Traditionally, all investment research and decisions are based on the assumption that individuals are risk averse, utility maximizers, and rational. Traditional finance hypothesizes that all available information is always reflected in market prices. Markets behaving in a manner consistent with this hypothesis are said to be efficient. Traditional asset pricing models assume market prices are determined through an unbiased analysis of risk and return. The intrinsic value of an asset is its expected cash flows discounted at a required return, based on risk-free rate and fundamental risk premium. The behavioral asset pricing model adds a sentiment premium to the discount rate.
Individuals neither always act rationally nor take all relevant and available information into account while making investment decisions. Behavioral finance confronts the assumptions of traditional finance; it challenges individual investors’ perfect rationality at the micro level, and questions the perfect efficiency of the markets at the macro level.
Behavioral finance takes into account the cognitive and emotional biases displayed by individuals while making investment decisions. Cognitive biases are basic statistical errors, information processing errors, or memory errors that cause the decision to deviate from rational decisions of traditional finance. Emotional biases arise spontaneously as a result of an individual’s attitudes and feelings. Since cognitive errors are the outcome of faulty reasoning, better education and advice can often help moderate or even eliminate the effect of such biases. Emotional biases, on the other hand, are linked to feelings, perceptions, and beliefs, causing investors to make suboptimal decisions. It is difficult to correct emotional biases; therefore efforts can only be made to adapt the decisions to those biases.
Bounded rationality is one such notion in behavioral finance which recognizes that while making decisions, a person’s rationality is restricted by his cognitive limitations. Investors in this view seek satisfactory solutions over optimal ones. In other words, the decision makers choose to “satisfice”—(Satisfy+Suffice) rather than optimize, to limit the cost and time required to find an optimal solution. The quest for an optimal solution can be so complicated and time-consuming that it is not feasible at all. Thus, instead of looking at all possible alternatives, constraints are set on alternatives that will satisfy the needs.
Furthermore, the prospect theory identifies individuals as loss-averse rather than risk-averse. Investors place a higher value in change of loss than on gain of the wealth of the same amount. Investors tend to fear losses and hence become risk seeking in an attempt to avoid them. Holding on to loss-making investments with the hope that the price would return to the mean is one such example in which investors show aversion to losses by not quitting the investment at the right time, thereby aggravating the damage further.
Some of the above biases can be corrected if the information is stored in one place and made easily accessible. It is the brain’s natural tendency to focus on what is easy to get. The evolution of financial databases has made it much easier to store and process information. Investment advisors can retrieve the required information, process the data by building models, analyze the results, and finally achieve an optimal outcome.
In conclusion, behavioral finance can improve client-advisor relationships as it helps the advisor to understand the reasons for the goals of the client. It also adds structure and professionalism to the relationship, so that the advisor is better equipped to meet the expectations of the client.
SGA Editorial Desk