Monte Carlo Portfolio Simulator
Run thousands of simulations to calculate the probability of success for your retirement portfolio based on historical market volatility and drift.
Projected Portfolio Value Over Time
Inflation AdjustedYear-by-Year Projections
| Year ↕ | 10th Percentile ↕ | 25th Percentile ↕ | Median (50th) ↕ | 75th Percentile ↕ | 90th Percentile ↕ |
|---|
Methodology & Data Sources
This Monte Carlo simulator models future portfolio performance by drawing random annual returns from a normal distribution based on historical market data. It runs 1,000 independent trials to construct a probability distribution of potential outcomes.
Asset Class Parameters (Last 20 Years)
- US Equities (SPY proxy): The model uses historical annualized return and volatility (standard deviation) over the last 20 years to simulate stock performance.
- US Aggregate Bonds (AGG proxy): The model uses historical annualized return and volatility over the last 20 years to simulate bond performance.
- Correlation: The model assumes a standard historical correlation between stocks and bonds when calculating the blended portfolio return and volatility.
Note: Real market returns are not perfectly normally distributed and exhibit "fat tails" (extreme events happen more frequently than predicted by a normal distribution). This tool is for educational purposes and should not replace a comprehensive financial plan.
Frequently Asked Questions
What is a Monte Carlo simulation for retirement?
A Monte Carlo simulation uses random sampling and statistical modeling to generate thousands of possible future return scenarios. This allows you to estimate the probability of success for your retirement plan under varying market conditions rather than assuming a fixed annual return.
How does this portfolio Monte Carlo simulator work?
The simulator takes your starting balance, annual contribution, withdrawal expectations, and asset allocation, then runs 1,000 simulations. It uses historical mean returns and standard deviation (volatility) of stocks and bonds to project future percentile outcomes.
What is considered a good probability of success?
Most financial planners consider a probability of success between 80% and 90% as acceptable. A 100% success rate may mean you are over-saving or under-spending, while anything below 70% suggests you may need to adjust your savings rate, retirement age, or spending expectations.
Are Monte Carlo simulations accurate for stock markets?
Monte Carlo simulations provide a range of probabilities, not a guaranteed forecast. They are highly dependent on the assumptions used for average return and volatility. Real markets experience "fat tails" (extreme events) more often than a normal distribution predicts, so simulations should be used as a guide, not a certainty.
Why is sequence of returns risk important in retirement?
Sequence of returns risk refers to the danger of experiencing poor market performance early in retirement. Because you are simultaneously withdrawing funds, early losses deplete your portfolio faster, leaving less capital to benefit from future market recoveries. Monte Carlo simulations help measure this risk by randomly varying the order of good and bad return years.
Cite This Page
Westmount Fundamentals. "Monte Carlo Portfolio Simulator." westmountfundamentals.com/monte-carlo-portfolio-simulator, 2026.