Overconfidence

Overconfidence - An overconfident trader overestimates their skill or information, often trading more frequently and taking larger risks. In automation, overconfidence might appear as excessive parameter tuning or believing a model will never fail. Overconfident investors “trade excessively, resulting in higher transaction costs and poor performance”. They may ignore uncertainty in backtests and underestimate risk. Bots can mitigate this by incorporating conservative risk settings (e.g. strict maximum drawdown) and validation (e.g. walk-forward testing). The literature notes that overconfident traders often feel more skilled than average, which leads to suboptimal choices and reliance on intuition over data.