The loss ratio formula in trading answers one question: for every dollar your winning trades made, how much did your losing trades give back? It is gross loss divided by gross profit. Under 1.0, the strategy made money over the sample. Over 1.0, it lost.
That is the whole formula. The useful part is everything around it — which trades go in, why fees belong on the row, how it relates to profit factor and win rate, and why the number only means something per setup, not per account.
If you came for the insurance metric (claims plus adjustment expenses over earned premiums), that is a different ratio with the same name — the insurance loss ratio on Wikipedia covers it. This page is about trading.
The trading loss ratio formula
Loss ratio = gross loss ÷ gross profit
- Gross loss — the sum of every losing trade, as a positive number, after commissions and fees.
- Gross profit — the sum of every winning trade, also net of fees.
- Scratches (closed at exactly zero after costs) belong in neither total; they still count toward your trade count elsewhere.
Read it like this:
| Loss ratio | What it means for the sample |
|---|---|
| Below 0.5 | Losers gave back less than half of what winners made |
| 0.5 – 0.8 | Profitable, with room for costs and a bad month |
| 0.8 – 1.0 | Barely profitable — one slipped stop flips it |
| 1.0 | Break-even |
| Above 1.0 | Losing strategy for this period |
There is no universal “good” number. A trend follower can live at 0.8 for a long time; a scalper at 0.8 is usually one fee change away from 1.0. Compare your number to your previous samples of the same setup, not to someone else’s screenshot.
Worked example: ten trades
Here is a ten-trade log, already net of commissions:
| Trade | Result | Win / loss |
|---|---|---|
| 1 | +$150 | Win |
| 2 | −$75 | Loss |
| 3 | +$200 | Win |
| 4 | −$100 | Loss |
| 5 | −$50 | Loss |
| 6 | +$90 | Win |
| 7 | −$120 | Loss |
| 8 | +$250 | Win |
| 9 | −$60 | Loss |
| 10 | −$80 | Loss |
- Gross profit: $150 + $200 + $90 + $250 = $690
- Gross loss: $75 + $100 + $50 + $120 + $60 + $80 = $485
- Loss ratio: $485 ÷ $690 = 0.70
For every dollar this strategy made, losing trades gave back 70 cents. Net P&L is $205, or $20.50 per trade.
Notice the win rate: only 4 of 10 trades won (40%). The strategy is still profitable because the average win ($172.50) is more than twice the average loss ($80.83). That is why the loss ratio cannot be read alone — more on that below. The arithmetic for net results is in calculating trading profit.
Loss ratio vs profit factor vs win rate
Three numbers get mixed up constantly. They are related, but they answer different questions.
| Metric | Formula | Question it answers | Example (above) |
|---|---|---|---|
| Loss ratio | Gross loss ÷ gross profit | How much do losers give back per $1 won? | 0.70 |
| Profit factor | Gross profit ÷ gross loss | How many dollars won per $1 lost? | 1.42 |
| Win rate | Winning trades ÷ total trades | How often do I win? | 40% |
| Payoff ratio | Average win ÷ average loss | How big are wins vs losses? | 2.13 |
| Expectancy | Net P&L ÷ number of trades | What does one more trade earn on average? | $20.50 |
The loss ratio is the inverse of profit factor. A profit factor of 1.42 and a loss ratio of 0.70 are the same fact written two ways. Pick one and stick with it in your reviews; most journals and backtest reports show profit factor, so it is easier to compare. The free win rate and expectancy calculator returns profit factor and expectancy from the same inputs.
Two other things people call “loss ratio”
- Loss rate — losing trades ÷ total trades. In the example, 60%. It is simply 1 − win rate and says nothing about size.
- Win/loss ratio — sometimes the count of wins to losses (4:6), sometimes average win to average loss (2.13). Ask which one before you compare numbers with anyone.
When someone quotes a “loss ratio,” check which of the three they mean. They are not interchangeable.
How win rate and loss ratio work together
A loss ratio is the result of two inputs: how often you lose and how big the losses are compared to the wins.
- Low win rate, low loss ratio — classic trend or breakout profile. You lose often, but small. Fine, as long as the stops stay small.
- High win rate, loss ratio near 1.0 — common for mean reversion and scalping. Many small wins, occasional large losses. Healthy only if the large losses are planned stops, not moved ones.
- Low win rate, loss ratio above 1.0 — losses are both frequent and large. Stop trading the setup and review the stops before anything else.
The fastest way to wreck a good loss ratio is one oversized loser. A single trade that ran to 5R because the stop was moved can erase a month of 1R wins. That is a risk management problem, not a strategy problem — and the loss ratio is often where it first shows up.
Calculate it per setup, not per account
An account-level loss ratio blends everything you trade. A profitable breakout setup can hide a losing afternoon fade, and the blended 0.85 looks “fine” while one setup quietly bleeds.
Calculate it per tag instead:
- Tag every trade with one setup name. Same string every time —
ORB, not “opening range” one day and “OR break” the next. The tagging approach is in best trading strategies. - Wait for a sample. Roughly 30 trades in a single tag before you trust the ratio. Below that, one outlier moves it by 0.2 or more.
- Use net numbers. Fees and slippage go on the row. Scalping and high-frequency tags die from costs first, and a gross loss ratio hides it.
- Look at it next to plan-followed. A loss ratio of 1.1 with stops that matched the plan is information about the setup. A loss ratio of 1.1 with four moved stops is information about you.
A spreadsheet can do this with a pivot table by tag — see building a pivot table for trade analysis. A journal does it without the formulas.
How often to check your loss ratio
Match the review to how many trades you take:
- Day traders: weekly, per tag. Enough trades accumulate to see a change within a month.
- Swing traders: monthly. A week of four trades will swing the ratio wildly.
- Position traders: quarterly, and treat it as a rough signal until the sample grows.
Whatever the cadence, write one decision after each review: keep, pause, or change one thing about one setup. A ratio you check but never act on is a number, not a process. The weekly habit is covered in why every trader needs a trading journal.
Frequently Asked Questions
What is a good loss ratio in trading?
Anything below 1.0 means the sample was profitable. Many traders treat 0.5–0.8 as a comfortable range because it leaves room for costs and a bad month, but there is no universal benchmark — compare each setup with its own history.
Is loss ratio the same as profit factor?
No, but they carry the same information. Loss ratio is gross loss ÷ gross profit; profit factor is gross profit ÷ gross loss. A loss ratio of 0.5 equals a profit factor of 2.0.
Can a loss ratio be above 100%?
Yes. A loss ratio above 1.0 (100%) means losing trades cost more than winning trades earned during the period. The strategy lost money for that sample.
Should I include commissions in the loss ratio?
Yes. Calculate gross profit and gross loss from net trade results. Leaving fees out flatters active strategies and can turn a real 1.05 into a reported 0.95.
How is the trading loss ratio different from the insurance loss ratio?
The insurance loss ratio compares claims and adjustment expenses with earned premiums. The trading loss ratio compares losing trades with winning trades. Same name, different inputs.
Bottom line
The loss ratio formula for traders is gross loss ÷ gross profit, net of fees. Below 1.0 the sample made money; above it, it lost. It is the mirror image of profit factor, so pick one for your reviews, and always read it next to win rate and average win vs average loss. Most of all, calculate it per setup with at least ~30 trades — an account-wide number hides the setup that is costing you.
When you want profit factor, win rate and expectancy per tag without maintaining formulas, open the journal and tag your next trades.
This article is for education, not investment advice. Past results do not guarantee future performance.