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Anchoring effect

AnalyticsTrade Team
AnalyticsTrade Team Last updated on 26 Apr 2023

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Anchoring Effect

The anchoring effect is a cognitive bias that occurs when people rely too heavily on the first piece of information they receive when making decisions. This initial piece of information, or “anchor,” serves as a reference point from which all subsequent decisions are made. The anchoring effect is a common phenomenon in the world of finance, where investors and traders often rely on the first piece of information they receive when making decisions about investments.

History of the Anchoring Effect

The anchoring effect was first identified by psychologists Amos Tversky and Daniel Kahneman in 1974. They conducted a series of experiments to test the effect of anchoring on people’s decisions. In one experiment, they asked participants to estimate the percentage of African countries in the United Nations. Before answering, participants were asked to spin a wheel of fortune that had numbers ranging from 0 to 100. Unbeknownst to the participants, the wheel was rigged so that it always landed on either 10 or 65. The researchers found that those who spun the wheel with the number 10 estimated the percentage of African countries to be lower than those who spun the wheel with the number 65. This showed that the initial number served as an anchor, influencing the participants’ subsequent estimates.

Table of Comparisons

Anchor Estimate
10 25%
65 45%

Summary

The anchoring effect is a cognitive bias that occurs when people rely too heavily on the first piece of information they receive when making decisions. This initial piece of information, or “anchor,” serves as a reference point from which all subsequent decisions are made. The anchoring effect was first identified by psychologists Amos Tversky and Daniel Kahneman in 1974. To learn more about the anchoring effect, visit websites such as Investopedia, The Balance, and Psychology Today.

See Also

  • Confirmation Bias
  • Availability Heuristic
  • Framing Effect
  • Representativeness Heuristic
  • Status Quo Bias
  • Loss Aversion
  • Hindsight Bias
  • Overconfidence Bias
  • Confirmation Bias
  • Optimism Bias

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