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Behavioral

Recency bias

Overweighting recent events when forming expectations. Causes traders to chase recent winners and avoid recent losers — usually wrong.

What it means

Recency bias is the cognitive tendency to weight recent observations more heavily than historical patterns. In trading: after 3 consecutive winning trades, traders feel highly confident (often over-sizing the next trade). After 3 losses, they feel doubt and undersize, even when their system's long-term expectancy is positive. The recent sample dominates the long-run base rate.

Why it matters

Recency bias destroys position sizing discipline. After winning streaks, traders take outsized positions just as the system is most likely to mean-revert. After losing streaks, they reduce positions just before the system's edge re-asserts. The pattern is documented across thousands of retail accounts and is one of the dominant sources of underperformance.

How to use it

Size positions based on long-run statistics, not recent streak. Use fixed-fractional sizing (1% of equity) regardless of recent results. If you must adjust, adjust slowly: lower size by 0.25× after 5+ consecutive losses, raise by 0.25× after 5+ consecutive wins. The shorter the lookback, the more recency bias contaminates the sizing decision.

Take it further

Want a worked example or a deeper dive? Ask Rocky how this concept applies to your specific watchlist or trade idea.

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