Traditional finance assumes that individuals act rationally by considering all available information in their decision-making process. This leads to optimal outcomes and efficient markets.
Behavioral finance challenges these assumptions by incorporating research on how individuals and markets actually behave. It assumes that people act “normal” rather than rational. It recognizes that people have behavioral biases that impact financial decision making. Behavioral biases can cause decisions to differ from the “rational” decisions of traditional finance.
This reading is organized as follows:
Behavioral biases can be either cognitive errors or emotional biases.
Cognitive errors:
Emotional biases:
There are two categories of cognitive biases: 1) belief perseverance biases and 2) information-processing biases.
Instructor’s Note: A summary of the nine cognitive errors is provided below. They are covered in detail in the subsequent sections. Memorize this summary.
Belief perseverance biases
Information-processing biases
Belief perseverance is the tendency to cling to one’s previously held beliefs irrationally
or illogically. Belief perseverance biases are closely related to cognitive dissonance. Cognitive dissonance is the mental discomfort that occurs when new information conflicts with old beliefs or cognitions.
The belief perseverance biases discussed in this reading are: conservatism, confirmation, representativeness, illusion of control, and hindsight.
Individuals maintain prior views by inadequately incorporating new information. From the traditional finance perspective, this can be described as the failure to update probabilities using Bayes’ formula.
This bias has aspects of both statistical and information-processing errors. It causes individuals to overweight initial beliefs about probabilities and outcomes; and under-react to new information.
Consequences of conservatism bias:
Detecting and overcoming conservatism bias:
Confirmation bias occurs when individuals look for and notice what confirms their beliefs and ignore what contradicts their beliefs.
Embedded Example
A client insists on continuing to hold stock, even when the adviser recommends otherwise because the client’s follow-up research seeks only information that confirms his belief that the investment is still a good value.
Consequences of confirmation bias:
Detecting and overcoming confirmation bias:
Representativeness bias is when people classify new information based on past experiences and classifications. The two types of representativeness bias are ‘base-rate neglect’ and ‘sample-size neglect’.
In base-rate neglect the base rate, or probability of the categorization is not adequately considered. For example, categorizing Company ABC as a “growth stock” without appropriate due diligence. FMPs rely on stereotypes when making investment decisions without adequately incorporating the base probability of the stereotype occurring. So, the classification of ABC is based on FMPs stereotypes about growth companies, but it ignores the base probability that the company may not be a growth company.
In sample-size neglect FMPs incorrectly assume that small sample sizes are representative of populations (or “real” data). In the investment context, sample size neglect can be seen when a few data points are naïvely extrapolated as being representative of a long-term trend. For example, an investor who puts too much emphasis on short-term results when considering a potential investment.
Consequences of representativeness bias:
Detecting and overcoming representativeness bias:
Illusion of control bias occurs when individuals incorrectly believe that they can control or influence outcomes when they cannot.
Consequences of illusion of control:
Detecting and overcoming illusion of control bias:
Hindsight bias is a bias where people may see past events as having been predictable and reasonable to expect. In hindsight, poorly reasoned decisions with positive results may
be described as brilliant tactical moves, and poor results of well-reasoned decisions
may be described as avoidable mistakes. Also, people will remember their own predictions
of the future as more accurate than they actually were because they are biased by the knowledge of what has actually happened.
Consequences of hindsight bias:
Detecting and overcoming the bias:
The second category of cognitive error is information-processing biases. These biases result in information being processed and used illogically or irrationally. In contrast to belief perseverance biases, these are less related to errors of memory and more to do with
how information is processed. The processing errors discussed in this reading are anchoring and adjustment, mental accounting, framing, and availability.
Anchoring and adjustment bias is an information-processing bias in which the use
of a psychological heuristic influences the way people estimate probabilities. People set an anchor that influences their decisions; they adjust the anchor up or down to reflect subsequent information. Irrespective of how the initial anchor was chosen, people often fail to adjust their anchors properly, and as a result produce biased approximations.
This bias is closely related to the conservatism bias. In the conservatism bias, people place undue weight on past information compared to new information. In anchoring and adjustment, people place undue weight on an “anchored” value.
Consequences of anchoring and adjustment bias:
Detecting and overcoming anchoring and adjustment bias:
Mental accounting bias is a bias in which people treat one sum of money differently from another sum based on which mental account (layer) the money is assigned to.
An investor may create three layers of money – the first layer includes conservative investments, the second layer has moderate risk investments, and the third layer has high-risk assets. Investors assign investments into discrete “buckets,” i.e., several non-fungible mental accounts. This method is problematic and contradicts rational economic thought because money is inherently fungible (interchangeable).
Consequences of mental accounting bias:
Detecting and overcoming mental accounting bias:
Framing bias occurs when an individual answers a question differently, depending on how it is asked (framed).
Embedded Example
A situation may be presented within a gain context (one in four start-up companies succeed) or within a loss context (three out of four start-ups fail).
Given the first frame, an FMP may adopt a positive outlook and make venture capital investments. Given the second frame, the FMP may avoid making the investment.
Consequences of framing bias:
Detecting and overcoming framing bias:
Availability bias is when people take a heuristic (sometimes called a rule of thumb or a mental shortcut) approach to estimating the probability of an outcome based on how easily the outcome comes to mind. Easily recalled and understandable outcomes are perceived as more likely than harder to recall ones.
The four sources of the bias most applicable to FMPs are retrievability, categorization, narrow range of experience, and resonance.
Retrievability: If an answer or idea comes to mind more quickly than others, it will likely be chosen as correct even if it is not. For example, a study was done in which
subjects listened to a list of 50 names and were then asked to judge if the list contained
more men or women. The list contained 30 generic women names, but the 20 men were all famous. As availability theory would predict, most of the subjects concluded that the list contained more men than women because they immediately recalled the famous men’s names.
Categorization: When solving problems, people gather information from what they
recognize as relevant search sets. If it is difficult to come up with a search set, the estimated probability may be biased. For example, in the US, baseball is a popular sport, but soccer is not. If an American is asked to list famous baseball players and famous soccer players, the list of soccer players will be relatively short. An American may incorrectly conclude that there are more famous baseball players than soccer players. Because in their categorization, there are more baseball players than soccer players.
Narrow Range of Experience: This bias occurs when a person with a narrow range
of experience uses too narrow a frame of reference based upon that experience when
he makes an estimate. For example, assume that an investor advisor has only been in the market for three years. When he makes conclusions or decisions, his availability bias will be based on three years of experience. He would not have seen the great stock market crashes, the booms/bursts of the past.
Resonance: The conclusions or decisions people take are often biased by how closely a situation resonates with their personal experience. For example, jazz music lovers are likely to overestimate how many people listen to jazz music. On the other hand, people who dislike jazz music are likely to overestimate the number of people who dislike jazz music.
Consequences of availability bias:
Detecting and overcoming availability bias:
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