Set out the behavioural biases that investors commonly show
The idea
Behavioural finance catalogues the ways real investors depart from the rational agent the models assume. Overconfidence produces too much trading and too little diversification. Loss aversion makes a loss hurt more than an equivalent gain pleases, which is why losing positions are held and winning ones sold - the disposition effect. Anchoring fixes a judgement to an irrelevant number such as the purchase price. Herding substitutes other people's conviction for one's own analysis, and confirmation bias filters out the evidence that would have changed a view. Knowing the list does not remove the biases; what limits them is process - written rules, decided in advance, that do not require calm judgement in the moment.
Formulas
Gain needed to recover a loss
gain needed = fall ÷ (1 − fall)
- fall
- the percentage drop from the old price, as a decimal
- gain needed
- the percentage rise from the new price that gets back to the old one
A fall of 50% needs a gain of 100%. The gain is measured on a smaller base, which is why avoiding large losses matters more than it looks.
A practice question
Loss aversion describes the tendency for a loss to feel:
- more painful than an equal gain feels good - correct
- less painful than an equal gain feels goodWhy not: This reverses the bias. Losses are weighted more heavily than gains.
- as painful as an equal gain is pleasantWhy not: This is what a rational, symmetric investor would feel. Loss aversion is the finding that people do not.
Loss aversion is a quirk of human feelings. A loss hurts more than a gain of the same size feels good. Losing 1,000 feels worse than gaining 1,000 feels nice, and studies suggest the pain is roughly twice as strong. A purely logical investor would treat both equally, but real people do not. This is why investors often avoid selling a losing investment, because selling makes the loss real. There is no formula; the idea is: pain of a loss > pleasure of an equal gain.
A harder one
Overconfidence in investing most commonly shows up as:
- excessive cautionWhy not: Caution reflects doubt. Overconfidence produces the opposite: larger and more frequent bets.
- excessive trading and under-diversification - correct
- slow updating of views as new information arrivesWhy not: That describes conservatism, a different bias. Overconfident investors tend to act on their own view too readily, not too slowly.
Overconfidence means believing your own judgement and information are better than they really are. An investor who thinks she can pick winners will trade more often, because she thinks each trade adds value. She will also hold a few favourite stocks rather than many, because she sees little need to protect against being wrong. Both raise costs and risk without raising returns. Caution and slow updating of views are different biases. There is no formula.
The hardest tier
Frequent portfolio monitoring can worsen outcomes for a long-horizon investor because:
- each review triggers a transaction feeWhy not: Looking at a portfolio does not itself cost anything. The harm comes from behaviour.
- losses are seen more often, tempting reactive trades - correct
- prices become less accurate when watchedWhy not: Observation does not change prices. The risk is the investor's reaction to what is seen.
Checking often means seeing more losses, and losses hurt more than equal gains please (loss aversion). Shares can be down in many single months or quarters yet rise over years. An investor who checks daily sees many small losses, each feeling about twice as painful as a gain of the same size, and she is tempted to sell at a bad time. This is called myopic (short-sighted) loss aversion. Checking once a year shows far fewer losses, so she is more likely to stay invested. There is no formula.
In the app: 18 practice questions on this outcome, a narrated walkthrough with diagrams, spaced review that brings it back before you forget it.
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