounting
The tendency for people to put their money into separate accounts based on a variety of subjective criteria, like the source of the money and intent for each account. According to the theory, individuals assign different functions to each asset group, which has an often irrational and detrimental effect on their consumption decisions and other behaviors. For example, people often have a special "money jar" or fund set aside for a vacation or a new home, while still carrying substantial credit card debt.

Paralysis by analysis
Investors have thousands of funds to choose from plus an abundance of market “noise” telling them what they should do. The more choices they have the harder it is for them to choose one, making it more likely they won’t make a choice and will fail to invest. For example, employees pass up billions every year in free money offered by their employer’s matching retirement plans. They do this simply because they can’t decide which investment course to take.

What is behavioral economics?
Behavioral economics explores the emotions and biases that lead investors and consumers to sometimes make irrational economic decisions. It also studies why and how their behavior does not follow the predictions of standard economic models that assume people make rational choices about spending money to “maximize their total satisfaction.”

Many behavioral pitfalls are based on the finding that investors are risk averse. They dislike losses almost twice as much as they like comparable gains and may take on more risk hoping to avoid a loss than realize a gain. They may also abandon a sound strategy under the stress of a loss. Investors should carefully consider this when choosing their all-important asset allocation.

Investors may not sense risk-aversion bias when an asset allocation is made. It will, however, present itself during a market downturn or crash, when the emotional stress of a loss can cause panic. If the asset allocation was not properly based on their risk tolerance, they are likely to abandon the market and sell low.

History
Many ideas now accepted in behavioral economics can be traced back to groundbreaking contributions by mathematician Daniel Bernoulli, New Theory on the Measurement of Risk (1738) and philosopher Adam Smith, The Theory of Moral Sentiments (1759). The key to these early works was their elements of psychology, but psychology was subsequently rejected by economists at the turn of the 20th century because they thought it provided too unsteady a foundation for economics.

In the second half of the 20th century, several researchers challenged the dismissal of psychology as a branch of economics. George Katona, Harvey Leibenstein, Tibor Scitovsky, and Herbert Simon wrote books and articles suggesting the importance of psychological measures and bounds on rationality. They attracted attention, but did not alter the fundamental direction of economics. Additional work by Allais (1953), Ellsberg (1961) , Markowitz (1952) , and Strotz (1955) added more data, and the argument for psychology as a valid branch of economics became more convincing and generally accepted.

Enter Prospect Theory
The final step in the advancement of behavioral economics as a significant field of economic research is often thought to have started with the work of psychologists Daniel Kahneman and Amos Tversky. Kahneman and Tversky began their joint work in 1969, and the excellent working relationship ultimately led to the publishing of their seminal paper, Prospect Theory, ten years later (1979). Prospect Theory offers a framework for how people frame economic outcomes as gains and losses and how this framing affects people's economic decisions and choices. Tversky died in 1996. Kahneman received the Nobel Prize in Economic Sciences for his work in 2002.

Prospect Theory and the Individual Investor
Prospect theory is important because it brings awareness to the common and costly pitfalls that frequently trip up investors. There are two ways pitfalls arise: heuristics and cognitive biases.

Heuristics are mental shortcuts people use for processing complex information. The process falls back on experience by trial and error, rule of thumb, or common sense. While heuristics provide a fast decision, often those decisions are faulty when applied to investing. Anchoring is a heuristic.

Cognitive bias describes inherent thinking errors that humans make in processing information. When investors act on a bias, they do not explore the full issue and can be ignorant of evidence that contradicts their initial opinions. Confirmation bias is an example of cognitive bias.