Should you change your rules after a losing streak?
Four, five, six losers in a row, and the doubt sets in: maybe the stops are too tight, maybe you should sit out until things “calm down.” This is the moment that decides whether you have a strategy or just a mood. A normal losing streak is not a malfunction — it's a sample.
Every edge with less than a 100% win rate produces losing streaks — routinely, and longer than your intuition expects. A strategy that wins 55% of the time will still string together five and six losers regularly across a year. When it happens, it feels like the edge has broken. Almost always, it's the edge behaving exactly as the math said it would.
Mid-streak is the worst time to redesign
Widening your stops because the tight ones “keep getting hit,” or sitting out signals until you feel better, changes the very system you're judging — mid-experiment, on emotional evidence. You'll likely sit out the recovery, or take the next winner at a degraded risk profile, and conclude the changes “worked” or “didn't” from a sample of approximately nothing.
The streak is already in the model
This is where Monte Carlo earns its keep: it shows you that streaks of this length are normal paths within your edge, not signs of failure. The disciplined response to a drawdown that lives inside your modeled distribution is to keep executing the rules unchanged. Changing them under emotional pressure is the textbook failure mode — and the reason a machine that can't feel the streak has a structural advantage over you.
A losing streak isn't your edge breaking — it's your edge being an edge. The worst time to change the rules is the moment a drawdown makes you want to.
Discipline you don't have to summon
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