Risk/reward ratio and R-multiples, explained

What R is

When you enter a trade with a stop, you have decided the most you are willing to lose. That amount — in price, in pips, in money, it does not matter which — is 1R. Everything that happens afterwards is measured against it. If the stop is hit, the result is −1R. If you take profit at twice the distance of the stop, the result is +2R. A trade closed for a small gain might be +0.3R; a trade you moved the stop on and gave back might be −1.4R.

Because R is defined by the risk you chose, it makes trades of different sizes comparable. A $40 win on a $20 risk and a $4,000 win on a $2,000 risk are both +2R: same decision quality, different bet size. Journals that measure only in money confuse the two constantly.

Entry 2,340.00   Stop 2,336.00   → 1R = 4.00 points
Target 2,350.00  → reward 10.00 points → ratio 1 : 2.5
Exit at 2,347.20 → (2,347.20 − 2,340.00) ÷ 4.00 = +1.8R
Stopped out      → −1R (or worse, if price gapped through the stop)

The ratio and the win rate are one number, not two

A 1:3 risk-to-reward ratio sounds obviously better than 1:1. It is not — it is differently good. A trader taking 1:3 trades can be wrong three times out of four and still break even; a trader taking 1:1 trades must be right more than half the time. Neither is superior; each demands a different win rate, and the market decides which you can actually achieve on a given setup.

Break-even win rate = 1 ÷ (1 + ratio). The risk/reward calculator does this for any entry, stop and target, and shows the expectancy at whatever win rate you type in.

Expectancy: the number that actually pays

Expectancy is what you make, on average, per trade, in R. The formula is simple: (win rate × average winning R) − (loss rate × average losing R). A system that wins 40% of the time with average wins of +2.2R and average losses of −1.0R has an expectancy of 0.4 × 2.2 − 0.6 × 1.0 = +0.28R per trade. Over a hundred trades at 1% risk, that is roughly +28% before costs — from a strategy that loses more often than it wins.

Notice what expectancy depends on: not the planned ratio, but the achieved average win and average loss. Traders who plan 1:3 and routinely take profit at +1.2R, or who move stops and average −1.4R on losers, have a very different expectancy from the one on paper. This gap is one of the first things a journal that measures in R will show you.

Planned versus achieved

Look at any month of trades and compute two ratios: the average planned reward-to-risk (target distance ÷ stop distance at entry) and the average achieved R on winners. For most discretionary traders the second is much lower than the first — profits taken early, targets moved closer as price approaches. That is not necessarily wrong; sometimes early exits are the right call. But you cannot know until you test the alternative.

"Should I have held?" is an empirical question

Here is the question every trader argues with themselves about: if I had just held to 2R or 3R every time, would I have made more? People answer it from memory, which mostly recalls the trades that ran. It can be answered exactly instead: for each trade, take the entry and the stop you had at fill, then walk the real price path minute by minute and see which is hit first — the fixed target or the stop. Do that for every target level and you get a table: at 1R, 1.5R, 2R, 3R… win rate, average R, total R, profit factor, drawdown.

Practical rules that follow from the arithmetic

• Decide the stop first, then the size, then whether the target is far enough to justify the trade. A stop placed to fit a desired size is not a stop.
• Track average winning R and average losing R separately. A system can be saved or ruined by either one.
• Distrust any advice that names a ratio without a win rate. "Always take 1:3" is only good advice for setups that win at least 25% of the time.
• Test your management. If your achieved winners average +1.1R on trades planned at 1:3, run the simulation before assuming that discipline would fix it — sometimes the early exit is the edge.