Monte Carlo Simulation

Monte Carlo simulation is a technique that stress-tests a trading strategy by re-running its historical trades thousands of times in randomised order, sometimes also resampling them or perturbing their sizes. Each run produces a different equity curve from the same underlying trade population, and the collection of runs forms a distribution of outcomes: how deep drawdowns could plausibly get, how long losing streaks might last, and how often the strategy would have breached a given loss limit. The method matters because a single backtest shows only one ordering of results, and metrics such as maximum drawdown depend heavily on that ordering. Traders use the simulated distribution to set position sizes and drawdown buffers with margin for sequences worse than the one history happened to deliver. Named after the Monaco casino district, the approach originated in mid-20th-century physics.