Recency bias is the tendency to overweight recent events and outcomes when making decisions, while underweighting longer-term data. In trading, this manifests as assuming recent market conditions will persist indefinitely — expecting further gains after a rally or further losses after a crash. Recency bias creates a dangerous feedback loop where traders chase recent performance rather than evaluating current probabilities objectively.
Overweighting recent trades, wins, or losses in decision-making. Assuming recent market conditions (trending, ranging, volatile) will continue. Performance chasing: allocating to assets that have recently performed well. Strategy abandonment: discarding a system after a short losing streak. Recency bias is strongest immediately after an emotional event.
Before entering, review performance over a statistically significant sample size (50+ trades), not just the last few. Evaluate whether the current setup meets your system's criteria regardless of recent outcomes. Check whether you are drawn to an asset or strategy because of its recent performance rather than objective edge. Use systematic rules to prevent recency-driven entries.
Do not abandon a strategy after a short losing streak — check whether the drawdown is within historical norms. Avoid holding positions longer than planned because 'the trend has been working'. Exit based on predetermined criteria, not on extrapolation of recent price action. Review trade journals quarterly to maintain long-term perspective.
Ongoing self-assessment; particularly important during strategy review and portfolio rebalancing
Combat recency bias by maintaining detailed trading statistics over long periods — when you can see that your current drawdown is within the normal range of your system's history, you are less likely to panic and deviate. Deliberately seek out counter-examples to your current bias: if you have been bullish recently, study bear market scenarios. Time-decay your weightings — give equal importance to all data, not just the most recent.
Loss aversion, a cornerstone of Prospect Theory developed by Kahneman and Tversky, states that the psychological pain of losing is approximately twice as powerful as the pleasure of an equivalent gain. In trading, this manifests as: holding losers too long (hoping they'll come back), cutting winners too short (fear of giving back gains), and avoiding trades after recent losses.
FOMO (Fear Of Missing Out) drives traders to enter positions impulsively because they see prices rising or because social media is buzzing about an asset. Herding behaviour — following the crowd — amplifies FOMO by creating social proof. Together, these biases cause buying at tops and chasing momentum that's already exhausted.
The sunk cost fallacy occurs when traders continue holding a losing position or investing additional capital because of the resources already committed, rather than evaluating the position on its current merits and future prospects. The time, money, and emotional energy already spent become anchors that prevent rational decision-making, leading to escalating commitment to failing trades.
Revenge trading is the emotionally driven behaviour of immediately re-entering the market after a loss with the goal of recovering the lost money as quickly as possible. This reactive pattern abandons the trading plan, increases position sizes, and lowers entry standards — compounding losses rather than recovering them. Revenge trading is one of the most destructive behavioural patterns and is responsible for turning manageable losses into account-threatening drawdowns.