Explain WHAT DRIVES the returns of a ticker, ETF or built-in portfolio by decomposing them into common factor exposures (market, size, value, momentum, quality, low-volatility, duration, credit) plus an idiosyncratic residual. Use this when the user asks why two assets move together, what a fund is really exposed to, whether a stock is a growth or value tilt, how much of a return is just market beta, whether it has real alpha, or what is driving a portfolio's returns. Returns betas (loadings), t-stats, an additive variance decomposition (shares sum to R²), annualized alpha, idiosyncratic vs total volatility, and for a portfolio the holdings that drive each factor. Computed by OLS regression on real price history via tradeable ETF proxies (long-short factor spreads): measured exposure, not a forecast. Provide exactly one of `target` (a ticker, computed live), `template` (a built-in model portfolio), `strategy` (a canonical strategy) or `assets` (your own allocation, including nested portfolios, rotations and strategies as holdings, computed live); portfolio ids are answered from precomputed monthly data through the stated month. Portfolios (ids and `assets`) use the five default factors (market, size, value, duration, credit), are monthly and ignore `frequency` and `factors`. For performance numbers use analyze_portfolio. Read-only.