Edge per trade multiplied by how many trades you get, which is the figure that actually determines account growth.
Two systems: A earns plus 0.5R per trade and trades twice a month; B earns plus 0.15R per trade and trades daily. Per trade, A is more than three times better. Per year, A earns 12R and B earns roughly 37R. B compounds faster despite the weaker-looking signal.
Compute it as expectancy x trade frequency over the same window, and adjust for capital occupancy: a trade holding capital for ten days at plus 0.4R yields 0.04R per day, while one holding for two days at plus 0.2R yields 0.10R per day. That comparison is the justification for time-stop rules.
The limit on the logic is cost and capacity. More trades means more slippage-budget and more chances to deviate from process, and both scale with frequency while the edge does not. Beyond some rate, added frequency subtracts.
Original diagrams for the ideas on this page. Illustrative, not real market data.
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.Slippage on a market order. You click at 20.00, but only 300 shares are resting there, so the rest of the order fills at 20.01, 20.03 and 20.04. The average price paid is 20.02, and that two-cent gap is slippage.
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