Advanced Investment Strategies
Advanced Investment Strategies
Module Coordinator/Lecturers
Study Programmes
Master's degree programme in Innovative Finance
Project Description
The Advanced Investment Strategies course is designed to provide students with in-depth knowledge and practical
skills in advanced portfolio management and investment strategies. The course is structured into two main parts. The first half focuses on advanced portfolio management and optimization techniques such as improved estimates, Black-Litterman and equal risk contribution portfolios. The second half involves student groups presenting and implementing (in R) advanced investment strategies from selected papers, covering various techniques (e.g. statistical arbitrage) and datasets (such as bonds, exchange rates, crypto currencies or derivatives).
Key topics covered in this course include:
skills in advanced portfolio management and investment strategies. The course is structured into two main parts. The first half focuses on advanced portfolio management and optimization techniques such as improved estimates, Black-Litterman and equal risk contribution portfolios. The second half involves student groups presenting and implementing (in R) advanced investment strategies from selected papers, covering various techniques (e.g. statistical arbitrage) and datasets (such as bonds, exchange rates, crypto currencies or derivatives).
Key topics covered in this course include:
- Advanced Portfolio Management Techniques
- Optimization Methods: Improved Estimates, Black-Litterman, Equal Risk Contribution
- Statistical Arbitrage
- Investment Strategies for Bonds
- Exchange Rate Strategies
- Cryptocurrency Strategies
- Derivative-based Strategies
- Implementation of Investment Strategies using R
Teaching Method
- The module involves interactive lectures with exercises to integrate theoretical knowledge with critical analysis skills.
- Case studies are used to discuss the course contents.
- Contemporary scientific publications from Information Systems and Human-Centred Design are discussed in class.
Learning Results
After successful completion of the course, students will
Professional competences
Methodological competences
Technological competences
Social competences
Personal competences
Professional competences
- gain advanced knowledge in portfolio management and optimization techniques.
- understand and apply various advanced investment strategies to different asset classes.
- develop the ability to critically evaluate and implement investment strategies.
Methodological competences
- utilize advanced optimization methods for portfolio management.
- apply statistical arbitrage and other quantitative investment techniques.
- integrate financial theories with practical investment strategy implementation.
Technological competences
- proficiently use R for advanced portfolio management and strategy implementation.
- analyse and manage different datasets using R for investment decision-making.
- leverage technology to enhance investment strategy development and execution.
Social competences
- collaborate effectively in groups to research and present investment strategies.
- communicate complex investment concepts and strategies clearly and concisely.
- engage in constructive discussions and provide feedback on peer presentations.
Personal competences
- develop independent research skills in advanced investment techniques.
- enhance problem-solving abilities in the context of financial data and strategies.
- reflect on the ethical and practical implications of advanced investment strategies.
Assessment Methods
Final written exam