How it works

Methodology

The full math, the data sources, and the gaps we’re honest about.

Last reviewed May 27, 2026

Editorial review pending — see editorial process

This page is for the careful reader. If you want to know exactly how Yearfold turns your inputs into a success probability, this is the long version. If you have something to flag — a number that looks wrong, a 2026 rule we missed, a citation that doesn't hold up — write to hello@yearfold.com. We update this page whenever a data source changes.

The 30-second version

You give Yearfold five inputs (your age, your savings, your monthly contribution, your target retirement age, and your monthly retirement spending). The engine plays out 10,000 simulated retirements against real US market history from 1928 to 2025, with returns and inflation paired month-by-month so the correlations are honest. For each simulated future it tracks your portfolio month by month from now to age 95, applies Social Security and Medicare under the 2026 rules, and records the balance trajectory. The output is a probability distribution — not one cheerful number — plus three concrete fixes when you're not on track.

What "Monte Carlo" actually means here

Monte Carlo simulation was invented in the late 1940s by Stanislaw Ulam and John von Neumann at Los Alamos, originally to model neutron diffusion in atomic-bomb cores. Ulam reportedly came up with the technique while playing solitaire in recovery from an illness — wondering how to estimate his odds of winning, he realised the calculation was easier if you just dealt the cards a thousand times and counted. The name was Nicholas Metropolis's, after Ulam's uncle who borrowed money to gamble at Monte Carlo. The technique migrated into finance in the 1960s as computers got cheap enough to run thousands of trials, and is now standard inside every major brokerage and pension fund.

The principle is simple: when a problem has too many variables to solve analytically, replay the past — in different orders, with random sampling — many thousands of times, and read the answer off the resulting distribution.

Monte Carlo simulation is a way of answering "what's likely to happen?" by replaying the past, in different orders, ten thousand times.

For each of those 10,000 simulated retirements, we step through your life month by month from your current age to age 95. At each step we apply a market return drawn from history, an inflation rate drawn from the same month, your contributions while working, your withdrawals once retired, and any Social Security income. We record your portfolio balance at every age.

Across the 10,000 paths, we then ask:

  • In how many did your money outlast you to age 95? (success probability)
  • What was the median portfolio balance at each age? (P50 line)
  • What did the worst 1-in-10 path look like? (P10 — the "rough seas" outcome)
  • What did the best 1-in-10 look like? (P90 — the "calm" case)
  • For the failed paths: at what age did the money run out? (depletion distribution)

The output isn't a forecast. It's a stress test of your plan against scenarios that have actually happened in US economic history.

What other calculators show — vs what reality actually looks like.

Illustrative

The dashed line is the smooth 7%-a-year projection most retirement calculators produce. The green band is the range a 10,000-path Monte Carlo produces from the same inputs. The dashed line lives in the middle of the band — but in any given run, your real path could land anywhere inside it.

Single-line projection vs Monte Carlo fanA line chart over 30 years of retirement. A dashed terracotta line shows the cheerful 7%-a-year projection that most retirement calculators display — growing smoothly from $1,000,000 to about $2,180,000. Behind it, a green band shows the 10th-to-90th percentile range of outcomes a Monte Carlo simulation produces from the same inputs: the median ends near $1.2 million, the 10th percentile depletes around year 20, and the 90th percentile ends near $8.5 million.$0$1.0M$2.0M$3.0M$4.0M$5.0M$6.0M$7.0M$8.0M$9.0MYear 0Year 5Year 10Year 15Year 20Year 25Year 30Years into retirementMonte Carlo P10–P90 rangeMedian path (P50)Cheerful 7%-a-year line
View data table
YearSingle-line 7% projectionMonte Carlo P10Monte Carlo median (P50)Monte Carlo P90
0$1,000,000$1,000,000$1,000,000$1,000,000
5$1,172,522$750,000$1,100,000$1,600,000
10$1,414,493$500,000$1,300,000$2,500,000
15$1,753,871$200,000$1,500,000$4,000,000
20$2,229,865$0$1,600,000$5,500,000
25$2,897,471$0$1,400,000$7,000,000
30$3,833,824$0$1,200,000$8,500,000

Source: Illustrative simulation calibrated to S&P 500 1928–2025 bootstrap (Shiller / NYU Stern) · Last reviewed May 26, 2026

The historical data

We use monthly returns from 1928 through 2025 (98 years, 1,176 months) for two asset classes:

  • US large-cap stocks — S&P 500 total return (price + reinvested dividends).
  • US 10-year Treasuries — total return (yield + price change from yield moves).

