🎲 Risk/reward and expectancy: why a 40% win rate can make money

🎯 In 30 seconds: Whether a trading method makes money depends on two numbers together: how often it wins and how big the wins are compared with the losses. Expectancy combines them: (win rate x average win) minus (loss rate x average loss). A method that wins only 40% of the time can make money if its wins are three times its losses. A method that wins 60% can lose money if its losses are twice its wins. In India, STT, brokerage and exchange charges come off every trade and can wipe out a small edge completely. And you need far more trades than most people think before your measured numbers can be trusted.

Two dosa stalls

Two friends open dosa stalls on the same street. The first sells cheap plain dosas, hundreds a day, at a thin margin. The second sells fewer, fancier dosas at a fat margin. Neither friend can tell who is doing better by counting customers. They have to count customers and the profit on each one, and then subtract rent, gas and the cost of the dosas that went in the bin.

Trading works the same way. Counting winning trades tells you little. You need the size of the wins, the size of the losses and the costs, all together.

The words you need

• Win rate (W): the share of trades that make money. 40 winners out of 100 trades is a 40% win rate.
• Loss rate: 1 minus the win rate. Here, 60%.
• Average win and average loss: the average rupee result of the winning trades and of the losing trades, counted after all charges.
• Reward-to-risk ratio: how much you aim to make compared with how much you risk. Buy at ₹480, stop at ₹456, target ₹528: you risk ₹24 to make ₹48, a 2:1 ratio. When measured from actual results (average win / average loss) it is often called the payoff ratio. In formulas below it is written b.
• Expectancy: the average amount you expect to make or lose per trade over many trades.

Planned and actual reward-to-risk are often different. You may plan 2:1, but if you take profits early, let stops slip or pay charges you did not count, your real payoff ratio might be 1.2:1. Always compute it from your trading journal and your broker's P&L report, not from your plans.

The expectancy formula

expectancy = (win rate x average win) - (loss rate x average loss)

If you measure results in R, the rupee amount you risk per trade (see Position sizing), and your average loss is 1R, the formula becomes:

expectancy in R = (W x b) - (1 - W)

Positive expectancy means the method makes money on average. Zero means it breaks even. Negative means each trade, on average, costs you money, and trading more just loses faster.

Worked example: two hypothetical traders

Trader A wins 40% of the time. Average win ₹3,000, average loss ₹1,000, both after charges.

(0.40 x ₹3,000) - (0.60 x ₹1,000) = ₹1,200 - ₹600 = +₹600 per trade

Trader B wins 60% of the time. Average win ₹1,000, average loss ₹2,000.

(0.60 x ₹1,000) - (0.40 x ₹2,000) = ₹600 - ₹800 = -₹200 per trade

Trader B will feel more successful. Most days end green in the broker app. But a few large losses erase all the small wins. This pattern is common when people book small profits quickly and let losers run, and in option-selling strategies that collect small premiums most weeks and occasionally take a large hit on a big index move.

Trader A has the opposite feeling. Losing six trades out of ten is uncomfortable, and long losing streaks are normal (see Drawdowns and losing streaks). But the math works. Many trend-following methods look like Trader A.

The breakeven win rate

Set expectancy to zero and solve for the win rate. If your average loss is 1R and your average win is b times that:

breakeven win rate = 1 / (1 + b)

This is why a 40% win rate is not a bad number by itself. At 2:1 you only need 33.33% to break even. At 1:1, 40% is a losing method.

Expectancy grid

Here is expectancy in R per trade for a range of win rates and payoff ratios, before costs:

To turn R into rupees, multiply by your risk per trade. At ₹2,000 risk, +0.20R is +₹400 per trade on average. Over 50 trades that is an expected ₹20,000, but the actual result will scatter widely around that figure.

Indian charges move the line

Every Indian trade pays a stack of charges. For shares, STT is 0.1% on both the buy and the sell for delivery trades, and 0.025% on the sell side for intraday trades. For F&O, from 1 April 2026, STT is 0.05% of the sell value of futures and 0.15% of the premium when you sell an option. On top come brokerage, exchange transaction charges, the SEBI fee, stamp duty on the buy side, 18% GST on brokerage and exchange charges, and a DP charge when you sell delivery shares. What trading really costs has a full contract note.

