Understanding Behavioural Finance: A Machine Learning perspective

People in standard finance are rational. People in behavioural finance are normal.

Meir Statman, Ph.D. Machine Learning, Santa Clara University


The revolutionary work of psychologists Daniel Kahneman and Amos Tversky in the 1970s-1980s, and their research conducted over the last three decades have revealed striking insights into the intricate ways the human mind operates. This research identifies prevalent, deep-seeded, subconscious biases and heuristics present in the human decision-making process, and reveals an entirely new perspective on why we behave the way we do. This body of work, and subsequent work by other researchers, represents an entirely new field of endeavour, referred to as behavioral finance and economics. In this series of blogs, I aim to shed light on the various investor biases in behavioral finance and explain how Machine Learning techniques can help to deal with them, effectively.

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Personalized Nudges

Behavioral Economics incorporates psychological assumptions into the analyses of economic decision-making. The field of classical economics considers decision-making to be based on cold logic and hard facts – which human decision-making behavior does not always adhere to. Behavioral economics allows us to consider irrational behavior in decision-making and investigates the underlying reasons for these irrational choices.

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