Stochastic processes provide a rigorous framework for modelling systems that evolve over time under uncertainty, while extremal theory offers the tools for understanding the behaviour of rare, ...

Stochastic processes and duality relations constitute a fundamental framework in the study of interacting particle systems, offering a powerful methodology to disentangle complex dynamics. At its core ...

The paper investigates stochastic processes directed by a randomized time process. A new family of directing processes called Hougaard processes is introduced. Monotonicity properties preserved under ...

A cylindrical Lévy process does not enjoy a cylindrical version of the semimartingale decomposition which results in the need to develop a completely novel approach to stochastic integration. In this ...

This course provides doctoral students the foundations of applied probability and stochastic modeling. The first part of the course covers basic concepts in probability, such as the Borel Cantelli ...

Simulation research derives new methods for the design, analysis, and optimization of simulation experiments. Research on stochastic models develops and analyzes models of systems with random behavior ...

As global financial markets become increasingly interconnected, accurately modelling correlations between assets is essential. Traditional models often assume static correlations, which fail to ...