What is Monte Carlo simulation for retirement planning?

Monte Carlo simulation tests your retirement plan against 1,000+ randomized market return sequences to estimate your probability of success (never running out of money). Unlike average-return projections, it captures sequence-of-returns risk — the danger that a market crash in your first few retirement years permanently impairs your portfolio.

Formula

Success Rate = (Scenarios where portfolio > $0 at death) ÷ Total scenarios × 100%

Example

Plan: $2M portfolio, $80k/year withdrawals, 40-year retirement. Average projection: works fine at 7%. Monte Carlo: 87% success rate — 13% of random sequences lead to running out. Solution: reduce to $70k or build a 2-year cash buffer → 96% success.

How it works in detail

A simple projection using average 7% returns always looks fine. But real markets don't return 7% every year — they might return +25%, -15%, +8%, -30% in sequence. Monte Carlo randomly shuffles historical returns to simulate thousands of possible market histories. Your 'success rate' is the percentage of scenarios where your money lasts. 90%+ is generally considered safe. The key insight: retiring into a 2008-style crash is far more dangerous than experiencing one mid-retirement, because you're withdrawing from a shrinking base. This is 'sequence-of-returns risk' and only Monte Carlo reveals it.

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