A Monte Carlo simulation is a computational algorithm that relies on repeated random sampling to model the probability of different outcomes in a process that cannot easily be predicted due to the intervention of random variables.
In finance, it uses historical metrics—like expected return, volatility, and the covariances between assets—to generate 10,000 or more possible future market paths (using Geometric Brownian Motion or bootstrapping). This allows investors to shift from asking 'How much will I have?' to 'What is the probability I will have enough?'
StressTest.pro uses institutional-grade Monte Carlo engines to show you the 10th percentile (pessimistic), 50th percentile (median), and 90th percentile (optimistic) projected wealth targets over long horizons.