Monte Carlo Portfolio Simulation
Run thousands of random scenarios to forecast portfolio outcomes and assess risk probabilities.
Success probability = P(final value ≥ target)
Adjust results for purchasing power
Monte Carlo simulation uses random sampling to model the probability of different outcomes in financial forecasting. By running thousands of simulations with varying assumptions, it provides a range of possible portfolio values and their likelihoods.
Uses historical return data to estimate expected returns and volatility for each asset.
The fan chart shows the range of possible outcomes over time. Wider bands indicate greater uncertainty. The median (P50) line represents the most likely outcome, while P5 and P95 show extreme scenarios.