Behavioural Finance, History, Concepts, Applications, Criticism (2024)

Behavioural finance is a relatively new field of study that combines the principles of psychology with traditional finance to explain how and why people make financial decisions. The field seeks to identify and explain the cognitive and emotional biases that influence investor behaviour, often leading to irrational financial decisions.

Traditional finance assumes that investors are rational and always act in their best interests. However, behavioural finance research has shown that this is not always the case. Investors are often influenced by emotions and biases, which can lead to suboptimal decision-making. Behavioural finance aims to identify these biases and understand how they affect financial decisions.

History of Behavioural Finance:

Behavioural finance emerged in the late 1970s and early 1980s as psychologists and economists began to question the rationality assumptions of traditional finance. The pioneers of the field include Amos Tversky and Daniel Kahneman, who proposed the prospect theory in 1979. The prospect theory explains how people evaluate and make decisions under uncertainty, and it challenges the rational choice theory that underpins traditional finance.

In the decades since, behavioural finance has become an increasingly popular field of study, with researchers exploring various biases and heuristics that influence financial decisions. Some of the most significant contributors to the field include Richard Thaler, who won the Nobel Prize in Economics in 2017 for his contributions to behavioural economics, and Robert Shiller, who won the Nobel Prize in Economics in 2013 for his work on asset pricing and financial bubbles.

Concepts in Behavioural Finance:

• Loss Aversion: Loss aversion is the tendency to feel more pain from a loss than pleasure from a gain. This can lead to investors holding on to losing investments longer than they should, in the hope of recovering their losses. Loss aversion can also lead to risk aversion, where investors are willing to accept lower returns to avoid losses.
• Confirmation Bias: Confirmation bias is the tendency to seek out information that confirms our existing beliefs and to ignore information that contradicts them. This can lead investors to make decisions based on incomplete or biased information.
• Overconfidence Bias: Overconfidence bias is the tendency to overestimate one’s abilities and knowledge. This can lead to overconfidence in investment decisions, leading investors to take on too much risk or make unwise investment choices.
• Herding Behaviour: Herding behaviour is the tendency to follow the crowd and make decisions based on the actions of others. This can lead to market bubbles and crashes, as investors pile into or out of investments based on the actions of others.
• Anchoring Bias: Anchoring bias is the tendency to rely too heavily on the first piece of information received when making decisions. This can lead investors to make decisions based on outdated or irrelevant information.
• Availability Bias: Availability bias is the tendency to make decisions based on readily available information, rather than more comprehensive data. This can lead investors to make decisions based on incomplete or misleading information.

Applications of Behavioural Finance:

• Portfolio Management: Behavioural finance can be used to design investment strategies that account for the biases and heuristics that influence investor behaviour. For example, a portfolio manager may design a portfolio that incorporates diversification and risk management to help mitigate the effects of loss aversion.
• Financial Planning: Financial planners can use behavioural finance to help clients make better financial decisions by understanding their biases and heuristics. For example, a financial planner may help a client develop a long-term investment plan that accounts for their tendency towards loss aversion.
• Market Analysis: Behavioural finance can help analysts understand market trends and predict market behaviour by identifying the biases and heuristics that influence investor behaviour. For example, an analyst may use behavioural finance to identify market bubbles or crashes based on herding behaviour or overconfidence bias.
• Risk Management: Behavioural finance can help identify and mitigate the risks associated with financial decision-making. For example, a risk manager may use behavioural finance to identify areas of the market where investors are susceptible to herding behaviour or overconfidence bias and take steps to manage those risks.
• Investment Education: Behavioural finance can help investors become more aware of their biases and heuristics and make better financial decisions. For example, investment education programs may incorporate behavioural finance principles to help individuals better understand their decision-making processes and how to overcome their biases.
• Corporate Finance: Behavioural finance can help corporations make better financial decisions by understanding how their own biases and heuristics influence decision-making. For example, a company may use behavioural finance to design compensation structures that incentivize executives to make decisions that are aligned with the company’s long-term goals.

Criticism of Behavioural Finance:

While behavioural finance has gained significant traction in recent years, it is not without its critics. Some argue that behavioural finance overemphasizes the role of emotions and biases in financial decision-making and downplays the role of rationality. Others argue that the field is too broad and lacks clear frameworks for understanding and predicting financial behaviour.

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