no code implementations • 20 Nov 2023 • Silvana M. Pesenti, Steven Vanduffel
This gives raise to a rich variety of novel asymmetric MK divergences, which subsume the family of Bregman-Wasserstein divergences.
no code implementations • 24 Aug 2023 • Marlon Moresco, Mélina Mailhot, Silvana M. Pesenti
We find that uncertainty sets stemming from f-divergences lead to strong time-consistency while the Wasserstein distance results in a new time-consistent notion of weak recursiveness.
no code implementations • 22 Aug 2023 • Emma Kroell, Sebastian Jaimungal, Silvana M. Pesenti
Insurers meanwhile seek to maximise their expected utility without ambiguity.
no code implementations • 18 May 2023 • Sebastian Jaimungal, Silvana M. Pesenti, Yuri F. Saporito, Rodrigo S. Targino
We define and develop an approach for risk budgeting allocation -- a risk diversification portfolio strategy -- where risk is measured using a dynamic time-consistent risk measure.
no code implementations • 2 Feb 2023 • Bernardo Freitas Paulo da Costa, Silvana M. Pesenti, Rodrigo S. Targino
Risk budgeting is a portfolio strategy where each asset contributes a prespecified amount to the aggregate risk of the portfolio.
1 code implementation • 6 Nov 2022 • Emma Kroell, Silvana M. Pesenti, Sebastian Jaimungal
We find that under the stressed measure, the intensity and the severity distribution of the process depend on time and state.
no code implementations • 18 May 2022 • Carole Bernard, Silvana M. Pesenti, Steven Vanduffel
The robustness of risk measures to changes in underlying loss distributions (distributional uncertainty) is of crucial importance in making well-informed decisions.
no code implementations • 2 Jul 2021 • Silvana M. Pesenti
The modeller seeks to understand how the model (the distribution of the input factors as well as the output) changes under a stress on the output's distribution.