Monte Carlo Portfolio Simulator
A simulation tool that projects thousands of potential investment portfolio outcomes using Monte Carlo methods, helping users understand the range of possibilities rather than relying on a single expected return.
Motivation
Most portfolio calculators give you one number: an average expected return. But real markets are stochastic. I wanted a tool that shows the full distribution of outcomes: the best case, the worst case, and everything in between. That's what Monte Carlo simulation does.
How it works
- User inputs portfolio allocation, initial investment, time horizon, and contribution schedule
- The simulator samples thousands of return paths from historical distributions
- Results show percentile bands (5th, 25th, 50th, 75th, 95th) of portfolio value over time
- Visualizations make it easy to understand the range of outcomes and tail risks
Technical details
Built in Python with NumPy for fast vectorized simulation of thousands of parallel portfolio paths. Pandas handles data manipulation and historical return processing. Matplotlib generates the probability fan charts. The simulator supports configurable asset correlations and rebalancing strategies.