Monte Carlo Simulation
Also known as: Monte Carlo analysis, trade reshuffling
What is it?
A Monte Carlo simulation takes a strategy's set of past trades and reshuffles or resamples them thousands of times to map the wide range of equity paths and drawdowns that could have occurred, rather than relying only on the single sequence that actually happened. The core insight is that the order in which wins and losses arrive is largely a matter of chance. The one historical equity curve you see is just one possible ordering of those trades; if the same trades had landed in a different sequence, the account's journey, and especially its worst drawdown, could have looked very different. By generating thousands of alternative orderings, a Monte Carlo simulation reveals how bad an unlucky run could realistically have been.
For example, the trades that produced a 25% historical drawdown might, in a different order, have produced a 40% drawdown. This reframes risk from a single number into a distribution of outcomes, which leads to more conservative and survivable position sizing. A sensible practice is to size your risk around a high-percentile drawdown from the simulation rather than the single historical one, leaving margin for a bad sequence. Two cautions are essential.
A Monte Carlo simulation is built from past trades, so it inherits their assumptions and cannot capture conditions those trades never encountered. It is a risk-analysis tool, not a forecast or a promise. Past performance does not guarantee future results, no strategy is risk-free, and your capital is always at risk.
Why it matters: The single historical curve is just one of many orderings; Monte Carlo shows how bad a run could realistically have been, which informs sizing.
Monte Carlo reframes risk as a distribution, leading to more conservative, survivable sizing.
Real-world example
Resampling the trade sequence reveals that, with a different order, the same strategy could have drawn down 40% rather than 25%.
How SignalBots handles it
Where SignalBots presents risk ranges, the intent is to show a distribution of outcomes, not a single optimistic path. See /risk-warning.
Pro tip
Size from a high-percentile Monte Carlo drawdown, not the single historical one, to leave margin for an unlucky sequence.
Common pitfalls
Treating the one realised equity curve as the worst case when reshuffling shows much deeper paths were possible.
Frequently asked questions
What does Monte Carlo tell me?
How a strategy might have performed under different trade orderings, exposing deeper possible drawdowns than the single historical run. It is a risk tool, not a forecast or a guarantee of future results.
Why reshuffle trades that already happened?
Because the order of wins and losses is largely luck. The one sequence you saw is just one of many possible. Reshuffling shows how much worse a different, equally plausible order could have been.
How should Monte Carlo affect my position sizing?
Many traders size around a high-percentile drawdown from the simulation rather than the single historical figure, leaving a margin of safety for an unlucky sequence. Survivability comes first.
Can Monte Carlo predict the future?
No. It only reshuffles past trades and inherits their assumptions, so it cannot capture conditions those trades never faced. It maps a range of historical possibilities, not a forecast. Capital is at risk.
Does it cover everything that could go wrong?
No. It explores different orderings of past trades but not entirely new market events outside that data, such as a sudden regime change. Treat it as one useful risk lens among several, not a complete safety check.
Trading involves substantial risk of loss. Historical and backtested results do not guarantee future performance. Read the full risk warning.