A backtest is one path; Monte Carlo shows the distribution
Your MT5 Strategy Tester produces one equity curve: the specific sequence of trades that happened, in the order they happened. That is a single sample from the distribution of all possible orderings of those same trades. If you had taken the same trades in a different sequence — say, the month of losses before the month of gains instead of after — the maximum drawdown on the curve could be drastically different, even though the final P&L is identical.
Monte Carlo reshuffles the trade sequence thousands of times to produce a distribution of possible equity curves. The 5th percentile curve shows you a realistic worst case. The median curve shows what is typical. The spread between them tells you how dependent the strategy is on lucky trade ordering.
What survival probability actually means
Algo Studio runs 10,000 shuffled simulations per backtest upload and reports: median drawdown, 95th percentile drawdown, survival probability (percentage of simulations that do not breach a target maximum drawdown), and expected days to recovery.
A strategy with 60% survival means four in ten sequence orderings of the same trades breach your drawdown tolerance. That is often surprising — and it is exactly the surprise that separates traders who know their risk from traders who got lucky. Survival below 70% typically means the strategy is too thin (not enough trades, or too dependent on a few large winners). Survival above 90% is robust.
When Monte Carlo reveals curve fitting
If your backtest P&L is €10,000 but the 5th percentile Monte Carlo outcome is −€3,000, you have a curve-fit strategy. The specific sequence of trades that produced the backtest is an outlier among possible orderings — in most parallel universes, the same trades lose money.
This is the fastest curve-fitting detector for EAs that pass a traditional backtest. It does not require out-of-sample data, walk-forward testing, or parameter sweeps. It works on the trade list you already have.