Retirement Withdrawal Simulator

Monte Carlo analysis of portfolio longevity & sequence-of-returns risk

Simulation Parameters
Fixed dollar amount each year, nominal.
4.00%
$40,000 / $1,000,000
60%
40% fixed income
1,000
Running simulations…
Simulation Results
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Success Rate
portfolio lasted full period
—
Median Years Survived
—
Worst Case (10th %ile)
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Best Case (90th %ile)
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Ruin Probability
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Median Final Value
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Median Deplete Year
Portfolio Projection — Fan Chart
25th–75th Percentile
10th–25th / 75th–90th Percentile
Below 10th Percentile
Constant Return (no volatility)
Frequently Asked Questions
What is Monte Carlo simulation for retirement?
Monte Carlo simulation is a computational technique that runs thousands of random scenarios to model the uncertainty in retirement outcomes. Instead of assuming a single average return, it generates many possible market trajectories based on historical volatility and return patterns. For each scenario, the simulator tracks how a portfolio performs year by year given your withdrawal rate. The result is a distribution of outcomes — from best case to worst case — giving you a probabilistic sense of how likely your retirement plan is to succeed.
What is sequence of returns risk?
Sequence of returns risk is the danger that poor market returns early in retirement — combined with ongoing withdrawals — permanently damages a portfolio before it has time to recover. A 30% loss in year one followed by 15% gains later is far worse for a retiree than the same 30% loss in year fifteen. This is because early losses are compounded by withdrawals taken from a shrunken base. Monte Carlo simulation captures this by running many randomized return sequences, making it the most realistic way to assess this risk.
What is the 4% rule?
The 4% rule is a retirement planning guideline suggesting you can safely withdraw 4% of your initial portfolio value each year (adjusted for inflation) and have a high probability of your money lasting 30 years. It was popularized by the Trinity Study and is based on historical U.S. stock and bond returns. In today's environment with lower expected returns, some planners suggest 3–3.5% is more prudent. This simulator lets you test any withdrawal rate to see how it affects your personal success probability.
How does asset allocation affect retirement success?
Asset allocation — the split between stocks and bonds — is one of the most powerful levers in retirement planning. Stocks offer higher long-term returns but more year-to-year volatility. Bonds provide stability and negative correlation to stocks in downturns, but lower expected real returns. A 60/40 portfolio has historically offered a good balance for retirees: enough growth potential to sustain 30+ years of withdrawals, with enough bonds to cushion early-sequence losses. This simulator lets you test any split from 0% to 100% stocks to find what works for your risk tolerance.
What is the difference between fixed and inflation-adjusted withdrawals?
Fixed withdrawals mean you take the same inflation-adjusted dollar amount every year — if you withdraw $40,000 in year one, you withdraw $40,000 (nominal dollars) in year 30. Inflation-adjusted withdrawals increase each year with inflation — preserving your purchasing power. If inflation runs at 2.5% and you withdraw $40,000 in year one, you'd withdraw $41,000 in year two. Inflation-adjusted withdrawals are more realistic for a 30+ year retirement but significantly increase the total amount withdrawn over time, raising the risk of portfolio depletion.
How many simulation paths should I run?
More paths always produce more stable results. With 500 paths, you'll see meaningful trends but some statistical noise. 1,000 paths is a good default — it gives stable percentile estimates without long wait times. 5,000–10,000 paths are useful when you need high precision, such as when comparing two very similar withdrawal strategies. The default in this simulator is 1,000, which balances accuracy and responsiveness for real-time use.
What does the fan chart show?
The fan chart displays the full distribution of simulated portfolio outcomes over time. Each colored band represents a percentile range of outcomes: the darkest green shows the 25th to 75th percentile (where half of all simulations fall), lighter green shows 10th to 25th and 75th to 90th, and red shows the lowest 10th percentile. The dashed white line shows what would happen under a constant average return (no volatility) for comparison. Watching how quickly the fan widens over time shows how uncertainty compounds — and how the worst scenarios diverge from the median.
What is a safe withdrawal rate?
A safe withdrawal rate (SWR) is the annual withdrawal rate that gives a high probability (typically 90–95%) of a portfolio lasting a specified period, such as 30 years. The 'right' SWR depends on your time horizon, asset allocation, and personal risk tolerance. Historically, 4% of initial portfolio value has been considered safe for a 30-year retirement with a 60/40 portfolio. Lower rates (3–3.5%) are more conservative; higher rates (5–6%) dramatically increase ruin probability. This simulator lets you find the withdrawal rate that matches your target success probability.
How does withdrawing a percentage of portfolio work?
Withdrawing a percentage of the current portfolio value means your dollar withdrawal scales with market performance. In a down year, you withdraw less; in an up year, you withdraw more. This is naturally self-regulating — you spend less when the market is weak and more when it's strong. The risk is that a severe early downturn could force very low withdrawals, potentially failing to meet needs. This approach offers downside protection but sacrifices predictable income. Many dynamic withdrawal strategies use this as a base with a floor and ceiling.
Why do some paths run out of money while others don't?
Because market returns vary randomly. A retiree who happens to face a severe bear market in years 1–3 and then strong returns thereafter is far more likely to run out of money than one who faces strong returns early (allowing the portfolio to grow before any major losses). Since we cannot predict which sequence of returns we'll get, Monte Carlo simulation samples thousands of possible sequences and reports the probability distribution of outcomes. Even if the median outcome looks fine, the 10th percentile outcome — the bad-luck scenarios — is what determines your ruin probability.