We study the preferences 
of agents for diversification and better outcomes when they are facing both, in Frank Knight's 
formulation,
measurable as well as 
unmeasurable uncertainty. Following Anscombe and Aumann, such a situation can be modeled by preferences 
expressed on stochastic kernels, 
that is scenario dependent lotteries. By means of automatic continuity methods based on Banach-Dieudonné's 
Theorem on Fréchet spaces, we 
provide a robust representation. This gives us some insight into the 
nature of uncertainty aversion 
these preferences are expressing. We further investigate under which conditions these two intricate 
dimensions of uncertainty can be 
disentangle into a distributional uncertainty, in the direction of von Neumann and Morgenstern's theory, and a 
probability model uncertainty, in 
the spirit of risk measures. These results allow in particular to address both Allais as well as Elsberg's 
paradox.

LOCATION:
The seminar will be held on Wednesday, 15 January, at 18.00 
at Aula di Rappresentanza, Department of Mathematics, Milano University, Via 
Saldini 50, Milano.
A refreshment will be offered at 
17.30.

Scientific Committee:

Prof. Marco Frittelli (Univ. 
degli Studi di Milano)
Prof. Fabio Maccheroni (Univ. Bocconi)
Prof. 
Massimo Marinacci (Univ. Bocconi)
Prof. Emanuela Rosazza Gianin (Univ. 
Milano-Bicocca)
Dott. Simone 
Cerreia-Voglio (Univ. Bocconi)
Dott. Marco Maggis (Univ. degli Studi di 
Milano)