Model, not market data
The same trades show a much higher share of ruined paths as the risk per trade rises
A backtest gives one path through the past, and the order of wins and losses shaped that path. Monte Carlo asks what other paths were possible with the same trades. It draws the trades again in random order, which keeps the total and changes the path, or resamples them with replacement, which changes the total as well. It records the result of each run.
The output is a range, not a single number. A strategy with a positive average per trade can still show a deep drawdown in a large share of simulated paths, because losses come in streaks. The ruin figure is the share of paths that cross a loss level set in advance, and the sizing rule decides how often that happens.
The chart is a model, not a real trade list. It draws each trade from a win rate and a payoff, risks a fixed share of the account on each one, and counts the paths that cross the ruin level. The inputs are listed under the chart, they are illustrative, and the model is seeded, so the same inputs give the same bars.
Three cautions apply. The trades must be real, costed trades from a clean out of sample test, or the simulation only reshuffles a flattering history. Random order assumes the trades are independent, which regimes and expiry clusters break. And a low ruin share in a simulation describes the model, not the account.
The same win rate and payoff can support very different sizes, and the bars rise steeply as the share risked nears and passes the Kelly fraction of these inputs. The size is the part the trader controls.
Before you trade. Derivatives trading carries a high risk of loss. SEBI's study "Profitability of Individual Traders in the Equity Derivatives Segment (FY25 to FY26)" (August 2026) found that 87.7% of individual traders in equity F&O made net losses in FY26, with aggregate net losses of Rs 91,685 crore. Read the SEBI study