Methodology

This calculator is built on transparent, well-documented financial-planning math. Every projection you see can be derived from the formulas below.

1. Compound growth

FV = PV × (1 + r)^n + C × [((1 + r)^n − 1) ÷ r]

PV is your current invested portfolio. r is the blended real return for your allocation. n is years to retirement.C is your annualized contribution.

2. Blended portfolio return

Each asset class (stocks, bonds, real estate, gold) has an expected return and a volatility. The portfolio return is the weighted average of the asset-class returns; the portfolio volatility is derived from the weights and an assumed equity-bond correlation.

3. Retirement target

Retirement Target = Annual Spending ÷ Safe Withdrawal Rate

The Trinity Study and follow-on research (Bengen, Pfau) support a 3.25–4% withdrawal rate depending on retirement length. The calculator lets you set this directly.

4. Coast number

Coast Number = Retirement Target ÷ (1 + Real Return)^Years Until Retirement

This is how much you need today, with zero further contributions, to compound into the retirement target.

5. Real vs. nominal returns

Real Return = (1 + Nominal Return) ÷ (1 + Inflation) − 1

All projections are reported in today's dollars so you can compare them directly to today's spending budget.

6. Monte Carlo

The engine draws annual returns from a normal distribution defined by the expected return and volatility. It runs thousands of independent paths, applies contributions and inflation-adjusted withdrawals, and reports the distribution of outcomes plus survival probability.

7. Stress scenarios

On top of Monte Carlo, the calculator supports configurable shocks: lost decades, early-retirement crashes, multiple crashes, inflation shocks, high-rate regimes, job loss, healthcare events, late-career income drops, panic selling, and lifestyle inflation. Each is implemented as a deterministic modifier on the year's return, contribution, or withdrawal.

8. Historical bootstrap

For an alternative to parametric Monte Carlo, the bootstrap simulator samples rolling windows of actual U.S. market history. This captures fat tails and autocorrelation that a normal distribution misses.

Limitations

• Results are estimates, not predictions.
• Taxes are modeled only implicitly via the withdrawal rate.
• Healthcare and long-term-care costs are treated as discrete events.
• Behavioral risks (selling at the bottom, missing rebalances) are user-supplied scenarios, not automatic.

See also: About · Disclaimer · Back to calculator