Data published by hypothesess.com, 8 November 2026. The data as JSON.

Read the article: Full Kelly, half Kelly or 2% risk: what a misjudged win rate costs per trade

Expected growth per trade at the wrong win rate: full Kelly, half Kelly and a 2% risk, with break-even win rates, two ways

Our own calculation, 8 November 2026 (UTC), for the article "Full Kelly, half Kelly or 2% risk: what a misjudged win rate costs per trade". A trade gains 10% of the position with probability p and loses 10% otherwise; f is the position as a share of capital (f = 2 is full Kelly for an estimated 60% win rate: f* = p/l - q/g = 0.6/0.1 - 0.4/0.1 = 2; f = 1 is half Kelly; f = 0.2 risks 2% of capital). Expected log growth per trade: p ln(1 + 0.1 f) + (1 - p) ln(1 - 0.1 f). Way 1: that formula. Way 2: the average log growth over an exact sequence of 10,000 trades with p x 10,000 wins (the same to rounding). Break-even win rates: way 1 a numeric search for the p where growth is zero; way 2 the closed form p* = ln(1/(1 - 0.1 f)) / ln((1 + 0.1 f)/(1 - 0.1 f)); the two agree to nine decimals.

What we found

True win rate f = 0.2 (risk 2%) f = 1 (half Kelly) f = 2 (full Kelly at 60%)
40% -0.42% -2.51% -6.10%
45% -0.22% -1.51% -4.07%
50% -0.02% -0.50% -2.04%
55% +0.18% +0.50% -0.01%
60% +0.38% +1.50% +2.01%
65% +0.58% +2.51% +4.04%

What this cannot tell you: real markets, where gains and losses are not a fixed 10% and the win rate drifts.