Abstract:
Investment performance measurement and attribution are key functions of portfolio management, bringing transparency in terms of the true drivers of portfolio risk and return. Performance analysts provide real added value and are often the only independent source equipped to understand the sources of risk and return of all portfolios and benchmarks operating within an asset management firm. Performance attribution aims to split the total outperformance of a portfolio versus its benchmark into fair contributions from the active individual decisions as well as from markets’ movements. Whereas on one hand this goal can be successfully achieved with attribution schemes that match as closely as possible the management structure of the portfolio, running different attributions on the other hand can help managers to identify unexpected, sometimes possibly unwanted sources of risk and return and adjust the management process accordingly. Performance attribution models vary from the simplest ones 1) total return or sector based attribution to the most sophisticated ones 2) factor based attribution based on a set of common risk factors and 3) hybrid performance attribution, which bridges 1) and 2). In all cases these frameworks need to accurately deal with the complexities of portfolio management: portfolio assets spread over different markets, asset classes and currencies, multiple investment horizons, multi-period compounding, derivatives handling, dynamic management, bad or missing security prices and analytics, etc.In the first part of the presentation the focus will be on factor based attribution. Risk factor models are not only indispensable tools for risk forecasting or portfolio optimization, but also largely used for performance attribution purposes. With their choice of portfolio analytics providers investment management firms need to be very selective, since there is no such a thing like a perfect model and a proper model governance and understanding of the model strengths and weaknesses are key. We use the latest generation of risk factor model suites from Bloomberg and MSCI, both leading providers of critical decision support tools.In the second part of the presentation we show examples on how hybrid performance attribution can be used to analyse the performance of fixed income portfolios by splitting total outperformance into two parts: that explained by bottom-up common factor aggregation and that in excess of common factors, which is further top-down (recursively) split into allocation/sector management on a user-defined hierarchical partition.

16:35 • ETH Zentrum, Rämistrasse 101, Zürich, Building HG, Room E 7

ETH Zürich

Risk Day

Dacheng Xiu (University of Chicago)

Expected Returns and Large Language Models abstract

17:40 • ETH Zentrum, Rämistrasse 101, Zürich, Building HG, Room E 7

address: Alessandra Naldi Windler, Departement Mathematik, HG G 51.4, ETH Zurich, Raemistrasse 101, CH-8092 Zurich
email: bulletin@math.ch | phone: +41 44 632 3684 | url: https://math.ch

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