Inflation comes from the CPI-U index (Consumer Price Index for All Urban Consumers), published monthly by the Bureau of Labor Statistics.

These three series are drawn jointly from the same historical month. If a simulated path samples June 1932, it gets June 1932's stock return, June 1932's bond return, and June 1932's inflation rate together. This preserves the correlation between asset classes and the macroeconomic regime — bond/stock correlations are not constant over time, and naive independent sampling would understate joint risk.

Why bootstrap, not parametric simulation

A common alternative to historical bootstrap is parametric simulation — assume returns are log-normally distributed with mean μ and standard deviation σ, then draw from that distribution. We don't, for two reasons:

  1. Real returns aren't log-normal. Equity markets have fat tails. Crashes happen more often than a Gaussian would predict, and they happen in clusters (volatility persists). Bootstrapping from real history captures this.
  2. Returns aren't independent across months. There's measurable serial correlation in volatility regimes. The 1929-1932 sequence of monthly returns isn't well described by independent draws from a single distribution.

The honest tradeoff: bootstrap restricts you to the regimes that have already happened. The next 30 years could include a regime worse than anything in 1928-2025. We think that's a fair limitation to acknowledge — and it's why we publish the P10 band and the depletion distribution, not just the median.

Asset allocation

You pick one of three preset allocations on the calculator. Each is a fixed mix of stocks and bonds:

  • Conservative: 30% stocks / 70% bonds
  • Balanced: 60% stocks / 40% bonds
  • Growth: 80% stocks / 20% bonds

Each simulation rebalances monthly back to your target weights. Real-world cash positions, alternative assets, and individual security holdings are not modeled — they fold into the broad asset-class returns above.

In a future release we'll let you specify a glide path (more conservative as you age) and add a real-estate / REIT class.

Five cohorts. Same plan. Five very different decades.

$1,000,000 starting balance, $40,000 withdrawn in year 1 then increased each year for actual CPI, over 30 years of retirement. The only thing that differs is the year the retiree retired into. Balances are in real (start-year) dollars.

Historical retirement cohorts: same $1M plan, five different decadesA line chart over 30 years of retirement showing real (inflation- adjusted) portfolio balance for five retirement cohorts that all started with $1,000,000 and withdrew $40,000 in year 1 adjusted for actual CPI thereafter. The 1929 cohort depletes around year 22 under the Great Depression and post-war inflation. The 1966 and 2000 cohorts end below $300,000. The 1973 cohort ends near $725,000. The 2008 cohort, in the post-GFC bull market, reaches about $2.1 million by year 18. Same plan, very different outcomes driven entirely by what decade the retiree happened to retire into.$0$500k$1.0M$1.5M$2.0M$2.5MY0Y5Y10Y15Y20Y25Y30Years since retirement1929 (to 1950)196619732000 (to 2025)2008 (to 2025)1929 · Great Depression1966 · Stagflation onset1973 · Oil shock2000 · Dot-com crash2008 · Global Financial Crisis
View data table
Years since retirementRetire 1929Retire 1966Retire 1973Retire 2000Retire 2008
0$1,000,000$1,000,000$1,000,000$1,000,000$1,000,000
5$441,500$766,902$504,857$574,628$740,720
10$424,950$483,555$405,946$333,515$1,184,476
15$189,740$395,539$495,242$347,013$1,350,362
20$50,325$334,681$602,393$299,901— (data ends 2025)
25— (data ends 2025)$294,384$1,003,853$241,987— (data ends 2025)
30— (data ends 2025)$287,190$724,678— (data ends 2025)— (data ends 2025)

