Past & Ongoing Thesis Supervision
2025-01-15
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5 min read
University of Liechtenstein
PhD Theses
- In Progress:
- Parameter Uncertainty and Portfolio Management (PhD, A. Lukas Salcher )
- Machine Learning in Financial Economics (PhD, A. Merlin Bartel)
- Machine Learning in Bank Treasury (PhD, A. Michael Nigsch)
- Innovative AI Models for Advanced Risk Management in Financial Institutions (PhD, A. Simon Kühne)
MSc Theses
In Progress:
2024:
- Explaining Factor Momentum: The Impact of Shared Stocks in Long and Short Factor Portfolios (MSc, A. Oliver Nägele, best Master in Finance 2024)
- Modern Portfolio Optimization: Clustering, Machine Learning, and Higher-Order Moments (MSc, A. Matěj Ingršt)
- The Effects of Geopolitical Conflicts on Financial Markets - Examining the Effect on the Performance of US Defense Stocks (MSc, A. Pascal Herrmann)
2023:
- Parameter Uncertainty and Equity Premium Prediction via Machine Learning Techniques (MSc, A. Moritz Graf)
- Factor Momentum Performance in Multivariate Characteristic Based Portfolios (MSc, A. Paul Burkart)
- Measurement and Comparability of Impact Investing in Asset Management (MSc, A. Susanne Schneider)
- Predicting stock returns in the presence of breaks by following the approach from Smith and Timmermann (2021): Evidence from the European market (MSc)
2022:
- The Risk Premium of Critical Raw Materials - A Signal for Priority Needs in Realising the European Green Deal (MSc, A. Caroline White)
- Empirical asset pricing via Machine Learning: Evidence from the Cryptocurrency Market (MSc, A. Stefan Macanovic)
- Inflation-Hedged Portfolios within the European Stock Market (MSc, A. Fabian Köffel)
- Robust Portfolio Optimization with Deep learning - Using past Forecast Errors to Improve Return Predictions (MSc, A. Markus Wabnig, best Master in Finance 2022)
- The EUR/CHF Exchange Rate and Euro Area Stress (MSc, A. Nicolas Tschütscher, best Master Thesis in Finance 2022)
- Incorporating ESG Score Changes in Portfolio Management via Deep Learning (MSc, A. Lukas Müller)
- Neural Network for KPI based Time Series Sales Forecasting (MSc, A. Niklas Leibinger)
- Optimal Portfolio Building using Deep Learning Techniques (MSc, A. Michael Metz)
- Economic Uncertainty Premia in U.S. Stock Markets during the COVID-19 Pandemic (MSc, A. Leo Pitscheneder)
2021:
- Multivariate Factor Forecasting and Smart Beta Investments (MSc, A. Dominik Brändle)
- Evaluating Dollar-Cost Averaging under the Aumann-Serrano Framework (MSc, A. Jonas Sterk)
- Impact of ESG exclusion on firms’ cost of capital (MSc, A. Fabian Müller)
- Sales Forecasting with Machine Learning (MSc, A. Johannes Gassner)
- Investors’ herding in the German equity options market: Evidence from the COVID-19 crisis (MSc, A. Dmytro Livshyts)
2020:
- Momentum meets Uncertainty (MSc, A. Dominik Kaiser, best Master Thesis in Finance 2020)
- Changes in Investor Attention and the Cross-Section of Stock Returns: Evidence from Thomson Reuters and Google Trends (MSc, A. Emanuel Broger)
2019:
- Cross-Sectional Volatility and the Prediction of Factor Premia (MSc, A. Maibach, Runner-Up Finance Award)
- Multi-Factor Timing (MSc, B. Bruno Jäger, Winner of Finance Award, best Master Thesis in Business Science)
- Stock Age as Proxy for Uncertainty of Parameters (MSc, S. Sven Sturzenegger)
- The Influence of News Coverage on Stock Returns – Evidence from European Markets (MSc, A. Alexander Person)
2018:
- Liquid betting against beta revisited: Evidence from all over the world (MSc, L. Lukas Salcher)
- From IPO to Obsolete: Stock Age related investment strategies (MSc, P. Thoma)
- Eurex index dividend futures hedging (MSc, A. Adrian Spiegel)
- Predicting Equity Bear and Bull Markets: International Evidence (MSc, L. Luca Liepert)
2017:
- Liquidity and the Polish Stock Market: Empirical Tests of Asset Pricing Models and Inclusion of Liquidity Factors (MSc, P. Pavol Ruzicka)
- Dynamic Asset Allocation Strategies and An Optimisation Framework: How Optimal is Optimised? (MSc, F. Frank Balz)
- Prediction of the Monthly Sovereign Yield Spread Changes in EMU Countries from 2000 to 2016 using the Illiquidity Measure ‘Noise’ in Bond Prices (MSc, P. Philippe Heise)
2016:
- Terrorism and its effect on financial markets (MSc, S. Geiger)
- Betting Against Beta (MSc, C. Claudio Lamprecht)
- Cross-Sectional and Option-Implied (Higher) Moments and the Predictability of Historical Volatility: US Study (MSc, O. Vukovic)
2015:
- The Relationship between Commodities and the Stock Market - Empirical Evidence for the Eurozone (MSc, P. Kain)
- The Effectiveness of Constant and Time-Varying Futures Optimal Hedge Ratios - Empirical Evidence from the European Stock Market (MSc, E. Panagakou)
BSc Theses
- 2024:
- Auswirkungen von Indexänderungen auf Einzelaktien (BSc, A. Kenny Seifert, Runner-Up best Bachelor Thesis in Financial Services 2024)
- 2023:
- Performancevergleich und -entwicklung von aktiv und passiv gemanagten Schweizer Aktienfonds im Zeitraum von 1989 bis 2022 (BSc, A. Jessica Albrecht)
- 2022:
- Sub-portfolio Optimization (BSc, A. Jasminko Kulenovic)
- Stock Market Prediction With Long Short-Term Memory Recurrent Neural Networks (BSc, A. Elizabeth Sanyal)
- 2021:
- Cryptocurrency: Delisting Bias in the coinmarketcap database (BSc, A. Fabian Köffel)
- 2020:
- “Long/Short” Momentum-Strategie am Kryptowährungsmarkt (BSc, A. Timothy Rist, best Bachelor Thesis in Business Administration 2020)
- 2019:
- Portfolio Optimization in a Cryptocurrency Environment: An Omega Optimization (BSc, D. Dominik Brändle, Runner-Up Finance Award)
- 2018:
- The North Korea threat and its effect on global stock markets: The case of South Korea, Japan and the USA (BSc, M. Markus Wabnig)
- 2017:
- Using momentum to improve low-volatility strategies: Evidence from the US stock market (BSc, M. Amann)
- 2016:
- Prognose von Aktienrenditen - Eine empirische Forschung über die Vorhersagbarkeit der zukünftigen Renditen des Swiss Performance Index anhand von Renditen-Dispersionen (BSc, B. Bruno Jäger)
Other Theses
- 2020:
- Künstliche Intelligenz und Anwendungsmöglichkeiten in der Vermögensberatung (MBA, A. Lukas Schäper)
- Stock Price Prediction for Portfolio Management Using Recurrent Neural Networks and Machine Learning (EMBA, A. Jensen Chang)