Prof. Nils Deterings research spans a wide range of topics within financial mathematics, with a particular focus on quantifying systemic risk in the financial system, and advanced pricing and risk management strategies for energy markets. Additionally, he develops machine learning methods for addressing problems in financial mathematics. He has published over 20 scientific articles in Finance & Stochastics, SIAM Journal on Financial Mathematics, Mathematics and Financial Economics, and in Stochastic Processes and Their Applications, among others.

Before joining Heinrich-Heine University in 2023, Prof. Nils Detering was a tenured Associate Professor at the University of California in Santa Barbara. He holds a PhD from Frankfurt School of Finance & Management, and an undergraduate degree in Mathematics from Georg-August University in Göttingen.

Research interests

• Financial systemic risk and random graphs, in particular percolation on random graphs
• Infinite-dimensional stochastic analysis and energy markets
• Machine learning for finance

Publications

For a detailed list, please refer to publications.

Teaching

• Probability Theory (Wahrscheinlichkeitstheorie) (Fall 2023)
• Special Topic (Random Graphs and Random Matrices) (Spring 2020)
• Probability and Combinatorics (Spring 2019, Fall 2020, Fall 2021)
• Applied Stochastic Processes (Fall 2018, Winter 2019, Winter 2021, Spring 2022, Fall 2022, Winter 2023)
• Introduction to Mathematical Finance (Winter 2017, Fall 2017, Spring 2018)
• Measure Theory for Probability (Fall 2016, Fall 2017, Fall 2019, Fall 2020)
• Introduction To Probability Theory And Stochastic Processes (Fall 2021, Fall 2022)
• Advanced Probability Theory (Random Graphs and Systemic Risk) (Winter 2017)
• Advanced Topics in Financial Modeling (Systemic Risk) (Spring 2018)
• Advanced Stochastic Processes/Financial Modelling (Winter 2023)
• Advanced Probability Theory/Financial Modelling (Spring 2023)

For further details concerning Prof. Detering's teaching at HHU please refer to this page: teaching.