Source: S&P 500 1928–2025 (Damodaran / NYU Stern) · CPI (US BLS) · series rebuilt in lib/monte-carlo/historical-returns.ts · Last reviewed May 26, 2026

Social Security

We compute Social Security benefits using the 2026 SSA rules:

  1. AIME (Average Indexed Monthly Earnings) — your highest 35 years of earnings, indexed to the year you turn 60. If you don't enter an earnings record, we estimate AIME from your current household income.
  2. PIA (Primary Insurance Amount) — applies the 2026 bend points ($1,226 and $7,391) and the 90/32/15 percentage formula to your AIME.
  3. Claim age adjustment — claiming at 62 reduces your benefit by 30% (assuming FRA = 67); claiming at 70 increases it by 24%. The adjustments are linear within each year.
  4. Spousal and survivor benefits — for couples, we compute each spouse's own benefit and the spousal benefit (50% of the higher earner's PIA), then take the greater. On the first death, the survivor switches to the higher of the two benefits.
  5. COLA (Cost of Living Adjustment) — each January, we apply the simulated year's inflation rate as the COLA. This means Social Security real income stays roughly flat through inflation regimes.

What we don't model yet:

  • WEP / GPO offsets for non-covered government employees.
  • Spousal benefit reductions for early claiming when the higher earner has not yet claimed.
  • Disability or auxiliary benefits.

Cumulative Social Security by claim age.

Cumulative lifetime Social Security benefits for a worker with a $3,000/month Primary Insurance Amount at full retirement age (67), claimed at 62, 67, or 70. The dashed verticals mark the break-even ages — where claiming later finally overtakes claiming earlier.

Cumulative Social Security by claim ageThree lines showing cumulative Social Security benefits from ages 62 to 95 for a worker with a $3,000-a-month PIA. Claiming at 62 starts earliest at $2,100 a month and pulls ahead until about age 79. Claiming at the full retirement age of 67 starts at $3,000 a month and overtakes the age-62 line around 79, then is overtaken by the age-70 line around 82-83. Claiming at 70 starts latest at $3,720 a month but produces the highest cumulative benefit for anyone who lives past about age 83.$0$200k$400k$600k$800k$1.0M$1.2MAge 62Age 67Age 70Age 75Age 80Age 85Age 90Age 95Current age≈ age 7962 vs 67≈ age 8367 vs 70Claim at 62Claim at 67 (FRA)Claim at 70
View data table
AgeClaim at 62 ($2,100/mo)Claim at 67 ($3,000/mo)Claim at 70 ($3,720/mo)
62$0$0$0
67$126,000$0$0
70$201,600$108,000$0
75$327,600$288,000$223,200
79$428,400$432,000$401,760
80$453,600$468,000$446,400
83$529,200$576,000$580,320
85$579,600$648,000$669,600
90$705,600$828,000$892,800
95$831,600$1,008,000$1,116,000

Source: SSA — Retirement Benefits: Effect of Early or Delayed Retirement · Last reviewed May 26, 2026

Couples: claim together, or stagger?

Illustrative

Two PIAs ($2,000/mo and $3,000/mo at full retirement age). Strategy A: both claim at FRA (67). Strategy B: lower earner claims at 62 (-30%), higher earner waits to 70 (+24%). Both spouses live to 85; lower-earner spouse survives to 95 and picks up the higher benefit. The big win in Strategy B is the survivor benefit, not the years both spouses are alive.

