Behavioral finance models make certain assumptions. We will look at a few of them.
Aversion to Loss
Investors are strongly averse to risk and will take them only if the expected returns are high and compensates them for the risk.
Daniel Kahneman and Amos Tversky came up with a study on how people react to risk called the Prospect Theory. The theory outlines how individuals react differently in undertaking risk for gains and when they concern losses.
Kahneman explains this with an example. A group of Princeton students
were asked to take a bet where if they tossed the coin and got heads they would lose $10, just how much would the researchers have to pay for the student to take the bet? The amount he says is about $125. If a ratio were to be put on how much individuals are averse to losses more than they like winning is put at about 2 to 3. This is seen in the manner in which they would invest as well.
In an interview with PBS, Kahneman states that individuals indicate similar patterns as they did 20 years ago. If changes have occurred they have in the sphere of institutions. You can watch and understand risk aversion in the words of Kahneman himself at http://www.youtube.com/watch?v=rZUylXXJbhE
Overconfidence
On the other end of the spectrum, overconfidence is another characteristic used to explain pricing anomalies. Individuals who are overconfident will stop being rational and over-estimate their abilities to take risk and therefore take calls on securities that are not in their benefit. A group of such investors can lead to the security being mispriced. In the long run, prices will adjust but by then these over confident investors would have taken a hit on their investments. The issue to consider is the actual period of adjustment before markets return to equilibrium, as if it’s possible to predict market mispricing and use it to earn abnormal profits. This is particularly true of large companies, where over confidence occurs and the time of adjustment for new information is far slower.
How individuals take risks and therefore their trading choices are explained by several behavioral models.
Some of them are gamblers fallacy, mental accounting, conservatism, disposition effect, narrow framing and representativeness. All these theories point out that there is no homogeneity in the way they ascertain the price of the asset. This leads to them exhibiting different investing methods, which can explain pricing anomalies to some degree.
- Narrow Framing sees investors seeing issues in isolation.
- Disposition effect explains that investors tend to want to avoid mistakes rather than making gains.
- Conservatism is the model that states that many investors tend to react slowly to new information about an asset.
- Mental accounting sees individuals maintaining separate mental accounts of their investments, rather than taking an organic point of view.
- Gamblers fallacy highlights how if an investor is on a winning streak, he will tend to wrongly assume that the trend will continue and make investment assumptions accordingly.
- Representativeness refers to when investors use current trends to predict probability of outcomes.
Information Cascades
Behavioral finance uses its models to understand how individuals invest and how the group impacts their behavior as well. Humans like other animals like cows, goats tend to seek strength in numbers and look for signs within the group to invest. Recent examples of this behavior are the mortgage backed securities and the dotcom bubble. The pricing at the peak of these bubbles were not on account of fundamental strengths in the securities, but an irrational exuberance. The sense that ‘if everybody is investing in them so should I’ kicks into play. Once the bubble bursts and money is lost investors in retrospect wonder why they did what they did. This phenomenon is called herding.
Information cascading on the other hand is slightly less irrational. True here too market participants follow someone, but it is based on reported outcomes and data. If an investor is making picks based on an analysts findings and outcomes and an exchange of such information spreads wider and wider in the investment circle we say the information cascade is strong. It is a good mechanism where information is dissipated.
In conclusion it can be said that behavioral finance aims at understanding why investors invest the way they do and thereby market pricing anomalies. How do investors view risk and how do they make decisions. It tries to explain why the emotional tail wags the rational dog.
