Constant %Heuristic
◆ The PatternRisk a constant percentage of equity on each trade
Fixed fractional sizing sets position size so the dollar risk (distance to stop × shares) equals a fixed fraction f of current equity.
Position = (Equity × f) / (Entry − Stop)
Typical f values: 0.5 %–2 %. This keeps risk proportional to equity — positions shrink after losses and grow after gains, providing natural anti-martingale behavior.
// Interactive — risk fraction and equity curve
Risk fraction %
Ruin probability. At 1 % risk per trade each loss is 1 % of what is left, so the account shrinks but never reaches zero: 20 straight losers still leave 82 %.
Pattern bridge: Stop distance interacts with ATR-based stops.
Worked example
50,000 of equity, 1% risk per trade, entry 40 and stop 37: 166 shares, so a stopped-out trade loses about 500. Because each bet is 1% of what is left, losses shrink as equity falls. Twenty losers in a row leave 40,895 (82%); even a hundred leave 18,302. You never quite reach zero — but you do need ever larger gains to climb back.
Where it misleads
- The stop is assumed to fill at 37. Gaps and fast markets fill below it, so the real risk per trade is higher than 1%.
- Correlated positions are one bet: five trades at 1% on the same theme risk closer to 5%.
- It controls the size of losses, not whether the strategy has an edge.
In code
equity, risk = 50_000, 0.01 # risk 1% of equity per trade entry, stop = 40.0, 37.0 shares = int(equity * risk / (entry - stop)) after_20_losses = equity * (1 - risk) ** 20 after_100_losses = equity * (1 - risk) ** 100
Assumes import numpy as np and import pandas as pd. Each snippet carries its own example numbers; the comments say which are made up or simulated.
Sources
- Portfolio Management Formulas, R. Vince, Wiley, 1990
- Trade Your Way to Financial Freedom, V. K. Tharp, McGraw-Hill, 1998
- J. L. Kelly Jr., “A New Interpretation of Information Rate”, Bell System Technical Journal 35(4), 1956
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