One of the more consistent patterns in trading psychology research is what happens to behavior, not just outcomes, after a losing streak. The general finding across behavioral finance literature is that losses tend to change how traders act on their next few decisions, often in ways that increase risk rather than reduce it.
The general pattern
After a string of losses, many traders show two related tendencies: they increase position size, and they increase how frequently they trade. Both moves are consistent with an attempt to recover losses quickly rather than a considered reassessment of the strategy itself.
This lines up with loss aversion, a well documented behavioral tendency where losses are felt more intensely than equivalent gains. The discomfort of an open loss creates pressure to resolve it fast, and increasing size or frequency is often the path of least resistance in the moment.
An illustrative example
The figures below are illustrative only, meant to demonstrate how this pattern tends to look in practice. They are not drawn from a specific verified study and should not be read as measured statistics.
| Period | Illustrative average position size | Illustrative trades per day |
|---|---|---|
| Before losing streak | Baseline | Baseline |
| During losing streak | Above baseline | Above baseline |
| After a cooldown period | Near baseline | Near baseline |
The pattern this table is meant to illustrate is directional: size and frequency tend to rise during a losing streak and settle back down after a deliberate pause, not the specific numbers themselves.
Why this matters more than win rate
Win rate gets most of the attention, but it does not capture what is happening to risk per trade. A trader can have an unchanged win rate while quietly increasing how much is at stake on each trade during a rough stretch, which changes the risk profile of the account even if the strategy itself has not changed at all.
Tracking position size and trade frequency around your own losing streaks is a more direct way to catch this pattern than watching win rate alone, since the shift usually shows up in behavior well before it shows up in results.
