Risk/Reward Ratio Calculator
Compute risk/reward ratio from entry, stop-loss, and take-profit prices. Get break-even win rate, position size, and max loss based on account size and risk percentage.
Risk/Reward Ratio Calculator
How to use the Risk/Reward Ratio Calculator
Set direction + the three prices
Pick LONG (you expect price to go up) or SHORT (you expect price to go down). Enter your entry price (where you'll open the trade), stop-loss price (where you'll exit at a loss if wrong), and take-profit price (where you'll exit at a profit if right). For long trades: stop must be BELOW entry and target ABOVE entry. For short trades: target BELOW entry and stop ABOVE entry. These three numbers fully define the trade's risk/reward profile.
Read the risk/reward ratio
"1 : 3" means risking $1 to potentially make $3. Higher is better. 1:1 = breakeven trade, needs 50%+ win rate. 1:2 = needs 33% win rate to break even — most beginner-friendly setup. 1:3 = needs 25% win rate. 1:5+ = trend-following / breakout setups. The break-even win rate is the math: if your R:R is 1:2, you need to win at least 33% of trades to be profitable. Track your actual historical win rate to know if your R:R is sustainable.
Use position sizing — never skip this
Set your account size and the % you're willing to risk per trade (1-2% is the universal rule among serious traders). The calculator computes: max dollar loss, position size in dollars, and number of shares. Example: $10,000 account with 1% risk = max $100 loss per trade. If stop is $5 away from entry, max position = $100/$5 = 20 shares (worth $2000 at $100 entry). This sizing ensures no single trade can blow up your account.
Apply this before every trade
The discipline of pre-trade R:R calculation separates serious traders from gamblers. Use this calculator BEFORE entering any trade — never compute it after. If the R:R doesn't justify the risk (below 1:1.5 for most setups), skip the trade. Most professional traders reject 70-80% of potential setups for failing this filter. The hardest part of trading isn't finding setups — it's having the discipline to wait for ones with proper R:R.
Risk/reward — the math that separates traders from gamblers
The risk/reward ratio is the single most important pre-trade discipline in active trading. It quantifies, before you enter, what you stand to lose vs gain. The math is simple: distance from entry to stop = risk; distance from entry to target = reward; reward divided by risk = R:R. A 1:3 R:R means you can be wrong 75% of the time and still break even — the math allows for high error rates as long as the few wins are big enough. Conversely, a 1:0.5 R:R means you need to win 67% of trades just to avoid losing money — a punishingly high bar that virtually nobody sustains over time. The discipline of skipping trades that don't offer proper R:R is what separates traders from gamblers.
The expectancy formula — why R:R combines with win rate
Expectancy = (Win Rate × Average Win) − (Loss Rate × Average Loss). For a strategy to be profitable, expectancy must be positive. Two ways to achieve this: high win rate with small wins (most professional discretionary traders), or low win rate with big wins (trend-followers, breakout traders). Both work; both require the math to line up. The calculator's "break-even win rate" tells you the minimum hit rate needed for your specific R:R: 50% for 1:1 R:R, 33% for 1:2, 25% for 1:3, 20% for 1:4. Track your real win rate over 50+ trades; if you're below your break-even threshold, the strategy is losing money mathematically regardless of how it feels.
Risk/reward is the entry ticket; win rate is the actual experience. Don't take any trade where R:R requires a higher win rate than you've historically achieved. The math doesn't care about your conviction.
Position sizing — the multiplier you can't ignore
Even a winning strategy goes broke with bad position sizing. Risking 10% of your account on each trade means a 5-loss streak (statistically expected within 50 trades for a 50% win rate strategy) takes you down 41% — a devastating drawdown to recover from. Risking 1% means the same streak only costs 5% — easily recovered. The Kelly Criterion gives the mathematically optimal sizing (f* = (bp − q) / b, where b = R:R, p = win rate, q = 1−p), but it's brutal — at full Kelly, you'd risk 20%+ per trade. Almost all serious traders use "fractional Kelly" (¼ or ⅓ Kelly), which works out to 1-3% per trade for typical strategies. The 1-2% rule encoded in this calculator is the conservative standard taught at every prop trading firm.
