Behavioral Finance and Investing Bias
The CFA Institute dedicates an entire session to what drives investors behaviors. There are three themes to this topic and I’m going to highlight the first theme they focus on in this post: Heuristic-driven bias. Its a fascinating subject matter primarily because all investors, whether they be inexperienced or sophisticated, fall prey to these bias’ during their investing lifetime. Guarding against them is an ongoing endeavor.
Heuristic-driven bias is based on the notion that investors develop a “heuristic learning process”. They develop investment decision-making rules based on rules of thumb derived from personal experience, trial and error or just plain experiments. This doesn’t sound all too bad, except, for when you realize there is no real research into relevant financial data or other important data to help support their decisions, its more of a hunch based on the knowledge they they have casually gathered over time.
Generally their heuristic-driven decision come in four forms: Representativeness, Overconfidence, Anchoring and Adjustment and Aversion to Ambiguity.
Representativeness is a bias that comes from expectations based upon past experiences, otherwise known as stereo-types. One train of thought is that a firm that reports good earnings, will continue to report good earnings… without determining if the performance will actually continue. Another example is thinking of “environmentally aware” firms as inherently “good” firms, without considering the notion that they good be very bad investments, despite the high level of “environmental awareness”.
Overconfidence is an easy one. Generally, most people think highly of their thought process and their ability to predict the future. This will almost always lead to surprises as people’s confidence levels often lead them to significantly “underestimating” the downside risk or the upside reward of their decisions.
Anchoring-and-Adjustment tends to be a lessen in managing humility. An analyst may have published a glowing projecting for a firm, based on positive earning expectations that will be released soon. When the earnings are actually released and are much more negative then the analyst had forecasted (calling for a much more somber growth path), the analyst will likely be hesitant to deviate sufficiently from his/her previous conclusions. The analyst may adjust downward his previous projections, but egos often make it difficult for them to throw out old assumptions and start fresh based on the newly released data. This leads to still “too rosy” of a picture, given the new data.
Aversion-to-Ambiguity is really “fear of the unkown”. People don’t like to invest in what they don’t understand. Many times that is why many people invest “too much” in companies they work for, because they “understand” the company and the industry. This bias can also be demonstrated in trending markets. Where there is a trend, there is higher confidence on the part of the investor. If there is no trend (high volatility) an investors confidence is shaken, because they can’t play the odds of a particular trend, if it doesn’t exist. This can also be demonstrated by discussing the housing bubble… housing “always” goes up, we all “understand” real estate, look at how many people have made money investing in real estate! All of the previous notions, create a sense of clarity for the investor (less ambiguity) and they begin to poor-in.
I’ll discuss the other themes of Behavioral Finance in future posts.