5 citations · 6 across the 12 of their papers we have counts for
15 papers
A sub-asymptotic model for bivariate threshold exceedances
Mirco Lescart, Anna Kiriliouk, Philippe Naveau
Extreme value theory offers a statistical framework for quantifying the risk of rare events, with the generalized Pareto (GP) distribution providing the canonical limit model for u…
A penalized least squares estimator for extreme-value mixture models
Anas Mourahib, Anna Kiriliouk, Johan Segers
Estimating the parameters of max-stable parametric models poses significant challenges, particularly when some parameters lie on the boundary of the parameter space. This situation…
Tail Risk Analysis for Financial Time Series
Anna Kiriliouk, Chen Zhou
This book chapter illustrates how to apply extreme value statistics to financial time series data. Such data often exhibits strong serial dependence, which complicates assessment o…
X-Vine Models for Multivariate Extremes
Anna Kiriliouk, Jeongjin Lee, Johan Segers
Regular vine sequences permit the organisation of variables in a random vector along a sequence of trees. Regular vine models have become greatly popular in dependence modelling as…
Multivariate generalized Pareto distributions along extreme directions
Anas Mourahib, Anna Kiriliouk, Johan Segers
When modeling a vector of risk variables, extreme scenarios are often of special interest. The peaks-over-thresholds method hinges on the notion that, asymptotically, the excesses…
Estimating probabilities of multivariate failure sets based on pairwise tail dependence coefficients
Anna Kiriliouk, Chen Zhou
Estimating probabilities of extreme events involving multiple risk factors is a critical challenge in fields such as finance and climate science. This paper proposes a parametric a…