BBS Summer Term 2018
The PhD Research Seminar in Mathematics for Economics and Business ("Brown Bag Seminar") takes place on Wednesdays from 12:30 to 13:30 in seminar room D4.4.008 (Building D4, Entrance A, Level 4).
The seminar is a forum where PhD students and postdocs present their research projects; work in progress is fully ok. Typically, each presentation is followed up by a short discussion. Moreover, some more senior faculty members talk about their work.
Seminar Schedule
March 14 / 12:30 / D4.0.019
Gregor Kastner: Sophisticated and small versus simple and sizeable: When does it pay off to introduce drifting coefficients in Bayesian VARs?
[Discussant: Sylvia Frühwirth-Schnatter]
> Slides > PaperMarch 21 / 12:30 / D4.4.008
Tina Wakolbinger and Vera Hemmelmayr (both: Institute for Transport and Logistics Management, WU): Sustainable logistics and humanitarian supply chains: Research topics and methodsApril 18 / 12:30 / D4.4.008 (Research Seminar)
Eric Eisenstat (School of Economics, The University of Queensland, Brisbane, Australia): Efficient Estimation of Structural VARMAs with Stochastic VolatilityApril 25 / 12:30 / D4.4.008
Rainer Hirk: mvord: An R Package for Fitting Multivariate Ordinal Regression Models
> Slides > Package mvord
[Discussant: Florian Schwendinger]May 2 / 12:30 / D4.4.008
Kevin Kurt: A Dynamic Credit Risk Model for European Safe Bonds
[Discussant: Annalisa Cadonna]May 9 / 12:30 / D4.4.008
Stefan Voigt (VGSF): Large-Scale Portfolio Allocation Under Transaction Costs and Model UncertaintyMay 16 / 12:30 / D4.4.008
Gabriela Kovacova: Time Consistency of the Mean-Risk Problem and Dynamic Vector Optimization Problems
[Discussant: Christian Diem]May 23 / 12:30 / D4.4.008
Annalisa Cadonna: Bayesian spectral modeling for locally-stationary time series
[Discussant: Sylvia Frühwirth-Schnatter]May 30 / 12:30 / D4.4.008
Stefan Bachhofner: ReKlaSat 3D - Deep Learning on Satellite Images
[Discussant: Niklas Schmidinger]June 13 / 12:30 / D4.4.008
no seminarJune 20 / 12:30 / D4.4.008
Gertraud Malsiner-Walli: Learning the number of components and the number of clusters in Bayesian finite mixture models
[Discussant: Riccardo Rastelli]