compoundsimMonte Carlo Investment Simulator
1,000 market paths drawn from real S&P 500, Nasdaq 100 and MSCI ACWI history show how well, and how badly, your monthly plan could go.
Monte Carlo simulation for recurring investments
What Monte Carlo adds
Instead of a single fixed return, the simulator runs 1,000 paths from a model fitted to the history you choose, switching between a calm and a wild market regime. The result is a range rather than one number: a median path and the 10th to 90th percentile band. How the model works, and why a short history widens the band, is explained in the article below.
Reading the percentiles
The median is the middle outcome: half of the paths finished above it and half below. About one path in ten fell below the band's lower edge and one in ten rose above its upper edge, so a wider band means the index's volatility adds more uncertainty to the plan. Why the median is not a forecast is covered in the article below.
Reading the drawdown charts
A drawdown is how far the balance sits below its highest point so far. The range chart shows where the paths stand at each year end; the histogram shows the deepest fall each path went through in any month, and the threshold gives the share of paths that fell that far at least once. Early on, contributions are large next to the balance and keep drawdowns shallow; later the balance dominates and falls go deeper. Set the monthly amount to 0 to see the index's own drawdowns. The wild regime lasts a few months at a time, so slumps stretch over several months, but a slide as long as 2007–2009 remains rarer here than in history, and these probabilities may be optimistic.
About the historical data
The months come from month-end, dividend-adjusted closes of an ETF standing in for each asset (SPY for the S&P 500 since 1993, QQQ for the Nasdaq 100, AGG for US bonds, GLD for gold and so on), and from Bitcoin's own price since 2014. The info icon on the projected range shows the months that history covers, with their return and volatility. Past returns do not predict future ones; volatile assets such as SOX or Bitcoin produce much wider bands.