This optional module allows for various kinds of research studies. It is closely connected to the five units of the Liechtenstein School of Architecture and is usually part of ongoing research projects. The supervision consists of directing the students towards clear results within a given field of research. The individual study is reviewed within the respective unit.

Urbanism, Architecture & Society Unit:
This Independent Study is part of the Erasmus+ project “Socio-Eco-Hoods” and supports the preparatory work for participatory activities in the Liechtenstein work package. It centers on stakeholder mapping in the Mühleholz/Ebenholz neighborhood, aiming to identify and analyze key actors that shape spatial and social developments.Students will map associations, community initiatives, municipal organizations, or informal networks to understand their roles, interests, and interrelations—and reflect on the role the University could play in neighborhood development. Methods may include semi-structured interviews, stakeholder analysis, and visual mapping techniques. The outcome will be a clear and usable overview of the local actor landscape, supporting future collaboration, co-creation, and public engagement in the design studio and workshops. This study provides a useful tool to situate the university within the neighborhood and enhances students’ skills in actor analysis for design and participation processes.

ASSESSMENT Written Assignment (20,000 to approx. 30,000 characters (incl. spaces)) and Oral Presentation

Self-defined design or research studies, developed individually or in groups agreed upon with research units and under the guidance of mentors. The size of the module is determined by the respective unit.

After successful completion of the course, students will be able to

Minimum 75% compulsory attendance, regular meetings with instructors, continuous assessment, portfolio and final review.
The final grade is calculated according to the weighting of the following components: final submission (80%) and oral presentation (20%).

Individual appointments will be set with the tutor.

You can register for this independent study alone or in a group. For registration and enrolment, please get in touch with Johannes Herburger: johannes.herburger@uni.li or Cornelia Faisst: cornelia.faisst@uni.li

Asset pricing is the process of determining the fair value of financial assets. It involves using various financial theories and models to estimate the price of these assets based on factors like time discounting, future cash flows, interest rates, and risk. By analysing historical data, empirical asset pricing seeks to validate or refine theories about how prices are set, how risks are compensated, and how various factors influence asset prices. Ultimately, it aims to enhance our understanding of financial markets and improve investment strategies.
Key topics covered are:

• Efficient Markets and the Valuation of Assets
• The Capital Asset Pricing Model (CAPM)
• Empirical Validation of the CAPM
• The Arbitrage Pricing Theory
• Multi Factor Models and Anomalies
• Pricing of Alternative Asset Classes
• Predictability in Financial Markets

• Lectures
• Asset pricing exercises
• Asset pricing project
• Short paper presentation

After successful completion of the course, students will
Professional competence

• understand cornerstones of asset pricing theory.
• apply crucial empirical methods to validate or challenge the fundamental theory.
• understand the concepts of market efficiency, risk factors, and the impact of investor behaviour on asset prices.
• evaluate the correct pricing of assets.
• recognize the challenges of outperforming the market.

Methodological competence

• estimate and evaluate expected returns.
• apply empirical asset pricing methods to realistic scenarios in R.
• evaluate a model’s asset pricing performance.

Social competence

• collaborate effectively in an asset pricing project.
• develop and enhance presentation skills.

Short paper presentation (10%), Written exam (60%), Empirical asset pricing project (30%); Attendance is mandatory (80%)

Growth Strategies & Alliances

• Wachstum in unterschiedlichen Dimensionen als Erfolgstreiber für junge und etablierte Unternehmen.
• Ober- und Untergrenzen des Wachstums.
• Strategische Wachstumsrichtungen.
• Implikationen des Wachstums für Organisation und Führung.
• Strategische Allianzen als Expansionsstrategie.
• Möglichkeiten und Grenzen der Kollaboration junger Unternehmen mit grossen, etablierten Unternehmen.

Growth Simulation

• Entwicklung von Wachstumsstrategien junger Unternehmen in der komplexen Simulation "Growth".
• Zusammenhänge zwischen strategischer und operativer Führung (Galweiler-Schema).
• Unterschiede zwischen den Wachstumsstrategien junger Unternehmen und den strategischen Möglichkeiten grosser, etablierter Unternehmen.
• Ergänzung der Erfolgsbewertung der teilnehmenden Teams durch IT-gestützte Berechnung der Aktienkurse auf der Basis von KPIs.

