Biases in Risk Perception

Monday, 16/03/2015 | 10:20 GMT by Liam O'Brien
  • In Behavioural Finance there is a branch known as Prospect Theory, which deals with the way ordinary people make decisions about risk.
Biases in Risk Perception
  1. In Behavioural Finance there is a branch known as Prospect Theory, which deals with the way ordinary people make decisions about risk when knowing the probability of the outcome. It’s well accepted that people are not rational when they have to make decisions pertaining to risk, as they are influenced by many cognitive biases and distortions.
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Prospect Theory & Cognitive Biases

The founding fathers of Prospect Theory, Amos Tversky and Daniel Kahneman (Noble prize winner), were the first researchers to identify and carefully study Cognitive Biases. They proved that a simple version of Expected Utility Theory did not accurately describe human behaviour.

The original Prospect Theory was later refined to produce Cumulative Prospect Theory which includes some of the following components:

Narrow Framing – When a person makes a decision, whether to invest or to make a gamble, they tend to act as though this decision was being taken in isolation. This is understandable since making the best decision requires taking into account all the risks a person is facing in their entire life, which is often too complex.

Reference Return – For example, if the market went up 20%, and a person made 5% on their position, most people wouldn’t be pleased with that outcome. Conversely, if the market fell 10%, and a person made 5% on their position, most people would be rather pleased. This shows that the utility that one gets from an investment is not simply a function of the actual return, but also depends on how that return compares to some mental point of reference the person has.

Loss Aversion – For most people, the pain of losing $1,000 is about twice the magnitude of the pleasure of gaining $1,000. Undoubtedly this distorts people’s decision making. For example, a person may decline a potential profit opportunity to avoid a potential loss even though the loss is comparatively small.

Probability Weighting – People tend to skew probabilities when making decisions by giving an unlikely event a higher probability than what is actually experienced, such as winning a lottery or getting a rare disease. On the other hand, people act as though likely events are somewhat less likely than they actually are.

Curved Value Function – People are risk averse with respect to gains, but become much more willing to take risks when facing a potential loss. To illustrate, if guaranteed a gain of $1,000 versus a 50% chance to gain $2,000 or $0, most would take the first option even though the expected value is the same. However, if guaranteed a loss of $1,000 versus a 50% loss of $2,000 or $0, most would take the second option, preferring to take the chance that they lose nothing. In terms of gains, people are risk sensitive, but regarding loss, they are less risk sensitive.

About:

Founder and Managing Director of R3 Analytics, Liam O’Brien has considerable experience and knowledge in trading and Risk Management across multiple asset classes, developed over more than a decade in the financial services industry. Liam began as a proprietary trader in the industry and has since held roles in funds management, electronic trading, quantitative trading and risk, and broader investment banking. He has an intimate understanding of managing risk across all business units and a full appreciation of the role financial technologies serve in making Forex trading firms successful. Liam studied at and is a graduate of Harvard Business School.

Email or call +61 2 8188 4400 for risk management consultation and solutions.

  1. In Behavioural Finance there is a branch known as Prospect Theory, which deals with the way ordinary people make decisions about risk when knowing the probability of the outcome. It’s well accepted that people are not rational when they have to make decisions pertaining to risk, as they are influenced by many cognitive biases and distortions.
binary

Prospect Theory & Cognitive Biases

The founding fathers of Prospect Theory, Amos Tversky and Daniel Kahneman (Noble prize winner), were the first researchers to identify and carefully study Cognitive Biases. They proved that a simple version of Expected Utility Theory did not accurately describe human behaviour.

The original Prospect Theory was later refined to produce Cumulative Prospect Theory which includes some of the following components:

Narrow Framing – When a person makes a decision, whether to invest or to make a gamble, they tend to act as though this decision was being taken in isolation. This is understandable since making the best decision requires taking into account all the risks a person is facing in their entire life, which is often too complex.

Reference Return – For example, if the market went up 20%, and a person made 5% on their position, most people wouldn’t be pleased with that outcome. Conversely, if the market fell 10%, and a person made 5% on their position, most people would be rather pleased. This shows that the utility that one gets from an investment is not simply a function of the actual return, but also depends on how that return compares to some mental point of reference the person has.

Loss Aversion – For most people, the pain of losing $1,000 is about twice the magnitude of the pleasure of gaining $1,000. Undoubtedly this distorts people’s decision making. For example, a person may decline a potential profit opportunity to avoid a potential loss even though the loss is comparatively small.

Probability Weighting – People tend to skew probabilities when making decisions by giving an unlikely event a higher probability than what is actually experienced, such as winning a lottery or getting a rare disease. On the other hand, people act as though likely events are somewhat less likely than they actually are.

Curved Value Function – People are risk averse with respect to gains, but become much more willing to take risks when facing a potential loss. To illustrate, if guaranteed a gain of $1,000 versus a 50% chance to gain $2,000 or $0, most would take the first option even though the expected value is the same. However, if guaranteed a loss of $1,000 versus a 50% loss of $2,000 or $0, most would take the second option, preferring to take the chance that they lose nothing. In terms of gains, people are risk sensitive, but regarding loss, they are less risk sensitive.

About:

Founder and Managing Director of R3 Analytics, Liam O’Brien has considerable experience and knowledge in trading and Risk Management across multiple asset classes, developed over more than a decade in the financial services industry. Liam began as a proprietary trader in the industry and has since held roles in funds management, electronic trading, quantitative trading and risk, and broader investment banking. He has an intimate understanding of managing risk across all business units and a full appreciation of the role financial technologies serve in making Forex trading firms successful. Liam studied at and is a graduate of Harvard Business School.

Email or call +61 2 8188 4400 for risk management consultation and solutions.

About the Author: Liam O'Brien
Liam O'Brien
  • 2 Articles
  • 6 Followers
About the Author: Liam O'Brien
Liam O’Brien has considerable experience and knowledge in trading and risk management across multiple asset classes, having developed over more than a decade in the financial services industry. Liam began as a proprietary trader in the industry and has since held roles in funds management, electronic trading, quantitative trading and risk, and broader investment banking. He has an intimate understanding of managing risk across all business units and a full appreciation of the role financial technologies serve in making forex trading firms successful. Liam studied at and is a graduate of Harvard Business School. Liam O’Brien has considerable experience and knowledge in trading and risk management across multiple asset classes, having developed over more than a decade in the financial services industry. Liam began as a proprietary trader in the industry and has since held roles in funds management, electronic trading, quantitative trading and risk, and broader investment banking. He has an intimate understanding of managing risk across all business units and a full appreciation of the role financial technologies serve in making forex trading firms successful. Liam studied at and is a graduate of Harvard Business School.
  • 2 Articles
  • 6 Followers

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