Historical Simulation
Using decades of real-world data to evaluate an investment strategy's ultimate resilience.
What is it?
Historical simulation (or "Backtesting") evaluates an investment strategy by running it through actual historical market data. It answers the question: "If I had instituted this exact strategy 20 years ago, what would my account value, drawdowns, and compound return be today?"
How It Works
A robust historical simulation goes beyond simply taking the "average annual return" of assets. An accurate backtest evaluates:
- Sequence of Returns: Analyzing the actual month-by-month path taken, which dictates compounding math and maximum drawdown depths.
- Cashflows & DCA: Implementing real-world cash injection schedules (e.g., $1000/month contributions).
- Rebalancing Rules: Correctly simulating portfolio drift and periodic rebalancing (e.g., rebalancing annually or when a threshold is triggered), which naturally enforces "buy low, sell high" behavior.
- Survivorship Bias: Understanding if the selected assets only exist today because they survived past market crashes.
The Golden Rule
Past performance is not indicative of future results
While historical simulation is an incredibly powerful tool for understanding risk and behavioral expectations (i.e. "Could I stomach a 40% drop over a 16 month period?"), it cannot precisely predict future returns. The primary purpose of an historical backtest is verifying robust asset correlations during real-world stress limits.
Run your own Historical Backtest
Use our engine to simulate comprehensive portfolios backtest from 2005 to today with customizable contributions and rebalancing strategies.
Start Simulation