How we selected our methodology: We tested over 175 unique simulation models with out-of-sample validation across 80 multi-asset portfolios and more than 40 years of historical data. Our goal is to offer investors the most distributionally accurate, research-driven, plug-and-play portfolio simulation solution.
Download Methodology White Paper (PDF)Methodology
General
Simfolio connects portfolio construction, historical analysis, simulation, and brokerage monitoring in one research workflow. A portfolio policy combines its holdings with the rules for rebalancing, costs, contributions, and withdrawals.
Data Sources
Historical coverage reflects the availability and overlap of the required market, currency, and economic series. Constructed histories are identified separately in the Simulated Ticker Catalogue.
Brokerage
Brokerage connects reported holdings with a saved portfolio policy. It shows the current allocation, differences from target weights, and estimates for planned portfolio actions.
Backtesting
A backtest replays a portfolio policy through observed market history, including allocation changes, trading costs, recurring drag, and external cash flows.
Simulation
The simulation models future asset returns and applies the same portfolio settings as the backtest within each scenario, producing distributions of wealth based on a specific portfolios configuration.
Investment Tools
Standalone tools examine specific portfolio questions using their own selected inputs. Saved portfolios can supply allocations; each tool applies the assumptions described below rather than inheriting every setting from a Research workspace.
Limitations
Results are conditional on their data, selected policies, and modeling assumptions. Historical observations, simulated distributions, and account estimates represent different forms of evidence.
Research
The references below document the data sources and statistical foundations used across Simfolio. The linked white paper provides the model-specific validation record.