Risk management · Intermediate

Risk/Reward Ratios

Risk/reward is half of an equation, and the half on its own tells you nothing about whether a strategy makes money.

Last reviewed 15 September 2026 by the MarketPro research desk · Editorial policy

In short

A risk/reward ratio compares the distance from entry to stop against the distance from entry to target, so risking 25 pips to make 50 is 1:2. The break-even proportion of winners for a given ratio is 1 / (1 + R), meaning 1:1 needs more than half of trades to reach target, 1:2 needs more than a third, and 1:3 needs more than a quarter, before costs.

What to remember

The break-even formula is 1 / (1 + R). A 1:2 trade needs more than 33.3% of trades to reach target, before spread and commission.
A high proportion of winners loses money if the rare losses are large. A high ratio loses money if the target is rarely reached.
Expectancy is measured, not designed. It comes from a sample of trades you actually took, not from the plan you wrote.
Stretching a target past structure to improve the ratio usually lowers completion by more than the ratio gains.

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What the ratio actually measures

Risk/reward compares the distance from your entry to your stop against the distance from your entry to your target. Risk 25 pips to make 50 and you have a 1:2 trade. Risk 40 to make 40 and you have 1:1. Most traders eventually stop talking in pips and start talking in R, where one R is the amount risked on that trade: a winner that reached twice the stop distance is +2R, a full loss is -1R, and a trade closed early for half the risk is +0.5R.

The reason R is useful is that it makes trades comparable. A 30-pip winner on EUR/USD and a 200-pip winner on GBP/JPY might both be +2R, and for the purposes of judging your own decisions they are the same trade.

The ratio is only half of the equation

A risk/reward ratio on its own tells you nothing about whether a strategy makes money. It has to be paired with how often the target is actually reached. The break-even proportion of winners for a given ratio is 1 / (1 + R):

Risk/reward	Proportion of winners needed to break even
1:0.5	66.7%
1:1	50%
1:2	33.3%
1:3	25%
1:5	16.7%

Those are break-even figures before costs. Spread, commission and swap all push the real threshold higher, and on a short-target strategy the spread can be a meaningful fraction of the target itself.

Read the table in both directions. A strategy that is right nine times out of ten still loses money if the rare loss is five times the size of a typical win. A strategy targeting 1:5 still loses money if the target is reached less than one time in six. Neither number means anything without the other.

Expectancy is the number that matters

Combine them and you get expectancy, the average result per trade:

Expectancy = (proportion of winners x average win) minus (proportion of losers x average loss)

Say your journal shows 40 trades: 16 winners averaging +2.1R and 24 losers averaging -0.95R. Expectancy is (0.4 x 2.1) minus (0.6 x 0.95) = 0.84 minus 0.57 = +0.27R per trade. Positive, which is what you want, and modest, which is what real numbers look like. At 1% risk per trade that is about 0.27% of the account per trade before costs, and the variance around it is wide enough that forty trades is barely a hint rather than proof.

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Costs belong in that calculation and are usually left out. If a typical trade risks 25 pips and the spread is 1.2 pips, you are paying roughly 0.05R in spread on every trade before anything else happens. Over 200 trades that is 10R, which on a modest edge is most of the year. Scalping strategies with 8-pip stops pay 0.15R per trade in the same conditions, which is why cost sensitivity rises sharply as the stop shrinks. The pip calculator turns those fractions into the currency your account is denominated in.

The practical implication is that expectancy is measured, not designed. You cannot decide your strategy has positive expectancy, you can only find out from a sample of trades you actually took. That is what a disciplined risk process and an honest journal are for.

How the ratio gets faked

Stretching the target. Pushing a target beyond a major resistance level to claim 1:4 does not improve the strategy. It lowers how often the target is reached, usually by more than the ratio improves. The target must be justified by structure, not chosen to make the ratio look respectable.
Squeezing the stop. The mirror image, and worse. Tightening the stop inside the noise improves the ratio on paper and destroys it in practice, because most of those trades now end at -1R for reasons unrelated to the idea.
Measuring the planned ratio, not the realised one. If you routinely close winners at +0.8R and let losers run to -1.2R, your planned 1:2 system is a 1:0.67 system. Only the realised numbers count.
Judging on too few trades. Thirty to fifty trades is the minimum before the numbers mean much, and even then a single outlier moves the average noticeably.
Ignoring partial exits. If you close half at +1R and let the rest run to +3R, the trade is +2R, not +3R. Journals that record the best level reached rather than the money actually banked flatter the strategy badly.

What to do with this

Before every entry, mark the stop from structure and the target from structure, then look at the ratio that results. If it is poor, that is information: the trade may simply be in a bad location, and skipping it costs nothing. Do not fix a poor ratio by moving a level. Fix it by waiting for a better entry, which is usually a pullback closer to the invalidation point.

Then track the realised R of every closed trade. Over time, that column tells you more about your trading than any indicator will. The profit calculator converts levels into cash before you commit, and the position size calculator turns the stop distance into the lot size that makes 1R mean what you intended.

One more habit is worth adopting early: record the ratio you planned and the ratio you realised, side by side, on every trade. The gap between those two columns is a direct measure of your execution, and it is usually the fastest thing to fix in a struggling strategy. A system designed at 1:2 that realises 1:1.1 does not need a new indicator. It needs the trader to stop closing winners at the first sign of a pullback.

Stop asking how often you are right. Start asking what your average R is, and whether the size you are using lets you keep collecting the sample.

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Written and reviewed by the MarketPro research desk

MarketPro is a trading-signal and trading-education app operated by Harajuku Holdings LTD (Cyprus). Our signal desk publishes and tracks every trade idea in-app, and every page here is checked against the app's live behaviour before publishing. Last reviewed 15 September 2026. How we produce signals and content · About MarketPro

FAQ

Risk/Reward Ratios: questions

What is a good risk/reward ratio for forex?

There is no universally correct figure, because the ratio only makes sense alongside how often your target is actually reached. Many discretionary strategies aim for 1:1.5 to 1:3 because those ratios tolerate a realistic proportion of losses. The test is whether your realised expectancy over thirty or more trades is positive, not whether the planned ratio looks impressive.

How do I calculate expectancy?

Expectancy is the proportion of winners multiplied by the average win, minus the proportion of losers multiplied by the average loss, with wins and losses expressed in R. Sixteen winners averaging +2.1R out of forty trades, against twenty-four losers averaging -0.95R, gives (0.4 x 2.1) - (0.6 x 0.95) = +0.27R per trade. Positive expectancy means the average trade gains, not that any single trade will.

Should I take a trade with a 1:1 risk/reward ratio?

It depends entirely on how often that setup reaches its target and what it costs to trade. A 1:1 strategy needs more than half its trades to win once spread and commission are counted, which is achievable for some mean-reversion approaches and unrealistic for most breakout ones. Judge it on your own recorded results rather than on the ratio alone.

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