Best Risk-to-Reward Ratio: 1:1 vs 1:2 vs 1:3 Profit Targets

Every trading forum has a guy who swears 1:3 is the only “professional” risk-to-reward ratio. He usually also has a lifetime win rate he won’t share. Here’s what the math actually says about 1:1, 1:2 and 1:3 profit targets — and why the “best” one is probably not the biggest one.

01 — THE MATHWhat a Risk-to-Reward Ratio Actually Tells You

A risk-to-reward ratio compares the distance from entry to your stop with the distance from entry to your target. Risk 20 points to make 40 and you’re trading 1:2. That’s it — it’s a ruler, not a crystal ball. Knowing it before entry tells you how often you need to be right just to stand still. [Rupeezy]

The magic number is the break-even win rate, and the formula is refreshingly short. Divide one by one plus your reward multiple and you get the minimum percentage of winners required to not lose money. [Liberated Stock Trader]

Run the numbers down the ladder and the appeal of big ratios is obvious: at 1:3 you can be wrong three times out of four and still break even, while 1:1 leaves zero room for error at a coin-flip hit rate. This is the part of the sales pitch everyone remembers. [TradingView]

Notice the shape of that curve. Going from 1:1 to 1:2 drops your required hit rate by almost 17 percentage points. Going from 1:3 to 1:4 only buys you five. Diminishing returns kick in early, and they arrive right around the ratios people love to brag about. [Liberated Stock Trader]

02 — THE CATCHWhy the Ratio Alone Is Useless

Here’s the part the 1:3 evangelists skip: a ratio on its own says nothing about profitability. What drives long-run results is the ratio of your average win to your average loss, paired with how often you win. A beautiful 1:5 setup that never reaches its target is just a very elegant way to lose money. [Macroption]

The metric that ties it together is expectancy — the average amount you make or lose per trade over a large sample. Multiply your win rate by your average win, subtract your loss rate times your average loss, and you have the only number that actually predicts whether your account grows. [BabyPips]

Expressed in R-multiples, the grid below shows expectancy per trade for common win-rate and ratio combinations. Green means the system makes money; red means you’re donating. A 70% win rate at 1:0.5 barely scrapes positive, while a 40% win rate at 1:3 is comfortably profitable — which is exactly why “high win rate” and “good strategy” are not synonyms. [TradeZella]

03 — THE EVIDENCEWhat Real Traders Actually Do Wrong

The data on retail traders is brutally consistent. DailyFX’s “Traits of Successful Traders” research, built from more than 12 million live trades at a major FX broker, found that clients were right more than half the time — and still lost money, because their losing trades were far larger than their winners. [DailyFX]

The worst example was almost comical. Traders won roughly two out of three GBP/JPY trades, yet lost overall, averaging about 52 pips on winners against roughly 122 pips on losers. A 66% win rate with an effective 1:0.4 ratio isn’t a strategy; it’s a slow-motion account liquidation. DailyFX’s takeaway was simple: enforce at least a 1:1 ratio with stops and limits. [DailyFX]

Professionals aren’t immune either. A study in the Financial Analysts Journal of a U.S. proprietary stock-trading desk found the traders closed winners much faster than losers — the classic disposition effect — and that the habit cut into their intraday profits. The authors concluded the team could have earned more by holding winners longer and dumping losers sooner. [CFA Institute]

The behavioral root goes back to Terrance Odean’s 1998 work on 10,000 brokerage accounts, which found investors were about 1.5 times more likely to sell a winning position than a losing one. Translation: your brain is wired to turn your planned 1:2 into a realized 1:0.8, and it will absolutely do so the moment a green trade starts to wobble. [TradesViz]

04 — THE CONTENDERS1:1 vs 1:2 vs 1:3, Honestly Compared

1:1 — The scalper’s coin flip (with a rake)

A 1:1 target needs a 50% win rate just to break even, which sounds fine until you remember the house takes a cut on every trade. Commissions, exchange fees and slippage push your real break-even above the textbook number, and at 1:1 there’s no cushion to absorb them. [Rupeezy]

Here’s how that looks on NQ, where each index point is worth $20 per contract. A 20-point stop and a 20-point target is $400 at risk to make $400. Assume a hypothetical $5 round-turn in costs: winners net $395, losers cost $405, and your true break-even becomes 50.6%. Drop to MNQ at $2 per point with the same 20-point bracket and, say, $1.50 in costs, and break-even climbs to nearly 52%. Smaller size, same fees, worse math. [CME Group]

