LearnRiskBehavioural Biases & Risk
Risk · Lesson 13 of 13

Behavioural Biases & Risk

6 min read  ·  Intermediate

You can understand every financial risk concept perfectly and still make catastrophic risk management decisions — because risk decisions happen under uncertainty, emotion, and social pressure. Behavioural biases are the cognitive shortcuts and emotional responses that cause intelligent people to take risks they shouldn't, avoid risks they should take, and ignore warning signs that are right in front of them.

Overconfidence — the most pervasive bias

Studies consistently show that investors dramatically overestimate both the quality of their information and their ability to interpret it. In one landmark study, 74% of US fund managers rated themselves "above average." Statistically, this is impossible. Overconfidence leads to: under-diversification (too convinced about individual ideas), overtrading (too convinced about short-term direction), and inadequate risk management (too convinced things will work out).

How overconfidence manifests in investing behaviour
Under-diversification "I know this stock will do well, so I put 40% in it" Result: one bad outcome = disaster Overtrading "I can tell when to buy and sell perfectly" Result: fees and taxes erode gains No stop-loss "It'll recover — I'm sure of my thesis" Result: small losses become big ones All three driven by the same root cause: overconfidence in your own judgement

Herding — safety in numbers (until it isn't)

Herding is following the crowd — buying what's popular, selling what everyone else is selling. It feels safe: if everyone is doing it, surely it's right? But herding is what creates bubbles and crashes. The dotcom peak, the 2021 meme stock mania, the 2021 crypto peak — all driven by herding. By the time an asset is widely popular enough for herding to be obvious, most of the value has already been captured by earlier buyers.

Recency bias — extrapolating the recent past

After three years of rising markets, investors expect markets to keep rising — extrapolating recent performance indefinitely. After a crash, they expect more crashes. This produces the classic mistake: buying high (after recent gains) and selling low (after recent losses). The 2020 COVID crash saw massive retail outflows from equity funds at the bottom — then massive inflows 6 months later after the recovery, at higher prices.

Anchoring to the wrong number

Anchoring to a purchase price ("I need to get back to break-even before I sell") ignores whether the current price makes sense given current information. The past price is irrelevant — the stock doesn't know what you paid for it. Only one question matters: given what I know now, is this the best use of this capital going forward? Anchoring prevents investors from cutting losses early and can turn a small mistake into a large one.

The defence: rules. Pre-commit to specific decisions before you're in the emotional grip of the situation. Write your sell thesis when you buy (what would make me exit?). Set position size limits before you're excited about an idea. Automate savings and rebalancing so the decision happens without your emotional input. The investors who beat their own behaviour are the ones who've systematically removed themselves from the decision-making process for their most dangerous choices.

That completes the Risk section — all 13 lessons from volatility and VIX through to the behavioural biases that make risk management so hard in practice. You now have all 88 RIP. lessons complete across all 7 subjects.

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