Who this is for — Anyone underestimating one «big» loss. Average loss reveals whether defense holds or negative outliers poison the system.
Average loss is the mean of closed losing trades: sum of losses ÷ number of losses. In R, it should stay ≤ 1R if you respect risk per trade and stops.
In plain terms — What it costs on average to be wrong — the «ticket price» of your edge.
Control thresholds
| Average loss (R) | Diagnosis |
|---|---|
| ≤ 1.0R | Defense ok |
| 1.0–1.3R | Occasional slippage or widened stops |
| > 1.5R | Removed stops, revenge, averaging |
Typical causes: no stop, revenge, illiquid news, size after loss.
Recovery math
| Capital loss | Gain to break even |
|---|---|
| −10% | +11.1% |
| −25% | +33.3% |
| −50% | +100% |
Containing average loss protects more than raising average win.
Typical mistake — One −10R in 50 trades — average loss poisoned for months; remove outliers, do not ignore them.
Example — 20 losses: 18 at −1R, 2 at −1.2R (slippage) → average loss −1.02R. Ok.
Summary card
- Target: ≤ 1R on sample ≥ 30 losses.
- Review: tag negative outliers.
- Pair: average win → payoff.
Silver path — Metrics module. Index: Silver path.