Monte Carlo Simulation
Definition
A computational method that generates a probability distribution of valuation outcomes by running a large number of scenarios, each with input assumptions drawn randomly from defined probability distributions. Monte Carlo simulation is used in valuation analysis to produce a range of probable outcomes and their relative likelihoods, rather than a single point estimate. It is applicable when multiple key assumptions are uncertain and the interaction between them affects the outcome in non-linear ways.
Common Misapplication
The most common misapplication is using Monte Carlo simulation to produce a wide range of outputs from which a favourable scenario is then selected and presented without the distribution context. The purpose of Monte Carlo simulation is to present the full distribution of outcomes with their probabilities, not to generate a range from which a preferred number is extracted.
FFI Standard Reference
This term is defined and applied in Book 4, Section 4.7: Probabilistic Valuation Methods.
Related Terms
Citable URL
This term may be cited using the following permanent URL.
Full citation format: Founder Financial Infrastructure Standard, Beta v0.5, Glossary: Monte Carlo Simulation. https://ffistandard.org/glossary/monte-carlo-simulation/. 2026.