Retirement readiness calculator

This calculator uses a set of Capital Market Assumptions (CMAs) — the statistical parameters that govern how simulated market returns are generated. These assumptions are grounded in long-run historical data and peer-reviewed financial literature. They are not predictions; they represent a calibrated probability distribution of plausible outcomes. All simulations are run client-side in your browser using a deterministic pseudorandom number generator seeded at runtime.

Annual equity volatility (σ)

15.0%

Annualized standard deviation of monthly returns. Calibrated to long-run U.S. diversified equity (S&P 500 historical σ ≈ 15–17%).

Monthly volatility applied

4.33%

σ / √12. Each monthly simulation step applies an independent draw from N(0, 4.33%).

Return distribution

Normal

Log-normal returns modeled via arithmetic normal shocks. Does not model fat tails or skewness; actual markets exhibit negative skew.

Inflation assumption

Implicit

All figures are in nominal dollars. Your gross return assumption should be entered as a nominal (pre-inflation) return.

Withdrawal rule (SWR)

4.00%

The "4% rule" derived from the Trinity Study (Bengen, 1994). Applied to portfolio need calculations; actual withdrawals are simulated dynamically.

Simulation count

1,000

1,000 independent paths provides <3% sampling error on success-rate estimates at the 95% confidence level.

Random number generation

Monthly return shocks are generated using the Box-Muller transform, which converts pairs of uniform random variables U(0,1) into independent standard normal variates. Each monthly step: r_t = μ_net + σ_monthly × ε_t where ε_t ~ N(0,1). This is the same methodology used in commercial Monte Carlo planning tools.

Sequence of returns risk

The model simulates both accumulation and drawdown phases continuously, meaning each path carries its full sequence of returns into retirement. Poor early-retirement return sequences that deplete portfolios before recovery are naturally captured — this is what makes Monte Carlo superior to deterministic projections.

Fee modeling

Fees are modeled as a continuous drag on the net return: r_net = r_gross − fee_rate applied monthly. This slightly understates fee drag versus compounding-based calculations but is standard practice in scenario modeling tools.

Key limitations

This model does not account for: tax drag on taxable accounts, required minimum distributions, inflation-adjusted withdrawals, Social Security COLA adjustments, healthcare cost escalation, or regime-switching market dynamics. Results should be treated as illustrative, not prescriptive.

Important disclosure: Capital market assumptions are inherently uncertain and are not guarantees of future performance. Historical return and volatility data are not predictive. This tool is for educational and illustrative purposes only and does not constitute financial, investment, or tax advice. Consult a qualified fiduciary financial advisor before making retirement planning decisions.

Your profile

Current age

Target retirement age

Current portfolio value ($)

Monthly savings rate ($)

Assumptions

Expected gross annual return

7.0%

3%14%

All-in fee rate (expense ratios + advisory)

1.00%

0%3%

Target monthly retirement income ($)

Plan to age (longevity target)

Include Social Security estimate

Estimated monthly Social Security benefit ($)

—

/ 100

—

Derived from 1,000 Monte Carlo simulations

Median projected nest egg

—

at retirement

Monthly income gap

—

vs. target

Monte Carlo success rate

—

funded to target age

Portfolio needed (4% SWR)

—

to fund income gap

Total lifetime fee drag

—

vs. zero-fee scenario

Years to retirement

—

accumulation runway

Monte Carlo success probability

—

Simulations run

1,000

Annual vol (σ)

15.00%

Net return used

—

Distribution

N(μ, σ)

Successful paths

—

Fee impact — current rate vs. zero fees

At current fee rate

Fee rate—

Net return—

Median nest egg—

Monthly income (SWR)—

Effective retirement date—

                  At zero fees
                
                  Fee rate0.00%
                
                  Net return—
                
                  Median nest egg—
                
                  Monthly income (SWR)—
                
                  Effective retirement date—

—

Portfolio projection — 1,000 Monte Carlo paths

Median (p50)

p25–p75 band

p5–p95 band

Portfolio needed

Projected monthly income at retirement

Top actions to improve your score

Detailed insights

v2.3.0 · 2026-03-16 · 1,000 Monte Carlo simulations · Box-Muller RNG · σ = 15% · For illustrative purposes only. Not financial advice.