Dynamic robust risk measures with applications
Abstract
Pesenti explores distributionally robust risk measures in this webinar, examining how they represent the maximum value within uncertainty sets—plausible alternative distributions around a reference point. The talk covers worst-case distortion risk measures for Wasserstein uncertainty sets, applied to portfolio optimization. Silvana then delves into the dynamic setting, introducing dynamic robust risk measures and uncertainty sets, studying conditions for well-known properties like convexity and coherence, and providing proofs for time-consistency and recursive representation.
Watch recording ↗About the speaker
Since July 2025, Silvana Pesenti is an Associate Professor (with tenure) in Insurance Risk Management at the Department of Statistical Sciences at the University of Toronto. From 2019 to 2025 Silvana was an Assistant Professor in Insurance Risk Management at the University of Toronto. Silvana was named the 2022 Rising Star in Quant Finance by Risk.net for the paper Portfolio Optimisation within a Wasserstein Ball. She received the 2020 Peter Clark Best Paper Prize for her research paper “Reverse Sensitivity Testing: what does it take to break the model?” from the Institute and Faculty of Actuaries (IFoA). In 2019, Silvana was awarded the Dorothy Shoichet Women Faculty Science Award of Excellence. Silvana Pesenti is an Associate Editor of SIAM J. on Financial Mathematics (since 2026), of Annals of Actuarial Science (since 2023), and on the Editorial Board of Dependence Modeling (since 2024), of Applied Mathematical Finance (since 2023), of ASTIN Bulletin (since 2023), and of Computational and Applied Mathematics (2022 – 2025). Silvana Pesenti received her PhD in Actuarial Science and Insurance from Bayes Business School (formerly Cass Business School), London, UK, in December 2018. Her PhD thesis was awarded the Dimitris N. Chorafas Prize 2018 from the Weizmann Institute of Science. Further, Silvana holds a MSc and a BSc in Mathematics from ETH Zurich.