HomeMonte Carlo Simulation

Monte Carlo Simulation

Retirement planning isn't a single number; it's a range of possible futures. Monte Carlo simulation models thousands of those futures so you can see the full picture of your retirement security.

Methodology UpdatedSeptember 15, 2026

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 by default) to measure how often your income covers your spending in every simulated year. 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 by default, and tells you how often your plan succeeds across all of them.

How It Works

RetireCiv runs 10,000 independent simulation trials by default (1,000 and 50,000 are selectable). 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.

01

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.

02

Randomize the variables

For each trial, market returns, inflation, and other variables are randomly drawn from their respective distributions, producing a unique sequence of economic conditions for that trial.

03

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.

04

Count successes and failures

A trial is a "success" if your income covers your spending in every simulated year: your annuity, any SRS bridge until 62, Social Security, VA compensation, pensions, other income you entered (for example rental or part-time income) and portfolio withdrawals together, plus your spouse’s streams when entered, against the spending you chose. A "failure" is any trial with a year the plan cannot fund. A retiree whose pension covers spending can exhaust the portfolio entirely and still succeed.

05

Report the distribution

Results are reported as a probability distribution, showing the 20th, 50th (median), and 80th 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

Each trial draws a lifespan from a distribution around the life-expectancy range you set, capped at the top of that range and floored at five years past your retirement age (never in the past). With a spouse modeled, their lifespan is drawn separately and the household runs to the later of the two deaths.

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 at a 1.8% default, consistent with the long-run average FERS COLA retirees have historically received, and adjustable in Settings. FERS COLA runs below full CPI in high-inflation years, making this a conservative and realistic baseline.

Part-Time or Bridge Income

Other income you entered, such as rental, part-time, or business income, is paid at that amount in every simulated retirement year, with no COLA applied and no end date, because the calculator does not collect one.

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 trials in the run.

Portfolio Value at End of Plan: Percentile Bands

80th percentile

Above-average outcomes

50th (median)

Middle of all outcomes

20th percentile

Below-average outcomes

The median (50th percentile) represents the outcome you'd expect roughly half the time. The 20th percentile (the lower band the simulation reports) shows what your plan looks like when markets run against you for years at a stretch. Planning to the 20th percentile produces a resilient retirement strategy.

Success Rate Explained

Your Plan Success Rate is the percentage of simulation trials in which your income covers your spending in every simulated year: your annuity, any SRS bridge until 62, Social Security, VA compensation, pensions, other income you entered (for example rental or part-time income) and portfolio withdrawals together, plus your spouse's streams when entered, against the spending you chose. A retiree whose guaranteed income covers spending can exhaust the portfolio entirely and still succeed. It is the single most important output of the simulation.

90%+: High confidence

95%

75–89%: Moderate

82%

60–74%: At risk

67%

Below 60%: Low confidence

45%

What counts as success?

A trial is successful if your income covers your spending in every simulated year. A shortfall year (spending the plan cannot fund) fails the whole trial, even if some balance remains at the end.

What is the planning horizon?

The top of your life-expectancy range (90 by default), adjustable on the simulation page. With a spouse modeled, each run continues to the later of the two deaths. 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 seeds these defaults, all of which are adjustable with the sliders on the simulation page before every run:

Pre-retirement return

7.0% mean, 3.0% std dev

Growth-oriented allocation (equity-heavy, e.g., TSP L 2040+)

Post-retirement return

4.0% mean, 2.0% std dev

Conservative allocation (bond-heavy, e.g., TSP L Income)

Inflation rate

2.5% mean, 1.0% std dev

Long-run CPI band centered near the Federal Reserve target

FERS COLA

1.8%/yr from age 62

Settings default; adjustable, applied per the FERS COLA rules

Planning horizon

Age 90

Top of the life-expectancy slider; longer horizon = more conservative result

Spending level

55–80% of pre-retirement income

Pension and Social Security cover it first; the portfolio funds the rest

Number of trials

10,000 (standard)

Three depths: 1,000, 10,000, or 50,000 trials

Every row above is adjustable with the sliders and depth selector on the simulation page. The COLA and withdrawal assumptions come from Settings and are saved locally in your browser; your data never reaches our servers.

Simulation Engine

RetireCiv runs 10,000 trials per simulation at the standard depth (1,000 and 50,000 are selectable). That count 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; each year's draw is independent
  • The simulation uses the Box-Muller transform to generate normally distributed random variables from uniform random seeds
  • Every trial runs in your browser. No input, intermediate value, or result is sent to a server
  • 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

FERS Pension (guaranteed)$2,800/mo
Social Security$1,600/mo
TSP Withdrawal$900/mo
Total Monthly Income$5,300/mo

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 follows the curve you choose

Real (inflation-adjusted) spending follows your selected spending pattern: constant by default, with retirement-smile and declining options in Settings. Research on actual retiree spending motivates the non-constant curves.

Out-of-pocket healthcare not separately modeled

With the optional Taxes & Deductions estimate on, FEHB, FEGLI, FEDVIP and Medicare premiums are modeled in the after-tax view. Out-of-pocket healthcare beyond premiums is not a separate spending category; consider padding your spending assumption for it.

Tax treatment is simplified

With the optional Taxes & Deductions estimate on, a second pass models federal tax, the Social Security provisional-income rule, and an approximate state rate on the same simulated draws. The state rate applies your state’s modeled retirement-income exclusion where it has one. The IRS Simplified Method and capital-gains treatment are not modeled. With the estimate off, results are pre-tax.

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.

support@retireciv.com