Modules WS 2024/2025

  • Data Management covers the modern data-management cycle, from the collection of data from diverse sources to the preparation of data for data-driven applications. Students learn how to handle various data formats, how to assess and improve data quality, and how to store and process data using SQL, NoSQL, and Hadoop technologies. The course covers eight primary topics:Modern data-management requirementsDatabase system architectureDiagnosing and handling data quality problemsRelational databases (SQL)Hands-on labs with MySQLConcurrency control techniquesNoSQL databases (e.g., MongoDB)Apache Hadoop (HDFS, MapReduce)
  • Systematically identify and exploit opportunities.
  • Market-Pull, Technology-Push and Blue Ocean.
  • Opportunity Recognition as a process.
  • Systematization of business models and components.
  • Analysis and evaluation of business models.
  • Application of big data algorithms to identify new markets and technologies.
  • This course provides a comprehensive introduction to the principles and practices of academic writing. It focuses on developing the skills necessary for producing clear, well-structured, and scholarly texts. Students will learn to navigate and adhere to academic standards, ensuring their work meets the rigorous expectations of the academic community.Key topics covered are:Basic principles of academic writingProper citation standards (e.g., APA)Conducting comprehensive literature reviewsStructuring research projects Formulating research questionsDeveloping testable hypothesesEffective use of visuals and data in writing
  • This course is designed to foster critical thinking skills among first-semester Master in Finance students. The mod-ule consists of two input sessions, where foundational concepts and techniques of critical thinking are introduced, followed by four discussion sessions. In these discussion sessions, students will analyse and debate current topics with a strong emphasis on applying critical thinking principles to evaluate arguments and evidence.Key topics covered are:Introduction to critical thinkingAnalytical techniquesLogical reasoningBias identificationArgument evaluationCurrent topic discussionsInteractive debatesEvidence-based analysisReflective thinking
Crypto Finance covers an introduction to the blockchain and its applications to crypto markets and portfolio man-agement. The course builds on the basic concepts of the blockchain technology and Bitcoin. The course then ex-tends to the development of Altcoins and their features. The course concludes with the integration of crypto as-sets into portfolio management.
Key topics covered are:
· Blockchain Technologies
· Consensus Mechanisms
· Forks
· Bitcoin
· Altcoins
· Token Sales
· Crypto Portfolio Management
  • This course aims to optimize English language and general communication skills while raising self-awareness to enhance competence. Students will engage in focused information gathering, discussions, and practice. The course covers academic writing skills, negotiations, techniques of persuasion, presentation skills, and decision making. Emphasis is placed on self-reflection and teamwork in a shared learning environment.Key topics covered are:Academic writingPresentation skillsNegotiation techniquesPersuasion and argumentationDecision makingMicro office skillsLanguage developmentSelf-awareness and self-reflection
tba
The course is an introduction to the field of Finance, reiterating the most important concepts from a bachelor's degree with a focus on Finance. It builds on the time value of money principle and applies it to the valuation of bonds, interest rates, and capital budgeting. The course also highlights some of the most significant markets for financial instruments. The main goal is to establish a strong foundation for understanding the key concepts of Finance.
Key topics covered are:
  • Introduction to financial markets
  • Interest rates and bond prices
  • Structure of interest rates
  • Market efficiency
  • Funds markets
  • Money markets
  • Bond markets
  • Introduction to International Tax Policy and Tax Standards
  • Economic and Legal Principles of National and International Taxation
  • International Taxation in an Integrated and globalised World
  • International and European Tax Framework
  • International Tax Competition and Tax Cooperation
  • International Tax Compliance and Tax Law
  • OECD-Tax Agenda: New World Tax Order (Pillar one and two)
  • EU-Tax Agenda: Business Taxation for the 21st Century
  • International re-allocation of taxing rights: Determination of connecting factors
  • Global tax initiatives and actions: OECD, EU, US, UK, RCEP, IMF, UN, and NGOs.
  • This course introduces students to the essential principles and practices of project management, with a particular focus on the finance sector. Students will learn to manage projects in both business and academic settings, devel-oping skills necessary for successful project completion. The interactive nature of the class will involve case studies, group work, and real-world project simulations to enhance learning.Key topics covered are:Project fundamentalsFinancial project managementInteractive learningCase studiesGroup workReal-world simulationsProject planningRisk managementPerformance measurement
  • This course provides a comprehensive introduction to the application of econometric techniques in finance. Stu-dents will delve into both univariate and multivariate time-series analysis, gaining insights into key concepts of modern econometrics. Overall, students will be equipped with the necessary skills to analyse and interpret com-plex financial time-series data effectively. This course combines theoretical knowledge with practical application using R. Key topics covered are:Stationarity, differencing, and co-integrationHeteroskedasticity and volatility clusteringSelf-dependence and endogeneityVector auto regressions.Time series modelling, including ARMA and GARCHImplement and empirically test the above mentioned in R
  • The purpose of this course is to familiarize students with the statistical methods and tools necessary not only for producing high quality research output in finance, but also necessary to understand and apply the quantitative tools that are at the core of a modern and innovative financial business. In this context, students will recapture common statistical concepts such as regression analysis and hypothesis testing within financial data as well as the basics of linear algebra. Simultaneously, students will learn how to use R, a statistical software that has become standard in research and industry. A third competence gained during the course is about how to find and down-load data from professional (Refinitiv) and open-source data providers. Key topics covered are:Statistical programming in R (tidy data handling, programming)Basics of linear algebra (vectors, matrices, systems of linear equations)Descriptive statistics for uni- and multivariate analysisTime series analysisHypothesis testingRegression analysis: uni-/ multivariate, (non-)linear