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Séminaire : A coherent representation of worst-case distributions - demystifying distributionally robust risk measures

Séminaire : A coherent representation of worst-case distributions - demystifying distributionally robust risk measures

Séminaire du GERAD conjoint avec la Chaire de recherche du Canada sur la prise de décision en incertitude 

Titre : A coherent representation of worst-case distributions - demystifying distributionally robust risk measures

Conférencier : Jonathan Y. Li – Telfer School of Management, Canada 


In this talk, we will present two main results in our study of distributionally robust risk measures (a.k.a. worst-case risk measures), where the largest risk level needs to be estimated in the case that only on the mean and variance information is available. We show that the problem can be boiled down to a closed-form expression for any (law invariant) coherent risk measure, and most importantly, the worst-case distributions giving the largest risk estimate can be fully characterized by distributions bounded from below. In particular, the worst-case distributions are coherent in their representation of one’s subjective risk aversion and hence, they provide convincing intuition for the usefulness of distributionally robust risk measures.

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Entrée gratuite.
Bienvenue à tous!

 

Date

Mardi 27 juin 2017
Débute à 14h00

Prix

gratuit

Contact

Lieu

Université de Montréal - Pavillon André-Aisenstadt
2920, chemin de la Tour
Montréal
QC
Canada
H3T 1N8
514 343-6111
4488

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