Our Methodology
How we calculate your projections.
From your inputs to actionable insights in four steps.
Your Inputs
Current age, retirement age, savings, spending, asset allocation, Social Security, and other income sources.
- ·Current portfolio value
- ·Monthly contributions until retirement
- ·Expected retirement spending
- ·Social Security claiming age
- ·Pension or other income
Historical Data
Two data sources: Shiller's dataset (1871–present) for Historical Bootstrap mode, or per-asset Yahoo Finance data for Parametric mode.
- ·Shiller: annual stock and bond returns (bundled snapshot)
- ·Yahoo Finance: per-asset CAGR and volatility
- ·Bootstrap preserves real stock/bond correlations within each year
- ·Choose your data source per scenario
Monte Carlo Simulation
Two simulation methods: Historical Bootstrap samples full-year tuples; Parametric generates correlated returns from per-asset distributions.
- ·Historical Bootstrap samples real year tuples with replacement
- ·Parametric: correlated normals via Cholesky decomposition
- ·Bootstrap preserves fat tails and regime changes
- ·Free: up to 200 runs; Retirement Confidence: up to 10,000 runs
Results Analysis
We analyze all scenarios to calculate success probability, safe withdrawal rates, and risk metrics.
- ·Success rate (% of paths where money lasts)
- ·Percentile bands (10th, 25th, 50th, 75th, 90th)
- ·Worst-case analysis
- ·Optimal withdrawal recommendations
Key insight: Unlike simple calculators that assume a fixed 7% annual return, Monte Carlo simulation shows you the range of possible outcomes. Markets don't return a steady percentage — they're volatile. Our approach captures that reality.
Monte Carlo Simulation.
The gold standard for retirement planning used by financial institutions worldwide.
Monte Carlo simulation runs your retirement plan through thousands of scenarios based on historical market data. Instead of assuming markets return a steady 7% every year (they don't), we test what happens when you retire into a bull market, a bear market, or anything in between.
How Bootstrap Sampling Works
We use a technique called bootstrap sampling. For each simulation:
- We randomly select a year from history (e.g., 1973)
- We use that year's actual stock returns and bond returns
- We repeat for each year of your retirement (e.g., 30 times)
- This creates one possible "retirement path"
- We run hundreds to thousands of paths to build a distribution of outcomes
Because we sample entire years together, we preserve the real correlation between stocks and bonds. When stocks crashed in 2008, bonds rallied. That relationship is captured in our simulations. Inflation is handled separately using your configured rate.
Two Simulation Modes
Historical Bootstrap
Draws full calendar-year tuples (stock return, bond return) from Shiller's dataset spanning 1871–present. Preserves real correlations, fat tails, and regime changes. Best for traditional stock/bond portfolios.
Parametric
Uses per-asset CAGR and volatility from Yahoo Finance, then generates correlated returns via Cholesky decomposition. Better for portfolios with non-traditional assets like crypto or individual stocks.
Why Not Just Use Average Returns?
Deterministic Projection
Assumes a fixed 7% annual return every year.
- ✓Simple to understand
- ✓Single clear answer
- ×Ignores volatility
- ×Misses sequence risk
- ×Overconfident
Monte Carlo (Stochastic)
Simulates many possible futures using historical return patterns.
- ✓Captures real market behavior
- ✓Shows probability of success
- ✓Reveals tail risks
- ×More complex output
- ×Requires interpretation
⚠Understanding Sequence of Returns Risk
Two retirees with identical average returns can have vastly different outcomes depending on when the bad years occur. A market crash early in retirement (when you're withdrawing from a depleting portfolio) is far more damaging than the same crash late in retirement. Monte Carlo simulation captures this "sequence risk" that simple calculators miss entirely.
See it in action.
Run a simplified Monte Carlo simulation. $1,000,000 starting balance, $40,000 annual withdrawal, 30 years.
Press Run to simulate.
Demo uses a simplified annual-returns sample. The production simulator uses Shiller's full 1871–present dataset (Historical Bootstrap) or per-asset Yahoo Finance distributions (Parametric).
Our Assumptions.
