Im Modul Controlling werden die Grundlagen der Kostenrechnung sowie wichtige Inhalte der elementaren Finanzmathematik unterrichtet. Bei der Kostenrechnung geht es um die fixen und variablen Kosten, die Break-even-Analyse, die Divisions- und Zuschlagskalkulation, die Deckungsbeitragsrechnung und die Normalkostenrechnung. Anschliessend werden Grundlagen für die Erstellung von betriebswirtschaftlichen Statistiken, von Vergleichsrechnungen und Planungsrechnungen dargestellt. Zusätzlich wird in die Cash-Flow-Rechnung eingeführt, indem direkte und indirekte Verfahren beleuchtet werden. Im Rahmen der elementaren Finanzmathematik werden insbes. die Zins- und Rentenrechnung sowie die Anwendung einer nachschüssigen Verzinsung behandelt.

Präsentationen, Fallstudien, Diskussionen

Schriftliche Prüfung (90min)

This course provides students with the knowledge of relevant methodologies in finance, especially in asset pricing. Students will learn to test market efficiency, estimate and test asset pricing models, and forecast stock returns. The course emphasizes practical implementation using R, based on "Tidy Finance with R".
Key topics covered are:

• Introduction to empirical methods in finance and R
• Market efficiency and testing for random walks
• Asset pricing models and portfolio sorts
• Fama-MacBeth regressions
• Return forecasts and predictability
• Integrating financial economics concepts with empirical tests

• Use R and related tools proficiently for empirical analysis.
• Utilize online platforms for data collection, collaboration, and presentation.
• Leverage technology for efficient and accurate empirical research.

After successful completion of the course, students will
Professional competence

• demonstrate proficiency in empirical methods relevant to finance.
• exhibit a deep understanding of market efficiency, asset pricing models, and return forecasting tech-niques.
• possess the ability to critically analyse and interpret empirical findings in financial data.

Methodological competence

• master statistical and econometric techniques applicable to financial data.
• show expertise in using R for conducting empirical research and data analysis.
• design and execute robust empirical tests for financial hypotheses.

Social competence

• collaborate effectively on empirical research projects.
• communicate empirical findings clearly and engage in scholarly discussions.
• appreciate diverse perspectives in empirical research and analysis.

Personal competence

• conduct independent research and engage in self-directed learning.
• apply critical thinking and problem-solving skills in the context of empirical finance.
• reflect on personal biases and methodological approaches.

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Technological competence

• apply data analysis in financial data in R and RStudio.
• Understand, use and adapt advanced empirical methods in R.
• Leverage technology for efficient and accurate empirical research.

Short paper presentation (10%), Empirical project report (60%), Project presenta-tion (30%); Attendance is mandatory (80%)

• Grundlagen der Kosten- und Leistungsrechnung (Aufgaben und Aufbau),
• Kostentheorie und Kostenstrukturen (Gliederung nach Zurechnung auf Kostenträger, Gliederung nach Verhalten bei Beschäftigungsänderungen, Gliederung und Bewertung der Leistungsarten),
• Kostenrechnungssysteme,
• Vollkostenrechnung,
• Kostenartenrechnung (Aufgaben und Zwecke, Betriebsüberleitungsbogen), - Kostenstellenrechnung (Aufgaben und Bildung von Kostenstellen, Betriebsabrechnungsbogen, Verrechnung primärer und sekundärer Stellenkosten, Ermittlung von Zuschlagssätzen),
• Kostenträgerrechnung (Kostenträgerstückrechnung nach Zuschlags-, Divisions- und Kuppelkalkulation, Kostenträgerzeitrechnung),
• Teilkostenrechnung (Kostenaufspaltung, Kostenauflösung),
• Kostenrechnungsschema,
• Deckungsbeitragsrechnung (als Stückrechnung bzw als Periodenrechnung),
• stufenweise Fixkostendeckung,
• Plankosten- und Prozesskostenrechnung,
• Entscheidungsfindungen,
• Kennzahlen,
• Überleitung ins Controlling.

Präsentationen, Fallstudien, Diskussionen

Präsentation und Fallstudienanalyse

Das nachhaltige Agieren innerhalb der historischen Baukultur wird kritisch analysiert und Lehren für die zeitgenössische Architektur und Baukonstruktion werden entwickelt. Das Essential-Modul gibt einen Überblick über die Geschichte der Architektur und Kunst der erweiterten Moderne sowie über die für den Erhalt relevanten Methoden und Techniken.
Anhand ausgewählter Beispiele werden Aufgaben und Problemstellungen in der Architekturgeschichte intensiv diskutiert und die Genese des sich wandelnden ArchitektInnenberufs wird analysiert. Die behandelten Bauten und Objekte versinnbildlichen den Bestand, der unser Erbe ist. Denkmaltheoretisches Grundlagenwissen wird zusammen mit Strategien und Methoden der Erhaltung und Weiterentwicklung des Baubestandes vermittelt.

siehe nachfolgende Lehrveranstaltungen

Die Lernergebnisse und zu erwerbenden Kompetenzen dieses Moduls ergeben sich aus den nachfolgend beschriebenen Lehrveranstaltungen.

