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Kevin Kamm

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MIT-huset, plan 3, Matematik och matematisk statistik, MIT.D.345 Umeå universitet, 901 87 Umeå

While studying mathematics at the Technische Universität Berlin, I discovered a strong fascination for stochastic analysis and financial mathematics. This led me to pursuing a Ph.D. in financial mathematics as a member of the ABC-EU-XVA project at the University of Bologna. Today, I am thrilled to be conducting cutting-edge research on optimal strategies within the area of commodities, leveraging the power of Deep Learning techniques to make current models more realistic. I am also very intrigued by the exciting possibilities of high-performance computing (HPC) in the context of SPDEs and financial mathematics in general.

Quantitative finance (Print)
Ewald, Christian Oliver; Kamm, Kevin
Mathematics and Computers in Simulation, Elsevier 2023, Vol. 207 : 189-208
Kamm, Kevin; Pagliarani, Stefano; Pascucci, Andrea
International Journal of Financial Studies, MDPI 2022, Vol. 10, (2) : 38-38
Di Francesco, Marco; Kamm, Kevin
SeMA Journal, Springer Nature 2021, Vol. 79, (4) : 593-618
Di Francesco, Marco; Kamm, Kevin
Journal of Scientific Computing, Springer Nature 2021, Vol. 89, (3)
Kamm, Kevin; Pagliarani, Stefano; Pascucci, Andrea
  • Lectures:
    • Financial Mathematics, Spring 2023
    • Stochastic Differential Equations, Autumn 2023
  • Master Thesis Supervision
    • Conrad Jonsson & Jonas Gustafsson: Generate Stress Test Scenarios using Machine Learning