Department seminar by Dr. Jonathan Yu-Meng Li, University of OttawaExport this event to calendar

Friday, May 31, 2019 — 10:30 AM EDT

Worst-case risk measures and distributionally robust optimization

Distributional ambiguity refers to the situation where the probability distribution of uncertain outcomes is unknown. The question of how to account for distributional ambiguity has been of central interest in risk management, and more generally, many fields involving decision making under uncertainty. In this talk, we present a general framework of risk minimization based on distortion risk measures (also known as dual utility) and show how the worst-case risk can be evaluated when only the support and moments are known for the underlying distribution. We also show that the problem of minimizing the worst-case risk, also known as distributionally robust optimization (DRO) problem, can be solved efficiently in large scale for a large class of decision problems including portfolio optimization, production and transportation planning, among many others. Worst-case distributions, i.e. distributions attaining the worst-case risk, are characterized, which offer useful intuition about the worst-case scenarios. 

Location 
M3 - Mathematics 3
Room: 3127
200 University Avenue West

Waterloo, ON N2L 3G1
Canada

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