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Monte Carlo Simulation for Trading Strategy Validation

June 8, 2026 8 min read

Use Monte Carlo simulation to estimate the probability of drawdowns, ruin, and profitable outcomes from your backtest.

A single backtest shows what happened in one historical path. Monte Carlo simulation shows what could have happened by reshuffling trades thousands of times, giving you a distribution of possible outcomes.

What Monte Carlo Reveals

Monte Carlo helps answer questions like: What is the probability of a 20% drawdown? What is the chance of losing money over the next year? How lucky was my original backtest result?

Common Methods

  • Trade reshuffling: Randomize the order of historical trades.
  • Bootstrapping: Sample trades with replacement to create new equity curves.
  • Return resampling: Resample daily returns to simulate alternative paths.

Interpreting Results

Look at the median outcome, the 5th percentile (worst realistic case), and the 95th percentile. If the worst realistic case is still acceptable, your strategy is robust.

Run It in NeuroBacktest

Type: "Run Monte Carlo simulation on my Bollinger Bands strategy for MSFT with 5,000 iterations."