We extend the study of an established parametric latent model for extreme values which captures serial dependence in the exceedances above a threshold using so-called trawl processes - a family of stationary and infinitely divisible random processes. We prove that the observed process is...

We apply wavelet analysis to observe financial returns. We demonstrate how useful wavelets can be to separate normal market conditions from stressed market conditions. After noise removal, a process appears to manifest itself during period of financial distress and show a remarkable alignment...

Algorithms used to detect outliers in regression models have a positive probability of finding outliers even when the data generation process has no outliers. We propose two sets of tests for the overall presence of outliers based on the false-discovery rate of outliers. First, `simple' tests on...

This paper considers some univariate and multivariate operational risk models, in which the loss severities are modelled by some weakly tail dependent and heavy-tailed positive random variables, and the loss frequency processes are some general counting processes. In such models, we derive some...

Consumers often make decisions based on the extremeness of choice alternatives. Prior research has argued that extremeness aversion is a function of the relational properties of choice alternatives and that the middle option, defined such that its attribute values are between the values of the...