Non-Gaussian process

Understanding Extremal Dependence in Lévy Driven Processes

1 min read · Sun, Sep 14 2025

Exponential tail Extremal dependence Moving average process Non-Gaussian process

A new study by researchers Zhongwei Zhang, David Bolin, Sebastian Engelke, and Raphaël Huser tackles the open problem of characterizing extreme event dependence in certain non-Gaussian stochastic processes. The work focuses on continuous-time moving average processes driven by exponential-tailed Lévy noise, models that extend classical Gaussian processes to capture heavy deviations and jump discontinuities. Until now, it was unclear how extremes in these models behave jointly across different spatial locations or time points, depending on the domain in which the process is defined. The