About the Monte Carlo Simulation
What is the Monte Carlo Simulation?
Real returns are not a smooth 12% every year — they bounce around. A Monte Carlo simulation runs hundreds of possible futures, each with randomly drawn yearly returns, to show the range of outcomes your plan could produce instead of a single number.
Enter your initial investment, monthly contribution, expected annual return, volatility, number of years and number of simulations. The calculator reports the median outcome, the pessimistic 10th percentile (P10) and the optimistic 90th percentile (P90), and plots the range over time.
How to use the Monte Carlo Simulation
- Initial Investment (INR) (sample: 5,00,000)
- Monthly Contribution (INR) (sample: 10,000)
- Expected Return (%) (sample: 12)
- Annual Volatility (%) (sample: 18)
- Years (sample: 15)
- Simulation Count (sample: 200)
- Press Run Simulation (results also refresh as you type). The result card shows the Median Outcome, along with Downside (P10), Upside (P90) and Simulations.
Formula used
Balanceₜ = (Balanceₜ₋₁ + 12 × Monthly contribution) × (1 + Rₜ)
- Rₜ = a random return drawn from a normal distribution with your mean and volatility
- P10 / P50 / P90 = the 10th, 50th and 90th percentiles of all simulated outcomes
Each run uses different random draws, so results change slightly every time you calculate.
Worked example
These are the sample values already filled in the calculator above, and the result it returns for them:
| Input | Sample value |
|---|---|
| Initial Investment (INR) | 5,00,000 |
| Monthly Contribution (INR) | 10,000 |
| Expected Return (%) | 12 |
| Annual Volatility (%) | 18 |
| Years | 15 |
| Simulation Count | 200 |
| Result | Value |
|---|---|
| Median Outcome | ₹75,25,691 |
| Downside (P10) | ₹38,21,019 |
| Upside (P90) | ₹1,34,36,386 |
| Simulations | 200 |
Tips for using the Monte Carlo Simulation
- Plan around the P10 outcome if missing the goal would be costly.
- Higher volatility widens the gap between P10 and P90 even when the average return is the same.
- Run 300–500 simulations for more stable percentiles.