Execution Discipline
The gap between the plan and what actually gets done. A strategy followed inconsistently is a different strategy from the one that was tested, usually a worse one, and the deviations cluster in exactly the moments that matter most.
Loss Aversion
Losses feel roughly twice as painful as equivalent gains feel good. The practical result is holding losers, hoping to exit at breakeven, while taking profits early to lock in the good feeling. That is the precise inverse of what positive-expectancy trading requires.
Revenge Trading
Increasing size after a loss to win it back quickly. It converts a normal losing trade into an account-threatening one, and it is the single most common way otherwise competent traders are removed from the market.
Drawdown Tolerance
How much decline you can sit through without intervening. This is a personal limit, not a technical one, and it should be decided before deploying rather than discovered during. A strategy with a historical 40% drawdown is unusable by someone who will stop it at 15%.
Overtrading
Trading more than the edge justifies, usually from boredom or a need to feel active. Each unnecessary trade pays fees and slippage against a nonexistent edge, and the cumulative cost is often larger than the losses from the trades that were actually wrong.
What Automation Fixes
Automation reliably removes in-the-moment execution failures: hesitation, early exits, revenge sizing, missed entries. It cannot decide your risk tolerance, and it cannot stop you switching a strategy off at the worst moment. The decision to abandon a system during a drawdown is still a human one, and it is where most automated traders lose.