Costs make every win smaller and every loss bigger. Here is what they do to a small edge.

An intraday example. You trade ₹1,00,000 of a liquid stock intraday, risking ₹1,000 per trade (1R). With a hypothetical broker charging ₹20 per order, the round trip costs about ₹83: ₹40 brokerage, about ₹25 STT, about ₹6 exchange charges, ₹3 stamp duty, about ₹8 GST and about 20 paise of SEBI fee. That is about 0.08R per trade.

Say your method wins 50% of the time with a payoff of 1.2:1. Before costs:

(0.50 x 1.2) - (0.50 x 1) = +0.10R

After 0.08R of costs, wins become 1.12R and losses become 1.08R:

(0.50 x 1.12) - (0.50 x 1.08) = 0.56 - 0.54 = +0.02R

Costs took four fifths of the edge. The breakeven win rate rose from 45.45% to 1.08 / (1.12 + 1.08) = 49.09%. Your ₹100 average gain per trade became ₹20, and one bad fill a week would wipe that out. This does not even count slippage, the gap between the price you expected and the price you got, which you see on every market order and every stop.

A delivery example. A swing trade of ₹40,000 that risks ₹2,000 costs about ₹150 for the round trip with the same broker, mostly STT. That is about 0.075R, similar in R terms. Swing trades usually aim for bigger moves, so the same rupee cost is a smaller share of the typical win.

What SEBI found about costs

SEBI's studies show costs are not a rounding error for Indian traders.

• In the equity cash intraday study (July 2024), loss-making traders added 57% on top of their trading losses through trading costs in FY23. Profit-makers spent 19% of their trading profits on costs.
• In the derivatives study covering FY26 (August 2026), individual traders paid about ₹24,859 crore in transaction costs (SEBI notes the full figure is likely higher, because its data covers most but not all turnover). Costs were 35% of the gross losses of loss-makers and 21% of the gross profits of profit-makers.
• The same study found that about 4.4 lakh traders who had a gross trading profit in FY26 became net loss-makers once transaction costs were deducted.

The lesson for expectancy: a method with a small positive edge before costs can be a losing method after costs, and the more often you trade it, the more certain that becomes.

How many trades before you can trust the numbers?

Your measured win rate is an estimate, and small samples are noisy. A rough 95% range for a measured 40% win rate is:

These use the standard formula for the error of a proportion, 1.96 x square root of (W x (1 - W) / n). After 20 trades, a "40% win rate" is consistent with anything from a clear loser to a strong winner. Even 100 trades leaves a wide range. Payoff ratios are noisy too, because one big winner can change the average a lot.

Practical meaning: do not judge a method after a good or bad week. Keep risk small and keep collecting results. Testing a rule on past data first can give you a larger sample faster, as long as you avoid the traps in Does technical analysis work? and Testing ideas.

What the evidence says about expectancy in practice

Positive expectancy is hard to find and harder to keep after costs. SEBI's FY26 derivatives study found 87.7% of individual traders were loss-makers. In the intraday cash study, even among traders who had been trading for three years, 54% were still loss-makers in FY23. That was better than the overall 71%, but it shows that experience alone did not turn most traders into winners.

That does not prove no one can have an edge. It does mean you should assume you do not have one until your own records, over many trades and after every rupee of charges, say otherwise.

Try it

Download the tradebook or P&L report for the last few months from your broker's back office, or use 20 practice trades from a notebook if you have no real ones. If you have fewer than 20, keep practising until you do (see Practice first). Compute win rate, average win, average loss and expectancy in rupees and in R. Then add up the charges column, or take them from your contract notes, and compute it again after charges. Finally, look up the 95% range for your win rate in the table above and ask: is my edge still positive at the bottom of that range?

Sources

• NSE: SEBI turnover fees, STT and other levies (updated April 2026)
• NSE circular (27 February 2026): Revision in transaction charges
• Union Budget 2026-27: Memorandum explaining the provisions in the Finance Bill (STT on futures and options)
• SEBI (July 2024): Analysis of intraday trading by individuals in equity cash segment
• SEBI (August 2026): Profitability of individual traders in the equity derivatives segment, FY25 to FY26