Retirement Planning · After Retirement
Monte Carlo Retirement Simulator
Simulate thousands of possible market paths to estimate the probability that your retirement corpus survives your planned, inflation-rising withdrawals — with the range of balances you might have along the way, and when the money tends to run out in the paths that fail.
Also listed inFinance & Investment
Your inputs
Quick start — try a typical case
₹ 3 crore
₹ 12 lakh
Raised every year with inflation.
The long-run average of yearly returns of your portfolio mix.
Standard deviation of yearly returns: ~4 % for debt, ~16–20 % for equity, ~10–12 % for a 50/50 mix.
Your result Live
Chance Your Money Lasts to 90 — A coin flip — risky
67%
1,336 of 2,000 simulated market paths never ran out
- Initial Withdrawal Rate
- 4.0%
- Median Balance at 90
- ₹3,88,36,632 (₹67,61,851 in today's money)
- Bad Case (10th percentile) at 90
- ₹0
- Good Case (90th percentile) at 90
- ₹23,77,41,371
- When Failing Paths Ran Out (median)
- Around age 84
- Paths that lasted67%
- Paths that ran out33%
Each path is a different random sequence of yearly returns with the same average and volatility. The result is a probability under these assumptions, not a forecast — the same seed is used every time, so results only change when you change an input.
To raise the odds: withdraw less, keep a cash buffer for bad years, delay retirement, or add guaranteed income (an annuity or pension).
An estimate from the assumptions you entered, not a guaranteed outcome.
How this is calculated
Each year: Balance = (Balance − Withdrawal) × (1 + Rₜ); Withdrawal grows with inflation; Rₜ ~ lognormal(mean m, volatility s)
- Rₜ
- A random yearly return: ln(1 + R) is normal with σ² = ln(1 + s² ÷ (1 + m)²), μ = ln(1 + m) − σ² ÷ 2
- Success
- The balance never reaches zero before the planning age
A fixed-return planner assumes markets deliver the average every year. Real returns vary, and the order matters: a crash in the first years of retirement, while you are withdrawing, does far more damage than the same crash later (sequence-of-returns risk). Monte Carlo simulation runs thousands of possible return sequences and counts how often the money lasts.
Assumptions & sources
- Yearly returns are independent and lognormally distributed with constant mean and volatility; real markets have fatter tails and regimes.
- Withdrawals are made at the start of each year and grow with inflation; taxes and fees are not deducted unless included in the return.
- A fixed random seed is used so results are reproducible; a different seed changes results by about ±1 percentage point.
- 1CFA Program Curriculum — Private Wealth Management: retirement planning and the time value of money — CFA Institute
- 2Retirement planning investor education — PFRDA — Pension Fund Regulatory and Development Authority
- 3Determining Withdrawal Rates Using Historical Data (Bengen, 1994) — Journal of Financial Planning
- 4Monte Carlo Methods in Financial Engineering (Glasserman, 2003) — Springer
Calculator ID FIN-SIM-MC-001 · version 1.0.0
Common questions
What success rate should I aim for?
Many planners target 80–90 %. Aiming for 100 % usually means spending much less than you could; a lower rate is acceptable if you can cut spending in bad years.
Why does volatility matter if the average is the same?
Because withdrawals lock in losses: selling units after a fall leaves fewer to recover. Two portfolios with the same average return can have very different chances of lasting.
Is the result a prediction?
No. It's the share of simulated paths that work under your assumptions. Treat it as a stress test and revisit it every year or two.