New Research Helps Explain the Underperformance of Active Managers

larry swedroeBy applying artificial intelligence and Chat GPT to statements made by active fund managers, researchers have found that their underperformance can be partly explained by overconfidence that led to, among other things, excessive risk taking.

Behavioral finance is the study of how psychological factors affect financial decision-making, examining how emotions, biases, and cognitive limitations can lead to making irrational decisions in markets. Behavioral finance research has shown that investors are often susceptible to a variety of biases, such as:

  • Loss aversion: tending to experience more pain from losses than pleasure from equivalent gains;
  • Herding: tending to follow the crowd, even when doing so is irrational;
  • Overconfidence: often overestimating their own knowledge and abilities; and
  • Recency bias: giving too much weight to recent information and events.

Another well-documented bias is self-attribution: a cognitive bias where individuals tend to attribute their successes to internal, personal factors (skill) and their failures to external, situational factors (bad luck). Self-attribution bias is viewed as a learning bias that hinders investors from objectively updating beliefs about their own ability based on their past investment performance. It results in overweighting their successes and underweighting their failures – leading to overconfidence, excessive risk taking, excessive trading, and underperformance.