A free R-multiple calculator built for India: punch in your entry, stop-loss and exit to get the R-multiple and risk:reward instantly. Works for long and short, equity and F&O.
Gross of charges. In India, STT + brokerage + GST + stamp reduce realised R — track net R automatically →
An R-multiple expresses a trade's outcome as a multiple of what you risked. Your initial risk — the distance from your entry price to your stop-loss — is defined as 1R. Every result is then measured in units of that risk, so a ₹2,000 win on ₹2,000 of risk (+1R) is directly comparable to a ₹10,000 win on ₹10,000 of risk (+1R). The rupee amounts are different; the quality of the decision is identical. That is the whole point of the R-multiple: it strips position size out of the equation so you can judge your trading on skill, not stake.
The concept was popularised by Van Tharp, but it has quietly become the common language of professional traders everywhere — from prop desks in Mumbai to swing traders working a Zerodha account from home. Once you start thinking in R, a ₹5,000 loss is no longer "a big loss" or "a small loss" in the abstract; it is either a clean −1R (you were stopped out exactly where you planned) or an ugly −3R (you let it run against you). The number tells you instantly whether your process held up, regardless of how the rupees landed.
For a long trade: R = (exit − entry) ÷ (entry − stop)
For a short trade: R = (entry − exit) ÷ (stop − entry)
The denominator — the gap between entry and stop — is your 1R risk per share. The numerator is your actual reward per share. Divide one by the other and you have your R-multiple. A positive number means the trade made money relative to risk; a negative number means it lost. The calculator above auto-detects direction: if your stop-loss sits below your entry it treats the trade as long, and if it sits above entry it treats it as short, so you never have to pick.
Worked example. You buy a stock at ₹1,500 and place your stop at ₹1,470. Your 1R risk is ₹30 per share. You exit at ₹1,560, a ₹60 gain per share. R = 60 ÷ 30 = +2R — a clean two-R winner. Now suppose the same trade had gone wrong and you were stopped at ₹1,470: that is exactly −1R, the loss you signed up for. The discipline of knowing your R before you enter is what separates planned trading from hoping.
There are two moments worth measuring. Your planned R (often called the risk:reward ratio) is calculated before you enter, using your target instead of your exit: it tells you whether the trade is even worth taking. Your realised R is calculated after you close, using the price you actually got out at. The gap between the two is where most edge is won or lost — traders who consistently realise far less than they planned are usually exiting winners too early or moving stops on losers. Logging both numbers for every trade is the fastest way to spot that leak, and it is one of the first things a structured trading journal will surface for you.
There is no universal "good" number, but there is a useful anchor: most consistently profitable traders aim for a planned reward of at least 1.5R to 2R per trade. The reason is mathematical, not motivational. If your average winner is 2R and your average loser is 1R, you can be wrong more often than you are right and still make money. A trader who wins just 40% of the time at an average of +2R per win and −1R per loss still comes out comfortably ahead. Chasing a 90% win rate with tiny targets and wide stops, by contrast, is how accounts quietly bleed out — one −5R disaster erases a long streak of +0.5R scalps.
A word of warning on the headline ratio, though: a 5R setup on paper is worthless if you never actually reach the target. This is why planned R should always be sanity-checked against your historical realised R. If your records show you rarely capture more than 2R in practice, planning trades around 4R targets is wishful thinking, not strategy. Pick a reward target you can genuinely hit given your instrument, timeframe and temperament, then let the data — not your hopes — tell you whether to stretch it. Honest measurement beats an ambitious spreadsheet every single time.
Because a single number — expectancy — decides whether you make money over the long run: (win% × avg win R) − (loss% × avg loss R). A positive expectancy means you have a genuine statistical edge; a negative one means that, however good individual trades feel, the system is bleeding. You cannot compute expectancy honestly in rupees, because position sizes vary trade to trade and a few oversized bets will distort the average. In R terms, every trade carries equal weight, so the expectancy figure is clean. This is the metric that lets you answer the only question that matters: if I keep trading exactly like this, do I make money?
R-multiples also fix the psychology. When you measure in rupees, a string of small wins followed by one large loss feels like bad luck. When you measure in R, the same sequence shows up as +0.5R, +0.5R, +0.5R, −4R — and the problem is obvious: your risk management, not your entries. Trading in R turns vague frustration into a specific, fixable behaviour, which is exactly the kind of pattern that destroys accounts through revenge trading and oversized positions.
The R-multiple works just as well for derivatives, with one caveat: define your 1R as the premium (or points) you are willing to lose, not the notional value of the contract. For a long option, 1R is the distance from your entry premium to the premium at which you will cut the position; reward is measured the same way. Because options decay and gap, realised R for F&O traders often drifts further from planned R than it does in equity — which makes disciplined logging even more important. If you trade options, our guide to building an options trading journal in India walks through the extra fields worth capturing.
This calculator uses price levels, so it reports the gross R-multiple. In India, the real cost of trading — STT, brokerage, exchange transaction charges, GST, SEBI fees and stamp duty — quietly reduces the R you actually keep, and those costs bite hardest on intraday and short-term traders who turn over capital frequently. A planned +2R trade can realise meaningfully less once charges are netted out, especially on small per-share moves. To see your net-of-cost R across every trade, you need a journal that imports your broker's charge breakdown automatically rather than asking you to estimate it.
That is exactly what TradeDiary does. It pulls your tradebook straight from Zerodha, Upstox, Kotak and other brokers, computes R, win rate and expectancy for every fill, bakes in real charges, and lays it all out on a colour-coded calendar and analytics dashboard. The R-multiple you calculate here is a snapshot of one trade; a journal turns that snapshot into the story of your entire edge. For the full picture of how to build that habit, start with our complete trading journal India guide.
An R-multiple expresses a trade's result as a multiple of the amount you risked. 1R is your initial risk (entry minus stop-loss). Risk ₹2,000 and make ₹6,000 and that's a +3R trade. R-multiples let you compare trades of different sizes on equal footing.
Reward per unit ÷ risk per unit. Long: (exit − entry) ÷ (entry − stop). Short: (entry − exit) ÷ (stop − entry). Positive is a win in R terms; negative is a loss.
Many profitable traders target a planned reward of at least 1.5R–2R, because it keeps them profitable even below a 50% win rate. What matters more than any single trade is expectancy: (win% × avg win R) − (loss% × avg loss R).
This calculator uses price levels, so it shows gross R. In India, STT, brokerage, exchange fees, GST and stamp duty reduce realised R. For net-of-cost R across all your trades, use a journal that imports broker charges automatically.
This tool computes one trade. TradeDiary computes R, expectancy and win rate across every trade — net of Indian charges — straight from your broker.
Start Free — No Card →