You are now in the main content area

Colloquium talk: Robust Risk Measures: Static to Dynamic

Date
November 02, 2023
Time
12:10 PM EDT - 1:00 PM EDT
Location
ENGLG24
Open To
All Faculty, staff, students and guests are welcome to attend
Contact
Dr. Pawel Pralat (pralat@torontomu.ca)

TORONTO METROPOLITAN UNIVERSITY DEPARTMENT OF MATHEMATICS

COLLOQUIUM

Dr. Silvana Pesenti

Department of Statistical Sciences

University of Toronto

Date: Thursday, November 2, 2023

Time: 12:10 pm

Location: ENGLG24

Robust Risk Measures: Static to Dynamic

Abstract:

In this talk I discuss robust risk measures - also called worst-case risk measures – which are the largest value a risk measure can attain within an uncertainty set. An uncertainty set is defined as a set of random variables which are considered as plausible alternatives and are typically characterised by balls around a reference random variable. Examples include robust distortion risk measures and uncertainty sets induced by the Wasserstein distance and moment constraints.

I further consider the dynamic setting, where the risk of stochastic processes is evaluated using time-consistent dynamic risk measures. In the dynamic setting we introduce dynamic uncertainty sets which quantify at each point in time the uncertainty of the future process. We discuss conditions on the uncertainty sets that lead to well-known properties of dynamic robust risk measures, such as convexity and coherence. Furthermore, we proof necessary and sufficient properties of dynamic uncertainty sets that lead to time-consistency of robust dynamic risk measures.

This talk is based on:

• Moresco, M., Mailhot, M., Pesenti S.M., (2023) Uncertainty Propagation and Dynamic Robust Risk Measures

• Bernard, C., Pesenti S., Vanduffel, S. (2023) Robust Distortion Risk Measures, Mathematical

Finance (forthcoming)

All Faculty, staff, students and guests are welcome to attend