Monte Carlo analysis
A probability-based simulation running thousands of scenarios to assess the likelihood of financial plan success.
Example
“The Monte Carlo analysis showed an 89% probability her retirement assets would last 35 years.”
Memory Tip
PROBABILITY — not certainty. Monte Carlo shows the range of possible outcomes.
Why It Matters
Monte Carlo analysis helps you understand the real probability of achieving your financial goals rather than relying on single-point estimates or best-case scenarios. By testing thousands of possible outcomes based on realistic market variations, you can make more confident decisions about retirement timing, savings rates, and investment strategies.
Common Misconception
Many people think Monte Carlo analysis predicts the future or tells you exactly what will happen with your money. In reality, it only shows the range of possible outcomes and their probabilities based on historical patterns and assumptions, not guaranteed predictions.
In Practice
Suppose you plan to retire with a 2 million dollar portfolio and need 80,000 dollars annually. A Monte Carlo simulation running 10,000 scenarios might show that in 92 percent of cases your money lasts 30 years, accounting for varying market returns, inflation, and withdrawal amounts. This 92 percent success rate helps you decide if you need to work longer or save more.
Etymology
Named after the Monte Carlo casino — using probability and randomness to model uncertainty.
Common Misspellings
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See Also
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