In one paragraph
What is a Monte Carlo simulation for retirement planning?
A Monte Carlo simulation runs your retirement plan through thousands of randomly-generated market scenarios (RetireCiv uses 10,000 trials) to measure the probability your savings last as long as you need. Each trial varies investment returns, inflation, and the sequence of those events to reflect real-world uncertainty. The output is a success rate: for example, “your plan succeeds in 87% of simulated futures.” This page explains the methodology, what variables we model, and how to interpret your results.
What Is Monte Carlo?
A Monte Carlo simulation is a computational technique that uses random sampling to model the probability of different outcomes in a system with inherent uncertainty. It was originally developed by physicists working on the Manhattan Project and is now widely used in finance, engineering, and risk analysis.
Applied to retirement planning, Monte Carlo simulation answers a question that deterministic calculators cannot: given that markets, inflation, and your lifespan are all uncertain, what is the probability that your retirement income will last as long as you need it to?
A standard retirement calculator shows one projected future. RetireCiv's Monte Carlo simulation shows 10,000 possible futures, and tells you how often your plan succeeds across all of them.
How It Works
RetireCiv runs 10,000 independent simulation trials. In each trial, every uncertain variable (market return, inflation rate, sequence of returns) is randomly sampled from a probability distribution calibrated to historical data. Each trial produces a complete retirement income trajectory from your retirement date to your end-of-plan age.
Define your plan
Your retirement date, income sources (pension, TSP, Social Security), planned spending, and time horizon are used as the baseline for every trial.
Randomize the variables
For each of the 10,000 trials, market returns, inflation, and other variables are randomly drawn from their respective distributions, producing a unique sequence of economic conditions for that trial.
Run each trial to completion
The simulation projects your portfolio balance and income year by year, applying withdrawals, growth, and inflation adjustments until the end of your plan horizon.
Count successes and failures
A trial is a "success" if your portfolio remains solvent through your full planning horizon. A "failure" is any trial where your portfolio is depleted before the end of the plan.
Report the distribution
Results are reported as a probability distribution, showing the 10th, 25th, 50th (median), 75th, and 90th percentile outcomes, plus the overall success rate.
Variables Modeled
Every uncertain variable in your retirement picture is modeled probabilistically. RetireCiv uses historical distributions and configurable assumptions for each of the following:
TSP Market Returns
Annual returns for each TSP fund are sampled from a distribution based on long-term historical mean and standard deviation. The sequence of returns (order of good/bad years) is also randomized, a critical risk factor in early retirement.
Inflation Rate
General inflation is modeled as a random variable drawn from a distribution calibrated to historical CPI data, with configurable floor and ceiling. Your FERS COLA (Cost of Living Adjustment) is modeled separately.
Longevity Risk
Your plan horizon can be set to a fixed age or modeled probabilistically using actuarial life tables by gender and health status. The latter produces a distribution of outcomes weighted by actual survival probability.
Sequence of Returns Risk
Each trial generates a unique sequence of annual returns. Poor returns in the early years of retirement, while withdrawals are highest, can permanently impair a portfolio. Monte Carlo captures this risk precisely.
FERS COLA
Annual COLA adjustments to your FERS pension are modeled using a fixed 1.8% "diet COLA" assumption, consistent with the long-run average FERS COLA retirees have historically received. FERS COLA is always less than full CPI, making this a conservative and realistic baseline.
Part-Time or Bridge Income
If you plan to work part-time in early retirement, that income is included in the simulation for the years specified and phased out at your designated end date.
Reading Your Results
Your simulation results are presented as a probability distribution, a fan chart showing the range of possible portfolio values over time. Each band represents a different percentile of outcomes across all 10,000 trials.
Portfolio Value at End of Plan: Percentile Bands
90th percentile
Best-case outcomes
75th percentile
Above-average outcomes
50th (median)
Middle of all outcomes
25th percentile
Below-average outcomes
10th percentile
Worst-case outcomes
The median (50th percentile) represents the outcome you'd expect roughly half the time. The 10th percentile shows what your plan looks like in near-worst-case conditions. Planning to the 10th percentile produces a highly resilient retirement strategy.
Success Rate Explained
Your Success Rate is the percentage of the 10,000 simulation trials in which your portfolio remains positive through the end of your planning horizon. It is the single most important output of the simulation.
90%+: Excellent
95%
80–89%: Strong
85%
70–79%: Acceptable
75%
60–69%: Marginal
65%
Below 60%: At Risk
45%
What counts as success?
