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Backtesting & Validation Formula

Expectancy Formula

Expectancy is the average profit (or loss) a system produces per trade: the win rate times the average win minus the loss rate times the average loss. It is the single most important number for a trading system, because a positive expectancy traded repeatedly with sound sizing compounds, while a negative one guarantees ruin no matter how exciting the winners look.

By AI Fin Hub Research · AI Fin Hub Team
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Formula

Copy the exact expression or work through it step by step below.

Expectancy = (WinRate x AvgWin) - (LossRate x AvgLoss) R-multiple form: Expectancy_R = (WinRate x AvgWin_R) - (LossRate x 1) where LossRate = 1 - WinRate and AvgWin_R is the average win in units of initial risk

Variables

WinRate

Win rate

Fraction of trades that close profitably.

AvgWin

Average win

Mean profit of winning trades. Expectancy weights it by how often wins occur.

LossRate

Loss rate

Fraction of trades that close at a loss, equal to 1 minus the win rate.

AvgLoss

Average loss

Mean loss of losing trades, as a positive number. Subtracting the probability-weighted average loss from the probability-weighted average win yields the per-trade edge.

AvgWin_R

Average win in R

Average win measured in multiples of the initial risk (R). Framing expectancy in R-multiples makes it independent of position size and comparable across setups.

Step By Step

  1. 1

    Determine the win rate and loss rate.

    Win rate 0.40, loss rate 0.60.

  2. 2

    Determine the average win and average loss in currency or in R-multiples.

    Average win 250, average loss 100 (so average win is 2.5R if risk per trade is 100).

  3. 3

    Multiply win rate by average win and loss rate by average loss.

    0.40 x 250 = 100; 0.60 x 100 = 60.

  4. 4

    Subtract the second from the first for expectancy per trade.

    100 - 60 = 40 profit per trade.

Worked Example

Breakout system with a 40% win rate, risking 100 per trade

Win rate / loss rate

0.40 / 0.60

Average win / average loss

250 / 100

Expectancy = (0.40 x 250) - (0.60 x 100) = 100 - 60 = 40 per trade. In R-multiples, average win is 250/100 = 2.5R, so Expectancy_R = (0.40 x 2.5) - (0.60 x 1) = 1.0 - 0.6 = 0.4R per trade.

Expectancy of +40 per trade, or +0.4R. Each trade is worth, on average, 40% of the amount risked. Over 200 trades that is roughly 80R of expected edge before compounding, which is what makes the system worth trading despite losing 60% of individual trades. Expectancy says nothing about the path, so pair it with drawdown and Kelly sizing.

Common Variations

Expectancy per unit time (system quality): expectancy multiplied by trade frequency, comparing systems that trade at different rates.
SQN (System Quality Number): Tharp's metric, expectancy-in-R divided by the standard deviation of R-multiples, times the square root of trade count.
Profit factor: a ratio form of the same edge, gross profit over gross loss, that drops the currency scale expectancy keeps.

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Planning estimates only — not financial, tax, or investment advice.