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Metrics

R-Multiple — Risk-Normalized Returns

One number that lets you compare a 50€ win on a 50€ stop to a 5,000€ win on a 5,000€ stop apples-to-apples. R = trade outcome ÷ initial risk.

What it is

R-Multiple is a trade's outcome divided by the risk you took at entry — the distance from your fill to your stop, multiplied by your position size. It strips out the absolute money figure so two trades on different account sizes, different symbols, different volatilities can sit on the same scale.

+2R = you made twice your risk. −1R = stopped out at the planned distance. +0R = breakeven. +0.5R = you took half the planned target. The unit is your own predetermined risk, not a market-defined ratio — that's the whole point. It's the most personal of the trade-quality metrics because the R you call yours is the one you set when you placed the stop.

Formula
Long: R = (Exit − Entry) / |Entry − Stop|
Short: R = (Entry − Exit) / |Stop − Entry|
Example

Buy EURUSD at 1.1000, stop at 1.0950 (50 pips risk), target 1.1100. You exit at 1.1080.

ResultR = (1.1080 − 1.1000) / 0.0050 = 80 / 50 = +1.6R
How to read it

How to read your R distribution: - Average R per trade > 0 — your strategy has positive expectancy in risk-normalized units. The level above zero is roughly your edge. - Average R between −0.2 and +0.1 — you're hovering around breakeven. Win-rate alone won't tell you which side; R does. - A few +5R or +10R outliers in a sea of small Rs — letting winners run. Healthy if your win rate is on the lower side; suspect if your win rate is also high (you're banking small + tail-risking large). - No outliers above +2R — you're scalping out targets. Fine if your win-rate compensates; problematic if win-rate is < 50%. - Big cluster at exactly −1R — discipline is intact, stops are honored. - Cluster between −1R and −2R — stops are slipping. Either widening manually mid-trade or weekend gaps you didn't price in.

Where TradeOnyx uses it

TradeOnyx computes R automatically for every trade where the stop price is recorded at entry. The Trades-tab list carries an R column you can sort or filter by — "show me every trade worse than −1R" surfaces the discipline leaks immediately. Aggregate R per playbook tells you which strategy actually produces the right shape of distribution, not just which generates the most wins.

The Expectancy KPI tile in the Overview is closely related: Expectancy = average R × number of trades, in money. R is the per-trade unit, Expectancy is the rolled-up book. If you read the Expectancy article and wondered "how do I see the unit-economics for one trade in isolation?" — R is that view.

A practical loop: at the end of every week, sort the Trades tab by R ascending. The bottom three trades are your worst-R losses. Open each, read the journal note, and ask: same setup, same time, same symbol? That's the leak. The R framing keeps the comparison fair across trades of vastly different absolute sizes.

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