A trial is successful if your portfolio balance is ≥ $0 at the end of your planning horizon. It does not require a specific ending balance; any positive balance counts.
What is the planning horizon?
By default, RetireCiv plans to age 100, a conservative horizon that stress-tests your plan across a long retirement. You can adjust this downward; a shorter horizon will increase your success rate but reduces your safety margin.
What success rate should I target?
Most financial planners recommend targeting 85–90%+ for a robust retirement plan. FERS retirees often achieve higher success rates due to the pension and Social Security providing a guaranteed income floor that does not depend on portfolio performance.
Why not target 100%?
A 100% success rate requires extremely conservative withdrawal rates or large portfolios. For federal retirees with a guaranteed pension, targeting 85–90% is generally sufficient and avoids unnecessary lifestyle sacrifice.
Assumptions & Inputs
The simulation uses the following default assumptions, all of which are configurable in your RetireCiv settings:
Pre-retirement return
7.0% mean, 12% std dev
Growth-oriented allocation (equity-heavy, e.g., TSP L 2040+)
Post-retirement return
4.0% mean, 6% std dev
Conservative allocation (bond-heavy, e.g., TSP L Income)
Inflation rate
2.4% mean, 1.2% std dev
SSA 2024 Trustees Report ultimate long-run CPI-W projection
FERS COLA
1.8% fixed (diet COLA)
Conservative long-run FERS COLA average
Planning horizon
Age 100
Configurable; longer horizon = more conservative result
Withdrawal rate floor
Income need – fixed income
Only TSP withdrawals modeled; pension/SS treated as guaranteed
Number of trials
10,000
Fixed; sufficient for statistical stability
All assumptions can be overridden on the Monte Carlo settings page. Adjusted assumptions are saved locally in your browser and applied across all future simulation runs on the same device; your data never reaches our servers.
Simulation Engine
RetireCiv runs 10,000 trials per simulation. This produces statistically stable results; the success rate and percentile bands converge and change negligibly with additional trials beyond this count.
- Each trial generates a full year-by-year sequence of random returns and inflation rates using a normal distribution with configurable mean and standard deviation
- Returns are not serially correlated by default; each year's draw is independent. An autocorrelation mode (momentum/mean-reversion) is available in advanced settings
- The simulation uses the Box-Muller transform to generate normally distributed random variables from uniform random seeds
- Results are computed server-side and returned as a complete percentile matrix, not recalculated in your browser
- Simulation runtime is typically under 2 seconds for 10,000 trials
What a Good Result Looks Like
FERS retirees often achieve higher Monte Carlo success rates than private-sector retirees because their pension and Social Security provide a guaranteed income floor, income that does not depend on portfolio performance. This significantly reduces the portfolio withdrawal burden.
Example: Typical FERS Retiree at Age 62
With only $900/mo drawn from the TSP, the portfolio faces minimal depletion risk, resulting in success rates often exceeding 95%.
Limitations
Important: Read Before Relying on Results
Monte Carlo simulation is a powerful planning tool, but it has inherent limitations that every user should understand.
Historical distributions may not repeat
Return and inflation assumptions are calibrated to historical data. Future market conditions may differ materially, particularly in sustained low-return or high-inflation environments.
Normal distribution assumption
The simulation draws returns from a normal distribution. Real markets exhibit fat tails: extreme outcomes (crashes, windfalls) occur more frequently than a normal distribution predicts. Tail risk may be understated.
Spending is modeled as constant (real)
The simulation assumes your real (inflation-adjusted) spending remains constant. Actual retirement spending often declines in later years, which would improve real-world outcomes relative to the simulation.
Healthcare costs not separately modeled
FEHB premiums and out-of-pocket healthcare costs are not modeled as a separate, inflation-sensitive spending category. Consider adjusting your spending assumption to account for healthcare cost growth.
Tax treatment is simplified
The simulation does not model federal or state income tax on TSP withdrawals, pension income, or Social Security. A financial advisor can help you model after-tax income more precisely.
Not a substitute for professional advice
Monte Carlo results are estimates for planning purposes only. They do not constitute financial, tax, or legal advice. Consult a licensed financial planner before making retirement decisions.
Contact
Questions about the simulation methodology, assumptions, or how to interpret your results? We're happy to help.
RetireCiv Support
We typically respond within 2 business days.