Monte Carlo Simulation
Reference model
Monte Carlo simulation helps visualize the range of possible outcomes based on variable uncertainty.
About this model
A computational algorithm that relies on repeated random sampling to obtain numerical results, often used to assess risk in financial and operational contexts.
Originator not stated.
How to read it
- Look for the distribution of outcomes to understand risk.
- Identify the most likely scenarios and their probabilities.
What this does
Models the probability of different outcomes in a process that cannot easily be predicted due to the intervention of random variables.
When to use it
Use it when you need to understand the impact of risk and uncertainty in financial forecasts or project plans.
Not when: Do not use it when the underlying processes are deterministic or when data is insufficient to create a meaningful model.
What happens next
Consider a sensitivity analysis to identify key drivers of risk.
Golden thread
Builds on ←
- Problem statement
- Risk assessment
Feeds into →
- Decision-making framework
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Drafted with AI and reviewed by Eccellere on 04/11/2026. Guidance, not advice: apply your own judgement.