Couples Social Security: claim together vs staggerTwo horizontal bars comparing lifetime household Social Security benefit under two claim strategies for a couple. Strategy A (both claim at full retirement age 67) totals about $1.5M. Strategy B (lower earner claims at 62, higher earner waits to 70) totals about $1.5M, a difference of about $71k driven largely by the surviving spouse inheriting the higher-claim benefit.$0$200k$400k$600k$800k$1.0M$1.2M$1.4M$1.6MCumulative household benefit (nominal $)A · Both at 67$1.5MB · 62 / 70 stagger$1.5M+$71kSurvivor at 85+ inherits $3,000/moSurvivor at 85+ inherits $3,720/moFRA = age 67 · PIAs $2k / $3k · joint life to 85/95
View data table
PhaseYearsStrategy A (both at 67)Strategy B (62 / 70)
62–66 (lower active, higher delaying)5$0$84,000
67–69 (FRA reached for both)3$180,000$50,400
70–84 (both claiming)15$900,000$921,600
85–95 (lower survives, survivor benefit kicks in)11$396,000$491,040
Total lifetime household benefit$1,476,000$1,547,040

Source: SSA — Retirement Benefits + Survivors Benefits · Last reviewed May 26, 2026

Medicare

For retirees age 65+, we apply 2026 Medicare costs:

  • Part B base premium: $202.90/month (2026 CMS-final).
  • Part D base premium: $38.99/month (2026 national base beneficiary premium).
  • IRMAA surcharges for high-MAGI households: tiered surcharges based on the 2026 IRMAA brackets, applied per-spouse for couples. First-tier MAGI thresholds: $109,001 (single) / $218,001 (married filing jointly); top tier: $500,000 / $750,000. See The IRMAA cliff for the full bracket table and the 2-year-lookback mechanic.

Healthcare is the single biggest source of variance in retirement spending. Our defaults assume Medicare A (free), B + D plus a Medigap premium of approximately $200/month per person. Long-term care costs are NOT modeled — that's a separate risk requiring dedicated insurance or self-funding.

Inflation

Inflation is sampled jointly with returns (see above). For Social Security COLA and for inflation-adjusting your monthly retirement spending target, we use the simulated year's CPI-U change.

When your inputs are in "today's dollars" (e.g., your $5,000/month spending target), we inflate them year over year so the real purchasing power stays constant.

Federal income tax

We apply the 2026 federal tax brackets:

  • Standard deduction — $15,750 single, $31,500 married filing jointly.
  • Marginal brackets — 10% / 12% / 22% / 24% / 32% / 35% / 37%.
  • Social Security taxation — up to 85% of benefits taxable depending on combined income; we apply the standard 1983 / 1993 worked formula.
  • RMDs (Required Minimum Distributions) start at age 73 for traditional IRAs and 401(k)s, using the 2022 SECURE 2.0 Uniform Lifetime Table.

For a plain-English breakdown of what the 2026 federal brackets are and why they look this way after the One Big Beautiful Bill Act made them permanent, see The TCJA cliff was averted.

What we don't model:

  • State income tax. Florida, Texas, and a handful of other states have no state income tax; California and New York are above 9% at retirement-relevant income levels. State tax can move your effective retirement tax rate by several percentage points. Add it manually if it matters for your situation.
  • Capital gains brackets. All taxable income is treated as ordinary for now.
  • Roth conversion ladders.
  • Tax-loss harvesting.

These will land in the Pro tier in 2027.

Withdrawal strategy

In retirement, your monthly spending target (in today's dollars, inflated to the simulated year) is funded in this order:

  1. Pre-tax accounts (Traditional IRA / 401(k)) until RMDs begin at 73.
  2. Taxable accounts when funded.
  3. Roth accounts last (so they continue compounding tax-free).

This is a simplified version of the "tax-efficient withdrawal" approach commonly recommended by fee-only advisors. It is NOT the only valid strategy — for some households, a small Roth conversion ladder during low-income early retirement years materially improves outcomes. Yearfold doesn't simulate that yet.

Same 7% average. Very different outcomes.

Illustrative

Two retirees both start with $1,000,000 and withdraw $40,000 a year for 20 years. Both earn an arithmetic-mean 7% return. The only difference is the order the returns arrive in.

