[FAM-news] reminder for upcoming seminars and talks

Sandra Trenovatz sandra at fam.tuwien.ac.at
Mon Dec 14 01:57:50 CET 2015

Joint Seminar: TU Vienna, University of Vienna and WU Vienna

Th., 17.12.2015, 16:30, seminar room SR09
University of Vienna, 1090, Oskar-Morgenstern-Platz 1, 2nd floor

    Kevin Schnelli (Institute of Science and Technology, Klosterneuburg)
    "Local law of addition of random matrices on optimal scale"
    (Vienna Seminar in Mathematical Finance and Probability)

For further details (including abstracts) see

Vienna Graduate School of Finance (VGSF)

Fr., 18.12.2015, 11:00, room D3.0.221
WU Wien, 1020, Welthandelsplatz 1, WU Campus, building D3, ground floor

    Frederico Belo (University of Minnesota, US)
    "External Equity Financing Shocks, Financial Flows, and Asset Prices"
    (Finance Research Seminar)

For further details (including abstracts) see

To find the room on the WU Campus search for "D3.0.221" on:

Announcement of a Habilitation Talk at WU Wien

Fr., 18.12.2015, 12:00, room D4.0.022
WU Wien, 1020, Welthandelsplatz 1, building D4, ground floor

    Birgit Rudloff (WU Wien)
    "Multivariate Risks"
    (Habilitation Talk)

To find the room on the WU Campus search for "D4.0.022" on:

The talk addresses the question how to measure the risk of a 
multivariate random variable X, representing e.g. the vector of risky 
holdings of banks in a system of d banks or a portfolio with random 
outcomes in d assets. In the past literature, one often applies an 
aggregation function to the vector X, then a classical scalar risk 
measure can be used and the problem is reduced to a scalar problem. The 
aim of the habilitation thesis is to discuss shortcomings of the 
aggregation approach in various situations, to develop an alternative 
theory with a economic meaningful interpretation and provide 
computational methods to implement the alternative. It is based on the 
idea that for a multivariate input X, the output of a risk measure can 
(and often should) also be multivariate (e.g. a vector of capital 
requirements of the d banks). As the vector of initial 
capitals/portfolios that makes X acceptable will in generally not be 
unique anymore, this leads naturally to set-valued risk measures. The 
theory of set-valued functions and their optimization has seen rapid 
development within the last decade and provides for the first time the 
mathematical tools that are needed to understand and work with 
set-valued risk measures. In the thesis, a mathematical theory of 
dynamic set-valued risk measures is developed. Somewhat surprisingly, 
many results (e.g. on equivalent characterizations of time consistency, 
dual representations) known for scalar risk measures have a counterpart 
in the the set-valued case. We show that the computation of set-valued 
risk measures is linked to vector optimization and new and improved 
algorithms to solve linear and convex vector optimization problems are 
developed that are also of independent interest in the optimization 
community. Furthermore, we provide a connection between the computation 
of time consistent dynamic risk measures and a set-valued dynamic 
programming principle, which also enables the computation of time 
consistent scalar multivariate risk measures like the scalar super 
hedging price in markets with transaction costs.


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