Prospect Theory is probably the most important piece of literature in behavioral finance. The conclusions made in prospect theory underlie a lot of aversions and biases, which have been discussed in different articles. Hence, in order to understand all those biases and the behavioral finance theory in general, it is important to understand what the prospect theory is and how it impacts the decisions of investors.
Prelude to Prospect Theory
Prospect theory can be best understood by first understanding its predecessor theories. Before behavioral finance, traditional economic theories considered man to be a rational agent. Hence they assumed that human beings are making decisions to maximize certain variables. The earlier assumption was that human beings were maximizing expected value. This was changed by a mathematician named Bernoulli, who claimed that investors always try to maximize utility. This theory was in practice for close to 300 years before being replaced by prospect theory!
What is Prospect Theory?
The interesting thing about prospect theory is that it was not proposed by a finance or economics academician. Instead, this theory was developed and propounded by a psychologist. This is the reason why this theory does not make an inherent assumption that people are indeed rational. Instead, this theory tries to describe the world as it is.
The gist of the prospect theory is that human beings have a cognitive bias. This bias gets them to view losses and gains differently. This perception of loss or gain plays a critical role in decision making. This is best understood with the help of an example.
Your initial net worth is $1000. Then, you are given two options:
- A 50% chance of winning another $1000
- 100% chance of winning $500
In this case, your initial net worth is $2000. Once again, you are given two options:
- A 50% chance of losing $1000
- 100% chance of losing $500
The Nobel prize-winning psychologist Kahneman actually conducted this experiment. He found that in the case of example 1, most people would choose option 2, whereas, in the case of example 2, most people would choose option 1.
This was clearly irrational behavior. This is because if investors are risk-seeking, then in both cases, they should play the odds and go with option 1. On the other hand, if they are risk-averse, then in both cases, they should avoid the uncertainty and take a certain outcome and choose option B. If the investors are trying to maximize the expected value, then they should be indifferent to the options because in both cases, the expected value is the same, i.e., $1500.
The Conclusion from the Experiment
It was concluded that human behavior is clearly influenced by the starting point, i.e., their reference point. In case one, the reference point was $1000, and the question was framed in terms of gains. Here the investor wanted to make sure that there was at least some gain. Hence, they choose the option where the gain is less but certain. It needs to be noted that investors exhibited risk aversion here.
On the other hand, in the second example, the reference point was $2000. Here the choices were framed in terms of losses. The question really being asked to the investors was whether they would like to surely lose an amount or take a chance at losing a larger amount. The real answer the investors wanted to give was that they do not want to lose any amount. Hence investors choose the option where there is a chance of not losing any money even if it also means that they might lose more money in the process. It needs to be noted that the investors were exhibiting risk-seeking behavior here.
Hence, the same investor was exhibiting different behaviors even though the utility, as well as the expected value, was the same. This was when it was concluded that human beings view gains and losses differently. When faced with a gain, they tend to become conservative. However, when faced with a loss, they tend to start taking excessive risks. This risk is taken in order to avoid the loss.
Prospect Theory and the S-Curve
The prospect theory has been represented in the form of a curve to make it easier to understand. The X-axis represents the gains and losses, whereas the Y-axis represents the utility. While dealing with gains, the curve has a convex shape. This shows the risk avoidance behavior of the investor. At the same time, while dealing with losses, the curve has a concave shape showing the tendency to take risks.
The prospect theory has changed the way in which investments are marketed across the world. Sellers always try to frame the prospect theory in the form of a loss. It has also led to further research, which ended up in describing the loss aversion bias and framing bias in more detail.
The bottom line is that human beings are not rational. However, they are not completely irrational, i.e., their behavior is not completely unpredictable either. Instead, it follows a series of contradictory steps depending upon how the situation is perceived by the investors. This situation is explained in the form of prospect theory and the S-curve.
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- Behavioral Finance - An Introduction
- Heuristics and their role in Finance
- Advantages of Behavioral Finance
- Limitations of Behavioral Finance
- FAQ’s About Behavioral Finance
- Prospect Theory
- How Loss Aversion Affects Investment Decisions
- The Sunk Cost Fallacy
- The Endowment Effect
- Regret Aversion Bias
- Self-Control Bias
- Anchoring Bias in Behavioural Finance
- Confirmation Bias in Behavioral Finance
- Herd Mentality Bias
- Mental Accounting
- Recency Bias
- Overconfidence Bias
- Conservatism Bias
- Framing Bias
- Behavioral Portfolios
- Hindsight Bias
- Illusion of Control Bias
- Status Quo Bias
- Sample Size Neglect
- Optimism Bias
- Cognitive Dissonance Bias
- Home Country Bias
- Availability Bias in Behavioural Investing
- The Bias Blind Spot
- The Narrative Fallacy
- The Planning Fallacy
- Base Rate Fallacy
- Contrarian Investing
- Cultural Influences on Financial Decisions
- Behavioral Life Cycle Theory
- The Barnewall Model
- Bielard, Biel and Kaiser (BBK) Model
- Three Dimensional Pscychographic Model
- Categorizing Behavioral Biases
- Lessons Learned in Behavioural Finance