Life Cycle Management of Product & Services

• Life Cycle Management als Prozess.
• Roadmapping als Planungsgrundlage für erfolgreiches Life Cycle Management.
• Product und Services Development.
• Market Test und Market Launch Strategien.
• Wachstum durch Product-Service-Systems.
• Strategien zur De-Commoditisierung.
• Kunden-Analytics im Life Cycle Management.

• In this module, students will write a thesis on a finance topic of their choice. The module involves identifying and analysing a research problem, structuring it into research questions, selecting and applying appropriate research methods, and writing a comprehensive thesis. Students will also discuss their progress with experts and faculty members and defend their thesis in an oral examination. Both tracks provide research-based knowledge but differ in their focus. The research track emphases the methodology pillar, while the industry track puts more weight on the expert knowledge pillar and the development of business-related personality skills.

The number of characters should be between 150.000-300.000 characters. That relates to the contents in the text section of the work. It does not include the abstract or any lists, illustrations, tables, appendices, etc. These numbers are meant to be benchmark values; deviating from these values is possible after confirming with the supervisor

Key topics covered in this course include:

• Identifying a research problem
• Structuring research questions
• Applying research methods
• Writing the thesis
• Discussing progress with experts
• Defending the thesis

• The thesis is assessed by a faculty member from the Liechtenstein Business School (professor, assistant professor, visiting professor or senior lecturer).
• The thesis is presented and defended in an oral examination. The examination committee is composed of the Academic Director, another faculty member, and an external expert.

After successful completion of the course, students will

• Professional competenceidentify and analyse a research problem in finance.structure a research problem into clear research questions.apply appropriate research methods effectively.

• Methodological competencedevelop and implement a research methodology.write a comprehensive thesis, including methodology, results, and interpretation.

• Social competencediscuss research progress with experts and faculty.present and defend the thesis in an oral examination.

• Personal competencedemonstrate critical thinking and analytical skills.manage a significant research project independently.

• Technological competenceutilize advanced research tools and software.apply digital tools for writing and data analysis.

• Start of the Thesis Project:winter semester: 01.07.summer semester: 01.02. - Submission deadline of the Master thesis:winter semester: 30.11.summer semester: 30.06. - Grading:70% Thesis30% P&D

In this module, students will write a thesis on a finance topic of their choice. The module involves identifying and analysing a research problem, structuring it into research questions, selecting and applying appropriate research methods, and writing a comprehensive thesis. Students will also discuss their progress with experts and faculty members and defend their thesis in an oral examination. Both tracks provide research-based knowledge but differ in their focus. The research track emphases the methodology pillar, while the industry track puts more weight on the expert knowledge pillar and the development of business-related personality skills.

The number of characters should be between 90.000-180.000 characters. That relates to the contents in the text section of the work. It does not include the abstract or any lists, illustrations, tables, appendices, etc. These numbers are meant to be benchmark values; deviating from these values is possible after confirming with the supervisor

Key topics covered in this course include: • Identifying a research problem

• Structuring research questions
• Applying research methods
• Writing the thesis
• Discussing progress with experts
• Defending the thesis

• The thesis is assessed by a faculty member from the Liechtenstein Business School (professor, assistant professor, visiting professor or senior lecturer).
• The thesis is presented and defended in an oral examination. The examination committee is composed of the Academic Director, another faculty member, and an external expert.

After successful completion of the course, students will

Professional competence

• identify and analyse a research problem in finance.
• structure a research problem into clear research questions.
• apply appropriate research methods effectively.

Methodological competence

• develop and implement a research methodology.
• write a comprehensive thesis, including methodology, results, and interpretation.

Social competence

• discuss research progress with experts and faculty.
• present and defend the thesis in an oral examination.

Personal competence

• demonstrate critical thinking and analytical skills.
• manage a significant research project independently.

Technological competence

• utilize advanced research tools and software.
• apply digital tools for writing and data analysis.

Start of the Thesis Project:

• winter semester: 01.07.
• summer semester: 01.02.

Submission deadline of the Master thesis:

• winter semester: 30.11.
• summer semester: 30.06.

Grading:

• 70% Thesis
• 30% P&D