Sequence-of-returns riskA line chart comparing two retirement balance trajectories over 20 years. Both start at $1,000,000 with $40,000 annual withdrawals. The bad-first trajectory drops sharply in the first five years and ends near $46k. The good-first trajectory rises quickly, peaks around $5.8M, and ends at $2.4M, despite both sequences having the same 7% arithmetic-mean return.$0$1.0M$2.0M$3.0M$4.0M$5.0M$6.0MYear 0Year 5Year 10Year 15Year 20Years into retirementBad-first ends $46kGood-first ends $2.4MBad returns firstGood returns first
View data table
YearBad-first returnBad-first balanceGood-first returnGood-first balance
0 (start)$1,000,000$1,000,000
1-15%$810,00023%$1,190,000
2-15%$648,50023%$1,423,700
3-15%$511,22523%$1,711,151
4-15%$394,54123%$2,064,716
5-15%$295,36023%$2,499,600
610%$284,89610%$2,709,560
710%$273,38610%$2,940,516
810%$260,72410%$3,194,568
910%$246,79710%$3,474,025
1010%$231,47610%$3,781,427
1110%$214,62410%$4,119,570
1210%$196,08610%$4,491,527
1310%$175,69510%$4,900,680
1410%$153,26510%$5,350,748
1510%$128,59110%$5,845,823
1623%$118,167-15%$4,928,949
1723%$105,345-15%$4,149,607
1823%$89,575-15%$3,487,166
1923%$70,177-15%$2,924,091
2023%$46,317-15%$2,445,477

Source: Constructed example calibrated to S&P 500 1928–2025 return distribution (Shiller / NYU Stern) · Last reviewed May 26, 2026

Spending guardrails

The withdrawal strategy above answers "which accounts do I draw from?" The Spending Guardrails feature (Yearfold Pro) answers the question every retiree actually asks each year: "how much can I safely spend this year?"

It uses the Guyton-Klinger decision rules — the most widely understood framework for dynamic withdrawals. Instead of the static "4% rule" (spend a fixed, inflation-adjusted amount no matter what markets do), Guyton-Klinger flexes your spending within two guardrails:

  • Withdrawal rule — start at a chosen rate (we derive yours from your plan, clamped to a sane 3–7%) and adjust for inflation each year.
  • Capital Preservation rule (a "cut") — if a downturn pushes your current withdrawal rate more than ~20% above your starting rate, trim spending by ~10%. You trim only when you cross the guardrail, not on every dip.
  • Prosperity rule (a "raise") — if strong markets pull your rate more than ~20% below your starting rate, you can raise spending by ~10%.
  • Modified inflation rule — skip the inflation raise in any year your portfolio lost money.
  • Guardrails are suspended in roughly the final 15 years of the horizon (less time to recover), and all of these are adjustable.

Every number is computed by the same deterministic engine and historical-bootstrap data described above — applied year by year, in today's dollars. We also report the success probability of following the guardrails versus spending a fixed amount, so you can see what the discipline is worth. This is an educational framework for sizing a spending range; it is not advice, and it never tells you which specific account or fund to draw from.

Primary source: Jonathan Guyton & William Klinger, "Decision Rules and Maximum Initial Withdrawal Rates" (Journal of Financial Planning, 2006) — the original framework.

What we don't simulate

We've been honest about the gaps already, but here's the consolidated list. None of these are in v1; some are planned for 2027:

  • State income tax
  • Long-term care insurance and self-funded LTC costs
  • Healthcare events that breach Medicare's out-of-pocket maximums
  • Social Security claim-age dynamic optimization (we let you pick a fixed claim age; we don't search for the optimal one across life-expectancy distributions yet — there's a separate "Claim age explorer" tab on the results page that runs every age from 62 to 70)
  • Annuity products (SPIAs, deferred annuities, QLACs)
  • Real estate income, mortgage payoff strategy, reverse mortgages
  • Self-employment retirement vehicles (SEP-IRA, Solo 401(k), defined-benefit cash-balance plans) beyond simple contribution amounts
  • Behavior — selling at the bottom, panic moves, holiday spending
  • Sequence-of-returns hedging strategies (bond tents, rising equity glide paths, bucket strategies)
  • Inheritance, gifts, lottery wins

