Monte Carlo Equity Curve Simulator

Two traders with the same strategy — same win rate, same reward-to-risk — can end the year with wildly different equity curves. This simulator makes that variance visible. Set your parameters, run a few thousand curves, and watch what luck alone does to identical edges. Everything runs in your browser; nothing is uploaded.

What the parameters teach you

Risk per trade is the volatility dial. Rerun the default (1% risk) and then try 5% and 10%. The expectation per trade is identical, but the 5th-percentile curve — the unlucky trader with your exact strategy — collapses, and the ruin percentage climbs. This is the entire argument for small position sizes, made visually. How small, given that the win rate itself is an estimate, is the Kelly-under-uncertainty calculator’s question.

Win rate and reward-to-risk are one number in disguise. A 35% win rate at 3:1 and a 65% win rate at 0.85:1 have similar expectation (+0.05R vs +0.10R per trade), but they produce very different paths: the low-win-rate curve endures brutal losing streaks (watch the max-consecutive-losses stat) that most traders abandon in practice. Simulate both before deciding which one you can psychologically hold.

Percent-risk cannot mathematically ruin you; fixed-risk can. With percent sizing, losses shrink your bets — equity decays but never hits zero. With fixed-dollar sizing, a losing streak takes you to zero directly. Reality is in between: minimum position sizes, gaps, and fees make percent sizing less protective than the simulation shows. That gap between model and reality is exactly what the production checklist’s drawdown limits exist for.

The band is the strategy; a single backtest is one thread of it. Any individual equity curve — including your live track record — is one draw from a distribution like this fan. Judging a strategy (or a fund manager) on one path without knowing the fan’s width is how survivorship stories get sold. The same logic underpins our skepticism about single-backtest papers in the research hubs.

Model: each trade risks the configured amount; wins pay risk × ratio, losses lose the risk; equity floors at $0. Trades are independent — real markets have regime clustering, so treat these bands as optimistic. This tool rebuilds the equity-curve simulator formerly hosted on the author’s personal site (2018–2023), with percentile bands and ruin statistics added.