Vorlesungsverzeichnis

Valuation and Value-based Management (V+Ü) (Vorlesung)

Inhalt: This course establishes a link between the external valuation of companies (e.g., by investors and analysts), and the internal practices that top executives apply to manage a company in a value-based manner. It thereby demonstrates the link between the areas of accounting, corporate finance, and management control. The course covers the following topics (not exhaustive): • Essential theories and purposes of valuation using financial statements • Valuation methods (e.g., earnings, cash, or assets) • Analyses of profitability and risk • Financial forecasting and trend analyses • Diffusion of Value-based Management (VBM) • Empirical evidence on the antecedents and performance effects of VBM • Internal VBM-tools, selected fields of application, and stakeholder implications • Real-life valuation examples (selected topics with practice partners)

Masterprogramm Management - Management & Sustainable Accounting and Finance - Valuation & Value-based Management

Masterforum Management & Sustainable Accounting and Finance (Kolloquium)

Dozent/in: Henning Schröder, Patrick Velte

Masterprogramm Management - Management & Sustainable Accounting and Finance - Masters Forum

Empirical Research Design and Causal Inference: Applications and Reflections (Seminar)

Dozent/in: Henning Schröder

Inhalt: The course aims to introduce students to empirical research methods and applied data analysis. It will help participants to better understand common empirical research designs frequently applied in the field social sciences. Specifically, the course discusses how these methods are used in top-tier research papers and provides an introduction on how to apply the discussed methods to real-world archival data using statistical software. The first part of the course reviews econometric fundamentals and introduces students to the widely used statistical software STATA (available via a Campus license). In the second part of the course the focus will be on endogeneity issues, causal inference, and empirical identification strategies. The course is well suited for students who want to work with archival data in future research projects or during their master thesis. Participants should have at least a basic knowledge in statistics. However, this course will not resemble the statistics courses students might have taken. Instead, the course is designed to be more hands-on and discussion-oriented. The goal is to demystify the key concepts and fundamentals of modern empirical analysis, to provide practical skills, and to encourage students to develop their own empirical research projects.

Bachelor-Kolloquium Management & Sustainable Accounting and Finance (Seminar)