P&L

Expectancy is just average rupees per closed trade

A one-line formula that becomes useful the moment you attach a sample size to it.

2025-10-28 · 6 min read

Expectancy has an intimidating name and a schoolbook formula: win rate times average win, minus loss rate times average loss.

What it produces is mundane and useful — the average rupees a trade from this filtered set was worth.

Run it on a real filter

Pick a set: one financial year, one product, closed trades only. Compute the four inputs. The answer moves when the filter moves, and that is the point, not a flaw.

The same book, sliced three ways
FilterTradesWin rateAvg winAvg lossExpectancy
All trades21248%₹4,200₹3,400₹247
Index options only13852%₹4,900₹3,100₹1,060
Stock futures only7441%₹2,700₹4,000−₹1,253

One account, one year. The blended number hid both stories. Illustrative journal data, not a live book and not a performance claim.

Pick one side of the fee argument

If average win is gross and average loss is net, you have invented a number that describes nothing. Use net throughout when the question is money, use gross throughout when the question is entry quality, and write the convention on the chart.

Then be rude about sample size

Twelve trades with a fat expectancy is a coin wearing lipstick. Print n. If n is small, hide the trophy and show the count instead.

And the obvious warning: a positive historic expectancy is a description of trades that already closed. It is not permission to increase size.

Expectancy per trade as the sample grows
₹0₹532₹1k₹2k₹2k ₹2kFirst 20₹900First 50₹420First 100₹300First 160₹247All 212

Early samples flatter. Illustrative journal data, not a live book and not a performance claim.

Key takeaways

Your book already has these numbers. Import a broker CSV and the charts above draw themselves from your own closed trades.
Open the journal