Every model makes assumptions. Here are ours — and how you can adjust them.
Inflation Rate
We default to the long-term historical average. The Federal Reserve targets 2%, but realized inflation since 1926 has averaged about 3%.
- Higher inflation erodes purchasing power faster
- TIPS and I-bonds can hedge inflation risk
- Healthcare inflation typically exceeds general inflation
Investment Returns
By default, we sample actual historical years via bootstrap. You can also switch to parametric mode and override CAGR and volatility per asset.
- Stock returns: historical average ~10% nominal, ~7% real
- Bond returns: historical average ~5% nominal, ~2.5% real
- Future returns may differ from historical patterns
Social Security
We assume you receive your estimated benefit at your chosen claiming age. Benefits are inflation-adjusted. Calculations use current SSA rules for earnings tests, claiming adjustments, and COLA.
- Claiming at 62 reduces benefits by ~30%
- Delaying to 70 increases benefits by ~24%
- You can model reduced benefits (e.g., 77%) for pessimistic scenarios
Life Expectancy
You set your planning horizon explicitly when creating a scenario. Standalone tools typically default to age 85–90. We recommend planning conservatively.
- 50% of 65-year-olds live past 85
- Women live ~3 years longer than men on average
- Family history and health matter significantly
Spending Patterns
By default, we assume your spending needs remain constant in real (inflation-adjusted) terms throughout retirement.
- Research suggests spending declines ~1% per year in retirement
- Healthcare costs often increase in later years
- You can model "spending smiles" or phases
Tax Treatment
We apply a single effective tax rate to all withdrawals in projections. A separate Roth vs Traditional comparison tool models marginal brackets. No progressive bracket modeling in the core simulator.
- Actual taxes depend on income level and state
- The default 22% approximates a moderate-income retiree
- Use the Roth vs Traditional tool for bracket-level analysis
Withdrawal Strategies.
How you withdraw money in retirement matters as much as how much you've saved.
4% Rule (Constant Dollar)
Withdraw 4% of initial portfolio in year 1, then adjust for inflation annually.
- Simple and predictable
- Well-researched (Trinity Study)
- Stable income
- Ignores portfolio performance
- May leave money on the table
- 30-year horizon only
Best for: Those who prioritize spending stability over optimization
Variable Percentage Withdrawal (VPW)
Withdraw a percentage of current portfolio using the IRS Single Life Expectancy Table for age-based divisors.
- Adapts to market performance
- Lower failure risk
- Accounts for mortality
- Income varies year to year
- Requires flexibility
- More complex
Best for: Those comfortable with income variability who want to optimize spending
Guardrails (Guyton-Klinger)
Start with a base withdrawal rate, but adjust up/down based on portfolio performance thresholds.
- Balances stability and adaptability
- Clear decision rules
- Limits extreme outcomes
- More complex to implement
- Requires monitoring
- Still has failure scenarios
Best for: Those who want some spending stability with market-responsive adjustments
Fixed Percentage
Withdraw a fixed percentage (e.g., 4%) of current portfolio value each year.
- Never runs out of money
- Simple rule
- Fully market-responsive
- Highly variable income
- Can drop significantly in downturns
- No inflation protection
Best for: Those with significant flexibility or other income sources
Floor-Ceiling
Withdraw a percentage of your portfolio each year, but clamp the result between inflation-adjusted dollar floor and ceiling amounts.
- Never runs out of money (like %)
- Limits downside spending cuts
- Caps excessive withdrawals
- Income still varies within range
- Requires setting initial floor/ceiling
- More complex than fixed percentage
Best for: Those who want percentage-based flexibility with hard spending boundaries
Strategy Comparison
| Metric | 4% Rule | VPW | Guardrails | Fixed % | Floor-Ceiling |
|---|---|---|---|---|---|
| Failure Risk | Medium | Low | Low | None* | None* |
| Income Stability | High | Low | Medium | Low | Medium |
| Upside Capture | Low | High | Medium | High | Medium |
| Complexity | Low | Medium | Medium | Low | Medium |
| Best Use Case | Stability | Optimization | Balanced | Flexibility | Bounded |
*Fixed percentage never "fails" because you always withdraw a % of what remains, but income can drop to very low levels.
