Teaching
Please find an overviewed of some courses. If you have any specific questions about course topics, feel free to message my office, and a teaching staff member will respond as soon as possible.
Machine Learning in Finance
Winter Semester
This master course covers machine learning techniques and their application in finance. It begins with an introduction to machine learning and data handling in finance, followed by supervised regression models, including Ridge and Lasso regression. Practical sessions focus on Python and R, teaching students to implement and evaluate models. The course also covers decision trees, ensemble methods like Random Forests, and deep learning with neural networks for predicting stock returns. Advanced techniques such as optimization, model tuning, and case studies provide practical insights into real-world financial applications.
Summer Semester
This seminar focuses on the application of data science techniques to asset pricing in financial markets. Students explore advanced topics in asset pricing, including factor models, risk premia, and market anomalies, alongside data science methodologies. The seminar is designed to enhance students' understanding of how data-driven approaches can be applied to develop and test asset pricing models. Through a combination of empirical research and hands-on data analysis, students undertake projects that apply these techniques to real-world financial data, presenting their findings and contributing to discussions on contemporary challenges in asset pricing.
Winter Semester
This master course covers foundational models, such as the Capital Asset Pricing Model (CAPM) and multi-factor models, along with their applications in estimating expected returns and assessing risk. The course also includes portfolio construction and optimization strategies, focusing on methods like mean-variance optimization, the Black-Litterman model, and robust optimization techniques. Students engage with real-world data and case studies to develop skills in constructing efficient portfolios, evaluating investment strategies, and understanding the trade-offs between risk and return in various market conditions.
Summer Semester
This lecture at the bachelor level covers theories and best practices related to firms’ financial and investment decisions. Students learn about the time value of money, how to use financial information to make decisions, such as reading balance statements, and using company performance indicators to find an adequate capital structure and estimate the cost of capital. Furthermore, they are able to apply concepts of capital budgeting and investment analysis to choose among investments.
Winter Semester
This seminar is designed to teach undergraduate students how to perform financial valuation techniques in the context of financial management. The course emphasizes practical skills in valuing companies, projects, and investment opportunities using various methodologies, including discounted cash flow (DCF) analysis and relative valuation. Students apply their theoretical knowledge to real-world cases, conducting comprehensive valuations and developing investment recommendations.