Methodology
How the site turns local assumptions into portfolio-level outcomes.
The methodology is intentionally transparent and plain-English so advisers can explain the logic without needing to translate technical implementation detail in front of clients.
Strategic allocation framing
PortfolioLogica is designed for adviser-led conversations about long-term portfolio mix, expected outcomes, and resilience under historical stress scenarios.
Default and comparison assumptions
Macquarie is the default assumption set throughout the experience. JPM is available only as a secondary comparison view using the specified first-pass proxy mappings.
Expected return calculation
Portfolio expected return is calculated as the weighted average of asset-class expected returns from the selected assumption set.
Expected risk calculation
Portfolio expected risk is estimated from a covariance matrix using the seeded volatility inputs and a full correlation matrix across all canonical asset classes.
Stress scenario calculation
Each historical scenario return is calculated by applying the asset-class shock table to the current portfolio weights and summing the weighted impacts.
Builder normalisation
When a sleeve is adjusted, the remaining sleeves are automatically reweighted proportionally so the total remains at 100% without leaving broken states in the interface.
Implementation Notes
Data is local and strongly typed by design so the current placeholder source can be replaced later with a CMS or API without rebuilding the presentation layer.
The application separates local data files under /data, shared TypeScript models under /types, and calculation utilities under /lib. This keeps the current seeded implementation tidy while leaving a clear handoff path for final approved content and future integration work.