Data Sources.
Our calculations are only as good as the data behind them. We use authoritative, publicly available sources.
Robert Shiller's Dataset
Annual US stock and bond returns from 1871-present (see live endpoint for exact range). The gold standard for long-term market analysis, bundled with the application.
- Annual stock total returns
- Annual bond total returns
- Annual CPI inflation
Yahoo Finance
Historical price data for individual securities, ETFs, mutual funds, and crypto. Used to compute per-asset CAGR and volatility for parametric simulations.
- Current prices
- Historical prices (5-year default)
- Computed CAGR
- Annualized volatility
Social Security Administration
Official benefit formulas for Social Security projections. Claiming-age adjustments, spousal and survivor benefits, and earnings test rules.
- PIA adjustment formulas
- Early/delayed claiming rules
- COLA adjustments
- Spousal & survivor benefits
IRS Publication 590-B
Single Life Expectancy Table used for Variable Percentage Withdrawal (VPW) strategy calculations.
- Life expectancy divisors (ages 50-115)
- Used for VPW withdrawal strategy
Data freshness: Shiller's historical return data is bundled with the application as an annual snapshot. Asset prices from Yahoo Finance are fetched in real-time with a 15-minute cache. SSA, IRS, healthcare, and federal-bracket rules reflect the current-year published tables; refresh the page to load the live freshness summary from our API.
Known Limitations.
Every model has limitations. Understanding them helps you use the tool appropriately.
Historical Data ≠ Future Returns
Past performance doesn't guarantee future results. The future may differ significantly from any historical period. Our simulations show what would have happened historically, not what will happen. That's why we test against 150+ years of data — including the worst periods in market history.
US-Centric Data
Our primary dataset covers US markets. International diversification benefits and risks aren't fully captured. If you have significant non-US holdings, results may vary. You can override return assumptions for any asset class in the simulator.
Simplified Tax Model
Projections apply a single flat effective tax rate (default 22%) to all withdrawals. We don't model progressive brackets, state taxes, capital gains nuances, or account-type-specific treatment in the core simulator. For bracket-level analysis, use the Roth vs Traditional tool.
No Behavioral Factors
Models assume you'll follow the plan. In reality, investors often panic-sell in downturns or overspend in bull markets. Behavioral discipline matters. The Guardrails strategy builds automatic adjustments into your spending plan.
Healthcare Cost Uncertainty
Healthcare costs are highly variable and can be catastrophic. While we model average healthcare inflation, individual outcomes vary dramatically. Use the Medicare and Healthcare Bridge tools for detailed cost projections.
Black Swan Events
Monte Carlo simulations are based on historical volatility. True black swan events (worse than any historical period) aren't captured. The worst historical periods (1929, 2008) are included in every simulation.
Important Disclaimer
This tool is for educational and planning purposes only. This is not financial advice.
- We are not registered investment advisors, financial planners, or tax professionals.
- Results are projections based on historical data and your inputs, not predictions.
- Consult qualified professionals for personalized advice about your specific situation.
- You are solely responsible for your financial decisions.
The research behind your numbers.
Our methodology is built on peer-reviewed research spanning 30+ years. The 4% rule was first established by William Bengen in 1994 and stress-tested by the Trinity Study across 75 years of market data.
Foundational Research
The original "4% rule" paper that established safe withdrawal rate research.
Expanded Bengen's work with various asset allocations and withdrawal rates.
Robert Shiller's seminal work on market valuations and the CAPE ratio.
Monte Carlo & Simulation
Overview of how Monte Carlo methods apply to retirement planning.
Technical background on bootstrap methods for financial simulation.
Withdrawal Strategies
Community-developed approach to dynamic withdrawal rates.
The guardrails approach to managing withdrawal rates.
How spending flexibility impacts sustainable withdrawal rates.
Ready to see your own numbers?
Open the simulator and stress-test your plan against 150+ years of market history. Free tier available forever — upgrade to Retirement Confidence or Investing Engine when you need more power.