Profit factor is gross profit divided by gross loss. If a strategy earned $6,000 from all its winning trades and lost $4,000 across all its losing trades, the profit factor is 6,000 / 4,000 = 1.5. Anything above 1.0 means the strategy made more than it gave back. Below 1.0 means it lost money.
The profit factor formula
Profit factor = Gross profit / Gross loss
- Gross profit - the sum of every winning trade, added together as positive numbers.
- Gross loss - the sum of every losing trade, added together as a positive number.
Notice that profit factor uses totals, not averages. This makes it a whole-strategy efficiency score: for every unit of money the strategy lost, how many units did it make back?
How to read the number
- Below 1.0 - the strategy is a net loser. Do not trade it as written.
- 1.0 to 1.2 - marginal. It may not survive spread, slippage, and psychology.
- 1.3 to 1.5 - a solid, realistic edge for many discretionary strategies.
- 1.5 to 2.5 - strong, if it holds across a large and varied sample.
- Above 3.0 - be suspicious. On historical data this often means over-fitting or too few trades.
Why sample size changes everything
A 2.8 profit factor over 12 trades is far less convincing than a 1.45 profit factor over 300 trades across trending and ranging markets. Small samples let a single outlier winner inflate gross profit and hand you a beautiful ratio that vanishes the moment conditions change. Always read profit factor beside the number of trades and the range of market conditions in the test. This is the same discipline that every backtest metric demands.
Important: remove your single best trade and recalculate. If the profit factor collapses from 1.9 to 1.1, the strategy is leaning on one lucky outlier rather than a repeatable edge. Robust strategies barely flinch when you delete their biggest winner.
Profit factor vs expectancy
These two metrics answer different questions and are strongest together. Profit factor is a ratio describing the whole sample's efficiency. Expectancy is the average result of one trade. A strategy can have an attractive profit factor but a tiny expectancy if it takes very few trades, which limits how much money the edge can actually produce. Read both: profit factor tells you the edge is efficient, expectancy tells you what each trade is worth, and trade count tells you how often you get to use it.
Where profit factor can mislead you
- Too few trades: the ratio is dominated by chance.
- One market regime: a strong figure from a single trending year can fail in a range.
- Skipped losers: if the test quietly ignored valid losing setups, gross loss is understated.
- No costs: a ratio built on clean prices ignores spread and commission that every real trade pays.
Reading profit factor in your own tests
You do not need a spreadsheet to track this. When you replay charts and log trades in a backtesting simulator, the session report calculates gross profit, gross loss, and profit factor automatically, alongside win rate, expectancy, and drawdown. That lets you judge efficiency the moment a test finishes and decide whether the strategy is ready to forward test or needs another round of refinement.
Profit factor FAQ
What is a good profit factor?
Above 1.0 means the strategy made more than it lost. Many traders treat 1.3 to 1.5 as solid and 1.75 or higher as strong, but a high figure on a small sample is usually luck rather than a durable edge.
What is the difference between profit factor and expectancy?
Profit factor is total winnings divided by total losses across the whole sample. Expectancy is the average profit or loss per single trade. One measures overall efficiency, the other measures the value of a typical trade.
Can profit factor be too high?
Yes. A figure above roughly 3 or 4 on historical data often signals over-optimization or too small a sample, and rarely survives forward testing.