A method that reshuffles your trades thousands of times to map the range of outcomes your edge could realistically produce.
A Monte Carlo simulation takes your trades and replays them in thousands of different random orders to show the full range of outcomes your edge could have produced, not just the single sequence you happened to get. Your real equity curve is one roll of the dice. Monte Carlo rolls it 10,000 more times, so you can see how lucky or unlucky your actual result was, and how deep a drawdown the same edge could hand you on a worse run.
It shows the spread of results your edge could realistically produce, instead of the single path you actually walked. You get a range of likely final returns and, more useful, a range of likely worst drawdowns.
The drawdown part is the point. Your backtest shows one max drawdown; the same trades in a slightly unluckier order could draw down half again as deep. If that deeper number would have broken your account, the strategy is riskier than your single curve ever admitted.
It cannot turn a bad sample into a good one. Reshuffle 30 trades ten thousand times and you still hold 30 trades of information, dressed up to look like far more.
Most simple Monte Carlo also assumes your trades are independent and that the future looks like the past, and both can be wrong. A strategy whose losses cluster in trending markets will look tamer in a naive reshuffle than it is live. Treat the output as a stress test of one sample, never a crystal ball. This is close cousin to the trap described in overfitting.
A backtest is one history. Monte Carlo is thousands of plausible histories built from the same trades.
The backtest answers what happened. Monte Carlo answers what could happen with the same edge, which is the question that actually keeps your account alive. Reading them together gives you both the result and the risk around it. To weigh a real edge against a lucky run, see is your edge real or luck.
Quantprove runs a Monte Carlo simulation inside your Backtest analysis, resampling your closed trades to map the range of equity curves and worst drawdowns your edge could produce.
It sits right next to the permutation test, which asks a sharper question: could random noise have produced your result at all? One maps the range of your edge, the other checks the edge is real, and both feed how far you should trust your Edge Score.