The ASEAN trader's angle
Active trading across ASEAN has been democratised by zero-commission brokers (Tiger Brokers, Webull, Moomoo, Saxo Markets, Interactive Brokers, Phillip Securities). Singapore: the most developed retail trading scene, with strong forex (regulated by MAS) + crypto + equities pools. Malaysia / Indonesia / Philippines / Vietnam / Thailand: rapidly growing retail trading via mobile apps; meme-coin + meme-stock waves have hit the region. Regulatory considerations: leveraged trading is restricted in SG (max 1:20 forex for retail) and increasingly so across ASEAN; CFD platforms are scrutinised more heavily post-2020 retail loss waves. Tax treatment: capital gains are generally tax-free for individuals in Singapore (the most trader-friendly tax regime globally for retail). Malaysia + Indonesia tax frequent trading as business income. The math in this calculator is universal — R:R discipline works identically regardless of regulatory regime. The cultural emphasis in ASEAN trading communities (Telegram groups, Discord servers, Carousell + Lazada chat threads) often skews toward "win rate" psychology over R:R discipline; that's why so many retail traders fail. Mathematical discipline beats narrative conviction.
10 Things to Know About Risk/Reward
R:R = (target − entry) / (entry − stop). The mathematical core of every trade decision. Compute BEFORE entering, never after.
A 1:2 R:R needs only a 33% win rate to break even. Most retail traders chase 1:1 with 70% win rates — far harder.
The 1-2% rule: never risk more than 1-2% of your account on any single trade. Universal standard at prop trading firms.
The Kelly Criterion gives mathematically optimal position size: f* = (bp − q) / b. Full Kelly is too aggressive; use ¼ or ⅓ Kelly.
Most professional traders reject 70-80% of setups for failing the R:R filter. The hardest part isn't finding trades — it's having patience for good ones.
The expectancy formula: E = (Win% × Avg Win) − (Loss% × Avg Loss). Must be positive for the strategy to make money long-term.
A 5-loss streak is statistically expected within 50 trades at 50% win rate. Position sizing ensures it doesn't destroy the account.
Trend-following strategies often have 30-40% win rates with 1:3 to 1:5 R:R — mathematically profitable despite "losing more often than winning."
Risking 10% per trade means a 5-loss streak costs 41% of the account. Risking 1% means the same streak costs only 5%. Position size compounds dramatically.
Singapore's capital gains tax regime is among the most trader-friendly globally — most individual trading gains are tax-free, which is why retail forex/crypto trading is so popular.
Frequently Asked Questions
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Depends on your strategy and historical win rate. Universal benchmarks: 1:1 = bad, requires 50%+ win rate. 1:2 = standard, needs 33% win rate — most achievable for retail. 1:3 = strong, needs 25% win rate. 1:5+ = trend-following territory, allows for very low hit rates. Match your R:R to your real win rate. If your historical win rate is 40%, target 1:2+ R:R; if it's 30%, target 1:3+. Don't fool yourself about win rate — track 50+ real trades to get an honest number.
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Three common approaches. Volatility-based: place stop at 1-3× ATR (Average True Range) — adjusts to instrument's normal noise. Structure-based: place stop beyond a recent swing low (for longs) or swing high (for shorts) — protects against the move you're trading reversing. Percentage-based: fixed % away (e.g. 5% for swing trades) — simple but ignores instrument volatility. Most pros use volatility OR structure; pure percentage stops are too simplistic. The stop should be where, if hit, your trade thesis is invalidated.
