Expectancy — P&L

Expected value per trade in account currency. Average net P&L across all trades.

Computed from: Trades list
Scope: Single report
Range: Any real number
Direction: Higher is better

Basis

Computed on the Per-Trade P&L Axis (account currency)

Expectancy is the bottom line of a trading edge: the average amount you can expect to make (or lose) per trade, over many trades. It rolls win rate and payoff ratio into one number — and if it's positive, the system makes money in the long run.

How it's calculated

Expectancy = (Win% × AvgWin) − (Loss% × AvgLoss)
          = mean(net P&L per trade)

Win% / Loss%: share of winning / losing trades
AvgWin / AvgLoss: average size of a win / a loss (loss as a positive magnitude)

In this product: Both lines give the same number: the top builds it from win rate and average sizes; the bottom just says "add up every trade's result and divide by the number of trades." Same answer, two routes. You can also measure expectancy in % return or in pips instead of dollars — those versions ignore how big your positions were, so you can fairly compare two strategies, or two different currency pairs, side by side. (Pros often quote expectancy in R-multiples — profit per unit of risk taken, e.g. "+0.2R per trade"; the pips% version is the closest sizing-neutral equivalent here.)

What it tells you

Expectancy is the per-trade "edge." Combined with how many trades you take, it gives a first-order estimate of expected income:

Expected weekly result ≈ Expectancy × trades per week

This is an estimate, not a forecast — it assumes the edge, the trade frequency, and the position sizing all keep holding (see Pitfalls).

Expectancy is where the average of every trade lands. Just above zero, compounded over thousands of trades, is a business.

Worked example

A system wins 45% of trades, with an average win of +$300 and an average loss of −$180:

Expectancy = 0.45 × 300 − 0.55 × 180 = 135 − 99 = +$36 per trade

At 40 trades a week that averages to roughly +$1,440/week — but read that as a long-run mean, not a paycheck. The real path swings hard around it: losing streaks are normal, and a positive-expectancy system can still ruin an over-sized account before the average ever shows up. It also assumes the historical edge keeps working (see Pitfalls).

Pitfalls

Pitfalls & caveats

It's a rear-view mirror. Expectancy is measured on trades that already closed. A positive number is evidence of a past edge, not a promise of a future one — edges decay as markets, crowding, and spread conditions change. The more recent and the more numerous the sample, the more you can lean on it; a thin or stale record projects poorly.
An average hides the variance — and the risk of ruin. A positive expectancy still comes with losing streaks, and bad sizing can ruin the account before the long-run average ever arrives. Size positions so you survive the streaks (see Kelly).
Driven by outliers. A handful of huge winners can carry expectancy; if they don't repeat, the edge evaporates. Cross-check profit concentration — and check when the edge shows up, since a system that earns its whole year in a few sessions is far harder to trade than its expectancy suggests.
Costs scale with frequency. The ×trades multiplier in the projection multiplies costs too — slippage and spread that look tiny per trade add up at 40 trades/week, and live fills rarely match a clean historical record.
Which version you use matters. The $-version weights big positions more; the return-% and pips% versions ignore position size. Use the size-neutral versions when comparing strategies.

Expectancy vs profit factor

Both summarize the trade distribution. Profit factor is a ratio (total wins ÷ total losses, scale-free); expectancy is an amount (per-trade, in real units). Profit factor tells you the edge's quality; expectancy times frequency tells you the edge's size in money.

Built fromWin Rate Payoff Ratio