Master's Thesis
A Master’s thesis at the Chair of Mathematical Finance provides the opportunity to engage with mathematics both in its theoretical depth and its practical relevance. Students may choose to work in topics ranging from in pure mathematic, like stochastic calculus, to more applied aspects within mathematical finance and actuarial science. In general, the research is mathematical finance is inherently interdisciplinary: techniques from probability theory, stochastic analysis, optimization, numerical analysis, and statistics are combined to study issues that arise in finance, insurance, economics, and modern data-driven applications. A Master’s thesis in this environment allows you to deepen your theoretical knowledge, strengthen your methodological skills, and contribute to ongoing research at the interface of mathematics and its applications.
We supervise Master’s theses across a broad spectrum of topics, ranging from theoretical to applied, including:
- actuarial science
- computational finance
- mathematical finance
- mathematical foundations of machine learning
- stochastic analysis
- stochastic differential equations
- rough path theory
Target Audience
Motivated students of (business) mathematics with a strong interest in mathematics itself and its applications, in particular in quantitative finance and actuarial science, are welcome. We strive to select engaging topics that match each student’s background while still providing a stimulating challenge. As in all areas of mathematics, a certain degree of persistence is certainly an advantage.
Course of Studies
With its extensive range of courses, the University of Mannheim offers an excellent opportunity to specialize in mathematical finance and stochastics during the Master’s program.
As a foundation for writing a Master's thesis at the Chair of Mathematical Finance, we strongly recommend attainting the following course:
- Mathematical Finance (if not taking during the Bachelor studies),
- Stochastic Calculus,
- Advanced Topics in Mathematical Finance,
- Seminar “Finanzmathematik”.
Complementing the courses mentioned above, the School of Business Informatics and Mathematics offers numerous opportunities to deepen and broaden your knowledge in actuarial science, mathematical finance, and stochastics, including:
- Stochastic Processes,
- Functional Analysis,
- Algorithmic Trading and Stochastic Control,
- Computational Finance,
- Monte Carlo Methods 2.
This broad range of courses allows you to specialize in (business) mathematics according to your personal interests, from purely theoretical to highly applied aspects
In addition, a variety of applied courses in quantitative finance are offered by the Department of Economics and the Business School at the University of Mannheim.
Topics from Recent Years
As a reference, you will find here a list of Master’s thesis topics from previous years:
- Stability of Optimal Stopping Problems under the Adapted Wasserstein Distance
- An optimal stopping approach to the pricing of variable annuity contracts
- Market Making with Model Uncertainty
- Portfolio Optimization under Risk Constraints
- Stability of efficient hedging prices
- Asset Price Bubbles and Their Detection Using Deep Learning Methods
- Optimal stopping with rough path signatures
- Signature Methods Applied to Stochastic Portfolio Optimization
- Detecting Statistical Arbitrage with Deep Neural Networks
- Validation of capital market modeling for PRIIPs
- Portfolio Optimization with Reinforcement Learning
- Analysis of Signature-based models and their application in Mathematical Finance
- The Decarbonization Game: A mean-field perspective on Green Finance
- Deep approximation of super-hedging prices
- Derivatives Pricing using signatue methods
- Generative Time Series Modelling via Neural Differential Equations
- Calibration of Financial Models: RKHS Regularization of Local Stochastic Volatility Models
- Portfolio Optimization in Rough Volatility Models
- On the exact calibration of local stochastic volatility models
- On relative arbitrage of functionally generated portfolios
- On stochastic integration for Gaussian processes
- Pathwise one-dimensional SDEs
- Existence and Uniqueness of Solutions of Stochastic Volterra Equations
- Optimal Hedging under Integer Constraints
- Generalisations of Universal Portfolios in Stochastic Portfolio Theory
- Pathwise Delta hedging of Exotic options
- Option pricing in delayed Black-Scholes models
Application
For Master’s theses at the Chair of Mathematical Finance, no formal application process is required. Nevertheless, please contact David Prömel early to plan your thesis, but no later than five weeks before the intended starting date.
You are also very welcome to contract us at the beginning of your Master’s studies for an advisory meeting and support with planning your studies.