Profit Factor — P&L
Gross profit / gross loss in account currency. The standard Profit Factor. Affected by position sizing. >1 = net profitable.
- Computed from
- Trades list
- Scope
- Single report
- Range
- ≥ 0
- Direction
- Higher is better
Profit factor is the simplest honest summary of a trading system: how many dollars it won for every dollar it lost. It's the total of all your winning trades (gross profit) divided by the total of all your losing trades (gross loss). Above 1 means the wins outweigh the losses; below 1 means the system bleeds. ("Gross" here means summed across trades — all winners vs all losers — not "before costs"; each trade is already net of fees.)
How it's calculated
Profit Factor = Σ(winning trades) / |Σ(losing trades)|
- Σ(winning trades)
- gross profit — sum of all positive net P&L
- Σ(losing trades)
- gross loss — sum of all negative net P&L, with the minus sign dropped so one can be divided by the other
The dollar version above is all most people need. The three blocks below cover the sizing-agnostic versions — skip them if you're just getting started.
On the P&L axis this is the classic profit factor in account currency — gross winning dollars over gross losing dollars. It is affected by position sizing: a few oversized winners inflate it.
What it tells you
| Value | Reading | Notes |
|---|---|---|
| < 1.0 | Losing | Losses exceed wins — not viable. |
| 1.0 – 1.3 | Marginal | A thin edge, easily erased by costs. |
| 1.3 – 2.0 | Workable | A real, tradeable edge. |
| > 2.0 | Strong | Wins comfortably dominate losses. |
Worked example
Over 200 trades the winners sum to +$16,000 and the losers to −$10,000:
Profit Factor = 16000 / 10000 = 1.6
The system returned $1.60 for every $1.00 it gave back — a workable edge.
Pitfalls
- A backtest profit factor flatters live results. Costs hit the loss side hardest — every trade pays spread/commission, shrinking winners and enlarging losers — so a strategy showing 1.8 on historical data can come in near 1.2, or below 1, once real spread, slippage and fills apply. Trust it only on data that already includes realistic execution costs, and treat anything under ~1.5 as fragile. The tighter the average trade (scalping, high-frequency), the bigger the gap.
- One trade can dominate it. A single huge winner can lift profit factor above 2 while the system is otherwise mediocre. Check profit concentration (top-1% share).
- One number, one regime. It needs a decent sample (rough rule: 100+ trades) and collapses regime detail — compute it per month and a "1.6 system" can swing from 3.0 to 0.7. It also says nothing about how much you make per trade or per year (1.6 on 50 trades/yr ≠ 1.6 on 5,000) — pair it with expectancy.
- Sizing flatters the dollar version. Bet big on winners, small on losers, and the $-based figure rises without any real edge. Use the Return or pips% version to neutralize sizing.
- Undefined with no losses. A record with zero losing trades has an infinite profit factor — almost always a sign of too few trades, not a perfect system.
Profit factor vs payoff ratio vs win rate
They're three views of the same trade distribution:
| Metric | Question it answers |
|---|---|
| Win rate | how often do I win? |
| Payoff ratio | how big is a win vs a loss? |
| Profit factor | the two combined — do total wins beat total losses? |
You can win only 40% of the time and still post a profit factor of 2, if the wins are large enough.