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Targets are harder than stops because reward is uncertain. Common approaches: Fixed R:R multiple: target = entry + 2× (entry − stop). Simple and consistent. Structure-based: target the next major resistance (long) or support (short). Volatility-based: target = entry + N × ATR. Scaled-out: take profit on 50% at 1:1, 50% at 1:3 (banks gains, lets winners run). For beginners, fixed R:R (target = 2-3× stop distance) is simplest and most consistent. As experience grows, structure-based targets can capture larger moves.
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1% is the conservative standard taught at most prop firms. 2% is acceptable for experienced traders with proven edge. Above 2% gets risky: a 5-loss streak at 3% costs 14%; at 5% costs 23%. For backtest analysis with positive expectancy, you can quantify the optimal size via Kelly Criterion + drawdown tolerance. For real trading without years of statistical confidence in your edge, 1% is right. Bigger accounts can scale this DOWN further (0.5% on $1M+ accounts) since dollar risk gets large quickly.
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Forex + crypto: yes, the math is identical. Use price levels regardless of pair or symbol. Leverage doesn't change R:R math — but it changes effective position size. Be careful: 10× leverage means 1% account risk becomes 10× exposure, magnifying both wins and losses. Options: more complex — risk isn't just stop-distance. For long options, max loss = premium paid (R:R = (target − premium) / premium for ITM strategy). For spreads, R:R = max profit / max loss. This calculator works for simple stop/target trades; for options, use options-specific calculators that account for theta + delta.
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The mathematically optimal position size for maximising long-term geometric growth, given known win rate + R:R: f* = (bp − q) / b, where b = R:R, p = win rate, q = 1 − p. Example: 1:2 R:R + 50% win rate → f* = 25% per trade. Problem: full Kelly is too aggressive in practice — small estimation errors in win rate produce huge drawdowns. Most professionals use "fractional Kelly" (¼ or ⅓ of full Kelly), which approximates the 1-2% rule for typical R:R + win rate combos. For trading, the 1-2% rule of thumb is functionally similar to ¼-Kelly and much easier to apply.
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Yes — they're linked by expectancy math. Strategies cluster into archetypes: High win rate + low R:R (scalping, mean-reversion): 70-80% win rate with 1:1 R:R. Sensitive to losing streaks. Low win rate + high R:R (trend-following, breakout): 30-40% win rate with 1:3+ R:R. Long stretches of small losses, occasional big wins. Balanced: 50-60% win rate with 1:1.5-2 R:R. Most retail traders. Pick the archetype that fits your psychology — both can be profitable; neither is universally better.
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Material impact, especially on smaller R:R setups. The bid-ask spread + slippage typically costs 1-3 ticks per round-trip in liquid markets, more in illiquid ones. For a 10-tick risk + 20-tick reward (1:2 R:R), 2 ticks of spread/slippage effectively makes it 1:1.5. For scalping with tighter R:R, transaction costs can flip a positive-expectancy strategy negative. Always include transaction costs in backtest math; many retail traders ignore them and end up confused about why their "edge" doesn't materialise. Singapore retail commissions are now $0-$2.50 per equity trade; crypto exchanges charge 0.1-0.5% per side; forex spreads are 1-3 pips for majors.
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No. All calculations run entirely in your browser via JavaScript. There's no server roundtrip — open DevTools → Network and confirm zero outbound requests as you change inputs. Your trade details stay on your device. Safe for confidential trading plans, prop firm pre-trade checks, or any sensitive trading data.
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Three intertwined reasons. (1) Poor R:R discipline: taking 1:1 trades with random outcomes — guaranteed to break even minus transaction costs (i.e., lose). (2) Bad position sizing: risking 5-20% per trade and getting wiped out by inevitable losing streaks. (3) Behavioural mistakes: moving stops further away (loss aversion), taking profits too early (recency bias), revenge-trading after losses. Mathematical discipline (this calculator's framework) addresses #1 and #2. Behavioural discipline is harder — most retail traders need to lose money for several years before internalising that the math is unforgiving and emotions are the enemy.
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