Monte Carlo Retirement Simulator
Run thousands of retirement scenarios using 150+ years of historical market data from 16 countries. Test fixed and dynamic withdrawal strategies, custom cash flows, and asset allocation — powered by Block Bootstrap sampling for realistic sequence-of-returns modeling.
Plan looks good, with room to optimize — consider tuning withdrawal or allocation.
Success Rate
84.7%
Funded Ratio
94.5%
Median Final Portfolio
7.32M
Mean Final Portfolio
18.05M
Initial Withdrawal Rate
4.0%
| Base withdrawal | 40,000 | 100.0% |
| Total | 40,000 | 100% |
Probability-weighted expected plan spending in today's purchasing power: probabilistic cash flows enter at their probability weight; this is not any single path. Dashed line: Monte Carlo mean recorded spending (depleted paths count as 0); shown only when the simulation matches current parameters.
Combines your simulated solvency with SSA 2021 life-table mortality (Gompertz fit, cohort-adjusted with a 0.7%/yr mortality-improvement assumption). At any age, the green band is the chance you are both alive and still funded.
box = P25–P75 · light band = P10–P90 · whisker = P5–P95 · ◆ Mean 18.05M （pulled up by the right tail）
Log scale · real (inflation-adjusted) amounts · based on 5,000 simulations
Show exact figures
| Metric | Value |
|---|---|
| Success Rate | 84.7% |
| Simulations | 5,000 |
| Mean Final Portfolio | 18,047,590 |
| Min Final Portfolio | 0 |
| P5 | 0 |
| P10 | 0 |
| P25 | 1,632,897 |
| P50 (Median) | 7,317,336 |
| P75 | 19,886,440 |
| P90 | 46,125,091 |
| P95 | 72,801,919 |
| Max Final Portfolio | 640,654,254 |
| --- | --- |
| Withdrawal Stats (Final Year) | |
| WD P5 | 0 |
| WD P10 | 0 |
| WD P25 | 40,000 |
| WD P50 | 40,000 |
| WD P75 | 40,000 |
| WD P90 | 40,000 |
| WD P95 | 40,000 |
| Mean Withdrawal | 33,833 |
| Metric | P10 | P25 | P50 | P75 | P90 |
|---|---|---|---|---|---|
| Ann. Nominal Return | 6.98% | 7.86% | 8.98% | 10.24% | 11.45% |
| Ann. Real Return | 3.68% | 4.74% | 6.01% | 7.27% | 8.54% |
| Ann. Inflation | 1.60% | 2.25% | 2.92% | 3.57% | 4.14% |
| Ann. Volatility | 11.78% | 13.04% | 14.54% | 16.15% | 17.48% |
| Max Real Drawdown | -54.47% | -53.67% | -36.60% | -32.61% | -28.95% |
| Ulcer Index | 7.52% | 9.35% | 11.89% | 15.01% | 18.52% |
| Max Underwater Years | 5.0 | 6.0 | 7.0 | 10.0 | 15.0 |
What this retirement simulator does
FIRE Lab runs thousands of Monte Carlo retirement paths using real historical market data instead of assumed average returns. Each path resamples multi-year blocks of stock, bond, and inflation history from 16 developed countries (1871–2025), preserving the momentum, volatility clustering, and cross-asset correlations that make sequence-of-returns risk real. The result is a full distribution of outcomes — not a single projection — plus a success rate and funded ratio for your plan.
Why Block Bootstrap sampling matters
Simple Monte Carlo tools draw each year independently, which understates the risk of long bear markets and inflationary decades. Block Bootstrap samples contiguous runs of history (5–15 years at a time), so simulated retirements experience realistic sequences like the 1970s stagflation or the 2000s lost decade in full. This typically produces more conservative — and more trustworthy — success rates than independent-draw simulators.
Withdrawal strategies and custom cash flows
You can test fixed inflation-adjusted withdrawals, Vanguard-style dynamic spending, declining consumption (EBRI), retirement spending smile, CAPE-based rules, and risk-based guardrails. Custom cash flows model pensions, Social Security, part-time income, or one-off expenses — including probabilistic scenario groups for events that may or may not happen.
Frequently asked questions
- Is this retirement simulator really free?
- Yes. All features — Monte Carlo simulation, historical backtesting, guardrail strategies, allocation optimization — are free to use with no account required.
- Should I use US-only or global pooled data?
- Global pooled data (16 countries, equal probability) gives a more conservative and robust baseline, since US history was exceptionally good. A common approach: plan with pooled data, then check the US dataset as an optimistic scenario.
- Are results inflation-adjusted?
- Yes. All simulations use real (inflation-adjusted) returns, and every amount shown — portfolio values, withdrawals — is in today's purchasing power.