Risk-Reward Ratio Explained: Why 1:2 Is Not Magic

What the ratio means

The risk-reward ratio compares two distances: from your entry to your stop-loss (the risk) and from your entry to your target (the reward). If you buy at ₹200 with a stop at ₹195 and a target at ₹210, you risk ₹5 to make ₹10. That is written 1:2.

It is a planning tool, not a promise. Price may never reach the target, and a stop can fill worse than planned. But knowing the ratio before you enter forces you to ask a useful question: is the possible gain worth the possible loss?

How to calculate it

For a long (buy) trade: risk = entry - stop-loss, reward = target - entry, ratio = reward ÷ risk. Entry ₹1,000, stop ₹980, target ₹1,050 gives risk ₹20, reward ₹50, ratio 2.5, written 1:2.5.

For a short (sell) trade it flips: risk = stop-loss - entry, reward = entry - target.

Charges reduce the reward and add to the risk. On a small intraday move, a ratio that looks like 1:2 before costs can be closer to 1:1.6 after brokerage, STT and fees, so include them when the distances are small.

Win rate and ratio work together

A ratio means nothing without the win rate, the percentage of trades that reach the target before the stop. The two together decide whether a method makes or loses money over time.

The break-even win rate for a ratio is 1 ÷ (1 + ratio). At 1:1 you need to win more than 50% of trades. At 1:2 you need more than about 33%. At 1:3, about 25%. This is why traders who use wide targets can be profitable while losing more trades than they win.

But the reverse is also true. Far targets are reached less often. A trader who changes every target from 1:1 to 1:4 does not automatically earn more, because many trades that used to reach the close target will now turn back and hit the stop. Ratio and win rate pull against each other.

Expectancy: the number that combines both

Expectancy is the average result per trade over many trades. In risk units: expectancy = (win rate x average reward) - (loss rate x average risk).

Example: you win 40% of trades with an average reward of 2R and lose 60% with an average loss of 1R. Expectancy = 0.4 x 2 - 0.6 x 1 = +0.2R per trade. If R is ₹2,000, the method averages about ₹400 per trade over a large number of trades, before charges.

Expectancy can only be estimated from data: your own trade history or a backtest. A single trade tells you nothing; twenty trades tell you a little; a hundred start to mean something.

Setting targets that make sense

A target should come from the chart, just like the stop. Common choices are the next resistance level (for a buy), a previous swing high, or a multiple of ATR. If the nearest resistance gives you only 1:0.8, the honest answer may be to skip the trade rather than invent a far target.

Some traders take partial profit at 1:1 and trail the rest. This raises the win rate of the first half and lets the second half catch bigger moves. Whether it helps depends on the stock and timeframe, which is exactly the sort of question a backtest can answer.

Where risk-reward fits in a full trade plan

A complete plan answers five questions before entry: why this trade, where it is wrong (the stop), where it is likely to pause (the target), how much to buy (the size), and what would make you leave early (for example a result date or a market-wide fall).

Risk-reward links the second and third answers. If the honest target is close and the logical stop is far, the ratio will be poor, and that is useful information: it is telling you this is not a good place to enter, even if the idea itself is reasonable. Waiting for a better entry price often improves the ratio more than any change to the target.

Common mistakes

Moving the stop wider to make the ratio look better. The ratio improves on paper while the real risk grows.

Choosing a target only to make the numbers look good, with no reason in the chart.

Exiting winners early out of nervousness but letting losers run. This quietly turns a planned 1:2 into an actual 1:0.7.

Judging a method on a handful of trades. Short runs of luck in either direction are normal.

A worked example: two styles, same market

Trader P likes quick trades: risk ₹10 per share, target ₹10 (1:1), and wins 58% of the time. Over 100 trades the average result is 0.58 x 10 - 0.42 x 10 = ₹1.60 per share per trade before charges. Small, but positive.

Trader Q holds for bigger moves: risk ₹10, target ₹30 (1:3), but wins only 30% of the time. Average = 0.30 x 30 - 0.70 x 10 = ₹2 per share per trade. Slightly better on paper, but Q will often lose six, eight or ten trades in a row, which is emotionally much harder.

Now add charges of ₹1 per share per trade. P's edge falls to ₹0.60, Q's to ₹1.00. Charges hurt the frequent, small-target style more. Neither style is right or wrong; the numbers simply show what each one asks of you, in patience and in discipline.

The lesson is to judge a method on all three together: ratio, win rate and costs. A ratio on its own says very little.

Try it on iTradeChart

Use the free risk-reward calculator, or draw a Long / Short position on any chart: it shows the ratio, the percentage moves and the rupee amounts for your plan. Place the plan as a bracket order so the stop and target are both set.

To estimate win rate and expectancy for a rule, build it in the Strategy builder and run a backtest over 1-5 years. The results show win rate, average win and loss, and drawdown, including realistic charges.