Given the growing need for managing financial risk and the recent global crisis, risk prediction is a crucial issue in banking and finance. In this paper, we show how recent advances in the statistical analysis of extreme events can provide solid methodological fundamentals for modeling extreme...

The analysis of return series from financial markets is often based on the Peaks-over-threshold (POT) model. This model assumes independent and identically distributed observations and therefore a Poisson process is used to characterize the occurrence of extreme events. However, stylized facts...

Crude oil is a dynamically traded commodity that affects many economies. We propose a collection of marked self-exciting point processes with dependent arrival rates for extreme events in oil markets and related risk measures. The models treat the time among extreme events in oil markets as a...