Die Erholunsgzone vor dem D4 Gebäude über dem Brunnen.

Abstracts

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Theresa Traxler - Mean Game Theory and Applications

MFG theory involves optimal control problems with a large number of rational agents, who optimize their behavior by anticipating others' strategies. In finite N-player games, such games result in Nash equilibria, where no controller has an incentive to deviate from the equilibrium strategy. In MFG, however, strategies are implemented based on the distribution of other players. This simplification makes the concept suitable for large populations. The talk will cover the mathematical framework, numerical aspects, as well as some first ideas regarding an application of the concept to Renewable Energy Certificates markets in a continuous time setting.

Andreas Celary - Regime-Switching Affine Term Structures

A term structure relates the price of a contract with its time of maturity. We aim to extend the classical HJM framework for interest rates and energy futures by introducing Markov regime switches. We focus in particular on finite-dimensional realisations in the proposed framework. We obtain no-arbitrage conditions for this model setup and analyse admissible curve families. In the present talk, we will discuss our approach with a multidimensional driving noise process and the implications on the families of admissible curves for the present model.

Sourav Adhikari - Gaining Insights on U.S. Senate Speeches Using a Time Varying Text Based Ideal Point Model

Estimating political positions of lawmakers has a long tradition in political science. Traditionally these estimates were based on their voting behavior. Recent research also investigated the usefulness of text data to infer their political positions. We present the time varying text based ideal point model (TV-TBIP) which allows to study the political positions of lawmakers based on text data in a completely unsupervised way. In addition to identifying political positions, the model also provides insights into topical contents and their change over time. The TV-TBIP model is used to analyze the speeches given in the U.S. Senate by Congress representatives between

1981 and 2016. We demonstrate how the model results allow to conclude that partisanship between Republicans and Democrats has gone up in recent years, confirming empirical results provided using a supervised approach. In addition we investigate the political positions of single representatives over time as well as their position at a specific time point to identify representatives which are positioned at the extremes of their political party based on their speeches. The topics extracted are inspected to assess how their term compositions differ in dependence of the political position as well as how these term compositions change over time.