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Edge

A repeatable reason your trades should have positive expectancy over many attempts; without one, trading is paying spread to gamble.

The spread of outcomes behind an expectancyA histogram of forty trades: a tall block of small losses on the left, a low spread of larger wins on the right, and a line marking the average outcome.NUMBER OF TRADES051024 LOSSES, AVG −$20016 WINS, AVG +$600EXPECTANCY +$120−$400−$200$0+$200+$400+$600+$800PROFIT OR LOSS PER TRADEexpectancy = (40% × $600) − (60% × $200) = +$120 per trade
Expectancy: the average trade. Forty trades sorted by outcome: 24 small losses and 16 larger wins. Weighting each side by how often it happens gives the average result per trade, marked here by the dashed line at +$120.

An edge can come from information, speed, a structural inefficiency, superior risk-management, or patience that others lack. It must be small enough to be believable and large enough to survive slippage and costs.

Most retail edges are behavioral: being willing to sit out, take small losses, and hold winners while others do the opposite. An edge is proven by a trading-journal over a real sample-size, not by conviction.

Example: a setup that wins 45% with 2R average winners has an expectancy of +0.35R. After 0.1R in costs it is +0.25R. That is an edge. The same setup at 40% and 1.5R is +0.0R after costs, which is not.

Related: expectancy, sample-size, trading-journal, backtesting

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