Numerical and software notes

  • Random number generator. We use a seeded mulberry32 PRNG so simulations are reproducible. The default seed is derived from the current timestamp; pass a fixed seed in tests for byte-stable output.
  • Floating point. All money is stored as number (IEEE 754 double precision). Compounded over 70 years × 10,000 paths, accumulated rounding is well below the precision of any input you'd enter. We round to whole dollars only on display.
  • Web Worker. The 10,000-path simulation runs in a Web Worker so the UI thread stays responsive. On an M1 MacBook Air, a typical run completes in well under one second; on a 2020 mid-range Android device, in roughly two seconds.
  • Privacy. Your inputs never leave your browser unless you explicitly save a plan (which requires sign-in) or generate a PDF. Anonymous aggregate telemetry — success probability bucket, household type, run time — is recorded so we can monitor calculator health.

Update cadence

Each underlying number gets refreshed on a known schedule, anchored to the official source's publication date:

NumberSourceWhen it changesYearfold updates
Social Security COLA + bend pointsSSA — published mid-October each yearNew numbers in effect Jan 1Pushed in Yearfold within 2 weeks of SSA release
IRS contribution limits, brackets, standard deductionIRS Rev Proc — published early NovemberIn effect Jan 1Pushed before Jan 1
Medicare Part B/D base premium + IRMAA bracketsCMS — published in NovemberIn effect Jan 1Pushed before Jan 1
State income tax ratesTax Foundation roundup — published AprilEffective varies by stateAnnual refresh in Q2
Historical return data (Shiller / S&P)Shiller updates monthly; S&P TR via FREDContinuousPulled annually in Q1

When a number changes, the change log below records it and the Last reviewed date in the page header is bumped. If you're using a saved plan and the rules change, you'll see a "rules updated" banner the next time you open it with a one-click "re-run with the current rules" action.

Change log

DateChange
2026-05-04Added 30-second-version summary, Monte Carlo historical origin (Ulam, 1940s), update-cadence table, and per-source last-accessed dates.
2026-05-03Initial public methodology page.
2026-04-24Updated 2026 IRMAA brackets (CMS final rule).
2026-04-15Switched historical return data from monthly resampling to joint monthly bootstrap.
2026-03-12Added Web Worker for off-main-thread simulation.

Sources

We cite primary sources for every number that matters. Each link below is the canonical page; the last accessed date is when a Yearfold human last verified the page existed and the cited number matched.

  • Social Security Administration — bend points, PIA formula, claim age adjustments. ssa.gov/oact/cola/Benefits.html · last accessed 2026-05-04
  • SSA period life tables — used for claim-age NPV and survivor analysis. ssa.gov/oact/STATS/table4c6.html · last accessed 2026-05-04
  • Centers for Medicare and Medicaid Services — Part B premiums, IRMAA brackets. cms.gov/medicare/medicare-costs · last accessed 2026-05-04
  • IRS — federal tax brackets, standard deduction, RMD tables. irs.gov/retirement-plans · last accessed 2026-05-04
  • Bureau of Labor Statistics — CPI-U inflation series. bls.gov/cpi · last accessed 2026-05-04
  • Federal Reserve / FRED — historical interest rate and macroeconomic series. fred.stlouisfed.org · last accessed 2026-05-04
  • Yale / Robert Shiller — long-run S&P 500 total return data with CAPE. shillerdata.com · last accessed 2026-05-04
  • Tax Foundation — annual state income tax roundup used for the 50-state effective-rate table. taxfoundation.org/data/all/state · last accessed 2026-05-04

If we got something wrong, please tell us at hello@yearfold.com. The "last reviewed" date in the page header reflects the most recent end-to-end check of every section.

Yearfold is a financial-education tool. It is not a registered investment adviser and does not provide personalized investment, tax, or legal advice. Results are probabilistic projections based on historical data and stated assumptions; they are not guarantees. Methodology