Multi-Asset Class​ Hybrid Performance Attribution​ in PORT​

If you are already registered for this event you can watch the live session here: https://events.bloombergevents.com/ZxXz30 Understanding what drove portfolio performance is critical to evaluating investment decisions and communicating results. Bloomberg’s Multi-Asset Class Hybrid Performance Attribution (MAC HPA) helps investors break down the drivers of return across equities, fixed income and multi-asset portfolios, with flexible models that can be tailored to different investment strategies. In this session, we’ll walk through how performance attribution works across Bloomberg’s PORT ecosystem, from the data and quality-control processes that support the calculations to interactive analysis, AI-generated summaries, and reporting workflows. We’ll also explore tools for time-series analysis and performance transparency, as well as the range of model choices, weighting approaches, and customization options available to support different portfolio structures and investment processes. Finally, we’ll look ahead at Bloomberg’s roadmap for performance attribution, including expanded total portfolio coverage, greater model flexibility, enhanced transparency, AI-enabled workflows, and continued investments in scale and performance.