performance-attribution

To decompose portfolio returns, you use Brinson-Fachler equity attribution to isolate allocation effects from security selection. This breaks down performance into actionable components, showing exactly how much return came from strategic asset allocation versus individual stock picks.

Factor-based attribution identifies the impact of systematic market factors like size, value, and momentum on your portfolio's performance. It analyzes your portfolio's factor exposures to determine which market drivers generated your returns using returns-based or holdings-based methodologies.

Yes, you can analyze fixed-income drivers and currency impacts for international portfolios. The analysis handles asset class specific performance drivers, isolating how currency movements and bond selection contributed to your overall international portfolio returns.

Yes, performance attribution requires Python scripts and depends on numpy to handle multi-period geometric linking. It processes quantitative analysis tasks, calculating compounded attribution effects across multiple periods using numpy arrays for numerical operations.

Use holdings-based attribution when you have complete portfolio holdings data to analyze specific security level drivers. Use returns-based attribution when you only have portfolio return series, analyzing systematic factor exposures through regression against market factors.

The best way to analyze portfolio underperformance against a benchmark is using Brinson-Fachler attribution to determine if the deficit originated from allocation decisions in wrong sectors or poor security selection within those sectors.