A Monte Carlo Analysis is a randomized computer trial used to test various financial scenarios. The term originated during World War II, when scientists used random sampling to simulate atomic reactions.
A Monte Carlo Analysis offers a “stress test” for one’s long-term financial plan. The analysis simulates hundreds or thousands of randomized return sequences using historical risk and returns data. Next, the analysis considers the individual’s spending needs and accounts for necessary portfolio withdrawals. The end results show the financial plan’s sustainability under the best-case and worst-case market scenarios. Contrast this with a static analysis that applies a fixed rate of return for the duration of the plan. This simplified approach does not account for inevitable market volatility and timing risks.
The exact methodology depends on the planner. It is common to run 1,000 simulations and target a success rate of 80%. Put simply, this means the plan has sufficient resources to cover all spending needs in at least 800 of the 1,000 trials. Monte Carlo projections are by no means predictive. Rather, the analysis is intended to illustrate the random and unpredictable nature of portfolio performance. Any analysis is dictated by its inputs. Scrutiny should be given to risk, return, and spending assumptions to ensure the analysis adequately reflects the individual’s circumstances.
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