Back to Glossary
Monte Carlo Simulation
Definition
Monte Carlo simulation models portfolio evolution by generating many possible sequences of asset returns — called paths — and tracking portfolio value through time along each path. Each path represents one possible market environment. By aggregating results across thousands or millions of paths, the method produces a probability distribution of outcomes rather than a single deterministic forecast. For endowments, this means understanding not just the expected terminal value but the full range of possible outcomes, including tail risks at the 5th and 1st percentiles.
In the Context of Endowment Management
Monte Carlo simulation has become the standard analytical framework for institutional portfolio decision-making because it directly addresses the question investment committees most need answered: not "what will happen" but "how bad could it get, and how likely is that?" The method is particularly valuable for evaluating spending policy sustainability, asset allocation trade-offs, and compliance risk across market regimes.