Monte Carlo Simulation
A method that runs your plan through hundreds or thousands of randomized market scenarios to estimate the probability it succeeds.
A Monte Carlo simulation tests a financial plan against uncertainty by running it many times — often a thousand or more — each with a different randomized sequence of market returns drawn from realistic ranges. Instead of a single projection, you get a distribution of outcomes and a success probability, like 'this plan survived in 87% of scenarios.'
Its value is honesty about risk. A single straight-line projection at an average return hides sequence of returns risk and makes a plan look more certain than it is. Monte Carlo surfaces the range — including the unlucky paths — so you can see how much margin you actually have.
The output is only as good as the assumptions feeding it: the return and volatility ranges, the inflation model, and your spending estimate. A high success percentage isn't a guarantee, and a moderate one isn't a failure — it's information to weigh against your own flexibility and risk tolerance.
This definition is general information to help you understand a term, not financial, tax, or legal advice. Figures that change year to year (limits, thresholds, rates) should be confirmed against current official sources. For guidance on your situation, a licensed fee-only fiduciary is the right next step.