Modules WS 2022/2023

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 requirements
  • Database system architecture
  • Diagnosing and handling data quality problems
  • Relational databases (SQL)
  • Hands-on labs with MySQL
  • Concurrency control techniques
  • NoSQL databases (e.g., MongoDB)
  • Apache Hadoop (HDFS, MapReduce)
  • Overview on different Forms and Asset Classes of Alternative Investments
  • Chances and Risks of Alternative Investments
  • Alternative Investments in a Portfolio Context
  • Regulation of Alternative Investments
  • Socially Responsible Investments and Impact
  • Alternative Investments and Corporate Governance
  • Cost of capital and capital budgeting
  • Discounted cash flow valuation and financial multiples
  • Payout policy
  • Equity and debt financing
  • Applications of option pricing theory
  • Corporate control and recapitalizations
  • Enterprise Risk Management
  • Role and Responsibility of Owners
  • Practice of Right of Control for Various Actors
  • Board structures and diversity
  • Theory, Principles, and World-Views
  • The Ethical Leader: Self-Mastery and Ethics, Mind-Sets
  • Corporate Ethics: Shared Values, Professionalism (as part of Standards of Professional Conduct)
  • Developing research questions and hypothesis
  • Designing qualitative and quantitative research
  • Writing and communicating research proposals
  • Students will study the concepts of regression and classification problems (supervised learning) as well as principal components and clustering (unsupervised learning).
  • In parallel, they will learn how to work with financial data with all its pitfalls, cover univariate and multivariate time series models of the mean and volatility and correlations, as well as model long-run relationships.
  • General improvement of the English language skillsReading techniquesFormulation of research questionsBuilding up an argumentWriting convincing textsNegotiation skillsEffective communication in presentationsRelationship Building and Networking
  • Theory, Principles, and World-Views on Ethics
  • The Ethical Leader: Self-Mastery and Ethics, Mind-Sets
  • Corporate Ethics: Shared Values, Professionalism (as part of Standards of Professional Conduct)
  • Introduction to financial economics Equilibrium and arbitrage Valuation, state prices, risk-neutral probabilities Expected utility, risk aversion, mean-variance theory Optimal portfolios
  • Introduction to financial marketsInterest rates and bond pricesThe structure of interest ratesMarket efficiencyMonetary policyMoney marketsBond marketsMortgage marketsDerivative markets
The course aims to introduce students to the critical assessment of financial statements, such that they are able to understand managers’ motivation and capability to engage in earnings management. The assessment of firms’ accounting quality is essential for the reliability of cash-flow forecasts in the context of corporate finance and business valuation. Students will engage with current research in the area, and they will be able to understand the relevance of identifying managerial discretion in accounting choices for the analysis and valuation of companies. Students will work empirically with corporate finance data. This module prepares students for the modules «Alternative Investments» and «Corporate Finance».

Topics covered include (e.g.):

  • The analysis of financial statements
  • The decision-usefulness of accounting information
  • Determinants and managerial motivations for earnings management
  • Earnings smoothing
  • Audit quality and audit fees
  • Empirical research
  • Global Financial Environment
  • International Parity Conditions
  • Foreign Exchange Rate Determination and Forecasting
  • The Foreign Exchange Market and the Use of Foreign Currency Derivatives
  • Foreign Exchange Exposure
  • Financing the Global Firm
  • Foreign Investment Decisions
  • International Trade Finance
  • Working Capital Management
Paper-based preparation of topics, strategy implementation and testing, presentation and discussion
  • Investment Strategies by Asset Class: Equity, Fixed Income, Derivatives Strategies
  • Investment Strategies for Different Economic Environments
  • Asset Management Practice
  • Identification of a research problem and development of a research questionThematically formulating a problem and developing a solution through application of - scientific methods Independence in handling a research problem determined in the course of an assessment.Discussion with the advisor about methodological and content issues in solving a research - topic.Completion of a comprehensive assignment where the students deal with a theoretical or - practice-oriented problem in their field of specialisation by drawing on scientific work methods. Completion of presentation documentation on a research problem within their specialised - field. Defense of the elaborated research topic and in-depth discussion with the examination board.
  • Modelling the Human Life Cycle
  • Models of Human Mortality
  • Valuation Models of Deterministic Interest
  • Models of Risky Financial Investments
  • Models of Pension Life Annuities
  • Models of Life Insurance
  • Models of DB vs. DC Pensions
  • Sustainable Spending at Retirement
  • The Liechtenstein Pension System
  • Overview and introduction to different forms of qualitative methods in finance
  • Key concepts of experimental research approaches
  • Experimental methods to test market and trader behavior
  • Current topics in Basic principles for writing academic textsInternational EconomicsDevelopments in Banking and FinanceInnovation FinanceSustainable Finance
  • Risk modelling
  • Strategical and tactical asset allocation
  • International diversification
  • Forecasting moments of asset returns
  • Foreign exchange rate risks and management
  • Portfolio management
  • Performance analysis
  • Behavioural finance
  • Dividend policy
  • Company valuation
  • Legal and tax issues in financial decisions
  • 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.
  • Statistics is an important module of the MSc in Finance program, with the purpose of making students familiar 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.
  • This involves in particular the concept of statistical learning (the foundation of machine learning and artificial intelligence).
  • In this context students will briefly recapture simple statistical concepts such as hypothesis testing within financial data while at the same time learning to use R, a statistical software package that has become standard in research as well as practice.
  • Additionally, they will learn to find and download data from professional providers (Refinitiv) as well as the internet.
Extracurriculare Activities comprise of various activities that are not linked to the Curriculum of the MSc in Banking and Financial Management, which are optional and further support the studying of the Master programme.