1:1 isn’t automatically wrong. It suits setups with a demonstrably high hit rate — mean reversion into a level, for example — where you have the journal data to prove you win well north of 55%. Without that proof, it’s a coin flip with a rake, and the casino has better lighting. [NexusFi]

1:2 — The boring answer that keeps working

At 1:2 you only need to win one trade in three to break even, and a 40% win rate produces a healthy +0.2R per trade. More importantly, a 2R target on an intraday futures setup is usually inside the realistic range of a single move, so it gets hit often enough that the win rate doesn’t collapse. That’s why it shows up as the default in so much trading education — not because it’s sacred, but because it’s survivable. [Liberated Stock Trader]

1:3 — Great on paper, rough on the psyche

A 1:3 target only needs a 25% hit rate, and a strategy with a 45% win rate at 3:1 is very profitable — if you actually let the winners reach the target instead of panicking out at 1R. That “if” is doing heavy lifting. Low-hit-rate systems mean long strings of consecutive losers, and that’s exactly when traders start overriding their own plan. [Day Trading Toolkit]

05 — THE REAL ANSWERLet Your Own Data Pick the Target

The best profit target is the one that maximizes expectancy for your setup, and the only way to find it is to measure how far your trades actually run before reversing — maximum favorable excursion, or MFE. Pull it from your journal or backtest, then calculate how often each target level would have been hit. [TradesViz]

Consider a hypothetical continuation setup where a 1R target gets hit 58% of the time, 2R gets hit 36% of the time, and 3R only 22% of the time. Plug each into the expectancy formula and the “worse” ratio wins: 1:1 returns +0.16R per trade, 1:2 returns +0.08R, and 1:3 actually loses 0.12R. Same entries, same stop — the target alone flips the system from profitable to broke. [BabyPips]

Flip the scenario and the answer flips with it. A trend-continuation setup that regularly runs three or four R before pulling back will make far more money at 1:3 than at 1:1. The ratio isn’t the edge; matching the target to how your setup actually behaves is. A target built on a fantasy move is worse than having no target at all. [Rupeezy]

A quick process to find your number

Pull your last 50–100 trades on one setup. For each, log the stop distance and the farthest price traveled in your favor before the stop or exit. Count how many reached 1R, 1.5R, 2R and 3R. Run expectancy at each level and pick the highest — then trade it mechanically long enough to see if live results match. Review in blocks of trades rather than reacting to every single outcome. [DailyFX]

06 — THE PROP FIRM FACTORHow Funded Account Rules Bend the Answer

If you’re trading an evaluation, the “best” ratio has another variable: the rulebook. Topstep’s Trading Combine, for example, uses a consistency target that caps your single best day at roughly half of the profit target; blow past it and your profit target gets raised. A strategy that lives on one monster 1:4 runner a week can technically be profitable and still fail the consistency math. Check the firm’s current help center, because these percentages get tweaked. [Topstep]

Trailing drawdowns compound the problem. Low-win-rate systems produce longer losing streaks, and a streak that’s statistically normal at 1:3 can still chew through a tight trailing threshold before the big winner shows up. Under those constraints, a steadier 1:1.5 to 1:2 profile often passes more evaluations even if a 1:3 profile has slightly higher theoretical expectancy. Compare the rules side by side in our prop firm comparison tool before you choose a firm for your style. [Liberated Stock Trader]

07 — THE MIDDLE PATHPartials and Runners: Having It Both Ways

You don’t have to marry one ratio. A common structure is to scale out part of the position at 1R, move the stop on the remainder to break-even, and let a runner aim for 2R or 3R. It raises your effective win rate while keeping some exposure to bigger moves. The cost is that your average win shrinks versus holding everything to the full target — so measure blended expectancy, not just the feel-good of locking in green. [TradeZella]

Whatever structure you choose, decide it before entry and stick to it. Every study above points at the same failure: traders shrink winners and stretch losers in real time. A mechanical target — even an imperfect one — beats an “optimal” target you abandon the second the trade gets interesting. [CFA Institute]

08 — VERDICTSo, What’s the Best Profit Target?

If you want a default to start with, use 1:2. It only needs a 33% hit rate, it’s realistic for most intraday futures moves, and it leaves room for fees and bad weeks. Then stop treating it as gospel: measure your setup’s MFE, run expectancy at every target level, and move to whatever number the data favors — 1:1.5, 1:2.5, even 1:1 if your hit rate earns it. The traders who brag about 1:3 rarely mention how many of those targets got hit. Your journal will tell you. [Macroption]

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Educational content only, not financial advice. Futures trading involves substantial risk of loss. Hypothetical examples are illustrative and do not represent actual trading results.