Monte Carlo Simulation & Backtesting
Monte Carlo Simulation
Monte Carlo runs thousands of random scenarios to project portfolio outcomes.
4 Statistical Models
| Model | Description |
|---|---|
| GBM | Classic log-normal returns with constant drift/volatility |
| Student-t | Fat-tail modeling — extreme events more likely |
| GARCH | Time-varying volatility — volatility clusters |
| Regime-Switching | Two states (bull/bear) with transition probabilities |
Results Include
- Fan chart (5th, 25th, 50th, 75th, 95th percentiles)
- Scenario comparison (all 4 models side by side)
- Required savings calculator
- Terminal value distribution histogram
Backtesting
Backtest tests strategies against historical data.
Preset Strategies
| Strategy | Allocation |
|---|---|
| 60/40 | 60% SPY / 40% AGG |
| All Equity | 100% SPY |
| Conservative | 30% stocks / 50% bonds / 20% cash |
| Growth | 80% stocks / 10% intl / 10% EM |
| All Weather | 30% stocks / 40% long bonds / 15% inter bonds / 7.5% gold / 7.5% commodities |
Your Portfolio
Select your actual portfolio — the tool uses your real holdings weighted by market value.
Periods
1Y, 3Y, 5Y, 10Y, or 20Y of historical data.
Results
- Cumulative return chart vs benchmarks (SPY + 60/40)
- Drawdown chart
- Monthly returns heatmap
- Key metrics: CAGR, Max Drawdown, Sharpe, Sortino, Best/Worst Year