Die Abschlussnote wird errechnet aus den Noten der beiden Lehrveranstaltungen mit einer Gewichtung von jeweils 50%. Ein erfolgreicher Abschluss setzt zudemvoraus, dass in beiden Lehrveranstaltungen jeweils mindestens die Note 4.0 erreicht wurde. Modalität siehe Lehrveranstaltung.

• Introduction to taxation of individuals and legal entities in selected jurisdictions: FL, AT, CH, DE
• Application of Double Tax Treaties, Exchange of Information and Mandatory Disclosure Obligations
• National and international taxation of Wealth Structures incl. their Settlors and Beneficiaries
• International Tax Planning and Investment Hubs: CH, FL, HK, IRL, LU, SG
• International Wealth Tax Management of UHNWI with Wealth Structures
• Onboarding of Private Clients (UHNWI) with Wealth Structures: Input Statements by banks & trustees
• Case studies on International Tax Planning of Private Clients (UHNWI) with Wealth Structures and Investments in Participations, Private Equity, Financial Instruments, Real Estate and Tangible Assets
• CFA level III: Topics in Private Wealth Management

Interactive lecture with input statements from local banks, trustees and asset managers

After successful completion of this module, students

• are familiar with tax features of several selected jurisdictions regarding individuals and legal entities;
• are familiar with the characteristics of the various legal entities and financial instruments as well as the national and international links to taxation of asset investments and structures;
• understand the legal basis of asset investments and structures, including tax directives and tax agreements;
• are familiar with practical implications of onboarding private clients with wealth structures
• are familiar with the most common wealth structures used on international tax planning for private clients

see course(s) within the module

Für die Anmeldung zum Modul Research Methods II muss das Modul Research Methods I erfolgreich absolviert sein.

This course is provided through Coursera and is offered by the University of Virginia.

The Economics of AI

The course introduces you to cutting-edge research in the economics of AI and the implications for economic growth and labor markets. We start by analyzing the nature of intelligence and information theory. Then we connect our analysis to modeling production and technological change in economics, and how these processes are affected by AI. Next we turn to how technological change drives aggregate economic growth, covering a range of scenarios including a potential growth singularity. We also study the impact of AI-driven technological change on labor markets and workers, evaluating to what extent fears about technological unemployment are well-founded. We continue with an analysis of economic policies to deal with advanced AI. Finally, we evaluate the potential for transformative progress in AI to lead to significant disruptions and study the problem of how humans can control highly intelligent AI algorithms.

Instructor: Anton Korinek, University of Virginia

This module consists of 6 courses.

Course 1: What is Intelligence?
Course 2: Modeling Technological Progress
Course 3: AI and Economic Growth
Course 4: Labor Markets and Inequality
Course 5: Economic Policy in the Age of AI
Courses 6: The Economics of Transformative AI

The course starts on 10th of February 2025.
The course must be completed by 23rd of May 2025.

All parts of this course are free of charge.

Online courses

You learn how advanced artificial intelligence will affect our economy and our society.

see the course descriptions

Attenance min. 80% mandatory

Grading

This course is designed to guide MSc in Finance students through the essential steps and processes of creating and
developing a start-up in the finance sector, with a special focus on fintech start-ups. Students will learn about idea
generation, business model development, financial planning, and market analysis. The course is highly interactive
and practical, involving workshops, case studies, and hands-on projects to help students transform their ideas into
viable business plans.

Key topics covered in this course include:

• Idea generation
• Business model development
• Financial planning
• Market analysis
• Fintech start-ups
• Workshops
• Case studies
• Hands-on projects

• The course involves interactive seminars with workshops and regular presentations.
• The faculty and a jury of representatives from regional companies evaluate the students’ solutions interms of innovativeness and usefulness and provide them with feedback and advice.

After successful completion of the course, students will

Professional competence

• understand the start-up creation process.
• apply business model development techniques.
• analyse financial planning for start-ups.
• evaluate market opportunities in the finance sector.

Methodological competence

• create viable business plans.
• apply market analysis techniques.
• develop financial projections and budgets.

Social competence

• collaborate effectively in entrepreneurial teams.
• communicate start-up ideas and plans persuasively.
• analyse and incorporate feedback from peers and mentors.

Personal competence

• develop entrepreneurial thinking and mindset.
• improve problem-solving skills.
• enhance creativity in business development.

Presentations (30%), Business Plan (70%); Attendance is mandatory (80%)

• Fundamentals of online trading (esp. e-commerce)
• Economical, legal and ethical aspects of e-commerce
• Business models differentiation of Business-to-Business (B2B) and Business-to-Consumers (B2C)
• Architectures and functionalities (especially marketing, security and payment systems)
• Technologies (intranet, extranets, web shops, collaboration systems and social media,
• E-government
• Case study

Enrollment from WS23/24
These admission requirements:

• To register for modules in the specialization, the modules Statistics, Business Mathematics, and English I must have been successfully completed.
• In addition, the module Information Systems must be successfully completed in order to register for the IMIT specialization.

Enrollment before WS23/24
Either the above admission requirements or:

• To register for fifth semester modules, all modules from the first year of study must be successfully completed.
• Elective courses are not taken into account for these regulations.